Through the Quantum Computer User Program (QCUP), a research scientist at Lawrence Berkeley National Laboratory has, for the first time, modeled hadronization, the process where quarks bind together, on an IBM quantum computer. This simulation offers a new avenue for particle physics research, bypassing limitations inherent in classical computing, and focuses on a crucial step occurring immediately after collisions at the Large Hadron Collider (LHC) at CERN. Understanding hadronization is fundamental, as protons and neutrons, the building blocks of atomic nuclei, are created through this process, directly impacting our understanding of matter and the universe. “In principle, we know the theory that describes hadronization, but we are unable to make predictions using it because the calculations have been too difficult for a classical computer,” said Anthony Ciavarella, the Berkeley Lab researcher who led the project; he believes quantum computers should allow direct predictions of hadronization details, aiding searches for new physics.
Hadronization Process Simulated via Quantum Computing
Simulating the birth of matter with quantum processors offers a new window into the universe’s fundamental structure. This accomplishment bypasses limitations inherent in classical supercomputing, opening new avenues for particle physics research. The simulation, while employing a simplified model, establishes a framework for leveraging quantum computers to tackle calculations beyond the reach of even the most powerful classical machines. Classical computers struggle with accurately simulating quantum chromodynamics (QCD), the theory governing the strong force binding quarks and gluons, due to the exponential increase in processing power and memory required to represent the quantum states of these particles.
Quantum computers, utilizing qubits that can exist in multiple states simultaneously, offer a more efficient approach. “One of the original motivations for building quantum computers was that they naturally have this quantum phenomenology built into how they’re constructed. And in these simulations of subatomic systems, we’ve got large amounts of entanglement and quantum correlations that you just can’t efficiently represent on a regular computer,” Ciavarella explained. The initial simulation focused on string breaking, a key mechanism where gluon strings connecting quarks stretch and snap, forming new hadrons, and utilized 104 of the 156 qubits on an IBM Heron processor. This work represents a crucial step toward simulating complex QCD systems on future quantum computers, even with their current limitations in qubit count and error rates.
One of the original motivations for building quantum computers was that they naturally have this quantum phenomenology built into how they’re constructed. And in these simulations of subatomic systems, we’ve got large amounts of entanglement and quantum correlations that you just can’t efficiently represent on a regular computer.
QCUP Access & IBM Heron Processor Utilization
Access to quantum computing resources is no longer limited to large institutions with dedicated hardware; the Quantum Computer User Program (QCUP) is expanding the scope of research possible in fields like particle physics. Hadronization occurs immediately following collisions at facilities like CERN’s Large Hadron Collider, rendering direct observation of each step impossible and necessitating computational modeling to understand the underlying physics. The Berkeley Lab scientist, Anthony Ciavarella, leveraged 104 of the 156 qubits available on IBM’s Heron processor via cloud access provided by QCUP. To manage computational demands, Ciavarella utilized a “scalable circuit concurrent variational quantum solver,” a technique he co-developed during his graduate studies.
This allowed him to bring the quantum computer’s qubits to a quantum vacuum state, optimizing circuits for increasing system sizes and enabling extrapolation to larger, more complex simulations. “The idea is to optimize these vacuum preparation circuits on a small system size. Then you do it slightly bigger and slightly bigger and slightly bigger. So, by doing this, you can understand how the parameters of your circuit depend on the system size, and you can then extrapolate that out to doing it for a large system,” Ciavarella said. The initial simulation was limited to one dimension, but Ciavarella intends to expand to additional dimensions as quantum hardware and algorithms improve, having already reproduced results consistent with those obtained using classical supercomputers.
“One of the findings that we reproduced here is that, in the middle of the gluon string, it starts to look like it’s gasifying at a finite temperature before it separates,” he noted, suggesting a potential fundamental feature of quantum chromodynamics.
In principle, we know the theory that describes hadronization, but we are unable to make predictions using it because the calculations have been too difficult for a classical computer. However, on a quantum computer, we should be able to directly make predictions for the details of how hadronization occurs, which will help with the searches for new physics performed at colliders such as the LHC.
Anthony Ciavarella, the Berkeley Lab research scientist
Scalable Circuit Variational Solver for Quantum Vacuum
This technique focuses on optimizing circuits for small systems, then incrementally increasing complexity to extrapolate results for larger, more realistic models. Ciavarella’s method builds upon existing techniques used in classical QCD simulations, but adapts them for the unique capabilities of quantum computers. He initially simplified the simulation by focusing on heavy quarks, which are easier to model due to their limited spatial spread, and restricted the simulation to one dimension. This allowed for a focused test of the “scalable circuit concurrent variational quantum solver” and its ability to prepare the necessary quantum vacuum. Specifically, the simulation confirmed that the gluon string connecting quarks appears to gasify before breaking apart, a finding Ciavarella believes could be a fundamental feature of quantum chromodynamics. Ciavarella intends to expand the simulation to include additional dimensions as quantum computing technology advances, further refining the understanding of these fundamental interactions.
The idea is to optimize these vacuum preparation circuits on a small system size. Then you do it slightly bigger and slightly bigger and slightly bigger. So, by doing this, you can understand how the parameters of your circuit depend on the system size, and you can then extrapolate that out to doing it for a large system. For example, you can optimize this on up to qubits and then extrapolate that out to hundreds if you choose to do so.
String Breaking & Reproduction of Classical Results
Simulating the intricate process of hadronization, where quarks bind to form hadrons like protons and neutrons, has long been a challenge for classical supercomputers, but recent work demonstrates a successful quantum simulation of this phenomenon. Ciavarella’s work focused on string breaking, a fundamental mechanism within hadronization where gluon strings stretch and ultimately snap, creating new quark-antiquark pairs. To simplify the simulation, he utilized a heavy quark limit, focusing on more massive quarks that are easier to model. This approach allows for extrapolation to larger, more complex systems. The simulation, limited to one spatial dimension for computational efficiency, successfully reproduced results obtained from classical supercomputers, validating the quantum approach. The team notably observed a phenomenon within the gluon string itself. This initial success paves the way for more complex, multi-dimensional simulations and a deeper understanding of the fundamental building blocks of matter and the universe.
One of the findings that we reproduced here is that, in the middle of the gluon string, it starts to look like it’s gasifying at a finite temperature before it separates. This is exciting because, if we see this reproduced across a wide range of different simplified models, then it should be more likely it’s an actual feature of QCD that describes the world we live in.
