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rustytorch/archive/legacy_files_backup/error_detection_backup.rs
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2026-03-04 00:08:42 +00:00

1629 lines
40 KiB
Rust

//! Error Detection and Syndrome Analysis Systems
//!
//! This module contains error syndrome detection, pattern recognition,
//! and alerting systems for quantum error correction.
use crate::error::{AiContextError, AiContextResult};
use super::error_correction_core::{ErrorCorrectionConfig, QuantumErrorType, ErrorLocation, CorrectionRecommendation, CorrectionOperation, CorrectionType};
use serde::{Deserialize, Serialize};
use std::collections::HashMap;
use std::sync::Arc;
use tokio::sync::RwLock;
use tokio::time::{Duration, Instant};
use tracing::{debug, info, trace};
/// Error syndrome detection result
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ErrorSyndrome {
/// Syndrome identifier
pub syndrome_id: String,
/// Detection timestamp
pub detected_at: crate::temporal::TemporalTimestamp,
/// Syndrome pattern
pub pattern: SyndromePattern,
/// Error type classification
pub error_type: QuantumErrorType,
/// Error location
pub location: ErrorLocation,
/// Syndrome confidence
pub confidence: f64,
/// Correction recommendation
pub correction: CorrectionRecommendation,
}
/// Syndrome pattern for error detection
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct SyndromePattern {
/// Pattern bits
pub bits: Vec<u8>,
/// Pattern weight
pub weight: u32,
/// Pattern parity
pub parity: u8,
/// Stabilizer measurements
pub stabilizer_outcomes: Vec<StabilizerOutcome>,
}
/// Stabilizer measurement outcome
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct StabilizerOutcome {
/// Stabilizer identifier
pub stabilizer_id: String,
/// Measurement result
pub measurement: u8, // 0 or 1
/// Measurement confidence
pub confidence: f64,
/// Associated qubits
pub qubits: Vec<usize>,
}
/// Quantum parity check for error detection
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct QuantumParityCheck {
/// Check identifier
pub check_id: String,
/// Parity check matrix
pub check_matrix: ParityCheckMatrix,
/// Check qubits
pub check_qubits: Vec<usize>,
/// Data qubits
pub data_qubits: Vec<usize>,
/// Check frequency
pub frequency: f64,
/// Detection efficiency
pub efficiency: f64,
}
/// Parity check matrix
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ParityCheckMatrix {
/// Matrix dimensions
pub dimensions: (usize, usize),
/// Matrix elements
pub elements: Vec<Vec<u8>>,
/// Matrix rank
pub rank: usize,
/// Null space dimension
pub null_space_dim: usize,
}
/// Error syndrome detector
#[derive(Debug)]
pub struct ErrorSyndromeDetector {
/// Detection algorithms
algorithms: Vec<SyndromeDetectionAlgorithm>,
/// Syndrome database
syndrome_db: Arc<RwLock<SyndromeDatabase>>,
/// Real-time detector
realtime_detector: Arc<RealtimeSyndromeDetector>,
/// Pattern recognizer
pattern_recognizer: Arc<SyndromePatternRecognizer>,
}
/// Syndrome detection algorithm
#[derive(Debug, Clone)]
pub struct SyndromeDetectionAlgorithm {
/// Algorithm identifier
pub algorithm_id: String,
/// Detection method
pub method: DetectionMethod,
/// Detection accuracy
pub accuracy: f64,
/// Detection latency
pub latency: Duration,
/// Resource requirements
pub resources: DetectionResources,
}
/// Detection methods
#[derive(Debug, Clone)]
pub enum DetectionMethod {
ParityCheck,
StabilizerMeasurement,
ProcessTomography,
RandomizedBenchmarking,
QuantumVolumeMeasurement,
CrossEntropyBenchmarking,
}
/// Detection resource requirements
#[derive(Debug, Clone)]
pub struct DetectionResources {
/// Measurement shots
pub shots: u64,
/// Classical processing
pub classical_compute: f64,
/// Quantum circuit depth
pub circuit_depth: u32,
/// Measurement time
pub measurement_time: Duration,
}
/// Syndrome database
#[derive(Debug)]
pub struct SyndromeDatabase {
/// Known syndromes
syndromes: HashMap<String, KnownSyndrome>,
/// Syndrome patterns
patterns: Vec<SyndromePatternEntry>,
/// Database statistics
statistics: SyndromeStatistics,
}
/// Known syndrome entry
#[derive(Debug, Clone)]
pub struct KnownSyndrome {
/// Syndrome identifier
pub syndrome_id: String,
/// Syndrome signature
pub signature: SyndromeSignature,
/// Associated errors
pub errors: Vec<AssociatedError>,
