Bringing the Quantum to the Classical: A Hybrid Simulation of Supernova Neutrinos

Posted on April 18, 2024

By Daniel Heimsoth, Physics PhD student

Simulating quantum systems on classical computers is currently a near-impossible task, as memory and computation time requirements scale exponentially with the size of the system. Quantum computers promise to solve this scalability issue, but there is just one problem: they can’t reliably do that right now because of exorbitant amounts of noise.

So when UW–Madison physics postdoc Pooja Siwach, former undergrad Katie Harrison BS ‘23, and professor Baha Balantekin wanted to simulate neutrino evolution inside a supernova, they needed to get creative.

Pooja Siwach

Their focus was on a phenomenon called collective neutrino oscillations, which describes a peculiar type of interaction between neutrinos. Neutrinos are unique among elementary particles in that they change type, or flavor, as they propagate through space. These oscillations between flavors are dictated by the density of neutrinos and other matter in the medium, both of which change from the core to the outer layers of a supernova. Physicists are interested in how the flavor composition of neutrinos evolve in time; this is calculated using a time evolution simulation, one of the most popular calculations currently done on quantum computers.

Ideally, researchers could calculate each interaction between every possible pair of neutrinos in the system. However, supernovae produce around 10^58 neutrinos, a literally astronomical number. “It’s really complex, it’s very hard to solve on classical computers,” Siwach says. “That’s why we are interested in quantum computing because quantum computers are a natural way to map such problems.”

Katie Harrison

This naturalness is due to the “two-level” similarities between quantum computers and neutrino flavors. Qubits are composed of two-level states, and neutrino flavor states are approximated as two levels in most physical systems including supernovae.

In a paper published in Physical Review D in October, Siwach, Harrison, and Balantekin studied the collective oscillation problem using a quantum-assisted simulator, or QAS, which combines the benefits of the natural mapping of the system onto qubits and classical computers’ strength in solving matrix equations.

In QAS, the interactions between particles are broken down into a linear combination of products of Pauli matrices, which are the building blocks for quantum computing operations, while the state itself is split into a sum of simpler states. The quantum portion of the problem then boils down to computing products of basis states with each Pauli term in the interaction. These products are then inputted into the oscillation equations.

a graph with 4 neutrino traces in 4 colors — Flavor composition (y-axis) of four supernova neutrinos over time due to collective oscillations, calculated using the quantum-assisted simulator. The change in flavor for each neutrino over time shows the effect of neutrino-neutrino interactions.

“Then we get the linear-algebraic equations to solve, and solving such equations on a quantum computer requires a lot of resources,” explains Siwach. “That part we do on classical computers.”

This approach allows researchers to use the quantum computers only once before the actual time evolution simulation is done on a classical computer, avoiding common pitfalls in quantum calculations such as error accumulation over the length of the simulation due to noisy gates. The authors showed that the QAS results for a four-neutrino system match with a pure classical calculation, showcasing the power of this approach, especially compared to a purely quantum simulation which quickly deviates from the exact solution due to accumulated errors from gates controlling two qubits at the same time.

Still, as with any current application of quantum computers, there are limitations. “There’s only so much information that we can compute in a reasonable amount of time [on quantum computers],” says Siwach. She also laments the scalability of both the QAS and full quantum simulation. “One more hurdle is scaling to a larger number of neutrinos. If we scale to five or six neutrinos, it will require more qubits and more time, because we have to reduce the time step as well.”

Harrison, who was an undergraduate physics student at UW–Madison during this project, was supported by a fellowship from the Open Quantum Initiative, a new program to expand undergrad research experiences in quantum computing and quantum information science. She enjoyed her time in the program and thinks that it benefits students looking to get involved in research in the field: “I think it’s really good for students to see what it really means to do research and to see if it’s something that you’re capable of doing or something that you’re interested in.”

trace of neutrino flavor composition over time comparing a quantum simulation to a full classical one — Flavor composition of a neutrino over time using a full quantum simulation (red points) compared to exact solution (black line). The points start to drift from the exact solution after only a few oscillations, highlighting how noise in the quantum computer negatively affects the calculation.

