Coarse-grained quantum state tomography with optimal POVM construction

Abstract

Constructing an integrated large-scale qubit system of realistic size requires addressing the challenge of physical crowding among qubits. This constraint poses an issue of coarse-grained (CG) measurement, wherein information from the multi-qubit system is collectively gathered. In this work, we introduce a novel approach to reconstruct the target density matrix from a comprehensive set of Positive Operator-Valued Measures (POVM) using a Parameterized Quantum Circuit (PQC) under the constraint of CG measurement. We improve the robustness and stability of CG quantum state tomography (QST) by optimizing the POVM set to achieve a generalized symmetric informationally complete (GSIC) POVM through maximization of the von Neumann entropy. This optimized construction of CG-POVMs is scalable to an N-qubit system. We further discuss a more efficient construction of N-qubit CG-QST without exponential increases in two-qubit gates or circuit depth per measurement. Our scheme offers a viable pathway towards a detector-efficient large-scale solid-state embedded qubit platform by reconstructing crucial quantum information from collective measurements.