US Department of Energy names eight science problems to guide fault tolerant quantum computing

[Rabbit]

The US Department of Energy has published what it calls the Quantum Genesis Priority Applications, HPCwire reports. They are eight scientific problems meant to guide DOE's effort to build fault tolerant quantum computers that are useful for science. The list builds on DOE's earlier Blueprint for Quantum Supercomputing and a report from its Office of Science advisory committee. The idea is to give everyone a clear target for what scientific relevance means

The problems fall into four areas. In chemistry, the focus is on reaction mechanisms and light sensitive processes. In materials, it covers quantum, topological and superconducting materials, plus materials in extreme environments. Subatomic physics includes nuclear structure, the forces that hold protons and neutrons together and dense matter relevant to fusion, while applied mathematics covers linear and differential equations

DOE says it is also watching plasma physics, biochemistry and optimisation. Results will be benchmarked against the best supercomputing methods, which is exactly the right test. The priorities will guide three things: a Q Competition, a National Quantum Computing User Facility and focused research on fault tolerant applications. DOE is coordinating with the Department of Defense, the Laboratory for Physical Sciences and NASA

Darío Gil, DOE's Under Secretary for Science, called the list a bold declaration of how quantum computing will open up new scientific frontiers. Separately, Quantum Computing Report says DOE has made 12 Phase II awards worth $159 million in its wider Genesis Mission programme, which pairs AI and supercomputing with national lab testbeds. Two of those are quantum projects. One, led by Harvard, uses AI with real quantum processors to choose error correction codes, and another, led by Oak Ridge with Brookhaven, uses AI to design magnetic materials for quantum hardware

I think a published list of target problems is very useful. Too much quantum work has been about finding a problem to fit the machine rather than the other way round. Saying here are the eight things we care about, and we will compare you against our best supercomputers, keeps everyone honest. It also gives startups a clear idea of where the funding will flow

Which of the four areas do you think will see a quantum advantage first? And does benchmarking against the best supercomputers set the bar too high?

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