SchWARMA: A model-based approach for time-correlated noise in quantum circuits

Schultz, Kevin; Quiroz, Gregory; Titum, Paraj; Clader, B. D.

doi:10.1103/physrevresearch.3.033229

Cited by 9 publications

(8 citation statements)

References 70 publications

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“…In this section, we study how these different methods affect the performance of ZNE in the presence of timecorrelated noise. For all the simulations presented in this section we used the following Python libraries: Mezze [67] for modeling SchWARMA noise, Mezze's TensorFlow Quantum [77] interface for simulating quantum circuits and Mitiq [70] for applying unitary folding and zero-noise extrapolation.…”

Section: Resultsmentioning

confidence: 99%

“…In the SchWARMA formalism, there is not a mechanism for stretching pulses per se as it operates at the gate level in a circuit (without pulse-level control on H c (t)). However, as discussed in the supplement to [67], it is possible to manipulate and stretch the spectrum of a SchWARMA model. So, for the task of numerically simulating pulse stretching, instead of implementing equation Eq.…”

Section: B Zero-noise Extrapolation With Colored Noisementioning

confidence: 99%

“…The recently developed [67] and experimentally validated [68] Schrödinger wave autoregressive moving average (SchWARMA) technique provides a natural mechanism for the exploration of so-called digital ZNE techniques [51,52,69] that operate at the gate level in a quantum circuit. Building on techniques from classical time-series modeling in statistics and signal processing, SchWARMA was conceived as a highly flexible mechanism for simulating a wide-range of spatiotemporally correlated errors in quantum circuits.…”

Section: Introductionmentioning

confidence: 99%

“…In the SchWARMA modeling approach [67], the impact of the continuous time Hamiltonian in (1) is modeled in a quantum circuit formalism by inserting correlated Z-error operators after each "gate" determined by the control H c . This is accomplished by generating a timecorrelated sequence of rotation angles y k defined from independent Gaussian inputs x k using an autoregressive moving average (ARMA) model [71,72],…”

Section: Introductionmentioning

confidence: 99%

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Reducing the impact of time-correlated noise on zero-noise extrapolation

Schultz¹,

LaRose²,

Mari³

et al. 2022

Preprint

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Zero-noise extrapolation is a quantum error mitigation technique that has typically been studied under the ideal approximation that the noise acting on a quantum device is not time-correlated. In this work, we investigate the feasibility and performance of zero-noise extrapolation in the presence of time-correlated noise. We show that, in contrast to white noise, time-correlated noise is harder to mitigate via zero-noise extrapolation because it is difficult to scale the noise level without also modifying its spectral distribution. This limitation is particularly strong if "local" gate-level methods are applied for noise scaling. However, we find that "global" noise scaling methods, e.g., global unitary folding, can be sufficiently reliable even in the presence of time-correlated noise. We also introduce gate Trotterization as a new noise scaling technique that may be of independent interest.

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Section: Resultsmentioning

confidence: 99%

Section: B Zero-noise Extrapolation With Colored Noisementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Reducing the impact of time-correlated noise on zero-noise extrapolation

Schultz¹,

LaRose²,

Mari³

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

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“…Moreover, the noise characterization in model devices [69] and the impact of non-Markovian types of noise could be further evaluated [21,70]. Future development in QuTiP aims at providing a unified interface to the open system solvers, which would enable a simpler integration with qutip-qip.…”

Section: Discussionmentioning

confidence: 99%

Pulse-level noisy quantum circuits with QuTiP

Ahmed

Saraogi

et al. 2022

Quantum

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The study of the impact of noise on quantum circuits is especially relevant to guide the progress of Noisy Intermediate-Scale Quantum (NISQ) computing. In this paper, we address the pulse-level simulation of noisy quantum circuits with the Quantum Toolbox in Python (QuTiP). We introduce new tools in qutip-qip, QuTiP's quantum information processing package. These tools simulate quantum circuits at the pulse level, leveraging QuTiP's quantum dynamics solvers and control optimization features. We show how quantum circuits can be compiled on simulated processors, with control pulses acting on a target Hamiltonian that describes the unitary evolution of the physical qubits. Various types of noise can be introduced based on the physical model, e.g., by simulating the Lindblad density-matrix dynamics or Monte Carlo quantum trajectories. In particular, the user can define environment-induced decoherence at the processor level and include noise simulation at the level of control pulses. We illustrate how the Deutsch-Jozsa algorithm is compiled and executed on a superconducting-qubit-based processor, on a spin-chain-based processor and using control optimization algorithms. We also show how to easily reproduce experimental results on cross-talk noise in an ion-based processor, and how a Ramsey experiment can be modeled with Lindblad dynamics. Finally, we illustrate how to integrate these features with other software frameworks.

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