blueqatパッケージ

Submodules

blueqat.circuit module

This module defines Circuit and the setting for circuit.

class blueqat.circuit.BlueqatGlobalSetting

ベースクラス: object

Setting for Blueqat.

static get_default_backend_name()

Get the default backend name.

Returns:

str: The name of default backend.

static register_backend(name, backend, allow_overwrite=False)

Register new backend.

Args:

name (str): The name of backend.

gateclass (type): The type object of backend

allow_overwrite (bool, optional): If True, allow to overwrite the existing backend.

Otherwise, raise the ValueError.

Raises:

ValueError: The name is duplicated with existing backend.

When allow_overwrite=True, this error is not raised.

static register_gate(name, gateclass, allow_overwrite=False)

Register new gate to gate set.

Args:

name (str): The name of gate.

gateclass (type): The type object of gate.

allow_overwrite (bool, optional): If True, allow to overwrite the existing gate.

Otherwise, raise the ValueError.

Raises:

ValueError: The name is duplicated with existing gate.

When allow_overwrite=True, this error is not raised.

static register_macro(name: str, func: Callable, allow_overwrite: bool = False) → None

Register new macro to Circuit.

Args:

name (str): The name of macro.

func (callable): The function to be called.

allow_overwrite (bool, optional): If True, allow to overwrite the existing macro.

Otherwise, raise the ValueError.

Raises:

ValueError: The name is duplicated with existing macro, gate or method.

When allow_overwrite=True, this error is not raised.

static remove_backend(name)

This method is deperecated. Use unregister_backend method.

static set_default_backend(name)

Set the default backend to be used by Circuit. Args:

name (str): The name of the default backend.

Raises:

ValueError: Specified backend is not registered.

static unregister_backend(name)

Unregister a backend.

Args:

name (str): The name of the backend to be unregistered.

Raises:

ValueError: Specified backend is not registered.

static unregister_gate(name)

Unregister a gate from gate set

Args:

name (str): The name of the gate to be unregistered.

Raises:

ValueError: Specified gate is not registered.

static unregister_macro(name)

Unregister a macro.

Args:

name (str): The name of the macro to be unregistered.

Raises:

ValueError: Specified gate is not registered.

class blueqat.circuit.Circuit(n_qubits=0, ops=None)

ベースクラス: object

Store the gate operations and call the backends.

copy(copy_backends=True, copy_default_backend=True, copy_cache=None, copy_history=None)

Copy the circuit.

params:

copy_backends :bool copy backends if True.

copy_default_backend :bool copy default_backend if True.

dagger(ignore_measurement=False, copy_backends=False, copy_default_backend=True)

Make Hermitian conjugate of the circuit.

This feature is beta. Interface may be changed.

ignore_measurement (bool, optional):

If True, ignore the measurement in the circuit.

Otherwise, if measurement in the circuit, raises ValueError.

get_default_backend_name()

Get the default backend of this circuit or global setting.

Returns:

str: The name of default backend.

make_cache(backend=None)

Make a cache to reduce the time of run. Some backends may implemented it.

This is temporary API. It may changed or deprecated.

run(*args, backend=None, **kwargs)

Run the circuit.

Circuit have several backends. When backend parameter is specified, use specified backend, and otherwise, default backend is used. Other parameters are passed to the backend.

The meaning of parameters are depends on the backend specifications. However, following parameters are commonly used.

Commonly used args (Depends on backend):

shots (int, optional): The number of sampling the circuit.

returns (str, optional): The category of returns value.

e.g. "statevector" returns the state vector after run the circuit.

"shots" returns the counter of measured value.

token, url (str, optional): The token and URL for cloud resource.

Returns:

Depends on backend.

Raises:

Depends on backend.

set_default_backend(backend_name)

Set the default backend of this circuit.

This setting is only applied for this circuit. If you want to change the default backend of all gates, use BlueqatGlobalSetting.set_default_backend().

After set the default backend by this method, global setting is ignored even if BlueqatGlobalSetting.set_default_backend() is called. If you want to use global default setting, call this method with backend_name=None.

Args:

backend_name (str or None): new default backend name.

If None is given, global setting is applied.

