Vertical Versus Horizontal Poincare Inequalities
Assaf Naor
Courant Institute
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Bi-Lipschitz distortion
a metric space and a Banach space.
the infimum over those for which there exists satisfying
(M;dM) (X;k ¢ kX)
cX(M) = D 2 (1;1]
f :M !X
MD,¡!X:
8 x; y 2M; dM(x; y) 6 kf(x)¡ f(y)kX 6DdM(x; y):
The discrete Heisenberg group
• The group generated by subject to the relation stating that the commutator of is in the center:
where
H a; ba; b
ac= ca and bc= cb
c = [a; b] = aba¡1b¡1
Concretely,
H =
8<:
0@1 x z
0 1 y
0 0 1
1A : x; y; z 2 Z
9=;
a =
0@1 1 0
0 1 0
0 0 1
1A and b =
0@1 0 0
0 1 1
0 0 1
1A
c =
0@1 0 1
0 1 0
0 0 1
1A
The left-invariant word metric on corresponding to the generating set is denoted .
fa; a¡1; b; b¡1gH
dW
Uniform convexity
The modulus of uniform convexity of :
±X(²) = inf
½1¡
°°°°x+ y
2
°°°°X
: kxkX = kykX = 1; kx¡ ykX = ²
¾(X;k ¢ kX)
PnX
i=1
Pn
i=1bkblblRR 10f(x)dx
Pn
i=1
Pn
i=1
Pn
i=1
x
y0
x+y
2
²
1¡°°x¡y
2
°°X¸ ±X(²)
• X is uniformly convex if
• For , X is q-convex if it admits an equivalent norm with respect to which
Theorem (Pisier, 1975). If X is uniformly convex then it is q-convex for some .
is -convex for .
8 ² 2 (0;1); ±X(²) > 0:
q 2 [2;1)
±X(²) & ²q:
q 2 [2;1)
`p maxf2; pg p > 1
Mostow (1973), Pansu (1989), Semmes (1996)
Theorem. The metric space does not admit a bi-Lipschitz embedding into for any .
(H; dW )
Rn n 2 N
Assouad’s embedding theorem (1983)
• A metric space is K-doubling if any ball can be covered by K-balls of half its radius.
(M;dM)
Assouad’s embedding theorem (1983)
• A metric space is K-doubling if any ball can be covered by K-balls of half its radius.
(M;dM)
Assouad’s embedding theorem (1983)
• A metric space is K-doubling if any ball can be covered by K-balls of half its radius.
(M;dM)
Assouad’s embedding theorem (1983)
• A metric space is K-doubling if any ball can be covered by K-balls of half its radius.
(M;dM)
Assouad’s embedding theorem (1983)
• A metric space is K-doubling if any ball can be covered by K-balls of half its radius.
(M;dM)
Assouad’s embedding theorem (1983)
• A metric space is K-doubling if any ball can be covered by K-balls of half its radius.
(M;dM)
Assouad’s embedding theorem (1983)
• A metric space is K-doubling if any ball can be covered by K-balls of half its radius.
(M;dM)
Assouad’s embedding theorem (1983)
• A metric space is K-doubling if any ball can be covered by K-balls of half its radius.
(M;dM)
Assouad’s embedding theorem (1983)
• A metric space is K-doubling if any ball can be covered by K-balls of half its radius.
(M;dM)
Assouad’s embedding theorem (1983)
• A metric space is K-doubling if any ball can be covered by K-balls of half its radius.
(M;dM)
Assouad’s embedding theorem (1983)
• A metric space is K-doubling if any ball can be covered by K-balls of half its radius.
(M;dM)
Assouad’s embedding theorem (1983)
• A metric space is K-doubling if any ball can be covered by K-balls of half its radius.
(M;dM)
Assouad’s embedding theorem (1983)
• A metric space is K-doubling if any ball can be covered by K-balls of half its radius.
(M;dM)
Assouad’s embedding theorem (1983)
• A metric space is K-doubling if any ball can be covered by K-balls of half its radius.
