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Let $\kappa:\mathbb{R}^d\times \mathbb{R}^d \to\mathbb{R}$ be a positive semidefinite kernel. If $A,B \subseteq \mathbb{R}^d$ are disjoint sets of equal, finite measure, then applying the definition of positive semidefiniteness to estimate the inner product of $\mathbf{1}_A-\mathbf{1}_B$ with its convolution with $\kappa$ shows that $$ \frac{1}{|A\cup B|^2}\iint_{A\cup B} \kappa(x,y)dxdy \leq \frac{1}{2}\left[\frac{1}{|A|^2}\iint_{A} \kappa(x,y)dxdy + \frac{1}{|B|^2}\iint_{B} \kappa(x,y)dxdy\right]. $$$$ \frac{1}{|A\cup B|^2}\iint_{A\cup B} \kappa(x,y)dxdy \leq \frac{1}{2}\left[\frac{1}{|A|^2}\iint_{A} \kappa(x,y)dxdy + \frac{1}{|B|^2}\iint_{B} \kappa(x,y)dxdy\right], $$ where $|A|$ denotes the volume of $A$. This can be thought of as a kind of monotonicity for the average of $\kappa$ over a set. Applying this estimate inductively yields that, if $\kappa(x,y)=\kappa(0,y-x)$ is translation-invariant, then the average of $\kappa$ over a box $[0,kr]^d$ is at most the average over $[0,r]^d$ for every $r>0$ and every natural number $k\geq 1$. (To see this, use the above fact to bound the average over $[0,kr]^{\ell}\times[0,r]^{d-\ell}$ inductively for $\ell=0,1,\ldots,d$.)

I am curious about the following questions:

  1. Is there a standard name or reference for this fact about averages of positive-definite functions over boxes decreasing in the side-length?
  2. Is there an analogous statement for balls, rather than boxes? What about other convex sets? (Of course we can get coarse versions of the inequality, involving a set-dependent constant, by taking boxes that inscribe and circumscribe the given convex set.)
  3. To what extent can the assumption that the scaling factor is an integer be relaxed?

Let $\kappa:\mathbb{R}^d\times \mathbb{R}^d \to\mathbb{R}$ be a positive semidefinite kernel. If $A,B \subseteq \mathbb{R}^d$ are disjoint sets of equal, finite measure, then applying the definition of positive semidefiniteness to estimate the inner product of $\mathbf{1}_A-\mathbf{1}_B$ with its convolution with $\kappa$ shows that $$ \frac{1}{|A\cup B|^2}\iint_{A\cup B} \kappa(x,y)dxdy \leq \frac{1}{2}\left[\frac{1}{|A|^2}\iint_{A} \kappa(x,y)dxdy + \frac{1}{|B|^2}\iint_{B} \kappa(x,y)dxdy\right]. $$ This can be thought of as a kind of monotonicity for the average of $\kappa$ over a set. Applying this estimate inductively yields that, if $\kappa(x,y)=\kappa(0,y-x)$ is translation-invariant, then the average of $\kappa$ over a box $[0,kr]^d$ is at most the average over $[0,r]^d$ for every $r>0$ and every natural number $k\geq 1$. (To see this, use the above fact to bound the average over $[0,kr]^{\ell}\times[0,r]^{d-\ell}$ inductively for $\ell=0,1,\ldots,d$.)

I am curious about the following questions:

  1. Is there a standard name or reference for this fact about averages of positive-definite functions over boxes decreasing in the side-length?
  2. Is there an analogous statement for balls, rather than boxes? What about other convex sets? (Of course we can get coarse versions of the inequality, involving a set-dependent constant, by taking boxes that inscribe and circumscribe the given convex set.)
  3. To what extent can the assumption that the scaling factor is an integer be relaxed?

Let $\kappa:\mathbb{R}^d\times \mathbb{R}^d \to\mathbb{R}$ be a positive semidefinite kernel. If $A,B \subseteq \mathbb{R}^d$ are disjoint sets of equal, finite measure, then applying the definition of positive semidefiniteness to estimate the inner product of $\mathbf{1}_A-\mathbf{1}_B$ with its convolution with $\kappa$ shows that $$ \frac{1}{|A\cup B|^2}\iint_{A\cup B} \kappa(x,y)dxdy \leq \frac{1}{2}\left[\frac{1}{|A|^2}\iint_{A} \kappa(x,y)dxdy + \frac{1}{|B|^2}\iint_{B} \kappa(x,y)dxdy\right], $$ where $|A|$ denotes the volume of $A$. This can be thought of as a kind of monotonicity for the average of $\kappa$ over a set. Applying this estimate inductively yields that, if $\kappa(x,y)=\kappa(0,y-x)$ is translation-invariant, then the average of $\kappa$ over a box $[0,kr]^d$ is at most the average over $[0,r]^d$ for every $r>0$ and every natural number $k\geq 1$. (To see this, use the above fact to bound the average over $[0,kr]^{\ell}\times[0,r]^{d-\ell}$ inductively for $\ell=0,1,\ldots,d$.)

I am curious about the following questions:

  1. Is there a standard name or reference for this fact about averages of positive-definite functions over boxes decreasing in the side-length?
  2. Is there an analogous statement for balls, rather than boxes? What about other convex sets? (Of course we can get coarse versions of the inequality, involving a set-dependent constant, by taking boxes that inscribe and circumscribe the given convex set.)
  3. To what extent can the assumption that the scaling factor is an integer be relaxed?
Source Link
tmh
  • 775
  • 4
  • 12

Monotonicity of averages for positive-definite kernels

Let $\kappa:\mathbb{R}^d\times \mathbb{R}^d \to\mathbb{R}$ be a positive semidefinite kernel. If $A,B \subseteq \mathbb{R}^d$ are disjoint sets of equal, finite measure, then applying the definition of positive semidefiniteness to estimate the inner product of $\mathbf{1}_A-\mathbf{1}_B$ with its convolution with $\kappa$ shows that $$ \frac{1}{|A\cup B|^2}\iint_{A\cup B} \kappa(x,y)dxdy \leq \frac{1}{2}\left[\frac{1}{|A|^2}\iint_{A} \kappa(x,y)dxdy + \frac{1}{|B|^2}\iint_{B} \kappa(x,y)dxdy\right]. $$ This can be thought of as a kind of monotonicity for the average of $\kappa$ over a set. Applying this estimate inductively yields that, if $\kappa(x,y)=\kappa(0,y-x)$ is translation-invariant, then the average of $\kappa$ over a box $[0,kr]^d$ is at most the average over $[0,r]^d$ for every $r>0$ and every natural number $k\geq 1$. (To see this, use the above fact to bound the average over $[0,kr]^{\ell}\times[0,r]^{d-\ell}$ inductively for $\ell=0,1,\ldots,d$.)

I am curious about the following questions:

  1. Is there a standard name or reference for this fact about averages of positive-definite functions over boxes decreasing in the side-length?
  2. Is there an analogous statement for balls, rather than boxes? What about other convex sets? (Of course we can get coarse versions of the inequality, involving a set-dependent constant, by taking boxes that inscribe and circumscribe the given convex set.)
  3. To what extent can the assumption that the scaling factor is an integer be relaxed?