/// Frequency of occurrence
pub frequency: f64,
/// Typical correction
pub correction: CorrectionOperation,
}
/// Syndrome signature
#[derive(Debug, Clone)]
pub struct SyndromeSignature {
/// Signature bits
pub bits: Vec<u8>,
/// Signature hash
pub hash: u64,
/// Signature confidence
pub confidence: f64,
}
/// Associated error
#[derive(Debug, Clone)]
pub struct AssociatedError {
/// Error description
pub description: String,
/// Error probability
pub probability: f64,
/// Error impact
pub impact: ErrorImpact,
}
/// Error impact assessment
#[derive(Debug, Clone)]
pub struct ErrorImpact {
/// Logical error probability
pub logical_error_prob: f64,
/// Performance degradation
pub performance_impact: f64,
/// Fidelity reduction
pub fidelity_impact: f64,
/// Cascading error potential
pub cascade_potential: f64,
}
/// Syndrome pattern entry
#[derive(Debug, Clone)]
pub struct SyndromePatternEntry {
/// Pattern identifier
pub pattern_id: String,
/// Pattern characteristics
pub characteristics: PatternCharacteristics,
/// Pattern evolution
pub evolution: PatternEvolution,
}
/// Pattern characteristics
#[derive(Debug, Clone)]
pub struct PatternCharacteristics {
/// Temporal structure
pub temporal_structure: TemporalStructure,
/// Spatial structure
pub spatial_structure: SpatialStructure,
/// Correlation structure
pub correlation_structure: CorrelationStructure,
}
/// Temporal structure of patterns
#[derive(Debug, Clone)]
pub struct TemporalStructure {
/// Pattern duration
pub duration: Duration,
/// Repetition frequency
pub frequency: f64,
/// Temporal correlations
pub correlations: Vec<TemporalCorrelation>,
}
/// Temporal correlation
#[derive(Debug, Clone)]
pub struct TemporalCorrelation {
/// Time lag
pub lag: Duration,
/// Correlation strength
pub strength: f64,
/// Correlation type
pub correlation_type: CorrelationType,
}
/// Types of correlations
#[derive(Debug, Clone)]
pub enum CorrelationType {
AutoCorrelation,
CrossCorrelation,
PartialCorrelation,
ConditionalCorrelation,
}
/// Spatial structure of patterns
#[derive(Debug, Clone)]
pub struct SpatialStructure {
/// Geometric layout
pub layout: GeometricLayout,
/// Connectivity patterns
pub connectivity: ConnectivityPattern,
/// Spatial correlations
pub correlations: Vec<SpatialCorrelation>,
}
/// Geometric layout
#[derive(Debug, Clone)]
pub struct GeometricLayout {
/// Layout type
pub layout_type: LayoutType,
/// Dimensions
pub dimensions: Vec<u32>,
/// Boundary conditions
pub boundaries: BoundaryConditions,
}
/// Types of geometric layouts
#[derive(Debug, Clone)]
pub enum LayoutType {
Square,
Hexagonal,
Triangular,
Cubic,
Hypercubic,
Irregular,
}
/// Boundary conditions
#[derive(Debug, Clone)]
pub struct BoundaryConditions {
/// Boundary type
pub boundary_type: BoundaryType,
/// Periodic boundaries
pub periodic: Vec<bool>,
/// Boundary effects
pub effects: Vec<BoundaryEffect>,
}
/// Types of boundaries
#[derive(Debug, Clone)]
pub enum BoundaryType {
Open,
Periodic,
Reflecting,
Absorbing,
Mixed,
}
/// Boundary effect
#[derive(Debug, Clone)]
pub struct BoundaryEffect {
/// Effect type
pub effect_type: EffectType,
/// Effect strength
pub strength: f64,
/// Affected region
pub region: Vec<usize>,
}
/// Types of boundary effects
#[derive(Debug, Clone)]
pub enum EffectType {
ErrorRateIncrease,
DecoherenceIncrease,
CorrelationIncrease,
FidelityDecrease,
}
/// Connectivity pattern
#[derive(Debug, Clone)]
pub struct ConnectivityPattern {
/// Pattern type
pub pattern_type: ConnectivityType,
/// Adjacency matrix
pub adjacency: Vec<Vec<bool>>,
/// Connection weights
pub weights: Vec<Vec<f64>>,
}
/// Types of connectivity
#[derive(Debug, Clone)]
pub enum ConnectivityType {
NearestNeighbor,
NextNearestNeighbor,
LongRange,
AllToAll,
Random,
SmallWorld,
}
/// Spatial correlation
#[derive(Debug, Clone)]
pub struct SpatialCorrelation {
/// Correlation range
pub range: f64,
/// Correlation strength
pub strength: f64,
/// Correlation function
pub function: CorrelationFunction,
}
/// Correlation functions
#[derive(Debug, Clone)]
pub enum CorrelationFunction {
Exponential,
PowerLaw,
Gaussian,
Polynomial,
Custom,
}
/// Correlation structure
#[derive(Debug, Clone)]
pub struct CorrelationStructure {
/// Correlation matrix
pub matrix: Vec<Vec<f64>>,
/// Principal components
pub principal_components: Vec<PrincipalComponent>,
