IBM Quantum Computer Used to Simulate Hadronization for the First Time

For decades, the fundamental process by which quarks bind through the strong nuclear force to form protons and neutrons—hadronization—has been modeled theoretically but never directly simulated on quantum hardware. That changed in 2026, when a research scientist at Lawrence Berkeley National Laboratory (Berkeley Lab) achieved a first-of-its-kind simulation of hadronization using an IBM quantum computer .

What Was Achieved

Anthony Ciavarella, a research scientist at Berkeley Lab, remotely accessed an IBM quantum computer through the Oak Ridge Leadership Computing Facility's Quantum Computing User Program (QCUP) and successfully simulated hadronization — the process by which quarks bind via the strong nuclear force to form composite particles such as protons and neutrons . This marks the first simulation of this key particle physics process on quantum hardware, laying groundwork for calculations that are impossible on classical supercomputers .

The work built on earlier research by Berkeley Lab physicists Christian Bauer, Marat Freytsis, and Benjamin Nachman, who in 2022 used a similar approach via QCUP to calculate the probability that an outgoing particle from a proton collision emits additional particles . Ciavarella's 2026 project, published in Physical Review D, focused specifically on modeling the full hadronization process .

Simplifications That Made the Simulation Possible

Today's quantum processors are still noisy and limited in qubit count. To make the hadronization calculation tractable, the team adopted several major simplifications :

• Reduced spatial dimensions: The simulation ran in a simplified 1+1 dimensional model of quantum mechanics, not in full 3D space .
• Heavy quark limit / Hilbert space truncation: The theory was mapped onto a lattice using SU(2) lattice gauge theory in 1+1 dimensions, with a truncation of the Hilbert space applied in the heavy quark limit . This dramatically reduced the number of quantum states to encode.
• Approximate interactions (locality): Because confinement limits strong-force interactions to roughly the size of a hadron, the researchers designed the simulation so that qubits only interacted with nearby neighbors rather than requiring all-to-all connectivity . This allowed the interaction to be converted into a sequence of quantum gates feasible on near-term hardware.
• Hybrid classical-quantum approach: The team used effective field theory to break the full calculation into components, running some parts on classical computers and only the most quantum-intensive parts on the quantum processor .

Key Finding: Reproducing String Breaking

The quantum simulation successfully reproduced a well-known phenomenon from earlier classical lattice QCD calculations: string breaking — the mechanism by which a gluon "string" of the strong force field between two separating quarks snaps, creating new quark-antiquark pairs . The OLCF article explicitly notes the project involved simulating "string-breaking hadronization" .

This finding validates that the simplified quantum model correctly captured the essential non-perturbative dynamics of the strong force that had previously only been accessible to classical lattice simulations. It confirms that the approach is physically meaningful, not merely a computational exercise.

Future Plans

The research team has outlined several next steps to expand the work :

• Increase dimensionality: Move from simplified 1+1 dimensional models to simulations in higher spatial dimensions.
• Relax approximations: Progress toward physics problems that are closer to nature, reducing the number of simplifications needed.
• Scale up: Take advantage of IBM's ~100+ qubit quantum systems available through QCUP to run larger, more complex simulations that classical computers cannot handle.
• Error mitigation: Continue developing and deploying error mitigation techniques to handle the noise inherent in current quantum hardware .
• Direct predictions for collider experiments: The ultimate goal is to make direct, first-principles predictions for hadronization that can be compared with data from the Large Hadron Collider, helping in the search for new physics beyond the Standard Model .