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Nonstandard Analysis as a computational foundation Sam Sanders SOTFOMIII, Vienna, Sept. 2015
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Page 1: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Nonstandard Analysis as a computationalfoundation

Sam Sanders

SOTFOMIII, Vienna, Sept. 2015

Page 2: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Computational Foundation?

Univalent foundations of mathematics is

Vladimir Voevodsky’s new program for a comprehensive,computational foundation for mathematics based on thehomotopical interpretation of type theory (aka HOTT).

Subliminal message: ZFC, the ‘old’ foundation of mathematics isnot ‘computational’, and therefore HOTT is better.

In this talk, we show that Nonstandard Analysis provides ZFC witha ‘computational’ foundation.

Page 3: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Computational Foundation?

Univalent foundations of mathematics is

Vladimir Voevodsky’s new program for a comprehensive,computational foundation for mathematics based on thehomotopical interpretation of type theory (aka HOTT).

Subliminal message: ZFC, the ‘old’ foundation of mathematics isnot ‘computational’, and therefore HOTT is better.

In this talk, we show that Nonstandard Analysis provides ZFC witha ‘computational’ foundation.

Page 4: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Computational Foundation?

Univalent foundations of mathematics is

Vladimir Voevodsky’s new program for a comprehensive,computational foundation for mathematics based on thehomotopical interpretation of type theory (aka HOTT).

Subliminal message: ZFC, the ‘old’ foundation of mathematics isnot ‘computational’, and therefore HOTT is better.

In this talk, we show that Nonstandard Analysis provides ZFC witha ‘computational’ foundation.

Page 5: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Computational Foundation?

What is a ‘computational’ foundation?

NOT: a computer implementation of mathematics: Wiedijk claims that

Mizar has the largest library; Mizar is based on classical logic and an

extension of ZFC.

Computational foundation: HOTT is based on Martin-Lof’s intuitionistic

type theory: BHK-interpretation of constructive mathematics.

We show that Nonstandard Analysis provides a similarly constructiveinterpretation of mathematics. (Bishop and Connes)

Page 6: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Computational Foundation?

What is a ‘computational’ foundation?

NOT: a computer implementation of mathematics:

Wiedijk claims that

Mizar has the largest library; Mizar is based on classical logic and an

extension of ZFC.

Computational foundation: HOTT is based on Martin-Lof’s intuitionistic

type theory: BHK-interpretation of constructive mathematics.

We show that Nonstandard Analysis provides a similarly constructiveinterpretation of mathematics. (Bishop and Connes)

Page 7: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Computational Foundation?

What is a ‘computational’ foundation?

NOT: a computer implementation of mathematics: Wiedijk claims that

Mizar has the largest library; Mizar is based on classical logic and an

extension of ZFC.

Computational foundation: HOTT is based on Martin-Lof’s intuitionistic

type theory: BHK-interpretation of constructive mathematics.

We show that Nonstandard Analysis provides a similarly constructiveinterpretation of mathematics. (Bishop and Connes)

Page 8: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Computational Foundation?

What is a ‘computational’ foundation?

NOT: a computer implementation of mathematics: Wiedijk claims that

Mizar has the largest library; Mizar is based on classical logic and an

extension of ZFC.

Computational foundation: HOTT is based on Martin-Lof’s intuitionistic

type theory:

BHK-interpretation of constructive mathematics.

We show that Nonstandard Analysis provides a similarly constructiveinterpretation of mathematics. (Bishop and Connes)

Page 9: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Computational Foundation?

What is a ‘computational’ foundation?

NOT: a computer implementation of mathematics: Wiedijk claims that

Mizar has the largest library; Mizar is based on classical logic and an

extension of ZFC.

Computational foundation: HOTT is based on Martin-Lof’s intuitionistic

type theory: BHK-interpretation of constructive mathematics.

We show that Nonstandard Analysis provides a similarly constructiveinterpretation of mathematics. (Bishop and Connes)

Page 10: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Computational Foundation?

What is a ‘computational’ foundation?

NOT: a computer implementation of mathematics: Wiedijk claims that

Mizar has the largest library; Mizar is based on classical logic and an

extension of ZFC.

Computational foundation: HOTT is based on Martin-Lof’s intuitionistic

type theory: BHK-interpretation of constructive mathematics.

We show that Nonstandard Analysis provides a similarly constructiveinterpretation of mathematics. (Bishop and Connes)

Page 11: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

A little test. . .

Which statement has the most constructive/numerical content?

(∀x , y ∈ [0, 1])[x ≈ y → f (x) ≈ f (y)]

↓(∀π, π′ ∈ P([0, 1]))(‖π‖, ‖π′‖ ≈ 0→ Sπ(f ) ≈ Sπ′(f ))

],

OR

(∀k0)(∀x , y ∈ [0, 1])(|x − y | < 1g(k) → |f (x)− f (y)| < 1

k )

↓(∀k ′)(∀π, π′ ∈ P([0, 1]))

(‖π‖, ‖π′‖ < 1

s(g ,k ′) → |Sπ(f )− Sπ′(f )| ≤ 1k ′

)As we will see: the first one! (up to finitistic manipulation)

Page 12: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

A little test. . .

Which statement has the most constructive/numerical content?

(∀x , y ∈ [0, 1])[x ≈ y → f (x) ≈ f (y)]

↓(∀π, π′ ∈ P([0, 1]))(‖π‖, ‖π′‖ ≈ 0→ Sπ(f ) ≈ Sπ′(f ))

],

OR

(∀k0)(∀x , y ∈ [0, 1])(|x − y | < 1g(k) → |f (x)− f (y)| < 1

k )

↓(∀k ′)(∀π, π′ ∈ P([0, 1]))

(‖π‖, ‖π′‖ < 1

s(g ,k ′) → |Sπ(f )− Sπ′(f )| ≤ 1k ′

)As we will see: the first one! (up to finitistic manipulation)

Page 13: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

A little test. . .

Which statement has the most constructive/numerical content?

(∀x , y ∈ [0, 1])[x ≈ y → f (x) ≈ f (y)]

↓(∀π, π′ ∈ P([0, 1]))(‖π‖, ‖π′‖ ≈ 0→ Sπ(f ) ≈ Sπ′(f ))

],

OR

(∀k0)(∀x , y ∈ [0, 1])(|x − y | < 1g(k) → |f (x)− f (y)| < 1

k )

↓(∀k ′)(∀π, π′ ∈ P([0, 1]))

(‖π‖, ‖π′‖ < 1

s(g ,k ′) → |Sπ(f )− Sπ′(f )| ≤ 1k ′

)

As we will see: the first one! (up to finitistic manipulation)

Page 14: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

A little test. . .

Which statement has the most constructive/numerical content?

(∀x , y ∈ [0, 1])[x ≈ y → f (x) ≈ f (y)]

↓(∀π, π′ ∈ P([0, 1]))(‖π‖, ‖π′‖ ≈ 0→ Sπ(f ) ≈ Sπ′(f ))

],

OR

(∀k0)(∀x , y ∈ [0, 1])(|x − y | < 1g(k) → |f (x)− f (y)| < 1

k )

↓(∀k ′)(∀π, π′ ∈ P([0, 1]))

(‖π‖, ‖π′‖ < 1

s(g ,k ′) → |Sπ(f )− Sπ′(f )| ≤ 1k ′

)As we will see: the first one! (up to finitistic manipulation)

Page 15: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Means to an end

Technical aim: To show that proofs of theorems of PURENonstandard Analysis can be mined to produce effective theoremsnot involving NSA, and vice versa.

PURE Nonstandard Analysis = only involving the nonstandarddefinitions (of continuity, compactness, diff., Riemann int., . . . )

Effective theorem = Theorem from constructive/computableanalysis OR an (explicit) equivalence from Reverse Math.

Vice versa? Certain effective theorems, called Herbrandisations,imply the nonstandard theorem from which they were obtained!

Motivation: Many authors have observed the ‘constructive nature’of the practice of NSA. (Horst Osswald’s local constructivity)

Page 16: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Means to an end

Technical aim: To show that proofs of theorems of PURENonstandard Analysis can be mined to produce effective theoremsnot involving NSA, and vice versa.

PURE Nonstandard Analysis = only involving the nonstandarddefinitions (of continuity, compactness, diff., Riemann int., . . . )

Effective theorem = Theorem from constructive/computableanalysis OR an (explicit) equivalence from Reverse Math.

Vice versa? Certain effective theorems, called Herbrandisations,imply the nonstandard theorem from which they were obtained!

Motivation: Many authors have observed the ‘constructive nature’of the practice of NSA. (Horst Osswald’s local constructivity)

Page 17: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Means to an end

Technical aim: To show that proofs of theorems of PURENonstandard Analysis can be mined to produce effective theoremsnot involving NSA, and vice versa.

PURE Nonstandard Analysis = only involving the nonstandarddefinitions (of continuity, compactness, diff., Riemann int., . . . )

Effective theorem = Theorem from constructive/computableanalysis OR an (explicit) equivalence from Reverse Math.

Vice versa? Certain effective theorems, called Herbrandisations,imply the nonstandard theorem from which they were obtained!

Motivation: Many authors have observed the ‘constructive nature’of the practice of NSA. (Horst Osswald’s local constructivity)

Page 18: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Means to an end

Technical aim: To show that proofs of theorems of PURENonstandard Analysis can be mined to produce effective theoremsnot involving NSA, and vice versa.

PURE Nonstandard Analysis = only involving the nonstandarddefinitions (of continuity, compactness, diff., Riemann int., . . . )

Effective theorem = Theorem from constructive/computableanalysis OR an (explicit) equivalence from Reverse Math.

Vice versa? Certain effective theorems, called Herbrandisations,imply the nonstandard theorem from which they were obtained!

Motivation: Many authors have observed the ‘constructive nature’of the practice of NSA. (Horst Osswald’s local constructivity)

Page 19: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Means to an end

Technical aim: To show that proofs of theorems of PURENonstandard Analysis can be mined to produce effective theoremsnot involving NSA, and vice versa.

PURE Nonstandard Analysis = only involving the nonstandarddefinitions (of continuity, compactness, diff., Riemann int., . . . )

Effective theorem = Theorem from constructive/computableanalysis OR an (explicit) equivalence from Reverse Math.

Vice versa? Certain effective theorems, called Herbrandisations,imply the nonstandard theorem from which they were obtained!

Motivation: Many authors have observed the ‘constructive nature’of the practice of NSA. (Horst Osswald’s local constructivity)

Page 20: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Introducing Nonstandard Analysis

Robinson’s semantic approach (1965):

For a given structure M, build∗M ) M, a nonstandard model of M (using free ultrafilter).

M

∗M

N = 0, 1, 2, . . .

∗N = 0, 1, 2, . . . . . . , ω, ω + 1, ω + 2, ω + 3, . . .︸ ︷︷ ︸nonstandard objects not in N

-X ∈ M ∗X ∈ ∗Mstar morphism

X contains the standard objects∗X \ X contains the nonstandard objects

Page 21: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Introducing Nonstandard Analysis

Robinson’s semantic approach (1965): For a given structure M, build∗M ) M, a nonstandard model of M (using free ultrafilter).

M

∗M

N = 0, 1, 2, . . .

∗N = 0, 1, 2, . . . . . . , ω, ω + 1, ω + 2, ω + 3, . . .︸ ︷︷ ︸nonstandard objects not in N

-X ∈ M ∗X ∈ ∗Mstar morphism

X contains the standard objects∗X \ X contains the nonstandard objects

Page 22: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Introducing Nonstandard Analysis

Robinson’s semantic approach (1965): For a given structure M, build∗M ) M, a nonstandard model of M (using free ultrafilter).

M

∗M

N = 0, 1, 2, . . .

∗N = 0, 1, 2, . . . . . . , ω, ω + 1, ω + 2, ω + 3, . . .︸ ︷︷ ︸nonstandard objects not in N

-X ∈ M ∗X ∈ ∗Mstar morphism

X contains the standard objects∗X \ X contains the nonstandard objects

Page 23: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Introducing Nonstandard Analysis

Robinson’s semantic approach (1965): For a given structure M, build∗M ) M, a nonstandard model of M (using free ultrafilter).

M

∗M

N = 0, 1, 2, . . .

∗N = 0, 1, 2, . . . . . . , ω, ω + 1, ω + 2, ω + 3, . . .︸ ︷︷ ︸nonstandard objects not in N

-X ∈ M ∗X ∈ ∗Mstar morphism

X contains the standard objects∗X \ X contains the nonstandard objects

Page 24: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Introducing Nonstandard Analysis

Robinson’s semantic approach (1965): For a given structure M, build∗M ) M, a nonstandard model of M (using free ultrafilter).

M

∗M

N = 0, 1, 2, . . .

∗N = 0, 1, 2, . . . . . . , ω, ω + 1, . . .

∗N = 0, 1, 2, . . . . . . , ω, ω + 1, ω + 2, ω + 3, . . .︸ ︷︷ ︸nonstandard objects not in N

-X ∈ M ∗X ∈ ∗Mstar morphism

X contains the standard objects∗X \ X contains the nonstandard objects

Page 25: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Introducing Nonstandard Analysis

Robinson’s semantic approach (1965): For a given structure M, build∗M ) M, a nonstandard model of M (using free ultrafilter).

M

∗M

N = 0, 1, 2, . . .

∗N = 0, 1, 2, . . . . . . , ω, ω + 1, ω + 2, ω + 3, . . .︸ ︷︷ ︸nonstandard objects not in N

-X ∈ M ∗X ∈ ∗Mstar morphism

X contains the standard objects∗X \ X contains the nonstandard objects

Page 26: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Introducing Nonstandard Analysis

Robinson’s semantic approach (1965): For a given structure M, build∗M ) M, a nonstandard model of M (using free ultrafilter).

M

∗M

N = 0, 1, 2, . . .

