quantrs2-ml 0.1.3

Quantum Machine Learning module for QuantRS2
Documentation
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
//! Device-specific model compilation for quantum machine learning
//!
//! This module provides device-aware compilation of quantum ML models,
//! optimizing circuits for specific hardware characteristics and constraints.

use crate::circuit_integration::{DeviceTopology, QubitProperties};
use crate::error::{MLError, Result};
use quantrs2_circuit::prelude::*;
use quantrs2_core::prelude::*;
use scirs2_core::ndarray::{Array1, Array2};
use std::collections::{HashMap, HashSet, VecDeque};

/// Device-specific model compiler
pub struct DeviceCompiler {
    /// Target device topology
    topology: DeviceTopology,
    /// Compilation options
    options: CompilationOptions,
    /// Device characterization data
    characterization: DeviceCharacterization,
}

/// Compilation options
#[derive(Debug, Clone)]
pub struct CompilationOptions {
    /// Optimization level (0-3)
    pub optimization_level: u8,
    /// Maximum compilation time (seconds)
    pub max_compilation_time: f64,
    /// Target gate error threshold
    pub error_threshold: f64,
    /// Enable noise-aware compilation
    pub noise_aware: bool,
    /// Enable crosstalk mitigation
    pub crosstalk_mitigation: bool,
    /// Routing algorithm
    pub routing_algorithm: RoutingAlgorithm,
    /// Gate synthesis method
    pub synthesis_method: SynthesisMethod,
}

impl Default for CompilationOptions {
    fn default() -> Self {
        Self {
            optimization_level: 2,
            max_compilation_time: 60.0,
            error_threshold: 0.01,
            noise_aware: true,
            crosstalk_mitigation: true,
            routing_algorithm: RoutingAlgorithm::SABRE,
            synthesis_method: SynthesisMethod::SolovayKitaev,
        }
    }
}

/// Routing algorithms
#[derive(Debug, Clone, Copy)]
pub enum RoutingAlgorithm {
    /// SABRE routing algorithm
    SABRE,
    /// Lookahead routing
    Lookahead,
    /// Token swapping
    TokenSwapping,
    /// Heuristic routing
    Heuristic,
}

/// Gate synthesis methods
#[derive(Debug, Clone, Copy)]
pub enum SynthesisMethod {
    /// Solovay-Kitaev decomposition
    SolovayKitaev,
    /// Shannon decomposition
    Shannon,
    /// KAK decomposition for two-qubit gates
    KAK,
    /// Cartan decomposition
    Cartan,
}

/// Device characterization data
#[derive(Debug, Clone)]
pub struct DeviceCharacterization {
    /// Gate error rates
    pub gate_errors: HashMap<String, f64>,
    /// Two-qubit gate errors (by qubit pair)
    pub two_qubit_errors: HashMap<(usize, usize), f64>,
    /// Readout errors
    pub readout_errors: Array1<f64>,
    /// Crosstalk matrix
    pub crosstalk_matrix: Array2<f64>,
    /// Gate times
    pub gate_times: HashMap<String, f64>,
    /// Calibration timestamp
    pub calibration_time: std::time::SystemTime,
}

impl DeviceCharacterization {
    /// Create default characterization
    pub fn default_for_device(num_qubits: usize) -> Self {
        let mut gate_errors = HashMap::new();
        gate_errors.insert("X".to_string(), 0.001);
        gate_errors.insert("Y".to_string(), 0.001);
        gate_errors.insert("Z".to_string(), 0.0001);
        gate_errors.insert("H".to_string(), 0.002);
        gate_errors.insert("CNOT".to_string(), 0.01);

        let mut gate_times = HashMap::new();
        gate_times.insert("X".to_string(), 0.02); // 20 ns
        gate_times.insert("Y".to_string(), 0.02);
        gate_times.insert("Z".to_string(), 0.0); // Virtual Z
        gate_times.insert("H".to_string(), 0.02);
        gate_times.insert("CNOT".to_string(), 0.2); // 200 ns

        Self {
            gate_errors,
            two_qubit_errors: HashMap::new(),
            readout_errors: Array1::from_elem(num_qubits, 0.02),
            crosstalk_matrix: Array2::zeros((num_qubits, num_qubits)),
            gate_times,
            calibration_time: std::time::SystemTime::now(),
        }
    }