/// Clustering information
pub clusters: Vec<CorrelationCluster>,
}
/// Principal component
#[derive(Debug, Clone)]
pub struct PrincipalComponent {
/// Component index
pub index: usize,
/// Eigenvalue
pub eigenvalue: f64,
/// Eigenvector
pub eigenvector: Vec<f64>,
/// Explained variance
pub explained_variance: f64,
}
/// Correlation cluster
#[derive(Debug, Clone)]
pub struct CorrelationCluster {
/// Cluster identifier
pub cluster_id: String,
/// Cluster members
pub members: Vec<usize>,
/// Cluster centroid
pub centroid: Vec<f64>,
/// Intra-cluster correlation
pub intra_correlation: f64,
}
/// Pattern evolution
#[derive(Debug, Clone)]
pub struct PatternEvolution {
/// Evolution trajectory
pub trajectory: Vec<EvolutionPoint>,
/// Evolution rate
pub rate: f64,
/// Evolution direction
pub direction: EvolutionDirection,
/// Stability measure
pub stability: f64,
}
/// Evolution point
#[derive(Debug, Clone)]
pub struct EvolutionPoint {
/// Timestamp
pub timestamp: crate::temporal::TemporalTimestamp,
/// Pattern state
pub state: PatternState,
/// State transition
pub transition: Option<StateTransition>,
}
/// Pattern state
#[derive(Debug, Clone)]
pub struct PatternState {
/// State characteristics
pub characteristics: StateCharacteristics,
/// State stability
pub stability: f64,
/// State entropy
pub entropy: f64,
}
/// State characteristics
#[derive(Debug, Clone)]
pub struct StateCharacteristics {
/// Energy level
pub energy: f64,
/// Complexity measure
pub complexity: f64,
/// Order parameter
pub order: f64,
/// Noise level
pub noise: f64,
}
/// State transition
#[derive(Debug, Clone)]
pub struct StateTransition {
/// Transition type
pub transition_type: TransitionType,
/// Transition probability
pub probability: f64,
/// Transition rate
pub rate: f64,
/// Activation energy
pub activation_energy: f64,
}
/// Types of state transitions
#[derive(Debug, Clone)]
pub enum TransitionType {
Continuous,
Discontinuous,
PhaseTransition,
QuantumPhaseTransition,
Topological,
}
/// Evolution directions
#[derive(Debug, Clone)]
pub enum EvolutionDirection {
OrderIncreasing,
OrderDecreasing,
ComplexityIncreasing,
ComplexityDecreasing,
Oscillatory,
Chaotic,
}
/// Syndrome statistics
#[derive(Debug, Clone)]
pub struct SyndromeStatistics {
/// Total syndromes recorded
pub total_syndromes: u64,
/// Unique syndrome patterns
pub unique_patterns: u64,
/// Average detection time
pub avg_detection_time: Duration,
/// Detection accuracy
pub accuracy: f64,
/// False positive rate
pub false_positive_rate: f64,
}
/// Real-time syndrome detector
#[derive(Debug)]
pub struct RealtimeSyndromeDetector {
/// Detection pipeline
pipeline: Arc<DetectionPipeline>,
/// Streaming processor
processor: Arc<StreamingSyndromeProcessor>,
/// Alert system
alert_system: Arc<SyndromeAlertSystem>,
}
/// Detection pipeline
#[derive(Debug)]
pub struct DetectionPipeline {
/// Pipeline stages
pub stages: Vec<DetectionStage>,
/// Pipeline throughput
pub throughput: f64,
/// Pipeline latency
pub latency: Duration,
}
/// Detection stage
#[derive(Debug, Clone)]
pub struct DetectionStage {
/// Stage identifier
pub stage_id: String,
/// Stage function
pub function: DetectionFunction,
/// Processing time
pub processing_time: Duration,
/// Stage accuracy
pub accuracy: f64,
}
/// Detection functions
#[derive(Debug, Clone)]
pub enum DetectionFunction {
DataIngestion,
Preprocessing,
SyndromeExtraction,
PatternMatching,
ErrorClassification,
ConfidenceAssessment,
}
/// Streaming syndrome processor
#[derive(Debug)]
pub struct StreamingSyndromeProcessor {
/// Processing buffers
buffers: Vec<ProcessingBuffer>,
/// Stream multiplexer
multiplexer: Arc<StreamMultiplexer>,
/// Output dispatcher
dispatcher: Arc<OutputDispatcher>,
}
/// Processing buffer
#[derive(Debug)]
pub struct ProcessingBuffer {
/// Buffer identifier
pub buffer_id: String,
/// Buffer capacity
pub capacity: usize,
/// Current utilization
pub utilization: f64,
/// Buffer type
pub buffer_type: BufferType,
}
/// Types of processing buffers
#[derive(Debug, Clone)]
pub enum BufferType {
Input,
Intermediate,
Output,
Cache,
History,
}
/// Stream multiplexer
#[derive(Debug)]
pub struct StreamMultiplexer {
/// Input streams
pub streams: Vec<InputStream>,
/// Multiplexing strategy
pub strategy: MultiplexingStrategy,
/// Load balancing
pub load_balancing: bool,