∗N = 0, 1, 2, . . . . . . , ω, ω + 1, ω + 2, ω + 3, . . .︸ ︷︷ ︸nonstandard objects not in N

-X ∈ M ∗X ∈ ∗M

star morphismX contains the standard objects∗X \ X contains the nonstandard objects

Page 27: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Introducing Nonstandard Analysis

Robinson’s semantic approach (1965): For a given structure M, build∗M ) M, a nonstandard model of M (using free ultrafilter).

M

∗M

N = 0, 1, 2, . . .

∗N = 0, 1, 2, . . . . . . , ω, ω + 1, ω + 2, ω + 3, . . .︸ ︷︷ ︸nonstandard objects not in N

-X ∈ M ∗X ∈ ∗Mstar morphism

X contains the standard objects∗X \ X contains the nonstandard objects

Page 28: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Introducing Nonstandard Analysis

Robinson’s semantic approach (1965): For a given structure M, build∗M ) M, a nonstandard model of M (using free ultrafilter).

M

∗M

N = 0, 1, 2, . . .

∗N = 0, 1, 2, . . . . . . , ω, ω + 1, ω + 2, ω + 3, . . .︸ ︷︷ ︸nonstandard objects not in N

-X ∈ M ∗X ∈ ∗Mstar morphism

X contains the standard objects

∗X \ X contains the nonstandard objects

Page 29: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Introducing Nonstandard Analysis

Robinson’s semantic approach (1965): For a given structure M, build∗M ) M, a nonstandard model of M (using free ultrafilter).

M

∗M

N = 0, 1, 2, . . .

∗N = 0, 1, 2, . . . . . . , ω, ω + 1, ω + 2, ω + 3, . . .︸ ︷︷ ︸nonstandard objects not in N

-X ∈ M ∗X ∈ ∗Mstar morphism

X contains the standard objects∗X \ X contains the nonstandard objects

Page 30: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Introducing Nonstandard Analysis

Robinson’s semantic approach (1965): For a given structure M, build∗M ) M, a nonstandard model of M (using free ultrafilter).

M

∗M

N = 0, 1, 2, . . .

∗N = 0, 1, 2, . . . . . . , ω, ω + 1, ω + 2, ω + 3, . . .︸ ︷︷ ︸nonstandard objects not in N

-X ∈ M ∗X ∈ ∗Mstar morphism

X contains the standard objects∗X \ X contains the nonstandard objects

Three important properties connecting M and ∗M:

Page 31: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Introducing Nonstandard Analysis

Robinson’s semantic approach (1965): For a given structure M, build∗M ) M, a nonstandard model of M (using free ultrafilter).

M

∗M

N = 0, 1, 2, . . .

∗N = 0, 1, 2, . . . . . . , ω, ω + 1, ω + 2, ω + 3, . . .︸ ︷︷ ︸nonstandard objects not in N

-X ∈ M ∗X ∈ ∗Mstar morphism

X contains the standard objects∗X \ X contains the nonstandard objects

Three important properties connecting M and ∗M:1) Transfer M ϕ↔ ∗M ∗ϕ (ϕ ∈ LZFC )

Page 32: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Introducing Nonstandard Analysis

Robinson’s semantic approach (1965): For a given structure M, build∗M ) M, a nonstandard model of M (using free ultrafilter).

M

∗M

N = 0, 1, 2, . . .

∗N = 0, 1, 2, . . . . . . , ω, ω + 1, ω + 2, ω + 3, . . .︸ ︷︷ ︸nonstandard objects not in N

-X ∈ M ∗X ∈ ∗Mstar morphism

X contains the standard objects∗X \ X contains the nonstandard objects

Three important properties connecting M and ∗M:1) Transfer M ϕ↔ ∗M ∗ϕ (ϕ ∈ LZFC )2) Standard Part (∀x ∈ ∗M)(∃y ∈ M)(∀z ∈ M)(z ∈ x ↔ z ∈ y)

(reverse of ∗)

Page 33: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Introducing Nonstandard Analysis

Robinson’s semantic approach (1965): For a given structure M, build∗M ) M, a nonstandard model of M (using free ultrafilter).

M

∗M

N = 0, 1, 2, . . .

∗N = 0, 1, 2, . . . . . . , ω, ω + 1, ω + 2, ω + 3, . . .︸ ︷︷ ︸nonstandard objects not in N

-X ∈ M ∗X ∈ ∗Mstar morphism

X contains the standard objects∗X \ X contains the nonstandard objects

Three important properties connecting M and ∗M:1) Transfer M ϕ↔ ∗M ∗ϕ (ϕ ∈ LZFC )2) Standard Part (∀x ∈ ∗M)(∃y ∈ M)(∀z ∈ M)(z ∈ x ↔ z ∈ y)(reverse of ∗)

Page 34: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Introducing Nonstandard Analysis

Robinson’s semantic approach (1965): For a given structure M, build∗M ) M, a nonstandard model of M (using free ultrafilter).

M

∗M

N = 0, 1, 2, . . .

∗N = 0, 1, 2, . . . . . . , ω, ω + 1, ω + 2, ω + 3, . . .︸ ︷︷ ︸nonstandard objects not in N

-X ∈ M ∗X ∈ ∗Mstar morphism

X contains the standard objects∗X \ X contains the nonstandard objects

Three important properties connecting M and ∗M:1) Transfer M ϕ↔ ∗M ∗ϕ (ϕ ∈ LZFC )2) Standard Part (∀x ∈ ∗M)(∃y ∈ M)(∀z ∈ M)(z ∈ x ↔ z ∈ y)(reverse of ∗)

3) Idealization/Saturation . . .

Page 35: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Introducing Nonstandard Analysis

Nelson’s Internal Set Theory is a syntactic approach toNonstandard Analysis.

Add a new predicate st(x) read ‘x is standard’ to LZFC . We write (∃stx)

and (∀sty) for (∃x)(st(x) ∧ . . . ) and (∀y)(st(y)→ . . . ). A formula is

internal if it does not contain ‘st’; external otherwise

Internal Set Theory IST is ZFC plus the new axioms:

Transfer: (∀stx)ϕ(x , t)→ (∀x)ϕ(x , t) for internal ϕ and standard t.

Standard Part: (∀x)(∃sty)(∀stz)(z ∈ x ↔ z ∈ y).

Idealization:. . . (push quantifiers (∀stx) and (∃sty) to the front)

Conservation: ZFC and IST prove the same internal sentences.

And analogous results for fragments of IST.

Page 36: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Introducing Nonstandard Analysis

Nelson’s Internal Set Theory is a syntactic approach toNonstandard Analysis.

Add a new predicate st(x) read ‘x is standard’ to LZFC .

We write (∃stx)

and (∀sty) for (∃x)(st(x) ∧ . . . ) and (∀y)(st(y)→ . . . ). A formula is

internal if it does not contain ‘st’; external otherwise

Internal Set Theory IST is ZFC plus the new axioms:

Transfer: (∀stx)ϕ(x , t)→ (∀x)ϕ(x , t) for internal ϕ and standard t.

Standard Part: (∀x)(∃sty)(∀stz)(z ∈ x ↔ z ∈ y).

Idealization:. . . (push quantifiers (∀stx) and (∃sty) to the front)

Conservation: ZFC and IST prove the same internal sentences.

And analogous results for fragments of IST.

Page 37: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Introducing Nonstandard Analysis

Nelson’s Internal Set Theory is a syntactic approach toNonstandard Analysis.

Add a new predicate st(x) read ‘x is standard’ to LZFC . We write (∃stx)

and (∀sty) for (∃x)(st(x) ∧ . . . ) and (∀y)(st(y)→ . . . ).

A formula is

internal if it does not contain ‘st’; external otherwise

Internal Set Theory IST is ZFC plus the new axioms:

Transfer: (∀stx)ϕ(x , t)→ (∀x)ϕ(x , t) for internal ϕ and standard t.

Standard Part: (∀x)(∃sty)(∀stz)(z ∈ x ↔ z ∈ y).

Idealization:. . . (push quantifiers (∀stx) and (∃sty) to the front)

Conservation: ZFC and IST prove the same internal sentences.

And analogous results for fragments of IST.

Page 38: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Introducing Nonstandard Analysis

Nelson’s Internal Set Theory is a syntactic approach toNonstandard Analysis.

Add a new predicate st(x) read ‘x is standard’ to LZFC . We write (∃stx)

and (∀sty) for (∃x)(st(x) ∧ . . . ) and (∀y)(st(y)→ . . . ). A formula is

internal if it does not contain ‘st’; external otherwise

Internal Set Theory IST is ZFC plus the new axioms:

Transfer: (∀stx)ϕ(x , t)→ (∀x)ϕ(x , t) for internal ϕ and standard t.

Standard Part: (∀x)(∃sty)(∀stz)(z ∈ x ↔ z ∈ y).

Idealization:. . . (push quantifiers (∀stx) and (∃sty) to the front)

Conservation: ZFC and IST prove the same internal sentences.

And analogous results for fragments of IST.

Page 39: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Introducing Nonstandard Analysis

Nelson’s Internal Set Theory is a syntactic approach toNonstandard Analysis.

Add a new predicate st(x) read ‘x is standard’ to LZFC . We write (∃stx)

and (∀sty) for (∃x)(st(x) ∧ . . . ) and (∀y)(st(y)→ . . . ). A formula is

internal if it does not contain ‘st’; external otherwise

Internal Set Theory IST is ZFC plus the new axioms:

Transfer: (∀stx)ϕ(x , t)→ (∀x)ϕ(x , t) for internal ϕ and standard t.

Standard Part: (∀x)(∃sty)(∀stz)(z ∈ x ↔ z ∈ y).

Idealization:. . . (push quantifiers (∀stx) and (∃sty) to the front)

Conservation: ZFC and IST prove the same internal sentences.

And analogous results for fragments of IST.

Page 40: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Introducing Nonstandard Analysis

Nelson’s Internal Set Theory is a syntactic approach toNonstandard Analysis.

Add a new predicate st(x) read ‘x is standard’ to LZFC . We write (∃stx)

and (∀sty) for (∃x)(st(x) ∧ . . . ) and (∀y)(st(y)→ . . . ). A formula is

internal if it does not contain ‘st’; external otherwise

Internal Set Theory IST is ZFC plus the new axioms:

Transfer: (∀stx)ϕ(x , t)→ (∀x)ϕ(x , t) for internal ϕ and standard t.

Standard Part: (∀x)(∃sty)(∀stz)(z ∈ x ↔ z ∈ y).

Idealization:. . . (push quantifiers (∀stx) and (∃sty) to the front)

Conservation: ZFC and IST prove the same internal sentences.

And analogous results for fragments of IST.

Page 41: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Introducing Nonstandard Analysis

Nelson’s Internal Set Theory is a syntactic approach toNonstandard Analysis.

Add a new predicate st(x) read ‘x is standard’ to LZFC . We write (∃stx)

and (∀sty) for (∃x)(st(x) ∧ . . . ) and (∀y)(st(y)→ . . . ). A formula is

internal if it does not contain ‘st’; external otherwise

Internal Set Theory IST is ZFC plus the new axioms:

Transfer: (∀stx)ϕ(x , t)→ (∀x)ϕ(x , t) for internal ϕ and standard t.

Standard Part: (∀x)(∃sty)(∀stz)(z ∈ x ↔ z ∈ y).

Idealization:. . . (push quantifiers (∀stx) and (∃sty) to the front)

Conservation: ZFC and IST prove the same internal sentences.

And analogous results for fragments of IST.

Page 42: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Introducing Nonstandard Analysis

Nelson’s Internal Set Theory is a syntactic approach toNonstandard Analysis.

Add a new predicate st(x) read ‘x is standard’ to LZFC . We write (∃stx)

and (∀sty) for (∃x)(st(x) ∧ . . . ) and (∀y)(st(y)→ . . . ). A formula is

internal if it does not contain ‘st’; external otherwise

Internal Set Theory IST is ZFC plus the new axioms:

Transfer: (∀stx)ϕ(x , t)→ (∀x)ϕ(x , t) for internal ϕ and standard t.

Standard Part: (∀x)(∃sty)(∀stz)(z ∈ x ↔ z ∈ y).

Idealization:. . . (push quantifiers (∀stx) and (∃sty) to the front)

Conservation: ZFC and IST prove the same internal sentences.

And analogous results for fragments of IST.

Page 43: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Introducing Nonstandard Analysis

Nelson’s Internal Set Theory is a syntactic approach toNonstandard Analysis.

Add a new predicate st(x) read ‘x is standard’ to LZFC . We write (∃stx)

and (∀sty) for (∃x)(st(x) ∧ . . . ) and (∀y)(st(y)→ . . . ). A formula is

internal if it does not contain ‘st’; external otherwise

Internal Set Theory IST is ZFC plus the new axioms:

Transfer: (∀stx)ϕ(x , t)→ (∀x)ϕ(x , t) for internal ϕ and standard t.

Standard Part: (∀x)(∃sty)(∀stz)(z ∈ x ↔ z ∈ y).

Idealization:. . . (push quantifiers (∀stx) and (∃sty) to the front)

Conservation: ZFC and IST prove the same internal sentences.

And analogous results for fragments of IST.

Page 44: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Introducing Nonstandard Analysis

Nelson’s Internal Set Theory is a syntactic approach toNonstandard Analysis.

Add a new predicate st(x) read ‘x is standard’ to LZFC . We write (∃stx)

and (∀sty) for (∃x)(st(x) ∧ . . . ) and (∀y)(st(y)→ . . . ). A formula is

internal if it does not contain ‘st’; external otherwise

Internal Set Theory IST is ZFC plus the new axioms:

Transfer: (∀stx)ϕ(x , t)→ (∀x)ϕ(x , t) for internal ϕ and standard t.

Standard Part: (∀x)(∃sty)(∀stz)(z ∈ x ↔ z ∈ y).

Idealization:. . . (push quantifiers (∀stx) and (∃sty) to the front)

Conservation: ZFC and IST prove the same internal sentences.

And analogous results for fragments of IST.

Page 45: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

A fragment based on Godel’s T

van den Berg, Briseid, Safarik, A functional interpretation ofnonstandard arithmetic, APAL2012

E-PAω is Peano arithmetic in all finite types with the axiom ofextensionality.