    /// Update gate error for specific qubits
    pub fn set_gate_error(&mut self, gate: &str, qubits: &[usize], error: f64) {
        if qubits.len() == 2 {
            self.two_qubit_errors.insert((qubits[0], qubits[1]), error);
        } else {
            self.gate_errors.insert(gate.to_string(), error);
        }
    }

    /// Get expected error for a gate operation
    pub fn get_gate_error(&self, gate: &str, qubits: &[usize]) -> f64 {
        if qubits.len() == 2 {
            self.two_qubit_errors
                .get(&(qubits[0], qubits[1]))
                .or_else(|| self.two_qubit_errors.get(&(qubits[1], qubits[0])))
                .copied()
                .unwrap_or_else(|| self.gate_errors.get(gate).copied().unwrap_or(0.01))
        } else {
            self.gate_errors.get(gate).copied().unwrap_or(0.001)
        }
    }
}

impl DeviceCompiler {
    /// Create a new device compiler
    pub fn new(topology: DeviceTopology) -> Self {
        let num_qubits = topology.num_qubits();
        Self {
            topology,
            options: CompilationOptions::default(),
            characterization: DeviceCharacterization::default_for_device(num_qubits),
        }
    }

    /// Set compilation options
    pub fn with_options(mut self, options: CompilationOptions) -> Self {
        self.options = options;
        self
    }

    /// Set device characterization
    pub fn with_characterization(mut self, characterization: DeviceCharacterization) -> Self {
        self.characterization = characterization;
        self
    }

    /// Compile quantum ML model for target device
    pub fn compile_model<const N: usize>(
        &self,
        model: &QuantumMLModel,
    ) -> Result<CompiledModel<N>> {
        let start_time = std::time::Instant::now();

        // Step 1: Convert model to circuit representation
        let mut circuit = self.model_to_circuit::<N>(model)?;

        // Step 2: Initial circuit optimization
        circuit = self.initial_optimization::<N>(&circuit)?;

        // Step 3: Qubit mapping and routing
        let (mut circuit, qubit_mapping) = self.route_circuit::<N>(&circuit)?;

        // Step 4: Gate synthesis for native gate set
        circuit = self.synthesize_gates::<N>(&circuit)?;

        // Step 5: Noise-aware optimization
        if self.options.noise_aware {
            circuit = self.noise_aware_optimization::<N>(&circuit)?;
        }

        // Step 6: Crosstalk mitigation
        if self.options.crosstalk_mitigation {
            circuit = self.mitigate_crosstalk::<N>(&circuit)?;
        }

        // Step 7: Final optimization
        circuit = self.final_optimization::<N>(&circuit)?;

        let compilation_time = start_time.elapsed().as_secs_f64();

        // Generate compilation metrics
        let metrics = self.analyze_compiled_circuit::<N>(&circuit, compilation_time)?;

        Ok(CompiledModel {
            circuit,
            qubit_mapping,
            metrics,
            target_device: self.topology.clone(),
            characterization: self.characterization.clone(),
        })
    }

    /// Convert ML model to quantum circuit
    fn model_to_circuit<const N: usize>(&self, model: &QuantumMLModel) -> Result<Circuit<N>> {
        let mut builder = CircuitBuilder::<N>::new();

        // Add model layers to circuit
        for layer in &model.layers {
            match layer {
                ModelLayer::Encoding(encoding_layer) => {
                    self.add_encoding_layer::<N>(&mut builder, encoding_layer)?;
                }
                ModelLayer::Variational(var_layer) => {
                    self.add_variational_layer::<N>(&mut builder, var_layer)?;
                }
                ModelLayer::Measurement(meas_layer) => {
                    self.add_measurement_layer::<N>(&mut builder, meas_layer)?;
                }
            }
        }

        Ok(builder.build())
    }

    /// Add encoding layer to circuit
    fn add_encoding_layer<const N: usize>(
        &self,
        builder: &mut CircuitBuilder<N>,
        layer: &EncodingLayer,
    ) -> Result<()> {
        match &layer.encoding_type {
            EncodingType::Amplitude => {
                // Add amplitude encoding gates
                for qubit in &layer.qubits {
                    builder.ry(*qubit, 0.0)?; // Placeholder parameter
                }
            }
            EncodingType::Angle => {
                // Add angle encoding gates
                for qubit in &layer.qubits {
                    builder.rz(*qubit, 0.0)?; // Placeholder parameter
                }
            }
            EncodingType::Basis => {
                // Add basis encoding (no gates needed)
            }
        }
        Ok(())
    }

