Self-consistent quantum measurement tomography based on semidefinite programming

Abstract

We propose an estimation method for quantum measurement tomography (QMT) based on semidefinite programming (SDP), and discuss how it may be employed to detect experimental imperfections, such as shot noise and/or faulty preparation of the input states on near-term quantum computers. Moreover, if the positive operator-valued measure (POVM) we aim to characterize is informationally complete, we put forward a method for self-consistent tomography, i.e., for recovering a set of input states and POVM effects that is consistent with the experimental outcomes and does not assume any a priori knowledge about the input states of the tomography. Contrary to many methods that have been discussed in the literature, our approach does not rely on additional assumptions such as low noise or the existence of a reliable subset of input states.

Accepted version

References in corpus (17)

• Experimental Quantum State Tomography of Optical Fields and Ultrafast Statistical Sampling
• Measuring measurement
• Scalable mitigation of measurement errors on quantum computers
• Gate Set Tomography
• Efficient estimation of Pauli observables by derandomization
• Measuring Measurement: Theory and Practice
• Learning to Measure: Adaptive Informationally Complete Generalized Measurements for Quantum Algorithms
• Mapping coherence in measurement via full quantum tomography of a hybrid optical detector
• Semidefinite Programming in Quantum Information Science
• Recursive quantum detector tomography
• A proposed testbed for detector tomography
• Modeling and mitigation of cross-talk effects in readout noise with applications to the Quantum Approximate Optimization Algorithm
• Universal compressive characterization of quantum dynamics
• Experimental Bayesian estimation of quantum state preparation, measurement, and gate errors in multi-qubit devices
• Efficient tomography with unknown detectors
• Modern compressive tomography for quantum information science
• Self-consistent state and measurement tomography with fewer measurements

Cited by in corpus (10)

• Tensor network noise characterization for near-term quantum computers
• Enhancing quantum state tomography via resource-efficient attention-based neural networks
• Gradient-descent methods for fast quantum state tomography
• Estimating molecular thermal averages with the quantum equation of motion and informationally complete measurements
• Practical techniques for high-precision measurements on near-term quantum hardware and applications in molecular energy estimation
• Mitigating the measurement overhead of ADAPT-VQE with optimised informationally complete generalised measurements
• Bayesian mitigation of measurement errors in multiqubit experiments
• Selective and efficient quantum state tomography for multi-qubit systems
• Calibration of syndrome measurements in a single experiment
• Improving shadow estimation with locally-optimal dual frames