Scientists from the universities of Alberta and Toronto developed a blueprint for a new quantum battery that doesn't leak charge.
"A quantumbatteryis a tiny, nano-size battery meant to be used for applications on the nano scale," explained U of A chemist Gabriel Hanna, who was principal investigator on the study.
He said the research provides a theoretical demonstration that creating a loss-freequantum batteryis possible—offering an advantage over previously proposed quantum batteries.
"The batteries that we are more familiar with—like the lithium-ion battery that powers your smartphone—rely on classical electrochemical principles, whereas quantum batteries rely solely on quantum mechanics," Hanna noted.
He said the batteries may become an important component in many quantum devices—able to power quantum computers, for example—and in practice, they could be built using current solid-state technologies.
To realize their idea, the research team considered an open quantum network model with high structural symmetry as a platform for storing excitonic energy—energy harnessed when an electron absorbs a sufficiently energetic photon of light. Using this model, they showed it is possible to store energy without any loss, despite being open to an environment.
"The key is to prepare this quantum network in what is called a dark state," explained Hanna. "While in a dark state, the network cannot exchange energy with its environment. In essence, the system becomes immune to all environmental influences. This means that the battery is highly robust to energy losses."
Using this model, the researchers also suggested a general method of discharging the stored energy from the battery upon demand that involves breaking the structural symmetry of the network in a controlled way.
Future research will explore viable ways of charging and discharging the battery, as well as ways of scaling it up for use in practical applications.
The study, "Loss-Free Excitonic Quantum Battery," was published in the Journal of Physical Chemistry C.
The importance of the achievement can be as hard to understand as quantum computing itself, a field made possible by the mind-bending behavior of atomic-scale physics. But if you want a takeaway, here it is: Quantum computing is only beginning to show some of the promise researchers have hyped for decades. We're still several breakthroughs away from seeing the true potential fulfilled.
Quantum computers work by embracing the strange nature of particles at the atomic scale. Where classical computers store data as bits that are either a one or a zero, the quantum computing equivalent, called a qubit, can store information that's part one and part zero. Next, a quantum computer gangs multiple qubits together, dramatically increasing the number of possible states they can record. Last, processing those qubits lets researchers explore countless possible solutions to a problem simultaneously instead of evaluating them one at a time. It's lousy for adding two and two, but potentially great for some problems classical computers just can't cope with.
Google's quantum researchers are already turning their attention to the next steps needed to make their machines more broadly useful, a step Intel calls quantum practicality.
"It will be a must-have resource at some point," Hartmut Neven, the researcher who began Google's quantum computing effort in 2006, said at a press event.
Marissa Giustina, a researcher with Google's quantum computer lab, draws a diagram showing "quantum supremacy" as only an early step on a path of quantum computer progress.
For those who want to try out Google's quantum computer, the company plans to make it available as a cloud computing service in 2020. That follows in the footsteps of IBM, which already has done so with its Q Experience.
What'll quantum computers be good for?
Google's quantum researchers are excited about the shift in their research from theory to experiment. "I started off ... bashing my head against the wall because all the algorithm development was for a machine that didn't exist," said Dave Bacon, who leads Google's quantum software work. Now comes the era when "I can just run it and see what happens."
Google has a lot of practical uses in mind:
Complicated optimization problems, such as calculating how to deliver packages in the shortest time while using the least energy. "Optimization problems occur everywhere at every company anywhere in the world," Bacon said. Addressing those challenges could both save money and help the environment.
Improving encryption technology by generating random numbers. Google's quantum team is talking to its encryption key generation team about using a random-number generation tool it's already developed for today's Sycamore machine.
Building machine learning systems better at tasks like distinguishing between real and fake items like bogus political videos. This was the original impetus for Neven's work, and Google researchers think it could be the first area to deliver on quantum computing's promise.
Perhaps most interesting, simulating the real physics of molecular-scale materials. Revolutionary developments there could mean more efficient solar panels, a new way to produce nitrogen fertilizer without needing so much energy and better electric car batteries.
Google's quantum computing competitors, including IBM, Intel and Rigetti Computing, are also eager for better simulation.
Limits of Google's quantum supremacy milestone
Quantum supremacy doesn't mean quantum computers outdo classical computers on every task. Indeed, they'll always be slower at a lot of crucial processing, meaning they'll serve alongside classical computers, not replace them.
Physicist Michel Dyakonov at the Université Montpellier in France, remains unconvinced quantum machines will become mainstream. "I don't believe they will ever become practical," he said. "The quest for 'supremacy' is somewhat artificial and belongs more to the hype than to science. Just show us an elementary quantum calculator that can do three times five or three plus five."
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Quantum computers face serious practical constraints. Qubits, the fundamental units of quantum information processing, are so easily perturbed that they must be housed in complex refrigeration units chilled to a fraction of a degree above absolute zero. Pausing operations to fiddle with the core hardware requires at least two days for the system to warm back up without damage, then restarting requires two more days to cool back down. You won't find a quantum computer in your laptop anytime soon.
Better qubit stability means a quantum computer can run a longer sequence of operations before tripping up. Right now, a qubit's useful longevity is about 10 millionths of a second, said Google quantum research scientist Marissa Giustina. "We hope to go up," she said.
Quantum computing is expensive, too. Google's Sycamore machines send control signals to the quantum chip using hundreds of cables that each cost $1,000 per 2-foot length. Pushing quantum computers into everyday computing jobs will require years more of heavy, sustained R&D investment.
Google believes it's on the right track, though, and that quantum progress will outstrip classical progress. It looks forward not merely to exponential performance improvements -- the kind that Moore's Law has charted for classical computers -- but double exponential improvements.
Google has a long to-do list, starting with improving how long qubits can run error-free. Errors mean a qubit flips to record bad information, stymying a calculation, and improving error rates is the top goal in the next year, said John Martinis, the University of California, Santa Barbara, researcher who now leads Google's quantum computing hardware team.
"The No. 1 thing we are trying to do is improve the errors of the device," Martinis said, standing in Google's lab with five hulking quantum computers suspended around him. "We've been kind of ignoring that trying to get to the supremacy result."
Later will come more fundamental changes, like quantum error correction techniques to sidestep qubit instabilities. Google researchers are unafraid to present plans stretching years into the future, when qubit counts rise from 54 to a million or more. And they're patient.
"We know that this decade-long march is going to require innovations across theory, engineering and actual physics," Bacon said.