Result in geometry
In mathematics , the Loomis–Whitney inequality is a result in geometry , which in its simplest form, allows one to estimate the "size" of a
d
{\displaystyle d}
-dimensional set by the sizes of its
(
d
− − -->
1
)
{\displaystyle (d-1)}
-dimensional projections. The inequality has applications in incidence geometry , the study of so-called "lattice animals", and other areas.
The result is named after the American mathematicians Lynn Harold Loomis and Hassler Whitney , and was published in 1949.
Statement of the inequality
Fix a dimension
d
≥ ≥ -->
2
{\displaystyle d\geq 2}
and consider the projections
π π -->
j
:
R
d
→ → -->
R
d
− − -->
1
,
{\displaystyle \pi _{j}:\mathbb {R} ^{d}\to \mathbb {R} ^{d-1},}
π π -->
j
:
x
=
(
x
1
,
… … -->
,
x
d
)
↦ ↦ -->
x
^ ^ -->
j
=
(
x
1
,
… … -->
,
x
j
− − -->
1
,
x
j
+
1
,
… … -->
,
x
d
)
.
{\displaystyle \pi _{j}:x=(x_{1},\dots ,x_{d})\mapsto {\hat {x}}_{j}=(x_{1},\dots ,x_{j-1},x_{j+1},\dots ,x_{d}).}
For each 1 ≤ j ≤ d , let
g
j
:
R
d
− − -->
1
→ → -->
[
0
,
+
∞ ∞ -->
)
,
{\displaystyle g_{j}:\mathbb {R} ^{d-1}\to [0,+\infty ),}
g
j
∈ ∈ -->
L
d
− − -->
1
(
R
d
− − -->
1
)
.
{\displaystyle g_{j}\in L^{d-1}(\mathbb {R} ^{d-1}).}
Then the Loomis–Whitney inequality holds:
‖
∏ ∏ -->
j
=
1
d
g
j
∘ ∘ -->
π π -->
j
‖
L
1
(
R
d
)
=
∫ ∫ -->
R
d
∏ ∏ -->
j
=
1
d
g
j
(
π π -->
j
(
x
)
)
d
x
≤ ≤ -->
∏ ∏ -->
j
=
1
d
‖ ‖ -->
g
j
‖ ‖ -->
L
d
− − -->
1
(
R
d
− − -->
1
)
.
{\displaystyle \left\|\prod _{j=1}^{d}g_{j}\circ \pi _{j}\right\|_{L^{1}(\mathbb {R} ^{d})}=\int _{\mathbb {R} ^{d}}\prod _{j=1}^{d}g_{j}(\pi _{j}(x))\,\mathrm {d} x\leq \prod _{j=1}^{d}\|g_{j}\|_{L^{d-1}(\mathbb {R} ^{d-1})}.}
Equivalently, taking
f
j
(
x
)
=
g
j
(
x
)
d
− − -->
1
,
{\displaystyle f_{j}(x)=g_{j}(x)^{d-1},}
we have
f
j
:
R
d
− − -->
1
→ → -->
[
0
,
+
∞ ∞ -->
)
,
{\displaystyle f_{j}:\mathbb {R} ^{d-1}\to [0,+\infty ),}
f
j
∈ ∈ -->
L
1
(
R
d
− − -->
1
)
{\displaystyle f_{j}\in L^{1}(\mathbb {R} ^{d-1})}
implying
∫ ∫ -->
R
d
∏ ∏ -->
j
=
1
d
f
j
(
π π -->
j
(
x
)
)
1
/
(
d
− − -->
1
)
d
x
≤ ≤ -->
∏ ∏ -->
j
=
1
d
(
∫ ∫ -->
R
d
− − -->
1
f
j
(
x
^ ^ -->
j
)
d
x
^ ^ -->
j
)
1
/
(
d
− − -->
1
)
.
{\displaystyle \int _{\mathbb {R} ^{d}}\prod _{j=1}^{d}f_{j}(\pi _{j}(x))^{1/(d-1)}\,\mathrm {d} x\leq \prod _{j=1}^{d}\left(\int _{\mathbb {R} ^{d-1}}f_{j}({\hat {x}}_{j})\,\mathrm {d} {\hat {x}}_{j}\right)^{1/(d-1)}.}
A special case
The Loomis–Whitney inequality can be used to relate the Lebesgue measure of a subset of Euclidean space
R
d
{\displaystyle \mathbb {R} ^{d}}
to its "average widths" in the coordinate directions. This is in fact the original version published by Loomis and Whitney in 1949 (the above is a generalization).[ 1]
Let E be some measurable subset of
R
d
{\displaystyle \mathbb {R} ^{d}}
and let
f
j
=
1
π π -->
j
(
E
)
{\displaystyle f_{j}=\mathbf {1} _{\pi _{j}(E)}}
be the indicator function of the projection of E onto the j th coordinate hyperplane. It follows that for any point x in E ,
∏ ∏ -->
j
=
1
d
f
j
(
π π -->
j
(
x
)
)
1
/
(
d
− − -->
1
)
=
∏ ∏ -->
j
=
1
d
1
=
1.
