Quantum state tomography and fidelity estimation via Phaselift

Yiping Lu, Qing Zhao

Yiping Lu, Qing Bo Zhao

Multi-photon system has been studied by many groups. The challenge facing by most groups is the limited samples are far from enough for detecting quantum entanglement. The problem is even more serious for the quantum state tomography. Adaptive quantum state tomography is one possible way to solve the problem. We develop a distribution scheme of samples and extend it into three step to improve the performance of adaptive quantum state tomography. Mean Square Error of reconstructed density matrix is improved for several states being tested numerically. In addition, Phaselift is applied to save the storage space of measurement operator.

Muhammad Hamza Waseem, Faizan-e-Ilahi, Muhammad Sabieh Anwar

M. Cramer, Martin Bodo Plenio, Steven T. Flammia +6 more

Haiyang Qin, Liangyu Che, Chao Wei +3 more

Fidelity estimation is an important technique for evaluating prepared quantum states in noisy quantum devices. A recent theoretical work proposed a frugal approach called neural quantum fidelity estimation (NQFE) [X. Zhang et al., Phys. Rev. Lett. 127, 130503 (2021).PRLTAO0031-900710.1103/PhysRevLett.127.130503]. While this requires a much smaller number of measurement operators than full quantum state tomography, it uses a weight-based floating measurement strategy that predetermines the top global Pauli operators that contribute the most to the fidelity and uses discrete fidelity intervals as predictions. In this Letter, we develop a measurement-fixed NQFE based on a transformer model which requires less measurement cost and can output continuous estimates of fidelity. Here we further experimentally apply the NQFE in a realistic situation using a nuclear spin quantum processor. We prepare the ground states of local Hamiltonians and arbitrary states and investigate how to estimate their fidelity with reference states, and we compare the fidelity estimation strategy with our and the original NQFE to conventional tomography. It is shown that NQFE can estimate the fidelity with comparable accuracy to the tomography approach. In the future, NQFE will become an important tool for benchmarking quantum states ahead of the advent of well-trusted fault-tolerant quantum computers.

Yi-Kai Liu, Shelby Kimmel

We develop a method for quantum process tomography that combines the efficiency of compressed sensing with the robustness of randomized benchmarking. Our method is robust to state preparation and measurement errors, and it achieves a quadratic speedup over conventional tomography when the unknown process is a generic unitary evolution. Our method is based on PhaseLift, a convex programming technique for phase retrieval. We show that this method achieves approximate recovery of almost all signals, using measurements sampled from spherical or unitary 2-designs. This is the first positive result on PhaseLift using 2-designs. We also show that exact recovery of all signals is possible using unitary 4-designs. Previous positive results for PhaseLift required spherical 4-designs, while PhaseLift was known to fail in certain cases when using spherical 2-designs.