32 lines
933 B
Python
32 lines
933 B
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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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 QASM with Quimb.
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backend (quimb): numpy, cupy, jax. Passed to ``opt_einsum``.
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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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