I is Nelson’s idealisation axiom in the language of finite types.

HACint is a weak version of Nelson’s Standard Part axiom:

(∀stxρ)(∃sty τ )ϕ(x , y)→ (∃stf ρ→τ∗)(∀stxρ)(∃y τ ∈ f (x))ϕ(x , y)

Only a finite sequence of witnesses; ϕ is internal.

No Transfer

P := E-PAω + I + HACint is a conservative extension of E-PAω.

Same for nonstandard version H of E-HAω and intuitionistic logic.

Page 46: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

A fragment based on Godel’s T

van den Berg, Briseid, Safarik, A functional interpretation ofnonstandard arithmetic, APAL2012

E-PAω is Peano arithmetic in all finite types with the axiom ofextensionality.

I is Nelson’s idealisation axiom in the language of finite types.

HACint is a weak version of Nelson’s Standard Part axiom:

(∀stxρ)(∃sty τ )ϕ(x , y)→ (∃stf ρ→τ∗)(∀stxρ)(∃y τ ∈ f (x))ϕ(x , y)

Only a finite sequence of witnesses; ϕ is internal.

No Transfer

P := E-PAω + I + HACint is a conservative extension of E-PAω.

Same for nonstandard version H of E-HAω and intuitionistic logic.

Page 47: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

A fragment based on Godel’s T

van den Berg, Briseid, Safarik, A functional interpretation ofnonstandard arithmetic, APAL2012

E-PAω is Peano arithmetic in all finite types with the axiom ofextensionality.

I is Nelson’s idealisation axiom in the language of finite types.

HACint is a weak version of Nelson’s Standard Part axiom:

(∀stxρ)(∃sty τ )ϕ(x , y)→ (∃stf ρ→τ∗)(∀stxρ)(∃y τ ∈ f (x))ϕ(x , y)

Only a finite sequence of witnesses; ϕ is internal.

No Transfer

P := E-PAω + I + HACint is a conservative extension of E-PAω.

Same for nonstandard version H of E-HAω and intuitionistic logic.

Page 48: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

A fragment based on Godel’s T

van den Berg, Briseid, Safarik, A functional interpretation ofnonstandard arithmetic, APAL2012

E-PAω is Peano arithmetic in all finite types with the axiom ofextensionality.

I is Nelson’s idealisation axiom in the language of finite types.

HACint is a weak version of Nelson’s Standard Part axiom:

(∀stxρ)(∃sty τ )ϕ(x , y)→ (∃stf ρ→τ∗)(∀stxρ)(∃y τ ∈ f (x))ϕ(x , y)

Only a finite sequence of witnesses; ϕ is internal.

No Transfer

P := E-PAω + I + HACint is a conservative extension of E-PAω.

Same for nonstandard version H of E-HAω and intuitionistic logic.

Page 49: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

A fragment based on Godel’s T

van den Berg, Briseid, Safarik, A functional interpretation ofnonstandard arithmetic, APAL2012

E-PAω is Peano arithmetic in all finite types with the axiom ofextensionality.

I is Nelson’s idealisation axiom in the language of finite types.

HACint is a weak version of Nelson’s Standard Part axiom:

(∀stxρ)(∃sty τ )ϕ(x , y)→ (∃stf ρ→τ∗)(∀stxρ)(∃y τ ∈ f (x))ϕ(x , y)

Only a finite sequence of witnesses; ϕ is internal.

No Transfer

P := E-PAω + I + HACint is a conservative extension of E-PAω.

Same for nonstandard version H of E-HAω and intuitionistic logic.

Page 50: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

A fragment based on Godel’s T

van den Berg, Briseid, Safarik, A functional interpretation ofnonstandard arithmetic, APAL2012

E-PAω is Peano arithmetic in all finite types with the axiom ofextensionality.

I is Nelson’s idealisation axiom in the language of finite types.

HACint is a weak version of Nelson’s Standard Part axiom:

(∀stxρ)(∃sty τ )ϕ(x , y)→ (∃stf ρ→τ∗)(∀stxρ)(∃y τ ∈ f (x))ϕ(x , y)

Only a finite sequence of witnesses; ϕ is internal.

No Transfer

P := E-PAω + I + HACint is a conservative extension of E-PAω.

Same for nonstandard version H of E-HAω and intuitionistic logic.

Page 51: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

A fragment based on Godel’s T

van den Berg, Briseid, Safarik, A functional interpretation ofnonstandard arithmetic, APAL2012

E-PAω is Peano arithmetic in all finite types with the axiom ofextensionality.

I is Nelson’s idealisation axiom in the language of finite types.

HACint is a weak version of Nelson’s Standard Part axiom:

(∀stxρ)(∃sty τ )ϕ(x , y)→ (∃stf ρ→τ∗)(∀stxρ)(∃y τ ∈ f (x))ϕ(x , y)

Only a finite sequence of witnesses; ϕ is internal.

No Transfer

P := E-PAω + I + HACint is a conservative extension of E-PAω.

Same for nonstandard version H of E-HAω and intuitionistic logic.

Page 52: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

A fragment based on Godel’s T

van den Berg, Briseid, Safarik, A functional interpretation ofnonstandard arithmetic, APAL2012

E-PAω is Peano arithmetic in all finite types with the axiom ofextensionality.

I is Nelson’s idealisation axiom in the language of finite types.

HACint is a weak version of Nelson’s Standard Part axiom:

(∀stxρ)(∃sty τ )ϕ(x , y)→ (∃stf ρ→τ∗)(∀stxρ)(∃y τ ∈ f (x))ϕ(x , y)

Only a finite sequence of witnesses; ϕ is internal.

No Transfer

P := E-PAω + I + HACint is a conservative extension of E-PAω.

Same for nonstandard version H of E-HAω and intuitionistic logic.

Page 53: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

A new computational aspect of NSA

TERM EXTRACTION

van den Berg, Briseid, Safarik, A functional interpretation ofnonstandard arithmetic, APAL2012

If system P (resp. H) proves (∀stx)(∃sty)ϕ(x , y) (ϕ internal)

then a term t can be extracted from this proof such that E-PAω

(resp. E-HAω) proves (∀x)(∃y ∈ t(x))ϕ(x , y).

(Compare to Godel-Gentzen and H. Friedman translation for Π02-formulas)

OBSERVATION: Nonstandard definitions (of continuity,compactness, Riemann int., etc) can be brought into the ‘normalform’ (∀stx)(∃sty)ϕ(x , y). Such normal forms are closed undermodes ponens (in both P and H)

All theorems of PURE Nonstandard Analysis can be mined usingthe term extraction result (of P and H).

Page 54: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

A new computational aspect of NSA

TERM EXTRACTION

van den Berg, Briseid, Safarik, A functional interpretation ofnonstandard arithmetic, APAL2012

If system P (resp. H) proves (∀stx)(∃sty)ϕ(x , y) (ϕ internal)

then a term t can be extracted from this proof such that E-PAω

(resp. E-HAω) proves (∀x)(∃y ∈ t(x))ϕ(x , y).

(Compare to Godel-Gentzen and H. Friedman translation for Π02-formulas)

OBSERVATION: Nonstandard definitions (of continuity,compactness, Riemann int., etc) can be brought into the ‘normalform’ (∀stx)(∃sty)ϕ(x , y). Such normal forms are closed undermodes ponens (in both P and H)

All theorems of PURE Nonstandard Analysis can be mined usingthe term extraction result (of P and H).

Page 55: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

A new computational aspect of NSA

TERM EXTRACTION

van den Berg, Briseid, Safarik, A functional interpretation ofnonstandard arithmetic, APAL2012

If system P (resp. H) proves (∀stx)(∃sty)ϕ(x , y) (ϕ internal)

then a term t can be extracted from this proof such that E-PAω

(resp. E-HAω) proves (∀x)(∃y ∈ t(x))ϕ(x , y).

(Compare to Godel-Gentzen and H. Friedman translation for Π02-formulas)

OBSERVATION: Nonstandard definitions (of continuity,compactness, Riemann int., etc) can be brought into the ‘normalform’ (∀stx)(∃sty)ϕ(x , y). Such normal forms are closed undermodes ponens (in both P and H)

All theorems of PURE Nonstandard Analysis can be mined usingthe term extraction result (of P and H).

Page 56: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

A new computational aspect of NSA

TERM EXTRACTION

van den Berg, Briseid, Safarik, A functional interpretation ofnonstandard arithmetic, APAL2012

If system P (resp. H) proves (∀stx)(∃sty)ϕ(x , y) (ϕ internal)

then a term t can be extracted from this proof such that E-PAω

(resp. E-HAω) proves (∀x)(∃y ∈ t(x))ϕ(x , y).

(Compare to Godel-Gentzen and H. Friedman translation for Π02-formulas)

OBSERVATION: Nonstandard definitions (of continuity,compactness, Riemann int., etc) can be brought into the ‘normalform’ (∀stx)(∃sty)ϕ(x , y). Such normal forms are closed undermodes ponens (in both P and H)

All theorems of PURE Nonstandard Analysis can be mined usingthe term extraction result (of P and H).

Page 57: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

A new computational aspect of NSA

TERM EXTRACTION

van den Berg, Briseid, Safarik, A functional interpretation ofnonstandard arithmetic, APAL2012

If system P (resp. H) proves (∀stx)(∃sty)ϕ(x , y) (ϕ internal)

then a term t can be extracted from this proof such that E-PAω

(resp. E-HAω) proves (∀x)(∃y ∈ t(x))ϕ(x , y).

(Compare to Godel-Gentzen and H. Friedman translation for Π02-formulas)

OBSERVATION: Nonstandard definitions (of continuity,compactness, Riemann int., etc) can be brought into the ‘normalform’ (∀stx)(∃sty)ϕ(x , y). Such normal forms are closed undermodes ponens (in both P and H)

All theorems of PURE Nonstandard Analysis can be mined usingthe term extraction result (of P and H).

Page 58: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

A new computational aspect of NSA

TERM EXTRACTION

van den Berg, Briseid, Safarik, A functional interpretation ofnonstandard arithmetic, APAL2012

If system P (resp. H) proves (∀stx)(∃sty)ϕ(x , y) (ϕ internal)

then a term t can be extracted from this proof such that E-PAω

(resp. E-HAω) proves (∀x)(∃y ∈ t(x))ϕ(x , y).

(Compare to Godel-Gentzen and H. Friedman translation for Π02-formulas)

OBSERVATION: Nonstandard definitions (of continuity,compactness, Riemann int., etc) can be brought into the ‘normalform’ (∀stx)(∃sty)ϕ(x , y). Such normal forms are closed undermodes ponens (in both P and H)

All theorems of PURE Nonstandard Analysis can be mined usingthe term extraction result (of P and H).

Page 59: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

A new computational aspect of NSA

TERM EXTRACTION

van den Berg, Briseid, Safarik, A functional interpretation ofnonstandard arithmetic, APAL2012

If system P (resp. H) proves (∀stx)(∃sty)ϕ(x , y) (ϕ internal)

then a term t can be extracted from this proof such that E-PAω

(resp. E-HAω) proves (∀x)(∃y ∈ t(x))ϕ(x , y).

(Compare to Godel-Gentzen and H. Friedman translation for Π02-formulas)

OBSERVATION: Nonstandard definitions (of continuity,compactness, Riemann int., etc) can be brought into the ‘normalform’ (∀stx)(∃sty)ϕ(x , y).

Such normal forms are closed undermodes ponens (in both P and H)

All theorems of PURE Nonstandard Analysis can be mined usingthe term extraction result (of P and H).

Page 60: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

A new computational aspect of NSA

TERM EXTRACTION

van den Berg, Briseid, Safarik, A functional interpretation ofnonstandard arithmetic, APAL2012

If system P (resp. H) proves (∀stx)(∃sty)ϕ(x , y) (ϕ internal)

then a term t can be extracted from this proof such that E-PAω

(resp. E-HAω) proves (∀x)(∃y ∈ t(x))ϕ(x , y).

(Compare to Godel-Gentzen and H. Friedman translation for Π02-formulas)

OBSERVATION: Nonstandard definitions (of continuity,compactness, Riemann int., etc) can be brought into the ‘normalform’ (∀stx)(∃sty)ϕ(x , y). Such normal forms are closed undermodes ponens (in both P and H)

All theorems of PURE Nonstandard Analysis can be mined usingthe term extraction result (of P and H).

Page 61: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

A new computational aspect of NSA

TERM EXTRACTION

van den Berg, Briseid, Safarik, A functional interpretation ofnonstandard arithmetic, APAL2012

If system P (resp. H) proves (∀stx)(∃sty)ϕ(x , y) (ϕ internal)

then a term t can be extracted from this proof such that E-PAω

(resp. E-HAω) proves (∀x)(∃y ∈ t(x))ϕ(x , y).

(Compare to Godel-Gentzen and H. Friedman translation for Π02-formulas)

OBSERVATION: Nonstandard definitions (of continuity,compactness, Riemann int., etc) can be brought into the ‘normalform’ (∀stx)(∃sty)ϕ(x , y). Such normal forms are closed undermodes ponens (in both P and H)

All theorems of PURE Nonstandard Analysis can be mined usingthe term extraction result (of P and H).

Page 62: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

The unreasonable effectiveness of NSA

Example I: Continuity.

From a proof that f is nonstandard uniformly continuous in P, i.e.

(∀x , y ∈ [0, 1])(x ≈ y → f (x) ≈ f (y)), (1)

we can extract a term t1 (from Godel’s T) such that E-PAω proves

(∀k0)(∀x , y ∈ [0, 1])(|x − y | < 1t(k) → |f (x)− f (y)| < 1

k ), (2)

AND VICE VERSA: E-PAω ` (2) implies P ` (1).

(2) is the notion of continuity (with a modulus t) used inconstructive analysis and computable math (Bishop, etc).

Et pour les constructivists: la meme chose!

Page 63: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

The unreasonable effectiveness of NSA

Example I: Continuity.

From a proof that f is nonstandard uniformly continuous in P, i.e.

