Quantum Computation to Tackle Fundamental Science

Tuesday, September 26, 2017

For more than 50 years, Moore’s Law has reigned supreme. The observation that the number of transistors on a computer chip doubles roughly every two years has set the pace for our modern digital revolution—making smartphones, personal computers and current supercomputers possible. But Moore’s Law is slowing. And even if it wasn’t, some of the big problems that scientists need to tackle might be beyond the reach of conventional computers.

For the past few years, researchers at Lawrence Berkeley National Laboratory (Berkeley Lab) have been exploring a drastically different kind of computing architecture based on quantum mechanics to solve some of science’s hardest problems. With Laboratory Directed Research and Development (LDRD) funding, they’ve developed quantum chemistry and optimization algorithms, as well as prototype superconducting quantum processors. Recently, they proved the viability of their work by using these algorithms on a quantum processor comprising two superconducting transmon quantum bits to successfully solve the chemical problem of calculating the complete energy spectrum of a hydrogen molecule.

Now, two research teams led by Berkeley Lab staff will receive funding from the Department of Energy (DOE) to build on this momentum. One team will receive $1.5 million over three years to develop novel algorithms, compiling techniques and scheduling tools that will enable near-term quantum computing platforms to be used for scientific discovery in the chemical sciences. The other team will work closely with these researchers to design prototype four- and eight-qubit processors to compute these new algorithms. This project will last five years and the researchers will receive $1.5 million for their first year of work. By year five, the hardware team hopes to demonstrate a 64-qubit processor with full control.

“Someday, universal quantum computers will be able to solve a wide range of problems, from molecular design to machine learning and cybersecurity, but we’re a long way off from that. So, the question we are currently asking is whether there are specific problems that we can solve with more specialized quantum computers,” says Irfan Siddiqi (picured left), Berkeley Lab Scientist and Founding Director of the Center for Quantum Coherent Science at UC Berkeley.

According to Siddiqi, today’s quantum coherent computing technologies do have the requisite coherence times, logical operation fidelities and circuit topologies to perform specialized computations for fundamental research in areas such as molecular and materials science, numerical optimization and high energy physics. In light of these advances, he notes that it is timely for DOE to explore how these technologies can be integrated into the high-performance computing community. On these new projects, the Berkeley Lab teams will work with collaborators in industry and academia to build on these advances and tackle difficult DOE-mission science problems such as calculating molecular system dynamics and quantum machine learning.

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Editor: 
Linda Vu