# Minimax $L_2$-Separation Rate in Testing the Sobolev-Type Regularity of a function

## TL;DR

This paper investigates the minimax $L_2$-separation rate for testing whether a function in a Sobolev space has higher smoothness, deriving bounds that reveal the rate's independence from the higher smoothness level.

## Contribution

It provides the first precise characterization of the minimax separation rate in Sobolev smoothness testing, showing it matches the rate in simple signal detection.

## Key findings

- The separation rate scales as $n^{-t/(2t+1/2)}$.
- The rate is independent of the higher smoothness level $s$.
- The results unify the understanding of smoothness testing and signal detection rates.

## Abstract

In this paper we study the problem of testing if an $L_2-$function $f$ belonging to a certain $l_2$-Sobolev-ball $B_t(R)$ of radius $R>0$ with smoothness level $t>0$ indeed exhibits a higher smoothness level $s>t$, that is, belongs to $B_s(R)$. We assume that only a perturbed version of $f$ is available, where the noise is governed by a standard Brownian motion scaled by $\frac{1}{\sqrt{n}}$. More precisely, considering a testing problem of the form $$H_0:~f\in B_s(R)~~\mathrm{vs.}~~H_1:~f\in B_t(R),~\inf_{h\in B_s}\Vert f-h\Vert_{L_2}>\rho$$ for some $\rho>0$, we approach the task of identifying the smallest value for $\rho$, denoted $\rho^\ast$, enabling the existence of a test $\varphi$ with small error probability in a minimax sense. By deriving lower and upper bounds on $\rho^\ast$, we expose its precise dependence on $n$: $$\rho^\ast\sim n^{-\frac{t}{2t+1/2}}.$$ As a remarkable aspect of this composite-composite testing problem, it turns out that the rate does not depend on $s$ and is equal to the rate in signal-detection, i.e. the case of a simple null hypothesis.