(∀x , y ∈ [0, 1])(x ≈ y → f (x) ≈ f (y)),

(1)

we can extract a term t1 (from Godel’s T) such that E-PAω proves

(∀k0)(∀x , y ∈ [0, 1])(|x − y | < 1t(k) → |f (x)− f (y)| < 1

k ), (2)

AND VICE VERSA: E-PAω ` (2) implies P ` (1).

(2) is the notion of continuity (with a modulus t) used inconstructive analysis and computable math (Bishop, etc).

Et pour les constructivists: la meme chose!

Page 64: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

The unreasonable effectiveness of NSA

Example I: Continuity.

From a proof that f is nonstandard uniformly continuous in P, i.e.

(∀x , y ∈ [0, 1])(x ≈ y → f (x) ≈ f (y)), (1)

we can extract a term t1 (from Godel’s T) such that E-PAω proves

(∀k0)(∀x , y ∈ [0, 1])(|x − y | < 1t(k) → |f (x)− f (y)| < 1

k ), (2)

AND VICE VERSA: E-PAω ` (2) implies P ` (1).

(2) is the notion of continuity (with a modulus t) used inconstructive analysis and computable math (Bishop, etc).

Et pour les constructivists: la meme chose!

Page 65: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

The unreasonable effectiveness of NSA

Example I: Continuity.

From a proof that f is nonstandard uniformly continuous in P, i.e.

(∀x , y ∈ [0, 1])(x ≈ y → f (x) ≈ f (y)), (1)

we can extract a term t1 (from Godel’s T) such that E-PAω proves

(∀k0)(∀x , y ∈ [0, 1])(|x − y | < 1t(k) → |f (x)− f (y)| < 1

k ), (2)

AND VICE VERSA: E-PAω ` (2) implies P ` (1).

(2) is the notion of continuity (with a modulus t) used inconstructive analysis and computable math (Bishop, etc).

Et pour les constructivists: la meme chose!

Page 66: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

The unreasonable effectiveness of NSA

Example I: Continuity.

From a proof that f is nonstandard uniformly continuous in P, i.e.

(∀x , y ∈ [0, 1])(x ≈ y → f (x) ≈ f (y)), (1)

we can extract a term t1 (from Godel’s T) such that E-PAω proves

(∀k0)(∀x , y ∈ [0, 1])(|x − y | < 1t(k) → |f (x)− f (y)| < 1

k ), (2)

AND VICE VERSA: E-PAω ` (2) implies P ` (1).

(2) is the notion of continuity (with a modulus t) used inconstructive analysis and computable math (Bishop, etc).

Et pour les constructivists: la meme chose!

Page 67: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

The unreasonable effectiveness of NSA

Example I: Continuity.

From a proof that f is nonstandard uniformly continuous in P, i.e.

(∀x , y ∈ [0, 1])(x ≈ y → f (x) ≈ f (y)), (1)

we can extract a term t1 (from Godel’s T) such that E-PAω proves

(∀k0)(∀x , y ∈ [0, 1])(|x − y | < 1t(k) → |f (x)− f (y)| < 1

k ), (2)

AND VICE VERSA: E-PAω ` (2) implies P ` (1).

(2) is the notion of continuity (with a modulus t) used inconstructive analysis and computable math (Bishop, etc).

Et pour les constructivists: la meme chose!

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Example II: Continuity implies Riemann integration

From a proof that nonstandard uniformly continuity implies nonstandard

Riemann integration in P, i.e.

(∀f : R→ R)[(∀x , y ∈ [0, 1])[x ≈ y → f (x) ≈ f (y)]

↓(∀π, π′ ∈ P([0, 1]))(‖π‖, ‖π′‖ ≈ 0→ Sπ(f ) ≈ Sπ′(f ))

],

we can extract a term s2 such that for f : R→ R and modulus g1:

(∀k0)(∀x , y ∈ [0, 1])(|x − y | < 1g(k) → |f (x)− f (y)| < 1

k ) (3)

↓(∀k ′)(∀π, π′ ∈ P([0, 1]))

(‖π‖, ‖π′‖ < 1

s(g ,k ′) → |Sπ(f )− Sπ′(f )| ≤ 1k ′

)is provable in E-PAω. (and the same for E-HAω)

But (3) is the theorem expressing continuity implies Riemann integration

from constructive analysis and computable math.

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Example II: Continuity implies Riemann integration

From a proof that nonstandard uniformly continuity implies nonstandard

Riemann integration in P, i.e.

(∀f : R→ R)[(∀x , y ∈ [0, 1])[x ≈ y → f (x) ≈ f (y)]

↓(∀π, π′ ∈ P([0, 1]))(‖π‖, ‖π′‖ ≈ 0→ Sπ(f ) ≈ Sπ′(f ))

],

we can extract a term s2 such that for f : R→ R and modulus g1:

(∀k0)(∀x , y ∈ [0, 1])(|x − y | < 1g(k) → |f (x)− f (y)| < 1

k ) (3)

↓(∀k ′)(∀π, π′ ∈ P([0, 1]))

(‖π‖, ‖π′‖ < 1

s(g ,k ′) → |Sπ(f )− Sπ′(f )| ≤ 1k ′

)is provable in E-PAω. (and the same for E-HAω)

But (3) is the theorem expressing continuity implies Riemann integration

from constructive analysis and computable math.

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Example II: Continuity implies Riemann integration

From a proof that nonstandard uniformly continuity implies nonstandard

Riemann integration in P, i.e.

(∀f : R→ R)[(∀x , y ∈ [0, 1])[x ≈ y → f (x) ≈ f (y)]

↓(∀π, π′ ∈ P([0, 1]))(‖π‖, ‖π′‖ ≈ 0→ Sπ(f ) ≈ Sπ′(f ))

],

we can extract a term s2 such that for f : R→ R and modulus g1:

(∀k0)(∀x , y ∈ [0, 1])(|x − y | < 1g(k) → |f (x)− f (y)| < 1

k ) (3)

↓(∀k ′)(∀π, π′ ∈ P([0, 1]))

(‖π‖, ‖π′‖ < 1

s(g ,k ′) → |Sπ(f )− Sπ′(f )| ≤ 1k ′

)is provable in E-PAω. (and the same for E-HAω)

But (3) is the theorem expressing continuity implies Riemann integration

from constructive analysis and computable math.

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Example II: Continuity implies Riemann integration

From a proof that nonstandard uniformly continuity implies nonstandard

Riemann integration in P, i.e.

(∀f : R→ R)[(∀x , y ∈ [0, 1])[x ≈ y → f (x) ≈ f (y)]

↓(∀π, π′ ∈ P([0, 1]))(‖π‖, ‖π′‖ ≈ 0→ Sπ(f ) ≈ Sπ′(f ))

],

we can extract a term s2 such that for f : R→ R and modulus g1:

(∀k0)(∀x , y ∈ [0, 1])(|x − y | < 1g(k) → |f (x)− f (y)| < 1

k ) (3)

↓(∀k ′)(∀π, π′ ∈ P([0, 1]))

(‖π‖, ‖π′‖ < 1

s(g ,k ′) → |Sπ(f )− Sπ′(f )| ≤ 1k ′

)

is provable in E-PAω. (and the same for E-HAω)

But (3) is the theorem expressing continuity implies Riemann integration

from constructive analysis and computable math.

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Example II: Continuity implies Riemann integration

From a proof that nonstandard uniformly continuity implies nonstandard

Riemann integration in P, i.e.

(∀f : R→ R)[(∀x , y ∈ [0, 1])[x ≈ y → f (x) ≈ f (y)]

↓(∀π, π′ ∈ P([0, 1]))(‖π‖, ‖π′‖ ≈ 0→ Sπ(f ) ≈ Sπ′(f ))

],

we can extract a term s2 such that for f : R→ R and modulus g1:

(∀k0)(∀x , y ∈ [0, 1])(|x − y | < 1g(k) → |f (x)− f (y)| < 1

k ) (3)

↓(∀k ′)(∀π, π′ ∈ P([0, 1]))

(‖π‖, ‖π′‖ < 1

s(g ,k ′) → |Sπ(f )− Sπ′(f )| ≤ 1k ′

)is provable in E-PAω.

(and the same for E-HAω)

But (3) is the theorem expressing continuity implies Riemann integration

from constructive analysis and computable math.

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Example II: Continuity implies Riemann integration

From a proof that nonstandard uniformly continuity implies nonstandard

Riemann integration in P, i.e.

(∀f : R→ R)[(∀x , y ∈ [0, 1])[x ≈ y → f (x) ≈ f (y)]

↓(∀π, π′ ∈ P([0, 1]))(‖π‖, ‖π′‖ ≈ 0→ Sπ(f ) ≈ Sπ′(f ))

],

we can extract a term s2 such that for f : R→ R and modulus g1:

(∀k0)(∀x , y ∈ [0, 1])(|x − y | < 1g(k) → |f (x)− f (y)| < 1

k ) (3)

↓(∀k ′)(∀π, π′ ∈ P([0, 1]))

(‖π‖, ‖π′‖ < 1

s(g ,k ′) → |Sπ(f )− Sπ′(f )| ≤ 1k ′

)is provable in E-PAω. (and the same for E-HAω)

But (3) is the theorem expressing continuity implies Riemann integration

from constructive analysis and computable math.

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Example II: Continuity implies Riemann integration

From a proof that nonstandard uniformly continuity implies nonstandard

Riemann integration in P, i.e.

(∀f : R→ R)[(∀x , y ∈ [0, 1])[x ≈ y → f (x) ≈ f (y)]

↓(∀π, π′ ∈ P([0, 1]))(‖π‖, ‖π′‖ ≈ 0→ Sπ(f ) ≈ Sπ′(f ))

],

we can extract a term s2 such that for f : R→ R and modulus g1:

(∀k0)(∀x , y ∈ [0, 1])(|x − y | < 1g(k) → |f (x)− f (y)| < 1

k ) (3)

↓(∀k ′)(∀π, π′ ∈ P([0, 1]))

(‖π‖, ‖π′‖ < 1

s(g ,k ′) → |Sπ(f )− Sπ′(f )| ≤ 1k ′

)is provable in E-PAω. (and the same for E-HAω)

But (3) is the theorem expressing continuity implies Riemann integration

from constructive analysis and computable math.

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Explicit Reverse Mathematics

Example III: The monotone convergence theorem

From a proof in P of the following equivalence:

(∀stf 1)[(∃n)f (n) = 0→ (∃stm)f (m) = 0] (Π0

1-TRANS)

↔Every standard monotone sequence in [0, 1] nonstandard converges

two terms u, v can be extracted such that E-PAω proves

If Ξ2 is the Turing jump functional, then u(Ξ) computes the rateof convergence of any monotone sequence in [0, 1].

If Ψ1→1 computes the rate of convergence of any monotonesequence in [0, 1], then v(Ψ) is the Turing jump functional.

The above is the EXPLICIT equivalence ACA0 ↔ MCT. (and H?)

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Explicit Reverse Mathematics

Example III: The monotone convergence theorem

From a proof in P of the following equivalence:

(∀stf 1)[(∃n)f (n) = 0→ (∃stm)f (m) = 0] (Π0

1-TRANS)

↔Every standard monotone sequence in [0, 1] nonstandard converges

two terms u, v can be extracted such that E-PAω proves

If Ξ2 is the Turing jump functional, then u(Ξ) computes the rateof convergence of any monotone sequence in [0, 1].

If Ψ1→1 computes the rate of convergence of any monotonesequence in [0, 1], then v(Ψ) is the Turing jump functional.

The above is the EXPLICIT equivalence ACA0 ↔ MCT. (and H?)

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Explicit Reverse Mathematics

Example III: The monotone convergence theorem

From a proof in P of the following equivalence:

(∀stf 1)[(∃n)f (n) = 0→ (∃stm)f (m) = 0] (Π0

1-TRANS)

↔Every standard monotone sequence in [0, 1] nonstandard converges

two terms u, v can be extracted such that E-PAω proves

If Ξ2 is the Turing jump functional, then u(Ξ) computes the rateof convergence of any monotone sequence in [0, 1].

If Ψ1→1 computes the rate of convergence of any monotonesequence in [0, 1], then v(Ψ) is the Turing jump functional.

The above is the EXPLICIT equivalence ACA0 ↔ MCT. (and H?)

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Explicit Reverse Mathematics

Example III: The monotone convergence theorem

From a proof in P of the following equivalence:

(∀stf 1)[(∃n)f (n) = 0→ (∃stm)f (m) = 0] (Π0

1-TRANS)

↔Every standard monotone sequence in [0, 1] nonstandard converges

two terms u, v can be extracted such that E-PAω proves

If Ξ2 is the Turing jump functional, then u(Ξ) computes the rateof convergence of any monotone sequence in [0, 1].

If Ψ1→1 computes the rate of convergence of any monotonesequence in [0, 1], then v(Ψ) is the Turing jump functional.

The above is the EXPLICIT equivalence ACA0 ↔ MCT. (and H?)

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Explicit Reverse Mathematics

Example III: The monotone convergence theorem

From a proof in P of the following equivalence:

(∀stf 1)[(∃n)f (n) = 0→ (∃stm)f (m) = 0] (Π0

1-TRANS)

↔Every standard monotone sequence in [0, 1] nonstandard converges

two terms u, v can be extracted such that E-PAω proves

If Ξ2 is the Turing jump functional, then u(Ξ) computes the rateof convergence of any monotone sequence in [0, 1].

If Ψ1→1 computes the rate of convergence of any monotonesequence in [0, 1], then v(Ψ) is the Turing jump functional.

The above is the EXPLICIT equivalence ACA0 ↔ MCT. (and H?)

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Explicit Reverse Mathematics

Example III: The monotone convergence theorem

From a proof in P of the following equivalence:

(∀stf 1)[(∃n)f (n) = 0→ (∃stm)f (m) = 0] (Π0

1-TRANS)

↔Every standard monotone sequence in [0, 1] nonstandard converges

two terms u, v can be extracted such that E-PAω proves

If Ξ2 is the Turing jump functional, then u(Ξ) computes the rateof convergence of any monotone sequence in [0, 1].

