Topological Data Analysis on Noisy Quantum Computers
Ismail Akhalwaya, Shashanka Ubaru, et al.
ICLR 2024
Monte Carlo matrix trace estimation is a popular randomized technique to estimate the trace of implicitly-defined matrices via averaging quadratic forms across several observations of a random vector. The most common approach to analyze the quality of such estimators is to consider the variance over the total number of observations. In this paper we present a procedure to compute the variance of the estimator proposed by Kong and Valiant [Ann. Statist. 45 (5), pp. 2218 - 2247] for the case of Gaussian random vectors and provide a sharper bound than previously available.
Ismail Akhalwaya, Shashanka Ubaru, et al.
ICLR 2024
Shu Tezuka
WSC 1991
Renu Tewari, Richard P. King, et al.
IS&T/SPIE Electronic Imaging 1996
Joy Y. Cheng, Daniel P. Sanders, et al.
SPIE Advanced Lithography 2008