pygsti.forwardsims.termforwardsim
¶
Defines the TermForwardSimulator calculator class
Module Contents¶
Classes¶
A forwardsimulation calculator that uses termpathintegration to compute probabilities. 

A set of errorterm paths. 

A path set, as specified for each atom of a 

A path set for a split 
 class pygsti.forwardsims.termforwardsim.TermForwardSimulator(model=None, mode='pruned', max_order=3, desired_perr=0.01, allowed_perr=0.1, min_term_mag=None, max_paths_per_outcome=1000, perr_heuristic='none', max_term_stages=5, path_fraction_threshold=0.9, oob_check_interval=10, cache=None, num_atoms=None, processor_grid=None, param_blk_sizes=None)¶
Bases:
pygsti.forwardsims.distforwardsim.DistributableForwardSimulator
A forwardsimulation calculator that uses termpathintegration to compute probabilities.
 Parameters
model (Model, optional) – The parent model of this simulator. It’s fine if this is None at first, but it will need to be set (by assigning self.model before using this simulator.
mode ({"taylororder", "pruned", "direct"}) – Overall method used to compute (approximate) circuit probabilities. The “taylororder” mode includes all taylorexpansion terms up to a fixed and predefined order, fixing a single “path set” at the outset. The “pruned” mode selects a path set based on a heuristic (sometimes a true upper bound) calculation of the error in the approximate probabilities. This method effectively “prunes” the paths to meet a fixed desired accuracy. The “direct” method is still under development. Its intention is to perform path integrals directly without the use of polynomial computation and caching. Initial testing showed the direct method to be much slower for common QCVV tasks, making it less urgent to complete.
max_order (int) – The maximum order of errorrate terms to include in probability computations. When polynomials are computed, the maximum Taylor order to compute polynomials to.
desired_perr (float, optional) – The desired maximumerror when computing probabilities.. Path sets are selected (heuristically) to target this error, within the bounds set by max_order, etc.
allowed_perr (float, optional) – The allowed maximumerror when computing probabilities. When rigorous bounds cannot guarantee that probabilities are correct to within this error, additional paths are added to the path set.
min_term_mag (float, optional) – Terms with magnitudes less than this value will be ignored, i.e. not considered candidates for inclusion in paths. If this number is too low, the number of possible paths to consder may be very large, impacting performance. If too high, then not enough paths will be considered to achieve an accurate result. By default this value is set automatically based on the desired error and max_paths_per_outcome. Only adjust this if you know what you’re doing.
max_paths_per_outcome (int, optional) – The maximum number of paths that can be used (summed) to compute a single outcome probability.
perr_heuristic ({"none", "scaled", "meanscaled"}) – Which heuristic (if any) to use when deciding whether a given path set is sufficient given the allowed error (allowed_perr).  “none”: This is the strictest setting, and is absence of any heuristic. if the pathmagnitude gap (the maximum  achieved sumofpathmagnitudes, a rigorous upper bound on the approximation error for a circuit outcome probability) is greater than allowed_perr for any circuit, the path set is deemed insufficient.  “scaled”: a path set is deemed insufficient when, for any circuit, the pathmagnitude gap multiplied by a scaling factor is greater than allowed_perr. This scaling factor is equal to the computed probability divided by the achieved sumofpathmagnitudes and is always less than 1. This scaling is essentially the ratio of the sum of the path amplitudes without and with an absolute value, and tries to quantify and offset the degree of pessimism in the computed pathmagnitude gap.  “meanscaled” : a path set is deemed insufficient when, the mean of all the scaled (as above) pathmagnitude gaps is greater than allowed_perr. The mean here is thus over the circuit outcomes. This heuristic is even more permissive of potentially bad path sets than “scaled”, as it allows badly approximated circuits to be offset by well approximated ones.
max_term_stages (int, optional) – The maximum number of “stage”, i.e. recomputations of a path set, are allowed before giving up.
path_fraction_threshold (float, optional) – When greater than this fraction of the total available paths (set by other constraints) are considered, no further recompuation of the path set will occur, as it is expected to give little improvement.
oob_check_interval (int, optional) – The optimizer will check whether the computed probabilities have sufficiently small error every oob_check_interval (outer) optimizer iteration.
cache (dict, optional) – A dictionary of precomputed compact polynomial objects. Keys are (max_order, rholabel, elabel, circuit) tuples, where max_order is an integer, rholabel and elabel are
Label
objects, and circuit is aCircuit
. Computed values are added to any dictionary that is supplied, so supplying an empty dictionary and using this calculator will cause the dictionary to be filled with values.num_atoms (int, optional) – The number of atoms (subtables) to use when creating the layout (i.e. when calling :method:`create_layout`). This determines how many units the element (circuit outcome probability) dimension is divided into, and doesn’t have to correclate with the number of processors. When multiple processors are used, if num_atoms is less than the number of processors then num_atoms should divide the number of processors evenly, so that num_atoms // num_procs groups of processors can be used to divide the computation over parameter dimensions.
