TY - GEN
T1 - Expander random walks
T2 - 53rd Annual ACM SIGACT Symposium on Theory of Computing, STOC 2021
AU - Cohen, Gil
AU - Peri, Noam
AU - Ta-Shma, Amnon
N1 - Publisher Copyright: © 2021 ACM.
PY - 2021/6/15
Y1 - 2021/6/15
N2 - In this work we ask the following basic question: assume the vertices of an expander graph are labelled by 0,1. What "test"functions f : { 0,1}t ? {0,1} cannot distinguish t independent samples from those obtained by a random walk? The expander hitting property due to Ajtai, Komlos and Szemeredi (STOC 1987) is captured by the AND test function, whereas the fundamental expander Chernoff bound due to Gillman (SICOMP 1998), Heally (Computational Complexity 2008) is about test functions indicating whether the weight is close to the mean. In fact, it is known that all threshold functions are fooled by a random walk (Kipnis and Varadhan, Communications in Mathematical Physics 1986). Recently, it was shown that even the highly sensitive PARITY function is fooled by a random walk Ta-Shma (STOC 2017). We focus on balanced labels. Our first main result is proving that all symmetric functions are fooled by a random walk. Put differently, we prove a central limit theorem (CLT) for expander random walks with respect to the total variation distance, significantly strengthening the classic CLT for Markov Chains that is established with respect to the Kolmogorov distance (Kipnis and Varadhan, Communications in Mathematical Physics 1986). Our approach significantly deviates from prior works. We first study how well a Fourier character ?S is fooled by a random walk as a function of S. Then, given a test function f, we expand f in the Fourier basis and combine the above with known results on the Fourier spectrum of f. We also proceed further and consider general test functions - not necessarily symmetric. As our approach is Fourier analytic, it is general enough to analyze such versatile test functions. For our second result, we prove that random walks on sufficiently good expander graphs fool tests functions computed by AC0 circuits, read-once branching programs, and functions with bounded query complexity.
AB - In this work we ask the following basic question: assume the vertices of an expander graph are labelled by 0,1. What "test"functions f : { 0,1}t ? {0,1} cannot distinguish t independent samples from those obtained by a random walk? The expander hitting property due to Ajtai, Komlos and Szemeredi (STOC 1987) is captured by the AND test function, whereas the fundamental expander Chernoff bound due to Gillman (SICOMP 1998), Heally (Computational Complexity 2008) is about test functions indicating whether the weight is close to the mean. In fact, it is known that all threshold functions are fooled by a random walk (Kipnis and Varadhan, Communications in Mathematical Physics 1986). Recently, it was shown that even the highly sensitive PARITY function is fooled by a random walk Ta-Shma (STOC 2017). We focus on balanced labels. Our first main result is proving that all symmetric functions are fooled by a random walk. Put differently, we prove a central limit theorem (CLT) for expander random walks with respect to the total variation distance, significantly strengthening the classic CLT for Markov Chains that is established with respect to the Kolmogorov distance (Kipnis and Varadhan, Communications in Mathematical Physics 1986). Our approach significantly deviates from prior works. We first study how well a Fourier character ?S is fooled by a random walk as a function of S. Then, given a test function f, we expand f in the Fourier basis and combine the above with known results on the Fourier spectrum of f. We also proceed further and consider general test functions - not necessarily symmetric. As our approach is Fourier analytic, it is general enough to analyze such versatile test functions. For our second result, we prove that random walks on sufficiently good expander graphs fool tests functions computed by AC0 circuits, read-once branching programs, and functions with bounded query complexity.
KW - Combinatorics and graph theory
KW - Computational complexity
KW - Randomness in computing
UR - http://www.scopus.com/inward/record.url?scp=85108145303&partnerID=8YFLogxK
U2 - 10.1145/3406325.3451049
DO - 10.1145/3406325.3451049
M3 - منشور من مؤتمر
T3 - Proceedings of the Annual ACM Symposium on Theory of Computing
SP - 1643
EP - 1655
BT - STOC 2021 - Proceedings of the 53rd Annual ACM SIGACT Symposium on Theory of Computing
A2 - Khuller, Samir
A2 - Williams, Virginia Vassilevska
PB - Association for Computing Machinery
Y2 - 21 June 2021 through 25 June 2021
ER -