{\displaystyle \prod _{j=1}^{d}f_{j}(\pi _{j}(x))^{1/(d-1)}=\prod _{j=1}^{d}1=1.}
Hence, by the Loomis–Whitney inequality,
∫ ∫ -->
R
d
1
E
(
x
)
d
x
=
|
E
|
≤ ≤ -->
∏ ∏ -->
j
=
1
d
|
π π -->
j
(
E
)
|
1
/
(
d
− − -->
1
)
,
{\displaystyle \int _{\mathbb {R} ^{d}}\mathbf {1} _{E}(x)\,\mathrm {d} x=|E|\leq \prod _{j=1}^{d}|\pi _{j}(E)|^{1/(d-1)},}
and hence
|
E
|
≥ ≥ -->
∏ ∏ -->
j
=
1
d
|
E
|
|
π π -->
j
(
E
)
|
.
{\displaystyle |E|\geq \prod _{j=1}^{d}{\frac {|E|}{|\pi _{j}(E)|}}.}
The quantity
|
E
|
|
π π -->
j
(
E
)
|
{\displaystyle {\frac {|E|}{|\pi _{j}(E)|}}}
can be thought of as the average width of
E
{\displaystyle E}
in the
j
{\displaystyle j}
th coordinate direction. This interpretation of the Loomis–Whitney inequality also holds if we consider a finite subset of Euclidean space and replace Lebesgue measure by counting measure .
The following proof is the original one[ 1]
Proof
Overview: We prove it for unions of unit cubes on the integer grid, then take the continuum limit. When
d
=
1
,
2
{\displaystyle d=1,2}
, it is obvious. Now induct on
d
+
1
{\displaystyle d+1}
. The only trick is to use Hölder's inequality for counting measures.
Enumerate the dimensions of
R
d
+
1
{\displaystyle \mathbb {R} ^{d+1}}
as
0
,
1
,
.
.
.
,
d
{\displaystyle 0,1,...,d}
.
Given
N
{\displaystyle N}
unit cubes on the integer grid in
R
d
+
1
{\displaystyle \mathbb {R} ^{d+1}}
, with their union being
T
{\displaystyle T}
, we project them to the 0-th coordinate. Each unit cube projects to an integer unit interval on
R
{\displaystyle \mathbb {R} }
. Now define the following:
I
1
,
.
.
.
,
I
k
{\displaystyle I_{1},...,I_{k}}
enumerate all such integer unit intervals on the 0-th coordinate.
Let
T
i
{\displaystyle T_{i}}
be the set of all unit cubes that projects to
I
i
{\displaystyle I_{i}}
.
Let
N
j
{\displaystyle N_{j}}
be the area of
π π -->
j
(
T
)
{\displaystyle \pi _{j}(T)}
, with
j
=
0
,
1
,
.
.
.
,
d
{\displaystyle j=0,1,...,d}
.
Let
a
i
{\displaystyle a_{i}}
be the volume of
T
i
{\displaystyle T_{i}}
. We have
∑ ∑ -->
i
a
i
=
N
{\displaystyle \sum _{i}a_{i}=N}
, and
a
i
≤ ≤ -->
N
0
{\displaystyle a_{i}\leq N_{0}}
.
Let
T
i
j
{\displaystyle T_{ij}}
be
π π -->
j
(
T
i
)
{\displaystyle \pi _{j}(T_{i})}
for all
j
=
1
,
.
.
.
,
d
{\displaystyle j=1,...,d}
.
Let
a
i
j
{\displaystyle a_{ij}}
be the area of
T
i
j
{\displaystyle T_{ij}}
. We have
∑ ∑ -->
i
a
i
j
=
N
j
{\displaystyle \sum _{i}a_{ij}=N_{j}}
.
