EQE-QAOA reduces qubit count for QAOA while exactly preserving optimization performance by confining dynamics to an invariant subspace and applying an isometric re-encoding.
Simulating quantum computa- tions on classical machines: A survey
3 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 3verdicts
UNVERDICTED 3representative citing papers
Orkan simulates quantum operations on Hermitian operators using a cache-friendly tiled lower-triangle layout, halving memory and achieving 2-4x speedups over Qiskit Aer, QuEST, and Qulacs.
A federated QLSTM model achieves near-classical accuracy on SUSY classification with under 300 parameters and 20K data points, claiming 100x efficiency gains over baselines.
citing papers explorer
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EQE-QAOA: An Equivalence-Preserving Qubit Efficient Framework for Combinatorial Optimization
EQE-QAOA reduces qubit count for QAOA while exactly preserving optimization performance by confining dynamics to an invariant subspace and applying an isometric re-encoding.
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Orkan: Cache-friendly simulation of quantum operations on hermitian operators
Orkan simulates quantum operations on Hermitian operators using a cache-friendly tiled lower-triangle layout, halving memory and achieving 2-4x speedups over Qiskit Aer, QuEST, and Qulacs.
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Federated Learning with Quantum Enhanced LSTM for Applications in High Energy Physics
A federated QLSTM model achieves near-classical accuracy on SUSY classification with under 300 parameters and 20K data points, claiming 100x efficiency gains over baselines.