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arXiv:2103.01928 · PRX Quantum

A Taxonomy of Small Markovian Errors

Robin Blume-Kohout, Marcus Palmer Da Silva, Erik Nielsen, Timothy J Proctor, Kenneth Rudinger, Mohan Sarovar, Kevin Young

Published May 13, 2022• 46 citations
arXivHTMLPDF

Abstract

Errors in quantum logic gates are usually modeled by quantum process matrices (CPTP maps).But process matrices can be opaque and unwieldy.We show how to transform the process matrix of a gate into an error generator that represents the same information more usefully.We construct a basis of simple and physically intuitive elementary error generators, classify them, and show how to represent the error generator of any gate as a mixture of elementary error generators with various rates.Finally, we show how to build a large variety of reduced models for gate errors by combining elementary error generators and/or entire subsectors of generator space.We conclude with a few examples of reduced models, including one with just 9N 2 parameters that describes almost all commonly predicted errors on an N -qubit processor.

DOI
10.1103/prxquantum.3.020335

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Errors in quantum logic gates are usually modeled by quantum process matrices (CPTP maps).But process matrices can be opaque and unwieldy.We show how to transform the process matrix of a gate into an error generator that represents the same information more usefully.We construct a basis of simple and physically intuitive elementary error generators, classify them, and show how to represent the error generator of any gate as a mixture of elementary error generators with various rates.Finally, we show how to build a large variety of reduced models for gate errors by combining elementary error generators and/or entire subsectors of generator space.We conclude with a few examples of reduced models, including one with just 9N 2 parameters that describes almost all commonly predicted errors on an N -qubit processor.
Noisy logic operations on a quantum computational register -- e.g., one or more qubits -- can be described by transfer matrices (a.k.a. CPTP maps or superoperators) that act linearly on the density matrix representing the register's quantum state. Collectively, these operations form a gate set. Gate sets have a gauge freedom; many gate sets that appear different actually predict the same experimental outcomes. A property of a gate set can be observable (and thus physically relevant) only if it is gauge-invariant. Unfortunately, no good gauge-invariant parameterizations of gate sets are known. We introduce the next best thing, a perturbative gauge-invariant parameterization of small Markovian errors in gate sets. We construct vector spaces of properties that are first-order gauge-invariant (FOGI). We show how to construct and understand FOGI properties, how to use them as coordinates to parameterize gate sets without gauge freedom, and how to extract approximately gauge-invariant error metrics.
We discuss characterization of experimental quantum gates by the error matrix, which is similar to the standard process matrix χχχ in the Pauli basis, except the desired unitary operation is factored out, by formally placing it either before or after the error process. The error matrix has only one large element, which is equal to the process fidelity, while other elements are small and indicate imperfections. The imaginary parts of the elements along the left column and/or top row directly indicate the unitary imperfection and can be used to find the needed correction. We discuss a relatively simple way to calculate the error matrix for a composition of quantum gates. Similarly, it is rather straightforward to find the first-order contribution to the error matrix due to the Lindblad-form decoherence. We also discuss a way to identify and subtract the tomography procedure errors due to imperfect state preparation and measurement. In appendices we consider several simple examples of the process tomography and also discuss an intuitive physical interpretation of the Lindblad-form decoherence.
Physical models of quantum gates can directly incorporate experimental degrees of freedom, such as laser power or microwave phase, but the forward simulation required to use these models can result in impractical overhead in computational time.In this poster, we develop a method for efficient, accurate interpolation of quantum process matrices over physical parameter space, and we apply our method to study the sensitivity of quantum applications at both the gate level and circuit level.We then implement an extension of gate-set tomography (GST) that provides a comprehensive view into the errors suffered by a quantum information processor.In its standard form, GST fits a general Markovian model to experimental data in terms of process matrices that are often difficult to interpret.Our extension to this method uses process matrices interpolated over physical parameters in the optimization loop of GST to directly estimate physical model parameters, providing a clear description of the errors in a quantum processor, while reducing the required number of GST sequences by orders of magnitude compared to its standard form.
Abstract A key requirement for an effective quantum error correction (QEC) scheme is that the physical qubits have error rates below a certain threshold. The value of this threshold depends on the details of the specific QEC scheme, and its hardware-level implementation. This is especially important with parity-check circuits, which are the fundamental building blocks of QEC codes. The standard way of constructing the parity check circuit is using a universal set of gates, namely sequential CNOT gates, single-qubit rotations and measurements. We exploit the insight that a QEC code does not require universal logic gates, but can be simplified to perform the sole task of error detection and correction. By building gates that are fundamental to QEC, we can boost the threshold and ease the experimental demands on the physical hardware. We present a rigorous formalism for constructing and verifying the error behavior of these gates, linking the physical measurement of a process matrix to the abstract error models commonly used in QEC analysis. This allows experimentalists to directly map the gates used in their systems to thresholds derived for a broad-class of QEC codes. We give an example of these new constructions using the model system of two nuclear spins, coupled to an electron spin, showing the potential benefits of redesigning fundamental gate sets using QEC primitives, rather than traditional gate sets reliant on simple single and two-qubit gates.
We develop an analytic perturbative framework that enables the analysis of small Markovian errors in probabilistic, photon-heralded quantum operations between non-interacting emitters. Building on and extending the Zero-Photon-Generation (ZPG) framework, we derive closed-form perturbative solutions that capture both ideal (zero-order) and noisy (low-order) gate dynamics conditioned on time-integrated photon counting. Our framework provides analytic solutions to process matrices and Pauli error weights up to leading order, bridging the gap between detailed physical imperfections of a system and its corresponding abstract Pauli noise models. Moreover, our framework captures imperfections across the full physical system stack, from photon generation to optical manipulation. We benchmark the resulting perturbative predictions on a repeat-until-success CZ gate against numerical simulations, demonstrating accurate modeling of source-induced noise, and then apply the same framework to analyze coherent phase-shifter miscalibrations as a representative example of optical-manipulation errors. The methods developed in this work enable physics-informed parameter tuning to optimize gate designs and develop tailored quantum error correction protocols toward fault-tolerant quantum computing using hybrid light--matter quantum systems.
One of the largest obstacles to building a quantum computer is gate error, where the physical evolution of the state of a qubit or group of qubits during a gate operation does not match the intended unitary transformation. Gate error stems from a combination of control errors and random single qubit errors from interaction with the environment. While great strides have been made in mitigating control errors, intrinsic qubit error remains a serious problem that limits gate fidelity in modern qubit architectures. Simultaneously, recent developments of small error-corrected logical qubit devices promise significant increases in logical state lifetime, but translating those improvements into increases in gate fidelity is a complex challenge. In this Letter, we construct protocols for gates on and between small logical qubit devices which inherit the parent device's tolerance to single qubit errors which occur at any time before or during the gate. We consider two such devices, a passive implementation of the three-qubit bit flip code, and the author's own [E. Kapit, Phys. Rev. Lett. 116, 150501 (2016)PRLTAO0031-900710.1103/PhysRevLett.116.150501] very small logical qubit (VSLQ) design, and propose error-tolerant gate sets for both. The effective logical gate error rate in these models displays superlinear error reduction with linear increases in single qubit lifetime, proving that passive error correction is capable of increasing gate fidelity. Using a standard phenomenological noise model for superconducting qubits, we demonstrate a realistic, universal one- and two-qubit gate set for the VSLQ, with error rates an order of magnitude lower than those for same-duration operations on single qubits or pairs of qubits. These developments further suggest that incorporating small logical qubits into a measurement based code could substantially improve code performance.