Other system-level benchmarking protocols

Protocols based on the Quantum Volume

Quantum Volume (QV) (2017) [1]
In a nutshell, the Quantum Volume (QV) evaluates the ability of a quantum computer to reliably run a square circuit. A quantum computer with a Quantum Volume (QV) of size \(n\) is able to reliably execute a quantum circuit with at most \(n\) qubits with maximum gate depth \(n\).
Circuit Layer Operation per Second (CLOPS) (2021) [2]
In a nutshell, the CLOPS protocol evaluates the number of layers of gates that can be successfully realized on a quantum computer in a single second. This protocol is based on the Quantum Volume protocol.

Quantum Linpack (2020) [3]
In a nutshell, the quantum LINPACK proposal aims to evaluate the capability of a quantum computer to block-encode a randomly generated matrix. This step is necessary for solving Quantum Linear System Problems (QLSP). The block-encoding is accomplished efficiently by constructing a random quantum circuit and defining the corresponding random matrix. The success of the operation is evaluated by estimating the probability of measuring the ancilla qubits of the block encoding step (generally one or two qubits depending on the type of the matrix being generated) in the \(\ket{0}\) state. This empirical probability is then compared to the ideal outcome obtained via exact classical simulation to assess the relative error of the quantum computer process.
Quantum Unitary Evolution Score (QUES) (2021) [4]
In a nutshell, the QUES score evaluates the ability of a quantum computer to reliably execute a minimal implementation of the Quantum Singular Value Transformation (QSVT) algorithm. This protocol involves \(n\) plus one ancilla qubit where \(n\) is set by the user. Notably, the scheme is scalable, as it requires measurement of only a single qubit, and it provides an estimate of the fidelity of the overall quantum operation.

Reliable Quantum Operations Per Second (rQOPS) (2023) [5]
In a nutshell, the rQOPS score measures the number of logical operations that a large-scale fault-tolerant quantum computer can realize per second.

[1]A. W. Cross, L. S. Bishop, S. Sheldon, P. D. Nation, and J. M. Gambetta, “Validating quantum computers using randomized model circuits,” Physical Review A, vol. 100, no. 3, p. 032328, 2019.
[2]A. Wack et al., “Quality, Speed, and Scale: three key attributes to measure the performance of near-term quantum computers.” 2021 [Online]. Available at: https://arxiv.org/abs/2110.14108
[3]Y. Dong and L. Lin, “Random circuit block-encoded matrix and a proposal of quantum LINPACK benchmark,” Physical Review A, vol. 103, no. 6, p. 062412, 2021.
[4]Y. Dong, K. B. Whaley, and L. Lin, “A quantum hamiltonian simulation benchmark,” npj Quantum Information, vol. 8, no. 1, Nov. 2022, doi: 10.1038/s41534-022-00636-x. [Online]. Available at: http://dx.doi.org/10.1038/s41534-022-00636-x
[5]C. Nayak, “Microsoft achieves first milestone towards a quantum supercomputer.” 2023 [Online]. Available at: https://azure.microsoft.com/en-us/blog/quantum/2023/06/21/microsoft-achieves-first-milestone-towards-a-quantum-supercomputer/