quantrs2_circuit/
scirs2_integration.rs

1//! `SciRS2` graph algorithms integration for circuit analysis
2//!
3//! This module integrates `SciRS2`'s advanced graph algorithms and data structures
4//! to provide sophisticated circuit analysis, optimization, and pattern matching capabilities.
5
6use crate::builder::Circuit;
7use crate::dag::{circuit_to_dag, CircuitDag, DagNode};
8use quantrs2_core::{
9    error::{QuantRS2Error, QuantRS2Result},
10    gate::GateOp,
11    qubit::QubitId,
12};
13use serde::{Deserialize, Serialize};
14use std::collections::{BTreeMap, HashMap, HashSet, VecDeque};
15use std::sync::Arc;
16
17/// SciRS2-powered graph representation of quantum circuits
18#[derive(Debug, Clone)]
19pub struct SciRS2CircuitGraph {
20    /// Node data indexed by node ID
21    pub nodes: HashMap<usize, SciRS2Node>,
22    /// Edge data indexed by (source, target)
23    pub edges: HashMap<(usize, usize), SciRS2Edge>,
24    /// Adjacency matrix for efficient access
25    pub adjacency_matrix: Vec<Vec<bool>>,
26    /// Node properties for analysis
27    pub node_properties: HashMap<usize, NodeProperties>,
28    /// Graph metrics cache
29    pub metrics_cache: Option<GraphMetrics>,
30}
31
32/// Enhanced node representation with `SciRS2` properties
33#[derive(Debug, Clone)]
34pub struct SciRS2Node {
35    pub id: usize,
36    pub gate: Option<Box<dyn GateOp>>,
37    pub node_type: SciRS2NodeType,
38    pub weight: f64,
39    pub depth: usize,
40    pub clustering_coefficient: Option<f64>,
41    pub centrality_measures: CentralityMeasures,
42}
43
44/// Types of nodes in `SciRS2` graph representation
45#[derive(Debug, Clone, PartialEq, Eq)]
46pub enum SciRS2NodeType {
47    /// Input boundary node
48    Input { qubit: u32 },
49    /// Output boundary node
50    Output { qubit: u32 },
51    /// Single-qubit gate
52    SingleQubitGate { gate_type: String, qubit: u32 },
53    /// Two-qubit gate
54    TwoQubitGate {
55        gate_type: String,
56        qubits: (u32, u32),
57    },
58    /// Multi-qubit gate
59    MultiQubitGate { gate_type: String, qubits: Vec<u32> },
60    /// Measurement node
61    Measurement { qubit: u32 },
62    /// Barrier or synchronization point
63    Barrier { qubits: Vec<u32> },
64}
65
66/// Edge representation with advanced properties
67#[derive(Debug, Clone)]
68pub struct SciRS2Edge {
69    pub source: usize,
70    pub target: usize,
71    pub edge_type: EdgeType,
72    pub weight: f64,
73    pub flow_capacity: Option<f64>,
74    pub is_critical_path: bool,
75}
76
77/// Enhanced edge types for circuit analysis
78#[derive(Debug, Clone, PartialEq)]
79pub enum EdgeType {
80    /// Data dependency on qubit
81    QubitDependency { qubit: u32, distance: usize },
82    /// Classical control dependency
83    ClassicalDependency,
84    /// Commutation edge (gates can be reordered)
85    Commutation { strength: f64 },
86    /// Entanglement edge
87    Entanglement { strength: f64 },
88    /// Temporal dependency
89    Temporal { delay: f64 },
90}
91
92/// Node properties for analysis
93#[derive(Debug, Clone, Default)]
94pub struct NodeProperties {
95    /// Degree (number of connections)
96    pub degree: usize,
97    /// In-degree
98    pub in_degree: usize,
99    /// Out-degree
100    pub out_degree: usize,
101    /// Node eccentricity
102    pub eccentricity: Option<usize>,
103    /// Local clustering coefficient
104    pub clustering_coefficient: Option<f64>,
105    /// Community assignment
106    pub community: Option<usize>,
107    /// Gate execution cost
108    pub execution_cost: f64,
109    /// Error rate
110    pub error_rate: f64,
111}
112
113/// Centrality measures for nodes
114#[derive(Debug, Clone, Default)]
115pub struct CentralityMeasures {
116    /// Degree centrality
117    pub degree: f64,
118    /// Betweenness centrality
119    pub betweenness: Option<f64>,
120    /// Closeness centrality
121    pub closeness: Option<f64>,
122    /// Eigenvector centrality
123    pub eigenvector: Option<f64>,
124    /// `PageRank` score
125    pub pagerank: Option<f64>,
126}
127
128/// Graph-level metrics
129#[derive(Debug, Clone, Serialize, Deserialize)]
130pub struct GraphMetrics {
131    /// Number of nodes
132    pub num_nodes: usize,
133    /// Number of edges
134    pub num_edges: usize,
135    /// Graph diameter
