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We present a systematic investigation of deep learning methods applied to quantum error mitigation of noisy output probability distributions from measured quantum circuits. We compare different architectures, from fully connected neural…

In this work, drawing inspiration from the type of noise present in real hardware, we study the output distribution of random quantum circuits under practical non-unital noise sources with constant noise rates. We show that even in the…

Quantum Physics · Physics 2023-06-30 Bill Fefferman , Soumik Ghosh , Michael Gullans , Kohdai Kuroiwa , Kunal Sharma

Noisy Intermediate-Scale Quantum (NISQ) devices fail to produce outputs with sufficient fidelity for deep circuits with many gates today. Such devices suffer from read-out, multi-qubit gate and crosstalk noise combined with short…

Quantum Physics · Physics 2021-07-15 Ellis Wilson , Frank Mueller , Lindsay Bassman , Constin Iancu

Contemporary methods for benchmarking noisy quantum processors typically measure average error rates or process infidelities. However, thresholds for fault-tolerant quantum error correction are given in terms of worst-case error rates --…

Quantum error mitigation (QEM) is vital for noisy intermediate-scale quantum (NISQ) devices. While most conventional QEM schemes assume discrete gate-based circuits with noise appearing either before or after each gate, the assumptions are…

Quantum Physics · Physics 2021-03-12 Jinzhao Sun , Xiao Yuan , Takahiro Tsunoda , Vlatko Vedral , Simon C. Bejamin , Suguru Endo

The most common error models for quantum computers assume the independence of errors on different qubits. However, most noise mechanisms have some correlations in space. We show how to improve quantum information processing for few-qubit…

Quantum Physics · Physics 2018-12-19 Vickram N. Premakumar , Robert Joynt

Current quantum computers suffer from non-stationary noise channels with high error rates, which undermines their reliability and reproducibility. We propose a Bayesian inference-based adaptive algorithm that can learn and mitigate quantum…

Quantum Physics · Physics 2023-08-30 Samudra Dasgupta , Arshag Danageozian , Travis S. Humble

Giving a convincing experimental evidence of the quantum supremacy over classical simulations is a challenging goal. Noise is considered to be the main problem in such a demonstration, hence it is urgent to understand the effect of noise.…

Quantum Physics · Physics 2022-03-08 Valery Shchesnovich

Randomized benchmarking has emerged as a popular and easy-to-implement experimental technique for gauging the quality of gate operations in quantum computing devices. A typical randomized benchmarking procedure identifies the exponential…

Quantum Physics · Physics 2021-02-24 Jiaan Qi , Hui Khoon Ng

A critical question for the field of quantum computing in the near future is whether quantum devices without error correction can perform a well-defined computational task beyond the capabilities of state-of-the-art classical computers,…

Expectation values of measurement operators, interpreted as measurement probabilities, arise frequently throughout quantum algorithms. When quantum states are randomly distributed, their expectation values are also randomly distributed. In…

Quantum Physics · Physics 2026-04-08 Matthew Duschenes , Roger G. Melko , Juan Carrasquilla , Raymond Laflamme

We consider quantum state transfer in a fully connected spin network, in which the results indicate that it is impossible to achieve high fidelity by free dynamics. However, the addition of certain kinds of noise can be helpful for this…

Quantum Physics · Physics 2015-06-16 Morteza Rafiee , Cosmo Lupo , Stefano Mancini

Remarkable experimental advances in quantum computing are exemplified by recent announcements of impressive average gate fidelities exceeding 99.9% for single-qubit gates and 99% for two-qubit gates. Although these high numbers engender…

Quantum Physics · Physics 2015-12-29 Yuval R Sanders , Joel J Wallman , Barry C Sanders

Meaningful quantum computing is currently bottlenecked by the error rates of current generation Noisy Intermediate Scale Quantum (NISQ) devices. To improve the fidelity of the quantum logic gates, it is essential to recognize the…

Virtual distillation has been proposed as an error mitigation protocol for estimating the expectation values of observables in quantum algorithms. It proceeds by creating a cyclic permutation of $M$ noisy copies of a quantum state using a…

Quantum Physics · Physics 2024-08-21 Pontus Vikstål , Giulia Ferrini , Shruti Puri

Quantum noise is conventionally viewed as a fundamental obstacle in near-term quantum computing, motivating extensive error correction and mitigation strategies. We present numerical evidence that challenges this consensus. Through…

Quantum Physics · Physics 2026-01-21 Linghua Zhu , Yulong Dong , Ziyu Zhang , Xiaosong Li

We present a detailed derivation of the master equation describing a general time-dependent quantum system with classical Poisson white noise and outline its various properties. We discuss the limiting cases of Poisson white noise and…

Quantum Physics · Physics 2017-01-17 Anthony Kiely , J. Gonzalo Muga , Andreas Ruschhaupt

The implementation of quantum gates with fidelities that exceed the threshold for reliable quantum computing requires robust gates whose performance is not limited by the precision of the available control fields. The performance of these…

Quantum Physics · Physics 2015-12-30 Alexandre M. Souza , Roberto S. Sarthour , Ivan S. Oliveira , Dieter Suter

We investigate the impact of a local random unitary noise on multipartite quantum states of an arbitrary dimension. We follow the dynamical approach, in which the single-particle unitaries are generated by local random Hamiltonians.…

Randomized benchmarking (RB) is an efficient and robust method to characterize gate errors in quantum circuits. Averaging over random sequences of gates leads to estimates of gate errors in terms of the average fidelity. These estimates are…

Quantum Physics · Physics 2019-09-11 Jonas Helsen , Joel J. Wallman , Steven T. Flammia , Stephanie Wehner