}
/// Input stream
#[derive(Debug, Clone)]
pub struct InputStream {
/// Stream identifier
pub stream_id: String,
/// Stream rate
pub rate: f64,
/// Stream priority
pub priority: u32,
/// Quality of service
pub qos: QualityOfService,
}
/// Quality of service parameters
#[derive(Debug, Clone)]
pub struct QualityOfService {
/// Maximum latency
pub max_latency: Duration,
/// Minimum throughput
pub min_throughput: f64,
/// Reliability requirement
pub reliability: f64,
/// Jitter tolerance
pub jitter_tolerance: Duration,
}
/// Multiplexing strategies
#[derive(Debug, Clone)]
pub enum MultiplexingStrategy {
RoundRobin,
Priority,
WeightedFairQueuing,
AdaptiveStrategy,
}
/// Output dispatcher
#[derive(Debug)]
pub struct OutputDispatcher {
/// Dispatch rules
rules: Vec<DispatchRule>,
/// Output channels
channels: HashMap<String, OutputChannel>,
}
/// Dispatch rule
#[derive(Debug, Clone)]
pub struct DispatchRule {
/// Rule identifier
pub rule_id: String,
/// Rule condition
pub condition: DispatchCondition,
/// Target channel
pub target: String,
/// Rule priority
pub priority: u32,
}
/// Dispatch condition
#[derive(Debug, Clone)]
pub struct DispatchCondition {
/// Condition type
pub condition_type: ConditionType,
/// Condition parameters
pub parameters: HashMap<String, f64>,
/// Evaluation logic
pub logic: String,
}
/// Types of dispatch conditions
#[derive(Debug, Clone)]
pub enum ConditionType {
SeverityThreshold,
ErrorType,
ConfidenceLevel,
TimeWindow,
FrequencyThreshold,
}
/// Output channel
#[derive(Debug)]
pub struct OutputChannel {
/// Channel identifier
pub channel_id: String,
/// Channel capacity
pub capacity: f64,
/// Current load
pub load: f64,
/// Channel reliability
pub reliability: f64,
}
/// Syndrome alert system
#[derive(Debug)]
pub struct SyndromeAlertSystem {
/// Alert rules
rules: Vec<SyndromeAlertRule>,
/// Active alerts
active_alerts: Arc<RwLock<Vec<SyndromeAlert>>>,
/// Escalation procedures
escalation: Vec<EscalationProcedure>,
}
/// Syndrome alert rule
#[derive(Debug, Clone)]
pub struct SyndromeAlertRule {
/// Rule identifier
pub rule_id: String,
/// Trigger condition
pub trigger: AlertTrigger,
/// Alert severity
pub severity: AlertSeverity,
/// Response procedure
pub response: ResponseProcedure,
}
/// Alert trigger conditions
#[derive(Debug, Clone)]
pub enum AlertTrigger {
ErrorRateExceeded(f64),
UnknownSyndrome,
CorrectionFailure,
SystemDegradation,
CriticalError,
}
/// Alert severity levels
#[derive(Debug, Clone)]
pub enum AlertSeverity {
Info,
Warning,
Error,
Critical,
Emergency,
}
/// Response procedure
#[derive(Debug, Clone)]
pub struct ResponseProcedure {
/// Procedure steps
pub steps: Vec<ResponseStep>,
/// Escalation threshold
pub escalation_threshold: Duration,
/// Auto-response enabled
pub auto_response: bool,
}
/// Response step
#[derive(Debug, Clone)]
pub struct ResponseStep {
/// Step description
pub description: String,
/// Step action
pub action: ResponseAction,
/// Step timeout
pub timeout: Duration,
}
/// Response actions
#[derive(Debug, Clone)]
pub enum ResponseAction {
LogEvent,
NotifyOperator,
AttemptCorrection,
IsolateError,
EscalateAlert,
ShutdownSystem,
}
/// Syndrome alert
#[derive(Debug, Clone)]
pub struct SyndromeAlert {
/// Alert identifier
pub alert_id: String,
/// Alert timestamp
pub timestamp: crate::temporal::TemporalTimestamp,
/// Alert severity
pub severity: AlertSeverity,
/// Alert message
pub message: String,
/// Associated syndrome
pub syndrome: String,
/// Response status
pub response_status: ResponseStatus,
}
/// Response status
#[derive(Debug, Clone)]
pub enum ResponseStatus {
Pending,
InProgress,
Completed,
Failed,
Escalated,
}
/// Escalation procedure
#[derive(Debug, Clone)]
pub struct EscalationProcedure {
/// Procedure identifier
pub procedure_id: String,
/// Escalation trigger
pub trigger: EscalationTrigger,
/// Escalation target
pub target: EscalationTarget,
/// Escalation timeline
pub timeline: Duration,
}
/// Escalation triggers
#[derive(Debug, Clone)]
pub enum EscalationTrigger {
TimeElapsed(Duration),
SeverityIncrease,
RepeatOccurrence,
SystemFailure,
ManualEscalation,
}
/// Escalation targets
#[derive(Debug, Clone)]
pub enum EscalationTarget {
NextLevel,
TechnicalTeam,
ManagementTeam,
ExternalSupport,
EmergencyProtocol,
}
/// Syndrome pattern recognizer
#[derive(Debug)]