(M;dM)
Assouad’s embedding theorem (1983)
• A metric space is K-doubling if any ball can be covered by K-balls of half its radius.
(M;dM)
Assouad’s embedding theorem (1983)
• A metric space is K-doubling if any ball can be covered by K-balls of half its radius.
(M;dM)
Assouad’s embedding theorem
• A metric space is K-doubling if any ball can be covered by K-balls of half its radius.
(M;dM)
Assouad’s embedding theorem
• A metric space is K-doubling if any ball can be covered by K-balls of half its radius.
(M;dM)
Assouad’s embedding theorem (1983)
• A metric space is K-doubling if any ball can be covered by K-balls of half its radius.
(M;dM)
Theorem (Assouad, 1983). Suppose that is K-doubling and . Then
Theorem (N.-Neiman, 2010). In fact
David-Snipes, 2013: Simpler deterministic proof.
(M;dM)
² 2 (0;1)
(M;d1¡²M )D(K;²),¡¡¡¡! RN(K;²):
(M;d1¡²M )D(K;²),¡¡¡¡! RN(K):
Obvious question: Why do we need to raise the metric to the power ?
1¡ ²
(M;d1¡²M )D(K;²),¡¡¡¡! RN(K;²):
Obvious question: Why do we need to raise the metric to the power ?
Since in we have
the metric space is O(1)-doubling.
By Mostow-Pansu-Semmes,
1¡ ²
(M;d1¡²M )D(K;²),¡¡¡¡! RN(K;²):
8m 2 N; jBmj ³m4;(H; dW )
(H; dW )
(H; dW) 6,! RN :
Proof of non-embeddability into
By a limiting argument and a non-commutative variant of Rademacher’s theorem on the almost-everywhere differentiability of Lipschitz functions (Pansu differentiation) we have the statement
“If the Heisenberg group embeds bi-Lipschitzly into then it also embeds into via a bi-Lipschitz mapping that is a group homomorphism.”
A non-Abelian group cannot be isomorphic to a subgroup of an Abelian group!
Rn
Rn Rn
Heisenberg non-embeddability
• Mostow-Pansu-Semmes (1996).
• Cheeger (1999).
• Pauls (2001).
• Lee-N. (2006).
• Cheeger-Kleiner (2006).
• Cheeger-Kleiner (2007).
• Cheeger-Kleiner (2008).
• Cheeger-Kleiner-N. (2009).
• Austin-N.-Tessera (2010).
• Li (2013).
Heisenberg non-embeddability
• Mostow-Pansu-Semmes (1996).
• Cheeger (1999).
• Pauls (2001).
• Lee-N. (2006).
• Cheeger-Kleiner (2006).
• Cheeger-Kleiner (2007).
• Cheeger-Kleiner (2008).
• Cheeger-Kleiner-N. (2009).
• Austin-N.-Tessera (2010).
• Li (2013).
H does not embed into
any uniformly convex space:
Heisenberg non-embeddability
• Mostow-Pansu-Semmes (1996).
• Cheeger (1999).
• Pauls (2001).
• Lee-N. (2006).
• Cheeger-Kleiner (2006).
• Cheeger-Kleiner (2007).
• Cheeger-Kleiner (2008).
• Cheeger-Kleiner-N. (2009).
• Austin-N.-Tessera (2010).
• Li (2013).
[ANT (2010)]: Hilbertian case
A limiting argument combined with [Aharoni-Maurey-Mityagin (1985), Gromov (2007)] shows that it suffices to treat embeddings that are 1-cocycles associated to an action by affine isometries. By [Guichardet (1972)] it further suffices to deal with coboundaries. This is treated by examining each irreducible representation separately.
c`2(Bn; dW) ³plogn:
[ANT (2010)]: q-convex case, continued
Qualitative statement: There is no bi-Lipschitz embedding of the Heisenberg group into an ergodic Banach space X via a 1-cocycle associated to an action by affine isometries.
