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Variational Quantum Algorithms for Trace Distance and Fidelity Estimation

by   Ranyiliu Chen, et al.

Estimating the difference between quantum data is crucial in quantum computing. In particular, trace distance and quantum fidelity are vital for verifying various quantum information processing tasks. In this work, we introduce hybrid quantum-classical algorithms for practical distance measure estimation on near-term quantum devices. First, we introduce the Variational Trace Distance Estimation (VTDE) algorithm. We in particular show that local measurement results can extract the desired spectrum information of any Hermitian matrix. We further exploit this fact to design a novel variational algorithm for trace norm estimation that only involves one ancillary qubit. Notably, the cost function in VTDE gathers information from a single-qubit observable and thus could avoid the barren plateau issue with logarithmic depth parameterized circuits. Second, we introduce the Variational Fidelity Estimation (VFE) algorithm. We combine Uhlmann's theorem and the freedom in purification to translate the estimation task into an optimization problem over a unitary on an ancillary system with fixed purified inputs. We then introduce a purification subroutine to complete the task. Numerical experiments for both algorithms have been conducted to show the validity of our methods. The metrics are estimated with high accuracy for randomly generated mixed states.


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