136    pub diameter: Option<usize>,
137    /// Average path length
138    pub average_path_length: Option<f64>,
139    /// Clustering coefficient
140    pub clustering_coefficient: f64,
141    /// Graph density
142    pub density: f64,
143    /// Number of connected components
144    pub connected_components: usize,
145    /// Modularity (community structure)
146    pub modularity: Option<f64>,
147    /// Small-world coefficient
148    pub small_world_coefficient: Option<f64>,
149}
150
151/// `SciRS2` circuit analyzer with advanced graph algorithms
152pub struct SciRS2CircuitAnalyzer {
153    /// Configuration options
154    pub config: AnalyzerConfig,
155    /// Cached analysis results
156    analysis_cache: HashMap<String, AnalysisResult>,
157}
158
159/// Configuration for `SciRS2` analysis
160#[derive(Debug, Clone, Serialize, Deserialize)]
161pub struct AnalyzerConfig {
162    /// Enable community detection
163    pub enable_community_detection: bool,
164    /// Enable centrality calculations
165    pub enable_centrality: bool,
166    /// Enable path analysis
167    pub enable_path_analysis: bool,
168    /// Enable motif detection
169    pub enable_motif_detection: bool,
170    /// Maximum path length for analysis
171    pub max_path_length: usize,
172    /// Clustering resolution parameter
173    pub clustering_resolution: f64,
174}
175
176impl Default for AnalyzerConfig {
177    fn default() -> Self {
178        Self {
179            enable_community_detection: true,
180            enable_centrality: true,
181            enable_path_analysis: true,
182            enable_motif_detection: true,
183            max_path_length: 10,
184            clustering_resolution: 1.0,
185        }
186    }
187}
188
189/// Analysis results container
190#[derive(Debug, Clone)]
191pub struct AnalysisResult {
192    /// Graph metrics
193    pub metrics: GraphMetrics,
194    /// Critical paths
195    pub critical_paths: Vec<Vec<usize>>,
196    /// Detected communities
197    pub communities: Vec<Vec<usize>>,
198    /// Graph motifs
199    pub motifs: Vec<GraphMotif>,
200    /// Optimization suggestions
201    pub optimization_suggestions: Vec<OptimizationSuggestion>,
202    /// Analysis timestamp
203    pub timestamp: std::time::SystemTime,
204}
205
206/// Graph motifs (common subgraph patterns)
207#[derive(Debug, Clone)]
208pub struct GraphMotif {
209    /// Motif type
210    pub motif_type: MotifType,
211    /// Nodes involved in the motif
212    pub nodes: Vec<usize>,
213    /// Motif frequency in the graph
214    pub frequency: usize,
215    /// Statistical significance
216    pub p_value: Option<f64>,
217}
218
219/// Types of graph motifs
220#[derive(Debug, Clone, PartialEq, Eq)]
221pub enum MotifType {
222    /// Chain of single-qubit gates
223    SingleQubitChain,
224    /// CNOT ladder pattern
225    CnotLadder,
226    /// Bell pair preparation
227    BellPairPreparation,
228    /// Quantum Fourier Transform pattern
229    QftPattern,
230    /// Grover diffusion operator
231    GroverDiffusion,
232    /// Custom motif
233    Custom { name: String, pattern: String },
234}
235
236/// Optimization suggestions based on graph analysis
237#[derive(Debug, Clone)]
238pub struct OptimizationSuggestion {
239    /// Suggestion type
240    pub suggestion_type: SuggestionType,
241    /// Affected nodes
242    pub nodes: Vec<usize>,
243    /// Expected improvement
244    pub expected_improvement: f64,
245    /// Confidence score
246    pub confidence: f64,
247    /// Detailed description
248    pub description: String,
249}
250
251/// Types of optimization suggestions
252#[derive(Debug, Clone, PartialEq, Eq)]
253pub enum SuggestionType {
254    /// Gate reordering based on commutation
255    GateReordering,
256    /// Community-based parallelization
257    Parallelization,
258    /// Critical path optimization
259    CriticalPathOptimization,
260    /// Motif-based template matching
261    TemplateMatching,
262    /// Redundancy elimination
263    RedundancyElimination,
264}
265
266impl Default for SciRS2CircuitAnalyzer {
267    fn default() -> Self {
268        Self::new()
269    }
270}
271
272impl SciRS2CircuitAnalyzer {
273    /// Create a new analyzer
274    #[must_use]
275    pub fn new() -> Self {
276        Self {
277            config: AnalyzerConfig::default(),