    /// Add variational layer to circuit
    fn add_variational_layer<const N: usize>(
        &self,
        builder: &mut CircuitBuilder<N>,
        layer: &VariationalLayer,
    ) -> Result<()> {
        match &layer.ansatz_type {
            AnsatzType::HardwareEfficient => {
                // Add hardware-efficient ansatz
                for qubit in &layer.qubits {
                    builder.ry(*qubit, 0.0)?;
                    builder.rz(*qubit, 0.0)?;
                }

                // Add entangling gates
                for i in 0..layer.qubits.len() - 1 {
                    builder.cnot(layer.qubits[i], layer.qubits[i + 1])?;
                }
            }
            AnsatzType::QAOA => {
                // Add QAOA ansatz
                for qubit in &layer.qubits {
                    builder.rx(*qubit, 0.0)?; // Mixer
                }

                // Problem-specific gates would be added here
            }
            AnsatzType::Custom(gates) => {
                // Add custom gate sequence
                for gate in gates {
                    self.add_custom_gate(builder, gate)?;
                }
            }
        }
        Ok(())
    }

    /// Add measurement layer to circuit
    fn add_measurement_layer<const N: usize>(
        &self,
        builder: &mut CircuitBuilder<N>,
        layer: &MeasurementLayer,
    ) -> Result<()> {
        for qubit in &layer.qubits {
            // builder.measure(*qubit)?; // Measurement method needs to be implemented
        }
        Ok(())
    }

    /// Add custom gate to circuit
    fn add_custom_gate<const N: usize>(
        &self,
        builder: &mut CircuitBuilder<N>,
        gate: &CustomGate,
    ) -> Result<()> {
        match gate {
            CustomGate::SingleQubit {
                qubit,
                gate_type,
                parameter,
            } => match gate_type.as_str() {
                "RX" => {
                    builder.rx(*qubit, *parameter)?;
                }
                "RY" => {
                    builder.ry(*qubit, *parameter)?;
                }
                "RZ" => {
                    builder.rz(*qubit, *parameter)?;
                }
                "H" => {
                    builder.h(*qubit)?;
                }
                _ => {
                    return Err(MLError::InvalidConfiguration(format!(
                        "Unknown gate type: {}",
                        gate_type
                    )))
                }
            },
            CustomGate::TwoQubit {
                control,
                target,
                gate_type,
                parameter,
            } => {
                match gate_type.as_str() {
                    "CNOT" => {
                        builder.cnot(*control, *target)?;
                    }
                    "CZ" => {
                        builder.cz(*control, *target)?;
                    }
                    "RZZ" => {
                        builder.crz(*control, *target, *parameter)?;
                    } // Using CRZ as approximation
                    _ => {
                        return Err(MLError::InvalidConfiguration(format!(
                            "Unknown two-qubit gate type: {}",
                            gate_type
                        )))
                    }
                }
            }
        }
        Ok(())
    }

    /// Initial circuit optimization
    fn initial_optimization<const N: usize>(&self, circuit: &Circuit<N>) -> Result<Circuit<N>> {
        let mut optimized = circuit.clone();

        if self.options.optimization_level >= 1 {
            // Remove redundant gates
            optimized = self.remove_redundant_gates::<N>(&optimized)?;
        }

        if self.options.optimization_level >= 2 {
            // Merge rotation gates
            optimized = self.merge_rotations::<N>(&optimized)?;
        }

        if self.options.optimization_level >= 3 {
            // Advanced optimizations
            optimized = self.commutation_optimization::<N>(&optimized)?;
        }

        Ok(optimized)
    }

    /// Route circuit to device topology
    fn route_circuit<const N: usize>(
        &self,
        circuit: &Circuit<N>,
    ) -> Result<(Circuit<N>, QubitMapping)> {
        match self.options.routing_algorithm {
            RoutingAlgorithm::SABRE => self.sabre_routing(circuit),
            RoutingAlgorithm::Lookahead => self.lookahead_routing(circuit),
            RoutingAlgorithm::TokenSwapping => self.token_swapping_routing(circuit),
            RoutingAlgorithm::Heuristic => self.heuristic_routing(circuit),
        }
    }

    /// SABRE routing algorithm
    fn sabre_routing<const N: usize>(
        &self,
        circuit: &Circuit<N>,
    ) -> Result<(Circuit<N>, QubitMapping)> {
        let mut routed_circuit = CircuitBuilder::<N>::new();
        let mut mapping = QubitMapping::identity(circuit.num_qubits());