Welcome, Professor Matthew Otten!

Posted on December 11, 2023

Matthew Otten

Atomic, molecular and optical and quantum theorist Matthew Otten will join the UW–Madison physics department as an assistant professor on January 3, 2024. He joins us most recently from HRL Laboratories. Prior to HRL, Otten earned his PhD from Cornell University, and then was the Maria Goeppert Mayer fellow at Argonne National Laboratory.

Please give an overview of your research.

Very generally, my goal is to make utility scale quantum computing a reality, and to get there faster than we would otherwise without my help. We have a lot of theoretical reasons to believe that quantum algorithms will be faster in certain areas; in practice, we need to know how expensive it’s going to be. It could be that a back of the envelope calculation says a quantum computer might be better, but because quantum computers are very expensive to build and have a lot of overhead, you could find that once you crunch the numbers really carefully, it turns out to cost more money or more energy or more time than just doing it on a supercomputer. In that case, it’s not worth the investment to build it, or at least not at this point. Part of my research is to understand and develop quantum algorithms and count how expensive they are. Once you do that, you can figure out the reason it’s so expensive is A and B. Then we go and we try to fix A and B, and then whack-a-mole all these bottlenecks down and eventually you go from, “It’ll never work,” to “Okay, it’ll work in twenty years.”

Another part of my research is looking at the physical qubits. These devices all have a lot of deep physics inside of them. If you just look at it from the quantum algorithm level, you might get so far. But if you dig down and try to understand the underlying physics, I think you can get further. You might be able to make devices cheaper, faster, or more performant in general. I do a lot of simulations of the underlying physics of these various types of qubits to understand what their properties are, what causes the noise that ruins computation, and what we can do to fix that noise. Through simulations on classical computers, sometimes very large ones, we come up with ways to tweak the system so that you get better performance, by coming up with better quantum algorithms and better qubits. Put those together and hopefully you get to a better quantum computer.

Once you arrive in Madison, what are one or two research projects you think your group will focus on first?

I’ll be bringing a few projects with me. The first is part of a DARPA program called Quantum Benchmarking, which I was part of while at HRL. We found really high-value computational tasks, not specifically quantum, that Boeing, which owns HRL, would like calculated: for instance, reducing corrosion. Corrosion causes planes to be grounded for maintenance, which is costly. Reducing corrosion will reduce maintenance costs and increase uptime. We’ve been developing ways to ask and answer the question, how close are today’s quantum computers to solving that problem? How big do quantum computers need to be to solve that problem? The specific task is understanding what it takes to solve such a large-scale problem, counting the quantum resources that are necessary and coming up with tests so that you could go to a quantum computer, run the tests, and hopefully be able to predict how much bigger or how much faster they would need to be to solve the problem.

Another one comes from the Wellcome Leap Foundation. We are trying to do the largest, most accurate calculation of biological objects — a molecule, string of carbon, something like this — possible on a real-life quantum computer. We’re trying to take techniques that have already been developed or develop new techniques to make circuits smaller, which means a less expensive quantum computer, and faster. That one is a competition, they gave us funding to do it, but if we complete the task better than other competitors, we get more funding to do more.

What attracted you to UW–Madison?

The strength of the science that’s happening in the physics and broader Wisconsin community is very attractive. When I visited, everyone was very nice, it’s a very collegial department. And being from St. Louis, I like the Midwest. I’ve lived in Southern California for a couple of years now and I haven’t seen snow, and that’s sad. Madison is a lovely area. Great people.

What is your favorite element and/or elementary particle?

I think it has to be silicon. Silicon is used in classical computing and potentially has use in quantum computing. And you’re carrying around silicon right now, just like everyone else.

What hobbies and interests do you have?

