Mitigation of readout noise in near-term quantum devices by classical post-processing based on detector tomography

Maciejewski, Filip B.; Zimborás, Zoltán; Oszmaniec, Michał

doi:10.22331/q-2020-04-24-257

Cited by 203 publications

(217 citation statements)

References 65 publications

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“…The same method was also recently studied by other authors as well, see, e.g., refs. 41,42 . Note that the norm invariance is also satisfied for simple matrix inversion: jjt matrix jj 1 ¼ jjmjj 1 by construction because ||Rx|| 1 = ||x|| 1 for all x so in particular for y = R −1 m, ||Ry|| 1 = ||y|| 1 implies that ||m|| 1 = ||R −1 m|| 1 .…”

Section: Unfolding Methodsmentioning

confidence: 99%

“…In particular, the most popular quantum simulators pyQuil 33 (by Rigetti), Cirq 34,35 (by Google), and XACC [36][37][38] implement a version of matrix inversion, and the other popular simulator Qiskit by IBM 39,40 uses a least squares method (see also refs. 41,42 ) that is the same as the matrix inversion solution when the the latter is nonnegative. Challenges with methods based on matrix inversion will be discussed in more detail below.…”

Section: Introductionmentioning

confidence: 99%

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Unfolding quantum computer readout noise

et al. 2020

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In the current era of noisy intermediate-scale quantum computers, noisy qubits can result in biased results for early quantum algorithm applications. This is a significant challenge for interpreting results from quantum computer simulations for quantum chemistry, nuclear physics, high energy physics (HEP), and other emerging scientific applications. An important class of qubit errors are readout errors. The most basic method to correct readout errors is matrix inversion, using a response matrix built from simple operations to probe the rate of transitions from known initial quantum states to readout outcomes. One challenge with inverting matrices with large off-diagonal components is that the results are sensitive to statistical fluctuations. This challenge is familiar to HEP, where prior-independent regularized matrix inversion techniques (“unfolding”) have been developed for years to correct for acceptance and detector effects, when performing differential cross section measurements. We study one such method, known as iterative Bayesian unfolding, as a potential tool for correcting readout errors from universal gate-based quantum computers. This method is shown to avoid pathologies from commonly used matrix inversion and least squares methods.

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Section: Unfolding Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Unfolding quantum computer readout noise

et al. 2020

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“…In the NISQ era, the quantum simulators are noisy and their performance is affected by the presence of decoherence. There are several attempts to simulate the effect of noise in existing digital quantum simulators [8,21,41,42,46,50,63,77]. Here, although in a very simplistic and rather naive fashion, we model some errors that can serve as a first glimpse into a more realistic scenario.…”

Section: Decoherencementioning

confidence: 99%

Accelerated variational algorithms for digital quantum simulation of many-body ground states

Lyu

Montenegro

Bayat

2020

Quantum

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One of the key applications for the emerging quantum simulators is to emulate the ground state of many-body systems, as it is of great interest in various fields from condensed matter physics to material science. Traditionally, in an analog sense, adiabatic evolution has been proposed to slowly evolve a simple Hamiltonian, initialized in its ground state, to the Hamiltonian of interest such that the final state becomes the desired ground state. Recently, variational methods have also been proposed and realized in quantum simulators for emulating the ground state of many-body systems. Here, we first provide a quantitative comparison between the adiabatic and variational methods with respect to required quantum resources on digital quantum simulators, namely the depth of the circuit and the number of two-qubit quantum gates. Our results show that the variational methods are less demanding with respect to these resources. However, they need to be hybridized with a classical optimization which can converge slowly. Therefore, as the second result of the paper, we provide two different approaches for speeding the convergence of the classical optimizer by taking a good initial guess for the parameters of the variational circuit. We show that these approaches are applicable to a wide range of Hamiltonian and provide significant improvement in the optimization procedure.

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“…Much recent work has been published on detecting, quantifying, and modeling crosstalk and crosstalk errors in quantum computing devices [6,42,18,44,51,39,16,23,49,50,48,17,2,19,21,11,35]. Variants of Ramsey sequences have been used to detect and quantify coherent coupling between qubits [2].…”

Section: Introductionmentioning

confidence: 99%

“…This technique is very hardware-specific and typically limited to detecting crosstalk in the form of unwanted Hamiltonian couplings of known form. Several groups have also demonstrated mitigation of crosstalk in readout lines by detailed characterization and compensation [23,49,11,35] (see also Supplementary Information in Refs. [6,42,16,19,21]).…”

Section: Introductionmentioning

confidence: 99%

Detecting crosstalk errors in quantum information processors

Sarovar

Proctor

Rudinger

et al. 2020

Quantum

166

100

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Crosstalk occurs in most quantum computing systems with more than one qubit. It can cause a variety of correlated and nonlocal crosstalk errors that can be especially harmful to fault-tolerant quantum error correction, which generally relies on errors being local and relatively predictable. Mitigating crosstalk errors requires understanding, modeling, and detecting them. In this paper, we introduce a comprehensive framework for crosstalk errors and a protocol for detecting and localizing them. We give a rigorous definition of crosstalk errors that captures a wide range of disparate physical phenomena that have been called ``crosstalk'', and a concrete model for crosstalk-free quantum processors. Errors that violate this model are crosstalk errors. Next, we give an equivalent but purely operational (model-independent) definition of crosstalk errors. Using this definition, we construct a protocol for detecting a large class of crosstalk errors in a multi-qubit processor by finding conditional dependencies between observed experimental probabilities. It is highly efficient, in the sense that the number of unique experiments required scales at most cubically, and very often quadratically, with the number of qubits. We demonstrate the protocol using simulations of 2-qubit and 6-qubit processors.

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Mitigation of readout noise in near-term quantum devices by classical post-processing based on detector tomography

Cited by 203 publications

References 65 publications

Unfolding quantum computer readout noise

Unfolding quantum computer readout noise

Accelerated variational algorithms for digital quantum simulation of many-body ground states

Detecting crosstalk errors in quantum information processors

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