Efficient quantum readout-error mitigation for sparse measurement outcomes of near-term quantum devices

Abstract

The readout error on near-term quantum devices is one of the dominant noise factors, which can be mitigated by classical postprocessing called quantum readout error mitigation (QREM). The standard QREM applies the inverse of noise calibration matrix to the outcome probability distribution using exponential computational resources to the number of measured qubits. This becomes infeasible for the current quantum devices with tens of qubits or more. Here we propose two efficient QREM methods finishing in $O(n{s}^2)$ time for probability distributions of $n$ qubits and $s$ shots, which mainly aim at mitigating sparse probability distributions such that only a few states are dominant. We compare the proposed methods with several recent QREM methods in the following three cases: expectation values of the GHZ state, its fidelities, and the estimation error of maximum likelihood amplitude estimation (MLAE) algorithm with a modified Grover iterator. The two cases of the GHZ state are on real IBM quantum devices, while the third is with numerical simulation. Using the proposed method, the mitigation of the 65-qubit GHZ state takes only a few seconds, and we witness the fidelity of the 29-qubit GHZ state exceeding 0.5. The proposed methods also succeed in reducing the estimation error in the MLAE algorithm, outperforming the results by other QREM methods in general.

13 pages, 10 figures, presented at the poster session in Asian Quantum Information Science (AQIS) Conference 2021

References in corpus (18)

• A Quantum Approximate Optimization Algorithm
• Hybrid quantum-classical algorithms and quantum error mitigation
• Measuring measurement
• Mitigating measurement errors in multi-qubit experiments
• Scalable mitigation of measurement errors on quantum computers
• Learning-based quantum error mitigation
• Optimal Quantum Measurements of Expectation Values of Observables
• Model-free readout-error mitigation for quantum expectation values
• Robust shadow estimation
• Mitigating realistic noise in practical noisy intermediate-scale quantum devices
• Generation and verification of 27-qubit Greenberger-Horne-Zeilinger states in a superconducting quantum computer
• Generalized quantum subspace expansion
• Low depth algorithms for quantum amplitude estimation
• Optimal resource cost for error mitigation
• Prospects and challenges of quantum finance
• Amplitude estimation via maximum likelihood on noisy quantum computer
• Readout Rebalancing for Near Term Quantum Computers
• Modified Grover operator for amplitude estimation

Cited by in corpus (22)

• Statistical phase estimation and error mitigation on a superconducting quantum processor
• Characterization of entanglement on superconducting quantum computers of up to 414 qubits
• Experimental demonstration of scalable cross-entropy benchmarking to detect measurement-induced phase transitions on a superconducting quantum processor
• Testing Scalable Bell Inequalities for Quantum Graph States on IBM Quantum Devices
• Quantum State Tomography with Locally Purified Density Operators and Local Measurements
• Quantum error mitigation for Fourier moment computation
• Teleporting two-qubit entanglement across 19 qubits on a superconducting quantum computer
• Superconducting Quantum Simulation for Many-Body Physics beyond Equilibrium
• Empirical learning of dynamical decoupling on quantum processors
• Statistics of topological defects across a phase transition in a digital superconducting quantum processor
• Low-Rank Variational Quantum Algorithm for the Dynamics of Open Quantum Systems
• Practical techniques for high-precision measurements on near-term quantum hardware and applications in molecular energy estimation
• Perturbative readout error mitigation for near term quantum computers
• Multireference error mitigation for quantum computation of chemistry
• Quantum noise modeling through Reinforcement Learning
• Resource-efficient Generalized Quantum Subspace Expansion
• Achieving computational gains with quantum error-correction primitives: Generation of long-range entanglement enhanced by error detection
• Bayesian mitigation of measurement errors in multiqubit experiments
• Reduced Sampling Overhead for Probabilistic Error Cancellation by Pauli Error Propagation
• Q-Cluster: Quantum Error Mitigation Through Noise-Aware Unsupervised Learning
• Feedforward suppression of readout-induced faults in quantum error correction
• Simplifying errors by symmetry and randomisation