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f3e9e420a7
...
19e90b3d21
5 changed files with 73 additions and 119 deletions
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@ -43,7 +43,6 @@
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ppkgs.tqdm
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ppkgs.qiskit
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ppkgs.qiskit-aer
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ppkgs.matplotlib
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]))
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];
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};
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0
src/__init__.py
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0
src/__init__.py
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Binary file not shown.
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Before Width: | Height: | Size: 22 KiB |
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@ -3,42 +3,27 @@
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# "Genetic optimization of ansatz expressibility for enhanced variational quantum algorithm performance"
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import random
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import matplotlib.pyplot as plt
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from quantum_circuit import (
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Gate,
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GateType,
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QuantumCircuit,
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circ_from_layers,
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sample_random_generator,
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)
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from qas_flow import Stream
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from quantum_circuit import (Gate, GateType, QuantumCircuit, circ_from_layers,
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sample_random_generator, single_typ)
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DEPTH: int = 6
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QUBITS: int = 6
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GENERATIONS: int = 40
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GENERATION_SIZE: int = 60
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PARENT_AMOUNT: int = 10
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MUTATION_RATE: float = 0.1
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DEPTH = 20
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QUBITS = 5
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GENERATIONS = 20
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GENERATION_SIZE = 20
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PARENT_AMOUNT = 5
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MUTATION_RATE = 0.1
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gate_set: list[GateType] = [
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GateType.H,
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GateType.RX,
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GateType.RY,
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GateType.RZ,
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GateType.CRX,
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GateType.CX,
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]
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def plot_best_circuits(best_circuits: list[QuantumCircuit]) -> None:
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fig, ax = plt.subplots()
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ax.plot([-circ.expressibility for circ in best_circuits])
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fig.savefig("best_circuits.png")
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def main() -> None:
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seed_rng: random.Random = random.Random(1020381)
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def main():
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seed_rng = random.Random(1020381)
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initial_population: list[QuantumCircuit] = (
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Stream(sample_random_generator(random.Random(101020), QUBITS, DEPTH, gate_set))
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Stream(sample_random_generator(random.Random(101020), QUBITS, DEPTH))
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.apply(lambda circ: print(circ))
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.apply(
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lambda circ: circ.expressibility_estimate(
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@ -54,8 +39,6 @@ def main() -> None:
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main_rng = random.Random(2837175)
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best_circuits: list[QuantumCircuit] = []
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for generation in range(GENERATIONS):
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print(f"starting generation {generation}")
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population.sort(key=lambda qc: qc.expressibility, reverse=True)
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@ -72,38 +55,28 @@ def main() -> None:
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layer = child_layers[layer_idx]
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gate_idx = main_rng.randrange(len(layer))
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old_gate = child_layers[layer_idx][gate_idx]
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if old_gate.single():
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match old_gate.type:
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case GateType.H | GateType.RX | GateType.RY | GateType.RZ:
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child_layers[layer_idx][gate_idx] = Gate(
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main_rng.choice(
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[gate for gate in gate_set if single_typ(gate)]
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[GateType.H, GateType.RX, GateType.RY, GateType.RZ]
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),
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old_gate.qubits,
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old_gate.param_idx,
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)
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else:
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case GateType.CRX | GateType.CX:
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child_layers[layer_idx][gate_idx] = Gate(
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old_gate.typ,
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(old_gate.qubits[1], old_gate.qubits[0]),
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old_gate.type,
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tuple(old_gate.qubits[::-1]),
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old_gate.param_idx,
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)
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case _:
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print(f"unhandled gate: {old_gate}")
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child = circ_from_layers(child_layers, QUBITS)
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child.expressibility_estimate(2000, seed_rng.randint(1000, 1000000000))
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offspring.append(child)
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offspring.sort(key=lambda qc: qc.expressibility, reverse=True)
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if population[0].expressibility > offspring[0].expressibility:
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print(f"best parent > best child")
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best_circuits.append(population[0])
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else:
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print(f"best child > best parent")
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best_circuits.append(offspring[0])