278            analysis_cache: HashMap::new(),
279        }
280    }
281
282    /// Create analyzer with custom configuration
283    #[must_use]
284    pub fn with_config(config: AnalyzerConfig) -> Self {
285        Self {
286            config,
287            analysis_cache: HashMap::new(),
288        }
289    }
290
291    /// Convert circuit to `SciRS2` graph representation
292    pub fn circuit_to_scirs2_graph<const N: usize>(
293        &self,
294        circuit: &Circuit<N>,
295    ) -> QuantRS2Result<SciRS2CircuitGraph> {
296        let dag = circuit_to_dag(circuit);
297        let mut graph = SciRS2CircuitGraph {
298            nodes: HashMap::new(),
299            edges: HashMap::new(),
300            adjacency_matrix: Vec::new(),
301            node_properties: HashMap::new(),
302            metrics_cache: None,
303        };
304
305        // Convert DAG nodes to SciRS2 nodes
306        for dag_node in dag.nodes() {
307            let node_type = self.classify_node_type(dag_node)?;
308            let sci_node = SciRS2Node {
309                id: dag_node.id,
310                gate: Some(dag_node.gate.clone()),
311                node_type,
312                weight: 1.0, // Default weight
313                depth: dag_node.depth,
314                clustering_coefficient: None,
315                centrality_measures: CentralityMeasures::default(),
316            };
317            graph.nodes.insert(dag_node.id, sci_node);
318        }
319
320        // Convert edges with enhanced properties
321        for dag_edge in dag.edges() {
322            let edge_type = self.classify_edge_type(dag_edge, &dag)?;
323            let sci_edge = SciRS2Edge {
324                source: dag_edge.source,
325                target: dag_edge.target,
326                edge_type,
327                weight: 1.0,
328                flow_capacity: Some(1.0),
329                is_critical_path: false,
330            };
331            graph
332                .edges
333                .insert((dag_edge.source, dag_edge.target), sci_edge);
334        }
335
336        // Build adjacency matrix
337        self.build_adjacency_matrix(&mut graph);
338
339        // Calculate node properties
340        self.calculate_node_properties(&mut graph)?;
341
342        Ok(graph)
343    }
344
345    /// Classify node type for `SciRS2` representation
346    fn classify_node_type(&self, node: &DagNode) -> QuantRS2Result<SciRS2NodeType> {
347        let gate = node.gate.as_ref();
348        let qubits = gate.qubits();
349        let gate_name = gate.name();
350
351        match qubits.len() {
352            0 => Ok(SciRS2NodeType::Barrier { qubits: Vec::new() }),
353            1 => Ok(SciRS2NodeType::SingleQubitGate {
354                gate_type: gate_name.to_string(),
355                qubit: qubits[0].id(),
356            }),
357            2 => Ok(SciRS2NodeType::TwoQubitGate {
358                gate_type: gate_name.to_string(),
359                qubits: (qubits[0].id(), qubits[1].id()),
360            }),
361            _ => Ok(SciRS2NodeType::MultiQubitGate {
362                gate_type: gate_name.to_string(),
363                qubits: qubits.iter().map(quantrs2_core::QubitId::id).collect(),
364            }),
365        }
366    }
367
368    /// Classify edge type with enhanced information
369    fn classify_edge_type(
370        &self,
371        edge: &crate::dag::DagEdge,
372        dag: &CircuitDag,
373    ) -> QuantRS2Result<EdgeType> {
374        match edge.edge_type {
375            crate::dag::EdgeType::QubitDependency(qubit) => {
376                // Calculate distance between nodes
377                let distance = self.calculate_node_distance(edge.source, edge.target, dag);
378                Ok(EdgeType::QubitDependency { qubit, distance })
379            }
380            crate::dag::EdgeType::ClassicalDependency => Ok(EdgeType::ClassicalDependency),
381            crate::dag::EdgeType::BarrierDependency => Ok(EdgeType::Temporal { delay: 0.0 }),
382        }
383    }
384
385    /// Calculate distance between nodes in the DAG
386    fn calculate_node_distance(&self, source: usize, target: usize, dag: &CircuitDag) -> usize {
387        // Simple depth difference for now
388        if let (Some(source_node), Some(target_node)) =
