The QED-C committee released (Feb 2023) a second pre-print of a paper describing the addition of combinatorial optimzation problems as advanced application-oriented benchmarks at: The QED-C committee which developed these benchmarks released (Oct 2021) a pre-print of a paper describing the theory and methdology supporting this work at
#Performance benchmark computer code#
They are designed to provide for users a quantum "jump start", so to speak, eliminating the need to develop for themselves uniform code patterns that facilitate quick development, deployment and experimentation. At the current stage in the evolution of quantum computing hardware, some applications will perform better on one hardware target, while a completely different set may execute better on another target. The application / algorithmic examples are structured using a uniform pattern for defining circuits, executing across different platforms, collecting results, and measuring the performance and fidelity in useful ways.Ī wide variety of "reference applications" are provided. Rather, they are offered as simple "prototypes", designed to make it as easy as possible for users to execute simple "reference applications" across multiple quantum computing APIs and platforms. Important Note - The examples maintained in this repository are not intended to be viewed as "performance standards". The repository is maintained by members of the Quantum Economic Development Consortium (QED-C) Technical Advisory Committee on Standards and Performance Metrics (Standards TAC). This repository contains a collection of prototypical application- or algorithm-centric benchmark programs designed for the purpose of characterizing the end-user perception of the performance of current-generation Quantum Computers. Reference: “Measuring the capabilities of quantum computers” by Timothy Proctor, Kenneth Rudinger, Kevin Young, Erik Nielsen and Robin Blume-Kohout, 20 December 2021, Nature Physics.Application-Oriented Performance Benchmarks for Quantum Computing Our method is the first tool for probing these error effects at scale.” “This is the first time these effects have been observed in many-qubit processors. “By applying our method to current quantum computers, we were able to learn a lot about the errors that these particular devices suffer - because different types of errors affect different programs a different amount,” Proctor said.
#Performance benchmark computer how to#
The mirror-circuit method also gives scientists greater insight into how to improve current quantum computers. “Our benchmarking experiments revealed that the performance of current quantum computers is much more variable on structured programs” than was previously known, Proctor said.
When an error is compounded it grows worse as the program runs, like a wide receiver who runs the wrong route, straying farther and farther from where they are supposed to be as the play goes on.īy mimicking functional programs, Sandia found final results often had larger discrepancies than randomized tests showed. Proctor and his colleagues found that randomized tests miss or underestimate the compound effects of errors. New method reveals flaws in conventional performance ratings Sandia is a leading member of the Quantum Systems Accelerator, a Department of Energy national quantum research center. The research was funded by the Department of Energy’s Office of Science and Sandia’s Laboratory Directed Research and Development program. So instead of waiting, scientists can immediately check the quantum computer’s result. With a mirror circuit, however, the output should always be the same as the input or some intentional modification. However, because quantum computers perform certain calculations much faster than conventional computers, researchers can spend a long time waiting for the regular computers to finish. If there are no errors, the results should match. Most benchmark tests check for errors by running the same set of instructions on a quantum machine and a conventional computer. The new testing method also saves time, which will help researchers evaluate increasingly sophisticated machines. “It is standard practice in the quantum computing community to use only random, disordered programs to measure performance, and our results show that this is not a good thing to do,” said computer scientist Timothy Proctor, a member of Sandia’s Quantum Performance Laboratory who participated in the research. Credit: Tim Proctor, Sandia National Laboratories Sandia National Laboratories computer scientist Tim Proctor is the first author on the Nature Physics paper describing a new way to benchmark quantum computers.
0 kommentar(er)