pub struct SyndromePatternRecognizer {
/// Recognition algorithms
algorithms: Vec<RecognitionAlgorithm>,
/// Pattern library
library: Arc<PatternLibrary>,
/// Machine learning models
ml_models: Vec<PatternRecognitionModel>,
}
/// Recognition algorithm
#[derive(Debug, Clone)]
pub struct RecognitionAlgorithm {
/// Algorithm identifier
pub algorithm_id: String,
/// Recognition method
pub method: RecognitionMethod,
/// Recognition accuracy
pub accuracy: f64,
/// Processing speed
pub speed: f64,
}
/// Recognition methods
#[derive(Debug, Clone)]
pub enum RecognitionMethod {
TemplateMatching,
FeatureMatching,
StatisticalMatching,
MachineLearning,
DeepLearning,
EnsembleMethod,
}
/// Pattern library
#[derive(Debug)]
pub struct PatternLibrary {
/// Library patterns
pub patterns: HashMap<String, LibraryPattern>,
/// Pattern hierarchies
pub hierarchies: Vec<PatternHierarchy>,
/// Search index
pub index: PatternSearchIndex,
}
/// Library pattern
#[derive(Debug, Clone)]
pub struct LibraryPattern {
/// Pattern identifier
pub pattern_id: String,
/// Pattern template
pub template: PatternTemplate,
/// Usage statistics
pub usage: UsageStatistics,
/// Pattern metadata
pub metadata: PatternMetadata,
}
/// Pattern template
#[derive(Debug, Clone)]
pub struct PatternTemplate {
/// Template structure
pub structure: TemplateStructure,
/// Variable parameters
pub parameters: Vec<TemplateParameter>,
/// Matching criteria
pub criteria: MatchingCriteria,
}
/// Template structure
#[derive(Debug, Clone)]
pub struct TemplateStructure {
/// Structure type
pub structure_type: StructureType,
/// Structure elements
pub elements: Vec<StructureElement>,
/// Element relationships
pub relationships: Vec<ElementRelationship>,
}
/// Types of template structures
#[derive(Debug, Clone)]
pub enum StructureType {
Sequential,
Hierarchical,
Network,
Tree,
Graph,
Matrix,
}
/// Structure element
#[derive(Debug, Clone)]
pub struct StructureElement {
/// Element identifier
pub element_id: String,
/// Element type
pub element_type: ElementType,
/// Element properties
pub properties: HashMap<String, f64>,
}
/// Types of structure elements
#[derive(Debug, Clone)]
pub enum ElementType {
Node,
Edge,
Cluster,
Substructure,
Marker,
}
/// Element relationship
#[derive(Debug, Clone)]
pub struct ElementRelationship {
/// Relationship identifier
pub relationship_id: String,
/// Source element
pub source: String,
/// Target element
pub target: String,
/// Relationship type
pub relationship_type: RelationshipType,
/// Relationship strength
pub strength: f64,
}
/// Types of element relationships
#[derive(Debug, Clone)]
pub enum RelationshipType {
Parent,
Child,
Sibling,
Dependency,
Association,
Aggregation,
}
/// Template parameter
#[derive(Debug, Clone)]
pub struct TemplateParameter {
/// Parameter name
pub name: String,
/// Parameter type
pub param_type: TemplateParameterType,
/// Default value
pub default: f64,
/// Value range
pub range: (f64, f64),
}
/// Types of template parameters
#[derive(Debug, Clone)]
pub enum TemplateParameterType {
Continuous,
Discrete,
Categorical,
Boolean,
}
/// Matching criteria for patterns
#[derive(Debug, Clone)]
pub struct MatchingCriteria {
/// Similarity threshold
pub similarity_threshold: f64,
/// Required features
pub required_features: Vec<String>,
/// Optional features
pub optional_features: Vec<String>,
/// Exclusion criteria
pub exclusions: Vec<String>,
}
/// Usage statistics for patterns
#[derive(Debug, Clone)]
pub struct UsageStatistics {
/// Usage frequency
pub frequency: f64,
/// Success rate
pub success_rate: f64,
/// Average processing time
pub avg_time: Duration,
/// User ratings
pub ratings: Vec<f64>,
}
/// Pattern metadata
#[derive(Debug, Clone)]
pub struct PatternMetadata {
/// Creation timestamp
pub created: crate::temporal::TemporalTimestamp,
/// Last updated
pub updated: crate::temporal::TemporalTimestamp,
/// Version number
pub version: String,
/// Author information
pub author: String,
/// Pattern tags
pub tags: Vec<String>,
}
/// Pattern hierarchy
#[derive(Debug, Clone)]
pub struct PatternHierarchy {
/// Hierarchy identifier
pub hierarchy_id: String,
/// Root patterns
pub roots: Vec<String>,
/// Parent-child relationships
pub relationships: Vec<HierarchyRelationship>,
/// Hierarchy depth
pub depth: u32,
}
/// Hierarchy relationship
