Computationally Efficient Quantum Expectation with Extended Bell Measurements

TL;DR

This paper introduces an extended Bell measurement method that efficiently evaluates quantum expectation values by grouping matrix elements, significantly reducing measurement complexity and variance, especially for band matrices, with demonstrated experimental validation.

Contribution

The paper presents a novel extended Bell measurement technique that assembles matrix elements into fewer groups for efficient quantum expectation evaluation, improving scalability and variance reduction.

Findings

Reduces measurement groups to O(n^{c+1}) for band matrices

Achieves lower variance compared to existing methods

Demonstrates efficiency on IBM-Q quantum system

Abstract

Evaluating an expectation value of an arbitrary observable $A\in{\mathbb C}^{2^n\times 2^n}$ through na\"ive Pauli measurements requires a large number of terms to be evaluated. We approach this issue using a method based on Bell measurement, which we refer to as the extended Bell measurement method. This analytical method quickly assembles the $4^n$ matrix elements into at most $2^{n+1}$ groups for simultaneous measurements in $O(nd)$ time, where $d$ is the number of non-zero elements of $A$. The number of groups is particularly small when $A$ is a band matrix. When the bandwidth of $A$ is $k=O(n^c)$, the number of groups for simultaneous measurement reduces to $O(n^{c+1})$. In addition, when non-zero elements densely fill the band, the variance is $O((n^{c+1}/2^n)\,{\rm tr}(A^2))$, which is small compared with the variances of existing methods. The proposed method requires a few additional gates for each measurement, namely one Hadamard gate, one phase gate and at most $n-1$ CNOT gates. Experimental results on an IBM-Q system show the computational efficiency and scalability of the proposed scheme, compared with existing state-of-the-art approaches. Code is available at https://github.com/ToyotaCRDL/extended-bell-measurements.