processor_grid (tuple optional) – Specifies how the total number of processors should be divided into a number of atomprocessors, 1stparameterderivprocessors, and 2ndparameterderivprocessors. Each level of specification is optional, so this can be a 1, 2, or 3 tuple of integers (or None). Multiplying the elements of processor_grid together should give at most the total number of processors.
param_blk_sizes (tuple, optional) – The parameter block sizes along the first or first & second parameter dimensions  so this can be a 0, 1 or 2tuple of integers or None values. A block size of None means that there should be no division into blocks, and that each block processor computes all of its parameter indices at once.
 classmethod _array_types_for_method(cls, method_name)¶
 _to_nice_serialization(self)¶
 classmethod _from_nice_serialization(cls, state)¶
 _set_evotype(self, evotype)¶
Called when the evotype being used (defined by the parent model) changes. evotype will be None when the current model is None
 __getstate__(self)¶
 copy(self)¶
Return a shallow copy of this TermForwardSimulator.
 Returns
TermForwardSimulator
 create_layout(self, circuits, dataset=None, resource_alloc=None, array_types=('E',), derivative_dimension=None, verbosity=0)¶
Constructs an circuitoutcomeprobabilityarray (COPA) layout for a list of circuits.
 Parameters
circuits (list) – The circuits whose outcome probabilities should be included in the layout.
dataset (DataSet) – The source of data counts that will be compared to the circuit outcome probabilities. The computed outcome probabilities are limited to those with counts present in dataset.
resource_alloc (ResourceAllocation) – A available resources and allocation information. These factors influence how the layout (evaluation strategy) is constructed.
array_types (tuple, optional) – A tuple of stringvalued array types. See :method:`ForwardSimulator.create_layout`.
derivative_dimension (int, optional) – Optionally, the parameterspace dimension used when taking first and second derivatives with respect to the cirucit outcome probabilities. This must be nonNone when array_types contains ‘ep’ or ‘epp’ types.
verbosity (int or VerbosityPrinter) – Determines how much output to send to stdout. 0 means no output, higher integers mean more output.
 Returns
TermCOPALayout
 _bulk_fill_probs_atom(self, array_to_fill, layout_atom, resource_alloc)¶
 _bulk_fill_dprobs_atom(self, array_to_fill, dest_param_slice, layout_atom, param_slice, resource_alloc)¶
 _bulk_fill_hprobs_atom(self, array_to_fill, dest_param_slice1, dest_param_slice2, layout_atom, param_slice1, param_slice2, resource_alloc)¶
 _compute_pruned_pathmag_threshold(self, rholabel, elabels, circuit, polynomial_vindices_per_int, repcache, circuitsetup_cache, resource_alloc, threshold_guess=None)¶
Finds a good pathmagnitude threshold for circuit at the current parameterspace point.
 Parameters
rholabel (Label) – The state preparation label.
elabels (list) – A list of
Label
objects giving the simplified effect labels.circuit (Circuit or tuple) – A tuplelike object of simplified gates (e.g. may include instrument elements like ‘Imyinst_0’)
polynomial_vindices_per_int (int) – The number of variable indices that can fit into a single platformwidth integer (can be computed from number of model params, but passed in for performance).
repcache (dict, optional) – Dictionaries used to cache operator representations to speed up future calls to this function that would use the same set of operations.
circuitsetup_cache (dict) – A cache holding specialized elements that store and eliminate the need to recompute percircuit information.
resource_alloc (ResourceAllocation) – Available resources for this computation. Includes the number of processors (MPI comm) and memory limit.
threshold_guess (float, optional) – A guess estimate of a good pathmagnitude threshold.
 Returns
npaths (int) – The number of paths found. (total over all circuit outcomes)
threshold (float) – The final pathmagnitude threshold used.
target_sopm (float) – The target (desired) sumofpathmagnitudes. (summed over all circuit outcomes)
achieved_sopm (float) – The achieved sumofpathmagnitudes. (summed over all circuit outcomes)
 _find_minimal_paths_set_atom(self, layout_atom, resource_alloc, exit_after_this_many_failures=0)¶
Find the minimal (smallest) path set that achieves the desired accuracy conditions.