Raises:

ValueError: If backend_name is not registered backend.

to_qasm(*args, **kwargs)

Returns the OpenQASM output of this circuit.

to_unitary(*args, **kwargs)

Returns sympy unitary matrix of this circuit.

blueqat.gate module

gate module implements quantum gate operations. This module is internally used.

class blueqat.gate.CCZGate(targets, params=(), **kwargs)

ベースクラス: blueqat.gate.Gate

2-Controlled Z gate

dagger()

Returns the Hermitian conjugate of self.

lowername = 'ccz'

class blueqat.gate.CHGate(targets, params=(), **kwargs)

ベースクラス: blueqat.gate.TwoQubitGate

Controlled-H gate

dagger()

Returns the Hermitian conjugate of self.

fallback(n_qubits)

Returns alternative gates to make equivalent circuit.

lowername = 'ch'

class blueqat.gate.CPhaseGate(targets, theta, **kwargs)

ベースクラス: blueqat.gate.TwoQubitGate

Rotate-Z gate but phase is different.

dagger()

Returns the Hermitian conjugate of self.

fallback(n_qubits)

Returns alternative gates to make equivalent circuit.

lowername = 'cphase'

class blueqat.gate.CRXGate(targets, theta, **kwargs)

ベースクラス: blueqat.gate.TwoQubitGate

Rotate-X gate

dagger()

Returns the Hermitian conjugate of self.

fallback(n_qubits)

Returns alternative gates to make equivalent circuit.

lowername = 'crx'

class blueqat.gate.CRYGate(targets, theta, **kwargs)

ベースクラス: blueqat.gate.TwoQubitGate

Rotate-Y gate

dagger()

Returns the Hermitian conjugate of self.

fallback(n_qubits)

Returns alternative gates to make equivalent circuit.

lowername = 'cry'

class blueqat.gate.CRZGate(targets, theta, **kwargs)

ベースクラス: blueqat.gate.TwoQubitGate

Rotate-Z gate

dagger()

Returns the Hermitian conjugate of self.

fallback(n_qubits)

Returns alternative gates to make equivalent circuit.

lowername = 'crz'

class blueqat.gate.CSwapGate(targets, params=(), **kwargs)

ベースクラス: blueqat.gate.Gate

Controlled SWAP gate

dagger()

Returns the Hermitian conjugate of self.

fallback(n_qubits)

Returns alternative gates to make equivalent circuit.

lowername = 'cswap'

class blueqat.gate.CU1Gate(targets, lambd, **kwargs)

ベースクラス: blueqat.gate.TwoQubitGate

Controlled U1 gate

U1 gate is as same as RZ gate and CU1 gate is as same as CPhase gate. It is because for compatibility with IBM's implementations.

You should probably use RZ/CRZ gates or Phase/CPhase gates instead of U1/CU1 gates.

dagger()

Returns the Hermitian conjugate of self.

fallback(n_qubits)

Returns alternative gates to make equivalent circuit.

lowername = 'cu1'

class blueqat.gate.CU2Gate(targets, phi, lambd, **kwargs)

ベースクラス: blueqat.gate.TwoQubitGate

Controlled U2 gate

dagger()

Returns the Hermitian conjugate of self.

fallback(n_qubits)

Returns alternative gates to make equivalent circuit.

lowername = 'cu2'

class blueqat.gate.CU3Gate(targets, theta, phi, lambd, **kwargs)

ベースクラス: blueqat.gate.TwoQubitGate

Controlled U3 gate

dagger()

Returns the Hermitian conjugate of self.

fallback(n_qubits)

Returns alternative gates to make equivalent circuit.

lowername = 'cu3'

class blueqat.gate.CXGate(targets, params=(), **kwargs)

ベースクラス: blueqat.gate.TwoQubitGate

Controlled-X (CNOT) gate

dagger()

Returns the Hermitian conjugate of self.

lowername = 'cx'

class blueqat.gate.CYGate(targets, params=(), **kwargs)

ベースクラス: blueqat.gate.TwoQubitGate

Controlled-Y gate

dagger()

Returns the Hermitian conjugate of self.

fallback(n_qubits)

Returns alternative gates to make equivalent circuit.

lowername = 'cy'

class blueqat.gate.CZGate(targets, params=(), **kwargs)