        // SABRE algorithm implementation (simplified)
        for gate in circuit.gates() {
            if gate.num_qubits() == 2 {
                let (q1, q2) = (gate.qubits()[0], gate.qubits()[1]);
                if !self.topology.are_connected(
                    mapping.logical_to_physical(q1.into()),
                    mapping.logical_to_physical(q2.into()),
                ) {
                    // Insert SWAP gates to make qubits adjacent
                    let swaps = self.find_swap_path(
                        mapping.logical_to_physical(q1.into()),
                        mapping.logical_to_physical(q2.into()),
                    )?;

                    for (qa, qb) in swaps {
                        routed_circuit.swap(qa, qb)?;
                        mapping.apply_swap(qa, qb);
                    }
                }
            }

            // Add the original gate with mapped qubits
            self.add_mapped_gate::<N>(&mut routed_circuit, gate.as_ref(), &mapping)?;
        }

        Ok((routed_circuit.build(), mapping))
    }

    /// Find shortest path of SWAPs between qubits
    fn find_swap_path(&self, start: usize, end: usize) -> Result<Vec<(usize, usize)>> {
        // Simplified shortest path algorithm
        let mut queue = VecDeque::new();
        let mut visited = HashSet::new();
        let mut parent = HashMap::new();

        queue.push_back(start);
        visited.insert(start);

        while let Some(current) = queue.pop_front() {
            if current == end {
                // Reconstruct path
                let mut path = Vec::new();
                let mut node = end;
                while let Some(&prev) = parent.get(&node) {
                    path.push((prev, node));
                    node = prev;
                }
                path.reverse();
                return Ok(path);
            }

            for neighbor in self.topology.neighbors(current) {
                if !visited.contains(&neighbor) {
                    visited.insert(neighbor);
                    parent.insert(neighbor, current);
                    queue.push_back(neighbor);
                }
            }
        }

        Err(MLError::InvalidConfiguration(
            "No path found between qubits".to_string(),
        ))
    }

    /// Other routing algorithms (simplified implementations)
    fn lookahead_routing<const N: usize>(
        &self,
        circuit: &Circuit<N>,
    ) -> Result<(Circuit<N>, QubitMapping)> {
        // Placeholder - would implement lookahead routing
        self.sabre_routing(circuit)
    }

    fn token_swapping_routing<const N: usize>(
        &self,
        circuit: &Circuit<N>,
    ) -> Result<(Circuit<N>, QubitMapping)> {
        // Placeholder - would implement token swapping
        self.sabre_routing(circuit)
    }

    fn heuristic_routing<const N: usize>(
        &self,
        circuit: &Circuit<N>,
    ) -> Result<(Circuit<N>, QubitMapping)> {
        // Placeholder - would implement heuristic routing
        self.sabre_routing(circuit)
    }

    /// Add gate with mapped qubits
    fn add_mapped_gate<const N: usize>(
        &self,
        builder: &mut CircuitBuilder<N>,
        gate: &dyn GateOp,
        mapping: &QubitMapping,
    ) -> Result<()> {
        let mapped_qubits: Vec<usize> = gate
            .qubits()
            .iter()
            .map(|&q| mapping.logical_to_physical(q.into()))
            .collect();

        match gate.name() {
            "H" => {
                builder.h(mapped_qubits[0])?;
            }
            "X" => {
                builder.x(mapped_qubits[0])?;
            }
            "Y" => {
                builder.y(mapped_qubits[0])?;
            }
            "Z" => {
                builder.z(mapped_qubits[0])?;
            }
            "RX" => {
                let theta = gate
                    .as_any()
                    .downcast_ref::<single::RotationX>()
                    .map(|g| g.theta)
                    .unwrap_or(0.0);
                builder.rx(mapped_qubits[0], theta)?;
            }
            "RY" => {
                let theta = gate
                    .as_any()
                    .downcast_ref::<single::RotationY>()
                    .map(|g| g.theta)
                    .unwrap_or(0.0);
                builder.ry(mapped_qubits[0], theta)?;
            }
            "RZ" => {
                let theta = gate
                    .as_any()
                    .downcast_ref::<single::RotationZ>()
                    .map(|g| g.theta)
                    .unwrap_or(0.0);
                builder.rz(mapped_qubits[0], theta)?;
            }
            "CNOT" => {
                builder.cnot(mapped_qubits[0], mapped_qubits[1])?;
            }
            "CZ" => {
                builder.cz(mapped_qubits[0], mapped_qubits[1])?;
            }
            "SWAP" => {
                builder.swap(mapped_qubits[0], mapped_qubits[1])?;
            }
            _ => {
                return Err(MLError::InvalidConfiguration(format!(
                    "Unknown gate type: {}",
                    gate.name()
                )))
            }
        }