By induction on each slice of
T
i
{\displaystyle T_{i}}
, we have
a
i
d
− − -->
1
≤ ≤ -->
∏ ∏ -->
j
=
1
d
a
i
j
{\displaystyle a_{i}^{d-1}\leq \prod _{j=1}^{d}a_{ij}}
Multiplying by
a
i
≤ ≤ -->
N
0
{\displaystyle a_{i}\leq N_{0}}
, we have
a
i
d
≤ ≤ -->
N
0
∏ ∏ -->
j
=
1
d
a
i
j
{\displaystyle a_{i}^{d}\leq N_{0}\prod _{j=1}^{d}a_{ij}}
Thus
N
=
∑ ∑ -->
i
a
i
≤ ≤ -->
∑ ∑ -->
i
N
0
1
/
d
∏ ∏ -->
j
=
1
d
a
i
j
1
/
d
=
N
0
1
/
d
∑ ∑ -->
i
=
1
k
∏ ∏ -->
j
=
1
d
a
i
j
1
/
d
{\displaystyle N=\sum _{i}a_{i}\leq \sum _{i}N_{0}^{1/d}\prod _{j=1}^{d}a_{ij}^{1/d}=N_{0}^{1/d}\sum _{i=1}^{k}\prod _{j=1}^{d}a_{ij}^{1/d}}
Now, the sum-product can be written as an integral over counting measure, allowing us to perform Holder's inequality:
∑ ∑ -->
i
=
1
k
∏ ∏ -->
j
=
1
d
a
i
j
1
/
d
=
∫ ∫ -->
i
∏ ∏ -->
j
=
1
d
a
i
j
1
/
d
=
‖
∏ ∏ -->
j
=
1
d
a
⋅ ⋅ -->
,
j
1
/
d
‖
1
≤ ≤ -->
∏ ∏ -->
j
‖ ‖ -->
a
⋅ ⋅ -->
,
j
1
/
d
‖ ‖ -->
d
=
∏ ∏ -->
j
=
1
d
(
∑ ∑ -->
i
=
1
k
a
i
j
)
1
/
d
{\displaystyle \sum _{i=1}^{k}\prod _{j=1}^{d}a_{ij}^{1/d}=\int _{i}\prod _{j=1}^{d}a_{ij}^{1/d}=\left\|\prod _{j=1}^{d}a_{\cdot ,j}^{1/d}\right\|_{1}\leq \prod _{j}\|a_{\cdot ,j}^{1/d}\|_{d}=\prod _{j=1}^{d}\left(\sum _{i=1}^{k}a_{ij}\right)^{1/d}}
Plugging in
∑ ∑ -->
i
a
i
j
=
N
j
{\displaystyle \sum _{i}a_{ij}=N_{j}}
, we get
N
d
≤ ≤ -->
∏ ∏ -->
j
=
0
d
N
j
{\displaystyle N^{d}\leq \prod _{j=0}^{d}N_{j}}
Corollary. Since
2
|
π π -->
j
(
E
)
|
≤ ≤ -->
|
∂ ∂ -->
E
|
{\displaystyle 2|\pi _{j}(E)|\leq |\partial E|}
, we get a loose isoperimetric inequality:
|
E
|
d
− − -->
1
≤ ≤ -->
2
− − -->
d
|
∂ ∂ -->
E
|
d
{\displaystyle |E|^{d-1}\leq 2^{-d}|\partial E|^{d}}
Iterating the theorem yields
|
E
|
≤ ≤ -->
∏ ∏ -->
1
≤ ≤ -->
j
<
k
≤ ≤ -->
d
|
π π -->
j
∘ ∘ -->
π π -->
k
(
E
)
|
(
d
− − -->
1
2
)
− − -->
1
{\displaystyle |E|\leq \prod _{1\leq j<k\leq d}|\pi _{j}\circ \pi _{k}(E)|^{{\binom {d-1}{2}}^{-1}}}
and more generally[ 2]
|
E
|
≤ ≤ -->
∏ ∏ -->
j
|
π π -->
j
(
E
)
|
(
d
− − -->
1
k
)
− − -->
1
{\displaystyle |E|\leq \prod _{j}|\pi _{j}(E)|^{{\binom {d-1}{k}}^{-1}}}
where
π π -->
j
{\displaystyle \pi _{j}}
enumerates over all projections of
R
d
{\displaystyle \mathbb {R} ^{d}}
to its
d
− − -->
k
{\displaystyle d-k}
dimensional subspaces.
Generalizations
The Loomis–Whitney inequality is a special case of the Brascamp–Lieb inequality , in which the projections πj above are replaced by more general linear maps , not necessarily all mapping onto spaces of the same dimension.
References
Sources
Alon, Noga ; Spencer, Joel H. (2016). The probabilistic method . Wiley Series in Discrete Mathematics and Optimization (Fourth edition of 1992 original ed.). Hoboken, NJ: John Wiley & Sons, Inc. ISBN 978-1-119-06195-3 . MR 3524748 . Zbl 1333.05001 .
Boucheron, Stéphane; Lugosi, Gábor; Massart, Pascal (2013). Concentration inequalities. A nonasymptotic theory of independence . Oxford: Oxford University Press . doi :10.1093/acprof:oso/9780199535255.001.0001 . ISBN 978-0-19-953525-5 . MR 3185193 . Zbl 1279.60005 .
Burago, Yu. D. ; Zalgaller, V. A. (1988). Geometric inequalities . Grundlehren der mathematischen Wissenschaften. Vol. 285. Translated by Sosinskiĭ, A. B. Berlin: Springer-Verlag . doi :10.1007/978-3-662-07441-1 . ISBN 3-540-13615-0 . MR 0936419 . Zbl 0633.53002 .
Hadwiger, H. (1957). Vorlesungen über Inhalt, Oberfläche und Isoperimetrie . Grundlehren der mathematischen Wissenschaften. Vol. 93. Berlin–Göttingen–Heidelberg: Springer-Verlag . doi :10.1007/978-3-642-94702-5 . ISBN 3-642-94702-6 . MR 0102775 . Zbl 0078.35703 .
Loomis, L. H. ; Whitney, H. (1949). "An inequality related to the isoperimetric inequality" . Bulletin of the American Mathematical Society . 55 (10): 961– 962. doi :10.1090/S0002-9904-1949-09320-5 . MR 0031538 . Zbl 0035.38302 .