UC Santa Barbara/Google
researchers demonstrate the power of 53 entangled qubits
October 23, 2019
UC Santa Barbara
Researchers have made good on
their claim to quantum supremacy. Using 53 entangled quantum bits ('qubits'),
their Sycamore computer has taken on -- and solved -- a problem considered
intractable for classical computers.
"A computation that would
take 10,000 years on a classical supercomputer took 200 seconds on our quantum
computer," said Brooks Foxen, a graduate student researcher in the
Martinis Group. "It is likely that the classical simulation time,
currently estimated at 10,000 years, will be reduced by improved classical
hardware and algorithms, but, since we are currently 1.5 trillion times faster,
we feel comfortable laying claim to this achievement."
The feat is outlined in a
paper in the journal Nature.
The milestone comes after
roughly two decades of quantum computing research conducted by Martinis and his
group, from the development of a single superconducting qubit to systems
including architectures of 72 and, with Sycamore, 54 qubits (one didn't
perform) that take advantage of the both awe-inspiring and bizarre properties
of quantum mechanics.
"The algorithm was chosen
to emphasize the strengths of the quantum computer by leveraging the natural
dynamics of the device," said Ben Chiaro, another graduate student
researcher in the Martinis Group. That is, the researchers wanted to test the
computer's ability to hold and rapidly manipulate a vast amount of complex,
unstructured data.
"We basically wanted to
produce an entangled state involving all of our qubits as quickly as we
can," Foxen said, "and so we settled on a sequence of operations that
produced a complicated superposition state that, when measured, returns
bitstring with a probability determined by the specific sequence of operations
used to prepare that particular superposition. The exercise, which was to
verify that the circuit's output correspond to the equence used to prepare the
state, sampled the quantum circuit a million times in just a few minutes,
exploring all possibilities -- before the system could lose its quantum
coherence.
'A complex superposition
state'
"We performed a fixed set
of operations that entangles 53 qubits into a complex superposition
state," Chiaro explained. "This superposition state encodes the
probability distribution. For the quantum computer, preparing this
superposition state is accomplished by applying a sequence of tens of control
pulses to each qubit in a matter of microseconds. We can prepare and then
sample from this distribution by measuring the qubits a million times in 200
seconds."
"For classical computers,
it is much more difficult to compute the outcome of these operations because it
requires computing the probability of being in any one of the 2^53 possible
states, where the 53 comes from the number of qubits -- the exponential scaling
is why people are interested in quantum computing to begin with," Foxen
said. "This is done by matrix multiplication, which is expensive for
classical computers as the matrices become large."
According to the new paper,
the researchers used a method called cross-entropy benchmarking to compare the
quantum circuit's output (a "bitstring") to its "corresponding
ideal probability computed via simulation on a classical computer" to
ascertain that the quantum computer was working correctly.
"We made a lot of design
choices in the development of our processor that are really advantageous,"
said Chiaro. Among these advantages, he said, are the ability to experimentally
tune the parameters of the individual qubits as well as their interactions.
While the experiment was
chosen as a proof-of-concept for the computer, the research has resulted in a
very real and valuable tool: a certified random number generator. Useful in a
variety of fields, random numbers can ensure that encrypted keys can't be
guessed, or that a sample from a larger population is truly representative,
leading to optimal solutions for complex problems and more robust machine
learning applications. The speed with which the quantum circuit can produce its
randomized bit string is so great that there is no time to analyze and
"cheat" the system.
"Quantum mechanical
states do things that go beyond our day-to-day experience and so have the
potential to provide capabilities and application that would otherwise be
unattainable," commented Joe Incandela, UC Santa Barbara's vice chancellor
for research. "The team has demonstrated the ability to reliably create
and repeatedly sample complicated quantum states involving 53 entangled
elements to carry out an exercise that would take millennia to do with a
classical supercomputer. This is a major accomplishment. We are at the
threshold of a new era of knowledge acquisition."
Looking ahead
With an achievement like
"quantum supremacy," it's tempting to think that the UC Santa
Barbara/Google researchers will plant their flag and rest easy. But for Foxen,
Chiaro, Martinis and the rest of the UCSB/Google AI Quantum group, this is just
the beginning.
"It's kind of a
continuous improvement mindset," Foxen said. "There are always
projects in the works." In the near term, further improvements to these
"noisy" qubits may enable the simulation of interesting phenomena in
quantum mechanics, such as thermalization, or the vast amount of possibility in
the realms of materials and chemistry.
In the long term, however, the
scientists are always looking to improve coherence times, or, at the other end,
to detect and fix errors, which would take many additional qubits per qubit
being checked. These efforts have been running parallel to the design and build
of the quantum computer itself, and ensure the researchers have a lot of work
before hitting their next milestone.
"It's been an honor and a
pleasure to be associated with this team," Chiaro said. "It's a great
collection of strong technical contributors with great leadership and the whole
team really synergizes well."
Story Source:
Materials provided by UC Santa Barbara. Original
written by Sonia Fernandez. Note: Content may be edited for style and
length.
Related Multimedia:
Journal Reference:
Frank Arute, Kunal Arya, Ryan
Babbush, Dave Bacon, Joseph C. Bardin, Rami Barends, Rupak Biswas, Sergio
Boixo, Fernando G. S. L. Brandao, David A. Buell, Brian Burkett, Yu Chen, Zijun
Chen, Ben Chiaro, Roberto Collins, William Courtney, Andrew Dunsworth, Edward
Farhi, Brooks Foxen, Austin Fowler, Craig Gidney, Marissa Giustina, Rob Graff,
Keith Guerin, Steve Habegger, Matthew P. Harrigan, Michael J. Hartmann, Alan
Ho, Markus Hoffmann, Trent Huang, Travis S. Humble, Sergei V. Isakov, Evan
Jeffrey, Zhang Jiang, Dvir Kafri, Kostyantyn Kechedzhi, Julian Kelly, Paul V.
Klimov, Sergey Knysh, Alexander Korotkov, Fedor Kostritsa, David Landhuis, Mike
Lindmark, Erik Lucero, Dmitry Lyakh, Salvatore Mandrà, Jarrod R. McClean,
Matthew McEwen, Anthony Megrant, Xiao Mi, Kristel Michielsen, Masoud Mohseni,
Josh Mutus, Ofer Naaman, Matthew Neeley, Charles Neill, Murphy Yuezhen Niu,
Eric Ostby, Andre Petukhov, John C. Platt, Chris Quintana, Eleanor G. Rieffel,
Pedram Roushan, Nicholas C. Rubin, Daniel Sank, Kevin J. Satzinger, Vadim
Smelyanskiy, Kevin J. Sung, Matthew D. Trevithick, Amit Vainsencher, Benjamin
Villalonga, Theodore White, Z. Jamie Yao, Ping Yeh, Adam Zalcman, Hartmut
Neven, John M. Martinis. Quantum supremacy using a programmable
superconducting processor. Nature, 2019; 574 (7779): 505 DOI: 10.1038/s41586-019-1666-5
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