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Trim trivial qubits from circuit and Hamiltonian (#302)
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Remove qubits that are in a deterministic state in quantum circuits, and simplify qubit Hamiltonian accordingly, in order to reduce resource requirements while computing expectation values.

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Co-authored-by: Valentin Senicourt <41597680+ValentinS4t1qbit@users.noreply.github.com>
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elloyd-1qbit and ValentinS4t1qbit authored May 17, 2023
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2 changes: 1 addition & 1 deletion tangelo/linq/circuit.py
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Expand Up @@ -245,7 +245,7 @@ def trim_qubits(self):
"""Trim unnecessary qubits and update indices with the lowest values possible.
"""
qubits_in_use = set().union(*self.get_entangled_indices())
mapping = {ind: i for i, ind in enumerate(qubits_in_use)}
mapping = {ind: i for i, ind in enumerate(sorted(list(qubits_in_use)))}
for g in self._gates:
g.target = [mapping[ind] for ind in g.target]
if g.control:
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92 changes: 92 additions & 0 deletions tangelo/toolboxes/operators/tests/test_trim_trivial_qubits.py
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# Copyright 2023 Good Chemistry Company.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import os
import unittest

import numpy as np
from openfermion.linalg import qubit_operator_sparse
from openfermion.utils import load_operator

from tangelo.linq import Gate, Circuit, get_backend
from tangelo.toolboxes.operators import QubitOperator
from tangelo.toolboxes.ansatz_generator.ansatz_utils import exp_pauliword_to_gates
from tangelo.toolboxes.operators.trim_trivial_qubits import trim_trivial_qubits, trim_trivial_operator, trim_trivial_circuit, is_bitflip_gate


pwd_this_test = os.path.dirname(os.path.abspath(__file__))

qb_ham = load_operator("H4_JW_spinupfirst.data", data_directory=pwd_this_test+"/data", plain_text=True)

# Generate reference and test circuits using single qcc generator
ref_qcc_op = 0.2299941483397896 * 0.5 * QubitOperator("Y0 X1 X2 X3")
qcc_op = 0.2299941483397896 * 0.5 * QubitOperator("Y1 X3 X5 X7")

ref_mf_gates = [Gate("RX", 0, parameter=np.pi), Gate("X", 2)]

mf_gates = [
Gate("RZ", 0, parameter=np.pi/2), Gate("RX", 0, parameter=3.14159),
Gate("RX", 1, parameter=np.pi), Gate("RZ", 2, parameter=np.pi),
Gate("X", 4), Gate("X", 5), Gate("Z", 6),
Gate("RZ", 6, parameter=np.pi), Gate("RX", 8, parameter=-3*np.pi),
Gate("X", 8), Gate("RZ", 9, parameter=np.pi), Gate("Z", 9)
]

ref_pauli_words_gates = sum((exp_pauliword_to_gates(pword, coef) for pword, coef in ref_qcc_op.terms.items()), start=[])
pauli_words_gates = sum((exp_pauliword_to_gates(pword, coef) for pword, coef in qcc_op.terms.items()), start=[])

ref_circ = Circuit(ref_mf_gates + ref_pauli_words_gates)
circ = Circuit(mf_gates + pauli_words_gates)

# Reference energy for H4 molecule with single QCC generator
ref_value = -1.8039875664891176

# Reference indices and states to be removed from system
ref_trim_states = {0: 1, 2: 0, 4: 1, 6: 0, 8: 0, 9: 0}

# Reference for which mf_gates are bitflip gates
ref_bool = [False, True, True, False, True, True, False, False, True, True, False, False]

sim = get_backend()


class TrimTrivialQubits(unittest.TestCase):
def test_trim_trivial_operator(self):
""" Test if trimming operator returns the correct eigenvalue """

trimmed_operator = trim_trivial_operator(qb_ham, trim_states={key: ref_trim_states[key] for key in [0, 2, 4, 6]}, reindex=False)
self.assertAlmostEqual(np.min(np.linalg.eigvalsh(qubit_operator_sparse(trimmed_operator).todense())), ref_value, places=5)

def test_is_bitflip_gate(self):
""" Test if bitflip gate function correctly identifies bitflip gates """
self.assertEqual(ref_bool, [is_bitflip_gate(g) for g in mf_gates])

def test_trim_trivial_circuit(self):
""" Test if circuit trimming returns the correct circuit, states, and indices """

trimmed_circuit, trim_states = trim_trivial_circuit(circ)
self.assertEqual(ref_circ._gates, trimmed_circuit._gates)
self.assertEqual(ref_trim_states, trim_states)

def test_trim_trivial_qubits(self):
""" Test if trim trivial qubit function produces correct and compatible circuits and operators """

trimmed_operator, trimmed_circuit = trim_trivial_qubits(qb_ham, circ)
self.assertAlmostEqual(np.min(np.linalg.eigvalsh(qubit_operator_sparse(trimmed_operator).todense())), ref_value, places=5)
self.assertEqual(ref_circ._gates, trimmed_circuit._gates)
self.assertAlmostEqual(sim.get_expectation_value(trimmed_operator, trimmed_circuit), ref_value, places=5)


if __name__ == "__main__":
unittest.main()
171 changes: 171 additions & 0 deletions tangelo/toolboxes/operators/trim_trivial_qubits.py
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# Copyright 2023 Good Chemistry Company.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import numpy as np