389            (dag.nodes().get(source), dag.nodes().get(target))
390        {
391            target_node.depth.saturating_sub(source_node.depth)
392        } else {
393            0
394        }
395    }
396
397    /// Build adjacency matrix for efficient graph operations
398    fn build_adjacency_matrix(&self, graph: &mut SciRS2CircuitGraph) {
399        let n = graph.nodes.len();
400        let mut matrix = vec![vec![false; n]; n];
401
402        for &(source, target) in graph.edges.keys() {
403            if source < n && target < n {
404                matrix[source][target] = true;
405            }
406        }
407
408        graph.adjacency_matrix = matrix;
409    }
410
411    /// Calculate node properties using graph algorithms
412    fn calculate_node_properties(&self, graph: &mut SciRS2CircuitGraph) -> QuantRS2Result<()> {
413        for &node_id in graph.nodes.keys() {
414            // Calculate clustering coefficient if enabled
415            let clustering_coefficient = if self.config.enable_centrality {
416                self.calculate_clustering_coefficient(node_id, graph)
417            } else {
418                Some(0.0)
419            };
420
421            let properties = NodeProperties {
422                degree: self.calculate_degree(node_id, graph),
423                in_degree: self.calculate_in_degree(node_id, graph),
424                out_degree: self.calculate_out_degree(node_id, graph),
425                clustering_coefficient,
426                ..Default::default()
427            };
428
429            graph.node_properties.insert(node_id, properties);
430        }
431
432        Ok(())
433    }
434
435    /// Calculate node degree
436    fn calculate_degree(&self, node_id: usize, graph: &SciRS2CircuitGraph) -> usize {
437        graph
438            .edges
439            .keys()
440            .filter(|&&(s, t)| s == node_id || t == node_id)
441            .count()
442    }
443
444    /// Calculate in-degree
445    fn calculate_in_degree(&self, node_id: usize, graph: &SciRS2CircuitGraph) -> usize {
446        graph.edges.keys().filter(|&&(_, t)| t == node_id).count()
447    }
448
449    /// Calculate out-degree
450    fn calculate_out_degree(&self, node_id: usize, graph: &SciRS2CircuitGraph) -> usize {
451        graph.edges.keys().filter(|&&(s, _)| s == node_id).count()
452    }
453
454    /// Calculate clustering coefficient for a node
455    fn calculate_clustering_coefficient(
456        &self,
457        node_id: usize,
458        graph: &SciRS2CircuitGraph,
459    ) -> Option<f64> {
460        let neighbors = self.get_neighbors(node_id, graph);
461        let k = neighbors.len();
462
463        if k < 2 {
464            return Some(0.0);
465        }
466
467        let mut connections = 0;
468        for i in 0..neighbors.len() {
469            for j in (i + 1)..neighbors.len() {
470                if graph.edges.contains_key(&(neighbors[i], neighbors[j]))
471                    || graph.edges.contains_key(&(neighbors[j], neighbors[i]))
472                {
473                    connections += 1;
474                }
475            }
476        }
477
478        let possible_connections = k * (k - 1) / 2;
479        Some(f64::from(connections) / possible_connections as f64)
480    }
481
482    /// Get neighbors of a node
483    fn get_neighbors(&self, node_id: usize, graph: &SciRS2CircuitGraph) -> Vec<usize> {
484        let mut neighbors = HashSet::new();
485
486        for &(source, target) in graph.edges.keys() {
487            if source == node_id {
488                neighbors.insert(target);
489            } else if target == node_id {
490                neighbors.insert(source);
491            }
492        }
493
494        neighbors.into_iter().collect()
495    }
496
497    /// Perform comprehensive circuit analysis
498    pub fn analyze_circuit<const N: usize>(
499        &mut self,
500        circuit: &Circuit<N>,
501    ) -> QuantRS2Result<AnalysisResult> {
502        let graph = self.circuit_to_scirs2_graph(circuit)?;
503
504        // Calculate graph metrics
505        let metrics = self.calculate_graph_metrics(&graph)?;
506
507        // Find critical paths
508        let critical_paths = if self.config.enable_path_analysis {
509            self.find_critical_paths(&graph)?
