Tag Archives: Charles Neill

Creating time crystals with a quantum computer

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This November 30, 2021 news item on phys.org about time crystals caught my attention,

There is a huge global effort to engineer a computer capable of harnessing the power of quantum physics to carry out computations of unprecedented complexity. While formidable technological obstacles still stand in the way of creating such a quantum computer, today’s early prototypes are still capable of remarkable feats.

For example, the creation of a new phase of matter called a “time crystal.” Just as a crystal’s structure repeats in space, a time crystal repeats in time and, importantly, does so infinitely and without any further input of energy—like a clock that runs forever without any batteries. The quest to realize this phase of matter has been a longstanding challenge in theory and experiment—one that has now finally come to fruition.

In research published Nov. 30 [2021] in Nature, a team of scientists from Stanford University, Google Quantum AI, the Max Planck Institute for Physics of Complex Systems and Oxford University detail their creation of a time crystal using Google’s Sycamore quantum computing hardware.

The Google Sycamore chip used in the creation of a time crystal. Credit: Google Quantum AI [downloaded from https://phys.org/news/2021-11-physicists-crystals-quantum.html]

A November 30, 2021 Stanford University news release (also on EurekAlert) by Taylor Kubota, which originated the news item, delves further into the work and into the nature of time crystals,

“The big picture is that we are taking the devices that are meant to be the quantum computers of the future and thinking of them as complex quantum systems in their own right,” said Matteo Ippoliti, a postdoctoral scholar at Stanford and co-lead author of the work. “Instead of computation, we’re putting the computer to work as a new experimental platform to realize and detect new phases of matter.”

For the team, the excitement of their achievement lies not only in creating a new phase of matter but in opening up opportunities to explore new regimes in their field of condensed matter physics, which studies the novel phenomena and properties brought about by the collective interactions of many objects in a system. (Such interactions can be far richer than the properties of the individual objects.)

“Time-crystals are a striking example of a new type of non-equilibrium quantum phase of matter,” said Vedika Khemani, assistant professor of physics at Stanford and a senior author of the paper. “While much of our understanding of condensed matter physics is based on equilibrium systems, these new quantum devices are providing us a fascinating window into new non-equilibrium regimes in many-body physics.”

What a time crystal is and isn’t

The basic ingredients to make this time crystal are as follows: The physics equivalent of a fruit fly and something to give it a kick. The fruit fly of physics is the Ising model, a longstanding tool for understanding various physical phenomena – including phase transitions and magnetism – which consists of a lattice where each site is occupied by a particle that can be in two states, represented as a spin up or down.

During her graduate school years, Khemani, her doctoral advisor Shivaji Sondhi, then at Princeton University, and Achilleas Lazarides and Roderich Moessner at the Max Planck Institute for Physics of Complex Systems stumbled upon this recipe for making time crystals unintentionally. They were studying non-equilibrium many-body localized systems – systems where the particles get “stuck” in the state in which they started and can never relax to an equilibrium state. They were interested in exploring phases that might develop in such systems when they are periodically “kicked” by a laser. Not only did they manage to find stable non-equilibrium phases, they found one where the spins of the particles flipped between patterns that repeat in time forever, at a period twice that of the driving period of the laser, thus making a time crystal.

The periodic kick of the laser establishes a specific rhythm to the dynamics. Normally the “dance” of the spins should sync up with this rhythm, but in a time crystal it doesn’t. Instead, the spins flip between two states, completing a cycle only after being kicked by the laser twice. This means that the system’s “time translation symmetry” is broken. Symmetries play a fundamental role in physics, and they are often broken – explaining the origins of regular crystals, magnets and many other phenomena; however, time translation symmetry stands out because unlike other symmetries, it can’t be broken in equilibrium. The periodic kick is a loophole that makes time crystals possible.

The doubling of the oscillation period is unusual, but not unprecedented. And long-lived oscillations are also very common in the quantum dynamics of few-particle systems. What makes a time crystal unique is that it’s a system of millions of things that are showing this kind of concerted behavior without any energy coming in or leaking out.

