`pygsti.evotypes.statevec_slow.opreps`

Operation representation classes for the statevec_slow evolution type.

Module Contents

Classes

`OpRep`	The base class for all operation representation classes
`OpRepDenseUnitary`	The base class for all operation representation classes
`OpRepStandard`	The base class for all operation representation classes
`OpRepComposed`	The base class for all operation representation classes
`OpRepSum`	The base class for all operation representation classes
`OpRepEmbedded`	The base class for all operation representation classes
`OpRepExpErrorgen`	The base class for all operation representation classes
`OpRepRepeated`	The base class for all operation representation classes
`OpRepLindbladErrorgen`	The base class for all operation representation classes
`OpRepRandomUnitary`	The base class for all operation representation classes
`OpRepStochastic`	The base class for all operation representation classes

class pygsti.evotypes.statevec_slow.opreps.OpRep(state_space)

Bases: pygsti.evotypes.basereps.OpRep

The base class for all operation representation classes

property dim

state_space

abstract acton(state)

abstract adjoint_acton(state)

acton_random(state, rand_state)

adjoint_acton_random(state, rand_state)

aslinearoperator()

copy()

class pygsti.evotypes.statevec_slow.opreps.OpRepDenseUnitary(mx, basis, state_space)

Bases: OpRep

The base class for all operation representation classes

basis

base

base_has_changed()

to_dense(on_space)

acton(state)

adjoint_acton(state)

class pygsti.evotypes.statevec_slow.opreps.OpRepStandard(name, basis, state_space)

Bases: OpRepDenseUnitary

The base class for all operation representation classes

name

class pygsti.evotypes.statevec_slow.opreps.OpRepComposed(factor_op_reps, state_space)

Bases: OpRep

The base class for all operation representation classes

factor_reps

acton(state): Act this gate map on an input state

adjoint_acton(state): Act the adjoint of this operation matrix on an input state

acton_random(state, rand_state): Act this gate map on an input state

adjoint_acton_random(state, rand_state): Act the adjoint of this operation matrix on an input state

reinit_factor_op_reps(new_factor_op_reps)

class pygsti.evotypes.statevec_slow.opreps.OpRepSum(factor_reps, state_space)

Bases: OpRep

The base class for all operation representation classes

factor_reps

acton(state): Act this gate map on an input state

adjoint_acton(state): Act the adjoint of this operation matrix on an input state

acton_random(state, rand_state): Act this gate map on an input state

adjoint_acton_random(state, rand_state): Act the adjoint of this operation matrix on an input state

class pygsti.evotypes.statevec_slow.opreps.OpRepEmbedded(state_space, target_labels, embedded_rep)

Bases: OpRep

The base class for all operation representation classes

target_labels

embedded_rep

num_basis_els

action_inds

blocksizes

basisInds_noop_blankaction

multipliers

basisInds_action

embeddedDim

ncomponents

active_block_index

nblocks

offset

acton(state)

adjoint_acton(state): Act the adjoint of this gate map on an input state

acton_random(state, rand_state)

adjoint_acton_random(state, rand_state): Act the adjoint of this gate map on an input state

class pygsti.evotypes.statevec_slow.opreps.OpRepExpErrorgen(errorgen_rep)

Bases: OpRep

The base class for all operation representation classes

errorgen_rep

errgenrep_has_changed(onenorm_upperbound)

acton(state)

adjoint_acton(state)

class pygsti.evotypes.statevec_slow.opreps.OpRepRepeated(rep_to_repeat, num_repetitions, state_space)

Bases: OpRep

The base class for all operation representation classes

repeated_rep

num_repetitions

acton(state): Act this gate map on an input state

adjoint_acton(state): Act the adjoint of this operation matrix on an input state

acton_random(state, rand_state): Act this gate map on an input state

adjoint_acton_random(state, rand_state): Act the adjoint of this operation matrix on an input state

class pygsti.evotypes.statevec_slow.opreps.OpRepLindbladErrorgen(lindblad_coefficient_blocks, state_space)

Bases: OpRep

The base class for all operation representation classes

Lterms = 'None'

Lterm_coeffs = 'None'

lindblad_coefficient_blocks

class pygsti.evotypes.statevec_slow.opreps.OpRepRandomUnitary(basis, unitary_rates, unitary_reps, seed_or_state, state_space)

Bases: OpRep

The base class for all operation representation classes

basis

unitary_reps

unitary_rates

state_space

acton_random(state, rand_state)

adjoint_acton_random(state, rand_state)

copy()

update_unitary_rates(rates)

to_dense(on_space)

class pygsti.evotypes.statevec_slow.opreps.OpRepStochastic(stochastic_basis, basis, initial_rates, seed_or_state, state_space)

Bases: OpRepRandomUnitary

The base class for all operation representation classes

rates

stochastic_basis

update_rates(rates)

pygsti.evotypes.statevec_slow.opreps

Module Contents

Classes

`pygsti.evotypes.statevec_slow.opreps`