1
Challenges in
quantum algorithms for
integer factorization
D. J. Bernstein
University of Illinois at Chicago
Prelude: What is the fastest
algorithm to sort an array?
def blindsort(x):
while not issorted(x):
permuterandomly(x)
2
def bubblesort(x):
for j in range(len(x)):
for i in reversed(range(j)):
x[i],x[i+1] = (
min(x[i],x[i+1]),
max(x[i],x[i+1])
)
bubblesort takes poly time.
Θ(n2) comparisons.
Huge speedup over blindsort!
Is this the end of the story?
2
def bubblesort(x):
for j in range(len(x)):
for i in reversed(range(j)):
x[i],x[i+1] = (
min(x[i],x[i+1]),
max(x[i],x[i+1])
)
bubblesort takes poly time.
Θ(n2) comparisons.
Huge speedup over blindsort!
Is this the end of the story?
No, still not optimal.
3
Analogous: What is the fastest
algorithm to factor integers?
Shor’s algorithm takes poly time.
Huge speedup over NFS!
b2(log b)1+o(1) qubit operations
to factor b-bit integer,
using standard subroutines
for fast integer arithmetic.
Is this the end of the story?
3
Analogous: What is the fastest
algorithm to factor integers?
Shor’s algorithm takes poly time.
Huge speedup over NFS!
b2(log b)1+o(1) qubit operations
to factor b-bit integer,
using standard subroutines
for fast integer arithmetic.
Is this the end of the story?
No, still not optimal.
“Shor’s algorithm: the bubble sort
of integer factorization.”
4
A simple exercise to illustrate
suboptimality of Shor’s algorithm:
Find a prime divisor of¨103009ı
˝.
3141592653589793238462643383279502884197169399375105820974944592307816406286208998628034825342117067982148086513282306647093844609550582231725359408128481117450284102701938521105559644622948954930381964428810975665933446128475648233786783165271201909145648566923460348610454326648213393607260249141273724587006606315588174881520920962829254091715364367892590360011330530548820466521384146951941511609433057270365759591953092186117381932611793105118548074462379962749567351885752724891227938183011949129833673362440656643086021394946395224737190702179860943702770539217176293176752384674818467669405132000568127145263560827785771342757789609173637178721468440901224953430146549585371050792279689258923542019956112129021960864034418159813629774771309960518707211349999998372978049951059731732816096318595024459455346908302642522308253344685035261931188171010003137838752886587533208381420617177669147303598253490428755468731159562863882353787593751957781857780532171226806613001927876611195909216420198938095257201065485863278865936153381827968230301952035301852968995773622599413891249721775283479131515574857242454150695950829533116861727855889075098381754637464939319255060400927701671139009848824012858361603563707660104710181942955596198946767837449448255379774726847104047534646208046684259069491293313677028989152104752162056966024058038150193511253382430035587640247496473263914199272604269922796782354781636009341721641219924586315030286182974555706749838505494588586926995690927210797509302955321165344987202755960236480665499119881834797753566369807426542527862551818417574672890977772793800081647060016145249192173217214772350141441973568548161361157352552133475741849468438523323907394143334547762416862518983569485562099219222184272550254256887671790494601653466804988627232791786085784383827967976681454100953883786360950680064225125205117392984896084128488626945604241965285022210661186306744278622039194945047123713786960956364371917287467764657573962413890865832645995813390478027590099465764078951269468398352595709825822620522489407726719478268482601476990902640136394437455305068203496252451749399651431429809190659250937221696461515709858387410597885959772975498930161753928468138268683868942774155991855925245953959431049972524680845987273644695848653836736222626099124608051243884390451244136549762780797715691435997700129616089441694868555848406353422072225828488648158456028506016842739452267467678895252138522549954666727823986456596116354886230577456498035593634568174324112515076069479451096596094025228879710893145669136867228748940560101503308617928680920874760917824938589009714909675985261365549781893129784821682998948722658804857564014270477555132379641451523746234364542858444795265867821051141354735739523113427166102135969536231442952484937187110145765403590279934403742007310578539062198387447808478489683321445713868751943506430218453191048481005370614680674919278191197939952061419663428754440643745123718192179998391015919561814675142691239748940907186494231961567945208
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Important variations in the
factorization problem:
• Maybe need one factor.• Maybe need all factors.• Maybe factors are small.• Maybe factors are large.• Maybe there are many inputs.• Maybe inputs in superposition.
Important variations in metrics
(even assuming perfect devices):
• Qubits.• Area (“A”, including wire area).• Qubit operations (“gates”).• Depth.• Time (“T”: latency).