“It’s a completely robust phase of matter, where you’re not fine-tuning parameters or states but your system is still quantum,” said Sondhi, professor of physics at Oxford and co-author of the paper. “There’s no feed of energy, there’s no drain of energy, and it keeps going forever and it involves many strongly interacting particles.”

While this may sound suspiciously close to a “perpetual motion machine,” a closer look reveals that time crystals don’t break any laws of physics. Entropy – a measure of disorder in the system – remains stationary over time, marginally satisfying the second law of thermodynamics by not decreasing.

Between the development of this plan for a time crystal and the quantum computer experiment that brought it to reality, many experiments by many different teams of researchers achieved various almost-time-crystal milestones. However, providing all the ingredients in the recipe for “many-body localization” (the phenomenon that enables an infinitely stable time crystal) had remained an outstanding challenge.

For Khemani and her collaborators, the final step to time crystal success was working with a team at Google Quantum AI. Together, this group used Google’s Sycamore quantum computing hardware to program 20 “spins” using the quantum version of a classical computer’s bits of information, known as qubits.

Revealing just how intense the interest in time crystals currently is, another time crystal was published in Science this month [November 2021]. That crystal was created using qubits within a diamond by researchers at Delft University of Technology in the Netherlands.

Quantum opportunities

The researchers were able to confirm their claim of a true time crystal thanks to special capabilities of the quantum computer. Although the finite size and coherence time of the (imperfect) quantum device meant that their experiment was limited in size and duration – so that the time crystal oscillations could only be observed for a few hundred cycles rather than indefinitely – the researchers devised various protocols for assessing the stability of their creation. These included running the simulation forward and backward in time and scaling its size.

“We managed to use the versatility of the quantum computer to help us analyze its own limitations,” said Moessner, co-author of the paper and director at the Max Planck Institute for Physics of Complex Systems. “It essentially told us how to correct for its own errors, so that the fingerprint of ideal time-crystalline behavior could be ascertained from finite time observations.”

A key signature of an ideal time crystal is that it shows indefinite oscillations from all states. Verifying this robustness to choice of states was a key experimental challenge, and the researchers devised a protocol to probe over a million states of their time crystal in just a single run of the machine, requiring mere milliseconds of runtime. This is like viewing a physical crystal from many angles to verify its repetitive structure.

“A unique feature of our quantum processor is its ability to create highly complex quantum states,” said Xiao Mi, a researcher at Google and co-lead author of the paper. “These states allow the phase structures of matter to be effectively verified without needing to investigate the entire computational space – an otherwise intractable task.”

Creating a new phase of matter is unquestionably exciting on a fundamental level. In addition, the fact that these researchers were able to do so points to the increasing usefulness of quantum computers for applications other than computing. “I am optimistic that with more and better qubits, our approach can become a main method in studying non-equilibrium dynamics,” said Pedram Roushan, researcher at Google and senior author of the paper.

“We think that the most exciting use for quantum computers right now is as platforms for fundamental quantum physics,” said Ippoliti. “With the unique capabilities of these systems, there’s hope that you might discover some new phenomenon that you hadn’t predicted.”

A view of the Google dilution refrigerator, which houses the Sycamore chip. Credit: Google Quantum AI [downloaded from https://scitechdaily.com/stanford-and-google-team-up-to-create-time-crystals-with-quantum-computers/]

