3 papers
math.OC2025
A Compressive Sensing Inspired Monte-Carlo Method for Combinatorial Optimization
Baptiste Chevalier, Shimpei Yamaguchi, Wojciech Roga +1
In this paper, we present a Monte-Carlo Compressive Optimization algorithm, a new method to tackle combinatorial optimization problems, including Black-Box or complicated objective…
quant-ph2025
Demonstration of sequential processors with quantum advantage and analysis of classical performance limits
Shota Tateishi, Wenhao Wang, Baptiste Chevalier +3
In this paper, we theoretically and experimentally analyze sequential processors with limited communication between parts. We compare the expressivity of sequential quantum and cla…
quant-ph2024
Compressed sensing enhanced by quantum approximate optimization algorithm
Baptiste Chevalier, Wojciech Roga, Masahiro Takeoka
We present a framework to deal with a range of large scale compressive sensing problems using a quantum subroutine. We apply a quantum approximate optimization algorithm (QAOA) to…