Microsoft big quantum error after all software#
“Quantum software engineering is really as important as the hardware engineering,” Troyer said. But if the task is structured to enable parallel processing and enhanced error correction, the required runtime can be shrunk to less than two days. The efficiency of computation and the ability to reduce errors can make a big difference, said Microsoft principal researcher Matthias Troyer.įor example, a standard approach to simulating the molecular mechanism behind nitrogen fixation for crops could require 30,000 years of processing time, he said. Over the past year and a half, Microsoft has released a new quantum-friendly programming language called Q# (“Q-sharp”) as part of its Quantum Development Kit, and has worked with researchers at Pacific Northwest National Laboratory and academic institutions around the world to lay the technical groundwork for the field.īut the power of quantum computing shouldn’t be measured merely by counting qubits. (The closest startup to Seattle is 1QBit, based in Vancouver, B.C.) Representatives from 16 startups were invited to this week’s Startup Summit, which features talks from Holmdahl and other leaders of Microsoft’s quantum team as well as demos and workshops focusing on Microsoft’s programming tools. We have been talking around here that we’re at the advent of the quantum economy.” Todd Holmdahl, Microsoft corporate vice president for the Azure Hardware Systems Group, speaks during a Startup Summit kicking off the Microsoft Quantum Network.
All of these things are possible and obtainable with a quantum computer. We think we have opportunities to solve problems around materials science, personal health care, machine learning. “We’re looking at solving big food production problems. “We’re looking at problems like climate change,” Holmdahl said. That could open the way to world-changing applications, said Todd Holmdahl, corporate vice president of Microsoft’s Azure Hardware Systems Group. This paper also gives us further confidence that quantum simulation will be able to provide answers to problems with a tremendous potential for scientific and economic impact.Įditor’s Note: The paper’s authors contributed to this post: Markus Reiher, Nathan Wiebe, Krysta Svore, Dave Wecker and Matthias Troyer.The quantum approach should be able to solve computational problems that can’t easily be solved using classical computers, such as modeling molecular interactions or optimizing large-scale systems. This paper shows that these kinds of necessary computations can be performed in reasonable time on realistic quantum computers-demonstrating that quantum computers will one day tackle important problems in chemistry without requiring exorbitant resources. The search for high-temperature superconductors is another example. Efficiently capturing carbon (to combat global warming) is in the same class of problem. This molecule is beyond the abilities of our largest supercomputers to analyze, but would be within the reach of a moderate scale quantum computer. However, we know that a tiny anaerobic bacteria in the roots of plants performs this same process every day at very low energy cost using a specific molecule- nitrogenase.
This relies on a process developed in the early 1900s that is extremely energy intensive-the reaction gas required is taken from natural gas, which is in turn required in very large amounts. Today, we spend approximately 3 percent of the world’s total energy output on making fertilizer. Our paper published earlier this week at the Proceedings of the National Academy of Sciences confirms the feasibility of such a practical application, showing that a quantum computer can be employed to reveal reaction mechanisms in complex chemical systems, using the open problem of biological nitrogen fixation in nitrogenase as an example. After all, even an exponential speedup may not lead to a useful algorithm if a typical, practical application requires an amount of time and memory that is beyond the reach of even a quantum computer. However, a number of important questions remain. Not the least of these is the question of how exactly to use a quantum computer to solve an important problem in chemistry. The inability to point to a clear use case complete with resource and cost estimates is a major drawback.
Many suspect that quantum computers will one day revolutionize chemistry and materials science the likely ability of quantum computers to predict specific properties of molecules and materials fits this outcome nicely. Much work has already been done towards identifying areas where quantum computing provides a clear improvement over traditional classical approaches.
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