6
Short-term RSA security
1995 Kitaev, 1996 Vedral–
Barenco–Ekert, 1996 Beckman–
Chari–Devabhaktuni–Preskill,
1998 Zalka, 1999 Mosca–Ekert,
2000 Parker–Plenio, 2001 Seifert,
2002 Kitaev–Shen–Vyalyi, 2003
Beauregard, 2006 Takahashi–
Kunihiro, 2010 Ahmadi–Chiang,
2014 Svore–Hastings–Freedman,
2015 Grosshans–Lawson–Morain–
Smith, 2016 Häner–Roetteler–
Svore, 2017 Eker̊a–Håstad, 2017
Johnston: try to squeeze constant
factors out of Shor’s algorithm.
7
2003 Beauregard: 2b + 3 qubits.
: : : 2016 Häner–Roetteler–Svore:
2b + 2 qubits; 64b3(lg b + O(1))
Toffoli gates; similar number of
CNOT gates; depth O(b3).
7
2003 Beauregard: 2b + 3 qubits.
: : : 2016 Häner–Roetteler–Svore:
2b + 2 qubits; 64b3(lg b + O(1))
Toffoli gates; similar number of
CNOT gates; depth O(b3).
Conventional wisdom:
cannot avoid 2b qubits
for controlled mulmod.
e.g. 4096 qubits for b = 2048,
very common RSA key size.
So 2048-bit factorization
needs 4096 qubits?
7
2003 Beauregard: 2b + 3 qubits.
: : : 2016 Häner–Roetteler–Svore:
2b + 2 qubits; 64b3(lg b + O(1))
Toffoli gates; similar number of
CNOT gates; depth O(b3).
Conventional wisdom:
cannot avoid 2b qubits
for controlled mulmod.
e.g. 4096 qubits for b = 2048,
very common RSA key size.
So 2048-bit factorization
needs 4096 qubits?
No: NFS uses 0 qubits.
8
NFS takes Lp+o(1) operations
with p =3p
92 + 26√
13=3 > 1:9,
log L = (log 2b)1=3(log log 2b)2=3.
Analysis for b = 2048 (not easy!):
very roughly 2112 operations.
8
NFS takes Lp+o(1) operations
with p =3p
92 + 26√
13=3 > 1:9,
log L = (log 2b)1=3(log log 2b)2=3.
Analysis for b = 2048 (not easy!):
very roughly 2112 operations.
2017 Bernstein–Biasse–Mosca:
Lq+o(1) operations
with q = 3p
8=3 ≈ 1:387,using b2=3+o(1) qubits
(and many non-quantum bits).
8
NFS takes Lp+o(1) operations
with p =3p
92 + 26√
13=3 > 1:9,
log L = (log 2b)1=3(log log 2b)2=3.
Analysis for b = 2048 (not easy!):
very roughly 2112 operations.
2017 Bernstein–Biasse–Mosca:
Lq+o(1) operations
with q = 3p
8=3 ≈ 1:387,using b2=3+o(1) qubits
(and many non-quantum bits).
Open: Analyze for b = 2048.
Fewer than 4096 qubits?
Fewer than 2048 qubits?
9
Counting operations is an
oversimplified cost model: ignores
communication costs, parallelism.
See, e.g., 1981 Brent–Kung AT
theorem for realistic chip model.
9
Counting operations is an
oversimplified cost model: ignores
communication costs, parallelism.
See, e.g., 1981 Brent–Kung AT
theorem for realistic chip model.
NFS suffers somewhat from
communication costs inside
big linear-algebra subroutine.
2001 Bernstein:
AT = Lp′+o(1) with p′ ≈ 1:976.
2017 Bernstein–Biasse–Mosca:
AT = Lq′+o(1) with q′ ≈ 1:456
using b2=3+o(1) qubits.
Open: Analyze for b = 2048.
10
Actually have many inputs.
Lower cost for some output?
Lower cost for many outputs?
10
Actually have many inputs.
Lower cost for some output?
Lower cost for many outputs?
1993 Coppersmith:
L1:638:::+o(1) operations
after precomp(b) involving
L2:006:::+o(1) operations.
10
Actually have many inputs.
Lower cost for some output?
Lower cost for many outputs?
1993 Coppersmith:
L1:638:::+o(1) operations
after precomp(b) involving
L2:006:::+o(1) operations.
2014 Bernstein–Lange:
AT = L2:204:::+o(1)
to factor L0:5+o(1) inputs;
L1:704:::+o(1) per input.
10
Actually have many inputs.
Lower cost for some output?
Lower cost for many outputs?
1993 Coppersmith:
L1:638:::+o(1) operations
after precomp(b) involving
L2:006:::+o(1) operations.
