English
Related papers

Related papers: Scalable randomized benchmarking of non-Clifford g…

200 papers

Randomized Benchmarking allows to efficiently and scalably characterize the average error of an unitary 2-design such as the Clifford group $\mathcal{C}$ on a physical candidate for quantum computation, as long as there are no…

Quantum Physics · Physics 2015-11-04 T. Chasseur , F. K. Wilhelm

With the development of controllable quantum systems, fast and practical characterization for multi-qubit gates is essential for building high-fidelity quantum computing devices. The usual way to fulfill this requirement via randomized…

Quantum Physics · Physics 2023-02-10 Yihong Zhang , Wenjun Yu , Pei Zeng , Guoding Liu , Xiongfeng Ma

Accurate benchmarking of quantum gates is crucial for understanding and enhancing the performance of quantum hardware. A standard method for this is interleaved benchmarking, a technique which estimates the error on an interleaved target…

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

Randomized benchmarking (RB) is a widely used strategy to assess the quality of available quantum gates in a computational context. RB involves applying known random sequences of gates to an initial state and using the statistics of a final…

We describe and expand upon the scalable randomized benchmarking protocol proposed in Phys. Rev. Lett. 106, 180504 (2011) which provides a method for benchmarking quantum gates and estimating the gate-dependence of the noise. The protocol…

Quantum Physics · Physics 2012-04-30 Easwar Magesan , Jay M. Gambetta , Joseph Emerson

We implement a complete randomized benchmarking protocol on a system of two superconducting qubits. The protocol consists of randomizing over gates in the Clifford group, which experimentally are generated via an improved two-qubit…

Randomized benchmarking (RB) is an important protocol for robustly characterizing the error rates of quantum gates. The technique is typically applied to the Clifford gates since they form a group that satisfies a convenient technical…

Quantum Physics · Physics 2017-05-26 Robin Harper , Steven T. Flammia

Characterising quantum processes is a key task in and constitutes a challenge for the development of quantum technologies, especially at the noisy intermediate scale of today's devices. One method for characterising processes is randomised…

Quantum Physics · Physics 2018-10-31 Ingo Roth , Richard Kueng , Shelby Kimmel , Yi-Kai Liu , David Gross , Jens Eisert , Martin Kliesch

Randomized benchmarking (RB) is the gold standard for experimentally evaluating the quality of quantum operations. The current framework for RB is centered on groups and their representations, but this can be problematic. For example,…

Quantum Physics · Physics 2022-12-22 Jianxin Chen , Dawei Ding , Cupjin Huang

We describe a practical experimental protocol for robustly characterizing the error rates of non-Clifford gates associated with dihedral groups, including gates in SU(2) associated with arbitrarily small angle rotations. Our dihedral…

Quantum Physics · Physics 2025-08-14 Arnaud Carignan-Dugas , Joel J. Wallman , Joseph Emerson

Typical quantum gate tomography protocols struggle with a self-consistency problem: the gate operation cannot be reconstructed without knowledge of the initial state and final measurement, but such knowledge cannot be obtained without…

As quantum devices scale up, many-body quantum gates and algorithms begin to surpass what is possible to simulate classically. Validation methods which rely on such classical simulation, such as process tomography and randomized…

Randomized benchmarking (RB) is widely used to measure an error rate of a set of quantum gates, by performing random circuits that would do nothing if the gates were perfect. In the limit of no finite-sampling error, the exponential decay…

Quantum Physics · Physics 2017-10-03 Timothy Proctor , Kenneth Rudinger , Kevin Young , Mohan Sarovar , Robin Blume-Kohout

Randomized benchmarking is a useful scheme for evaluation the average fidelity of a noisy quantum circuit. However, it is insensitive to the unitary error. Here, we propose a method of randomized benchmarking in which a unitary t-design is…

Quantum Physics · Physics 2017-12-13 Linxi Zhang , Chuanghua Zhu , Changxing Pei

Randomized benchmarking is a promising tool for characterizing the noise in experimental implementations of quantum systems. In this paper, we prove that the estimates produced by randomized benchmarking (both standard and interleaved) for…

Quantum Physics · Physics 2015-12-18 Joel J. Wallman , Steven T. Flammia

Quantum gate benchmarking is unavoidably influenced by state preparation and measurement errors. Randomized benchmarking addresses this challenge by employing group twirling to regularize the noise channel, then provides a characterization…

Quantum Physics · Physics 2026-02-02 Han Ye , Guoding Liu , Xiongfeng Ma

Recently, there has been an emergence of useful applications for noisy intermediate-scale quantum (NISQ) devices notably, though not exclusively, in the fields of quantum machine learning and variational quantum algorithms. In such…

Quantum Physics · Physics 2021-02-26 Ellen Derbyshire , Rawad Mezher , Theodoros Kapourniotis , Elham Kashefi

Benchmarking methods that can be adapted to multi-qubit systems are essential for assessing the overall or "holistic" performance of nascent quantum processors. The current industry standard is Clifford randomized benchmarking (RB), which…

Noise characterization methods such as randomized benchmarking (RB) are critical for the development of scalable quantum computers. Modern RB protocols for multiqubit systems extract physically relevant error rates by exploiting the…

Quantum Physics · Physics 2026-04-15 Yale Fan , Riley Murray , Thaddeus D. Ladd , Kevin Young , Robin Blume-Kohout