#[derive(Debug, Clone)]
pub struct HierarchyRelationship {
/// Parent pattern
pub parent: String,
/// Child pattern
pub child: String,
/// Relationship strength
pub strength: f64,
/// Inheritance properties
pub inheritance: Vec<String>,
}
/// Pattern search index
#[derive(Debug)]
pub struct PatternSearchIndex {
/// Index entries
pub entries: Vec<PatternIndexEntry>,
/// Search algorithms
pub algorithms: Vec<PatternSearchAlgorithm>,
}
/// Pattern index entry
#[derive(Debug, Clone)]
pub struct PatternIndexEntry {
/// Pattern identifier
pub pattern_id: String,
/// Search keywords
pub keywords: Vec<String>,
/// Feature vector
pub features: Vec<f64>,
/// Index score
pub score: f64,
}
/// Pattern search algorithm
#[derive(Debug, Clone)]
pub struct PatternSearchAlgorithm {
/// Algorithm identifier
pub algorithm_id: String,
/// Search method
pub method: PatternSearchMethod,
/// Search accuracy
pub accuracy: f64,
/// Search speed
pub speed: f64,
}
/// Pattern search methods
#[derive(Debug, Clone)]
pub enum PatternSearchMethod {
ExactMatch,
FuzzyMatch,
SemanticSearch,
VectorSimilarity,
GraphMatching,
MachineLearning,
}
/// Pattern recognition model
#[derive(Debug, Clone)]
pub struct PatternRecognitionModel {
/// Model identifier
pub model_id: String,
/// Model architecture
pub architecture: ModelArchitecture,
/// Training configuration
pub training: TrainingConfiguration,
/// Performance metrics
pub performance: ModelPerformance,
}
/// Model architecture
#[derive(Debug, Clone)]
pub struct ModelArchitecture {
/// Architecture type
pub arch_type: ArchitectureType,
/// Layer configuration
pub layers: Vec<LayerConfiguration>,
/// Activation functions
pub activations: Vec<ActivationFunction>,
/// Regularization
pub regularization: RegularizationConfig,
}
/// Types of model architectures
#[derive(Debug, Clone)]
pub enum ArchitectureType {
FeedForward,
Convolutional,
Recurrent,
Transformer,
ResNet,
Attention,
}
/// Layer configuration
#[derive(Debug, Clone)]
pub struct LayerConfiguration {
/// Layer type
pub layer_type: LayerType,
/// Layer size
pub size: usize,
/// Activation function
pub activation: String,
/// Dropout rate
pub dropout: f64,
}
/// Types of neural layers
#[derive(Debug, Clone)]
pub enum LayerType {
Dense,
Convolutional,
Pooling,
Normalization,
Dropout,
Attention,
}
/// Activation functions
#[derive(Debug, Clone)]
pub enum ActivationFunction {
ReLU,
Sigmoid,
Tanh,
Softmax,
LeakyReLU,
ELU,
}
/// Regularization configuration
#[derive(Debug, Clone)]
pub struct RegularizationConfig {
/// L1 regularization weight
pub l1_weight: f64,
/// L2 regularization weight
pub l2_weight: f64,
/// Dropout rate
pub dropout_rate: f64,
/// Batch normalization
pub batch_norm: bool,
}
/// Training configuration
#[derive(Debug, Clone)]
pub struct TrainingConfiguration {
/// Learning rate
pub learning_rate: f64,
/// Batch size
pub batch_size: usize,
/// Number of epochs
pub epochs: u32,
/// Optimizer type
pub optimizer: OptimizerType,
/// Loss function
pub loss_function: LossFunction,
}
/// Types of optimizers
#[derive(Debug, Clone)]
pub enum OptimizerType {
SGD,
Adam,
AdamW,
RMSprop,
Adagrad,
}
/// Loss functions
#[derive(Debug, Clone)]
pub enum LossFunction {
MeanSquaredError,
CrossEntropy,
BinaryCrossEntropy,
MeanAbsoluteError,
Huber,
}
/// Model performance metrics
#[derive(Debug, Clone)]
pub struct ModelPerformance {
/// Training accuracy
pub training_accuracy: f64,
/// Validation accuracy
pub validation_accuracy: f64,
/// Test accuracy
pub test_accuracy: f64,
/// F1 score
pub f1_score: f64,
/// Precision
pub precision: f64,
/// Recall
pub recall: f64,
}
// Implementation
impl ErrorSyndromeDetector {
pub async fn new(_config: &ErrorCorrectionConfig) -> AiContextResult<Self> {
Ok(Self {
algorithms: vec![],
syndrome_db: Arc::new(RwLock::new(SyndromeDatabase {
syndromes: HashMap::new(),
patterns: vec![],
statistics: SyndromeStatistics {
total_syndromes: 0,
unique_patterns: 0,
avg_detection_time: Duration::from_millis(1),
accuracy: 0.95,
false_positive_rate: 0.01,
},
})),
realtime_detector: Arc::new(RealtimeSyndromeDetector::new()),
pattern_recognizer: Arc::new(SyndromePatternRecognizer::new()),
})
}
pub async fn detect_syndromes(
&self,
_code: &str,
potential_errors: &[String],
) -> AiContextResult<Vec<ErrorSyndrome>> {
let mut syndromes = Vec::new();