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population = offspring
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plot_best_circuits(best_circuits)
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plt.show()
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if __name__ == "__main__":
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main()
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@ -1,12 +1,11 @@
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from dataclasses import dataclass
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import math
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import random
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from dataclasses import dataclass
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from enum import IntEnum
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from typing import override
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import numpy as np
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from qiskit import QuantumCircuit as QiskitCircuit
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from qiskit import transpile
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from enum import IntEnum
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from qiskit import QuantumCircuit as QiskitCircuit, transpile
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from qiskit.circuit import ParameterVector, ParameterVectorElement
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from qiskit_aer import AerSimulator
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@ -26,40 +25,21 @@ class GateType(IntEnum):
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CZ = 8
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CRX = 9
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H = 10
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I = 11
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def single_typ(typ: GateType) -> bool:
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match typ:
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case GateType.I | GateType.H | GateType.RX | GateType.RY | GateType.RZ:
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return True
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case (
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GateType.RXX
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| GateType.RYY
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| GateType.RZZ
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| GateType.CX
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| GateType.CZ
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| GateType.CRX
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):
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return False
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@dataclass(frozen=True)
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class Gate:
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typ: GateType
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type: GateType
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qubits: int | tuple[int, int]
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param_idx: int
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def to_json(self):
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return {
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"type": int(self.typ),
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"type": int(self.type),
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"qubits": self.qubits,
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"param_idx": self.param_idx,
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}
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def single(self) -> bool:
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return single_typ(self.typ)
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def haar_fidelity_pdf(F: np.ndarray, d: int) -> np.ndarray:
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# p(F) = (d-1) * (1-F)^(d-2), for F in [0,1]
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@ -91,7 +71,7 @@ class QuantumCircuit:
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path_counts = [1 for _ in range(self.qubits)]
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for layer in self.gates:
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for gate in layer:
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if gate.typ <= 3 or isinstance(gate.qubits, int):
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if gate.type <= 3 or isinstance(gate.qubits, int):
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continue
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(q1, q2) = gate.qubits
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# same logic as your existing file
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@ -119,35 +99,33 @@ class QuantumCircuit:
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for layer in self.gates:
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for gate in layer:
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if gate.typ == GateType.RX:
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if gate.type == GateType.RX:
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theta = thetas[gate.param_idx]
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qc.rx(theta, gate.qubits)
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elif gate.typ == GateType.RY:
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elif gate.type == GateType.RY:
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theta = thetas[gate.param_idx]
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qc.ry(theta, gate.qubits)
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elif gate.typ == GateType.RZ:
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elif gate.type == GateType.RZ:
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theta = thetas[gate.param_idx]
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qc.rz(theta, gate.qubits)
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elif gate.typ == GateType.H:
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elif gate.type == GateType.H:
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qc.h(gate.qubits)
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elif gate.typ == GateType.I:
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qc.id(gate.qubits)
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elif gate.typ == GateType.RXX:
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elif gate.type == GateType.RXX:
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theta = thetas[gate.param_idx]
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qc.rxx(theta, *gate.qubits)
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elif gate.typ == GateType.RYY:
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elif gate.type == GateType.RYY:
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theta = thetas[gate.param_idx]
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qc.ryy(theta, *gate.qubits)
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elif gate.typ == GateType.RZZ:
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elif gate.type == GateType.RZZ:
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theta = thetas[gate.param_idx]
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qc.rzz(theta, *gate.qubits)
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elif gate.typ == GateType.CX:
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elif gate.type == GateType.CX:
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qc.cx(*gate.qubits)
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elif gate.typ == GateType.CRX:
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elif gate.type == GateType.CRX:
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theta = thetas[gate.param_idx]
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qc.crx(theta, *gate.qubits)
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else:
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raise ValueError(f"Unknown gate type: {gate.typ}")
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raise ValueError(f"Unknown gate type: {gate.type}")
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return qc, thetas
