Error mitigation approach helps quantum computers level up

Date:
February 24, 2022
Source:
DOE/Lawrence Berkeley National Laboratory
Summary:
Recent research has yielded a new approach to quantum error
mitigation - 'noise estimation circuits' - that could help make
quantum computing's theoretical potential a reality.



FULL STORY ==========================================================================
A collaboration between Lawrence Berkeley National Laboratory's (Berkeley Lab's) Applied Mathematics and Computational Research Division (AMCRD)
and Physics Division has yielded a new approach to error mitigation that
could help make quantum computing's theoretical potential a reality.


==========================================================================
The research team describes this work in a paper published in Physical
Review Letters, "Mitigating Depolarizing Noise on Quantum Computers with
Noise- Estimation Circuits." "Quantum computers have the potential to
solve more complex problems way faster than classical computers," said
Bert de Jong, one of the lead authors of the study and the director of
the AIDE-QC and QAT4Chem quantum computing projects.

De Jong also leads the AMCRD's Applied Computing for Scientific Discovery Group. "But the real challenge is quantum computers are relatively
new. And there's still a lot of work that has to be done to make them reliable." For now, one of the problems is that quantum computers are
still too error- prone to be consistently useful. This is due in large
part to something known as "noise" (errors).

There are different types of noise, including readout noise and gate
noise. The former has to do with reading out the result of a run on a
quantum computer; the more noise, the higher the chance a qubit -- the
quantum equivalent of a bit on a classical computer -- will be measured in
the wrong state. The latter relates to the actual operations performed;
noise here means the probability of applying the wrong operation. And
the prevalence of noise dramatically increases the more operations one
tries to perform with a quantum computer, which makes it harder to tease
out the right answer and severely limits quantum computers' usability
as they're scaled up.

"So noise here just basically means: It's stuff you don't want, and
it obscures the result you do want," said Ben Nachman, a Berkeley Lab
physicist and co- author on the study who also leads the cross-cutting
Machine Learning for Fundamental Physics group.



==========================================================================
And while error correction -- which is routine in classical computers --
would be ideal, it is not yet feasible on current quantum computers due
to the number of qubits needed. The next best thing: error mitigation -- methods and software to reduce noise and minimize errors in the science outcomes of quantum simulations. "On average, we want to be able to say
what the right answer should be," Nachman said.

To get there, the Berkeley Lab researchers developed a novel approach
they call noise estimation circuits. A circuit is a series of operations
or a program executed on a quantum computer to calculate the answer of
a scientific problem.

The team created a modified version of the circuit to give a predictable
answer -- 0 or 1 -- and used the difference between the measured and
predicted answer to correct the output measured of the real circuit.

The noise estimation circuit approach corrects some errors, but not
all. The Berkeley Lab team combined their new approach with three
other different error mitigation techniques: readout error correction
using "iterative Bayesian unfolding," a technique commonly used in
high-energy physics; a homegrown version of randomized compiling; and
error extrapolation. By putting all these pieces together, they were
able to obtain reliable results from an IBM quantum computer.

Making bigger simulations possible This work could have far-reaching implications for the field of quantum computing. The new error mitigation strategy allows researchers to tease the right answer out of simulations
that require a large number of operations, "Way more than what people
generally have been able to do," de Jong said.



========================================================================== Instead of doing tens of so-called entanglement or controlled NOT
operations, the new technique allows researchers to run hundreds of
such operations and still get reliable results, he explained. "So we
can actually do bigger simulations that could not be done before."
What's more, the Berkeley Lab group was able to use these techniques effectively on a quantum computer that's not necessarily optimally tuned
to reduce gate noise, de Jong said. That helps broaden the appeal of
the novel error mitigation approach.

"It is a good thing because if you can do it on those kinds of
platforms, we can probably do it even better on ones that are less
noisy," he said. "So it's a very general approach that we can use on
many different platforms." For researchers, the new error mitigation
approach means potentially being able to tackle bigger, more complex
problems with quantum computers. For instance, scientists will be able
to perform chemistry simulations with a lot more operations than before,
said de Jong, a computational chemist by trade.

"My interest is trying to solve problems that are relevant to carbon
capture, to battery research, to catalysis research," he said. "And so
my portfolio has always been: I do the science, but I also develop the
tools that enable me to do the science." Advances in quantum computing
have the potential to lead to breakthroughs in a number of areas, from
energy production, de-carbonization, and cleaner industrial processes
to drug development and artificial intelligence. At CERN's Large Hadron Collider -- where researchers send particles crashing into each other at incredibly high speeds to investigate how the universe works and what it's
made of -- quantum computing could help find hidden patterns in LHC data.

To move quantum computing forward in the near term, error mitigation
will be key.

"The better the error mitigation, the more operations we can apply to our quantum computers, which means someday, hopefully soon, we'll be able
to make calculations on a quantum computer that we couldn't make now,"
said Nachman, who is especially interested in the potential for quantum computing in high- energy physics, such as further investigating the
strong force that is responsible for binding nuclei together.

A cross-division team effort The study, which started in late 2020, marks
the latest in a series of collaborations between Berkeley Lab's Physics
and Computational Research divisions. That kind of cross-division work is especially important in the research and development of quantum computing, Nachman said. A funding call a few years ago from the U.S. Department
of Energy (DOE) as part of a pilot program to see if researchers could
find ways of using quantum computing for high-energy physics initially
prompted Nachman and his colleague Christian Bauer, a Berkeley Lab
theoretical physicist, to approach de Jong.

"We said, 'We have this idea. We're doing these calculations. What do you think?' " Nachman said. "We put together a proposal. It was funded. And
now it's a huge fraction of what we do." A lot of people are interested
in this technology across the board, according to Nachman. "We have
benefited greatly from collaboration with (de Jong's) group, and I think
it goes both ways," he said.

De Jong agreed. "It has been fun learning each other's physics languages
and seeing that at the core we have similar requirements and algorithmic
needs when it comes to quantum computing," he said.

The Oak Ridge Leadership Computing Facility, a DOE Office of Science user facility at Oak Ridge National Laboratory, provided the researchers with
access to the IBM Q quantum computers used for the research.

In addition to de Jong, Nachman, and Bauer, participants in this research effort include Miroslav Urbanek, formerly of Berkeley Lab's Computational Research Division and now at Atom Computing; Vincent R. Pascuzzi, formerly
with the Physics Division and now a research associate at the Brookhaven National Laboratory's Computational Science Initiative; and Andre He,
formerly with the Physics Division and now a quantum hardware engineer
at IBM.

The study was supported by the DOE through the Office of Advanced
Scientific Computing Research Quantum Algorithms Team Program and the
Office of High Energy Physics through the Quantum Information Science
Enabled Discovery program.

========================================================================== Story Source: Materials provided by
DOE/Lawrence_Berkeley_National_Laboratory. Original written by Patrick
Riley. Note: Content may be edited for style and length.


========================================================================== Journal Reference:
1. Miroslav Urbanek, Benjamin Nachman, Vincent R. Pascuzzi, Andre He,
Christian W. Bauer, Wibe A. de Jong. Mitigating Depolarizing Noise
on Quantum Computers with Noise-Estimation Circuits. Physical
Review Letters, 2021; 127 (27) DOI: 10.1103/PhysRevLett.127.270502 ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2022/02/220224120636.htm

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