from tangelo.toolboxes.operators import QubitOperator, count_qubits
from tangelo.linq import Circuit
from tangelo.linq.helpers.circuits import pauli_string_to_of, pauli_of_to_string


def trim_trivial_operator(qu_op, trim_states, n_qubits=None, reindex=True):
"""
Calculate expectation values of a QubitOperator acting on qubits in a
trivial |0> or |1> state. Return a trimmed QubitOperator with updated coefficients
Args:
qu_op (QubitOperator): Operator to trim
trim_states (dict): Dictionary mapping qubit indices to states to trim, e.g. {1: 0, 3: 1}
n_qubits (int): Optional, number of qubits in full system
reindex (bool): Optional, if True, remaining qubits will be reindexed
Returns:
QubitOperator : trimmed QubitOperator with updated coefficients
"""

qu_op_trim = QubitOperator()
n_qubits = count_qubits(qu_op) if n_qubits is None else n_qubits

# Calculate expectation values of trivial qubits, update coefficients
for op, coeff in qu_op.terms.items():
term = pauli_of_to_string(op, n_qubits)
c = np.ones(len(trim_states))
new_term = term
for i, qubit in enumerate(trim_states.keys()):
if term[qubit] in {'X', 'Y'}:
c[i] = 0
break
elif (term[qubit], trim_states[qubit]) == ('Z', 1):
c[i] = -1

new_term = new_term[:qubit - i] + new_term[qubit - i + 1:] if reindex else new_term[:qubit] + 'I' + new_term[qubit + 1:]

if 0 in c:
continue

qu_op_trim += np.prod(c) * coeff * QubitOperator(pauli_string_to_of(new_term))
return qu_op_trim


def is_bitflip_gate(gate, atol=1e-5):
"""
Check if a gate is a bitflip gate.
A gate is a bitflip gate if it satisfies one of the following conditions:
1. The gate name is either X, Y.
2. The gate name is RX or RY, and has a parameter that is an odd multiple of pi.
Args:
gate (Gate): The gate to check.
atol (float): Optional, the absolute tolerance for gate parameter
Returns:
bool: True if the gate is a single qubit bitflip gate, False otherwise.
"""
if gate is None:
return False

if gate.name in {"X", "Y"}:
return True
elif gate.name in {"RX", "RY"}:
try:
parameter_float = float(gate.parameter)
except (TypeError, ValueError):
return False

# Check if parameter is close to an odd multiple of pi
return abs(parameter_float % (np.pi * 2) - np.pi) <= atol
else:
return False


def trim_trivial_circuit(circuit):
"""
Splits Circuit into entangled and unentangled components.
Returns entangled Circuit, and the indices and states of unentangled qubits
Args:
circuit (Circuit): circuit to be trimmed
Returns:
Circuit : Trimmed, entangled circuit
dict : dictionary mapping trimmed qubit indices to their states (0 or 1)
"""
# Split circuit and get relevant indices
circs = circuit.split()
e_indices = circuit.get_entangled_indices()

# Find qubits with no gates applied to them, store qubit index and state |0>
trim_states = {}
for qubit_idx in set(range(circuit.width)) - set(circuit._qubit_indices):
trim_states[qubit_idx] = 0

circuit_new = Circuit()
# Go through circuit components, trim if trivial, otherwise append to new circuit
for i, circ in enumerate(circs):
if circ.width != 1 or circ.size not in (1, 2):
circuit_new += circ
continue

# Calculate state of single qubit clifford circuits, ideally this would be done with a clifford simulator
# for now only look at first two gate combinations typical of the QMF state in QCC methods
gate0, gate1 = circ._gates[:2] + [None] * (2 - circ.size)
gate_0_is_bitflip = is_bitflip_gate(gate0)
gate_1_is_bitflip = is_bitflip_gate(gate1)

if circ.size == 1:
if gate0.name in {"RZ", "Z"}:
qubit_idx = e_indices[i].pop()
trim_states[qubit_idx] = 0
elif gate0.name in {"X", "RX"} and gate_0_is_bitflip:
qubit_idx = e_indices[i].pop()
trim_states[qubit_idx] = 1
else:
circuit_new += circ
elif circ.size == 2:
if gate1.name in {"Z", "RZ"}:
if gate0.name in {"RZ", "Z"}:
qubit_idx = e_indices[i].pop()
trim_states[qubit_idx] = 0
else:
circuit_new += circ
elif gate1.name in {"X", "RX"} and gate_1_is_bitflip:
if gate0.name in {"RX", "X"} and gate_0_is_bitflip:
qubit_idx = e_indices[i].pop()
trim_states[qubit_idx] = 0
elif gate0.name in {"Z", "RZ"}:
qubit_idx = e_indices[i].pop()
trim_states[qubit_idx] = 1
else:
circuit_new += circ
else:
circuit_new += circ
return circuit_new, trim_states


def trim_trivial_qubits(operator, circuit):
"""
Trim circuit and operator based on expectation values calculated from
trivial components of the circuit.
Args:
operator (QubitOperator): Operator to trim
circuit (Circuit): circuit to be trimmed
Returns:
QubitOperator : Trimmed qubit operator
Circuit : Trimmed circuit
"""
trimmed_circuit, trim_states = trim_trivial_circuit(circuit)
trimmed_operator = trim_trivial_operator(operator, trim_states, circuit.width, reindex=True)

return trimmed_operator, trimmed_circuit

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