2014 Bernstein–Lange:
AT = L2:204:::+o(1)
to factor L0:5+o(1) inputs;
L1:704:::+o(1) per input.
Open: Any quantum speedups
for factoring many integers?
11
Long-term RSA security
Long history of advances
in integer factorization.
Long history of RSA users
switching to larger key sizes,
not far beyond broken sizes.
11
Long-term RSA security
Long history of advances
in integer factorization.
Long history of RSA users
switching to larger key sizes,
not far beyond broken sizes.
“Expert” cryptographers:
“Obviously they won’t react to
Shor’s algorithm this way! They’ll
switch to codes, lattices, etc. long
before quantum computers break
RSA-2048! We don’t need to
analyze the security of RSA-4096,
RSA-8192, RSA-16384, etc.!”
12
We consider possible impact of
quantum computers. Shouldn’t
we also consider possible impact
of users wanting to stick to RSA?
12
We consider possible impact of
quantum computers. Shouldn’t
we also consider possible impact
of users wanting to stick to RSA?
2017 Bernstein–Heninger–Lou–
Valenta “Post-quantum RSA”
(pqRSA): Generated 1-terabyte
RSA key; 2000000 core-hours.
Shor’s algorithm: >2100 gates.
12
We consider possible impact of
quantum computers. Shouldn’t
we also consider possible impact
of users wanting to stick to RSA?
2017 Bernstein–Heninger–Lou–
Valenta “Post-quantum RSA”
(pqRSA): Generated 1-terabyte
RSA key; 2000000 core-hours.
Shor’s algorithm: >2100 gates.
Bernstein–Fried–Heninger–Lou–
Valenta: Draft NIST submission
proposing 1-gigabyte RSA keys.
Much faster to generate.
13
The secret primes are small:
4096 bits in terabyte key;
1024 bits in gigabyte key.
Important time-saver in
keygen, signing, decryption.
Is this a weakness?
ECM finds any prime
14
Analysis for y ≈ 21024:>2125 mulmods, huge depth;
and 233-bit mulmod is slow.
223 target primes, but
finding just one isn’t enough.
14
Analysis for y ≈ 21024:>2125 mulmods, huge depth;
and 233-bit mulmod is slow.
223 target primes, but
finding just one isn’t enough.
2017 Bernstein–Heninger–Lou–
Valenta: Grover+ECM
finds any prime
14
Analysis for y ≈ 21024:>2125 mulmods, huge depth;
and 233-bit mulmod is slow.
223 target primes, but
finding just one isn’t enough.
2017 Bernstein–Heninger–Lou–
Valenta: Grover+ECM
finds any prime
15
Minimum security level that
NIST allows for post-quantum
submissions: brute-force/Grover
search for a 128-bit AES key.
Is a gigabyte key so difficult for
Shor’s algorithm to break?
15
Minimum security level that
NIST allows for post-quantum
submissions: brute-force/Grover
search for a 128-bit AES key.
Is a gigabyte key so difficult for
Shor’s algorithm to break?
64b3 lg b ≈ 2110 for b = 233.
Not totally implausible to argue
that Grover’s algorithm could
break AES-128 faster than this.
15
Minimum security level that
NIST allows for post-quantum
submissions: brute-force/Grover
search for a 128-bit AES key.
Is a gigabyte key so difficult for
Shor’s algorithm to break?
64b3 lg b ≈ 2110 for b = 233.
Not totally implausible to argue
that Grover’s algorithm could
break AES-128 faster than this.
But Shor’s algorithm can (with
more qubits) use faster mulmods.
16
NIST allows submissions to
assume reasonable time limits:
“Plausible values for MAXDEPTH
range from 240 logical gates (the
approximate number of gates that
presently envisioned quantum
computing architectures are
expected to serially perform in
a year) through 264 logical gates
(the approximate number of gates
that current classical computing
architectures can perform serially
in a decade), to no more than 296
logical gates : : : ”
17
What is the minimum time
for b-bit integer multiplication?
Light takes time Ω(b1=2)
to cross a b1=2 × b1=2 chip.
1981 Brent–Kung AT theorem:
AT ≥ small constant · b3=2,even if wire latency is 0.
(Work around obstacles using
faster-than-light communication
through long-distance EPR pairs?
Haven’t seen plausible designs,
even if reversible computation
avoids FTL impossibility proofs.)
18
What is the minimum time
for Shor’s algorithm?
Main bottleneck: ae mod N
for 2b-bit superposition e.
Traditional approach: series of
controlled multiplications by
a and 1=a mod N;
a2 mod N and 1=a2 mod N;
a4 mod N and 1=a4 mod N; etc.