ベースクラス: blueqat.gate.TwoQubitGate

Controlled-Z gate

dagger()

Returns the Hermitian conjugate of self.

lowername = 'cz'

class blueqat.gate.Gate(targets, params=(), **kwargs)

ベースクラス: abc.ABC

Abstract quantum gate class.

dagger() → blueqat.gate.Gate

Returns the Hermitian conjugate of self.

fallback(n_qubits: int) → List[blueqat.gate.Gate]

Returns alternative gates to make equivalent circuit.

lowername = None

uppername

Upper name of the gate.

class blueqat.gate.HGate(targets, params=(), **kwargs)

ベースクラス: blueqat.gate.OneQubitGate

Hadamard gate

dagger()

Returns the Hermitian conjugate of self.

lowername = 'h'

class blueqat.gate.IGate(targets, params=(), **kwargs)

ベースクラス: blueqat.gate.OneQubitGate

Identity gate

dagger()

Returns the Hermitian conjugate of self.

fallback(n_qubits)

Returns alternative gates to make equivalent circuit.

lowername = 'i'

class blueqat.gate.Measurement(targets, params=(), **kwargs)

ベースクラス: blueqat.gate.OneQubitGate

Measurement operation

dagger()

Returns the Hermitian conjugate of self.

lowername = 'measure'

class blueqat.gate.OneQubitGate(targets, params=(), **kwargs)

ベースクラス: blueqat.gate.Gate

Abstract quantum gate class for 1 qubit gate.

target_iter(n_qubits)

The generator which yields the target qubits.

class blueqat.gate.PhaseGate(targets, theta, **kwargs)

ベースクラス: blueqat.gate.OneQubitGate

Rotate-Z gate but global phase is different.

Global phase doesn't makes any difference of measured result. You may use RZ gate or U1 gate instead, but distinguishing these gates may better for debugging or future improvement.

furthermore, phase gate may efficient for simulating. (It depends on backend implementation. But matrix of phase gate is simpler than RZ gate or U1 gate.)

dagger()

Returns the Hermitian conjugate of self.

fallback(n_qubits)

Returns alternative gates to make equivalent circuit.

lowername = 'phase'

class blueqat.gate.RXGate(targets, theta, **kwargs)

ベースクラス: blueqat.gate.OneQubitGate

Rotate-X gate

dagger()

Returns the Hermitian conjugate of self.

lowername = 'rx'

class blueqat.gate.RXXGate(targets, theta, **kwargs)

ベースクラス: blueqat.gate.TwoQubitGate

Rotate-XX gate

dagger()

Returns the Hermitian conjugate of self.

fallback(n_qubits)

Returns alternative gates to make equivalent circuit.

lowername = 'rxx'

class blueqat.gate.RYGate(targets, theta, **kwargs)

ベースクラス: blueqat.gate.OneQubitGate

Rotate-Y gate

dagger()

Returns the Hermitian conjugate of self.

lowername = 'ry'

class blueqat.gate.RYYGate(targets, theta, **kwargs)

ベースクラス: blueqat.gate.TwoQubitGate

Rotate-YY gate

dagger()

Returns the Hermitian conjugate of self.

fallback(n_qubits)

Returns alternative gates to make equivalent circuit.

lowername = 'ryy'

class blueqat.gate.RZGate(targets, theta, **kwargs)

ベースクラス: blueqat.gate.OneQubitGate

Rotate-Z gate

dagger()

Returns the Hermitian conjugate of self.

lowername = 'rz'

class blueqat.gate.RZZGate(targets, theta, **kwargs)

ベースクラス: blueqat.gate.TwoQubitGate

Rotate-ZZ gate

dagger()

Returns the Hermitian conjugate of self.

fallback(n_qubits)

Returns alternative gates to make equivalent circuit.

lowername = 'rzz'

class blueqat.gate.Reset(targets, params=(), **kwargs)

ベースクラス: blueqat.gate.OneQubitGate

Reset operation

dagger()

Returns the Hermitian conjugate of self.

lowername = 'reset'

class blueqat.gate.SDagGate(targets, params=(), **kwargs)

ベースクラス: blueqat.gate.OneQubitGate

Dagger of S gate

dagger()