If Ψ1→1 computes the rate of convergence of any monotonesequence in [0, 1], then v(Ψ) is the Turing jump functional.

The above is the EXPLICIT equivalence ACA0 ↔ MCT.

(and H?)

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Explicit Reverse Mathematics

Example III: The monotone convergence theorem

From a proof in P of the following equivalence:

(∀stf 1)[(∃n)f (n) = 0→ (∃stm)f (m) = 0] (Π0

1-TRANS)

↔Every standard monotone sequence in [0, 1] nonstandard converges

two terms u, v can be extracted such that E-PAω proves

If Ξ2 is the Turing jump functional, then u(Ξ) computes the rateof convergence of any monotone sequence in [0, 1].

If Ψ1→1 computes the rate of convergence of any monotonesequence in [0, 1], then v(Ψ) is the Turing jump functional.

The above is the EXPLICIT equivalence ACA0 ↔ MCT. (and H?)

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Explicit Reverse Mathematics

Example IV: Group Theory

From a proof in P of the following equivalence:

(∀stf 1)[(∃g1)(∀n)f (gn) = 0→ (∃stg1)(∀stm)f (gm) = 0]

(Π11-TRANS)

↔ Every standard countable abelian group is a direct sum

of a standard divisible group and a standard reduced group

two terms u, v can be extracted such that E-PAω proves

If Ξ2 is the Suslin functional, then u(Ξ) computes the divisible andreduced group for countable abelian groups.

If Ψ1→1 computes computes the divisible and reduced group forcountable abelian groups, then v(Ψ) is the Suslin functional.

The above is the EXPLICIT equivalence Π11-CA0 ↔ DIV.

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Explicit Reverse Mathematics

Example IV: Group Theory

From a proof in P of the following equivalence:

(∀stf 1)[(∃g1)(∀n)f (gn) = 0→ (∃stg1)(∀stm)f (gm) = 0]

(Π11-TRANS)

↔ Every standard countable abelian group is a direct sum

of a standard divisible group and a standard reduced group

two terms u, v can be extracted such that E-PAω proves

If Ξ2 is the Suslin functional, then u(Ξ) computes the divisible andreduced group for countable abelian groups.

If Ψ1→1 computes computes the divisible and reduced group forcountable abelian groups, then v(Ψ) is the Suslin functional.

The above is the EXPLICIT equivalence Π11-CA0 ↔ DIV.

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Explicit Reverse Mathematics

Example IV: Group Theory

From a proof in P of the following equivalence:

(∀stf 1)[(∃g1)(∀n)f (gn) = 0→ (∃stg1)(∀stm)f (gm) = 0]

(Π11-TRANS)

↔ Every standard countable abelian group is a direct sum

of a standard divisible group and a standard reduced group

two terms u, v can be extracted such that E-PAω proves

If Ξ2 is the Suslin functional, then u(Ξ) computes the divisible andreduced group for countable abelian groups.

If Ψ1→1 computes computes the divisible and reduced group forcountable abelian groups, then v(Ψ) is the Suslin functional.

The above is the EXPLICIT equivalence Π11-CA0 ↔ DIV.

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Explicit Reverse Mathematics

Example IV: Group Theory

From a proof in P of the following equivalence:

(∀stf 1)[(∃g1)(∀n)f (gn) = 0→ (∃stg1)(∀stm)f (gm) = 0]

(Π11-TRANS)

↔ Every standard countable abelian group is a direct sum

of a standard divisible group and a standard reduced group

two terms u, v can be extracted such that E-PAω proves

If Ξ2 is the Suslin functional, then u(Ξ) computes the divisible andreduced group for countable abelian groups.

If Ψ1→1 computes computes the divisible and reduced group forcountable abelian groups, then v(Ψ) is the Suslin functional.

The above is the EXPLICIT equivalence Π11-CA0 ↔ DIV.

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Explicit Reverse Mathematics

Example IV: Group Theory

From a proof in P of the following equivalence:

(∀stf 1)[(∃g1)(∀n)f (gn) = 0→ (∃stg1)(∀stm)f (gm) = 0]

(Π11-TRANS)

↔ Every standard countable abelian group is a direct sum

of a standard divisible group and a standard reduced group

two terms u, v can be extracted such that E-PAω proves

If Ξ2 is the Suslin functional, then u(Ξ) computes the divisible andreduced group for countable abelian groups.

If Ψ1→1 computes computes the divisible and reduced group forcountable abelian groups, then v(Ψ) is the Suslin functional.

The above is the EXPLICIT equivalence Π11-CA0 ↔ DIV.

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Explicit Reverse Mathematics

Example IV: Group Theory

From a proof in P of the following equivalence:

(∀stf 1)[(∃g1)(∀n)f (gn) = 0→ (∃stg1)(∀stm)f (gm) = 0]

(Π11-TRANS)

↔ Every standard countable abelian group is a direct sum

of a standard divisible group and a standard reduced group

two terms u, v can be extracted such that E-PAω proves

If Ξ2 is the Suslin functional, then u(Ξ) computes the divisible andreduced group for countable abelian groups.

If Ψ1→1 computes computes the divisible and reduced group forcountable abelian groups, then v(Ψ) is the Suslin functional.

The above is the EXPLICIT equivalence Π11-CA0 ↔ DIV.

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Example V: Compactness

X is nonstandard compact IFF (∀x ∈ X )(∃sty ∈ X )(x ≈ y).

From a proof in P of the following equivalence:

[0, 1] is nonstandard compact (STP)

↔Every ns-cont. function is ns-Riemann integrable on [0, 1]

two terms u, v can be extracted such that E-PAω proves

If Ω3 is the fan functional, then u(Ω) computes the Riemannintegral for any cont. function on [0, 1].

If Ψ(1→1)→1 computes the Riemann integral for any. cont functionon [0, 1], then v(Ψ) is the fan functional.

= the EXPLICIT version of FAN↔ (cont → Rieman int. on [0, 1]).

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Example V: Compactness

X is nonstandard compact IFF (∀x ∈ X )(∃sty ∈ X )(x ≈ y).

From a proof in P of the following equivalence:

[0, 1] is nonstandard compact (STP)

↔Every ns-cont. function is ns-Riemann integrable on [0, 1]

two terms u, v can be extracted such that E-PAω proves

If Ω3 is the fan functional, then u(Ω) computes the Riemannintegral for any cont. function on [0, 1].

If Ψ(1→1)→1 computes the Riemann integral for any. cont functionon [0, 1], then v(Ψ) is the fan functional.

= the EXPLICIT version of FAN↔ (cont → Rieman int. on [0, 1]).

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Example V: Compactness

X is nonstandard compact IFF (∀x ∈ X )(∃sty ∈ X )(x ≈ y).

From a proof in P of the following equivalence:

[0, 1] is nonstandard compact (STP)

↔Every ns-cont. function is ns-Riemann integrable on [0, 1]

two terms u, v can be extracted such that E-PAω proves

If Ω3 is the fan functional, then u(Ω) computes the Riemannintegral for any cont. function on [0, 1].

If Ψ(1→1)→1 computes the Riemann integral for any. cont functionon [0, 1], then v(Ψ) is the fan functional.

= the EXPLICIT version of FAN↔ (cont → Rieman int. on [0, 1]).

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Example V: Compactness

X is nonstandard compact IFF (∀x ∈ X )(∃sty ∈ X )(x ≈ y).

From a proof in P of the following equivalence:

[0, 1] is nonstandard compact (STP)

↔Every ns-cont. function is ns-Riemann integrable on [0, 1]

two terms u, v can be extracted such that E-PAω proves

If Ω3 is the fan functional, then u(Ω) computes the Riemannintegral for any cont. function on [0, 1].

If Ψ(1→1)→1 computes the Riemann integral for any. cont functionon [0, 1], then v(Ψ) is the fan functional.

= the EXPLICIT version of FAN↔ (cont → Rieman int. on [0, 1]).

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Example V: Compactness

X is nonstandard compact IFF (∀x ∈ X )(∃sty ∈ X )(x ≈ y).

From a proof in P of the following equivalence:

[0, 1] is nonstandard compact (STP)

↔Every ns-cont. function is ns-Riemann integrable on [0, 1]

two terms u, v can be extracted such that E-PAω proves

If Ω3 is the fan functional, then u(Ω) computes the Riemannintegral for any cont. function on [0, 1].

If Ψ(1→1)→1 computes the Riemann integral for any. cont functionon [0, 1], then v(Ψ) is the fan functional.

= the EXPLICIT version of FAN↔ (cont → Rieman int. on [0, 1]).

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Example V: Compactness

X is nonstandard compact IFF (∀x ∈ X )(∃sty ∈ X )(x ≈ y).

From a proof in P of the following equivalence:

[0, 1] is nonstandard compact (STP)

↔Every ns-cont. function is ns-Riemann integrable on [0, 1]

two terms u, v can be extracted such that E-PAω proves

If Ω3 is the fan functional, then u(Ω) computes the Riemannintegral for any cont. function on [0, 1].

If Ψ(1→1)→1 computes the Riemann integral for any. cont functionon [0, 1], then v(Ψ) is the fan functional.

= the EXPLICIT version of FAN↔ (cont → Rieman int. on [0, 1]).

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Example V: Compactness

X is nonstandard compact IFF (∀x ∈ X )(∃sty ∈ X )(x ≈ y).

From a proof in P of the following equivalence:

[0, 1] is nonstandard compact (STP)

↔Every ns-cont. function is ns-Riemann integrable on [0, 1]

two terms u, v can be extracted such that E-PAω proves

If Ω3 is the fan functional, then u(Ω) computes the Riemannintegral for any cont. function on [0, 1].

If Ψ(1→1)→1 computes the Riemann integral for any. cont functionon [0, 1], then v(Ψ) is the fan functional.

= the EXPLICIT version of FAN↔ (cont → Rieman int. on [0, 1]).

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Example VI: Compactness bisCompactness has multiple non-equivalent normal forms.

InExample V, the normal form of ns-compactness was a nonstandardversion of FAN. Here, the normal form expresses ‘the space can bediscretely divided into infinitesimal pieces’.

From a proof in P of the following theorem

For a uniformly ns-cont. f and ns-compact X , f (X ) is also ns-compact.

a term u can be extracted such that E-PAω proves

If Ψ witnesses that X is totally bounded and g is a modulus of uniform

cont. for f , then u(Ψ, g) witnesses that f (X ) is totally bounded.

. . . which is a theorem from constructive analysis and comp. math.

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Example VI: Compactness bisCompactness has multiple non-equivalent normal forms. InExample V, the normal form of ns-compactness was a nonstandardversion of FAN.

Here, the normal form expresses ‘the space can bediscretely divided into infinitesimal pieces’.

From a proof in P of the following theorem

For a uniformly ns-cont. f and ns-compact X , f (X ) is also ns-compact.

a term u can be extracted such that E-PAω proves

If Ψ witnesses that X is totally bounded and g is a modulus of uniform

cont. for f , then u(Ψ, g) witnesses that f (X ) is totally bounded.

. . . which is a theorem from constructive analysis and comp. math.

Page 97: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

The unreasonable effectiveness of NSA

Example VI: Compactness bisCompactness has multiple non-equivalent normal forms. InExample V, the normal form of ns-compactness was a nonstandardversion of FAN. Here, the normal form expresses ‘the space can bediscretely divided into infinitesimal pieces’.

From a proof in P of the following theorem

For a uniformly ns-cont. f and ns-compact X , f (X ) is also ns-compact.

a term u can be extracted such that E-PAω proves

If Ψ witnesses that X is totally bounded and g is a modulus of uniform

cont. for f , then u(Ψ, g) witnesses that f (X ) is totally bounded.

. . . which is a theorem from constructive analysis and comp. math.

Page 98: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

The unreasonable effectiveness of NSA

Example VI: Compactness bisCompactness has multiple non-equivalent normal forms. InExample V, the normal form of ns-compactness was a nonstandardversion of FAN. Here, the normal form expresses ‘the space can bediscretely divided into infinitesimal pieces’.

From a proof in P of the following theorem

For a uniformly ns-cont. f and ns-compact X , f (X ) is also ns-compact.

a term u can be extracted such that E-PAω proves

If Ψ witnesses that X is totally bounded and g is a modulus of uniform

cont. for f , then u(Ψ, g) witnesses that f (X ) is totally bounded.

. . . which is a theorem from constructive analysis and comp. math.

Page 99: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

The unreasonable effectiveness of NSA

Example VI: Compactness bisCompactness has multiple non-equivalent normal forms. InExample V, the normal form of ns-compactness was a nonstandardversion of FAN. Here, the normal form expresses ‘the space can bediscretely divided into infinitesimal pieces’.

From a proof in P of the following theorem

For a uniformly ns-cont. f and ns-compact X , f (X ) is also ns-compact.

a term u can be extracted such that E-PAω proves

If Ψ witnesses that X is totally bounded and g is a modulus of uniform

cont. for f , then u(Ψ, g) witnesses that f (X ) is totally bounded.

. . . which is a theorem from constructive analysis and comp. math.

Page 100: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

The unreasonable effectiveness of NSA

Example VI: Compactness bisCompactness has multiple non-equivalent normal forms. InExample V, the normal form of ns-compactness was a nonstandardversion of FAN. Here, the normal form expresses ‘the space can bediscretely divided into infinitesimal pieces’.

From a proof in P of the following theorem

For a uniformly ns-cont. f and ns-compact X , f (X ) is also ns-compact.

a term u can be extracted such that E-PAω proves

If Ψ witnesses that X is totally bounded and g is a modulus of uniform

cont. for f , then u(Ψ, g) witnesses that f (X ) is totally bounded.

. . . which is a theorem from constructive analysis and comp. math.

Page 101: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

The unreasonable effectiveness of NSA

Example VI: Compactness bisCompactness has multiple non-equivalent normal forms. InExample V, the normal form of ns-compactness was a nonstandardversion of FAN. Here, the normal form expresses ‘the space can bediscretely divided into infinitesimal pieces’.

