pytc.vmc.sampling.burn_in_with_importance

pytc.vmc.sampling.burn_in_with_importance(ansatz, walkers, n_steps, time_step, key, params, report_interval=100, mesh=None)[source]

Perform burn-in steps for MCMC sampling with importance sampling.

Parameters:

  • ansatz – Wavefunction object

  • walkers – Initial walker configurations

  • n_steps – Number of burn-in steps

  • time_step – Time step for the drift-diffusion process

  • key – PRNG key

  • params – Parameters for the ansatz, including jastrow and linear coefficients

  • report_interval – How often to print progress

Returns:

Tuple of (equilibrated_walkers, acceptance_history, new_key)