A research collaboration led by the Lawrence Berkeley National Laboratory (LBNL) has successfully simulated hadronization—the fundamental particle physics process where quarks bind via the strong nuclear force to create composite hadrons like protons and neutrons—on a physical quantum processor. Executed by LBNL research scientist Anthony Ciavarella and published in Physical Review D, the simulation mapped real-time string-breaking dynamics using 104 active qubits on an IBM Heron processor (ibm_torino). The access pipeline was facilitated by the Quantum Computer User Program (QCUP), a federal cloud-access infrastructure framework managed by the Oak Ridge Leadership Computing Facility (OLCF) at Oak Ridge National Laboratory.
[ LBNL Hadronization Simulation Stack ]
Compute Fabric ──► Cloud-routed access to IBM Heron QPU leveraging 104 active qubits.
Physical Mechanism ──► One-dimensional SU(2) lattice gauge theory tracking gluon string breaking.
Algorithmic Engine ──► Scalable circuit concurrent variational quantum solver for vacuum state prep.
Accurately calculating quantum chromodynamics (QCD)—the underlying physics governing how the strong interaction entangles quarks and gluons—presents an intractable exponential scaling problem for classical binary supercomputers. As system sizes or time steps grow, classical architectures must individually track every possible combined quantum permutation, doubling the memory requirement with every incremental step. Because qubits natively exploit quantum superposition and entanglement to model multi-body particle correlations without binary overhead, quantum processors are inherently optimized to simulate subatomic states. Ciavarella bypassed near-term hardware error limitations by applying a heavy quark limit within a simplified 1-D lattice gauge model, truncating the space of possible states while fully preserving essential gauge invariance and model symmetries.
A primary technical hurdle in utility-scale quantum simulation is preparing an accurate initial physical vacuum state before executing real-time evolution. To resolve this, the project deployed a scalable circuit concurrent variational quantum solver co-developed by Ciavarella at the University of Washington. The technique classically optimizes stable, low-energy vacuum preparation circuits on compact 10-to-12 qubit grids, determines how circuit parameters scale relative to system expansions, and then extrapolates that structural layout to over a hundred physical qubits. Following error mitigation, the Heron processor successfully reproduced early-stage string-breaking dynamics that aligned with classical references. Crucially, the quantum run captured a localized “gasifying” effect at finite temperatures just prior to gluon string separation—validating a theoretical QCD phenomenon previously observed only in restricted classical approximations.
The official project announcement, institutional computing guidelines, and administrative access parameters can be reviewed through the Oak Ridge Leadership Computing Facility. The peer-reviewed physical findings and 104-qubit lattice performance datasets can be audited directly via Physical Review D here.
July 4, 2026
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