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arXiv:1309.6405

Error matrices in quantum process tomography

Alexander N. Korotkov

Published Sep 25, 2013• 9 citations
arXivHTMLPDF

Abstract

We discuss characterization of experimental quantum gates by the error matrix, which is similar to the standard process matrix $χ$ 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.

DOI
10.48550/arxiv.1309.6405

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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.
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Abstract We present a tomographic protocol for the characterization of multiqubit quantum channels. We discuss a specific class of input states, for which the set of Pauli measurements at the output of the channel directly relates to its Pauli transfer matrix components. We compare our results to those of standard quantum process tomography, showing an exponential reduction in the number of different experimental configurations required by a single matrix element extraction, while keeping the same number of shots. This paves the way for more efficient experimental implementations, whenever a selective knowledge of the Pauli transfer matrix is needed. We provide several examples and simulations.
As progress is made towards the first generation of error-corrected quantum computers, robust characterization and validation protocols are required to assess the noise environments of physical quantum processors. While standard coherence metrics and characterization protocols such as T1{T}_{1}T1​ and T2{T}_{2}T2​, process tomography, and randomized benchmarking are now ubiquitous, these techniques provide only partial information about the dynamic multiqubit loss channels responsible for processor errors, which can be described more fully by a Lindblad operator in the master equation formalism. Here, we introduce and experimentally demonstrate Lindblad tomography, a hardware-agnostic characterization protocol for tomographically reconstructing the Hamiltonian and Lindblad operators of a quantum noise environment from an ensemble of time-domain measurements. Performing Lindblad tomography on a small superconducting quantum processor, we show that this technique naturally builds on standard process tomography and T1/T2{T}_{1}/{T}_{2}T1​/T2​ measurement protocols, characterizes and accounts for state-preparation and measurement errors, and allows one to place bounds on the fit to a Markovian model. Comparing the results of single- and two-qubit measurements on a superconducting quantum processor, we demonstrate that Lindblad tomography can also be used to identify and quantify sources of crosstalk on quantum processors, such as the presence of always-on qubit-qubit interactions.
We show that the Fano representation leads to a particularly simple and appealing form of the quantum process tomography matrix ${\ensuremath{\chi}}_{F}$, in that the matrix ${\ensuremath{\chi}}_{F}$ is real, the number of matrix elements is exactly equal to the number of free parameters required for the complete characterization of a quantum operation, and these matrix elements are directly related to evolution of the expectation values of the system's polarization measurements. These facts are illustrated in the examples of one- and two-qubit quantum noise channels.