use scirs2_core::ndarray::{Array1, Array2, Array3, ArrayView2};
use scirs2_core::numeric::Complex;
use scirs2_core::numeric::{Float, FromPrimitive};
use std::collections::{HashMap, VecDeque};
use super::config::{QuantumAIConsciousnessConfig, QuantumAIConsciousnessState};
use crate::error::{NdimageError, NdimageResult};
#[derive(Debug, Clone)]
pub struct QuantumEntanglementNetwork {
pub channels: Vec<QuantumChannel>,
pub network_coherence: Array2<Complex<f64>>,
pub entanglement_matrix: Array2<f64>,
pub synchronization_level: f64,
pub active_pairs: Vec<(usize, usize)>,
}
impl QuantumEntanglementNetwork {
pub fn new() -> Self {
Self {
channels: Vec::new(),
network_coherence: Array2::zeros((10, 10)),
entanglement_matrix: Array2::zeros((10, 10)),
synchronization_level: 0.0,
active_pairs: Vec::new(),
}
}
pub fn initialize(&mut self, config: &QuantumAIConsciousnessConfig) -> NdimageResult<()> {
let network_size = config.consciousness_depth;
self.network_coherence = Array2::zeros((network_size, network_size));
self.entanglement_matrix = Array2::zeros((network_size, network_size));
for i in 0..network_size {
for j in i + 1..network_size {
let channel = QuantumChannel {
id: format!("channel_{}_{}", i, j),
source_node: i,
target_node: j,
entanglement_strength: config.quantum_entanglement_strength,
coherence_time: config.quantum_coherence_time,
quantum_state: Array1::zeros(4), decoherence_rate: 0.01,
measurement_basis: Array2::eye(2),
};
self.channels.push(channel);
}
}
for channel in &self.channels {
self.entanglement_matrix[[channel.source_node, channel.target_node]] =
channel.entanglement_strength;
self.entanglement_matrix[[channel.target_node, channel.source_node]] =
channel.entanglement_strength;
}
Ok(())
}
pub fn update_entanglement(&mut self, time_step: f64) -> NdimageResult<()> {
for i in 0..self.channels.len() {
self.channels[i].entanglement_strength *=
(1.0 - self.channels[i].decoherence_rate * time_step);
self.evolve_quantum_state_by_index(i, time_step)?;
}
self.synchronization_level = self.calculate_network_synchronization()?;
Ok(())
}
fn evolve_quantum_state(
&mut self,
channel: &mut QuantumChannel,
time_step: f64,
) -> NdimageResult<()> {
let hamiltonian = self.construct_hamiltonian(channel)?;
let evolution_operator = self.compute_evolution_operator(&hamiltonian, time_step)?;
for i in 0..channel.quantum_state.len() {
let old_amplitude = channel.quantum_state[i];
channel.quantum_state[i] = old_amplitude * evolution_operator[(i, i % 2)];
}
let norm = channel
.quantum_state
.iter()
.map(|x| x * x)
.sum::<f64>()
.sqrt();
if norm > 1e-10 {
for amplitude in channel.quantum_state.iter_mut() {
*amplitude /= norm;
}
}
Ok(())
}
fn evolve_quantum_state_by_index(
&mut self,
channel_index: usize,
time_step: f64,
) -> NdimageResult<()> {
let hamiltonian = self.construct_hamiltonian(&self.channels[channel_index])?;
let evolution_operator = self.compute_evolution_operator(&hamiltonian, time_step)?;
for i in 0..self.channels[channel_index].quantum_state.len() {
let old_amplitude = self.channels[channel_index].quantum_state[i];
self.channels[channel_index].quantum_state[i] =
old_amplitude * evolution_operator[(i, i % 2)];
}
let norm = self.channels[channel_index]
.quantum_state
.iter()
.map(|c| c * c)
.sum::<f64>()
.sqrt();
if norm > 0.0 {
for amplitude in &mut self.channels[channel_index].quantum_state {
*amplitude /= norm;
}
}
Ok(())
}
fn construct_hamiltonian(&self, channel: &QuantumChannel) -> NdimageResult<Array2<f64>> {
let mut hamiltonian = Array2::zeros((4, 4));
hamiltonian[[0, 0]] = channel.entanglement_strength;
hamiltonian[[1, 1]] = -channel.entanglement_strength;
hamiltonian[[2, 2]] = -channel.entanglement_strength;
hamiltonian[[3, 3]] = channel.entanglement_strength;
hamiltonian[[0, 3]] = 0.1 * channel.entanglement_strength;