From a proof in P of the following theorem

For a uniformly ns-cont. f and ns-compact X , f (X ) is also ns-compact.

a term u can be extracted such that E-PAω proves

If Ψ witnesses that X is totally bounded and g is a modulus of uniform

cont. for f , then u(Ψ, g) witnesses that f (X ) is totally bounded.

. . . which is a theorem from constructive analysis and comp. math.

Page 102: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Conclusion

Nonstandard Analysis is unreasonably effective as follows:

a) Focus on theorems of pure NSA, i.e. involving the nonstandarddefinitions of continuity, differentiation, Riemann integration,compactness, open sets, et cetera.

b) TERM EXTRACTION works for HUGE class ‘theorems of pure NSA’

In particular:

a) Observation: Every theorem of pure NSA can be brought intothe normal form (∀stx)(∃sty)ϕ(x , y) (ϕ internal).

b) P has the TERM EXTRACTION property for normal forms:

If P proves (∀stx)(∃sty)ϕ(x , y), then from the latter proof, a termt can be extracted such that E-PAω proves (∀x)(∃y ∈ t(x))ϕ(x , y)

Thus, NSA provides a ‘computational foundation’ (for sosoa).

Page 103: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Conclusion

Nonstandard Analysis is unreasonably effective as follows:

a) Focus on theorems of pure NSA, i.e. involving the nonstandarddefinitions of continuity, differentiation, Riemann integration,compactness, open sets, et cetera.

b) TERM EXTRACTION works for HUGE class ‘theorems of pure NSA’

In particular:

a) Observation: Every theorem of pure NSA can be brought intothe normal form (∀stx)(∃sty)ϕ(x , y) (ϕ internal).

b) P has the TERM EXTRACTION property for normal forms:

If P proves (∀stx)(∃sty)ϕ(x , y), then from the latter proof, a termt can be extracted such that E-PAω proves (∀x)(∃y ∈ t(x))ϕ(x , y)

Thus, NSA provides a ‘computational foundation’ (for sosoa).

Page 104: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Conclusion

Nonstandard Analysis is unreasonably effective as follows:

a) Focus on theorems of pure NSA, i.e. involving the nonstandarddefinitions of continuity, differentiation, Riemann integration,compactness, open sets, et cetera.

b) TERM EXTRACTION works for HUGE class ‘theorems of pure NSA’

In particular:

a) Observation: Every theorem of pure NSA can be brought intothe normal form (∀stx)(∃sty)ϕ(x , y) (ϕ internal).

b) P has the TERM EXTRACTION property for normal forms:

If P proves (∀stx)(∃sty)ϕ(x , y), then from the latter proof, a termt can be extracted such that E-PAω proves (∀x)(∃y ∈ t(x))ϕ(x , y)

Thus, NSA provides a ‘computational foundation’ (for sosoa).

Page 105: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Conclusion

Nonstandard Analysis is unreasonably effective as follows:

a) Focus on theorems of pure NSA, i.e. involving the nonstandarddefinitions of continuity, differentiation, Riemann integration,compactness, open sets, et cetera.

b) TERM EXTRACTION works for HUGE class ‘theorems of pure NSA’

In particular:

a) Observation: Every theorem of pure NSA can be brought intothe normal form (∀stx)(∃sty)ϕ(x , y) (ϕ internal).

b) P has the TERM EXTRACTION property for normal forms:

If P proves (∀stx)(∃sty)ϕ(x , y), then from the latter proof, a termt can be extracted such that E-PAω proves (∀x)(∃y ∈ t(x))ϕ(x , y)

Thus, NSA provides a ‘computational foundation’ (for sosoa).

Page 106: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Conclusion

Nonstandard Analysis is unreasonably effective as follows:

a) Focus on theorems of pure NSA, i.e. involving the nonstandarddefinitions of continuity, differentiation, Riemann integration,compactness, open sets, et cetera.

b) TERM EXTRACTION works for HUGE class ‘theorems of pure NSA’

In particular:

a) Observation: Every theorem of pure NSA can be brought intothe normal form (∀stx)(∃sty)ϕ(x , y) (ϕ internal).

b) P has the TERM EXTRACTION property for normal forms:

If P proves (∀stx)(∃sty)ϕ(x , y), then from the latter proof, a termt can be extracted such that E-PAω proves (∀x)(∃y ∈ t(x))ϕ(x , y)

Thus, NSA provides a ‘computational foundation’ (for sosoa).

Page 107: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Conclusion

Nonstandard Analysis is unreasonably effective as follows:

a) Focus on theorems of pure NSA, i.e. involving the nonstandarddefinitions of continuity, differentiation, Riemann integration,compactness, open sets, et cetera.

b) TERM EXTRACTION works for HUGE class ‘theorems of pure NSA’

In particular:

a) Observation: Every theorem of pure NSA can be brought intothe normal form (∀stx)(∃sty)ϕ(x , y) (ϕ internal).

b) P has the TERM EXTRACTION property for normal forms:

If P proves (∀stx)(∃sty)ϕ(x , y), then from the latter proof, a termt can be extracted such that E-PAω proves (∀x)(∃y ∈ t(x))ϕ(x , y)

Thus, NSA provides a ‘computational foundation’ (for sosoa).

Page 108: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Conclusion

Nonstandard Analysis is unreasonably effective as follows:

a) Focus on theorems of pure NSA, i.e. involving the nonstandarddefinitions of continuity, differentiation, Riemann integration,compactness, open sets, et cetera.

b) TERM EXTRACTION works for HUGE class ‘theorems of pure NSA’

In particular:

a) Observation: Every theorem of pure NSA can be brought intothe normal form (∀stx)(∃sty)ϕ(x , y) (ϕ internal).

b) P has the TERM EXTRACTION property for normal forms:

If P proves (∀stx)(∃sty)ϕ(x , y), then from the latter proof, a termt can be extracted such that E-PAω proves (∀x)(∃y ∈ t(x))ϕ(x , y)

Thus, NSA provides a ‘computational foundation’ (for sosoa).

Page 109: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Conclusion

Nonstandard Analysis is unreasonably effective as follows:

a) Focus on theorems of pure NSA, i.e. involving the nonstandarddefinitions of continuity, differentiation, Riemann integration,compactness, open sets, et cetera.

b) TERM EXTRACTION works for HUGE class ‘theorems of pure NSA’

In particular:

a) Observation: Every theorem of pure NSA can be brought intothe normal form (∀stx)(∃sty)ϕ(x , y) (ϕ internal).

b) P has the TERM EXTRACTION property for normal forms:

If P proves (∀stx)(∃sty)ϕ(x , y), then from the latter proof, a termt can be extracted such that E-PAω proves (∀x)(∃y ∈ t(x))ϕ(x , y)

Thus, NSA provides a ‘computational foundation’ (for sosoa).

Page 110: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Towards meta-equivalence: Hebrandisations

From a proof that nonstandard uniformly continuity impliesnonstandard Riemann integration in P, i.e.

(∀f : R→ R)[(∀x , y ∈ [0, 1])[x ≈ y → f (x) ≈ f (y)]

↓ (4)

(∀π, π′ ∈ P([0, 1]))(‖π‖, ‖π′‖ ≈ 0→ Sπ(f ) ≈ Sπ′(f ))],

we can extract terms i , o such that for all f , g : R→ R, and ε′ > 0:

(∀x , y ∈ [0, 1], ε > i(g , ε′))(|x − y | < g(ε)→ |f (x)− f (y)| < ε)

↓ (5)

(∀π, π′ ∈ P([0, 1]))(‖π‖, ‖π′‖ < o(g , ε′)→ |Sπ(f )− Sπ′(f )| ≤ ε′

)is provable in E-PAω, AND VICE VERSA: if E-PAω ` (5), then P ` (4)

(5) is a thm from numerical analysis, called HERBRANDISATION of (4)

Every theorem of pure NSA has such a ‘meta-equivalent’ Hebrandisation.

Page 111: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Towards meta-equivalence: Hebrandisations

From a proof that nonstandard uniformly continuity impliesnonstandard Riemann integration in P, i.e.

(∀f : R→ R)[(∀x , y ∈ [0, 1])[x ≈ y → f (x) ≈ f (y)]

↓ (4)

(∀π, π′ ∈ P([0, 1]))(‖π‖, ‖π′‖ ≈ 0→ Sπ(f ) ≈ Sπ′(f ))],

we can extract terms i , o such that for all f , g : R→ R, and ε′ > 0:

(∀x , y ∈ [0, 1], ε > i(g , ε′))(|x − y | < g(ε)→ |f (x)− f (y)| < ε)

↓ (5)

(∀π, π′ ∈ P([0, 1]))(‖π‖, ‖π′‖ < o(g , ε′)→ |Sπ(f )− Sπ′(f )| ≤ ε′

)is provable in E-PAω, AND VICE VERSA: if E-PAω ` (5), then P ` (4)

(5) is a thm from numerical analysis, called HERBRANDISATION of (4)

Every theorem of pure NSA has such a ‘meta-equivalent’ Hebrandisation.

Page 112: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Towards meta-equivalence: Hebrandisations

From a proof that nonstandard uniformly continuity impliesnonstandard Riemann integration in P, i.e.

(∀f : R→ R)[(∀x , y ∈ [0, 1])[x ≈ y → f (x) ≈ f (y)]

↓ (4)

(∀π, π′ ∈ P([0, 1]))(‖π‖, ‖π′‖ ≈ 0→ Sπ(f ) ≈ Sπ′(f ))],

we can extract terms i , o such that for all f , g : R→ R, and ε′ > 0:

(∀x , y ∈ [0, 1], ε > i(g , ε′))(|x − y | < g(ε)→ |f (x)− f (y)| < ε)

↓ (5)

(∀π, π′ ∈ P([0, 1]))(‖π‖, ‖π′‖ < o(g , ε′)→ |Sπ(f )− Sπ′(f )| ≤ ε′

)is provable in E-PAω, AND VICE VERSA: if E-PAω ` (5), then P ` (4)

(5) is a thm from numerical analysis, called HERBRANDISATION of (4)

Every theorem of pure NSA has such a ‘meta-equivalent’ Hebrandisation.

Page 113: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Towards meta-equivalence: Hebrandisations

From a proof that nonstandard uniformly continuity impliesnonstandard Riemann integration in P, i.e.

(∀f : R→ R)[(∀x , y ∈ [0, 1])[x ≈ y → f (x) ≈ f (y)]

↓ (4)

(∀π, π′ ∈ P([0, 1]))(‖π‖, ‖π′‖ ≈ 0→ Sπ(f ) ≈ Sπ′(f ))],

we can extract terms i , o such that for all f , g : R→ R, and ε′ > 0:

(∀x , y ∈ [0, 1], ε > i(g , ε′))(|x − y | < g(ε)→ |f (x)− f (y)| < ε)

↓ (5)

(∀π, π′ ∈ P([0, 1]))(‖π‖, ‖π′‖ < o(g , ε′)→ |Sπ(f )− Sπ′(f )| ≤ ε′

)

is provable in E-PAω, AND VICE VERSA: if E-PAω ` (5), then P ` (4)

(5) is a thm from numerical analysis, called HERBRANDISATION of (4)

Every theorem of pure NSA has such a ‘meta-equivalent’ Hebrandisation.

Page 114: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Towards meta-equivalence: Hebrandisations

From a proof that nonstandard uniformly continuity impliesnonstandard Riemann integration in P, i.e.

(∀f : R→ R)[(∀x , y ∈ [0, 1])[x ≈ y → f (x) ≈ f (y)]

↓ (4)

(∀π, π′ ∈ P([0, 1]))(‖π‖, ‖π′‖ ≈ 0→ Sπ(f ) ≈ Sπ′(f ))],

we can extract terms i , o such that for all f , g : R→ R, and ε′ > 0:

(∀x , y ∈ [0, 1], ε > i(g , ε′))(|x − y | < g(ε)→ |f (x)− f (y)| < ε)

↓ (5)

(∀π, π′ ∈ P([0, 1]))(‖π‖, ‖π′‖ < o(g , ε′)→ |Sπ(f )− Sπ′(f )| ≤ ε′

)is provable in E-PAω,

AND VICE VERSA: if E-PAω ` (5), then P ` (4)

(5) is a thm from numerical analysis, called HERBRANDISATION of (4)

Every theorem of pure NSA has such a ‘meta-equivalent’ Hebrandisation.

Page 115: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Towards meta-equivalence: Hebrandisations

From a proof that nonstandard uniformly continuity impliesnonstandard Riemann integration in P, i.e.

(∀f : R→ R)[(∀x , y ∈ [0, 1])[x ≈ y → f (x) ≈ f (y)]

↓ (4)

(∀π, π′ ∈ P([0, 1]))(‖π‖, ‖π′‖ ≈ 0→ Sπ(f ) ≈ Sπ′(f ))],

we can extract terms i , o such that for all f , g : R→ R, and ε′ > 0:

(∀x , y ∈ [0, 1], ε > i(g , ε′))(|x − y | < g(ε)→ |f (x)− f (y)| < ε)

↓ (5)

(∀π, π′ ∈ P([0, 1]))(‖π‖, ‖π′‖ < o(g , ε′)→ |Sπ(f )− Sπ′(f )| ≤ ε′

)is provable in E-PAω, AND VICE VERSA: if E-PAω ` (5), then P ` (4)

(5) is a thm from numerical analysis, called HERBRANDISATION of (4)

Every theorem of pure NSA has such a ‘meta-equivalent’ Hebrandisation.

Page 116: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Towards meta-equivalence: Hebrandisations

From a proof that nonstandard uniformly continuity impliesnonstandard Riemann integration in P, i.e.