I have a Siberian Husky puppy and we’ll be very happy to go to Madison and do a lot of skijoring, which is cross country skiing, but the dog pulls you. I started running recently and I was jazzed up for my first half marathon and then I got COVID and I didn’t do it, so I’m still jazzed up for my first half marathon. I play a lot of board games and have a very large board game collection. And my daughter just turned one. She’s become a new hobby.

Ben Woods and team named finalists in 2023 WARF Innovation Awards

Posted on November 27, 2023

Each fall the WARF Innovation Awards recognize some of the best inventions at UW–Madison. WARF receives hundreds of new invention disclosures each year. Of these disclosures, the WARF Innovation Award finalists are considered exceptional in the following criteria:

Has potential for high long-term impact
Presents an exciting solution to a known important problem
Could produce broad benefits for humankind

One of the six finalists comes from Physics. Research Associate Benjamin Woods and a team including Distinguished Scientist Mark Friesen, John Bardeen Prof. of Physics Mark Eriksson, Honorary Associate Robert Joynt, and Graduate Student Emily Joseph developed a quantum device that shows a significant increase in valley splitting, a key property needed for error-free quantum computing. The device features a novel structural composition that turns conventional wisdom on its head.

Two winners, selected from the six finalists, will be announced in WARF’s annual holiday greeting; sign up to receive the greeting here. Each of the two Innovation Award winners receive $10,000, split among UW inventors.

“Sandwich” structure found to reduce errors caused by quasiparticles in superconducting qubits

Posted on September 27, 2023

Qubits are notoriously more prone to error than their classical counterparts. While superconducting quantum computers currently use on the order of 100 to 1000 qubits, an estimated one million qubits will be needed to track and correct errors in a quantum computer designed for real-world applications. At present, it is not known how to scale superconducting qubit circuits to this size.

In a new study published in PRX Quantum, UW–Madison physicists from Robert McDermott’s group developed and tested a new superconducting qubit architecture that is potentially more scalable than the current state of the art. Control of the qubits is achieved via “Single Flux Quantum” (SFQ) pulses that can be generated close to the qubit chip. They found that SFQ-based control fidelity improved ten-fold over their previous versions, providing a promising platform for scaling up the number of qubits in a quantum array.

Robert McDermott

Vincent Liu

The architecture involves a sandwich of two chips: one chip houses the qubits, while the other contains the SFQ control unit. The new approach suppresses the generation of quasiparticles, which are disruptions in the superconducting ground state that degrade qubit performance.

“This structure physically separates the two units, and quasiparticles on the SFQ chip cannot diffuse to the quantum chip and generate errors,” explains Chuan-Hong Liu, PhD ’23, a former UW–Madison physics graduate student and lead author of the study. “This design is totally new, and it greatly improves our gate fidelities.”

Liu and his colleagues assessed the fidelity of SFQ-based gates through randomized benchmarking. In this approach, the team established operating parameters to maximize the overall fidelity of complex control sequences. For instance, for a qubit that begins in the ground state, they performed long sequences incorporating many gates that should be equivalent to an identity operation; in the end, they measured the fraction of the population remaining in the ground state. A higher measured ground state population indicated higher gate fidelity.

Inevitably, there are residual errors, but the reduced quasiparticle poisoning was expected to lower the error rate and improve gate fidelities — and it did.

four panels showing the new chip architecture. The two on the left just show the two computer chips, and then the top right panel shows them "sandwiched" on top of each other. The bottom right panel is a circuit diagram of the whole setup. — The quantum-classical multichip module (MCM). (a) A micrograph of the qubit chip. (b) A micrograph of the SFQ driver chip. (c) A photograph showing the assembled MCM stack; the qubit chip is outlined in red and the SFQ chip is outlined in blue. (d) The circuit diagram for one qubit-SFQ pair. | From Liu et al, PRX Quantum.

“Most of the gates had 99% fidelity,” Liu says. “That’s a one order of magnitude reduction in infidelity compared to the last generation.”

Importantly, they showed the stability of the SFQ-based gates over the course of a six-hour experimental run.

