Quantum Algorithm for Estimating Volumes of Convex Bodies

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Shouvanik Chakrabarti, Andrew M. Childs, Shih-Han Hung, Tongyang Li, Chunhao Wang, Xiaodi Wu

Published: 2023, Last Modified: 08 May 2026ACM Trans. Quantum Comput. 2023EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: Estimating the volume of a convex body is a central problem in convex geometry and can be viewed as a continuous version of counting. We present a quantum algorithm that estimates the volume of an n-dimensional convex body within multiplicative error ε using Õ(n3 + n2.5/ε) queries to a membership oracle and Õ(n5+n4.5/ε) additional arithmetic operations. For comparison, the best known classical algorithm uses Õ(n3.5+n3/ε2) queries and Õ(n5.5+n5/ε2) additional arithmetic operations. To the best of our knowledge, this is the first quantum speedup for volume estimation. Our algorithm is based on a refined framework for speeding up simulated annealing algorithms that might be of independent interest. This framework applies in the setting of “Chebyshev cooling,” where the solution is expressed as a telescoping product of ratios, each having bounded variance. We develop several novel techniques when implementing our framework, including a theory of continuous-space quantum walks with rigorous bounds on discretization error. To complement our quantum algorithms, we also prove that volume estimation requires Ω (√ n+1/ε) quantum membership queries, which rules out the possibility of exponential quantum speedup in n and shows optimality of our algorithm in 1/ε up to poly-logarithmic factors.