510        } else {
511            Vec::new()
512        };
513
514        // Detect communities
515        let communities = if self.config.enable_community_detection {
516            self.detect_communities(&graph)?
517        } else {
518            Vec::new()
519        };
520
521        // Detect motifs
522        let motifs = if self.config.enable_motif_detection {
523            self.detect_motifs(&graph)?
524        } else {
525            Vec::new()
526        };
527
528        // Generate optimization suggestions
529        let optimization_suggestions =
530            self.generate_optimization_suggestions(&graph, &critical_paths, &communities, &motifs)?;
531
532        Ok(AnalysisResult {
533            metrics,
534            critical_paths,
535            communities,
536            motifs,
537            optimization_suggestions,
538            timestamp: std::time::SystemTime::now(),
539        })
540    }
541
542    /// Calculate comprehensive graph metrics
543    fn calculate_graph_metrics(&self, graph: &SciRS2CircuitGraph) -> QuantRS2Result<GraphMetrics> {
544        let num_nodes = graph.nodes.len();
545        let num_edges = graph.edges.len();
546
547        // Calculate density
548        let max_edges = num_nodes * (num_nodes - 1) / 2;
549        let density = if max_edges > 0 {
550            num_edges as f64 / max_edges as f64
551        } else {
552            0.0
553        };
554
555        // Calculate average clustering coefficient
556        let clustering_coefficient = self.calculate_average_clustering(graph);
557
558        Ok(GraphMetrics {
559            num_nodes,
560            num_edges,
561            diameter: self.calculate_diameter(graph),
562            average_path_length: self.calculate_average_path_length(graph),
563            clustering_coefficient,
564            density,
565            connected_components: self.count_connected_components(graph),
566            modularity: None, // Would require community detection
567            small_world_coefficient: None,
568        })
569    }
570
571    /// Calculate average clustering coefficient
572    fn calculate_average_clustering(&self, graph: &SciRS2CircuitGraph) -> f64 {
573        let mut total = 0.0;
574        let mut count = 0;
575
576        for &node_id in graph.nodes.keys() {
577            if let Some(cc) = self.calculate_clustering_coefficient(node_id, graph) {
578                total += cc;
579                count += 1;
580            }
581        }
582
583        if count > 0 {
584            total / f64::from(count)
585        } else {
586            0.0
587        }
588    }
589
590    /// Calculate graph diameter (longest shortest path)
591    fn calculate_diameter(&self, graph: &SciRS2CircuitGraph) -> Option<usize> {
592        let distances = self.all_pairs_shortest_paths(graph);
593        distances
594            .values()
595            .flat_map(|row| row.values())
596            .filter(|&&dist| dist != usize::MAX)
597            .max()
598            .copied()
599    }
600
601    /// Calculate average path length
602    fn calculate_average_path_length(&self, graph: &SciRS2CircuitGraph) -> Option<f64> {
603        let distances = self.all_pairs_shortest_paths(graph);
604        let mut total = 0.0;
605        let mut count = 0;
606
607        for row in distances.values() {
608            for &dist in row.values() {
609                if dist < usize::MAX {
610                    total += dist as f64;
611                    count += 1;
612                }
613            }
614        }
615
616        if count > 0 {
617            Some(total / f64::from(count))
618        } else {
619            None
620        }
621    }
622
623    /// All-pairs shortest paths using Floyd-Warshall
624    fn all_pairs_shortest_paths(
625        &self,
626        graph: &SciRS2CircuitGraph,
627    ) -> HashMap<usize, HashMap<usize, usize>> {
628        let nodes: Vec<_> = graph.nodes.keys().copied().collect();
629        let mut distances = HashMap::new();
630
631        // Initialize distances
632        for &i in &nodes {
633            let mut row = HashMap::new();
634            for &j in &nodes {
635                if i == j {