X is ergodic if for every linear isometry and every the sequence
converges in norm.
T :X!Xx 2X
1
n
n¡1X
j=1
T jx
[ANT (2010)]: q-convex case, continued
N.-Peres (2010): In the case of q-convex spaces, it suffices to treat 1-cocycle associated to an affine action by affine isometries.
For combining this step with the use of ergodicity, uniform convexity is needed, because by [Brunel-Sucheston (1972)], ultrapowers of X are ergodic if and only if X admits an equivalent uniformly convex norm.
[ANT (2010)]: q-convex case, continued
Conclusion of proof uses algebraic properties of cocycles combined with rates of convergence for the mean ergodic theorem in q-convex spaces.
Li (2013): A quantitative version of Pansu’s differentiation theorem. Suboptimal bounds.
Almost matching embeddability
Assouad (1983): If a metric space is O(1)-doubling then there exists and 1-Lipschitz functions such that for ,
(M;dM)
k 2 N©Áj :M ! Rk
ªj2Z x; y 2M
dM(x; y) 2 [2j¡1;2j] =) kÁj(x)¡Áj(y)k2 & dM(x; y):
Almost matching embeddability
Assouad (1983): If a metric space is O(1)-doubling then there exists and 1-Lipschitz functions such that for ,
So, define by
For the bi-Lipschitz distortion of f is of order
(M;dM)
k 2 N©Áj :M ! Rk
ªj2Z x; y 2M
dM(x; y) 2 [2j¡1;2j] =) kÁj(x)¡Áj(y)k2 & dM(x; y):
f : Bn !O(logn)M
j=1
Rk f(x) =
O(logn)M
j=1
Áj(x):
p 2 [2;1)
(logn)1=p:
Lafforgue-N., 2012
Theorem. For every q-convex space every and every ,
(X;k ¢ kX);n 2 Nf : H!X
n2X
k=1
X
x2Bn
kf(xck)¡ f(x)kqXk1+q=2
.XX
x2B21n
¡kf(xa)¡ f(x)kqX + kf(xb)¡ f(x)kqX
¢:
The proof of this inequality relies on real-variable Fourier analytic methods. Specifically, a vector-valued Littlewood-Paley-Stein inequality due to Martinez, Torrea and Xu (2006), combined with a geometric argument.
For embeddings into one can use the classical Littlewood-Paley inequality instead.
`p
Sharp non-embeddability
If
and
8x; y 2B22n; dW(x; y) 6 kf(x)¡ f(y)kX 6DdW(x; y);
X
x2B21n
¡kf(xa)¡ f(x)kqX + kf(xb)¡ f(x)kqX
¢
. DqjB21nj ³ Dqn4;
n2X
k=1
X
x2Bn
kf(xck)¡ f(x)kqXk1+q=2
>n2X
k=1
X
x2Bn
dW (xck; x)q
k1+q=2
&n2X
k=1
X
x2Bn
kq=2
k1+q=2³ jBnj logn ³ n4 log n:
so,
n2X
k=1
X
x2Bn
kf(xck)¡ f(x)kqXk1+q=2
.XX
x2B21n
¡kf(xa)¡ f(x)kqX + kf(xb)¡ f(x)kqX
¢;
n4 logn.X Dqn4 =) D &X (logn)1=q:
cX(Bn; dW) &X (logn)1=q:
Sharp distortion computation
p 2 (1;2] =) c`p (Bn; dW ) ³pplogn:
p 2 [2;1) =) c`p (Bn; dW) ³p (logn)1=p:
The Sparsest Cut Problem
Input: Two symmetric functions
Goal: Compute (or estimate) in polynomial time the quantity
C;D : f1; : : : ; ng£f1; : : : ; ng ! [0;1):
©¤(C;D) = min;6=S(f1;:::;ng
Pn
i;j=1C(i; j)j1S(i)¡ 1S(j)jPn
i;j=1D(i; j)j1S(i)¡ 1S(j)j:
The Goemans-Linial Semidefinite Program
The best known algorithm for the Sparsest Cut Problem is a continuous relaxation called the Goemans-Linial SDP (~1997).
