QFlow-SD matches canonical UCCSD energies for tested molecules while using substantially fewer qubits via reduced active spaces and constant-depth circuits, with a composite classical-quantum downfolding strategy demonstrated for water.
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Empirical scaling study reports VQS requires shallower circuits than Trotterization for time evolution as system size and simulation time grow.
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.
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Quantum Flow algorithm: quantum simulations of chemical systems using reduced quantum resources and constant depth quantum circuits
QFlow-SD matches canonical UCCSD energies for tested molecules while using substantially fewer qubits via reduced active spaces and constant-depth circuits, with a composite classical-quantum downfolding strategy demonstrated for water.
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Performance and scaling analysis of variational quantum simulation
Empirical scaling study reports VQS requires shallower circuits than Trotterization for time evolution as system size and simulation time grow.
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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.