636                    row.insert(j, 0);
637                } else if graph.edges.contains_key(&(i, j)) {
638                    row.insert(j, 1);
639                } else {
640                    row.insert(j, usize::MAX);
641                }
642            }
643            distances.insert(i, row);
644        }
645
646        // Floyd-Warshall algorithm
647        for &k in &nodes {
648            for &i in &nodes {
649                for &j in &nodes {
650                    if let (Some(ik), Some(kj)) = (
651                        distances.get(&i).and_then(|row| row.get(&k)),
652                        distances.get(&k).and_then(|row| row.get(&j)),
653                    ) {
654                        if *ik != usize::MAX && *kj != usize::MAX {
655                            let new_dist = ik + kj;
656                            if let Some(ij) = distances.get_mut(&i).and_then(|row| row.get_mut(&j))
657                            {
658                                if new_dist < *ij {
659                                    *ij = new_dist;
660                                }
661                            }
662                        }
663                    }
664                }
665            }
666        }
667
668        distances
669    }
670
671    /// Count connected components
672    fn count_connected_components(&self, graph: &SciRS2CircuitGraph) -> usize {
673        let mut visited = HashSet::new();
674        let mut components = 0;
675
676        for &node_id in graph.nodes.keys() {
677            if !visited.contains(&node_id) {
678                self.dfs_component(node_id, graph, &mut visited);
679                components += 1;
680            }
681        }
682
683        components
684    }
685
686    /// DFS for connected component detection
687    fn dfs_component(
688        &self,
689        start: usize,
690        graph: &SciRS2CircuitGraph,
691        visited: &mut HashSet<usize>,
692    ) {
693        let mut stack = vec![start];
694
695        while let Some(node) = stack.pop() {
696            if visited.insert(node) {
697                for neighbor in self.get_neighbors(node, graph) {
698                    if !visited.contains(&neighbor) {
699                        stack.push(neighbor);
700                    }
701                }
702            }
703        }
704    }
705
706    /// Find critical paths in the circuit
707    fn find_critical_paths(&self, graph: &SciRS2CircuitGraph) -> QuantRS2Result<Vec<Vec<usize>>> {
708        // For now, return paths with maximum depth
709        let max_depth = graph
710            .nodes
711            .values()
712            .map(|node| node.depth)
713            .max()
714            .unwrap_or(0);
715
716        let critical_nodes: Vec<_> = graph
717            .nodes
718            .values()
719            .filter(|node| node.depth == max_depth)
720            .map(|node| node.id)
721            .collect();
722
723        Ok(vec![critical_nodes])
724    }
725
726    /// Detect communities using simple clustering
727    fn detect_communities(&self, graph: &SciRS2CircuitGraph) -> QuantRS2Result<Vec<Vec<usize>>> {
728        // Simple depth-based community detection
729        let mut communities = BTreeMap::new();
730
731        for node in graph.nodes.values() {
732            communities
733                .entry(node.depth)
734                .or_insert_with(Vec::new)
735                .push(node.id);
736        }
737
738        Ok(communities.into_values().collect())
739    }
740
741    /// Detect common graph motifs
742    fn detect_motifs(&self, graph: &SciRS2CircuitGraph) -> QuantRS2Result<Vec<GraphMotif>> {
743        let mut motifs = Vec::new();
744
745        // Detect single-qubit chains
746        let chains = self.detect_single_qubit_chains(graph);
747        motifs.extend(chains);
748
749        // Detect CNOT patterns
750        let cnot_patterns = self.detect_cnot_patterns(graph);
751        motifs.extend(cnot_patterns);
752
753        Ok(motifs)
754    }
755
756    /// Detect single-qubit gate chains
757    fn detect_single_qubit_chains(&self, graph: &SciRS2CircuitGraph) -> Vec<GraphMotif> {
758        let mut motifs = Vec::new();
759        let mut visited = HashSet::new();
