Equation-of-state accuracy ε is proposed as a QA fidelity metric; classical QMC benchmarks reach 10^8 Rydberg atoms at ε ~ 10^{-2}–10^{-4}, outperforming estimated experimental platforms.
Challenging the Quantum Advantage Frontier with Large-Scale Classical Simulations of Annealing Dynamics
7 Pith papers cite this work, alongside 1 external citations. Polarity classification is still indexing.
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abstract
Recent demonstrations of D-Wave's annealing-based quantum simulators have established new benchmarks for quantum computational advantage [arXiv:2403.00910]. However, the precise location of the classical-quantum computational frontier remains an open question, as classical simulation strategies continue to evolve. Here, we demonstrate that time-dependent variational Monte Carlo (t-VMC) with a physically motivated Jastrow-Feenberg wave function can efficiently simulate the quantum annealing of spin glasses up to system sizes previously thought to be intractable. Our approach achieves accuracy comparable to that of quantum processing units while requiring only polynomially scaling computational resources, in stark contrast to entangled-limited tensor network methods that scale exponentially. For systems up to 128 spins on a three-dimensional diamond lattice, we maintain correlation errors below 7%, which match or exceed the precision of existing quantum hardware. Rigorous assessments of residual energies and time-dependent variational principle errors establish clear performance benchmarks for classical simulations. These findings substantially shift the quantum advantage frontier and underscore that classical variational techniques, which are not fundamentally constrained by entanglement growth, remain competitive at larger system sizes than previously anticipated.
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In the 2D Hubbard model, the long-time double occupancy after a ramp quench matches the canonical thermal value for U≤3 but deviates above U≈3–4, suggesting thermalization breakdown.
Deep Boltzmann Quantum States with natural-gradient optimization and annealing-like training match exact or best-known solutions for large infinite-range Ising spin glasses and solve job shop scheduling instances.
For unitaries from local or pairwise interactions, depolarizing noise above a critical strength makes open quantum spin chain dynamics exactly classically simulable by halting growth in the negative Markov chain representation.
SBQA adds inter-replica interactions to simulated bifurcation to mimic quantum tunneling and improves performance on sparse rugged optimization problems over standard SBM.
A parallel-in-time encoding turns quantum dynamical propagators into QUBO instances for direct benchmarking of quantum annealers against classical solvers on models from single-qubit rotations to PT-symmetric systems.
All-step fixed-point amplitude amplification on IBM Heron preserves sequential Tiger POMDP posteriors and planner actions across 8–32 step horizons inside a measured operating envelope.
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A fidelity metric for quantum annealing benchmarked by extreme scaling quantum Monte-Carlo simulations
Equation-of-state accuracy ε is proposed as a QA fidelity metric; classical QMC benchmarks reach 10^8 Rydberg atoms at ε ~ 10^{-2}–10^{-4}, outperforming estimated experimental platforms.
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Thermalization Dynamics in the Two-Dimensional Hubbard Model with Neural-Network Quantum States
In the 2D Hubbard model, the long-time double occupancy after a ramp quench matches the canonical thermal value for U≤3 but deviates above U≈3–4, suggesting thermalization breakdown.
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Solving Classical and Quantum Spin Glasses with Deep Boltzmann Quantum States
Deep Boltzmann Quantum States with natural-gradient optimization and annealing-like training match exact or best-known solutions for large infinite-range Ising spin glasses and solve job shop scheduling instances.
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Quantum-to-Classical Computability Transition via Negative Markov Chains
For unitaries from local or pairwise interactions, depolarizing noise above a critical strength makes open quantum spin chain dynamics exactly classically simulable by halting growth in the negative Markov chain representation.
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Simulated Bifurcation Quantum Annealing
SBQA adds inter-replica interactions to simulated bifurcation to mimic quantum tunneling and improves performance on sparse rugged optimization problems over standard SBM.
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Quantum-inspired dynamical models on quantum and classical annealers
A parallel-in-time encoding turns quantum dynamical propagators into QUBO instances for direct benchmarking of quantum annealers against classical solvers on models from single-qubit rotations to PT-symmetric systems.
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QANTIS: Hardware-Calibrated Sequential POMDP Belief Updates on IBM Heron
All-step fixed-point amplitude amplification on IBM Heron preserves sequential Tiger POMDP posteriors and planner actions across 8–32 step horizons inside a measured operating envelope.