Two UCLA computer scientists have shown that existing compilers that tell quantum computers how to use their circuitry to run quantum programs affect the computers̵
The computer scientists have created a family of benchmark quantum circuits with known optimal depths or sizes. In computer design, the smaller the circuit depth, the faster a calculation can be completed. Smaller circuits also mean that more calculations can be packed into the existing quantum computer. Quantum computer designers could use these benchmarks to improve design tools that could then find the best circuit design.
“We believe in ‘measure, then improve,'” said lead researcher Jason Cong, professor of computer science at UCLA’s Samueli School of Engineering. “Now that we have uncovered the large optimality gap, we are on our way to developing better quantum compilation tools, and we hope the entire quantum research community will too.”
Cong and PhD student Daniel (Bochen) Tan tested their benchmarks in four of the most widely used quantum compilation tools. A study of their research was published in IEEE transactions on computers, a peer-reviewed journal.
Tan and Cong have made the benchmarks available under the name QUEKO as open source and in the software repository GitHub.
Quantum computers use quantum mechanics to perform many calculations at the same time, which can make them exponentially faster and more powerful than the best supercomputers today. However, many issues must be addressed before these devices can leave the research laboratory.
For example, due to the sensitivity of how quantum circuits work, tiny environmental changes such as B. small temperature fluctuations that disrupt quantum computation. In this case, the quantum circuits are called decoherent, ie they have lost the information encoded in them.
“If we can consistently halve the circuit depth through better layout synthesis, we are effectively doubling the time it takes for a quantum device to become decoherent,” said Cong.
“This compilation research could effectively extend that time and would represent a tremendous advance in experimental physics and electrical engineering,” added Cong. “We therefore expect that these benchmarks will motivate both academia and industry to develop better tools for layout synthesis, which in turn will help drive advances in quantum computing.”
Cong and his colleagues made similar efforts in the early 2000s to optimize the design of integrated circuits in classic computers. This research has effectively driven two generations of advances in computer processing speed using only one optimized layout design that shortened the spacing between the transistors that make up the circuit. This cost-effective improvement has been achieved without further major investment in technological advances such as physically shrinking the circuitry itself.
“The quantum processors in existence today are extremely limited by environmental disturbances, which severely limits the length of computations that can be performed,” said Mark Gyure, executive director of the UCLA Center for Quantum Science and Technology, who was not involved in the study. “This is why the recent research by Professor Cong’s group is so important because it has shown that most implementations of quantum circuits to date are likely to be extremely inefficient, and more optimally compiled circuits could allow much longer algorithms to run. This could lead to today’s processors a lot Solving more interesting problems than previously thought. This is extremely important advancement for the field and incredibly exciting. ”
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Bochen Tan et al., Optimality Study of Existing Quantum Computer Layout Synthesis Tools, IEEE transactions on computers (2020). DOI: 10.1109 / TC.2020.3009140
Provided by the University of California, Los Angeles
Quote: Computer scientists set benchmarks for optimizing the performance of quantum computers (2020, August 14), which were accessed on August 15, 2020 from https://techxplore.com/news/2020-08-scientists-benchmarks-optimize-quantum.html
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