51 lines
1.3 KiB
Python
51 lines
1.3 KiB
Python
import numpy as np
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import jax
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from qibo.backends import construct_backend
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from qibo import Circuit, gates, hamiltonians
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from qibo.symbols import Z, X, Y
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# construct qibotn backend
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quimb_backend = construct_backend(backend="qibotn", platform="quimb")
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quimb_backend.setup_backend_specifics(
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qimb_backend="jax",
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optimizer='auto-hq'
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)
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quimb_backend.configure_tn_simulation(
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max_bond_dimension=10
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)
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# define Hamiltonian
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form = 0.5 * Z(0) * Z(1) +- 1.5 * X(0) * Z(2) + Z(3)
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hamiltonian = hamiltonians.SymbolicHamiltonian(form)
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# define circuit
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def build_circuit(nqubits, nlayers):
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"""Construct a Qibo parametric quantum circuit."""
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circ = Circuit(nqubits)
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for _ in range(nlayers):
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for q in range(nqubits):
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circ.add(gates.RY(q=q, theta=0.))
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circ.add(gates.RZ(q=q, theta=0.))
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[circ.add(gates.CZ(q % nqubits, (q + 1) % nqubits)) for q in range(nqubits)]
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circ.add(gates.M(*range(nqubits)))
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return circ
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nqubits = 4
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circuit = build_circuit(nqubits=nqubits, nlayers=3)
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quimb_circuit = quimb_backend._qibo_circuit_to_quimb(circuit)
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def f(params):
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circuit.set_parameters(params)
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return quimb_backend.expectation(
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circuit=circuit,
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observable=hamiltonian,
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)
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parameters = np.random.uniform(-np.pi, np.pi, size=len(circuit.get_parameters()))
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print(jax.value_and_grad(f)(parameters))
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