Returns the Hermitian conjugate of self.

fallback(n_qubits)

Returns alternative gates to make equivalent circuit.

lowername = 'sdg'

class blueqat.gate.SGate(targets, params=(), **kwargs)

ベースクラス: blueqat.gate.OneQubitGate

S gate

dagger()

Returns the Hermitian conjugate of self.

fallback(n_qubits)

Returns alternative gates to make equivalent circuit.

lowername = 's'

class blueqat.gate.SwapGate(targets, params=(), **kwargs)

ベースクラス: blueqat.gate.TwoQubitGate

Swap gate

dagger()

Returns the Hermitian conjugate of self.

fallback(n_qubits)

Returns alternative gates to make equivalent circuit.

lowername = 'swap'

class blueqat.gate.TDagGate(targets, params=(), **kwargs)

ベースクラス: blueqat.gate.OneQubitGate

Dagger of T ($pi/8$) gate

dagger()

Returns the Hermitian conjugate of self.

fallback(n_qubits)

Returns alternative gates to make equivalent circuit.

lowername = 'tdg'

class blueqat.gate.TGate(targets, params=(), **kwargs)

ベースクラス: blueqat.gate.OneQubitGate

T ($pi/8$) gate

dagger()

Returns the Hermitian conjugate of self.

fallback(n_qubits)

Returns alternative gates to make equivalent circuit.

lowername = 't'

class blueqat.gate.ToffoliGate(targets, params=(), **kwargs)

ベースクラス: blueqat.gate.Gate

Toffoli (CCX) gate

dagger()

Returns the Hermitian conjugate of self.

fallback(n_qubits)

Returns alternative gates to make equivalent circuit.

lowername = 'ccx'

class blueqat.gate.TwoQubitGate(targets, params=(), **kwargs)

ベースクラス: blueqat.gate.Gate

Abstract quantum gate class for 2 qubits gate.

control_target_iter(n_qubits)

The generator which yields the tuples of (control, target) qubits.

class blueqat.gate.U1Gate(targets, lambd, **kwargs)

ベースクラス: blueqat.gate.OneQubitGate

U1 gate

U1 gate is as same as RZ gate and CU1 gate is as same as CPhase gate. It is because for compatibility with IBM's implementations.

You should probably use RZ/CRZ gates or Phase/CPhase gates instead of U1/CU1 gates.

dagger()

Returns the Hermitian conjugate of self.

fallback(n_qubits)

Returns alternative gates to make equivalent circuit.

lowername = 'u1'

class blueqat.gate.U2Gate(targets, phi, lambd, **kwargs)

ベースクラス: blueqat.gate.OneQubitGate

U2 gate

dagger()

Returns the Hermitian conjugate of self.

fallback(n_qubits)

Returns alternative gates to make equivalent circuit.

lowername = 'u2'

class blueqat.gate.U3Gate(targets, theta, phi, lambd, **kwargs)

ベースクラス: blueqat.gate.OneQubitGate

U3 gate

dagger()

Returns the Hermitian conjugate of self.

lowername = 'u3'

class blueqat.gate.XGate(targets, params=(), **kwargs)

ベースクラス: blueqat.gate.OneQubitGate

Pauli's X gate

dagger()

Returns the Hermitian conjugate of self.

lowername = 'x'

class blueqat.gate.YGate(targets, params=(), **kwargs)

ベースクラス: blueqat.gate.OneQubitGate

Pauli's Y gate

dagger()

Returns the Hermitian conjugate of self.

lowername = 'y'

class blueqat.gate.ZGate(targets, params=(), **kwargs)

ベースクラス: blueqat.gate.OneQubitGate

Pauli's Z gate

dagger()

Returns the Hermitian conjugate of self.

lowername = 'z'

blueqat.gate.find_n_qubits(gates)

Find n_qubits from gates

blueqat.gate.get_maximum_index(indices)

Internally used.

blueqat.gate.qubit_pairs(args, length)

Internally used.

blueqat.gate.slicing(args, length)

Internally used.

blueqat.gate.slicing_singlevalue(arg, length)

Internally used.

blueqat.pauli module

The module for calculate Pauli matrices.

