We’re working on bringing the power of quantum computing – and quantum machine learning – to particle physics
Particle accelerators like the LHC take serious computing power. Often on the bleeding-edge of computing technology, accelerator projects sometimes even drive innovations in computing. In fact, while there is some controversy over exactly where the world wide web was created, it is often attributed to Tim Berners-Lee at CERN, who developed it to meet the demand for automated information-sharing between scientists in universities and institutes around the world.
With annual data generated by accelerators in excess of exabytes (a billion gigabytes), tens of millions of lines of code written to support the experiments, and incredibly demanding hardware requirements, it’s no surprise that the High Energy Physics community is interested in quantum computing, which offers real solutions to some of their hardest problems. Furthermore, the HEP community is well-positioned to support the early stages of technological development: with budgets in the 10s of billions per year and tens of thousands of scientists and engineers working on accelerator and computational physics, this is a ripe industry for quantum computing to tap.
As the authors of this paper stated: “[Quantum Computing] encompasses several defining characteristics that are of particular interest to experimental HEP: the potential for quantum speed-up in processing time, sensitivity to sources of correlations in data, and increased expressivity of quantum systems... Experiments running on high-luminosity accelerators need faster algorithms; identification and reconstruction algorithms need to capture correlations in signals; simulation and inference tools need to express and calculate functions that are classically intractable”
The authors go on to state: “Within the existing data reconstruction and analysis paradigm, access to algorithms that exhibit quantum speed-ups would revolutionize the simulation of large-scale quantum systems and the processing of data from complex experimental set-ups. This would enable a new generation of precision measurements to probe deeper into the nature of the universe. Existing measurements may contain the signatures of underlying quantum correlations or other sources of new physics that are inaccessible to classical analysis techniques. Quantum algorithms that leverage these properties could potentially extract more information from a given dataset than classical algorithms.”
Our scientists have been working with a team at DESY, one of the world’s leading accelerator centers, to bring the power of quantum computing to particle physics. DESY, short for Deutsches Elektronen-Synchrotron, is a national research center for fundamental science located in Hamburg and Zeuthen, where the Center for Quantum Technologies and Applications (CQTA) is based. DESY operates, develops, and constructs particle accelerators used to investigate the structure, dynamics and function of matter, and conducts a broad spectrum of interdisciplinary scientific research. DESY employs about 3,000 staff members from more than 60 nations, and is part of the worldwide computer network to store and analyze the enormous flood of data that is produced by the LHC in Geneva.
In a recent paper, our scientists collaborated with scientists from DESY, the Leiden Institute of Advanced Computer Science (LIACS), and Northeastern University to explore using a generative quantum machine learning model, called a “quantum Boltzmann machine” to untangle data from CERN’s LHC.
The goal was to learn probability distributions relevant to high energy physics better than the corresponding classical models. The data specifically contains “particle jet events”, which describe how colliders collect data about the subatomic particles generated during the experiments.
In some cases the quantum Boltzmann machine was indeed better, compared to a classical Boltzmann machine. The team is analyzed when and why this happens, understanding better how to apply these new quantum tools in this research setting. The team also studied the effect of the data encoding into a quantum state, noting that it can have a decisive effect on the training performance. Especially enticing is that the quantum Boltzmann machine is efficiently trainable, which our scientists showed in a recent paper published in Nature Communications Physics.
About Quantinuum
Quantinuum, the world’s largest integrated quantum company, pioneers powerful quantum computers and advanced software solutions. Quantinuum’s technology drives breakthroughs in materials discovery, cybersecurity, and next-gen quantum AI. With over 500 employees, including 370+ scientists and engineers, Quantinuum leads the quantum computing revolution across continents.
For a novel technology to be successful, it must prove that it is both useful and works as described.
Checking that our computers “work as described” is called benchmarking and verification by the experts. We are proud to be leaders in this field, with the most benchmarked quantum processors in the world. We also work with National Laboratories in various countries to develop new benchmarking techniques and standards. Additionally, we have our own team of experts leading the field in benchmarking and verification.
Currently, a lot of verification (i.e. checking that you got the right answer) is done by classical computers – most quantum processors can still be simulated by a classical computer. As we move towards quantum processors that are hard (or impossible) to simulate, this introduces a problem: how can we keep checking that our technology is working correctly without simulating it?
We recently partnered with the UK’s Quantum Software Lab to develop a novel and scalable verification and benchmarking protocol that will help us as we make the transition to quantum processors that cannot be simulated.
This new protocol does not require classical simulation, or the transfer of a qubit between two parties. The team’s “on-chip” verification protocol eliminates the need for a physically separated verifier and makes no assumptions about the processor’s noise. To top it all off, this new protocol is qubit-efficient.
The team’s protocol is application-agnostic, benefiting all users. Further, the protocol is optimized to our QCCD hardware, meaning that we have a path towards verified quantum advantage – as we compute more things that cannot be classically simulated, we will be able to check that what we are doing is right.
Running the protocol on Quantinuum System Model H1, the team ended up performing the largest verified Measurement Based Quantum Computing (MBQC) circuit to date. This was enabled by our System Model H1’s low cross-talk gate zones, mid-circuit measurement and reset, and long coherence times. By performing the largest verified MBQC computation to date, and by verifying computations significantly larger than any others to be verified before, we reaffirm the Quantinuum Systems as best-in-class.