for (i, error) in potential_errors.iter().enumerate() {
syndromes.push(ErrorSyndrome {
syndrome_id: format!("syndrome_{}", i),
detected_at: crate::temporal::TemporalTimestamp::now(),
pattern: SyndromePattern {
bits: vec![1, 0, 1, 0], // Simplified pattern
weight: 2,
parity: 0,
stabilizer_outcomes: vec![],
},
error_type: QuantumErrorType::BitFlipError,
location: ErrorLocation {
physical_qubits: vec![i],
logical_qubit: Some(0),
syndrome: vec![1, 0],
probability: 0.8,
confidence: 0.9,
},
confidence: 0.9,
correction: CorrectionRecommendation {
correction: CorrectionOperation {
operation_type: CorrectionType::PauliX,
target_qubits: vec![i],
parameters: HashMap::new(),
effectiveness: 0.95,
},
success_probability: 0.95,
alternatives: vec![],
cost: 0.1,
},
});
}
Ok(syndromes)
}
}
impl RealtimeSyndromeDetector {
pub fn new() -> Self {
Self {
pipeline: Arc::new(DetectionPipeline {
stages: vec![],
throughput: 1000.0,
latency: Duration::from_micros(100),
}),
processor: Arc::new(StreamingSyndromeProcessor::new()),
alert_system: Arc::new(SyndromeAlertSystem::new()),
}
}
}
impl StreamingSyndromeProcessor {
pub fn new() -> Self {
Self {
buffers: vec![],
multiplexer: Arc::new(StreamMultiplexer {
streams: vec![],
strategy: MultiplexingStrategy::Priority,
load_balancing: true,
}),
dispatcher: Arc::new(OutputDispatcher::new()),
}
}
}
impl OutputDispatcher {
pub fn new() -> Self {
Self {
rules: vec![],
channels: HashMap::new(),
}
}
}
impl SyndromeAlertSystem {
pub fn new() -> Self {
Self {
rules: vec![],
active_alerts: Arc::new(RwLock::new(Vec::new())),
escalation: vec![],
}
}
}
impl SyndromePatternRecognizer {
pub fn new() -> Self {
Self {
algorithms: vec![],
library: Arc::new(PatternLibrary {
patterns: HashMap::new(),
hierarchies: vec![],
index: PatternSearchIndex {
entries: vec![],
algorithms: vec![],
},
}),
ml_models: vec![],
}
}
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_error_syndrome_creation() {
let syndrome = ErrorSyndrome {
syndrome_id: "test_syndrome".to_string(),
detected_at: crate::temporal::TemporalTimestamp::now(),
pattern: SyndromePattern {
bits: vec![1, 0, 1, 1],
weight: 3,
parity: 1,
stabilizer_outcomes: vec![
StabilizerOutcome {
stabilizer_id: "X_stabilizer".to_string(),
measurement: 1,
confidence: 0.95,
qubits: vec![0, 1],
}
],
},
error_type: QuantumErrorType::BitFlipError,
location: ErrorLocation {
physical_qubits: vec![0, 1],
logical_qubit: Some(0),
syndrome: vec![1, 0, 1],
probability: 0.85,
confidence: 0.9,
},
confidence: 0.9,
correction: CorrectionRecommendation {
correction: CorrectionOperation {
operation_type: CorrectionType::PauliX,
target_qubits: vec![0],
parameters: HashMap::new(),
effectiveness: 0.98,
},
success_probability: 0.98,
alternatives: vec![],
cost: 0.05,
},
};
assert_eq!(syndrome.syndrome_id, "test_syndrome");
assert!(matches!(syndrome.error_type, QuantumErrorType::BitFlipError));
assert_eq!(syndrome.pattern.weight, 3);
assert_eq!(syndrome.location.physical_qubits.len(), 2);
assert!(matches!(syndrome.correction.correction.operation_type, CorrectionType::PauliX));
}
#[test]
fn test_syndrome_pattern() {
let pattern = SyndromePattern {
bits: vec![1, 1, 0, 1, 0],
weight: 3,
parity: 1,
stabilizer_outcomes: vec![],
};
assert_eq!(pattern.bits.len(), 5);
assert_eq!(pattern.weight, 3);
assert_eq!(pattern.parity, 1);
assert_eq!(pattern.stabilizer_outcomes.len(), 0);
}
#[test]
fn test_stabilizer_outcome() {
let outcome = StabilizerOutcome {
stabilizer_id: "Z_stabilizer_test".to_string(),
measurement: 0,
confidence: 0.87,
qubits: vec![1, 2, 3],
};
assert_eq!(outcome.stabilizer_id, "Z_stabilizer_test");
assert_eq!(outcome.measurement, 0);
assert_eq!(outcome.confidence, 0.87);
assert_eq!(outcome.qubits, vec![1, 2, 3]);
}
#[test]
fn test_quantum_parity_check() {
let parity_check = QuantumParityCheck {
check_id: "surface_code_check".to_string(),
check_matrix: ParityCheckMatrix {
dimensions: (4, 9),
elements: vec![
vec![1, 1, 0, 1, 1, 0, 0, 0, 0],
vec![0, 1, 1, 0, 1, 1, 0, 0, 0],
vec![0, 0, 0, 1, 1, 0, 1, 1, 0],
vec![0, 0, 0, 0, 1, 1, 0, 1, 1],
],
rank: 4,
null_space_dim: 1,
},
check_qubits: vec![0, 1, 2, 3],
data_qubits: vec![4, 5, 6, 7, 8],
frequency: 1000.0,
efficiency: 0.95,
};
assert_eq!(parity_check.check_id, "surface_code_check");
assert_eq!(parity_check.check_matrix.dimensions, (4, 9));
assert_eq!(parity_check.check_qubits.len(), 4);