class blueqat.pauli.Expr

ベースクラス: blueqat.pauli._ExprTuple

coeffs()

Generator which yields a coefficent for each Term.

commutator(other)

Returns commutator.

static from_number(num)

Make new Expr from a number

static from_term(term)

Make new Expr from a Term

static from_terms_dict(terms_dict)

For internal use.

static from_terms_iter(terms)

For internal use.

is_all_terms_commutable()

Test whether all terms are commutable. This function may very slow.

is_commutable_with(other)

Test whether self is commutable with other.

max_n()

Returns the maximum index of Pauli matrices in the Expr. If Expr is empty or only constant and identity matrix, returns -1.

simplify()

Simplify the Expr.

terms_to_dict()

For internal use.

to_expr()

Do nothing. This method is prepared to avoid TypeError.

to_matrix(n_qubits=-1, *, sparse=None)

Convert to the matrix.

static zero()

Returns 0 as Term

is_identity

If self is I, returns True, otherwise False.

n_qubits

Returns the number of qubits of the Term.

If Expr is empty or only constant and identity matrix, returns 0.

class blueqat.pauli.Term

ベースクラス: blueqat.pauli._TermTuple

Multiplication of Pauli matrices with coefficient. Note that this class is immutable.

Multiplied Pauli matrices are very important for quantum computation because it is an unitary matrix (without coefficient) and also it can be consider the time evolution of the term (with real coefficient) without Suzuki-Trotter expansion.

append_to_circuit(circuit, simplify=True)

Append Pauli gates to Circuit.

commutator(other)

Returns commutator.

static from_chars(chars)

Make Pauli's Term from chars which is written by "X", "Y", "Z" or "I". e.g. "XZIY" => X(0) * Z(1) * Y(3)

Args:

chars (str): Written in "X", "Y", "Z" or "I".

Returns:

Term: A Term object.

Raises:

ValueError: When chars conteins the character which is "X", "Y", "Z" nor "I".

static from_ops_iter(ops, coeff)

For internal use.

static from_pauli(pauli, coeff=1.0)

Make new Term from an Pauli operator

static from_paulipair(pauli1, pauli2)

Make new Term from two Pauli operator.

get_time_evolution()

Get the function to append the time evolution of this term.

Returns:

function(circuit: Circuit, t: float):

Add gates for time evolution to circuit with time t

is_commutable_with(other)

Test whether self is commutable with other.

static join_ops(ops1, ops2)

For internal use.

max_n()

Returns the maximum index of Pauli matrices in the Term. If there's no Pauli matrices, returns -1.

n_iter()

Returns an iterator which yields indices for each Pauli matrices in the Term.

simplify()

Simplify the Term.

to_expr()

Convert to Expr.

to_matrix(n_qubits=-1, *, sparse=None)

Convert to the matrix.

to_term()

Do nothing. This method is prepared to avoid TypeError.

is_identity

If self is I, returns True, otherwise False.

n_qubits

Returns the number of qubits of the term. If the term is constant with identity matrix, n_qubits is 0.

blueqat.pauli.commutator(expr1, expr2)

Returns [expr1, expr2] = expr1 * expr2 - expr2 * expr1.

Args:

expr1 (Expr, Term or Pauli operator): Pauli's expression.

expr2 (Expr, Term or Pauli operator): Pauli's expression.

Returns:

Expr: expr1 * expr2 - expr2 * expr1.

blueqat.pauli.is_commutable(expr1, expr2, eps=1e-08)

Test whether expr1 and expr2 are commutable.

Args:

expr1 (Expr, Term or Pauli operator): Pauli's expression.

expr2 (Expr, Term or Pauli operator): Pauli's expression.

eps (float, optional): Machine epsilon. If | [expr1, expr2 ]| < eps, consider it is commutable.

Returns:

bool: if expr1 and expr2 are commutable, returns True, otherwise False.

blueqat.pauli.pauli_from_char(ch, n=0)

Make Pauli matrix from an character.

Args:

ch (str): "X" or "Y" or "Z" or "I".

n (int, optional): Make Pauli matrix as n-th qubits.