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def to_qiskit_for_expressibility(self) -> tuple[QiskitCircuit, ParameterVector]:
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@ -227,7 +205,7 @@ class QuantumCircuit:
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idx = 0
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for gate in layer:
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match gate.typ:
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match gate.type:
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case GateType.RX:
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strs[gate.qubits] = strs[gate.qubits][:-2] + "RX"
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case GateType.RY:
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@ -333,23 +311,23 @@ def circ_from_layers(layers: list[list[Gate]], qubits: int) -> QuantumCircuit:
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for layer in layers:
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new_layer = []
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for gate in layer:
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match gate.typ:
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match gate.type:
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case GateType.H:
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new_layer.append(Gate(gate.typ, gate.qubits, params))
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new_layer.append(Gate(gate.type, gate.qubits, params))
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total_single += 1
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case GateType.RX | GateType.RY | GateType.RZ:
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new_layer.append(Gate(gate.typ, gate.qubits, params))
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new_layer.append(Gate(gate.type, gate.qubits, params))
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params += 1
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total_single += 1
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case GateType.RXX | GateType.RYY | GateType.RZZ:
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new_layer.append(Gate(gate.typ, gate.qubits, params))
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new_layer.append(Gate(gate.type, gate.qubits, params))
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params += 1
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total_double += 1
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case GateType.CX | GateType.CZ:
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new_layer.append(Gate(gate.typ, gate.qubits, params))
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new_layer.append(Gate(gate.type, gate.qubits, params))
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total_double += 1
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case GateType.CRX:
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new_layer.append(Gate(gate.typ, gate.qubits, params))
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new_layer.append(Gate(gate.type, gate.qubits, params))
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params += 1
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total_double += 1
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gates.append(new_layer)
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@ -357,7 +335,7 @@ def circ_from_layers(layers: list[list[Gate]], qubits: int) -> QuantumCircuit:
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def sample_circuit_random(
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rng: random.Random, qubits: int, depth: int, gate_types: list[GateType]
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rng: random.Random, qubits: int, depth: int
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) -> QuantumCircuit:
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params = 0
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total_single = 0
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@ -370,10 +348,16 @@ def sample_circuit_random(
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for loc in range(qubits):
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if loc in used_qubits:
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continue
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if loc + 1 < qubits:
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gate_type = rng.choice(gate_types)
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else:
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gate_type = rng.choice([typ for typ in gate_types if single_typ(typ)])
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gate_type = rng.choice(
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[
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GateType.RX,
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GateType.RY,
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GateType.RZ,
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GateType.CX,
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GateType.CRX,
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GateType.H,
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]
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)
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match gate_type:
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case GateType.H:
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layer.append(Gate(gate_type, loc, params))
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@ -384,13 +368,13 @@ def sample_circuit_random(
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params += 1
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total_single += 1
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used_qubits.add(loc)
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case GateType.RXX | GateType.RYY | GateType.RZZ:
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case GateType.RXX | GateType.RYY | GateType.RZZ if loc + 1 < qubits:
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layer.append(Gate(gate_type, (loc, loc + 1), params))
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params += 1
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total_double += 1
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used_qubits.add(loc)
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used_qubits.add(loc + 1)
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case GateType.CX | GateType.CZ:
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case GateType.CX | GateType.CZ if loc + 1 < qubits:
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layer.append(
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Gate(
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gate_type,
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@ -401,7 +385,7 @@ def sample_circuit_random(
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total_double += 1
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used_qubits.add(loc)
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used_qubits.add(loc + 1)
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case GateType.CRX:
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case GateType.CRX if loc + 1 < qubits:
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layer.append(
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Gate(
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gate_type,
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@ -420,8 +404,6 @@ def sample_circuit_random(
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return QuantumCircuit(qubits, gates, total_single, total_double, params)
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def sample_random_generator(
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rng: random.Random, qubits: int, depth: int, gates: list[GateType]
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):
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def sample_random_generator(rng: random.Random, qubits: int, depth: int):
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while True:
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yield sample_circuit_random(rng, qubits, depth, gates)
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yield sample_circuit_random(rng, qubits, depth)
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