Later in the study, the researchers investigated the source of the remaining errors. They found that the SFQ unit was emitting photons with sufficient energy to create quasiparticles on the qubit chip. With the unique source of the error identified, Liu and his colleagues can develop ways to improve the design.

“We realized this quasiparticle generation is due to spurious antenna coupling between the SFQ units and the qubit units,” Liu says. “This is really interesting because we usually talk about qubits in the range of one to ten gigahertz, but this error is in the 100 to 1000 gigahertz range. This is an area people have never explored, and we provide a straightforward way to make improvements.”

This study is a collaboration between the National Institute of Standards and Technology, Syracuse University, Lawrence Livermore National Laboratory, and UW–Madison.

This work was funded in part by the National Science Foundation (DMR-1747426); the Wisconsin Alumni Research Foundation (WARF) Accelerator; Office of the Director of National Intelligence, Intelligence Advanced Research Projects Activity (IARPA-20001-D2022-2203120004); and the NIST Program on Scalable Superconducting Computing and the National Nuclear Security Administration Advanced Simulation and Computing Beyond Moore’s Law program (LLNL-ABS-795437).

Partnerships bring together UW–Madison quantum computing research, industry leaders

Posted on June 15, 2023

Two leading companies in semiconductor quantum computing are partnering with researchers at the University of Wisconsin–Madison, itself a long-time academic leader in quantum computing.

UW–Madison’s separate partnerships with Intel and HRL Laboratories are part of a first round of collaborations announced June 14 by the LPS Qubit Collaboratory (LQC), a national Quantum Information Science Research Center hosted at the Laboratory for Physical Sciences (LPS). Established in support of the National Quantum Initiative Act, LQC is facilitating partnerships between industry and academic and national labs to advance research in quantum information science.

“These collaborations are great examples of UW–Madison partnering with industry on the development of important technologies, in this case semiconductor quantum computers,” says physics professor Mark Eriksson, the UW–Madison lead on the partnerships.

Read the full story

Finding some wiggle room in semiconductor quantum computers

Posted on January 25, 2023

a geometric pattern of lines in green, light gold, and black/dark purple, representing the qubit

Classical computers rarely make mistakes, thanks largely to the digital behavior of semiconductor transistors. They are either on or they’re off, corresponding to the ones and zeros of classical bits.

On the other hand, quantum bits, or qubits, can equal zero, one or an arbitrary mixture of the two, allowing quantum computers to solve certain calculations that exceed the capacity of any classical computer. One complication with qubits, however, is that they can occupy energy levels outside the computational one and zero. If those additional levels are too close to one or zero, errors are more likely to occur.

“In a classical computer, all the aspects of a transistor are super uniform,” says UW–Madison Distinguished Scientist Mark Friesen, an author on both papers. “Silicon qubits are in many ways like transistors, and we’ve gotten to the stage where we can control the qubit properties very well, except for one.”

That one property, known as the valley splitting, is the buffer between the computational one-zero energy levels and the additional energy levels, helping to reduce quantum computing errors.

In two papers published in Nature Communications in December, researchers from the University of Wisconsin–Madison, the University of New South Wales and TU-Delft showed that tweaking a qubit’s physical structure, known as a silicon quantum dot, creates sufficient valley splitting to reduce computing errors. The findings turn conventional wisdom on its head by showing that a less perfect silicon quantum dot can be beneficial.

Read the full story

Welcome, Roman Kuzmin, the Dunson Cheng Assistant Professor of Physics

Posted on December 27, 2022

Roman Kuzmin

In the modern, cutting-edge field of quantum computing, it can be a bit puzzling to hear a researcher relate their work to low-tech slide rules. Yet that is exactly the analogy that Roman Kuzmin uses to describe one of his research goals, creating quantum simulators to model various materials. He also studies superconducting qubits and ways to increase coherence in this class of quantum computer.

Kuzmin, a quantum information and condensed matter scientist, will join the department as an the Dunson Cheng Assistant Professor of Physics on January 1. He is currently a research scientist at the University of Maryland’s Joint Quantum Institute in College Park, Md, and recently joined us for an interview.