(∀f : R→ R)[(∀x , y ∈ [0, 1])[x ≈ y → f (x) ≈ f (y)]

↓ (4)

(∀π, π′ ∈ P([0, 1]))(‖π‖, ‖π′‖ ≈ 0→ Sπ(f ) ≈ Sπ′(f ))],

we can extract terms i , o such that for all f , g : R→ R, and ε′ > 0:

(∀x , y ∈ [0, 1], ε > i(g , ε′))(|x − y | < g(ε)→ |f (x)− f (y)| < ε)

↓ (5)

(∀π, π′ ∈ P([0, 1]))(‖π‖, ‖π′‖ < o(g , ε′)→ |Sπ(f )− Sπ′(f )| ≤ ε′

)is provable in E-PAω, AND VICE VERSA: if E-PAω ` (5), then P ` (4)

(5) is a thm from numerical analysis, called HERBRANDISATION of (4)

Every theorem of pure NSA has such a ‘meta-equivalent’ Hebrandisation.

Page 117: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Towards meta-equivalence: Hebrandisations

From a proof that nonstandard uniformly continuity impliesnonstandard Riemann integration in P, i.e.

(∀f : R→ R)[(∀x , y ∈ [0, 1])[x ≈ y → f (x) ≈ f (y)]

↓ (4)

(∀π, π′ ∈ P([0, 1]))(‖π‖, ‖π′‖ ≈ 0→ Sπ(f ) ≈ Sπ′(f ))],

we can extract terms i , o such that for all f , g : R→ R, and ε′ > 0:

(∀x , y ∈ [0, 1], ε > i(g , ε′))(|x − y | < g(ε)→ |f (x)− f (y)| < ε)

↓ (5)

(∀π, π′ ∈ P([0, 1]))(‖π‖, ‖π′‖ < o(g , ε′)→ |Sπ(f )− Sπ′(f )| ≤ ε′

)is provable in E-PAω, AND VICE VERSA: if E-PAω ` (5), then P ` (4)

(5) is a thm from numerical analysis, called HERBRANDISATION of (4)

Every theorem of pure NSA has such a ‘meta-equivalent’ Hebrandisation.

Page 118: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Application I: Cutting out the middle man in vagueness

The predicate ‘≈’ is the text-book formalisation of the vaguenotion ‘nearness’.

Literally: ‘≈’ from NSA has been used as a foundation formodelling vague predicates like nearness in AI, fuzzy set theory,and optimisation and control.

(∀x , y ∈ [0, 1])(x ≈ y → f (x) ≈ f (y))

Continuity in physics: If x , y are ‘very close’, so are their images.

However, an ‘expert’ has to come in and say what ‘≈’ should meanin every particular context.

Using Herbrandisations, we can faithfully remove vagueness (likenear, large, small, etc) from mathematical statements in theapplied sciences without the involvement of experts. (Sorites)

Page 119: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Application I: Cutting out the middle man in vagueness

The predicate ‘≈’ is the text-book formalisation of the vaguenotion ‘nearness’.

Literally: ‘≈’ from NSA has been used as a foundation formodelling vague predicates like nearness in AI, fuzzy set theory,and optimisation and control.

(∀x , y ∈ [0, 1])(x ≈ y → f (x) ≈ f (y))

Continuity in physics: If x , y are ‘very close’, so are their images.

However, an ‘expert’ has to come in and say what ‘≈’ should meanin every particular context.

Using Herbrandisations, we can faithfully remove vagueness (likenear, large, small, etc) from mathematical statements in theapplied sciences without the involvement of experts. (Sorites)

Page 120: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Application I: Cutting out the middle man in vagueness

The predicate ‘≈’ is the text-book formalisation of the vaguenotion ‘nearness’.

Literally: ‘≈’ from NSA has been used as a foundation formodelling vague predicates like nearness in AI, fuzzy set theory,and optimisation and control.

(∀x , y ∈ [0, 1])(x ≈ y → f (x) ≈ f (y))

Continuity in physics: If x , y are ‘very close’, so are their images.

However, an ‘expert’ has to come in and say what ‘≈’ should meanin every particular context.

Using Herbrandisations, we can faithfully remove vagueness (likenear, large, small, etc) from mathematical statements in theapplied sciences without the involvement of experts. (Sorites)

Page 121: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Application I: Cutting out the middle man in vagueness

The predicate ‘≈’ is the text-book formalisation of the vaguenotion ‘nearness’.

Literally: ‘≈’ from NSA has been used as a foundation formodelling vague predicates like nearness in AI, fuzzy set theory,and optimisation and control.

(∀x , y ∈ [0, 1])(x ≈ y → f (x) ≈ f (y))

Continuity in physics: If x , y are ‘very close’, so are their images.

However, an ‘expert’ has to come in and say what ‘≈’ should meanin every particular context.

Using Herbrandisations, we can faithfully remove vagueness (likenear, large, small, etc) from mathematical statements in theapplied sciences without the involvement of experts. (Sorites)

Page 122: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Application I: Cutting out the middle man in vagueness

The predicate ‘≈’ is the text-book formalisation of the vaguenotion ‘nearness’.

Literally: ‘≈’ from NSA has been used as a foundation formodelling vague predicates like nearness in AI, fuzzy set theory,and optimisation and control.

(∀x , y ∈ [0, 1])(x ≈ y → f (x) ≈ f (y))

Continuity in physics: If x , y are ‘very close’, so are their images.

However, an ‘expert’ has to come in and say what ‘≈’ should meanin every particular context.

Using Herbrandisations, we can faithfully remove vagueness (likenear, large, small, etc) from mathematical statements in theapplied sciences without the involvement of experts. (Sorites)

Page 123: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Application I: Cutting out the middle man in vagueness

The predicate ‘≈’ is the text-book formalisation of the vaguenotion ‘nearness’.

Literally: ‘≈’ from NSA has been used as a foundation formodelling vague predicates like nearness in AI, fuzzy set theory,and optimisation and control.

(∀x , y ∈ [0, 1])(x ≈ y → f (x) ≈ f (y))

Continuity in physics: If x , y are ‘very close’, so are their images.

However, an ‘expert’ has to come in and say what ‘≈’ should meanin every particular context.

Using Herbrandisations, we can faithfully remove vagueness (likenear, large, small, etc) from mathematical statements in theapplied sciences without the involvement of experts.

(Sorites)

Page 124: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Application I: Cutting out the middle man in vagueness

The predicate ‘≈’ is the text-book formalisation of the vaguenotion ‘nearness’.

Literally: ‘≈’ from NSA has been used as a foundation formodelling vague predicates like nearness in AI, fuzzy set theory,and optimisation and control.

(∀x , y ∈ [0, 1])(x ≈ y → f (x) ≈ f (y))

Continuity in physics: If x , y are ‘very close’, so are their images.

However, an ‘expert’ has to come in and say what ‘≈’ should meanin every particular context.

Using Herbrandisations, we can faithfully remove vagueness (likenear, large, small, etc) from mathematical statements in theapplied sciences without the involvement of experts. (Sorites)

Page 125: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Application II: Nominalism and poetic justice

Bishop, founder of Constructive Analysis, anticipated Herbrandisations. . .

on the same page of Historia Mathematica he trashes NSA.

Page 126: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Application II: Nominalism and poetic justice

Bishop, founder of Constructive Analysis, anticipated Herbrandisations. . .

on the same page of Historia Mathematica he trashes NSA.

Page 127: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Application II: Nominalism and poetic justice

Bishop, founder of Constructive Analysis, anticipated Herbrandisations. . .

on the same page of Historia Mathematica he trashes NSA.

Page 128: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Application II: Nominalism and poetic justice

In general, nominalism about infinitesimals seems meaningless inlight of Herbrandisations.

Herbrandisations lead to a rather structuralist view of mathematics:

The objects of mathematics do not matter, but mathematicalstructures do.

In particular, Herbrandisations give a way of talking ‘directly’about Nonstandard Analysis in the standard model.

‘directly’ means that the meta-equivalence between a nonstandardthm and its Herbrandisation is acceptable to thefinitist/constructivist.

Page 129: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Application II: Nominalism and poetic justice

In general, nominalism about infinitesimals seems meaningless inlight of Herbrandisations.

Herbrandisations lead to a rather structuralist view of mathematics:

The objects of mathematics do not matter, but mathematicalstructures do.

In particular, Herbrandisations give a way of talking ‘directly’about Nonstandard Analysis in the standard model.

‘directly’ means that the meta-equivalence between a nonstandardthm and its Herbrandisation is acceptable to thefinitist/constructivist.

Page 130: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Application II: Nominalism and poetic justice

In general, nominalism about infinitesimals seems meaningless inlight of Herbrandisations.

Herbrandisations lead to a rather structuralist view of mathematics:

The objects of mathematics do not matter, but mathematicalstructures do.

In particular, Herbrandisations give a way of talking ‘directly’about Nonstandard Analysis in the standard model.

‘directly’ means that the meta-equivalence between a nonstandardthm and its Herbrandisation is acceptable to thefinitist/constructivist.

Page 131: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Application II: Nominalism and poetic justice

In general, nominalism about infinitesimals seems meaningless inlight of Herbrandisations.

Herbrandisations lead to a rather structuralist view of mathematics:

The objects of mathematics do not matter, but mathematicalstructures do.

In particular, Herbrandisations give a way of talking ‘directly’about Nonstandard Analysis in the standard model.

‘directly’ means that the meta-equivalence between a nonstandardthm and its Herbrandisation is acceptable to thefinitist/constructivist.

Page 132: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Application III: Frege’s Sinn und bedeuting

Bedeutung ≈ the object to which a term refers.

Sinne ≈ the way a term refers to an object

Clark Kent and Superman refer to the same person (same Bedeutung).

However, they do so in a very different way (different Sinne)

The nonstandard theorem = the Bedeutung

The Hebrandisation/numerical version = the Sinne

Note that the numerical version is satisfied by infinitely manyterms i , o.

Page 133: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Application III: Frege’s Sinn und bedeuting

Bedeutung ≈ the object to which a term refers.

Sinne ≈ the way a term refers to an object

Clark Kent and Superman refer to the same person (same Bedeutung).

However, they do so in a very different way (different Sinne)

The nonstandard theorem = the Bedeutung

The Hebrandisation/numerical version = the Sinne

Note that the numerical version is satisfied by infinitely manyterms i , o.

Page 134: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Application III: Frege’s Sinn und bedeuting

Bedeutung ≈ the object to which a term refers.

Sinne ≈ the way a term refers to an object

Clark Kent and Superman refer to the same person (same Bedeutung).

However, they do so in a very different way (different Sinne)

The nonstandard theorem = the Bedeutung

The Hebrandisation/numerical version = the Sinne

Note that the numerical version is satisfied by infinitely manyterms i , o.

Page 135: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Application III: Frege’s Sinn und bedeuting

Bedeutung ≈ the object to which a term refers.

Sinne ≈ the way a term refers to an object

Clark Kent and Superman refer to the same person (same Bedeutung).

However, they do so in a very different way (different Sinne)

The nonstandard theorem = the Bedeutung

The Hebrandisation/numerical version = the Sinne

Note that the numerical version is satisfied by infinitely manyterms i , o.

Page 136: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Application III: Frege’s Sinn und bedeuting

Bedeutung ≈ the object to which a term refers.

Sinne ≈ the way a term refers to an object

Clark Kent and Superman refer to the same person (same Bedeutung).

However, they do so in a very different way (different Sinne)

The nonstandard theorem = the Bedeutung

The Hebrandisation/numerical version = the Sinne

Note that the numerical version is satisfied by infinitely manyterms i , o.

Page 137: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Mining standard proofs

Question: Can you also mine proofs not involving NSA?

Answer:Yes, but. . . !

The Ferreira-Gaspar system M (APAL2015) is similar to P butbased on strong majorizability (Bezem-Howard).

System M satisfies Kohlenbach’s non-classical uniformboundedness principles. As a consequence, M believes ‘ε-δ’ andnonstandard definitions are equivalent.

Thus, one can ‘indirectly’ mine proofs from E-PAω + WKL notinvolving NSA inside M.

Warning: Term extraction using M often produces vacuous truths(always for theorems requiring arithmetical comprehesion).

Page 138: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Mining standard proofs

Question: Can you also mine proofs not involving NSA? Answer:Yes, but. . . !

The Ferreira-Gaspar system M (APAL2015) is similar to P butbased on strong majorizability (Bezem-Howard).

System M satisfies Kohlenbach’s non-classical uniformboundedness principles. As a consequence, M believes ‘ε-δ’ andnonstandard definitions are equivalent.

Thus, one can ‘indirectly’ mine proofs from E-PAω + WKL notinvolving NSA inside M.

Warning: Term extraction using M often produces vacuous truths(always for theorems requiring arithmetical comprehesion).

Page 139: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Mining standard proofs

Question: Can you also mine proofs not involving NSA? Answer:Yes, but. . . !

The Ferreira-Gaspar system M (APAL2015) is similar to P butbased on strong majorizability (Bezem-Howard).

System M satisfies Kohlenbach’s non-classical uniformboundedness principles. As a consequence, M believes ‘ε-δ’ andnonstandard definitions are equivalent.

Thus, one can ‘indirectly’ mine proofs from E-PAω + WKL notinvolving NSA inside M.

Warning: Term extraction using M often produces vacuous truths(always for theorems requiring arithmetical comprehesion).

Page 140: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Mining standard proofs

Question: Can you also mine proofs not involving NSA? Answer:Yes, but. . . !

The Ferreira-Gaspar system M (APAL2015) is similar to P butbased on strong majorizability (Bezem-Howard).

System M satisfies Kohlenbach’s non-classical uniformboundedness principles.

As a consequence, M believes ‘ε-δ’ andnonstandard definitions are equivalent.

Thus, one can ‘indirectly’ mine proofs from E-PAω + WKL notinvolving NSA inside M.

Warning: Term extraction using M often produces vacuous truths(always for theorems requiring arithmetical comprehesion).

Page 141: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Mining standard proofs

Question: Can you also mine proofs not involving NSA? Answer:Yes, but. . . !

The Ferreira-Gaspar system M (APAL2015) is similar to P butbased on strong majorizability (Bezem-Howard).

System M satisfies Kohlenbach’s non-classical uniformboundedness principles. As a consequence, M believes ‘ε-δ’ andnonstandard definitions are equivalent.