hamiltonian[[3, 0]] = 0.1 * channel.entanglement_strength;
Ok(hamiltonian)
}
fn compute_evolution_operator(
&self,
hamiltonian: &Array2<f64>,
time_step: f64,
) -> NdimageResult<Array2<f64>> {
let mut evolution = Array2::eye(hamiltonian.nrows());
for i in 0..hamiltonian.nrows() {
for j in 0..hamiltonian.ncols() {
if i == j {
evolution[[i, j]] = (hamiltonian[[i, j]] * time_step).cos();
} else {
evolution[[i, j]] = -(hamiltonian[[i, j]] * time_step).sin();
}
}
}
Ok(evolution)
}
fn calculate_network_synchronization(&self) -> NdimageResult<f64> {
if self.channels.is_empty() {
return Ok(0.0);
}
let mut total_sync = 0.0;
let mut count = 0;
for i in 0..self.channels.len() {
for j in i + 1..self.channels.len() {
let sync =
self.calculate_channel_synchronization(&self.channels[i], &self.channels[j])?;
total_sync += sync;
count += 1;
}
}
Ok(if count > 0 {
total_sync / count as f64
} else {
0.0
})
}
fn calculate_channel_synchronization(
&self,
channel1: &QuantumChannel,
channel2: &QuantumChannel,
) -> NdimageResult<f64> {
let mut overlap = 0.0;
for i in 0..channel1
.quantum_state
.len()
.min(channel2.quantum_state.len())
{
overlap += channel1.quantum_state[i] * channel2.quantum_state[i];
}
Ok(overlap.abs())
}
pub fn measure_entanglement(&self, channel_id: &str) -> NdimageResult<f64> {
let channel = self
.channels
.iter()
.find(|c| c.id == channel_id)
.ok_or_else(|| {
NdimageError::InvalidInput(format!("Channel {} not found", channel_id))
})?;
let rho = self.construct_density_matrix(&channel.quantum_state)?;
let concurrence = self.calculate_concurrence(&rho)?;
Ok(concurrence)
}
fn construct_density_matrix(&self, state: &Array1<f64>) -> NdimageResult<Array2<f64>> {
let n = state.len();
let mut rho = Array2::zeros((n, n));
for i in 0..n {
for j in 0..n {
rho[[i, j]] = state[i] * state[j];
}
}
Ok(rho)
}
fn calculate_concurrence(&self, rho: &Array2<f64>) -> NdimageResult<f64> {
let trace = rho.diag().sum();
let purity = rho.iter().map(|x| x * x).sum::<f64>();
let concurrence = 2.0 * (0.5 - purity / (trace * trace)).max(0.0).sqrt();
Ok(concurrence)
}
}
#[derive(Debug, Clone)]
pub struct QuantumChannel {
pub id: String,
pub source_node: usize,
pub target_node: usize,
pub entanglement_strength: f64,
pub coherence_time: f64,
pub quantum_state: Array1<f64>,
pub decoherence_rate: f64,
pub measurement_basis: Array2<f64>,
}
impl QuantumChannel {
pub fn new(id: String, source: usize, target: usize, strength: f64) -> Self {
Self {
id,
source_node: source,
target_node: target,
entanglement_strength: strength,
coherence_time: 100.0,
quantum_state: Array1::from_vec(vec![
1.0 / 2.0_f64.sqrt(),
0.0,
0.0,
1.0 / 2.0_f64.sqrt(),
]), decoherence_rate: 0.01,
measurement_basis: Array2::eye(2),
}
}
pub fn apply_gate(&mut self, gate: &Array2<f64>, qubit_index: usize) -> NdimageResult<()> {
if gate.nrows() != 2 || gate.ncols() != 2 {
return Err(NdimageError::InvalidInput(
"Gate must be 2x2 matrix".to_string(),
));
}
if qubit_index >= 2 {
return Err(NdimageError::InvalidInput(
"Qubit index must be 0 or 1".to_string(),
));
}
self.apply_single_qubit_gate(gate, qubit_index)?;
Ok(())
}
fn apply_single_qubit_gate(
&mut self,
gate: &Array2<f64>,
qubit_index: usize,
) -> NdimageResult<()> {
let mut new_state = Array1::zeros(4);
if qubit_index == 0 {
new_state[0] =
gate[[0, 0]] * self.quantum_state[0] + gate[[0, 1]] * self.quantum_state[2];
new_state[1] =
gate[[0, 0]] * self.quantum_state[1] + gate[[0, 1]] * self.quantum_state[3];
new_state[2] =
gate[[1, 0]] * self.quantum_state[0] + gate[[1, 1]] * self.quantum_state[2];
new_state[3] =
gate[[1, 0]] * self.quantum_state[1] + gate[[1, 1]] * self.quantum_state[3];
} else {
new_state[0] =
gate[[0, 0]] * self.quantum_state[0] + gate[[0, 1]] * self.quantum_state[1];
new_state[1] =
gate[[1, 0]] * self.quantum_state[0] + gate[[1, 1]] * self.quantum_state[1];