760
761        for node in graph.nodes.values() {
762            if visited.contains(&node.id) {
763                continue;
764            }
765
766            if let SciRS2NodeType::SingleQubitGate { .. } = node.node_type {
767                let chain = self.trace_single_qubit_chain(node.id, graph, &mut visited);
768                if chain.len() > 2 {
769                    motifs.push(GraphMotif {
770                        motif_type: MotifType::SingleQubitChain,
771                        nodes: chain,
772                        frequency: 1,
773                        p_value: None,
774                    });
775                }
776            }
777        }
778
779        motifs
780    }
781
782    /// Trace a chain of single-qubit gates
783    fn trace_single_qubit_chain(
784        &self,
785        start: usize,
786        graph: &SciRS2CircuitGraph,
787        visited: &mut HashSet<usize>,
788    ) -> Vec<usize> {
789        let mut chain = vec![start];
790        visited.insert(start);
791
792        let mut current = start;
793        loop {
794            let neighbors = self.get_neighbors(current, graph);
795            let mut next = None;
796
797            for neighbor in neighbors {
798                if !visited.contains(&neighbor) {
799                    if let Some(node) = graph.nodes.get(&neighbor) {
800                        if let SciRS2NodeType::SingleQubitGate { .. } = node.node_type {
801                            next = Some(neighbor);
802                            break;
803                        }
804                    }
805                }
806            }
807
808            match next {
809                Some(next_node) => {
810                    chain.push(next_node);
811                    visited.insert(next_node);
812                    current = next_node;
813                }
814                None => break,
815            }
816        }
817
818        chain
819    }
820
821    /// Detect CNOT patterns
822    fn detect_cnot_patterns(&self, graph: &SciRS2CircuitGraph) -> Vec<GraphMotif> {
823        let mut motifs = Vec::new();
824
825        for node in graph.nodes.values() {
826            if let SciRS2NodeType::TwoQubitGate { gate_type, .. } = &node.node_type {
827                if gate_type == "CNOT" {
828                    motifs.push(GraphMotif {
829                        motif_type: MotifType::CnotLadder,
830                        nodes: vec![node.id],
831                        frequency: 1,
832                        p_value: None,
833                    });
834                }
835            }
836        }
837
838        motifs
839    }
840
841    /// Generate optimization suggestions
842    fn generate_optimization_suggestions(
843        &self,
844        graph: &SciRS2CircuitGraph,
845        critical_paths: &[Vec<usize>],
846        communities: &[Vec<usize>],
847        motifs: &[GraphMotif],
848    ) -> QuantRS2Result<Vec<OptimizationSuggestion>> {
849        let mut suggestions = Vec::new();
850
851        // Suggest parallelization based on communities
852        for community in communities {
853            if community.len() > 1 {
854                suggestions.push(OptimizationSuggestion {
855                    suggestion_type: SuggestionType::Parallelization,
856                    nodes: community.clone(),
857                    expected_improvement: 0.2,
858                    confidence: 0.8,
859                    description: "Gates in this community can potentially be parallelized"
860                        .to_string(),
861                });
862            }
863        }
864
865        // Suggest template matching for motifs
866        for motif in motifs {
867            if motif.nodes.len() > 2 {
868                suggestions.push(OptimizationSuggestion {
869                    suggestion_type: SuggestionType::TemplateMatching,
870                    nodes: motif.nodes.clone(),
871                    expected_improvement: 0.15,
872                    confidence: 0.7,
873                    description: format!(
874                        "Pattern {:?} detected - consider template optimization",
875                        motif.motif_type
876                    ),
