JaunatisBlue
c4a82614b3
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67 lines
1.9 KiB
Python
67 lines
1.9 KiB
Python
import copy
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import os
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import config
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import numpy as np
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import pytest
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import qibo
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from qibo.models import QFT
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def create_init_state(nqubits):
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init_state = np.random.random(2**nqubits) + 1j * np.random.random(2**nqubits)
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init_state = init_state / np.sqrt((np.abs(init_state) ** 2).sum())
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return init_state
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def qibo_qft(nqubits, init_state, swaps):
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circ_qibo = QFT(nqubits, swaps)
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state_vec = circ_qibo(init_state).state(numpy=True)
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return circ_qibo, state_vec
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@pytest.mark.parametrize(
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"nqubits, tolerance, is_mps",
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[(1, 1e-6, True), (2, 1e-6, False), (5, 1e-3, True), (10, 1e-3, False)],
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)
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def test_eval(nqubits: int, tolerance: float, is_mps: bool):
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"""Evaluate circuit with Quimb backend.
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Args:
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nqubits (int): Total number of qubits in the system.
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tolerance (float): Maximum limit allowed for difference in results
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is_mps (bool): True if state is MPS and False for tensor network structure
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"""
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# hack quimb to use the correct number of processes
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# TODO: remove completely, or at least delegate to the backend
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# implementation
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os.environ["QUIMB_NUM_PROCS"] = str(os.cpu_count())
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import qibotn.eval_qu
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init_state = create_init_state(nqubits=nqubits)
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init_state_tn = copy.deepcopy(init_state)
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# Test qibo
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qibo.set_backend(backend=config.qibo.backend, platform=config.qibo.platform)
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qibo_circ, result_sv = qibo_qft(nqubits, init_state, swaps=True)
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# Convert to qasm for other backends
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qasm_circ = qibo_circ.to_qasm()
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# Test quimb
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if is_mps:
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gate_opt = {}
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gate_opt["method"] = "svd"
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gate_opt["cutoff"] = 1e-6
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gate_opt["cutoff_mode"] = "abs"
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else:
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gate_opt = None
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result_tn = qibotn.eval_qu.dense_vector_tn_qu(
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qasm_circ, init_state_tn, gate_opt, backend=config.quimb.backend
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).flatten()
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assert np.allclose(
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result_sv, result_tn, atol=tolerance
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), "Resulting dense vectors do not match"
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