Returns:

If ch is "X" => X, "Y" => Y, "Z" => Z, "I" => I

Raises:

ValueError: When ch is not "X", "Y", "Z" nor "I".

blueqat.pauli.qubo_bit(n)

Represent QUBO's bit to Pauli operator of Ising model.

Args:

n (int): n-th bit in QUBO

Returns:

Expr: Pauli expression of QUBO bit.

blueqat.pauli.term_from_chars(chars)

Make Pauli's Term from chars which is written by "X", "Y", "Z" or "I". e.g. "XZIY" => X(3) * Z(2) * Y(0)

Args:

chars (str): Written in "X", "Y", "Z" or "I".

Returns:

Term: A Term object.

Raises:

ValueError: When chars conteins the character which is "X", "Y", "Z" nor "I".

blueqat.pauli.to_expr(term)

Convert to Expr from Term or Pauli operator (X, Y, Z, I).

Args:

term: (Term, X, Y, Z or I): A Term or Pauli operator.

Returns:

Expr: An Expr object.

blueqat.pauli.to_term(pauli)

Convert to Term from Pauli operator (X, Y, Z, I).

Args:

pauli (X, Y, Z or I): A Pauli operator

Returns:

Term: A Term object.

blueqat.vqe module

class blueqat.vqe.AnsatzBase(hamiltonian, n_params)

ベースクラス: object

get_circuit(params)

Make a circuit from parameters.

get_energy(circuit, sampler)

Calculate energy from circuit and sampler.

get_energy_sparse(circuit)

Get energy using sparse matrix. This method may be changed in the future release.

get_objective(sampler=None)

Get an objective function to be optimized.

make_sparse(fmt='csc', make_method=None)

Make sparse matrix. This method may be changed in the future release.

class blueqat.vqe.QaoaAnsatz(hamiltonian, step=1, init_circuit=None, mixer=None)

ベースクラス: blueqat.vqe.AnsatzBase

Ansatz for QAOA.

check_hamiltonian()

Check hamiltonian is commutable. This condition is required for QaoaAnsatz

get_circuit(params)

Make a circuit from parameters.

class blueqat.vqe.Vqe(ansatz, minimizer=None, sampler=None)

ベースクラス: object

run(verbose=False)

result

Vqe.result is deprecated. Use result = Vqe.run().

class blueqat.vqe.VqeResult(vqe=None, params=None, circuit=None)

ベースクラス: object

get_probs(sampler=None, rerun=None, store=True)

Get probabilities.

most_common(n=1)

probs

Get probabilities. This property is obsoleted. Use get_probs().

blueqat.vqe.expect(qubits, meas)

For the VQE simulation without sampling.

blueqat.vqe.get_measurement_sampler(n_sample, run_options=None)

Returns a function which get the expectations by sampling the measured circuit

blueqat.vqe.get_qiskit_sampler(backend, **execute_kwargs)

Returns a function which get the expectation by sampling via Qiskit.

This function requires qiskit module.

blueqat.vqe.get_scipy_minimizer(**kwargs)

Get minimizer which uses scipy.optimize.minimize

blueqat.vqe.get_state_vector_sampler(n_sample)

Returns a function which get the expectations by sampling the state vector

blueqat.vqe.non_sampling_sampler(circuit, meas)

Calculate the expectations without sampling.

blueqat.vqe.sparse_expectation(mat, vec)

Calculate expectation value <vec|mat|vec>.

Args:

mat (scipy sparse matrix): Sparse matrix vec (numpy array): Vector

Returns:

(Real part of) expectation value <vec|mat|vec>. Remarks: when mat is Hermitian, <vec|mat|vec> is real.

blueqat.wq module

class blueqat.wq.Opt

ベースクラス: object

Optimizer for SA/SQA.

add(qubo, M=1)

dw()

expand_qubo(qubo)

fit(vdata, shots=100, targetT=0.02, alpha=0.9, epsilon=0.1, epoch=100, verbose=True)

plot()

Draws energy chart using matplotlib.

qaoa(shots=1, step=2, verbose=False)

qi()

qubo_to_matrix(qubo)

rbm_model_qubo(shots=100, targetT=0.02)

reJ()

run(shots=1, sampler='normal', targetT=0.02, verbose=False)

Run SA with provided QUBO. Set qubo attribute in advance of calling this method.

sa(shots=1, sampler='normal')

setRBM(rbm_arr)

sqa()

Run SQA with provided QUBO. Set qubo attribute in advance of calling this method.