        Ok(())
    }

    /// Gate synthesis for native gate set
    fn synthesize_gates<const N: usize>(&self, circuit: &Circuit<N>) -> Result<Circuit<N>> {
        match self.options.synthesis_method {
            SynthesisMethod::SolovayKitaev => self.solovay_kitaev_synthesis(circuit),
            SynthesisMethod::Shannon => self.shannon_synthesis(circuit),
            SynthesisMethod::KAK => self.kak_synthesis(circuit),
            SynthesisMethod::Cartan => self.cartan_synthesis(circuit),
        }
    }

    /// Solovay-Kitaev synthesis
    fn solovay_kitaev_synthesis<const N: usize>(&self, circuit: &Circuit<N>) -> Result<Circuit<N>> {
        // Placeholder - would implement Solovay-Kitaev decomposition
        Ok(circuit.clone())
    }

    /// Shannon synthesis
    fn shannon_synthesis<const N: usize>(&self, circuit: &Circuit<N>) -> Result<Circuit<N>> {
        // Placeholder - would implement Shannon decomposition
        Ok(circuit.clone())
    }

    /// KAK synthesis
    fn kak_synthesis<const N: usize>(&self, circuit: &Circuit<N>) -> Result<Circuit<N>> {
        // Placeholder - would implement KAK decomposition
        Ok(circuit.clone())
    }

    /// Cartan synthesis
    fn cartan_synthesis<const N: usize>(&self, circuit: &Circuit<N>) -> Result<Circuit<N>> {
        // Placeholder - would implement Cartan decomposition
        Ok(circuit.clone())
    }

    /// Noise-aware optimization
    fn noise_aware_optimization<const N: usize>(&self, circuit: &Circuit<N>) -> Result<Circuit<N>> {
        let mut optimized = circuit.clone();

        // Reschedule gates to minimize decoherence
        optimized = self.schedule_for_coherence::<N>(&optimized)?;

        // Choose error-optimal gates
        optimized = self.select_low_error_gates::<N>(&optimized)?;

        Ok(optimized)
    }

    /// Schedule gates to minimize decoherence
    fn schedule_for_coherence<const N: usize>(&self, circuit: &Circuit<N>) -> Result<Circuit<N>> {
        // Placeholder - would implement coherence-aware scheduling
        Ok(circuit.clone())
    }

    /// Select gates with lowest error rates
    fn select_low_error_gates<const N: usize>(&self, circuit: &Circuit<N>) -> Result<Circuit<N>> {
        // Placeholder - would select optimal gates based on characterization
        Ok(circuit.clone())
    }

    /// Mitigate crosstalk effects
    fn mitigate_crosstalk<const N: usize>(&self, circuit: &Circuit<N>) -> Result<Circuit<N>> {
        // Placeholder - would implement crosstalk mitigation
        Ok(circuit.clone())
    }

    /// Final optimization pass
    fn final_optimization<const N: usize>(&self, circuit: &Circuit<N>) -> Result<Circuit<N>> {
        let mut optimized = circuit.clone();

        // Final gate merging
        optimized = self.merge_rotations::<N>(&optimized)?;

        // Remove identity gates
        optimized = self.remove_identity_gates::<N>(&optimized)?;

        Ok(optimized)
    }

    /// Remove redundant gates
    fn remove_redundant_gates<const N: usize>(&self, circuit: &Circuit<N>) -> Result<Circuit<N>> {
        // Placeholder - would implement redundant gate removal
        Ok(circuit.clone())
    }

    /// Merge rotation gates
    fn merge_rotations<const N: usize>(&self, circuit: &Circuit<N>) -> Result<Circuit<N>> {
        // Placeholder - would merge consecutive rotation gates
        Ok(circuit.clone())
    }

    /// Commutation-based optimization
    fn commutation_optimization<const N: usize>(&self, circuit: &Circuit<N>) -> Result<Circuit<N>> {
        // Placeholder - would implement commutation rules
        Ok(circuit.clone())
    }

