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quant-ph2025★ 1 cited
Neural Network Assisted Fermionic Compression Encoding: A Lossy-QSCI Framework for Resource-Efficient Ground-State Simulations
Yu-cheng Chen, Ronin Wu, M. H. Cheng +1
Quantum computing promises to revolutionize many-body simulations for quantum chemistry, but its potential is constrained by limited qubits and noise in current devices. In this wo…
quant-ph2023★ 2 cited
Optimal Particle-Conserved Linear Encoding for Practical Fermionic Simulation
M. H. Cheng, Yu-Cheng Chen, Qian Wang +4
Number-conserved subspace encoding reduces resources needed for quantum simulations, but scalable complexity trade-off bounds for modes and particles with $\mathcal{O}(N\lo…