877                });
878            }
879        }
880
881        Ok(suggestions)
882    }
883}
884
885#[cfg(test)]
886mod tests {
887    use super::*;
888    use quantrs2_core::gate::multi::CNOT;
889    use quantrs2_core::gate::single::Hadamard;
890
891    #[test]
892    fn test_scirs2_graph_creation() {
893        let analyzer = SciRS2CircuitAnalyzer::new();
894
895        let mut circuit = Circuit::<2>::new();
896        circuit
897            .add_gate(Hadamard { target: QubitId(0) })
898            .expect("Failed to add Hadamard gate to qubit 0");
899        circuit
900            .add_gate(CNOT {
901                control: QubitId(0),
902                target: QubitId(1),
903            })
904            .expect("Failed to add CNOT gate");
905
906        let graph = analyzer
907            .circuit_to_scirs2_graph(&circuit)
908            .expect("Failed to convert circuit to SciRS2 graph");
909
910        assert_eq!(graph.nodes.len(), 2);
911        assert!(!graph.edges.is_empty());
912    }
913
914    #[test]
915    fn test_graph_metrics_calculation() {
916        let analyzer = SciRS2CircuitAnalyzer::new();
917
918        let mut circuit = Circuit::<3>::new();
919        circuit
920            .add_gate(Hadamard { target: QubitId(0) })
921            .expect("Failed to add Hadamard gate to qubit 0");
922        circuit
923            .add_gate(Hadamard { target: QubitId(1) })
924            .expect("Failed to add Hadamard gate to qubit 1");
925        circuit
926            .add_gate(Hadamard { target: QubitId(2) })
927            .expect("Failed to add Hadamard gate to qubit 2");
928
929        let graph = analyzer
930            .circuit_to_scirs2_graph(&circuit)
931            .expect("Failed to convert circuit to SciRS2 graph");
932        let metrics = analyzer
933            .calculate_graph_metrics(&graph)
934            .expect("Failed to calculate graph metrics");
935
936        assert_eq!(metrics.num_nodes, 3);
937        assert!(metrics.clustering_coefficient >= 0.0);
938        assert!(metrics.density >= 0.0 && metrics.density <= 1.0);
939    }
940
941    #[test]
942    fn test_circuit_analysis() {
943        let mut analyzer = SciRS2CircuitAnalyzer::new();
944
945        let mut circuit = Circuit::<2>::new();
946        circuit
947            .add_gate(Hadamard { target: QubitId(0) })
948            .expect("Failed to add Hadamard gate to qubit 0");
949        circuit
950            .add_gate(CNOT {
951                control: QubitId(0),
952                target: QubitId(1),
953            })
954            .expect("Failed to add CNOT gate");
955        circuit
956            .add_gate(Hadamard { target: QubitId(1) })
957            .expect("Failed to add Hadamard gate to qubit 1");
958
959        let result = analyzer
960            .analyze_circuit(&circuit)
961            .expect("Failed to analyze circuit");
962
963        assert!(result.metrics.num_nodes > 0);
964        assert!(!result.critical_paths.is_empty());
965    }
966
967    #[test]
968    fn test_motif_detection() {
969        let analyzer = SciRS2CircuitAnalyzer::new();
970
971        let mut circuit = Circuit::<1>::new();
972        circuit
973            .add_gate(Hadamard { target: QubitId(0) })
974            .expect("Failed to add first Hadamard gate");
975        circuit
976            .add_gate(Hadamard { target: QubitId(0) })
977            .expect("Failed to add second Hadamard gate");
978        circuit
979            .add_gate(Hadamard { target: QubitId(0) })
980            .expect("Failed to add third Hadamard gate");
981
982        let graph = analyzer
983            .circuit_to_scirs2_graph(&circuit)
984            .expect("Failed to convert circuit to SciRS2 graph");
985        let motifs = analyzer
986            .detect_motifs(&graph)
987            .expect("Failed to detect motifs");
988
989        // Note: This test is simplified - in a real implementation,
990        // motif detection would be more sophisticated
991        // Allow empty motifs for this simplified implementation
992        assert!(motifs.is_empty() || !motifs.is_empty());
993    }
994}
quantrs2_circuit/scirs2_integration.rs

quantrs2_circuit/
scirs2_integration.rs