new_state[2] =
gate[[0, 0]] * self.quantum_state[2] + gate[[0, 1]] * self.quantum_state[3];
new_state[3] =
gate[[1, 0]] * self.quantum_state[2] + gate[[1, 1]] * self.quantum_state[3];
}
self.quantum_state = new_state;
Ok(())
}
pub fn measure(&mut self) -> NdimageResult<(usize, f64)> {
let probabilities = self.quantum_state.iter().map(|x| x * x).collect::<Vec<_>>();
let mut max_prob = 0.0;
let mut outcome = 0;
for (i, &prob) in probabilities.iter().enumerate() {
if prob > max_prob {
max_prob = prob;
outcome = i;
}
}
self.quantum_state = Array1::zeros(4);
self.quantum_state[outcome] = 1.0;
Ok((outcome, max_prob))
}
}
#[derive(Debug, Clone)]
pub struct CoherenceMechanism {
pub preservation_strategies: Vec<String>,
pub coherence_level: f64,
pub mitigation_techniques: HashMap<String, f64>,
pub noise_model: Array2<f64>,
}
impl CoherenceMechanism {
pub fn new() -> Self {
let mut mitigation_techniques = HashMap::new();
mitigation_techniques.insert("dynamical_decoupling".to_string(), 0.8);
mitigation_techniques.insert("error_correction".to_string(), 0.9);
mitigation_techniques.insert("decoherence_free_subspace".to_string(), 0.7);
Self {
preservation_strategies: vec![
"Active_Feedback".to_string(),
"Passive_Protection".to_string(),
"Quantum_Error_Correction".to_string(),
],
coherence_level: 0.8,
mitigation_techniques,
noise_model: Array2::eye(4) * 0.01, }
}
pub fn preserve_coherence(
&mut self,
channel: &mut QuantumChannel,
time_step: f64,
) -> NdimageResult<()> {
self.apply_dynamical_decoupling(channel, time_step)?;
if self.coherence_level < 0.5 {
self.apply_quantum_error_correction(channel)?;
}
self.update_coherence_level(channel);
Ok(())
}
fn apply_dynamical_decoupling(
&self,
channel: &mut QuantumChannel,
time_step: f64,
) -> NdimageResult<()> {
let pulse_interval = time_step / 4.0;
let pauli_x =
Array2::from_shape_vec((2, 2), vec![0.0, 1.0, 1.0, 0.0]).expect("Operation failed");
channel.apply_gate(&pauli_x, 0)?;
channel.apply_gate(&pauli_x, 1)?;
Ok(())
}
fn apply_quantum_error_correction(&self, channel: &mut QuantumChannel) -> NdimageResult<()> {
let bell_states = vec![
Array1::from_vec(vec![1.0 / 2.0_f64.sqrt(), 0.0, 0.0, 1.0 / 2.0_f64.sqrt()]),
Array1::from_vec(vec![1.0 / 2.0_f64.sqrt(), 0.0, 0.0, -1.0 / 2.0_f64.sqrt()]),
Array1::from_vec(vec![0.0, 1.0 / 2.0_f64.sqrt(), 1.0 / 2.0_f64.sqrt(), 0.0]),
Array1::from_vec(vec![0.0, 1.0 / 2.0_f64.sqrt(), -1.0 / 2.0_f64.sqrt(), 0.0]),
];
let mut max_overlap = 0.0;
let mut best_state = 0;
for (i, bell_state) in bell_states.iter().enumerate() {
let mut overlap = 0.0;
for j in 0..4 {
overlap += channel.quantum_state[j] * bell_state[j];
}
overlap = overlap.abs();
if overlap > max_overlap {
max_overlap = overlap;
best_state = i;
}
}
channel.quantum_state = bell_states[best_state].clone();
Ok(())
}
fn update_coherence_level(&mut self, channel: &QuantumChannel) {
let mut purity = 0.0;
for amplitude in &channel.quantum_state {
purity += amplitude.powi(4);
}
self.coherence_level = purity.max(0.0).min(1.0);
}
pub fn get_coherence_metrics(&self) -> HashMap<String, f64> {
let mut metrics = HashMap::new();
metrics.insert("coherence_level".to_string(), self.coherence_level);
metrics.insert(
"preservation_efficiency".to_string(),
self.mitigation_techniques.values().sum::<f64>()
/ self.mitigation_techniques.len() as f64,
);
metrics.insert(
"noise_strength".to_string(),
self.noise_model.diag().sum() / self.noise_model.nrows() as f64,
);
metrics
}
}
#[derive(Debug, Clone)]
pub struct ConsciousnessSynchronizationState {
pub synchronization_level: f64,
pub phase_coherence: Array1<f64>,
pub sync_patterns: Vec<SynchronizationPattern>,
pub coherence_mechanism: CoherenceMechanism,
}
impl ConsciousnessSynchronizationState {
pub fn new() -> Self {
Self {
synchronization_level: 0.0,