 Parameters
layout_atom (_TermCOPALayoutAtom) – The probability array layout containing the circuits to find a pathset for.
resource_alloc (ResourceAllocation) – Available resources for this computation. Includes the number of processors (MPI comm) and memory limit.
exit_after_this_many_failures (int, optional) – If > 0, give up after this many circuits fail to meet the desired accuracy criteria. This shortcircuits doomed attempts to find a good path set so they don’t take too long.
 Returns
TermPathSetAtom
 find_minimal_paths_set(self, layout, exit_after_this_many_failures=0)¶
Find a good, i.e. minimal, path set for the current modelparameter space point.
 Parameters
layout (TermCOPALayout) – The layout specifiying the quantities (circuit outcome probabilities) to be computed, and related information.
exit_after_this_many_failures (int, optional) – If > 0, give up after this many circuits fail to meet the desired accuracy criteria. This shortcircuits doomed attempts to find a good path set so they don’t take too long.
 Returns
TermPathSet
 _circuit_achieved_and_max_sopm(self, rholabel, elabels, circuit, repcache, threshold)¶
Computes the achieved and maximum sumofpathmagnitudes for circuit.
 Parameters
rholabel (Label) – The state preparation label.
elabels (list) – A list of
Label
objects giving the simplified effect labels.circuit (Circuit or tuple) – A tuplelike object of simplified gates.
repcache (dict, optional) – Dictionaries used to cache operator representations to speed up future calls to this function that would use the same set of operations.
threshold (float) – pathmagnitude threshold. Only sum path magnitudes above or equal to this threshold.
 Returns
achieved_sopm (float) – The achieved sumofpathmagnitudes. (summed over all circuit outcomes)
max_sopm (float) – The maximum possible sumofpathmagnitudes. (summed over all circuit outcomes)
 _achieved_and_max_sopm_atom(self, layout_atom)¶
Compute the achieved and maximum possible sumofpathmagnitudes for a single layout atom.
This gives a sense of how accurately the current path set is able to compute probabilities.
 Parameters
layout_atom (_TermCOPALayoutAtom) – The probability array layout specifying the circuits and outcomes.
 Returns
numpy.ndarray
 _bulk_fill_achieved_and_max_sopm(self, achieved_sopm, max_sopm, layout)¶
Compute element arrays of achieved and maximumpossible sumofpathmagnitudes.
These values are computed for the current set of paths contained in eval_tree.
 Parameters
achieved_sopm (numpy.ndarray) – An array containing the percircuitoutcome achieved sumofpathmagnitudes.
max_sopm (numpy.ndarray) – An array containing the percircuitoutcome maximum sumofpathmagnitudes.
layout (TermCOPALayout) – The layout specifiying the quantities (circuit outcome probabilities) to be computed, and related information.
 Returns
None
 bulk_test_if_paths_are_sufficient(self, layout, probs, verbosity=0)¶
Determine whether layout’s current path set (perhaps heuristically) achieves the desired accuracy.
The current path set is determined by the current (percircuti) pathmagnitude thresholds (stored in the evaluation tree) and the current parameterspace point (also reflected in the terms cached in the evaluation tree).
 Parameters
layout (TermCOPALayout) – The layout specifiying the quantities (circuit outcome probabilities) to be computed, and related information.
probs (numpy.ndarray) – The element array of (approximate) circuit outcome probabilities. This is needed because some heuristics take into account an probability’s value when computing an acceptable pathmagnitude gap.
verbosity (int or VerbosityPrinter, optional) – An integer verbosity level or printer object for displaying messages.
 Returns
bool
 bulk_sopm_gaps(self, layout)¶
Compute an element array sumofpathmagnitude gaps (the difference between maximum and achieved).
These values are computed for the current set of paths contained in eval_tree.
 Parameters
layout (TermCOPALayout) – The layout specifiying the quantities (circuit outcome probabilities) to be computed, and related information.
 Returns
numpy.ndarray – An array containing the percircuitoutcome sumofpathmagnitude gaps.
 _achieved_and_max_sopm_jacobian_atom(self, layout_atom)¶
Compute the jacobian of the achieved and maximum possible sumofpathmagnitudes for a single layout atom.
 Parameters
layout_atom (_TermCOPALayoutAtom) – The probability array layout specifying the circuits and outcomes.
 Returns
achieved_sopm_jacobian (numpy.ndarray) – The jacobian of the achieved sumofpathmagnitudes.
max_sopm_jacobian (numpy.ndarray) – The jacobian of the maximum possible sumofpathmagnitudes.
 _sopm_gaps_jacobian_atom(self, layout_atom)¶
Compute the jacobian of the (maximumpossible  achieved) sumofpathmagnitudes for a single layout atom.