Here’s a link to and a citation for the paper,

Time-Crystalline Eigenstate Order on a Quantum Processor by Xiao Mi, Matteo Ippoliti, Chris Quintana, Ami Greene, Zijun Chen, Jonathan Gross, Frank Arute, Kunal Arya, Juan Atalaya, Ryan Babbush, Joseph C. Bardin, Joao Basso, Andreas Bengtsson, Alexander Bilmes, Alexandre Bourassa, Leon Brill, Michael Broughton, Bob B. Buckley, David A. Buell, Brian Burkett, Nicholas Bushnell, Benjamin Chiaro, Roberto Collins, William Courtney, Dripto Debroy, Sean Demura, Alan R. Derk, Andrew Dunsworth, Daniel Eppens, Catherine Erickson, Edward Farhi, Austin G. Fowler, Brooks Foxen, Craig Gidney, Marissa Giustina, Matthew P. Harrigan, Sean D. Harrington, Jeremy Hilton, Alan Ho, Sabrina Hong, Trent Huang, Ashley Huff, William J. Huggins, L. B. Ioffe, Sergei V. Isakov, Justin Iveland, Evan Jeffrey, Zhang Jiang, Cody Jones, Dvir Kafri, Tanuj Khattar, Seon Kim, Alexei Kitaev, Paul V. Klimov, Alexander N. Korotkov, Fedor Kostritsa, David Landhuis, Pavel Laptev, Joonho Lee, Kenny Lee, Aditya Locharla, Erik Lucero, Orion Martin, Jarrod R. McClean, Trevor McCourt, Matt McEwen, Kevin C. Miao, Masoud Mohseni, Shirin Montazeri, Wojciech Mruczkiewicz, Ofer Naaman, Matthew Neeley, Charles Neill, Michael Newman, Murphy Yuezhen Niu, Thomas E. O’Brien, Alex Opremcak, Eric Ostby, Balint Pato, Andre Petukhov, Nicholas C. Rubin, Daniel Sank, Kevin J. Satzinger, Vladimir Shvarts, Yuan Su, Doug Strain, Marco Szalay, Matthew D. Trevithick, Benjamin Villalonga, Theodore White, Z. Jamie Yao, Ping Yeh, Juhwan Yoo, Adam Zalcman, Hartmut Neven, Sergio Boixo, Vadim Smelyanskiy, Anthony Megrant, Julian Kelly, Yu Chen, S. L. Sondhi, Roderich Moessner, Kostyantyn Kechedzhi, Vedika Khemani & Pedram Roushan. Nature (2021) DOI: https://doi.org/10.1038/s41586-021-04257-w Published 30 November 2021

This is a preview of the unedited paper being provided by Nature. Click on the Download PDF button (to the right of the title) to get access.

Quantum supremacy

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This supremacy, refers to an engineering milestone and a October 23, 2019 news item on ScienceDaily announces the milestone has been reached,

Researchers in UC [University of California] Santa Barbara/Google scientist John Martinis’ group 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.

…

An October 23, 2019 UC Santa Barbara news release (also on EurekAlert) by Sonia Fernandez, which originated the news item, delves further into the work,

“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.”

Here’s a link to and a citation for the paper,

Quantum supremacy using a programmable superconducting processor by 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. Nature volume 574, pages505–510 (2019) DOI: https://doi.org/10.1038/s41586-019-1666-5 Issue Date 24 October 2019

This paper appears to be open access.

Connecting chaos and entanglement

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Researchers seem to have stumbled across a link between classical and quantum physics. A July 12, 2016 University of California at Santa Barbara (UCSB) news release (also on EurekAlert) by Sonia Fernandez provides a description of both classical and quantum physics, as well as, the research that connects the two,

Using a small quantum system consisting of three superconducting qubits, researchers at UC Santa Barbara and Google have uncovered a link between aspects of classical and quantum physics thought to be unrelated: classical chaos and quantum entanglement. Their findings suggest that it would be possible to use controllable quantum systems to investigate certain fundamental aspects of nature.

“It’s kind of surprising because chaos is this totally classical concept — there’s no idea of chaos in a quantum system,” Charles Neill, a researcher in the UCSB Department of Physics and lead author of a paper that appears in Nature Physics. “Similarly, there’s no concept of entanglement within classical systems. And yet it turns out that chaos and entanglement are really very strongly and clearly related.”

Initiated in the 15th century, classical physics generally examines and describes systems larger than atoms and molecules. It consists of hundreds of years’ worth of study including Newton’s laws of motion, electrodynamics, relativity, thermodynamics as well as chaos theory — the field that studies the behavior of highly sensitive and unpredictable systems. One classic example of chaos theory is the weather, in which a relatively small change in one part of the system is enough to foil predictions — and vacation plans — anywhere on the globe.

