Index

_

__call__() (qmlhc.loss.task.TaskLoss method) __init__() (qmlhc.core.backend.QuantumBackend method) (qmlhc.core.model.HCModel method) (qmlhc.core.registry.BackendRegistry method) (qmlhc.hc.graph.HCGraph method) (qmlhc.hc.node.HCNode method)

A

AnticipatorConfig (class in qmlhc.predictors.anticipator)

append() (qmlhc.callbacks.base.CallbackList method)

B

backend_exists() (in module qmlhc.core.registry) BackendConfig (class in qmlhc.core.backend)

BackendRegistry (class in qmlhc.core.registry) branches (qmlhc.hc.node.NodeConfig attribute) (qmlhc.predictors.anticipator.AnticipatorConfig attribute)

C

Callback (class in qmlhc.callbacks.base) CallbackList (class in qmlhc.callbacks.base) capabilities (qmlhc.core.registry.Entry attribute) capabilities() (qmlhc.backends.cpp_backend.CppBackend method) (qmlhc.backends.pennylane_backend.PennyLaneBackend method) (qmlhc.backends.qiskit_backend.QiskitBackend method) (qmlhc.core.backend.QuantumBackend method) cg_solve() (in module qmlhc.optim.numpy_optim.utils) chain() (qmlhc.hc.graph.HCGraph class method)

CoherenceLoss (class in qmlhc.loss.coherence) ConsistencyLoss (class in qmlhc.loss.consistency) constructor (qmlhc.core.registry.Entry attribute) ContrafactualAnticipator (class in qmlhc.predictors.anticipator) cov_empirical() (in module qmlhc.optim.numpy_optim.utils) CppBackend (class in qmlhc.backends.cpp_backend) create() (qmlhc.core.registry.BackendRegistry method) create_backend() (in module qmlhc.core.registry) create_optimizer_numpy() (in module qmlhc.optim.registry_numpy) CrossEntropyLoss (class in qmlhc.loss.task)

D

default_branches (qmlhc.core.model.ModelConfig attribute) deflatten_params() (in module qmlhc.optim.numpy_optim.utils)

delta_lag() (in module qmlhc.metrics.forecasting) DepthScheduler (class in qmlhc.callbacks.depth_control) dst (qmlhc.hc.graph.Edge attribute)

E

early_roc_auc() (in module qmlhc.metrics.anomalies) Edge (class in qmlhc.hc.graph) encode() (qmlhc.backends.cpp_backend.CppBackend method) (qmlhc.core.backend.QuantumBackend method)

Entry (class in qmlhc.core.registry) exists() (qmlhc.core.registry.BackendRegistry method)

F

flatten_params() (in module qmlhc.optim.numpy_optim.utils) forward() (qmlhc.core.model.HCModel method) (qmlhc.hc.node.HCNode method)

forward_chain() (qmlhc.core.model.HCModel method)

G

generate() (qmlhc.predictors.anticipator.ContrafactualAnticipator method)

get() (qmlhc.core.registry.BackendRegistry method)

H

HCAdam (class in qmlhc.optim.numpy_optim.adam) HCDualAscent (class in qmlhc.optim.numpy_optim.dual_ascent) HCFiniteDiffOptimizer (class in qmlhc.optim.numpy_optim.finite_diff) HCGraph (class in qmlhc.hc.graph) HCKFACLike (class in qmlhc.optim.numpy_optim.kfac)

HCModel (class in qmlhc.core.model) HCMPCShortHorizon (class in qmlhc.optim.numpy_optim.mpc) HCNaturalGrad (class in qmlhc.optim.numpy_optim.natural_grad) HCNode (class in qmlhc.hc.node) HCSPSAOptimizer (class in qmlhc.optim.numpy_optim.spsa) HCTrustRegion (class in qmlhc.optim.numpy_optim.trust_region)

I

initialize() (qmlhc.optim.api.OptimizerAPI method) (qmlhc.optim.numpy_optim.adam.HCAdam method) (qmlhc.optim.numpy_optim.dual_ascent.HCDualAscent method) (qmlhc.optim.numpy_optim.finite_diff.HCFiniteDiffOptimizer method) (qmlhc.optim.numpy_optim.kfac.HCKFACLike method) (qmlhc.optim.numpy_optim.mpc.HCMPCShortHorizon method) (qmlhc.optim.numpy_optim.natural_grad.HCNaturalGrad method) (qmlhc.optim.numpy_optim.spsa.HCSPSAOptimizer method) (qmlhc.optim.numpy_optim.trust_region.HCTrustRegion method)

K

kl_proxy() (in module qmlhc.optim.numpy_optim.utils)

L

LinearProjector (class in qmlhc.predictors.projector)

list() (qmlhc.core.registry.BackendRegistry method) list_backends() (in module qmlhc.core.registry)

M

MAELoss (class in qmlhc.loss.task) make_gradient_descent() (in module qmlhc.optim.api) mape() (in module qmlhc.metrics.forecasting) mase() (in module qmlhc.metrics.forecasting) MeanPolicy (class in qmlhc.hc.policy) MedianPolicy (class in qmlhc.hc.policy) MemoryLogger (class in qmlhc.callbacks.telemetry) MinRiskPolicy (class in qmlhc.hc.policy) ModelConfig (class in qmlhc.core.model) module qmlhc.backends.cpp_backend qmlhc.backends.pennylane_backend qmlhc.backends.qiskit_backend qmlhc.callbacks.base qmlhc.callbacks.depth_control qmlhc.callbacks.telemetry qmlhc.core.backend qmlhc.core.model qmlhc.core.registry qmlhc.hc.graph qmlhc.hc.node qmlhc.hc.policy qmlhc.loss.coherence qmlhc.loss.consistency qmlhc.loss.task qmlhc.metrics.anomalies qmlhc.metrics.control qmlhc.metrics.forecasting qmlhc.optim.api qmlhc.optim.numpy_optim.adam qmlhc.optim.numpy_optim.dual_ascent qmlhc.optim.numpy_optim.finite_diff qmlhc.optim.numpy_optim.kfac qmlhc.optim.numpy_optim.mpc qmlhc.optim.numpy_optim.natural_grad qmlhc.optim.numpy_optim.spsa qmlhc.optim.numpy_optim.trust_region qmlhc.optim.numpy_optim.utils qmlhc.optim.registry_numpy qmlhc.predictors.anticipator qmlhc.predictors.projector

MSELoss (class in qmlhc.loss.task)

N

name (qmlhc.core.registry.Entry attribute)

NodeConfig (class in qmlhc.hc.node)

O

on_epoch_begin() (qmlhc.callbacks.base.Callback method) (qmlhc.callbacks.base.CallbackList method) (qmlhc.callbacks.depth_control.DepthScheduler method) (qmlhc.callbacks.telemetry.MemoryLogger method) (qmlhc.callbacks.telemetry.TelemetryLogger method) on_epoch_end() (qmlhc.callbacks.base.Callback method) (qmlhc.callbacks.base.CallbackList method) (qmlhc.callbacks.depth_control.DepthScheduler method) (qmlhc.callbacks.telemetry.MemoryLogger method) (qmlhc.callbacks.telemetry.TelemetryLogger method) on_error() (qmlhc.callbacks.base.Callback method) (qmlhc.callbacks.base.CallbackList method) (qmlhc.callbacks.depth_control.DepthScheduler method) (qmlhc.callbacks.telemetry.MemoryLogger method) (qmlhc.callbacks.telemetry.TelemetryLogger method)

on_step_begin() (qmlhc.callbacks.base.Callback method) (qmlhc.callbacks.base.CallbackList method) (qmlhc.callbacks.depth_control.DepthScheduler method) (qmlhc.callbacks.telemetry.MemoryLogger method) (qmlhc.callbacks.telemetry.TelemetryLogger method) on_step_end() (qmlhc.callbacks.base.Callback method) (qmlhc.callbacks.base.CallbackList method) (qmlhc.callbacks.depth_control.DepthScheduler method) (qmlhc.callbacks.telemetry.MemoryLogger method) (qmlhc.callbacks.telemetry.TelemetryLogger method) OptimizerAPI (class in qmlhc.optim.api) output_dim (qmlhc.core.backend.BackendConfig attribute) overshoot() (in module qmlhc.metrics.control)