Theorem (Arora, Lee, N., 2005). The Goemans-Linial SDP outputs a number that is guaranteed to be within a factor of
of
(logn)12+o(1)
©¤(C;D):
Minimize
over all ,
subject to the constraints
and
nX
i;j=1
C(i; j)kvi ¡ vjk22
v1; : : : ; vn 2 Rn
nX
i;j=1
D(i; j)kvi ¡ vjk22 = 1;
8 i; j; k 2 f1; : : : ; ng;kvi ¡ vjk22 6 kvj ¡ vkk22 + kvk ¡ vjk22:
The link to the Heisenberg group
Theorem (Lee-N., 2006): The Goemans-Linial SDP has an integrality gap of at least .
c`1(Bn; dW)
Cheeger-Kleiner-N., 2009: There exists a universal constant c>0 such that
Cheeger-Kleiner, 2007, 2008: Non-quantitative versions that also reduce matters to ruling out a certain more structured embedding.
Quantitative estimate controls phenomena that do not have qualitative counterparts.
c`1(Bn; dW) > (logn)c:
How well does the G-L SDP perform?
Conjecture:
Remark: In a special case called Uniform Sparsest Cut (approximating graph expansion) the G-L SDP might perform better. The best known performance guarantee is [Arora-Rao-Vazirani, 2004] and the best known integrality gap lower bound is
[Kane-Meka, 2013].
c`1(Bn; dW) &plogn:
.plogn
ecplog logn
Vertical perimeter versus horizontal perimeter
Conjecture: For every smooth and compactly supported
Lemma: A positive solution of this conjecture implies that
f : R3 ! R;ÃZ 1
0
µZ
R3jf(x; y; z + t)¡ f(x; y; z)jdxdydz
¶2dt
t2
! 12
.Z
R3
µ¯̄¯̄@f@x
(x; y; z)
¯̄¯̄+¯̄¯̄@f@y
(x; y; z) + x@f
@z(x; y; z)
¯̄¯̄¶dxdydz:
c`1(Bn; dW) &plogn:
Theorem (Lafforgue-N., 2012): For every p>1,
ÃZ 1
0
µZ
R3jf(x; y; z + t)¡ f(x; y; z)jpdxdydz
¶2=pdt
t2
!1=2
.p
µZ
R3
µ¯̄¯̄@f@x
(x; y; z)
¯̄¯̄p
+
¯̄¯̄@f@y
(x; y; z) + x@f
@z(x; y; z)
¯̄¯̄p¶
dxdydz
¶1=p
:
Equivalent form of the conjecture
Let A be a measurable subset of For t>0 define
Then
R3.
vt(A) = vol³©
(x; y; z) 2 A : (x; y; z + t) =2 Aª´
:
Z 1
0
vt(A)2
t2dt . PER(A)2:
Proof of the vertical versus horizontal Poincare inequality
Equivalent statement: Suppose that is q-convex and is smooth and compactly supported. Then
(X;k ¢ kX)f : R3 !X
µZ 1
0
Z
R3
kf(x; y; z + t)¡ f(x; y; z)kqXt1+q=2
dxdydz
¶ 1q
.X
µZ
R3
µ°°°°@f
@x(x; y; z)
°°°°q
X
+
°°°°@f
@y(x; y; z) + x
@f
@z(x; y; z)
°°°°q
X
¶dxdydz
¶ 1q
:
Proof of the equivalence: partition of unity argument + classical Poincare inequality for the Heisenberg group.