At smaller size and length scales in nature, however, such as those involving atoms and photons and their behaviors, classical physics falls short. In the early 20th century quantum physics emerged, with its seemingly counterintuitive and sometimes controversial science, including the notions of superposition (the theory that a particle can be located in several places at once) and entanglement (particles that are deeply linked behave as such despite physical distance from one another).

And so began the continuing search for connections between the two fields.

All systems are fundamentally quantum systems, according [to] Neill, but the means of describing in a quantum sense the chaotic behavior of, say, air molecules in an evacuated room, remains limited.

Imagine taking a balloon full of air molecules, somehow tagging them so you could see them and then releasing them into a room with no air molecules, noted co-author and UCSB/Google researcher Pedram Roushan. One possible outcome is that the air molecules remain clumped together in a little cloud following the same trajectory around the room. And yet, he continued, as we can probably intuit, the molecules will more likely take off in a variety of velocities and directions, bouncing off walls and interacting with each other, resting after the room is sufficiently saturated with them.

“The underlying physics is chaos, essentially,” he said. The molecules coming to rest — at least on the macroscopic level — is the result of thermalization, or of reaching equilibrium after they have achieved uniform saturation within the system. But in the infinitesimal world of quantum physics, there is still little to describe that behavior. The mathematics of quantum mechanics, Roushan said, do not allow for the chaos described by Newtonian laws of motion.

To investigate, the researchers devised an experiment using three quantum bits, the basic computational units of the quantum computer. Unlike classical computer bits, which utilize a binary system of two possible states (e.g., zero/one), a qubit can also use a superposition of both states (zero and one) as a single state. Additionally, multiple qubits can entangle, or link so closely that their measurements will automatically correlate. By manipulating these qubits with electronic pulses, Neill caused them to interact, rotate and evolve in the quantum analog of a highly sensitive classical system.

The result is a map of entanglement entropy of a qubit that, over time, comes to strongly resemble that of classical dynamics — the regions of entanglement in the quantum map resemble the regions of chaos on the classical map. The islands of low entanglement in the quantum map are located in the places of low chaos on the classical map.

“There’s a very clear connection between entanglement and chaos in these two pictures,” said Neill. “And, it turns out that thermalization is the thing that connects chaos and entanglement. It turns out that they are actually the driving forces behind thermalization.

“What we realize is that in almost any quantum system, including on quantum computers, if you just let it evolve and you start to study what happens as a function of time, it’s going to thermalize,” added Neill, referring to the quantum-level equilibration. “And this really ties together the intuition between classical thermalization and chaos and how it occurs in quantum systems that entangle.”

The study’s findings have fundamental implications for quantum computing. At the level of three qubits, the computation is relatively simple, said Roushan, but as researchers push to build increasingly sophisticated and powerful quantum computers that incorporate more qubits to study highly complex problems that are beyond the ability of classical computing — such as those in the realms of machine learning, artificial intelligence, fluid dynamics or chemistry — a quantum processor optimized for such calculations will be a very powerful tool.

“It means we can study things that are completely impossible to study right now, once we get to bigger systems,” said Neill.

Experimental link between quantum entanglement (left) and classical chaos (right) found using a small quantum computer. Photo Credit: Courtesy Image (Courtesy: UCSB)

Experimental link between quantum entanglement (left) and classical chaos (right) found using a small quantum computer. Photo Credit: Courtesy Image (Courtesy: UCSB)

Here’s a link to and a citation for the paper,

Ergodic dynamics and thermalization in an isolated quantum system by C. Neill, P. Roushan, M. Fang, Y. Chen, M. Kolodrubetz, Z. Chen, A. Megrant, R. Barends, B. Campbell, B. Chiaro, A. Dunsworth, E. Jeffrey, J. Kelly, J. Mutus, P. J. J. O’Malley, C. Quintana, D. Sank, A. Vainsencher, J. Wenner, T. C. White, A. Polkovnikov, & J. M. Martinis. Nature Physics (2016)  doi:10.1038/nphys3830 Published online 11 July 2016

This paper is behind a paywall.