Can you please give an overview of your research?

My main fields are quantum information and condensed matter physics. For example, one of my interests is to solve complicated condensed matter problems using new techniques and materials which quantum information science developed. Also, it works in the other direction. I am also trying to improve materials which are used in quantum information. I work in the subfield of superconducting circuits. There are several different directions in quantum information, and the physics department at Wisconsin has many of them already, so I will complement work in the department.

Once you’re in Madison and your lab is up and running, what are the first big one or two big things you want to really focus your energy on?

One is in quantum information and quantum computing. So, qubits are artificial atoms or building blocks of a quantum computer. I’m simplifying it, of course, but there are environments which try to destroy coherence. In order to scale up those qubits and make quantum computers larger and larger — because that’s what you need eventually to solve anything, to do something useful with it — you need to mitigate decoherence processes which basically prevent qubits from working long enough. So, I will look at the sources of those decoherence processes and try to make qubits live longer and be longer coherent.

A second project is more on the condensed matter part. I will build very large circuits out of Josephson junctions, inductors and capacitors, and such large circuits behave like some many-body objects. It creates a problem which is very hard to solve because it contains many parts, and these parts interact with each other such that the problem is much more complicated than just the sum of those parts.

What are some applications of your work?

Of course this work is interesting for developing theory and understanding our world. But the application, for example for the many-body system I just described, it’s called the quantum impurity. One of my goals is to use this to create a simulator which can potentially model some useful material. It’s like if you have a quantum computer, you can write a program and it will solve something for you. A slide rule is a physical device that allows you to do complicated, logarithmic calculations, but it’s designed to do only this one calculation. I’m creating kind of a quantum slide rule.

What is your favorite element and/or elementary particle?

So, I have my favorite circuit element: Josephson junction. (editor’s note: the question did not specify atomic element, so we appreciate this clever answer!). And for elementary particle, the photon, especially microwave photons, because that’s what I use in these circuits to do simulations. They’re very versatile and they’re just cool.

What hobbies and interests do you have?

I like reading, travelling, and juggling.

Cross-institutional collaboration leads to new control over quantum dot qubits

Posted on August 31, 2022

a greyscale image makes up the border of this square image, with a full-color square in the exact center. the image shows tiny tunnel-like features, all congregating in the middle

This story was originally published by the Chicago Quantum Exchange

Qubits are the building blocks of quantum computers, which have the potential to revolutionize many fields of research by solving problems that classical computers can’t.

But creating qubits that have the perfect quality necessary for quantum computing can be challenging.

Researchers at the University of Wisconsin–Madison, HRL Laboratories LLC, and University of New South Wales (UNSW) collaborated on a project to better control silicon quantum dot qubits, allowing for higher-quality fabrication and use in wider applications.

All three institutions are affiliated with the Chicago Quantum Exchange. The work was published in Physical Review Letters, and the lead author, J. P. Dodson, has recently transitioned from UW–Madison to HRL.

“Consistency is the thing we’re after here,” says Mark Friesen, Distinguished Scientist of Physics at UW–Madison and author on the paper. “Our claim is that there is actually hope to create a very uniform array of dots that can be used as qubits.”

Sensitive quantum states

While classical computer bits use electric circuits to represent two possible values (0 and 1), qubits use two quantum states to represent 0 and 1, which allows them to take advantage of quantum phenomena like superposition to do powerful calculations.

Qubits can be constructed in different ways. One way to build a qubit is by fabricating a quantum dot, or a very, very small cage for electrons, formed within a silicon crystal. Unlike qubits made of single atoms, which are all naturally identical, quantum dot qubits are man-made—allowing researchers to customize them to different applications.

But one common wrench in the metaphorical gears of these silicon qubits is competition between different kinds of quantum states. Most qubits use “spin states” to represent 0 and 1, which rely on a uniquely quantum property called spin. But if the qubit has other kinds of quantum states with similar energies, those other states can interfere, making it difficult for scientists to effectively use the qubit.

