jaunatisblue/final-qibotn
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Grouped codes to higher level functions

Browse Source
This commit is contained in:
tankya2
2023-04-21 16:20:49 +08:00
parent 0eb186b43b
commit fa11a0ffac
1 changed files with 37 additions and 37 deletions
Download Patch File Download Diff File Expand all files Collapse all files

74
src/qibotn/QiboCircuitConvertor.py
View File

@@ -19,33 +19,13 @@ class QiboCircuitToEinsum:
def __init__(self, circuit, dtype="complex128"): def __init__(self, circuit, dtype="complex128"):
self.backend = cp self.backend = cp
self.dtype = getattr(self.backend, dtype) self.dtype = getattr(self.backend, dtype)
self.init_basis_map(self.backend, dtype)
self.gate_tensors = [] self.init_intermediate_circuit(circuit)
gates_qubits = []
for gate in circuit.queue:
gate_qubits = gate.control_qubits + gate.target_qubits
gates_qubits.extend(gate_qubits)
# self.gate_tensors is to extract into a list the gate matrix together with the qubit id that it is acting on
# https://github.com/NVIDIA/cuQuantum/blob/6b6339358f859ea930907b79854b90b2db71ab92/python/cuquantum/cutensornet/_internal/circuit_parser_utils_cirq.py#L32
required_shape = self.op_shape_from_qubits(len(gate_qubits))
self.gate_tensors.append(
(
cp.asarray(gate.matrix).reshape(required_shape),
gate_qubits,
)
)
# self.active_qubits is to identify qubits with at least 1 gate acting on it in the whole circuit.
self.active_qubits = np.unique(gates_qubits)
def state_vector_operands(self): def state_vector_operands(self):
input_tensor_count = len(self.active_qubits) input_bitstring = "0" * len(self.active_qubits)
input_operands = self._get_bitstring_tensors( input_operands = self._get_bitstring_tensors(input_bitstring)
"0" * input_tensor_count, self.dtype, backend=self.backend
)
( (
mode_labels, mode_labels,
@@ -69,21 +49,13 @@ class QiboCircuitToEinsum:
return operand_exp_interleave return operand_exp_interleave
def _init_mode_labels_from_qubits(self, qubits): def _init_mode_labels_from_qubits(self, qubits):
frontier_dict = {}
n = len(qubits) n = len(qubits)
for x in range(n): frontier_dict = {qubits[x]: x for x in range(n)}
frontier_dict[qubits[x]] = x mode_labels = [[i] for i in range(n)]
return [[i] for i in range(n)], frontier_dict, n return mode_labels, frontier_dict, n
def _get_bitstring_tensors(self, bitstring, dtype=np.complex128, backend=cp): def _get_bitstring_tensors(self, bitstring):
asarray = backend.asarray return [self.basis_map[ibit] for ibit in bitstring]
state_0 = asarray([1, 0], dtype=dtype)
state_1 = asarray([0, 1], dtype=dtype)
basis_map = {"0": state_0, "1": state_1}
operands = [basis_map[ibit] for ibit in bitstring]
return operands
def _parse_gates_to_mode_labels_operands( def _parse_gates_to_mode_labels_operands(
self, gates, qubits_frontier, next_frontier self, gates, qubits_frontier, next_frontier
@@ -108,3 +80,31 @@ class QiboCircuitToEinsum:
(qubit_states,input_output) * qubits_involved (qubit_states,input_output) * qubits_involved
""" """
return (2, 2) * nqubits return (2, 2) * nqubits
def init_intermediate_circuit(self, circuit):
self.gate_tensors = []
gates_qubits = []
for gate in circuit.queue:
gate_qubits = gate.control_qubits + gate.target_qubits
gates_qubits.extend(gate_qubits)
# self.gate_tensors is to extract into a list the gate matrix together with the qubit id that it is acting on
# https://github.com/NVIDIA/cuQuantum/blob/6b6339358f859ea930907b79854b90b2db71ab92/python/cuquantum/cutensornet/_internal/circuit_parser_utils_cirq.py#L32
required_shape = self.op_shape_from_qubits(len(gate_qubits))
self.gate_tensors.append(
(
cp.asarray(gate.matrix).reshape(required_shape),
gate_qubits,
)
)
# self.active_qubits is to identify qubits with at least 1 gate acting on it in the whole circuit.
self.active_qubits = np.unique(gates_qubits)
def init_basis_map(self, backend, dtype):
asarray = backend.asarray
state_0 = asarray([1, 0], dtype=dtype)
state_1 = asarray([0, 1], dtype=dtype)
self.basis_map = {"0": state_0, "1": state_1}