Scientists Simulate Collider Physics on IBM Q Quantum Computer

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Exploring the smallest distance scales with particle colliders often requires detailed calculations of the spectra of outgoing particles (smallest filled green circles). (Image Credit: Benjamin Nachman, Berkeley Lab)

Research News Release — Lawrence Berkeley National Laboratory physicists Christian Bauer, Marat Freytsis and Benjamin Nachman have leveraged an IBM Q quantum computer through the Oak Ridge Leadership Computing Facility’s Quantum Computing User Program to capture part of a calculation of two protons colliding. The calculation can show the probability that an outgoing particle will emit additional particles.

In the team’s recent paper, published in Physical Review Letters, the researchers describe how they used a method called effective field theory to break down their full theory into components. Ultimately, they developed a quantum algorithm to allow the computation of some of these components on a quantum computer while leaving other computations for classical computers.

“For a theory that’s close to nature, we showed how this would work in principle. Then we took a very simplified version of that theory and did an explicit calculation on a quantum computer,” Nachman said.

The Berkeley Lab team aims to uncover insights about the smallest building blocks of nature by observing high-energy particle collisions in laboratory environments, such as the Large Hadron Collider in Geneva, Switzerland. The team is exploring what happens in these collisions by using calculations to compare predictions with the actual collision debris.

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“One of the difficulties of these kinds of calculations is that we want to describe a large range of energies,” Nachman said. “We want to describe the highest-energy processes down to the lowest-energy processes by analyzing the corresponding particles that fly into our detector.”

Using a quantum computer alone to solve these kinds of calculations requires a number of qubits that is well beyond the quantum compute resources available today. The team can calculate these problems on classical systems using approximations, but these ignore important quantum effects. Therefore, the team aimed to separate the calculation into different chunks that were either well-suited for classical systems or quantum computers.

The team ran experiments on the IBM Q through the OLCF’s QCUP program at the U.S. Department of Energy’s Oak Ridge National Laboratory to verify that the quantum algorithms they developed reproduced the expected results at a small scale that can still be computed and confirmed with classical computers.

“This is an absolutely critical demonstration problem,” Nachman said. “For us, it’s important that we describe these particles’ properties theoretically and then actually implement a version of them on a quantum computer. A lot of challenges that arise when you run on a quantum computer don’t happen theoretically. Our algorithm scales, so when we get more quantum resources, we will be able to make calculations that we couldn’t make classically.”

The team also aims to make quantum computers usable so that they can perform the kinds of science they hope to do. Quantum computers are noisy, and this noise introduces errors into the calculations. Therefore, the team also deployed error mitigation techniques that they had developed in previous work.

Next, the team hopes to add more dimensions to their problem, break their space up into a smaller number of points and scale up the size of their problem. Eventually, they hope to make calculations on a quantum computer that are not possible with classical computers.

“The quantum computers that are available through ORNL’s IBM Q agreement have around 100 qubits, so we should be able to scale up to bigger system sizes,” Nachman said.

The researchers also hope to relax their approximations and move to physics problems that are closer to nature so that they can perform calculations that are more than proof of concept.

The team performed the IBM Q calculations with funding from the DOE Office of Science Office of High Energy Physics as part of the Quantum Information Science Enabled Discovery program (QuantISED).

UT-Battelle LLC manages Oak Ridge National Laboratory for DOE’s Office of Science, the single largest supporter of basic research in the physical sciences in the United States. DOE’s Office of Science is working to address some of the most pressing challenges of our time. For more information, visit energy.gov/science.

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MENTIONED IN THE ARTICLE

Lawrence Berkeley National Laboratory
GovernmentUnited States · 1001-5000 FTEs

Lawrence Berkeley National Laboratory, operating under the U.S. Department of Energy, spearheads unclassified scientific research pivotal to climate technology. Their innovative work includes developing advanced energy-efficient technologies, renewable energy solutions, and cutting-edge climate modeling tools. These efforts are crucial in mitigating climate change, enhancing energy sustainability, and informing policy decisions to foster a resilient, low-carbon future.

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IBM
InvestorUnited States · 10001+ FTEs

IBM is an iconic technology pioneer founded in 1911 as the Computing-Tabulating-Recording Company and officially renamed International Business Machines Corporation in 1924. Beyond foundational computing, IBM possesses a deep legacy in aerospace and defense from building the guidance computers and Instrument Unit for NASA's historic Apollo missions to partnering with Airbus on CIMON, the first AI assistant on the ISS.

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U.S. Department of Energy (DOE)
GovernmentUnited States · 10001+ FTEs

The mission of the Department of Energy is to ensure America's security and prosperity by addressing its energy, environmental, and nuclear challenges through transformative science and technology solutions. In September, 2022, Research supported by ASCR demonstrated that classical machine learning algorithms can accurately predict ground state properties and classify quantum phases of matter using data generated from quantum experiments. In November, 2022, Research supported by Q-NEXT revealed that the performance of a sensor network is constrained by the intrinsic noise associated with the quantum states used in the network. In March, 2023, Research funded by DOE SC NP achieved the first experimental observation of entanglement between dissimilar particles, specifically positive and negative pions. In August, 2023, Research funded by DOE SC BER demonstrated strong preservation of entanglement in a two-photon absorption process involving organic molecules, offering a new approach for developing quantum light-based spectroscopy and microscopy.

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Oak Ridge National Laboratory Quantum Computing Institute (ORNL)
GovernmentUnited States · 5001-10000 FTEs

The Oak Ridge National Laboratory (ORNL) Quantum Computing Institute is a lab-wide collaboration that promotes the use of theory, computation, and experiment in the research and development of quantum computing for scientific applications of next-generation computer systems. The lab has various partnerships across the quantum ecosystem with major players such as IonQ, the EU Quantum Flagship and GENCI project, Qubitekk, Aliro Quantum, and many more.

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