 Parameters
layout_atom (_TermCOPALayoutAtom) – The probability array layout.
 Returns
numpy.ndarray – The jacobian of the sumofpathmagnitudes gap.
 bulk_sopm_gaps_jacobian(self, layout)¶
Compute the jacobian of the the output of :method:`bulk_sopm_gaps`.
 Parameters
layout (TermCOPALayout) – The layout specifiying the quantities (circuit outcome probabilities) to be computed, and related information.
resource_alloc (ResourceAllocation, optional) – Available resources for this computation. Includes the number of processors (MPI comm) and memory limit.
 Returns
numpy.ndarray – An numberofelements by numberofmodelparameters array containing the jacobian of the sumofpathmagnitude gaps.
 _prs_as_pruned_polynomial_reps(self, threshold, rholabel, elabels, circuit, polynomial_vindices_per_int, repcache, circuitsetup_cache, resource_alloc, mode='normal')¶
Computes polynomialrepresentations of circuitoutcome probabilities.
In particular, the circuitoutcomes under consideration share the same state preparation and differ only in their POVM effects. Employs a truncated or pruned pathintegral approach, as opposed to just including everything up to some Taylor order as in :method:`_prs_as_polynomials`.
 Parameters
threshold (float) – The pathmagnitude threshold. Only include (sum) paths whose magnitudes are greater than or equal to this threshold.
rholabel (Label) – The state preparation label.
elabels (list) – A list of
Label
objects giving the simplified effect labels.circuit (Circuit or tuple) – A tuplelike object of simplified gates (e.g. may include instrument elements like ‘Imyinst_0’)
polynomial_vindices_per_int (int) – The number of variable indices that can fit into a single platformwidth integer (can be computed from number of model params, but passed in for performance).
repcache (dict, optional) – Dictionaries used to cache operator representations to speed up future calls to this function that would use the same set of operations.
circuitsetup_cache (dict) – A cache holding specialized elements that store and eliminate the need to recompute percircuit information.
resource_alloc (ResourceAllocation) – Available resources for this computation. Includes the number of processors (MPI comm) and memory limit.
mode ({"normal", "achieved_sopm"}) – Controls whether polynomials are actually computed (“normal”) or whether only the achieved sumofpathmagnitudes is computed (“achieved_sopm”). The latter mode is useful when a threshold is being tested but not committed to, as computing only the achieved sumofpathmagnitudes is significantly faster.
 Returns
list – A list of
PolynomialRep
objects. These polynomial represetations are essentially barebones polynomials stored efficiently for performance. (To get a fullPolynomial
object, use :classmethod:`Polynomial.from_rep`.)
 _select_paths_set_atom(self, layout_atom, pathset, resource_alloc)¶
Selects (makes “current”) a path set and computes polynomials the new set for a single layout atom.
This routine updates the information held in layout_atom. After this call, layout_atom.pathset == pathset.
 Parameters
layout_atom (_TermCOPALayoutAtom) – The probability array layout whose pathset is being set.
pathset (PathSet) – The path set to select.
resource_alloc (ResourceAllocation) – Available resources for this computation. Includes the number of processors (MPI comm) and memory limit.
 Returns
None
 _prs_as_polynomials(self, rholabel, elabels, circuit, polynomial_vindices_per_int, resource_alloc, fastmode=True)¶
Computes polynomialrepresentations of circuitoutcome probabilities.
In particular, the circuitoutcomes under consideration share the same state preparation and differ only in their POVM effects.
 Parameters
rholabel (Label) – The state preparation label.
elabels (list) – A list of
Label
objects giving the simplified effect labels.circuit (Circuit or tuple) – A tuplelike object of simplified gates (e.g. may include instrument elements like ‘Imyinst_0’)
polynomial_vindices_per_int (int) – The number of variable indices that can fit into a single platformwidth integer (can be computed from number of model params, but passed in for performance).
resource_alloc (ResourceAllocation) – Available resources for this computation. Includes the number of processors (MPI comm) and memory limit.
fastmode (bool, optional) – Whether to use a faster and slightly more memoryhungry implementation for computing the polynomial terms. (Usually best to leave this as True).
 Returns
list – A list of Polynomial objects.
 _prs_as_compact_polynomials(self, rholabel, elabels, circuit, polynomial_vindices_per_int, resource_alloc)¶
Compute compactform polynomials of the outcome probabilities for circuit.
Note that these outcomes are defined as having the same state preparation and different POVM effects.