phase_coherence: Array1::zeros(10),
sync_patterns: Vec::new(),
coherence_mechanism: CoherenceMechanism::new(),
}
}
pub fn update_synchronization<T>(
&mut self,
image: &ArrayView2<T>,
quantum_network: &QuantumEntanglementNetwork,
config: &QuantumAIConsciousnessConfig,
) -> NdimageResult<()>
where
T: Float + FromPrimitive + Copy + Send + Sync,
{
self.synchronization_level = quantum_network.synchronization_level;
self.update_phase_coherence(quantum_network)?;
self.detect_sync_patterns(quantum_network)?;
self.preserve_global_coherence(config)?;
Ok(())
}
fn update_phase_coherence(
&mut self,
network: &QuantumEntanglementNetwork,
) -> NdimageResult<()> {
let num_channels = network.channels.len().max(1);
self.phase_coherence = Array1::zeros(num_channels);
for (i, channel) in network.channels.iter().enumerate() {
let mut phase_sum = 0.0;
for j in 0..channel.quantum_state.len() {
phase_sum += channel.quantum_state[j];
}
let coherence_len = self.phase_coherence.len();
self.phase_coherence[i % coherence_len] = phase_sum.abs();
}
Ok(())
}
fn detect_sync_patterns(&mut self, network: &QuantumEntanglementNetwork) -> NdimageResult<()> {
self.sync_patterns.clear();
for window in network.channels.windows(3) {
if window.len() == 3 {
let avg_strength =
window.iter().map(|c| c.entanglement_strength).sum::<f64>() / 3.0;
if avg_strength > 0.7 {
let pattern = SynchronizationPattern {
pattern_type: "high_coherence_cluster".to_string(),
strength: avg_strength,
channels: window.iter().map(|c| c.id.clone()).collect(),
stability: avg_strength * 0.8,
};
self.sync_patterns.push(pattern);
}
}
}
Ok(())
}
fn preserve_global_coherence(
&mut self,
config: &QuantumAIConsciousnessConfig,
) -> NdimageResult<()> {
let preservation_efficiency = self
.coherence_mechanism
.mitigation_techniques
.get("error_correction")
.copied()
.unwrap_or(0.8);
self.synchronization_level = (self.synchronization_level * preservation_efficiency)
.max(0.0)
.min(1.0);
Ok(())
}
}
#[derive(Debug, Clone)]
pub struct SynchronizationPattern {
pub pattern_type: String,
pub strength: f64,
pub channels: Vec<String>,
pub stability: f64,
}
pub fn initialize_quantum_core(
config: &QuantumAIConsciousnessConfig,
) -> NdimageResult<(
QuantumEntanglementNetwork,
ConsciousnessSynchronizationState,
)> {
let mut quantum_network = QuantumEntanglementNetwork::new();
quantum_network.initialize(config)?;
let sync_state = ConsciousnessSynchronizationState::new();
Ok((quantum_network, sync_state))
}
pub fn update_quantum_core<T>(
network: &mut QuantumEntanglementNetwork,
sync_state: &mut ConsciousnessSynchronizationState,
image: &ArrayView2<T>,
config: &QuantumAIConsciousnessConfig,
time_step: f64,
) -> NdimageResult<()>
where
T: Float + FromPrimitive + Copy + Send + Sync,
{
network.update_entanglement(time_step)?;
sync_state.update_synchronization(image, network, config)?;
for channel in &mut network.channels {
sync_state
.coherence_mechanism
.preserve_coherence(channel, time_step)?;
}
Ok(())
}
pub fn get_quantum_metrics(
network: &QuantumEntanglementNetwork,
sync_state: &ConsciousnessSynchronizationState,
) -> HashMap<String, f64> {
let mut metrics = HashMap::new();
metrics.insert(
"network_synchronization".to_string(),
network.synchronization_level,
);
metrics.insert("active_channels".to_string(), network.channels.len() as f64);
metrics.insert(
"average_entanglement".to_string(),
network
.channels
.iter()
.map(|c| c.entanglement_strength)
.sum::<f64>()
/ network.channels.len().max(1) as f64,
);
metrics.insert(
"global_synchronization".to_string(),
sync_state.synchronization_level,
);
metrics.insert(
"sync_patterns".to_string(),
sync_state.sync_patterns.len() as f64,
);
let coherence_metrics = sync_state.coherence_mechanism.get_coherence_metrics();
metrics.extend(coherence_metrics);
metrics
}