quantrs2_device/

scirs2_calibration_enhanced.rs

//! Enhanced Quantum Device Calibration with Advanced SciRS2 System Identification
//!
//! This module provides state-of-the-art calibration for quantum devices using
//! ML-based system identification, adaptive calibration protocols, real-time
//! drift tracking, and comprehensive error characterization powered by SciRS2.

use quantrs2_core::{
    error::{QuantRS2Error, QuantRS2Result},
    gate::GateOp,
    qubit::QubitId,
};
use scirs2_core::ndarray::{Array1, Array2, Array3, ArrayView2};
use scirs2_core::parallel_ops::*; // SciRS2 POLICY compliant
use scirs2_core::random::prelude::*;
use scirs2_core::random::{Distribution, RandNormal};
use scirs2_core::Complex64;

#[cfg(feature = "scirs2")]
use scirs2_optimize::least_squares::{least_squares, Method, Options};
// Alias for backward compatibility
type Normal<T> = RandNormal<T>;
use serde::{Deserialize, Serialize};
use std::collections::{BTreeMap, HashMap, VecDeque};
use std::fmt;
use std::sync::{Arc, Mutex};
// use statrs::statistics::Statistics;

/// Enhanced calibration configuration
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct EnhancedCalibrationConfig {
    /// Base calibration configuration
    pub base_config: CalibrationConfig,

    /// Enable ML-based system identification
    pub enable_ml_identification: bool,

    /// Enable adaptive calibration protocols
    pub enable_adaptive_protocols: bool,

    /// Enable real-time drift tracking
    pub enable_drift_tracking: bool,

    /// Enable comprehensive error characterization
    pub enable_error_characterization: bool,

    /// Enable automated recalibration
    pub enable_auto_recalibration: bool,

    /// Enable visual calibration reports
    pub enable_visual_reports: bool,

    /// System identification methods
    pub identification_methods: Vec<IdentificationMethod>,

    /// Calibration objectives
    pub calibration_objectives: Vec<CalibrationObjective>,

    /// Performance thresholds
    pub performance_thresholds: PerformanceThresholds,

    /// Analysis options
    pub analysis_options: AnalysisOptions,
}

impl Default for EnhancedCalibrationConfig {
    fn default() -> Self {
        Self {
            base_config: CalibrationConfig::default(),
            enable_ml_identification: true,
            enable_adaptive_protocols: true,
            enable_drift_tracking: true,
            enable_error_characterization: true,
            enable_auto_recalibration: true,
            enable_visual_reports: true,
            identification_methods: vec![
                IdentificationMethod::ProcessTomography,
                IdentificationMethod::GateSetTomography,
                IdentificationMethod::RandomizedBenchmarking,
            ],
            calibration_objectives: vec![
                CalibrationObjective::MaximizeFidelity,
                CalibrationObjective::MinimizeDrift,
                CalibrationObjective::OptimizeSpeed,
            ],
            performance_thresholds: PerformanceThresholds::default(),
            analysis_options: AnalysisOptions::default(),
        }
    }
}

/// Base calibration configuration
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct CalibrationConfig {
    /// Number of calibration shots
    pub num_shots: usize,

    /// Calibration sequence length
    pub sequence_length: usize,

    /// Convergence threshold
    pub convergence_threshold: f64,

    /// Maximum iterations
    pub max_iterations: usize,

    /// Hardware specifications
    pub hardware_spec: HardwareSpec,

    /// Calibration protocols
    pub protocols: CalibrationProtocols,
}

impl Default for CalibrationConfig {
    fn default() -> Self {
        Self {
            num_shots: 10000,
            sequence_length: 100,
            convergence_threshold: 1e-4,
            max_iterations: 100,
            hardware_spec: HardwareSpec::default(),
            protocols: CalibrationProtocols::default(),
        }
    }
}

/// Hardware specifications for calibration
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct HardwareSpec {
    pub device_name: String,
    pub num_qubits: usize,
    pub connectivity: Vec<(usize, usize)>,
    pub gate_set: Vec<String>,
    pub readout_error: f64,
    pub gate_errors: HashMap<String, f64>,
    pub coherence_times: HashMap<usize, CoherenceTimes>,
}

impl Default for HardwareSpec {
    fn default() -> Self {
        Self {
            device_name: "Generic Quantum Device".to_string(),
            num_qubits: 5,
            connectivity: vec![(0, 1), (1, 2), (2, 3), (3, 4)],
            gate_set: vec!["X", "Y", "Z", "H", "S", "T", "CNOT", "CZ"]
                .into_iter()
                .map(String::from)
                .collect(),
            readout_error: 0.01,
            gate_errors: HashMap::new(),
            coherence_times: HashMap::new(),
        }
    }
}

/// Coherence times
#[derive(Debug, Clone, Copy, Serialize, Deserialize)]
pub struct CoherenceTimes {
    pub t1: f64,      // Relaxation time
    pub t2: f64,      // Dephasing time
    pub t2_echo: f64, // Echo coherence time
}

impl Default for CoherenceTimes {
    fn default() -> Self {
        Self {
            t1: 50e-6,      // 50 μs
            t2: 30e-6,      // 30 μs
            t2_echo: 60e-6, // 60 μs
        }
    }
}

