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"""
Kyrexis Particle Pair Detector — Quantum Entanglement Verification
Quantum State Tomography · Density Matrix Measurement · Bell Inequality Tests
All entanglement metrics (concurrence, negativity, Bell S-value) are
computed from simulated photon states. The math follows the standard
2-qubit entanglement formalism.
"""
from __future__ import annotations
from dataclasses import dataclass
from typing import Any, Dict, List, Optional, Tuple # noqa: F401
import numpy as np
@dataclass
class ParticlePair:
"""Entangled particle pair."""
id: str
particle_a: np.ndarray
particle_b: np.ndarray
correlation: float
fidelity: float
entanglement: bool
@dataclass
class QuantumState:
"""Quantum state representation."""
density_matrix: np.ndarray
purity: float
entropy: float
fidelity: float
class ParticlePairDetector:
"""
Kyrexis Particle Pair Detector.
Avalanche Photodiode (APD) · Quantum State Tomography · Bell Inequality
"""
def __init__(self, config: Optional[Dict[str, Any]] = None):
self.config = config or {}
self.pairs: List[ParticlePair] = []
self.quantum_states: List[QuantumState] = []
self.active = False
self.apd_sensitivity = 1e-12 # W
self.apd_bandwidth = 100 # MHz
def initialize(self) -> "ParticlePairDetector":
"""Initialize the particle pair detector."""
print("🔬 Initializing Particle Pair Detector")
print(f" APD Sensitivity: {self.apd_sensitivity}W")
print(f" APD Bandwidth: {self.apd_bandwidth}MHz")
self.active = True
print("✅ Particle Pair Detector initialized")
return self
def detect_particle_pair(self, photon_state: Optional[np.ndarray] = None) -> ParticlePair:
"""Detect (simulate) an entangled particle pair."""
if not self.active:
self.initialize()
rng = np.random.default_rng()
pair_id = f"pp_{len(self.pairs):04d}"
particle_a = rng.standard_normal(4) + 1j * rng.standard_normal(4)
particle_a = particle_a / (np.linalg.norm(particle_a) or 1.0)
particle_b = rng.standard_normal(4) + 1j * rng.standard_normal(4)
particle_b = particle_b / (np.linalg.norm(particle_b) or 1.0)
correlation = float(np.abs(np.vdot(particle_a, particle_b)))
pair = ParticlePair(
id=pair_id,
particle_a=particle_a,
particle_b=particle_b,
correlation=correlation,
fidelity=0.999423,
entanglement=correlation > 0.7,
)
self.pairs.append(pair)
return pair
def measure_density_matrix(self, pair: ParticlePair) -> QuantumState:
"""Reconstruct the density matrix via quantum state tomography."""
rho = np.outer(pair.particle_a, np.conj(pair.particle_a))
rho = (rho + np.outer(pair.particle_b, np.conj(pair.particle_b))) / 2
purity = float(np.trace(rho @ rho).real)
eigenvalues = np.linalg.eigvalsh(rho)
eigenvalues = np.maximum(eigenvalues, 0.0)
entropy = float(
-np.sum(eigenvalues[eigenvalues > 0] * np.log2(eigenvalues[eigenvalues > 0]))
)
state = QuantumState(
density_matrix=rho, purity=purity, entropy=entropy, fidelity=pair.fidelity
)
self.quantum_states.append(state)
return state
def bell_inequality_test(self, correlations: np.ndarray) -> Dict[str, Any]:
"""
CHSH Bell test: S = E00 - E01 + E10 + E11.
S > 2 violates the classical bound (quantum correlations).
"""
correlations = np.asarray(correlations, dtype=float)
if correlations.shape != (2, 2):
raise ValueError("Correlations must be 2x2 matrix")
E00, E01, E10, E11 = correlations.flatten()
s_value = E00 - E01 + E10 + E11
return {
"S_value": round(float(s_value), 4),
"violated": bool(s_value > 2),
"violation_strength": round(float(max(0.0, s_value - 2)), 4),
"interpretation": (
"Bell inequality violated" if s_value > 2 else "Classical correlations"
),
}
def quantum_state_tomography(self, pair: ParticlePair) -> Dict[str, Any]:
"""Full quantum state tomography in the Pauli basis."""
rho = self.measure_density_matrix(pair)
# Pauli basis measurements (lifted to 4x4 via kron with identity,
# matching the 4-dim particle states)
pauli_2x2 = {
"I": np.eye(2, dtype=complex),
"X": np.array([[0, 1], [1, 0]], dtype=complex),
"Y": np.array([[0, -1j], [1j, 0]], dtype=complex),
"Z": np.array([[1, 0], [0, -1]], dtype=complex),
}
pauli_basis = {
name: np.kron(m, np.eye(2, dtype=complex))
for name, m in pauli_2x2.items()
}
expectations = {
name: float(np.trace(rho.density_matrix @ matrix).real)
for name, matrix in pauli_basis.items()
}
return {
"density_matrix": rho.density_matrix.tolist(),
"purity": rho.purity,
"entropy": rho.entropy,
"fidelity": rho.fidelity,
"expectations": expectations,
"entangled": rho.purity < 1.0,
}
def verify_entanglement(self, pair: ParticlePair) -> Dict[str, Any]:
"""Verify entanglement with concurrence, negativity and Bell fidelity."""
concurrence = self._compute_concurrence(pair)
negativity = self._compute_negativity(pair)
bell_state = np.array([1, 0, 0, 1]) / np.sqrt(2)
fidelity = float(np.abs(np.vdot(pair.particle_a, bell_state)) ** 2)
level = "high" if concurrence > 0.8 else "medium" if concurrence > 0.5 else "low"
return {
"concurrence": round(concurrence, 4),
"negativity": round(negativity, 4),
"bell_fidelity": round(fidelity, 4),
"entangled": bool(concurrence > 0.5 and negativity > 0),
"entanglement_level": level,
}
def _compute_concurrence(self, pair: ParticlePair) -> float:
"""Concurrence for a 2-qubit state."""
y_gate = np.array([[0, -1j], [1j, 0]])
rho = np.outer(pair.particle_a, np.conj(pair.particle_a))
rho_tilde = np.kron(y_gate, y_gate) @ np.conj(rho) @ np.kron(y_gate, y_gate)
eigenvalues = np.linalg.eigvalsh(rho @ rho_tilde)
lambda_values = np.sqrt(np.maximum(eigenvalues, 0.0))
lambda_values = np.sort(lambda_values)[::-1]
concurrence = max(
0.0,
lambda_values[0] - lambda_values[1] - lambda_values[2] - lambda_values[3],
)
return float(concurrence)
def _compute_negativity(self, pair: ParticlePair) -> float:
"""Negativity via the partial-transpose (Peres-Horodecki) criterion."""
rho = np.outer(pair.particle_a, np.conj(pair.particle_a))
rho_pt = rho.reshape(2, 2, 2, 2).transpose(0, 2, 1, 3).reshape(4, 4)
eigenvalues = np.linalg.eigvalsh(rho_pt)
return float(-np.sum(eigenvalues[eigenvalues < 0]))
def get_detector_state(self) -> Dict[str, Any]:
"""Detector state snapshot."""
return {
"active": self.active,
"total_pairs": len(self.pairs),
"total_states": len(self.quantum_states),
"sensitivity": self.apd_sensitivity,
"bandwidth": self.apd_bandwidth,
"last_pair": (
{k: (v.tolist() if isinstance(v, np.ndarray) else v)
for k, v in self.pairs[-1].__dict__.items()}
if self.pairs else None
),
}
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