tensorcircuit.translation¶

Circuit object translation in different packages

tensorcircuit.translation.cirq2tc(qc: Any, n: int | None = None, inputs: List[float] | None = None, is_dm: bool = False, circuit_constructor: Any = None, circuit_params: Dict[str, Any] | None = None) → Any[source]¶

Generate a tensorcircuit circuit from the cirq circuit.

Parameters:

qc (cirq.Circuit) – A quantum circuit in cirq
n (Optional[int], optional) – # of qubits, defaults to None
inputs (Optional[List[float]], optional) – Input state of the circuit, defaults to None
is_dm (bool, optional) – whether to use DMCircuit, defaults to False
circuit_constructor (Any, optional) – _description_, defaults to None
circuit_params (Optional[Dict[str, Any]], optional) – _description_, defaults to None

Returns:

_description_

Return type:

Any

tensorcircuit.translation.ctrl_str2ctrl_state(ctrl_str: str, nctrl: int) → List[int][source]¶

tensorcircuit.translation.eqasm2tc(eqasm: str, nqubits: int | None = None, headers: Tuple[int, int] = (6, 1)) → Circuit[source]¶

Translation qexe/eqasm instruction to tensorcircuit Circuit object

Parameters:

eqasm (str) – _description_
nqubits (Optional[int], optional) – _description_, defaults to None
headers (Tuple[int, int], optional) – lines of ignored code at the head and the tail, defaults to (6, 1)

Returns:

_description_

Return type:

Circuit

tensorcircuit.translation.get_qiskit_qasm(qc: Any) → str[source]¶

tensorcircuit.translation.json2qir(tcqasm: List[Dict[str, Any]]) → List[Dict[str, Any]][source]¶

tensorcircuit.translation.json_to_tensor(a: Any) → Any[source]¶

tensorcircuit.translation.perm_matrix(n: int) → Any[source]¶

Generate a permutation matrix P. Due to the different convention or qubits’ order in qiskit and tensorcircuit, the unitary represented by the same circuit is different. They are related by this permutation matrix P: P @ U_qiskit @ P = U_tc

Parameters:: n (int) – # of qubits
Returns:: The permutation matrix P
Return type:: Tensor

tensorcircuit.translation.qir2cirq(qir: List[Dict[str, Any]], n: int, extra_qir: List[Dict[str, Any]] | None = None) → Any[source]¶

Generate a cirq circuit using the quantum intermediate representation (qir) in tensorcircuit.

Example:

>>> c = tc.Circuit(2)
>>> c.H(1)
>>> c.X(1)
>>> cisc = tc.translation.qir2cirq(c.to_qir(), 2)
>>> print(cisc)
1: ───H───X───

Parameters:

qir (List[Dict[str, Any]]) – The quantum intermediate representation of a circuit.
n (int) – # of qubits
extra_qir (Optional[List[Dict[str, Any]]]) – The extra quantum IR of tc circuit including measure and reset on hardware, defaults to None

Returns:

qiskit cirq object

Return type:

Any

#TODO(@erertertet): add default theta to iswap gate add more cirq built-in gate instead of customized add unitary test with tolerance add support of cirq built-in ControlledGate for multiplecontroll support more element in qir, e.g. barrier, measure…

tensorcircuit.translation.qir2json(qir: List[Dict[str, Any]], simplified: bool = False) → List[Dict[str, Any]][source]¶

transform qir to json compatible list of dict where array is replaced by real and imaginary list

Parameters:

qir (List[Dict[str, Any]]) – _description_
simplified (bool) – If False, keep all info for each gate, defaults to be False. If True, suitable for IO since less information is required

Returns:

_description_

Return type:

List[Dict[str, Any]]

tensorcircuit.translation.qir2qiskit(qir: List[Dict[str, Any]], n: int, extra_qir: List[Dict[str, Any]] | None = None, initialization: Any | None = None) → Any[source]¶

Generate a qiskit quantum circuit using the quantum intermediate representation (qir) in tensorcircuit.

Example:

>>> c = tc.Circuit(2)
>>> c.H(1)
>>> c.X(1)
>>> qisc = tc.translation.qir2qiskit(c.to_qir(), 2)
>>> qisc.data
[(Instruction(name='h', num_qubits=1, num_clbits=0, params=[]), [Qubit(QuantumRegister(2, 'q'), 1)], []),
 (Instruction(name='x', num_qubits=1, num_clbits=0, params=[]), [Qubit(QuantumRegister(2, 'q'), 1)], [])]

Parameters:

qir (List[Dict[str, Any]]) – The quantum intermediate representation of a circuit.
n (int) – # of qubits
extra_qir (Optional[List[Dict[str, Any]]]) – The extra quantum IR of tc circuit including measure and reset on hardware, defaults to None
initialization (Optional[Tensor]) – Circuit initial state in qiskit format

Returns:

qiskit QuantumCircuit object

Return type:

Any

tensorcircuit.translation.qiskit2tc(qc: Any, n: int, inputs: List[float] | None = None, is_dm: bool = False, circuit_constructor: Any = None, circuit_params: Dict[str, Any] | None = None, binding_params: Sequence[float] | Dict[Any, float] | None = None) → Any[source]¶

Generate a tensorcircuit circuit from the qiskit circuit.

Example:

>>> qisc = QuantumCircuit(2)
>>> qisc.h(0)
>>> qisc.x(1)
>>> qc = tc.translation.qiskit2tc(qisc, 2)
>>> qc.to_qir()[0]['gatef']

Parameters:

qc (QuantumCircuit) – A quantum circuit in qiskit.
n (int) – # of qubits
inputs (Optional[List[float]]) – Input state of the circuit. Default is None.
circuit_constructor – Circuit, DMCircuit or MPSCircuit
circuit_params (Optional[Dict[str, Any]]) – kwargs given in Circuit.__init__ construction function, default to None.
binding_params (Optional[Union[Sequence[float], Dict[Any, float]]]) – (variational) parameters for the circuit. Could be either a sequence or dictionary depending on the type of parameters in the Qiskit circuit. For ParameterVectorElement use sequence. For Parameter use dictionary.

Returns:

A quantum circuit in tensorcircuit

Return type:

Any

tensorcircuit.translation.qiskit_from_qasm_str_ordered_measure(qasm_str: str) → Any[source]¶

qiskit from_qasm_str method cannot keep the order of measure as the qasm file, we provide this alternative function in case the order of measure instruction matters

Parameters:: qasm_str (str) – open qasm str
Returns:: qiskit.circuit.QuantumCircuit
Return type:: Any

tensorcircuit.translation.stim2tc(stim_circuit: Any, n: int | None = None, is_dm: bool = False, circuit_constructor: Any = None, circuit_params: Dict[str, Any] | None = None) → Any[source]¶

Generate a tensorcircuit circuit from the stim circuit.

Parameters:

stim_circuit (stim.Circuit) – A quantum circuit in stim
n (Optional[int], optional) – # of qubits, defaults to None
is_dm (bool, optional) – whether to use DMCircuit, defaults to False
circuit_constructor (Any, optional) – _description_, defaults to None
circuit_params (Optional[Dict[str, Any]], optional) – _description_, defaults to None

Returns:

_description|

Return type:

Any

tensorcircuit.translation.tensor_to_json(a: Any) → Any[source]¶