Quantum Simulations of SU(2) Lattice Gauge Theory with 18 Qubits Enable Study of Energy-Loss and Hadronization

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Understanding energy loss and hadronization, crucial processes in strongly-interacting matter, presents a significant challenge to physicists, but Zhiyao Li, Marc Illa from the Pacific Northwest National Laboratory, and Martin J. Savage from the University of Washington, have established a new framework for simulating these phenomena on a quantum computer. Their work overcomes conceptual hurdles inherent in simulating non-Abelian gauge theories, allowing researchers to compute the evolution of energy, charge densities, and entanglement within light quarks. By mapping heavy quarks to qubits and employing innovative techniques like Domain Decomposition and fermionic SWAP operations, the team successfully performs simulations on 18 qubits, achieving a level of complexity previously inaccessible. The resulting data aligns with classical simulations and, importantly, this framework extends to other non-Abelian groups, paving the way for more accurate modelling of chromodynamics and a deeper understanding of the fundamental forces governing matter. This work establishes a framework for performing simulations of such systems on a quantum computer, and applies it to a system of heavy quarks moving through a lattice of light quarks, utilizing an SU(2) model.
This research advances the ability to model non-equilibrium systems and provides a pathway toward simulating jet physics and hadronization in quantum chromodynamics, the theory describing the strong force. The study successfully implemented a method for evolving the energy of light quarks, their charge densities, and their entanglement, allowing for detailed observation of their interactions. Researchers mapped both heavy and light quarks to qubits, restricting heavy-quark movement to discrete steps across the lattice, and implemented color entanglement using hadronic operators. Zero-Noise Extrapolation of Pauli Matrix Elements Scientists have performed a quantum computation experiment using IBM’s ibm_pittsburgh quantum computer to characterize the ground state of a quantum system. The research team measured specific quantum properties, known as matrix elements, to understand the system’s behaviour. They compared these measurements to both theoretical calculations and results from a noiseless simulation, employing a technique called Zero-Noise Extrapolation (ZNE) to minimize the impact of errors inherent in quantum computers. ZNE involves running the computation with varying levels of added noise and then extrapolating to estimate the ideal, noise-free result. The results demonstrate the importance of error mitigation in quantum computation, as initial measurements significantly differed from theoretical predictions. By validating the quantum simulation against theoretical predictions, researchers confirmed the accuracy of their approach.
Simulating Heavy Quark Interactions in Strong Matter Scientists have achieved a significant breakthrough in simulating the behavior of strongly-interacting matter, essential for understanding extreme conditions found in high-energy heavy-ion collisions. Domain decomposition proved effective in preparing the initial quantum state, and scalable circuits were developed to account for the varying characteristics of the system. Experiments were performed using IBM’s ibm_pittsburgh quantum computer with 18 qubits, simulating a system spanning three spatial sites. The circuits required for state preparation, quark motion, and a single time evolution step achieved a significant level of complexity. A suite of error mitigation techniques was employed to extract accurate observables, yielding results consistent with classical simulations. Measurements confirm the ability to simulate the discrete motion of heavy quarks between lattice sites using specific quantum operations.
The team measured the energy loss of heavy quarks as they traverse the lattice, providing insights into the dynamics of energy transfer within the simulated medium. These simulations demonstrate a pathway toward understanding the complex processes occurring in extreme environments, such as those created in heavy-ion collisions, and offer a foundation for future studies of quantum field theories using quantum computers. The framework developed generalizes readily to other non-Abelian groups, including SU(3), which is central to the study of quantum chromodynamics. Quantum Simulation of Quark Energy Loss This research establishes a novel framework for simulating the dynamics of energy loss and hadronization within strongly-interacting matter, crucial for understanding the behaviour of matter under extreme conditions created in high-energy collisions. By applying this framework to a model system of heavy quarks moving through a lattice of light quarks, scientists have demonstrated the ability to simulate key aspects of energy transfer and the evolution of entanglement between particles.
The team successfully mapped the simulation onto a quantum computer, utilising 18 qubits to model the system and perform a simulation step, achieving results consistent with classical simulations. This work represents a significant step towards first-principles simulations of quantum chromodynamics, offering a pathway to investigate non-perturbative phenomena like fragmentation and hadronization that are difficult to model with traditional methods. The researchers acknowledge that current simulations are limited by the size and fidelity of available quantum hardware, restricting the scope to modest-sized, low-dimensional systems. Future research will focus on extending the framework to more complex systems, including three-dimensional simulations and the application to quantum chromodynamics itself, potentially unlocking a deeper understanding of the quark-gluon plasma and other exotic states of matter. 👉 More information 🗞 A Framework for Quantum Simulations of Energy-Loss and Hadronization in Non-Abelian Gauge Theories: SU(2) Lattice Gauge Theory in 1+1D 🧠 ArXiv: https://arxiv.org/abs/2512.05210 Tags:
