Searcharxiv⌕ Search

arXiv · 2611.07960

Monopoles, Scattering and Generalized Symmetries on a Quantum Computer

Abstract

Quantum computers have advanced to the stage that interesting many-body quantum phenomena can be observed. A striking example is the magnetic monopole paradox, a problem that was only solved recently using the language of generalized symmetries. Here we demonstrate a quantum spin chain analogue of magnetic monopole scattering on Quantinuum System Model H2. We implement a novel protocol for preparing a localized quasiparticle wavepacket on top of the ground state. By combining this protocol with time evolution across a duality defect, we efficiently convert local particles into non-local string-like excitations. We demonstrate this particle-to-string conversion in the transverse-field Ising model and a symmetry-protected topological (SPT) phase of the cluster model. Our results establish duality defects and generalized symmetries as practical resources for preparing and probing non-local excitations on quantum hardware.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Oliver O'Brien, Atsushi Ueda, Etienne Granet, Henrik Dreyer, Frank Verstraete. 2026-11-05. Monopoles, Scattering and Generalized Symmetries on a Quantum Computer. https://arxiv.org/abs/2611.07960

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Quantum-to-classical transition and the emergence of trajectory level Darwinism with measurements distributed in time: a path integral approach

We present a formulation for the emergence of classical dynamics in a quantum world using a path integral approach that incorporates continuous measurements. It complements decoherence and coarse-grained measurement frameworks. The formulation provides the joint statistics of a sequence of measurements, with each Feynman path picking up a random phase proportional to the measurement strength, and we give conditions under which trajectories near classical paths dominate the probability amplitude. Information proliferates across the environment, a key feature of quantum Darwinism, via plane-wave probe scattering. In the continuous limit, momentum kicks from the probes add a further phase to each trajectory--the origin of the back-action force. We provide conditions under which measurements yield enough ``which-path'' information while keeping the wave packet localized. This describes the quantum-to-classical transition at the level of individual measurement records, complementing the ensemble description by density matrices. The same scattering that decoheres a trajectory also heats it, tying decoherence and measurement back-action together. This bounds how redundantly a classical trajectory can be recorded before back-action randomizes it into Brownian motion. The bound is not restrictive for macroscopic systems. For a trapped particle, it is set by the resolution in units of the zero-point motion and collapses to a single record where the semiclassical description of the orbit fails; for a free coordinate it marks the loss of deterministic objectivity even while the classical action remains large. In both cases, it delimits the regime in which objective classical trajectories exist. The crossover is driven by photon recoil, already resolved in levitated optomechanics; the bound recasts it as the point where a redundantly recorded trajectory, still objective, stops being deterministic.

quant-ph↗

Toward fault-tolerant quantum computation exploiting quantum spatial distribution and gauge symmetry

We explore how the integrated use of quantum spatial distribution (QSD), or more specifically, a superposition of both spin and position states of particles, and gauge symmetry (GS) revealed by Poulin's stabilizer formalism enhances quantum error correction. The study employs $3+2$ particles on nested squares proposed in the companion paper (arXiv:2504.07941), where three of them encode Shor's nine-qubit code and the remaining two detect errors in this code through their spin state measurements. The first result is that the GS offers resilience against three types of noise acting on a particle: arbitrary decoherence of its spin or position state, and dephasing of both states, which completely or partly destroys its QSD. To show that, we formulate a noise model unifying the above noise sources and prove the correctability of this unified model under our error-correcting scheme. The second result is that the QSD, together with the GS, provides architectural flexibility, allowing us to stack the error-correcting systems both vertically and horizontally. Indeed, we present implementations of the error detection (stabilizer measurement), logical Hadamard and Toffoli gates, and a quantum adder with the required interactions only between nearest-neighbor and next-nearest-neighbor particles. Here, our treatment of the dynamics of particles, each having spin and position degrees of freedom, under nontrivial noise and gate operations indicates that the stabilizer formalism is a powerful tool for describing quantum many-body dynamics.

quant-ph↗

Multi-Objective Optimization with Quantum-Annealing-Inspired Algorithms

Combinatorial optimization is widely regarded as a primary application for near-term quantum processors, although a definitive demonstration of a practical quantum advantage remains elusive. Recent studies have reported that both gate-based quantum circuits and quantum annealers can outperform state-of-the-art classical heuristics on multi-objective optimization (MO-MaxCut) problems. However, these studies did not fully account for the substantial pre- and postprocessing overheads intrinsic to quantum solvers, leading to incomplete comparisons between quantum and classical approaches. In this work, we re-examine the same benchmark suite using GPU-based quantum-annealing-inspired algorithms (QAIAs), which generate probabilistic samples analogously to quantum processors and thus serve as formidable classical contenders. Our results show that QAIAs can sample candidate solutions approximately two orders of magnitude faster than the previously studied quantum processors, based on the reported sampling and device-access times. On the instances for which a complete pipeline can be compared, the measured end-to-end QAIA runtime, including model construction, sampling and Pareto filtering, is about an order of magnitude shorter than that of the exact objective-space baselines DCM and DPA-a, and the QAIA pipeline outperforms the tested evolutionary multi-objective heuristics under an equal wall-clock budget.

quant-ph↗