    /// Remove identity gates
    fn remove_identity_gates<const N: usize>(&self, circuit: &Circuit<N>) -> Result<Circuit<N>> {
        // Placeholder - would remove gates with zero rotation angles
        Ok(circuit.clone())
    }

    /// Analyze compiled circuit
    fn analyze_compiled_circuit<const N: usize>(
        &self,
        circuit: &Circuit<N>,
        compilation_time: f64,
    ) -> Result<CompilationMetrics> {
        let gate_count = circuit.num_gates();
        // Compute circuit depth as the length of the critical path through the gate dependency DAG.
        // For each qubit, track the depth of the last gate applied; a gate's layer is
        // max(last_layer[q] for q in gate.qubits()) + 1.  The circuit depth is the maximum
        // layer index reached across all gates.
        let depth = {
            let gates = circuit.gates();
            // Map from qubit index to the depth at which the most recent gate on that qubit sits.
            let mut qubit_depth: HashMap<usize, usize> = HashMap::new();
            let mut max_depth: usize = 0;
            for gate in gates {
                let qubits_usize: Vec<usize> = gate.qubits().iter().map(|&q| q.into()).collect();
                let gate_layer = qubits_usize
                    .iter()
                    .map(|q| qubit_depth.get(q).copied().unwrap_or(0))
                    .max()
                    .unwrap_or(0)
                    + 1;
                for q in &qubits_usize {
                    qubit_depth.insert(*q, gate_layer);
                }
                if gate_layer > max_depth {
                    max_depth = gate_layer;
                }
            }
            max_depth
        };
        let two_qubit_gate_count = circuit
            .gates()
            .iter()
            .filter(|g| g.num_qubits() == 2)
            .count();

        // Estimate total error
        let mut total_error = 0.0;
        for gate in circuit.gates() {
            let qubits_usize: Vec<usize> = gate.qubits().iter().map(|&q| q.into()).collect();
            total_error += self
                .characterization
                .get_gate_error(gate.name(), &qubits_usize);
        }

        // Estimate execution time
        let mut execution_time = 0.0;
        for gate in circuit.gates() {
            execution_time += self
                .characterization
                .gate_times
                .get(gate.name())
                .copied()
                .unwrap_or(0.1);
        }

        Ok(CompilationMetrics {
            gate_count,
            depth,
            two_qubit_gate_count,
            total_error,
            execution_time,
            compilation_time,
            swap_count: 0, // Would count actual SWAPs
        })
    }
}

/// Quantum ML model representation
#[derive(Debug, Clone)]
pub struct QuantumMLModel {
    /// Model layers
    pub layers: Vec<ModelLayer>,
    /// Total number of qubits
    pub num_qubits: usize,
    /// Parameter count
    pub num_parameters: usize,
}

/// Model layer types
#[derive(Debug, Clone)]
pub enum ModelLayer {
    /// Data encoding layer
    Encoding(EncodingLayer),
    /// Variational layer
    Variational(VariationalLayer),
    /// Measurement layer
    Measurement(MeasurementLayer),
}

/// Data encoding layer
#[derive(Debug, Clone)]
pub struct EncodingLayer {
    /// Qubits used for encoding
    pub qubits: Vec<usize>,
    /// Encoding method
    pub encoding_type: EncodingType,
}

/// Data encoding types
#[derive(Debug, Clone)]
pub enum EncodingType {
    /// Amplitude encoding
    Amplitude,
    /// Angle encoding
    Angle,
    /// Basis encoding
    Basis,
}

/// Variational layer
#[derive(Debug, Clone)]
pub struct VariationalLayer {
    /// Qubits in the layer
    pub qubits: Vec<usize>,
    /// Ansatz type
    pub ansatz_type: AnsatzType,
    /// Number of repetitions
    pub repetitions: usize,
}

/// Ansatz types
#[derive(Debug, Clone)]
pub enum AnsatzType {
    /// Hardware-efficient ansatz
    HardwareEfficient,
    /// QAOA ansatz
    QAOA,
    /// Custom gate sequence
    Custom(Vec<CustomGate>),
}

/// Custom gate definition
#[derive(Debug, Clone)]
pub enum CustomGate {
    /// Single-qubit gate
    SingleQubit {
        qubit: usize,
        gate_type: String,
        parameter: f64,
    },
    /// Two-qubit gate
    TwoQubit {
        control: usize,
        target: usize,
        gate_type: String,
        parameter: f64,
    },
}