Can multiply these in parallel,
using many more qubits;
but hard to parallelize initial
computation of a2i
mod N.
19
Why gigabyte keys are reasonable:
big enough to push latency
beyond the 264 limit,
under reasonable assumptions.
Gigabyte inputs are
millions of times larger
than 2048-bit inputs.
These algorithms will take
billions of times longer.
More cost to find all primes.
19
Why gigabyte keys are reasonable:
big enough to push latency
beyond the 264 limit,
under reasonable assumptions.
Gigabyte inputs are
millions of times larger
than 2048-bit inputs.
These algorithms will take
billions of times longer.
More cost to find all primes.
Open: What is minimum time
for integer factorization?
20
NIST’s middle security level
is defined by an AES-192 key.
20
NIST’s middle security level
is defined by an AES-192 key.
With maximum depth 264,
finding an AES-192 key
requires ≈2144 cores.
20
NIST’s middle security level
is defined by an AES-192 key.
With maximum depth 264,
finding an AES-192 key
requires ≈2144 cores.
This is nonsense! There is
not enough time to broadcast
the input to 2144 parallel
computations, and not enough
time to collect the results.
20
NIST’s middle security level
is defined by an AES-192 key.
With maximum depth 264,
finding an AES-192 key
requires ≈2144 cores.
This is nonsense! There is
not enough time to broadcast
the input to 2144 parallel
computations, and not enough
time to collect the results.
Is NIST implicitly assuming
a higher latency limit?
21
Some improvements to Shor
(2017 Bernstein–Biasse–Mosca)
Consider Shor’s algorithm
factoring N = pe11 · · · p
eff . Write
(pj −1)pej−1j as 2
tj uj with uj odd.
Unit group is isomorphic to
Z=2t1 × · · · × Z=2tf × Z=u1 × · · ·.
21
Some improvements to Shor
(2017 Bernstein–Biasse–Mosca)
Consider Shor’s algorithm
factoring N = pe11 · · · p
eff . Write
(pj −1)pej−1j as 2
tj uj with uj odd.
Unit group is isomorphic to
Z=2t1 × · · · × Z=2tf × Z=u1 × · · ·.
Shor’s algorithm (hopefully)
computes order r of random unit.
Order 2cj in Z=2tj is
2tj with probability 1=2;
2tj−1 with probability 1=4; etc.
22
Shor computes gcd{N; ar=2 − 1}.Divisible by pj exactly when
cj < max{c1; : : : ; cf }.
Factorization fails iff all cj are
equal. Chance ≤1=2f−1.
22
Shor computes gcd{N; ar=2 − 1}.Divisible by pj exactly when
cj < max{c1; : : : ; cf }.
Factorization fails iff all cj are
equal. Chance ≤1=2f−1.
More subtle problem:
Factorization is likely to
split off some of the
primes with maximum tj .
Can iterate Shor’s algorithm
enough times to completely
factor. Many full-size iterations;
many more for adversarial inputs.
23
Better method, inspired by
primality testing: compute gcd
with ar=2 + 1, ar=4 + 1, ar=8 + 1,
: : : , ad + 1, ad − 1, with odd d .
This splits pj according to cj .
Any two primes have chance
≥1=2 of being split.
Factors are around half size.
Much less overhead for recursion.
Also “parallel construction”:
Run several times in parallel,
giving several factorizations.
Then factor into coprimes.
24
These methods use >b qubits.
Didn’t we claim b2=3+o(1) qubits?
We actually use Grover’s method
to search for smooth b2=3+o(1)-bit
numbers in NFS.
Oracle for Grover’s method:
factor thoroughly enough
to recognize smooth inputs.
We tweak (improved) Shor to
work in superposition. Careful
with qubit budget for continued
fractions, power detection, etc.
25
A different way to improve
randomness of factorizations in
Shor’s algorithm: replace group
(Z=N)∗ with E(Z=N)
for a random elliptic curve E.
25
A different way to improve
randomness of factorizations in
Shor’s algorithm: replace group
(Z=N)∗ with E(Z=N)
for a random elliptic curve E.
Gal Dor suggests unifying
Grover+ECM with Shor: e.g.,
compute esP on E(Z=N) where
e is superposition of scalars,
s is smooth scalar,
E is superposition of curves.
25
A different way to improve
randomness of factorizations in
Shor’s algorithm: replace group
(Z=N)∗ with E(Z=N)
for a random elliptic curve E.
Gal Dor suggests unifying
Grover+ECM with Shor: e.g.,
compute esP on E(Z=N) where
e is superposition of scalars,
s is smooth scalar,
E is superposition of curves.
Open: What are minimum costs
for this unification?
