Quantum computational complexity of matrix functions

Schedule

Abstract

We investigate the dividing line between classical and quantum computational power in estimating properties of matrix functions. More precisely, we study the computational complexity of two primitive problems: given a function f and a Hermitian matrix A, compute a matrix element of f(A) or compute a local measurement on f(A)|0⟩⊗n, with |0⟩⊗n an n-qubit reference state vector, in both cases up to additive approximation error. We consider four functions -- monomials, Chebyshev polynomials, the time evolution function, and the inverse function -- and probe the complexity across a broad landscape covering different problem input regimes. Namely, we consider two types of matrix inputs (sparse and Pauli access), matrix properties (norm, sparsity), the approximation error, and function-specific parameters. We identify BQP-complete forms of both problems for each function and then toggle the problem parameters to easier regimes to see where hardness remains, or where the problem becomes classically easy. As part of our results we make concrete a hierarchy of hardness across the functions; in parameter regimes where we have classically efficient algorithms for monomials, all three other functions remain robustly BQP-hard, or hard under usual computational complexity assumptions. In identifying classically easy regimes, among others, we show that for any polynomial of degree poly(n) both problems can be efficiently classically simulated when A has O(logn) non-zero coefficients in the Pauli basis. This contrasts with the fact that the problems are BQP-complete in the sparse access model even for constant row sparsity, whereas the stated Pauli access efficiently constructs sparse access with row sparsity O(logn). Our work provides a catalog of efficient quantum and classical algorithms for fundamental linear-algebra tasks.

Personal information

Samson Wang is a postdoc at the Institute for Quantum Information and Matter at Caltech. Previously, he completed his PhD under the supervision of Mario Berta at Imperial College London, and then was a visiting researcher / postdoc at IRIF with Simon Apers.He is interested in theoretical aspects of quantum algorithms and near-term quantum computing.

Post Date

May 23, 2025

Centers

Quantum Computing Research Center

Topic

Quantum Computing