 Parameters
rholabel (Label) – The state preparation label.
elabels (list) – A list of
Label
objects giving the simplified effect labels.circuit (Circuit or tuple) – A tuplelike object of simplified gates (e.g. may include instrument elements like ‘Imyinst_0’)
polynomial_vindices_per_int (int) – The number of variable indices that can fit into a single platformwidth integer (can be computed from number of model params, but passed in for performance).
resource_alloc (ResourceAllocation) – Available resources for this computation. Includes the number of processors (MPI comm) and memory limit.
 Returns
list – A list of Polynomial objects.
 _cache_p_polynomials(self, layout_atom, resource_alloc, polynomial_vindices_per_int)¶
Compute and cache the compactform polynomials that evaluate the probabilities of a single layout atom.
These polynomials corresponding to all this tree’s operation sequences sandwiched between each state preparation and effect. The result is cached to speed up subsequent calls.
 Parameters
layout_atom (_TermCOPALayoutAtom) – The probability array layout containing the circuits to compute polynomials for.
resource_alloc (ResourceAllocation) – Available resources for this computation. Includes the number of processors (MPI comm) and memory limit.
polynomial_vindices_per_int (int) – The number of variable indices that can fit into a single platformwidth integer (can be computed from number of model params, but passed in for performance).
 Returns
None
 select_paths_set(self, layout, path_set)¶
Selects (makes “current”) a path set and computes polynomials the new set.
 Parameters
layout (TermCOPALayout) – The layout whose pathset should be set.
path_set (PathSet) – The path set to select.
 Returns
None
 _prepare_layout(self, layout, polynomial_vindices_per_int)¶
Performs preparatory work for computing circuit outcome probabilities.
Finds a good path set that meets (if possible) the accuracy requirements and computes needed polynomials.
 Parameters
layout (TermCOPALayout) – The layout to prepare.
polynomial_vindices_per_int (int) – The number of variable indices that can fit into a single platformwidth integer (can be computed from number of model params, but passed in for performance).
 Returns
None
 class pygsti.forwardsims.termforwardsim._TermPathSetBase(npaths, maxpaths, nfailed)¶
Bases:
object
A set of errorterm paths.
Each such path is comprised of a single “term” (usually a Taylor term of an errorgenerator expansion) for each gate operation or circuit layer (more generally, each factor within the product that evaluates to the probability).
A set of paths is specified by giving a pathmagnitude threshold for each circuit in a COPA layout. All paths with magnitude less than this threshold are a part of the path set. The term magnitudes that determine a path magnitude are held in Term objects resulting from a Model at a particular parameterspace point. Representations of these term objects (actually just the “highmagnitude” ones, as determined by a different, termmagnitude, threshold) are also held within the path set.
 Parameters
npaths (int) – The number of total paths.
maxpaths (int) – The maximumallowedpaths limit that was in place when this path set was created.
nfailed (int) – The number of circuits that failed to meet the desired accuracy (pathmagnitude gap) requirements.
 property allowed_path_fraction(self)¶
The fraction of maximal allowed paths that are in this path set.
 Returns
float
 class pygsti.forwardsims.termforwardsim._AtomicTermPathSet(thresholds, highmag_termrep_cache, circuitsetup_cache, npaths, maxpaths, nfailed)¶
Bases:
_TermPathSetBase
A path set, as specified for each atom of a
TermCOPALayout
. Parameters
thresholds (dict) – A dictionary whose keys are circuits and values are pathmagnitude thresholds. These thresholds store what
highmag_termrep_cache (dict) – A dictionary whose keys are gate or circuitlayer labels and whose values are internallyused “repcache” elements that each hold a list of the term representations for that gate having a “high” magnitude (magnitude above some threshold). This cache is an essential link between the pathmagnitude thresholds in thresholds and the actual set of paths that are evaluated by processing layout_atom (e.g. updating this cache by recomputing term magnitudes at a new parameterspace point will also update the set of paths that are evaluated given the same set of thresholds).
circuitsetup_cache (dict) – A dictionary that caches percircuit setup information and can be used to speed up multiple calls which use the same circuits.
npaths (int) – The number of total paths.
maxpaths (int) – The maximumallowedpaths limit that was in place when this path set was created.
nfailed (int) – The number of circuits that failed to meet the desired accuracy (pathmagnitude gap) requirements.
 class pygsti.forwardsims.termforwardsim.TermPathSet(local_atom_pathsets, comm)¶
Bases:
_TermPathSetBase
A path set for a split
TermEvalTree
. Parameters
local_atom_pathsets (list) – A list of path sets for each of the local layout atom (i.e. the atoms assigned to the current processor).
comm (mpi4py.MPI.Comm) – When not None, an MPI communicator for distributing the computation across multiple processors.