Peaked quantum circuits claimed to show quantum advantage can be classically simulated in one hour on a GPU via mirrored MPO contraction and unswapping.
Quantum optimization benchmarking library – the in- tractable decathlon
10 Pith papers cite this work, alongside 2 external citations. Polarity classification is still indexing.
10
Pith papers citing it
2
external citations · external index
representative citing papers
Fourier-based LCU decomposes diagonal and non-diagonal unitaries into hardware-friendly forms for QAOA-style optimization, trading circuit depth for sampling overhead with performance guarantees.
SGIR-QAOA uses spectral gap information to construct QAOA parameter schedules, showing better performance than linear-ramp QAOA on Grover's problem at fixed depth, shorter depths for equivalent success probability, extension to MIS, and persistence under extrapolated gaps and mild noise.
Demonstrates a quantum wire encoding using Rydberg atom chains to solve MWIS and QUBO problems on neutral atom arrays with reduced ancilla overhead and experimental validation.
End-to-end runtime definitions and strong classical baselines show that three recent quantum advantage claims in annealing, Simon's problem, and hybrid algorithms do not hold on NISQ hardware.
HUBO formulations for logistics problems offer qubit savings over QUBO at the expense of higher circuit depth, validated classically and simulated quantumly for small cases.
A sandbox platform enables end-to-end hybrid workflows that reduce graph problems, run QAOA on IBM hardware up to 128 qubits, and refine outputs classically for problems including vertex cover and clique.
A hybrid CPU-GPU algorithm derived from Schroeppel-Shamir's subset sum method solves market split feasibility instances with up to 10 constraints and 90 variables, with reported runtimes under 15 minutes for (9,80) and up to one day for (10,90).
The paper benchmarks approximation techniques and transfer learning for setting QAOA angles at utility scale and extracts operational guidance from hardware-validated results.
citing papers explorer
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Efficient Classical Simulation of Heuristic Peaked Quantum Circuits
Peaked quantum circuits claimed to show quantum advantage can be classically simulated in one hour on a GPU via mirrored MPO contraction and unswapping.
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Efficient Fourier-Based Linear Combination of Unitaries and Applications in Quantum Optimization
Fourier-based LCU decomposes diagonal and non-diagonal unitaries into hardware-friendly forms for QAOA-style optimization, trading circuit depth for sampling overhead with performance guarantees.
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Spectral Gap Informed Ramp QAOA
SGIR-QAOA uses spectral gap information to construct QAOA parameter schedules, showing better performance than linear-ramp QAOA on Grover's problem at fixed depth, shorter depths for equivalent success probability, extension to MIS, and persistence under extrapolated gaps and mild noise.
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A quantum wire approach to weighted combinatorial graph optimisation problems
Demonstrates a quantum wire encoding using Rydberg atom chains to solve MWIS and QUBO problems on neutral atom arrays with reduced ancilla overhead and experimental validation.
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Recent quantum runtime (dis)advantages
End-to-end runtime definitions and strong classical baselines show that three recent quantum advantage claims in annealing, Simon's problem, and hybrid algorithms do not hold on NISQ hardware.
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Quantum optimization beyond QUBO for industrial logistics and scheduling
HUBO formulations for logistics problems offer qubit savings over QUBO at the expense of higher circuit depth, validated classically and simulated quantumly for small cases.
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Experimental Workflows for Combinatorial Optimization: Towards Quantum Advantage
A sandbox platform enables end-to-end hybrid workflows that reduce graph problems, run QAOA on IBM hardware up to 128 qubits, and refine outputs classically for problems including vertex cover and clique.
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GPU accelerated variant of Schroeppel-Shamir's algorithm for solving the market split problem
A hybrid CPU-GPU algorithm derived from Schroeppel-Shamir's subset sum method solves market split feasibility instances with up to 10 constraints and 90 variables, with reported runtimes under 15 minutes for (9,80) and up to one day for (10,90).
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Setting angles in quantum approximate optimization at utility-scale
The paper benchmarks approximation techniques and transfer learning for setting QAOA angles at utility scale and extracts operational guidance from hardware-validated results.
- Quantum Variational Approaches to the Maximum Independent Set Problem at Utility Scale