Thus, one can ‘indirectly’ mine proofs from E-PAω + WKL notinvolving NSA inside M.

Warning: Term extraction using M often produces vacuous truths(always for theorems requiring arithmetical comprehesion).

Page 142: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Mining standard proofs

Question: Can you also mine proofs not involving NSA? Answer:Yes, but. . . !

The Ferreira-Gaspar system M (APAL2015) is similar to P butbased on strong majorizability (Bezem-Howard).

System M satisfies Kohlenbach’s non-classical uniformboundedness principles. As a consequence, M believes ‘ε-δ’ andnonstandard definitions are equivalent.

Thus, one can ‘indirectly’ mine proofs from E-PAω + WKL notinvolving NSA inside M.

Warning: Term extraction using M often produces vacuous truths(always for theorems requiring arithmetical comprehesion).

Page 143: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Mining standard proofs

Question: Can you also mine proofs not involving NSA? Answer:Yes, but. . . !

The Ferreira-Gaspar system M (APAL2015) is similar to P butbased on strong majorizability (Bezem-Howard).

System M satisfies Kohlenbach’s non-classical uniformboundedness principles. As a consequence, M believes ‘ε-δ’ andnonstandard definitions are equivalent.

Thus, one can ‘indirectly’ mine proofs from E-PAω + WKL notinvolving NSA inside M.

Warning: Term extraction using M often produces vacuous truths(always for theorems requiring arithmetical comprehesion).

Page 144: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Impredicative, predicative and . . . locally constructive

The Suslin functional (S2) is the functional version of Π11-CA0:

(∃S2)(∀f 1)[S(f ) = 0↔ (∃g1)(∀n0)(f (gn) = 0)

]. (S2)

The system P + (S2) is impredicative, but its term extractionproduces predicative results (terms from Godel’s T):

If P + (S2) proves (∀stx)(∃sty)ϕ(x , y), then a term t from Godel’s T can

be extracted such that E-PAω + (S2) proves (∀x)(∃y ∈ t(x))ϕ(x , y)

HOWEVER:If P + (S2)st proves (∀stx)(∃sty)ϕ(x , y), then a term t from Godel’s T can

be extracted such that E-PAω + (S2) proves (∀x)(∃y ∈ t(x ,S))ϕ(x , y)

Standard objects in P and H are those which are computationallyrelevant(cf. Berger’s uniform HA and Lifschitz’s calculable numbers)

RM: (S2) is equivalent to ‘all sets are located’. We can replacelocatedness by (S2), while still obtaining computational info!

Page 145: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Impredicative, predicative and . . . locally constructive

The Suslin functional (S2) is the functional version of Π11-CA0:

(∃S2)(∀f 1)[S(f ) = 0↔ (∃g1)(∀n0)(f (gn) = 0)

]. (S2)

The system P + (S2) is impredicative, but its term extractionproduces predicative results (terms from Godel’s T):

If P + (S2) proves (∀stx)(∃sty)ϕ(x , y), then a term t from Godel’s T can

be extracted such that E-PAω + (S2) proves (∀x)(∃y ∈ t(x))ϕ(x , y)

HOWEVER:If P + (S2)st proves (∀stx)(∃sty)ϕ(x , y), then a term t from Godel’s T can

be extracted such that E-PAω + (S2) proves (∀x)(∃y ∈ t(x ,S))ϕ(x , y)

Standard objects in P and H are those which are computationallyrelevant(cf. Berger’s uniform HA and Lifschitz’s calculable numbers)

RM: (S2) is equivalent to ‘all sets are located’. We can replacelocatedness by (S2), while still obtaining computational info!

Page 146: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Impredicative, predicative and . . . locally constructive

The Suslin functional (S2) is the functional version of Π11-CA0:

(∃S2)(∀f 1)[S(f ) = 0↔ (∃g1)(∀n0)(f (gn) = 0)

]. (S2)

The system P + (S2) is impredicative, but its term extractionproduces predicative results (terms from Godel’s T):

If P + (S2) proves (∀stx)(∃sty)ϕ(x , y), then a term t from Godel’s T can

be extracted such that E-PAω + (S2) proves (∀x)(∃y ∈ t(x))ϕ(x , y)

HOWEVER:If P + (S2)st proves (∀stx)(∃sty)ϕ(x , y), then a term t from Godel’s T can

be extracted such that E-PAω + (S2) proves (∀x)(∃y ∈ t(x ,S))ϕ(x , y)

Standard objects in P and H are those which are computationallyrelevant(cf. Berger’s uniform HA and Lifschitz’s calculable numbers)

RM: (S2) is equivalent to ‘all sets are located’. We can replacelocatedness by (S2), while still obtaining computational info!

Page 147: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Impredicative, predicative and . . . locally constructive

The Suslin functional (S2) is the functional version of Π11-CA0:

(∃S2)(∀f 1)[S(f ) = 0↔ (∃g1)(∀n0)(f (gn) = 0)

]. (S2)

The system P + (S2) is impredicative, but its term extractionproduces predicative results (terms from Godel’s T):

If P + (S2) proves (∀stx)(∃sty)ϕ(x , y), then a term t from Godel’s T can

be extracted such that E-PAω + (S2) proves (∀x)(∃y ∈ t(x))ϕ(x , y)

HOWEVER:If P + (S2)st proves (∀stx)(∃sty)ϕ(x , y), then a term t from Godel’s T can

be extracted such that E-PAω + (S2) proves (∀x)(∃y ∈ t(x ,S))ϕ(x , y)

Standard objects in P and H are those which are computationallyrelevant(cf. Berger’s uniform HA and Lifschitz’s calculable numbers)

RM: (S2) is equivalent to ‘all sets are located’. We can replacelocatedness by (S2), while still obtaining computational info!

Page 148: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Impredicative, predicative and . . . locally constructive

The Suslin functional (S2) is the functional version of Π11-CA0:

(∃S2)(∀f 1)[S(f ) = 0↔ (∃g1)(∀n0)(f (gn) = 0)

]. (S2)

The system P + (S2) is impredicative, but its term extractionproduces predicative results (terms from Godel’s T):

If P + (S2) proves (∀stx)(∃sty)ϕ(x , y), then a term t from Godel’s T can

be extracted such that E-PAω + (S2) proves (∀x)(∃y ∈ t(x))ϕ(x , y)

HOWEVER:If P + (S2)st proves (∀stx)(∃sty)ϕ(x , y), then a term t from Godel’s T can

be extracted such that E-PAω + (S2) proves (∀x)(∃y ∈ t(x ,S))ϕ(x , y)

Standard objects in P and H are those which are computationallyrelevant(cf. Berger’s uniform HA and Lifschitz’s calculable numbers)

RM: (S2) is equivalent to ‘all sets are located’. We can replacelocatedness by (S2), while still obtaining computational info!

Page 149: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Impredicative, predicative and . . . locally constructive

The Suslin functional (S2) is the functional version of Π11-CA0:

(∃S2)(∀f 1)[S(f ) = 0↔ (∃g1)(∀n0)(f (gn) = 0)

]. (S2)

The system P + (S2) is impredicative, but its term extractionproduces predicative results (terms from Godel’s T):

If P + (S2) proves (∀stx)(∃sty)ϕ(x , y), then a term t from Godel’s T can

be extracted such that E-PAω + (S2) proves (∀x)(∃y ∈ t(x))ϕ(x , y)

HOWEVER:If P + (S2)st proves (∀stx)(∃sty)ϕ(x , y), then a term t from Godel’s T can

be extracted such that E-PAω + (S2) proves (∀x)(∃y ∈ t(x ,S))ϕ(x , y)

Standard objects in P and H are those which are computationallyrelevant

(cf. Berger’s uniform HA and Lifschitz’s calculable numbers)

RM: (S2) is equivalent to ‘all sets are located’. We can replacelocatedness by (S2), while still obtaining computational info!

Page 150: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Impredicative, predicative and . . . locally constructive

The Suslin functional (S2) is the functional version of Π11-CA0:

(∃S2)(∀f 1)[S(f ) = 0↔ (∃g1)(∀n0)(f (gn) = 0)

]. (S2)

The system P + (S2) is impredicative, but its term extractionproduces predicative results (terms from Godel’s T):

If P + (S2) proves (∀stx)(∃sty)ϕ(x , y), then a term t from Godel’s T can

be extracted such that E-PAω + (S2) proves (∀x)(∃y ∈ t(x))ϕ(x , y)

HOWEVER:If P + (S2)st proves (∀stx)(∃sty)ϕ(x , y), then a term t from Godel’s T can

be extracted such that E-PAω + (S2) proves (∀x)(∃y ∈ t(x ,S))ϕ(x , y)

Standard objects in P and H are those which are computationallyrelevant(cf. Berger’s uniform HA and Lifschitz’s calculable numbers)

RM: (S2) is equivalent to ‘all sets are located’. We can replacelocatedness by (S2), while still obtaining computational info!

Page 151: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Impredicative, predicative and . . . locally constructive

The Suslin functional (S2) is the functional version of Π11-CA0:

(∃S2)(∀f 1)[S(f ) = 0↔ (∃g1)(∀n0)(f (gn) = 0)

]. (S2)

The system P + (S2) is impredicative, but its term extractionproduces predicative results (terms from Godel’s T):

If P + (S2) proves (∀stx)(∃sty)ϕ(x , y), then a term t from Godel’s T can

be extracted such that E-PAω + (S2) proves (∀x)(∃y ∈ t(x))ϕ(x , y)

HOWEVER:If P + (S2)st proves (∀stx)(∃sty)ϕ(x , y), then a term t from Godel’s T can

be extracted such that E-PAω + (S2) proves (∀x)(∃y ∈ t(x ,S))ϕ(x , y)

Standard objects in P and H are those which are computationallyrelevant(cf. Berger’s uniform HA and Lifschitz’s calculable numbers)

RM: (S2) is equivalent to ‘all sets are located’.

We can replacelocatedness by (S2), while still obtaining computational info!

Page 152: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Impredicative, predicative and . . . locally constructive

The Suslin functional (S2) is the functional version of Π11-CA0:

(∃S2)(∀f 1)[S(f ) = 0↔ (∃g1)(∀n0)(f (gn) = 0)

]. (S2)

The system P + (S2) is impredicative, but its term extractionproduces predicative results (terms from Godel’s T):

If P + (S2) proves (∀stx)(∃sty)ϕ(x , y), then a term t from Godel’s T can

be extracted such that E-PAω + (S2) proves (∀x)(∃y ∈ t(x))ϕ(x , y)

HOWEVER:If P + (S2)st proves (∀stx)(∃sty)ϕ(x , y), then a term t from Godel’s T can

be extracted such that E-PAω + (S2) proves (∀x)(∃y ∈ t(x ,S))ϕ(x , y)

Standard objects in P and H are those which are computationallyrelevant(cf. Berger’s uniform HA and Lifschitz’s calculable numbers)

RM: (S2) is equivalent to ‘all sets are located’. We can replacelocatedness by (S2), while still obtaining computational info!

Page 153: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Final Thoughts

The two eyes of exact science are mathematics and logic, the

mathematical sect puts out the logical eye, the logical sect puts out the

mathematical eye; each believing that it sees better with one eye than

with two.

Augustus De Morgan

‘. . . there are good reasons to believe that nonstandard analysis, insome version or other, will be the analysis of the future.’

Kurt Godel

We thank the John Templeton Foundation and Alexander VonHumboldt Foundation for their generous support!

Thank you for your attention!Any questions?

Page 154: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Final Thoughts

The two eyes of exact science are mathematics and logic, the

mathematical sect puts out the logical eye, the logical sect puts out the

mathematical eye; each believing that it sees better with one eye than

with two.

Augustus De Morgan

‘. . . there are good reasons to believe that nonstandard analysis, insome version or other, will be the analysis of the future.’

Kurt Godel

We thank the John Templeton Foundation and Alexander VonHumboldt Foundation for their generous support!

Thank you for your attention!Any questions?

Page 155: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Final Thoughts

The two eyes of exact science are mathematics and logic, the

mathematical sect puts out the logical eye, the logical sect puts out the

mathematical eye; each believing that it sees better with one eye than

with two.

Augustus De Morgan

‘. . . there are good reasons to believe that nonstandard analysis, insome version or other, will be the analysis of the future.’

Kurt Godel

We thank the John Templeton Foundation and Alexander VonHumboldt Foundation for their generous support!

Thank you for your attention!Any questions?

Page 156: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Final Thoughts

The two eyes of exact science are mathematics and logic, the

mathematical sect puts out the logical eye, the logical sect puts out the

mathematical eye; each believing that it sees better with one eye than

with two.

Augustus De Morgan

‘. . . there are good reasons to believe that nonstandard analysis, insome version or other, will be the analysis of the future.’

Kurt Godel

We thank the John Templeton Foundation and Alexander VonHumboldt Foundation for their generous support!

Thank you for your attention!Any questions?

Page 157: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Final Thoughts

The two eyes of exact science are mathematics and logic, the

mathematical sect puts out the logical eye, the logical sect puts out the

mathematical eye; each believing that it sees better with one eye than

with two.

Augustus De Morgan

‘. . . there are good reasons to believe that nonstandard analysis, insome version or other, will be the analysis of the future.’

Kurt Godel

We thank the John Templeton Foundation and Alexander VonHumboldt Foundation for their generous support!

Thank you for your attention!

Any questions?

Page 158: Nonstandard Analysis as a computational foundation · Nonstandard Analysis as a computational foundation Sam Sanders ... Nonstandard Analysis can be mined to producee ectivetheorems

Introduction: NSA 101 Mining NSA Some foundational applications

Final Thoughts

The two eyes of exact science are mathematics and logic, the

mathematical sect puts out the logical eye, the logical sect puts out the

mathematical eye; each believing that it sees better with one eye than

with two.

Augustus De Morgan

‘. . . there are good reasons to believe that nonstandard analysis, insome version or other, will be the analysis of the future.’

Kurt Godel

We thank the John Templeton Foundation and Alexander VonHumboldt Foundation for their generous support!

Thank you for your attention!Any questions?


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