pauxy.walkers package

Submodules

pauxy.walkers.handler module

class pauxy.walkers.handler.Walkers(walker_opts, system, trial, qmc, verbose=False, comm=None, nprop_tot=None, nbp=None)

Bases: object

Container for groups of walkers which make up a wavefunction.

Parameters:

• system (object) – System object.
• trial (object) – Trial wavefunction object.
• nwalkers (int) – Number of walkers to initialise.
• nprop_tot (int) – Total number of propagators to store for back propagation + itcf.
• nbp (int) – Number of back propagation steps.

add_field_config(nprop_tot, nbp, system, dtype)

Add FieldConfig object to walker object.

Parameters:

• nprop_tot (int) – Total number of propagators to store for back propagation + itcf.
• nbp (int) – Number of back propagation steps.
• nfields (int) – Number of fields to store for each back propagation step.
• dtype (type) – Field configuration type.

comb(comm, weights)

Apply the comb method of population control / branching.

See Booth & Gubernatis PRE 80, 046704 (2009).

Parameters:comm (MPI communicator) –

copy_bp_wfn(phi_bp)

Copy back propagated wavefunction.

Parameters:phi_bp (object) – list of walker objects containing back propagated walkers.

copy_historic_wfn()

Copy current wavefunction to psi_n for next back propagation step.

copy_init_wfn()

Copy current wavefunction to initial wavefunction.

The definition of the initial wavefunction depends on whether we are calculating an ITCF or not.

get_write_buffer(i)

orthogonalise(trial, free_projection)

Orthogonalise all walkers.

Parameters:

• trial (object) – Trial wavefunction object.
• free_projection (bool) – True if doing free projection.

pair_branch(comm)

pop_control(comm)

read_walkers(comm)

recompute_greens_function(trial, time_slice=None)

reset(trial)

set_total_weight(total_weight)

set_walker_from_buffer(i, buff)

write_walkers(comm)

pauxy.walkers.multi_ghf module

class pauxy.walkers.multi_ghf.MultiGHFWalker(walker_opts, system, trial, index=0, weights='zeros', wfn0='init')

Bases: object

Multi-GHF style walker.

Parameters:

• weight (int) – Walker weight.
• system (object) – System object.
• trial (object) – Trial wavefunction object.
• index (int) – Element of trial wavefunction to initalise walker to.
• weights (string) – Initialise weights to zeros or ones.
• wfn0 (string) – Initial wavefunction.

calc_otrial(trial)

Caculate overlap with trial wavefunction.

Parameters:trial (object) – Trial wavefunction object. Returns:ot – Overlap. Return type:float / complex

greens_function(trial)

Compute walker’s green’s function.

Parameters:trial (object) – Trial wavefunction object.

inverse_overlap(trial)

Compute inverse overlap matrix from scratch.

Parameters:trial (numpy.ndarray) – Trial wavefunction.

local_energy(system, two_rdm=None)

Compute walkers local energy

Parameters:system (object) – System object. Returns:(E, T, V) – Mixed estimates for walker’s energy components. Return type:tuple

reortho(trial)

Update overlap.

Parameters:

• probs (numpy.ndarray) – Probabilities for chosing particular field configuration.
• xi (int) – Chosen field configuration.
• coeffs (numpy.ndarray) – Trial wavefunction coefficients. For interface consistency.

update_inverse_overlap(trial, vtup, vtdown, i)

Update inverse overlap matrix given a single row update of walker.

Parameters:

• trial (object) – Trial wavefunction object.
• vtup (numpy.ndarray) – Update vector for spin up sector.
• vtdown (numpy.ndarray) – Update vector for spin down sector.
• i (int) – Basis index.

update_overlap(probs, xi, coeffs)

Update overlap.

Parameters:

• probs (numpy.ndarray) – Probabilities for chosing particular field configuration.
• xi (int) – Chosen field configuration.
• coeffs (numpy.ndarray) – Trial wavefunction coefficients. For interface consistency.

pauxy.walkers.single_det module

class pauxy.walkers.single_det.SingleDetWalker(walker_opts, system, trial, index=0, nprop_tot=None, nbp=None)

Bases: object

UHF style walker.

Parameters:

• weight (int) – Walker weight.
• system (object) – System object.
• trial (object) – Trial wavefunction object.
• index (int) – Element of trial wavefunction to initalise walker to.

calc_otrial(trial)

Caculate overlap with trial wavefunction.

Parameters:trial (object) – Trial wavefunction object. Returns:ot – Overlap. Return type:float / complex

get_buffer()

Get walker buffer for MPI communication

Returns:buff – Relevant walker information for population control. Return type:dict

greens_function(trial)

Compute walker’s green’s function.

Also updates walker’s inverse overlap.

Parameters:trial (object) – Trial wavefunction object.

inverse_overlap(trial)

Compute inverse overlap matrix from scratch.

Parameters:trial (numpy.ndarray) – Trial wavefunction.

local_energy(system, two_rdm=None)

Compute walkers local energy

Parameters:system (object) – System object. Returns:(E, T, V) – Mixed estimates for walker’s energy components. Return type:tuple

reortho(trial)

reorthogonalise walker.

Parameters:trial (object) – trial wavefunction object. for interface consistency.

reortho_excite(trial)

reorthogonalise walker.

Parameters:trial (object) – trial wavefunction object. for interface consistency.

rotated_greens_function()

Compute “rotated” walker’s green’s function.

Green’s function without trial wavefunction multiplication.

Parameters:trial (object) – Trial wavefunction object.

set_buffer(buff)

Set walker buffer following MPI communication

Parameters:buff (dict) – Relevant walker information for population control.

update_inverse_overlap(trial, vtup, vtdown, i)

Update inverse overlap matrix given a single row update of walker.

Parameters:

• trial (object) – Trial wavefunction object.
• vtup (numpy.ndarray) – Update vector for spin up sector.
• vtdown (numpy.ndarray) – Update vector for spin down sector.
• i (int) – Basis index.

update_overlap(probs, xi, coeffs)

Update overlap.

Parameters:

• probs (numpy.ndarray) – Probabilities for chosing particular field configuration.
• xi (int) – Chosen field configuration.
• coeffs (numpy.ndarray) – Trial wavefunction coefficients. For interface consistency.

Module contents