d
d²
¯̄¯̄²=0
f
0@0@1 x z
0 1 y
0 0 1
1A0@1 ² 0
0 1 0
0 0 1
1A1A
=d
d²
¯̄¯̄²=0
f
0@0@1 x+ ² z
0 1 y
0 0 1
1A1A =
@f
@x:
a =
0@1 1 0
0 1 0
0 0 1
1A and b =
0@1 0 0
0 1 1
0 0 1
1A
d
d²
¯̄¯̄²=0
f
0@0@1 x z
0 1 y
0 0 1
1A0@1 0 0
0 1 ²
0 0 1
1A1A
=d
d²
¯̄¯̄²=0
f
0@0@1 x z + ²x
0 1 y + ²
0 0 1
1A1A =
@f
@y+ x
@f
@z:
a =
0@1 1 0
0 1 0
0 0 1
1A and b =
0@1 0 0
0 1 1
0 0 1
1A
Heisenberg gradient
Proposition:
rHf =
µ@f
@x;@f
@y+ x
@f
@z
¶: R3 !X ©X:
µZ 1
0
Z
R3
kf(x; y; z + t)¡ f(x; y; z)kqXt1+q=2
dxdydz
¶ 1q
.µZ 1
0
tq¡1 kQt ¤ rHfkqLq(R3;X©X)dt
¶ 1q
:
Littlewood-Paley
By Martinez-Torrea-Xu (2006), the fact that X is q-convex implies
So, it remains to prove the proposition.
µZ 1
0
tq¡1 kQt ¤ rHfkqLq(R3;X©X)dt
¶ 1q
. krHfkLq(R3;X©X) :
By a variant of a classical argument (using Hardy’s inequality and semi-group properties),
µZ 1
0
Z
R3
kf(x; y; z + t)¡ f(x; y; z)kqXt1+q=2
dxdydz
¶ 1q
.µZ 1
0
tq2¡1 kQt ¤ fkqLq(R3;X)
dt
¶ 1q
:
So, we need to show that
µZ 1
0
tq2¡1 kQt ¤ fkqLq(R3;X)
dt
¶ 1q
.µZ 1
0
tq¡1 kQt ¤ rHfkqLq(R3;X©X) dt
¶ 1q
:
The desired estimate
Follows from key lemma by the telescoping sum
µZ 1
0
tq2¡1 kQt ¤ fkqLq(R3;X)
dt
¶ 1q
.µZ 1
0
tq¡1 kQt ¤ rHfkqLq(R3;X©X) dt
¶ 1q
Qt ¤ f =
1X
m=1
(Q2m¡1t ¡Q2mt ¤ f) :
Proof of key lemma
Since we have .
So, by identifying with , for every ,
P2t = Pt ¤Pt Q2t = Pt ¤Qt
R3 H h 2 R3
Qt ¤ f(h)¡Q2t ¤ f(h)= Qt ¤ f(h)¡ Pt ¤Qt ¤ f(h)
=
Z
RPt(u)
¡Qt ¤ f(h)¡Qt ¤ f(hc¡u)
¢du:
For every s>0 consider the commutator path
°s(µ) =8>><>>:
aµ if 0 6 µ 6ps;
apsbµ¡
ps if
ps 6 µ 6 2
ps;
apsbpsa¡µ+2
ps if 2
ps 6 µ 6 3
ps;
apsbpsa¡
psb¡µ+3
ps if 3
ps 6 µ 6 4
ps:
°s : [0;4ps]! R3;
So, and
Hence,
°s(4ps) =
haps; b
psi= [a; b]s = cs:
°s(0) = 0 = eH
Qt ¤ f(h)¡Qt ¤ f(hc¡u)
=
Z 4pu
0
d
dµQt ¤ f
¡hc¡u°u(µ)
¢dµ:
By design, is one of
or
where and .
We used here the fact that since is convolution along the center, it commutes with
ddµQt ¤ f (hc¡u°u(µ))
@aQt ¤ f(hc¡u°u(µ)) =Qt ¤ @af(hc¡u°u(µ))
@bQt ¤ f(hc¡u°u(µ)) =Qt ¤ @bf(hc¡u°u(µ));@a = @x @b = @y +x@z
Qt
@a; @b: