c3.libraries.propagation

A library for propagators and closely related functions

Module Contents

c3.libraries.propagation.unitary_deco(func)

Decorator for making registry of functions

c3.libraries.propagation.state_deco(func)

Decorator for making registry of functions

c3.libraries.propagation.solver_deco(func)

Decorator for making registry of solvers

c3.libraries.propagation.step_deco(func)

Decorator for making registry of solvers

c3.libraries.propagation.sum_h0_hks(h0, hks, cf_t)

Compute and Return

H(t) = H_0 + sum_k c_k H_k.

c3.libraries.propagation.pwc(model: c3.model.Model, gen: c3.generator.generator.Generator, instr: c3.signal.gates.Instruction, folding_stack: list, batch_size=None) → Dict

Solve the equation of motion (Lindblad or Schrรถdinger) for a given control signal and Hamiltonians.

Parameters

• signal (dict) – Waveform of the control signal per drive line.

• gate (str) – Identifier for one of the gates.

Returns

Matrix representation of the gate.

Return type

unitary

c3.libraries.propagation.tf_dU_of_t(h0, hks, cflds_t, dt)

Compute H(t) = H_0 + sum_k c_k H_k and matrix exponential exp(-i H(t) dt).

Parameters

• h0 (tf.tensor) – Drift Hamiltonian.

• hks (list of tf.tensor) – List of control Hamiltonians.

• cflds_t (array of tf.float) – Vector of control field values at time t.

• dt (float) – Length of one time slice.

Returns

dU = exp(-i H(t) dt)

Return type

tf.tensor

c3.libraries.propagation.tf_dU_of_t_lind(h0, hks, col_ops, cflds_t, dt)

Compute the Lindbladian and it’s matrix exponential exp(L(t) dt).

Parameters

• h0 (tf.tensor) – Drift Hamiltonian.

• hks (list of tf.tensor) – List of control Hamiltonians.

• col_ops (list of tf.tensor) – List of collapse operators.

• cflds_t (array of tf.float) – Vector of control field values at time t.

• dt (float) – Length of one time slice.

Returns

dU = exp(L(t) dt)

Return type

tf.tensor

c3.libraries.propagation.tf_batch_propagate(hamiltonian, hks, signals, dt, batch_size, col_ops=None, lindbladian=False)

Propagate signal in batches :param hamiltonian: Drift Hamiltonian :type hamiltonian: tf.tensor :param hks: List of control hamiltonians :type hks: Union[tf.tensor, List[tf.tensor]] :param signals: List of control signals, one per control hamiltonian :type signals: Union[tf.tensor, List[tf.tensor]] :param dt: Length of one time slice :type dt: float :param batch_size: Number of elements in one batch :type batch_size: int

c3.libraries.propagation.tf_propagation(h0, hks, cflds, dt)

Calculate the unitary time evolution of a system controlled by time-dependent fields.

Parameters

• h0 (tf.tensor) – Drift Hamiltonian.

• hks (list of tf.tensor) – List of control Hamiltonians.

• cflds (list) – List of control fields, one per control Hamiltonian.

• dt (float) – Length of one time slice.

Returns

List of incremental propagators dU.

Return type

list

c3.libraries.propagation.evaluate_sequences(propagators: Dict, sequences: list)

Compute the total propagator of a sequence of gates.

Parameters

• propagators (dict) – Dictionary of unitary representation of gates.

• sequences (list) –

  List of keys from propagators specifying a gate sequence. The sequence is multiplied from the left, i.e.

  sequence = [U0, U1, U2, …]

  is applied as

  … U2 * U1 * U0

Returns

Propagator of the sequence.

Return type

tf.tensor

c3.libraries.propagation.tf_expm(A, terms)

Matrix exponential by the series method.

Parameters

• A (tf.tensor) – Matrix to be exponentiated.

• terms (int) – Number of terms in the series.

Returns

expm(A)

Return type

tf.tensor

c3.libraries.propagation.tf_expm_dynamic(A, acc=1e-05)

Matrix exponential by the series method with specified accuracy.

Parameters

• A (tf.tensor) – Matrix to be exponentiated.

• acc (float) – Accuracy. Stop when the maximum matrix entry reaches

Returns

expm(A)

Return type

tf.tensor