pyquil.pyqvm module

class pyquil.pyqvm.AbstractQuantumSimulator(n_qubits: int, rs: numpy.random.mtrand.RandomState)[source]

Bases: abc.ABC

Initialize.

Parameters

  • n_qubits – Number of qubits to simulate.

  • rs – a RandomState (shared with the owning PyQVM) for doing anything stochastic.

abstract do_gate(gate: pyquil.quilbase.Gate) → pyquil.pyqvm.AbstractQuantumSimulator[source]

Perform a gate.

Returns

self to support method chaining.

abstract do_gate_matrix(matrix: numpy.ndarray, qubits: Sequence[int]) → pyquil.pyqvm.AbstractQuantumSimulator[source]

Apply an arbitrary unitary; not necessarily a named gate.

Parameters

  • matrix – The unitary matrix to apply. No checks are done

  • qubits – A list of qubits to apply the unitary to.

Returns

self to support method chaining.

abstract do_measurement(qubit: int) → int[source]

Measure a qubit and collapse the wavefunction

Returns

The measurement result. A 1 or a 0.

abstract do_post_gate_noise(noise_type: str, noise_prob: float, qubits: List[int]) → pyquil.pyqvm.AbstractQuantumSimulator[source]

Apply noise that happens after each gate application.

WARNING! This is experimental and the signature of this interface will likely change.

Parameters

  • noise_type – The name of the noise type

  • noise_prob – The probability of that noise happening

  • qubits – Apply noise to these qubits.

Returns

self to support method chaining

do_program(program: pyquil.quil.Program) → pyquil.pyqvm.AbstractQuantumSimulator[source]

Perform a sequence of gates contained within a program.

Parameters

program – The program

Returns

self

abstract expectation(operator: Union[pyquil.paulis.PauliTerm, pyquil.paulis.PauliSum]) → complex[source]

Compute the expectation of an operator.

Parameters

operator – The operator

Returns

The operator’s expectation value

abstract reset() → pyquil.pyqvm.AbstractQuantumSimulator[source]

Reset the wavefunction to the |000...00> state.

Returns

self to support method chaining.

abstract sample_bitstrings(n_samples: int) → numpy.ndarray[source]

Sample bitstrings from the current state.

Parameters

n_samples – The number of bitstrings to sample

Returns

A numpy array of shape (n_samples, n_qubits)

class pyquil.pyqvm.PyQVM(n_qubits: int, quantum_simulator_type: Optional[Type[pyquil.pyqvm.AbstractQuantumSimulator]] = None, seed: Optional[int] = None, post_gate_noise_probabilities: Optional[Dict[str, float]] = None)[source]

Bases: pyquil.api._qam.QAM[PyQVM]

PyQuil’s built-in Quil virtual machine.

This class implements common control flow and plumbing and dispatches the “actual” work to quantum simulators like ReferenceWavefunctionSimulator, ReferenceDensitySimulator, and NumpyWavefunctionSimulator

Parameters

  • n_qubits – The number of qubits. Typically this results in the allocation of a large ndarray, so be judicious.

  • quantum_simulator_type – A class that can be instantiated to handle the quantum aspects of this QVM. If not specified, the default will be either NumpyWavefunctionSimulator (no noise) or ReferenceDensitySimulator (noise)

  • post_gate_noise_probabilities – A specification of noise model given by probabilities of certain types of noise. The dictionary keys are from “relaxation”, “dephasing”, “depolarizing”, “phase_flip”, “bit_flip”, and “bitphase_flip”. WARNING: experimental. This interface will likely change.

  • seed – An optional random seed for performing stochastic aspects of the QVM.

execute(executable: Union[pyquil.api._abstract_compiler.EncryptedProgram, pyquil.quil.Program]) → pyquil.pyqvm.PyQVM[source]

Execute a program on the PyQVM. Note that the state of the instance is reset on each call to execute.

Returns

self to support method chaining.

execute_once(program: pyquil.quil.Program) → pyquil.pyqvm.PyQVM[source]

Execute one outer loop of a program on the PyQVM without re-initializing its state.

Note that the PyQVM is stateful. Subsequent calls to execute_once() will not automatically reset the wavefunction or the classical RAM. If this is desired, consider starting your program with RESET.

Returns

self to support method chaining.

find_label(label: Union[pyquil.quilatom.Label, pyquil.quilatom.LabelPlaceholder]) → int[source]

Helper function that iterates over the program and looks for a JumpTarget that has a Label matching the input label.

Parameters

label – Label object to search for in program

Returns

Program index where label is found

get_result(execute_response: pyquil.pyqvm.PyQVM) → pyquil.api._qam.QAMExecutionResult[source]

Return results from the PyQVM according to the common QAM API. Note that while the execute_response is not used, it’s accepted in order to conform to that API; it’s unused because the PyQVM, unlike other QAM’s, is itself stateful.

read_memory(*, region_name: str) → numpy.ndarray[source]
transition() → bool[source]

Implements a QAM-like transition.

This function assumes program and program_counter instance variables are set appropriately, and that the wavefunction simulator and classical memory ram instance variables are in the desired QAM input state.

Returns

whether the QAM should halt after this transition.

write_memory(*, region_name: str, offset: int = 0, value: int = 0) → pyquil.pyqvm.PyQVM[source]