AI coding agents evolve simple ground-state protocols into improved versions for VQE, DMRG, and AFQMC on spin models and molecules by using executable energy scores under fixed compute budgets.
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Numerical evidence that post-quench density profiles in the Lieb-Liniger gas acquire a scaling form in velocity that reflects the Bethe rapidity structure.
svPITE is a Python package for ground-state preparation via probabilistic imaginary-time evolution, supporting state-vector and shot-based modes with exact-diagonalization benchmarking and interoperability for dynamical observables.
citing papers explorer
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Optimizing ground state preparation protocols with autoresearch
AI coding agents evolve simple ground-state protocols into improved versions for VQE, DMRG, and AFQMC on spin models and molecules by using executable energy scores under fixed compute budgets.
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Dynamical Fermionization and Emergent Bethe Rapidity Structure in the Spatial Density of Cold quenched Lieb-Liniger gas
Numerical evidence that post-quench density profiles in the Lieb-Liniger gas acquire a scaling form in velocity that reflects the Bethe rapidity structure.
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svPITE: A Python package for the state-vector-based probabilistic imaginary-time evolution algorithm
svPITE is a Python package for ground-state preparation via probabilistic imaginary-time evolution, supporting state-vector and shot-based modes with exact-diagonalization benchmarking and interoperability for dynamical observables.