The Johns Hopkins University Applied Physics Laboratory (APL), in Laurel, MD, has been tapped by the Department of Energy to develop advanced quantum computing and networking technologies. The award is part of larger DOE effort to address basic research gaps in the ideas, methods and tools that connect quantum computing applications to hardware.
“We are on the threshold of a new era in quantum information science and quantum computing and networking, with potentially great promise for science and society,” said DOE Undersecretary for Science Paul Dabbar, in announcing the department’s quantum computing research grants. “These projects will help ensure U.S. leadership in these important new areas of science and technology.”
“We are still in
the early stages of quantum computing. We have still not achieved quantum
advantage, the point at which quantum computers outperform classical
computers,” said Dave Clader, a theoretical physicist and principal
investigator of the APL research team. “Despite this, hardware is scaling up
and more near-term applications are being considered that may finally push us
into the realm where quantum advantage is demonstrated.”
Because of this
promise, Clader continued, there has been a considerable amount of research
into algorithms and software development. “Unlike classical computing — where
the hardware can be abstracted from a software engineer — an algorithm designer
for near-term quantum hardware must have detailed knowledge of the underlying
hardware, noise characteristics and architecture,” he said.
APL researchers —
under an effort called TEAM, or Tough Errors Are no Match: Optimizing the
Quantum Compiler for Noise Resilience — will explore advanced noise
characterization and mitigation techniques, focusing on models that can be
easily incorporated into quantum compilers in a hardware-agnostic manner.
“Uncontrolled noise
is currently limiting quantum computers from reaching their full potential,”
explained Clader. “We are looking to integrate noise combating protocols into
quantum compilers. This will enable quantum programmers to write
noise-resilient quantum algorithms in an automated fashion that does not
require the algorithm designer to understand the detailed noise characteristics
of the hardware.”
APL has extensive expertise in quantum characterization and control — the essential building blocks for the team’s approach; the Laboratory is also collaborating with several institutions, including Dartmouth College, University of Maryland, University of Chicago, Stanford University, University of Colorado Boulder, the Unitary Fund and Lawrence Livermore National Laboratory.
Source: JHU APL
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