E = None

List of energies

Gf = None

Final strength of transverse magnetic field. [SQA]

Gs = None

Initial strength of transverse magnetic field. [SQA]

R = None

Descreasing rate of temperature [SA]

RBMvisible = None

RBM Models

Tf = None

Final temperature [SA]. Temperature [SQA]

Ts = None

Initial temperature [SA]

ite = None

Iterations [SA]

qubo = None

QUBO

tro = None

Trotter slices [SQA]

blueqat.wq.Ei(q3, j3)

blueqat.wq.Ei_sqa(q, J, T, P, G)

blueqat.wq.counter(narr)

blueqat.wq.dbms(dbms_arr, weight_init=0)

blueqat.wq.diag(diag_ele)

Create QUBO with diag from list

print(wq.diag([1,2,1]))
#=>
[[1 0 0]
[0 2 0]
[0 0 1]]

blueqat.wq.make_qs(n, m=None)

Make sympy symbols q0, q1, ...

Args:

n(int), m(int, optional):

If specified both n and m, returns [qn, q(n+1), ..., qm],

Only n is specified, returns[q0, q1, ..., qn].

Return:

tuple(Symbol): Tuple of sympy symbols.

blueqat.wq.mul(mulA, mulB)

blueqat.wq.nbody_separation(expr, qs)

Convert n-body problem to 2-body problem.

Args:

expr: sympy expressions to be separated.

qs: sympy's symbols to be used as supplementary variable.

Return:

new_expr(sympy expr), constraints(sympy expr), mapping(dict(str, str -> Symbol)):

new_expr is converted problem, constraints is constraints for supplementary variable.

You may use expr = new_expr + delta * constraints, delta is floating point variable.

mapping is supplementary variable's mapping.

blueqat.wq.net(narr, nnet)

Automatically create QUBO which has value 1 for all connectivity defined by array of edges and graph size N

print(wq.net([[0,1],[1,2]],4))
#=>
[[0. 1. 0. 0.]
[0. 0. 1. 0.]
[0. 0. 0. 0.]
[0. 0. 0. 0.]]

this create 4*4 QUBO and put value 1 on connection between 0th and 1st qubit, 1st and 2nd qubit

blueqat.wq.optm(quboh, numM)

blueqat.wq.optx(quboh)

blueqat.wq.pauli(qubo)

Convert to pauli operators of universal gate model.

blueqat.wq.qn_to_qubo(expr)

Convert Sympy's expr to QUBO.

Args:

expr: Sympy's quadratic expression with variable q0, q1, ...

Returns:

[[float]]: Returns QUBO matrix.

blueqat.wq.rands(rands_ele)

Create QUBO with random number

print(wq.rands(2))
#=>
[[0.89903411 0.68839641]
[0.         0.28554602]]

blueqat.wq.rbm_data_qubo(vdata, dbms_mat1)

blueqat.wq.rbm_hmodel(vdata, dbms_mat1)

blueqat.wq.sel(selN, selK, selarr=[])

Automatically create QUBO which select K qubits from N qubits

print(wq.sel(5,2))
#=>
[[-3  2  2  2  2]
[ 0 -3  2  2  2]
[ 0  0 -3  2  2]
[ 0  0  0 -3  2]
[ 0  0  0  0 -3]]

if you set array on the 3rd params, the result likely to choose the nth qubit in the array

print(wq.sel(5,2,[0,2]))
#=>
[[-3.5  2.   2.   2.   2. ]
[ 0.  -3.   2.   2.   2. ]
[ 0.   0.  -3.5  2.   2. ]
[ 0.   0.   0.  -3.   2. ]
[ 0.   0.   0.   0.  -3. ]]

blueqat.wq.sigm(x)

blueqat.wq.sqr(sqrA)

blueqat.wq.zeros(zeros_ele)

Create QUBO with all element value as 0

print(wq.zeros(3))
#=>
[[0. 0. 0.]
[0. 0. 0.]
[0. 0. 0.]]