Find the Quantinuum team at this year’s SC24 conference from November 17th – 22nd in Atlanta, Georgia. Meet our team at Booth #4351 to discover how Quantinuum is bridging the gap between quantum computing and high-performance compute with leading industry partners.
The Quantinuum team will be participating in the below panel and poster sessions to showcase our quantum computing technologies.
Monday, Nov 18, 8:00 - 8:25pm, EST
Panel: KAUST booth 1031
Nash Palaniswamy, Quantinuum’s CCO, will join a panel discussion with quantum vendors and KAUST partners to discuss advancements in quantum technology.
Wednesday, Nov 20, 3:30 – 5:00pm, EST
Panel: Educating for a Hybrid Future: Bridging the Gap between High-Performance and Quantum Computing
Vincent Anandraj, Quantinuum’s Director of Global Ecosystem and Strategic Alliances, will moderate this panel which brings together experts from leading supercomputing centers and the quantum computing industry, including PSC, Leibniz Supercomputing Centre, IQM Quantum Computers, NVIDIA, and National Research Foundation.
Thursday, Nov 21, 11:00 – 11:30am, EST
Presentation: Realizing Quantum Kernel Models at Scale with Matrix Product State Simulation
Pablo Andres-Martinez, Research Scientist at Quantinuum, will present research done in collaboration with HSBC, where the team applied quantum methods to fraud detection.
While it sounds like a gadget from Star Trek, teleportation is real – and it is happening at Quantinuum. In a new paper published in Science, our researchers moved a quantum state from one place to another without physically moving it through space - and they accomplished this feat with fault-tolerance and excellent fidelity. This is an important milestone for the whole quantum computing community and the latest example of Quantinuum achieving critical milestones years ahead of expectations.
While it seems exotic, teleportation is a critical piece of technology needed for full scale fault-tolerant quantum computing, and it is used widely in algorithm and architecture design. In addition to being essential on its own, teleportation has historically been used to demonstrate a high level of system maturity. The protocol requires multiple qubits, high-fidelity state-preparation, single-qubit operations, entangling operations, mid-circuit measurement, and conditional operations, making it an excellent system-level benchmark.
Our team was motivated to do this work by the US Government Intelligence Advance Research Projects Activity (IARPA), who set a challenge to perform high fidelity teleportation with the goal of advancing the state of science in universal fault-tolerant quantum computing. IARPA further specified that the entanglement and teleportation protocols must also maintain fault-tolerance, a key property that keeps errors local and correctable.
These ambitious goals required developing highly complex systems, protocols, and other infrastructure to enable exquisite control and operation of quantum-mechanical hardware. We are proud to have accomplished these goals ahead of schedule, demonstrating the flexibility, performance, and power of Quantinuum’s Quantum Charge Coupled Device (QCCD) architecture.
Quantinuum’s demonstration marks the first time that an arbitrary quantum state has been teleported at the logical level (using a quantum error correcting code). This means that instead of teleporting the quantum state of a single physical qubit we have teleported the quantum information encoded in an entangled set of physical qubits, known as a logical qubit. In other words, the collective state of a bunch of qubits is teleported from one set of physical qubits to another set of physical qubits. This is, in a sense, a lot closer to what you see in Star Trek – they teleport the state of a big collection of atoms at once. Except for the small detail of coming up with a pile of matter with which to reconstruct a human body...
This is also the first demonstration of a fully fault-tolerant version of the state teleportation circuit using real-time quantum error correction (QEC), decoding mid-circuit measurement of syndromes and implementing corrections during the protocol. It is critical for computers to be able to catch and correct any errors that happen along the way, and this is not something other groups have managed to do in any robust sense. In addition, our team achieved the result with high fidelity (97.5%±0.2%), providing a powerful demonstration of the quality of our H2 quantum processor, Powered by Honeywell.
Our team also tried several variations of logical teleportation circuits, using both transversal gates and lattice surgery protocols, thanks to the flexibility of our QCCD architecture. This marks the first demonstration of lattice surgery performed on a QEC code.
Lattice surgery is a strategy for implementing logical gates that requires only 2D nearest-neighbor interactions, making it especially useful for architectures whose qubit locations are fixed, such as superconducting architectures. QCCD and other technologies that do not have fixed qubit positioning might employ this method, another method, or some mixture. We are fortunate that our QCCD architecture allows us to explore the use of different logical gating options so that we can optimize our choices for experimental realities.
While the teleportation demonstration is the big result, sometimes it is the behind-the-scenes technology advancements that make the big differences. The experiments in this paper were designed at the logical level using an internally developed logical-level programming language dubbed Simple Logical Representation (SLR). This is yet another marker of our system’s maturity – we are no longer programming at the physical level but have instead moved up one “layer of abstraction”. Someday, all quantum algorithms will need to be run on the logical level with rounds of quantum error correction. This is a markedly different state than most present experiments, which are run on the physical level without quantum error correction. It is also worth noting that these results were generated using the software stack available to any user of Quantinuum’s H-Series quantum computers, and these experiments were run alongside customer jobs – underlining that these results are commercial performance, not hero data on a bespoke system.
Ironically, a key element in this work is our ability to move our qubits through space the “normal” way - this capacity gives us all-to-all connectivity, which was essential for some of the QEC protocols used in the complex task of fault-tolerant logical teleportation. We recently demonstrated solutions to the sorting problem and wiring problem in a new 2D grid trap, which will be essential as we scale up our devices.