A hardware-efficient binary-tree ansatz has a closed-form diagonal Fubini–Study metric, enabling metric-aware VQE and time evolution without auxiliary circuits, with linear-in-k pruning for sparse sectors.
Beguˇ si´ c, J
3 Pith papers cite this work. Polarity classification is still indexing.
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abstract
A recent quantum simulation of observables of the kicked Ising model on 127 qubits implemented circuits that exceed the capabilities of exact classical simulation. We show that several approximate classical methods, based on sparse Pauli dynamics and tensor network algorithms, can simulate these observables orders of magnitude faster than the quantum experiment, and can also be systematically converged beyond the experimental accuracy. Our most accurate technique combines a mixed Schr\"{o}dinger and Heisenberg tensor network representation with the Bethe free entropy relation of belief propagation to compute expectation values with an effective wavefunction-operator sandwich bond dimension >16,000,000, achieving an absolute accuracy, without extrapolation, in the observables of <0.01, which is converged for many practical purposes. We thereby identify inaccuracies in the experimental extrapolations and suggest how future experiments can be implemented to increase the classical hardness.
representative citing papers
Systematic numerical study of QAOA parameter transfer on heavy-hex Ising models with local cubic terms shows transferred angles from small instances yield improving expectation values up to 49 layers on instances up to 156 qubits, with hardware runs confirming gains up to p=10.
Classical solvers solve random Ising models on heavy-hex graphs efficiently, with Gurobi showing linear or weakly quadratic scaling up to 100k variables and simulated annealing showing exponential time-to-solution without cubic terms.
citing papers explorer
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A hardware-efficient variational ansatz with an exact diagonal metric for real- and imaginary-time evolution and Haar sampling
A hardware-efficient binary-tree ansatz has a closed-form diagonal Fubini–Study metric, enabling metric-aware VQE and time evolution without auxiliary circuits, with linear-in-k pruning for sparse sectors.
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Evaluating the Limits of QAOA Parameter Transfer at High-Rounds on Sparse Ising Models With Geometrically Local Cubic Terms
Systematic numerical study of QAOA parameter transfer on heavy-hex Ising models with local cubic terms shows transferred angles from small instances yield improving expectation values up to 49 layers on instances up to 156 qubits, with hardware runs confirming gains up to p=10.
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Classical Combinatorial Optimization Scaling for Random Ising Models on 2D Heavy-Hex Graphs
Classical solvers solve random Ising models on heavy-hex graphs efficiently, with Gurobi showing linear or weakly quadratic scaling up to 100k variables and simulated annealing showing exponential time-to-solution without cubic terms.