47 lines
1.6 KiB
Python
47 lines
1.6 KiB
Python
import numpy as np
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import quimb.tensor as qtn
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def init_state_tn(nqubits, init_state_sv):
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"""Create a matrix product state directly from a dense vector.
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Args:
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nqubits (int): Total number of qubits in the circuit.
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init_state_sv (list): Initial state in the dense vector form.
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Returns:
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list: Matrix product state representation of the dense vector.
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"""
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dims = tuple(2 * np.ones(nqubits, dtype=int))
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return qtn.tensor_1d.MatrixProductState.from_dense(init_state_sv, dims)
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def dense_vector_tn_qu(qasm: str, initial_state, mps_opts, backend="numpy"):
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"""Evaluate circuit in QASM format with Quimb.
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Args:
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qasm (str): QASM program.
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initial_state (list): Initial state in the dense vector form. If ``None`` the default ``|00...0>`` state is used.
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mps_opts (dict): Parameters to tune the gate_opts for mps settings in ``class quimb.tensor.circuit.CircuitMPS``.
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backend (str): Backend to perform the contraction with, e.g. ``numpy``, ``cupy``, ``jax``. Passed to ``opt_einsum``.
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Returns:
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list: Amplitudes of final state after the simulation of the circuit.
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"""
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if initial_state is not None:
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nqubits = int(np.log2(len(initial_state)))
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initial_state = init_state_tn(nqubits, initial_state)
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circ_cls = qtn.circuit.CircuitMPS if mps_opts else qtn.circuit.Circuit
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circ_quimb = circ_cls.from_openqasm2_str(
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qasm, psi0=initial_state, gate_opts=mps_opts
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)
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interim = circ_quimb.psi.full_simplify(seq="DRC")
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amplitudes = interim.to_dense(backend=backend)
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return amplitudes
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