/// Measurement layer
#[derive(Debug, Clone)]
pub struct MeasurementLayer {
    /// Qubits to measure
    pub qubits: Vec<usize>,
    /// Measurement basis
    pub basis: MeasurementBasis,
}

/// Measurement basis
#[derive(Debug, Clone)]
pub enum MeasurementBasis {
    /// Computational basis (Z)
    Computational,
    /// X basis
    X,
    /// Y basis
    Y,
    /// Custom Pauli string
    Pauli(String),
}

/// Compiled model
#[derive(Debug, Clone)]
pub struct CompiledModel<const N: usize> {
    /// Compiled circuit
    pub circuit: Circuit<N>,
    /// Qubit mapping
    pub qubit_mapping: QubitMapping,
    /// Compilation metrics
    pub metrics: CompilationMetrics,
    /// Target device
    pub target_device: DeviceTopology,
    /// Device characterization
    pub characterization: DeviceCharacterization,
}

/// Qubit mapping between logical and physical qubits
#[derive(Debug, Clone)]
pub struct QubitMapping {
    /// Logical to physical mapping
    logical_to_physical: Vec<usize>,
    /// Physical to logical mapping
    physical_to_logical: Vec<Option<usize>>,
}

impl QubitMapping {
    /// Create identity mapping
    pub fn identity(num_qubits: usize) -> Self {
        Self {
            logical_to_physical: (0..num_qubits).collect(),
            physical_to_logical: (0..num_qubits).map(Some).collect(),
        }
    }

    /// Get physical qubit for logical qubit
    pub fn logical_to_physical(&self, logical: usize) -> usize {
        self.logical_to_physical[logical]
    }

    /// Get logical qubit for physical qubit
    pub fn physical_to_logical(&self, physical: usize) -> Option<usize> {
        self.physical_to_logical.get(physical).copied().flatten()
    }

    /// Apply SWAP operation to mapping
    pub fn apply_swap(&mut self, q1: usize, q2: usize) {
        // Update logical to physical mapping
        for logical in &mut self.logical_to_physical {
            if *logical == q1 {
                *logical = q2;
            } else if *logical == q2 {
                *logical = q1;
            }
        }

        // Update physical to logical mapping
        self.physical_to_logical.swap(q1, q2);
    }
}

/// Compilation metrics
#[derive(Debug, Clone)]
pub struct CompilationMetrics {
    /// Total gate count
    pub gate_count: usize,
    /// Circuit depth
    pub depth: usize,
    /// Two-qubit gate count
    pub two_qubit_gate_count: usize,
    /// Total error estimate
    pub total_error: f64,
    /// Execution time estimate (microseconds)
    pub execution_time: f64,
    /// Compilation time (seconds)
    pub compilation_time: f64,
    /// Number of SWAP gates added
    pub swap_count: usize,
}

#[cfg(test)]
mod tests {
    use super::*;
    use crate::circuit_integration::DeviceTopology;

    #[test]
    fn test_device_compiler_creation() {
        let topology = DeviceTopology::new(5)
            .add_edge(0, 1)
            .add_edge(1, 2)
            .add_edge(2, 3)
            .add_edge(3, 4);

        let compiler = DeviceCompiler::new(topology);
        assert_eq!(compiler.options.optimization_level, 2);
    }

    #[test]
    fn test_device_characterization() {
        let mut char = DeviceCharacterization::default_for_device(3);
        char.set_gate_error("CNOT", &[0, 1], 0.005);

        assert_eq!(char.get_gate_error("CNOT", &[0, 1]), 0.005);
        assert_eq!(char.get_gate_error("X", &[0]), 0.001);
    }

    #[test]
    fn test_qubit_mapping() {
        let mut mapping = QubitMapping::identity(3);
        assert_eq!(mapping.logical_to_physical(1), 1);

        mapping.apply_swap(0, 2);
        assert_eq!(mapping.logical_to_physical(0), 2);
        assert_eq!(mapping.logical_to_physical(2), 0);
    }

    #[test]
    fn test_compilation_options() {
        let options = CompilationOptions {
            optimization_level: 3,
            noise_aware: false,
            routing_algorithm: RoutingAlgorithm::Lookahead,
            ..Default::default()
        };

        assert_eq!(options.optimization_level, 3);
        assert!(!options.noise_aware);
    }
}