Module contents

class blueqat.Circuit(n_qubits=0, ops=None)

ベースクラス: object

Store the gate operations and call the backends.

copy(copy_backends=True, copy_default_backend=True, copy_cache=None, copy_history=None)

Copy the circuit.

params:

copy_backends :bool copy backends if True.

copy_default_backend :bool copy default_backend if True.

dagger(ignore_measurement=False, copy_backends=False, copy_default_backend=True)

Make Hermitian conjugate of the circuit.

This feature is beta. Interface may be changed.

ignore_measurement (bool, optional):

If True, ignore the measurement in the circuit.

Otherwise, if measurement in the circuit, raises ValueError.

get_default_backend_name()

Get the default backend of this circuit or global setting.

Returns:

str: The name of default backend.

make_cache(backend=None)

Make a cache to reduce the time of run. Some backends may implemented it.

This is temporary API. It may changed or deprecated.

run(*args, backend=None, **kwargs)

Run the circuit.

Circuit have several backends. When backend parameter is specified, use specified backend, and otherwise, default backend is used. Other parameters are passed to the backend.

The meaning of parameters are depends on the backend specifications. However, following parameters are commonly used.

Commonly used args (Depends on backend):

shots (int, optional): The number of sampling the circuit.

returns (str, optional): The category of returns value.

e.g. "statevector" returns the state vector after run the circuit.

"shots" returns the counter of measured value.

token, url (str, optional): The token and URL for cloud resource.

Returns:

Depends on backend.

Raises:

Depends on backend.

set_default_backend(backend_name)

Set the default backend of this circuit.

This setting is only applied for this circuit. If you want to change the default backend of all gates, use BlueqatGlobalSetting.set_default_backend().

After set the default backend by this method, global setting is ignored even if BlueqatGlobalSetting.set_default_backend() is called. If you want to use global default setting, call this method with backend_name=None.

Args:

backend_name (str or None): new default backend name.

If None is given, global setting is applied.

Raises:

ValueError: If backend_name is not registered backend.

to_qasm(*args, **kwargs)

Returns the OpenQASM output of this circuit.

to_unitary(*args, **kwargs)

Returns sympy unitary matrix of this circuit.

class blueqat.BlueqatGlobalSetting

ベースクラス: object

Setting for Blueqat.

static get_default_backend_name()

Get the default backend name.

Returns:

str: The name of default backend.

static register_backend(name, backend, allow_overwrite=False)

Register new backend.

Args:

name (str): The name of backend.

gateclass (type): The type object of backend

allow_overwrite (bool, optional): If True, allow to overwrite the existing backend.

Otherwise, raise the ValueError.

Raises:

ValueError: The name is duplicated with existing backend.

When allow_overwrite=True, this error is not raised.

static register_gate(name, gateclass, allow_overwrite=False)

Register new gate to gate set.

Args:

name (str): The name of gate.

gateclass (type): The type object of gate.

allow_overwrite (bool, optional): If True, allow to overwrite the existing gate.

Otherwise, raise the ValueError.

Raises:

ValueError: The name is duplicated with existing gate.

When allow_overwrite=True, this error is not raised.

static register_macro(name: str, func: Callable, allow_overwrite: bool = False) → None

Register new macro to Circuit.

Args:

name (str): The name of macro.

func (callable): The function to be called.

allow_overwrite (bool, optional): If True, allow to overwrite the existing macro.

Otherwise, raise the ValueError.

Raises:

ValueError: The name is duplicated with existing macro, gate or method.

When allow_overwrite=True, this error is not raised.

static remove_backend(name)

This method is deperecated. Use unregister_backend method.

static set_default_backend(name)

Set the default backend to be used by Circuit. Args:

name (str): The name of the default backend.

Raises:

ValueError: Specified backend is not registered.

static unregister_backend(name)

Unregister a backend.

Args:

name (str): The name of the backend to be unregistered.

Raises:

ValueError: Specified backend is not registered.

static unregister_gate(name)

Unregister a gate from gate set

Args:

name (str): The name of the gate to be unregistered.

Raises:

ValueError: Specified gate is not registered.

static unregister_macro(name)

Unregister a macro.

Args:

name (str): The name of the macro to be unregistered.

Raises:

ValueError: Specified gate is not registered.