In silicon quantum dots, the states that most often compete with the ones needed for computing are “valley states,” named for their locations on an energy graph—they exist in the “valleys” of the graph.

To have the most effective quantum dot qubit, the valley states of the dot must be controlled such that they do not interfere with the quantum information-carrying spin states. But the valley states are extremely sensitive; the quantum dots sit on a flat surface, and if there is even one extra atom on the surface underneath the quantum dot, the energies of the valley states change.

The study’s authors say these kinds of single-atom defects are pretty much “unavoidable,” so they found a way to control the valley states even in the presence of defects. By manipulating the voltage across the dot, the researchers found they could physically move the dot around the surface it sits on.

“The gate voltages allow you to move the dot across the interface it sits on by a few nanometers, and by doing that, you change its position relative to atomic-scale features,” says Mark Eriksson, John Bardeen Professor and chair of the UW–Madison physics department, who worked on the project. “That changes the energies of valley states in a controllable way.

“The take home message of this paper,” he says, “is that the energies of the valley states are not determined forever once you make a quantum dot. We can tune them, and that allows us to make better qubits that are going to make for better quantum computers.”

Building on academic and industry expertise

The host materials for the quantum dots are “grown” with precise layer composition. The process is extremely technical, and Friesen notes that Lisa Edge at HRL Laboratories is a world expert.

“It requires many decades of knowledge to be able to grow these devices properly,” says Friesen. “We have several years of collaborating with HRL, and they’re very good at making really high-quality materials available to us.”

The work also benefitted from the knowledge of Susan Coppersmith, a theorist previously at UW–Madison who moved to UNSW in 2018. Eriksson says the collaborative nature of the research was crucial to its success.

“This work, which gives us a lot of new knowledge about how to precisely control these qubits, could not have been done without our partners at HRL and UNSW,” says Eriksson. “There’s a strong sense of community in quantum science and technology, and that is really pushing the field forward.”

Mark Saffman named WARF professor

Posted on May 19, 2022

This post is adapted from the original

Mark Saffman

Thirty-two members of the University of Wisconsin–Madison faculty — including physics professor Mark Saffman — have been awarded fellowships from the Office of the Vice Chancellor for Research and Graduate Education for 2022-23. The awardees span the four divisions on campus: arts and humanities, physical sciences, social sciences and biological sciences.

“These awards provide an opportunity for campus to recognize our outstanding faculty,” says Steve Ackerman, vice chancellor for research and graduate education. “They highlight faculty efforts to support the research, teaching, outreach and public service missions of the university.”

The awards are possible due to the research efforts of UW–Madison faculty and staff. Technology that arises from these efforts is licensed by the Wisconsin Alumni Research Foundation and the income from successful licenses is returned to the OVCRGE, where it’s used to fund research activities and awards throughout the divisions on campus.

Mark Saffman was awarded a WARF professorship. These professorships come with $100,000 and honor faculty who have made major contributions to the advancement of knowledge, primarily through their research endeavors, but also as a result of their teaching and service activities. Award recipients choose the names associated with their professorships. Saffman, the Johannes Rydberg Professor of Physics and director of The Wisconsin Quantum Institute, first began work on atomic physics and initiated a long-term effort to develop quantum computers. He is known for his research as a leader in the ongoing development of atomic quantum computers based on the Rydberg blockade mechanism.

In addition, physics affiliate professor Mikhail Kats received a Romnes Faculty Fellowship.

UW–Madison, industry partners run quantum algorithm on neutral atom quantum computer for the first time

Posted on April 20, 2022

a quantum computing lab with lots and lots of wires and a main hardware piece in the center

A university-industry collaboration has successfully run a quantum algorithm on a type of quantum computer known as a cold atom quantum computer for the first time. The achievement by the team of scientists from the University of Wisconsin–Madison, ColdQuanta and Riverlane brings quantum computing one step closer to being used in real-world applications. The work out of Mark Saffman’s group was published in Nature on April 20.

Read the joint press release

Read the press release tipsheet