P

PennyLaneBackend (class in qmlhc.backends.pennylane_backend) predict_sequence() (qmlhc.core.model.HCModel method) project() (qmlhc.predictors.projector.LinearProjector method) (qmlhc.predictors.projector.Projector method)

project_future() (qmlhc.backends.cpp_backend.CppBackend method) (qmlhc.backends.pennylane_backend.PennyLaneBackend method) (qmlhc.backends.qiskit_backend.QiskitBackend method) (qmlhc.core.backend.QuantumBackend method) Projector (class in qmlhc.predictors.projector)

Q

QiskitBackend (class in qmlhc.backends.qiskit_backend) qmlhc.backends.cpp_backend module qmlhc.backends.pennylane_backend module qmlhc.backends.qiskit_backend module qmlhc.callbacks.base module qmlhc.callbacks.depth_control module qmlhc.callbacks.telemetry module qmlhc.core.backend module qmlhc.core.model module qmlhc.core.registry module qmlhc.hc.graph module qmlhc.hc.node module qmlhc.hc.policy module qmlhc.loss.coherence module qmlhc.loss.consistency module qmlhc.loss.task module qmlhc.metrics.anomalies module

qmlhc.metrics.control module qmlhc.metrics.forecasting module qmlhc.optim.api module qmlhc.optim.numpy_optim.adam module qmlhc.optim.numpy_optim.dual_ascent module qmlhc.optim.numpy_optim.finite_diff module qmlhc.optim.numpy_optim.kfac module qmlhc.optim.numpy_optim.mpc module qmlhc.optim.numpy_optim.natural_grad module qmlhc.optim.numpy_optim.spsa module qmlhc.optim.numpy_optim.trust_region module qmlhc.optim.numpy_optim.utils module qmlhc.optim.registry_numpy module qmlhc.predictors.anticipator module qmlhc.predictors.projector module QuantumBackend (class in qmlhc.core.backend)

R

recall_at_lag() (in module qmlhc.metrics.anomalies) register() (qmlhc.core.registry.BackendRegistry method) register_backend() (in module qmlhc.core.registry) rmse() (in module qmlhc.metrics.forecasting) robustness() (in module qmlhc.metrics.control)

run() (qmlhc.backends.cpp_backend.CppBackend method) (qmlhc.backends.pennylane_backend.PennyLaneBackend method) (qmlhc.backends.qiskit_backend.QiskitBackend method) (qmlhc.core.backend.QuantumBackend method) run_batch() (qmlhc.backends.pennylane_backend.PennyLaneBackend method)

S

seed (qmlhc.core.backend.BackendConfig attribute) select() (qmlhc.hc.policy.MeanPolicy method) (qmlhc.hc.policy.MedianPolicy method) (qmlhc.hc.policy.MinRiskPolicy method) settling_time() (in module qmlhc.metrics.control) shots (qmlhc.core.backend.BackendConfig attribute) src (qmlhc.hc.graph.Edge attribute) step() (qmlhc.hc.graph.HCGraph method) (qmlhc.optim.api.OptimizerAPI method)

step_params() (qmlhc.optim.numpy_optim.adam.HCAdam method) (qmlhc.optim.numpy_optim.dual_ascent.HCDualAscent method) (qmlhc.optim.numpy_optim.finite_diff.HCFiniteDiffOptimizer method) (qmlhc.optim.numpy_optim.kfac.HCKFACLike method) (qmlhc.optim.numpy_optim.mpc.HCMPCShortHorizon method) (qmlhc.optim.numpy_optim.natural_grad.HCNaturalGrad method) (qmlhc.optim.numpy_optim.spsa.HCSPSAOptimizer method) (qmlhc.optim.numpy_optim.trust_region.HCTrustRegion method) symmetric (qmlhc.predictors.anticipator.AnticipatorConfig attribute)

T

TaskLoss (class in qmlhc.loss.task)

TelemetryLogger (class in qmlhc.callbacks.telemetry) total_loss_for() (in module qmlhc.optim.numpy_optim.utils)