assert_eq!(parity_check.data_qubits.len(), 5);
assert_eq!(parity_check.frequency, 1000.0);
assert_eq!(parity_check.efficiency, 0.95);
}
#[test]
fn test_syndrome_signature() {
let signature = SyndromeSignature {
bits: vec![1, 0, 1, 1, 0, 0, 1],
hash: 0xABCDEF123456789,
confidence: 0.92,
};
assert_eq!(signature.bits.len(), 7);
assert_eq!(signature.hash, 0xABCDEF123456789);
assert_eq!(signature.confidence, 0.92);
}
#[test]
fn test_detection_algorithm() {
let algorithm = SyndromeDetectionAlgorithm {
algorithm_id: "parity_check_detection".to_string(),
method: DetectionMethod::ParityCheck,
accuracy: 0.99,
latency: Duration::from_micros(50),
resources: DetectionResources {
shots: 1000,
classical_compute: 5.0,
circuit_depth: 3,
measurement_time: Duration::from_micros(10),
},
};
assert_eq!(algorithm.algorithm_id, "parity_check_detection");
assert!(matches!(algorithm.method, DetectionMethod::ParityCheck));
assert_eq!(algorithm.accuracy, 0.99);
assert_eq!(algorithm.resources.shots, 1000);
assert_eq!(algorithm.resources.circuit_depth, 3);
}
#[test]
fn test_temporal_correlation() {
let correlation = TemporalCorrelation {
lag: Duration::from_millis(5),
strength: 0.75,
correlation_type: CorrelationType::AutoCorrelation,
};
assert_eq!(correlation.lag, Duration::from_millis(5));
assert_eq!(correlation.strength, 0.75);
assert!(matches!(correlation.correlation_type, CorrelationType::AutoCorrelation));
}
#[test]
fn test_spatial_structure() {
let layout = GeometricLayout {
layout_type: LayoutType::Square,
dimensions: vec![7, 7],
boundaries: BoundaryConditions {
boundary_type: BoundaryType::Open,
periodic: vec![false, false],
effects: vec![],
},
};
assert!(matches!(layout.layout_type, LayoutType::Square));
assert_eq!(layout.dimensions, vec![7, 7]);
assert!(matches!(layout.boundaries.boundary_type, BoundaryType::Open));
}
#[test]
fn test_syndrome_alert() {
let alert = SyndromeAlert {
alert_id: "critical_error_001".to_string(),
timestamp: crate::temporal::TemporalTimestamp::now(),
severity: AlertSeverity::Critical,
message: "High error rate detected".to_string(),
syndrome: "syndrome_xyz".to_string(),
response_status: ResponseStatus::Pending,
};
assert_eq!(alert.alert_id, "critical_error_001");
assert!(matches!(alert.severity, AlertSeverity::Critical));
assert_eq!(alert.message, "High error rate detected");
assert!(matches!(alert.response_status, ResponseStatus::Pending));
}
#[test]
fn test_pattern_recognition_model() {
let model = PatternRecognitionModel {
model_id: "cnn_syndrome_classifier".to_string(),
architecture: ModelArchitecture {
arch_type: ArchitectureType::Convolutional,
layers: vec![
LayerConfiguration {
layer_type: LayerType::Convolutional,
size: 32,
activation: "relu".to_string(),
dropout: 0.1,
}
],
activations: vec![ActivationFunction::ReLU],
regularization: RegularizationConfig {
l1_weight: 0.01,
l2_weight: 0.001,
dropout_rate: 0.2,
batch_norm: true,
},
},
training: TrainingConfiguration {
learning_rate: 0.001,
batch_size: 32,
epochs: 100,
optimizer: OptimizerType::Adam,
loss_function: LossFunction::CrossEntropy,
},
performance: ModelPerformance {
training_accuracy: 0.95,
validation_accuracy: 0.92,
test_accuracy: 0.91,
f1_score: 0.90,
precision: 0.89,
recall: 0.91,
},
};
assert_eq!(model.model_id, "cnn_syndrome_classifier");
assert!(matches!(model.architecture.arch_type, ArchitectureType::Convolutional));
assert_eq!(model.training.learning_rate, 0.001);
assert_eq!(model.performance.test_accuracy, 0.91);
}
#[tokio::test]
async fn test_syndrome_detector_creation() {
let config = ErrorCorrectionConfig::default();
let detector = ErrorSyndromeDetector::new(&config).await;
assert!(detector.is_ok());
let detector = detector.unwrap();
assert_eq!(detector.algorithms.len(), 0); // Initially empty
}
#[tokio::test]
async fn test_syndrome_detection() {
let config = ErrorCorrectionConfig::default();
let detector = ErrorSyndromeDetector::new(&config).await.unwrap();
let code = "fn test() { vec![].get(0).unwrap(); }";
let errors = vec!["Potential panic".to_string(), "Out of bounds".to_string()];
let syndromes = detector.detect_syndromes(code, &errors).await;
assert!(syndromes.is_ok());
let syndromes = syndromes.unwrap();
assert_eq!(syndromes.len(), 2);
assert_eq!(syndromes[0].syndrome_id, "syndrome_0");
assert_eq!(syndromes[1].syndrome_id, "syndrome_1");
}
}