DQI-Kit automates encoding of objectives and constraints into Max-LINSAT instances and estimates expected DQI performance on the resulting problems.
arXiv preprint, 1901.04405 , year=
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BoolXLLM augments an existing Boolean rule learner with LLMs for feature selection, discretization thresholds, and natural-language rule translation to improve interpretability while preserving accuracy.
kA-QAOA matches MA-QAOA approximation ratios on 3-uniform hypergraphs while using significantly fewer function evaluations.
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.
VeloxQ is a classical QUBO solver that reports competitive or superior performance and unique scalability to 10^8-variable sparse instances across benchmarks against quantum annealers, physics-inspired methods, and conventional solvers.
Quantum annealing is described as a heuristic for discrete optimization and sampling that also serves as a platform for studying non-equilibrium many-body quantum dynamics with programmable spin systems.
citing papers explorer
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From Constraint to Code: DQI-Kit -- A Software Framework for Decoded Quantum Interferometry
DQI-Kit automates encoding of objectives and constraints into Max-LINSAT instances and estimates expected DQI performance on the resulting problems.
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BoolXLLM: LLM-Assisted Explainability for Boolean Models
BoolXLLM augments an existing Boolean rule learner with LLMs for feature selection, discretization thresholds, and natural-language rule translation to improve interpretability while preserving accuracy.
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Structured Parameterization and Non-Stabilizerness in Hypergraph QAOA
kA-QAOA matches MA-QAOA approximation ratios on 3-uniform hypergraphs while using significantly fewer function evaluations.
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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.
-
VeloxQ: A Fast and Efficient QUBO Solver
VeloxQ is a classical QUBO solver that reports competitive or superior performance and unique scalability to 10^8-variable sparse instances across benchmarks against quantum annealers, physics-inspired methods, and conventional solvers.
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Quantum Annealing: Optimisation, Sampling, and Many-Body Dynamics
Quantum annealing is described as a heuristic for discrete optimization and sampling that also serves as a platform for studying non-equilibrium many-body quantum dynamics with programmable spin systems.