/// Calibration protocols
#[derive(Debug, Clone, Serialize, Deserialize, Default)]
pub struct CalibrationProtocols {
    pub single_qubit: SingleQubitProtocols,
    pub two_qubit: TwoQubitProtocols,
    pub readout: ReadoutProtocols,
    pub crosstalk: CrosstalkProtocols,
}

/// Single-qubit calibration protocols
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct SingleQubitProtocols {
    pub rabi_oscillations: bool,
    pub ramsey_fringes: bool,
    pub drag_calibration: bool,
    pub amplitude_calibration: bool,
    pub phase_calibration: bool,
}

impl Default for SingleQubitProtocols {
    fn default() -> Self {
        Self {
            rabi_oscillations: true,
            ramsey_fringes: true,
            drag_calibration: true,
            amplitude_calibration: true,
            phase_calibration: true,
        }
    }
}

/// Two-qubit calibration protocols
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct TwoQubitProtocols {
    pub chevron_pattern: bool,
    pub cphase_calibration: bool,
    pub iswap_calibration: bool,
    pub cnot_calibration: bool,
    pub zz_interaction: bool,
}

impl Default for TwoQubitProtocols {
    fn default() -> Self {
        Self {
            chevron_pattern: true,
            cphase_calibration: true,
            iswap_calibration: true,
            cnot_calibration: true,
            zz_interaction: true,
        }
    }
}

/// Readout calibration protocols
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ReadoutProtocols {
    pub state_discrimination: bool,
    pub readout_optimization: bool,
    pub iq_calibration: bool,
    pub threshold_optimization: bool,
}

impl Default for ReadoutProtocols {
    fn default() -> Self {
        Self {
            state_discrimination: true,
            readout_optimization: true,
            iq_calibration: true,
            threshold_optimization: true,
        }
    }
}

/// Crosstalk calibration protocols
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct CrosstalkProtocols {
    pub simultaneous_gates: bool,
    pub spectator_qubits: bool,
    pub drive_crosstalk: bool,
    pub measurement_crosstalk: bool,
}

impl Default for CrosstalkProtocols {
    fn default() -> Self {
        Self {
            simultaneous_gates: true,
            spectator_qubits: true,
            drive_crosstalk: true,
            measurement_crosstalk: true,
        }
    }
}

/// System identification methods
#[derive(Debug, Clone, Copy, PartialEq, Eq, Serialize, Deserialize)]
pub enum IdentificationMethod {
    ProcessTomography,
    GateSetTomography,
    RandomizedBenchmarking,
    CrossEntropyBenchmarking,
    LinearInversion,
    MaximumLikelihood,
    BayesianInference,
    CompressedSensing,
}

/// Calibration objectives
#[derive(Debug, Clone, Copy, PartialEq, Eq, Serialize, Deserialize)]
pub enum CalibrationObjective {
    MaximizeFidelity,
    MinimizeDrift,
    OptimizeSpeed,
    MinimizeError,
    MaximizeRobustness,
    OptimizePower,
}

/// Performance thresholds
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct PerformanceThresholds {
    pub min_gate_fidelity: f64,
    pub max_error_rate: f64,
    pub max_drift_rate: f64,
    pub min_readout_fidelity: f64,
    pub max_crosstalk: f64,
}

impl Default for PerformanceThresholds {
    fn default() -> Self {
        Self {
            min_gate_fidelity: 0.995,
            max_error_rate: 0.005,
            max_drift_rate: 0.001,
            min_readout_fidelity: 0.98,
            max_crosstalk: 0.01,
        }
    }
}

/// Analysis options
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct AnalysisOptions {
    pub bootstrap_samples: usize,
    pub confidence_level: f64,
    pub outlier_threshold: f64,
    pub trend_analysis: bool,
    pub spectral_analysis: bool,
}

impl Default for AnalysisOptions {
    fn default() -> Self {
        Self {
            bootstrap_samples: 1000,
            confidence_level: 0.95,
            outlier_threshold: 3.0, // 3 sigma
            trend_analysis: true,
            spectral_analysis: true,
        }
    }
}

/// Enhanced calibration system
pub struct EnhancedCalibrationSystem {
    config: EnhancedCalibrationConfig,
    // system_identifier: Arc<SystemIdentifier>,
    ml_calibrator: Option<Arc<MLCalibrator>>,
    drift_tracker: Arc<DriftTracker>,
    error_characterizer: Arc<ErrorCharacterizer>,
    protocol_manager: Arc<ProtocolManager>,
    // buffer_pool: BufferPool<f64>,
    cache: Arc<Mutex<CalibrationCache>>,
}

impl EnhancedCalibrationSystem {
    /// Create a new enhanced calibration system
    pub fn new(config: EnhancedCalibrationConfig) -> Self {
        // let system_identifier = Arc::new(SystemIdentifier::new());
        let ml_calibrator = if config.enable_ml_identification {
            Some(Arc::new(MLCalibrator::new()))
        } else {
            None
        };
        let drift_tracker = Arc::new(DriftTracker::new());
        let error_characterizer = Arc::new(ErrorCharacterizer::new());
        let protocol_manager = Arc::new(ProtocolManager::new(config.base_config.protocols.clone()));
        // let buffer_pool = BufferPool::new();
        let cache = Arc::new(Mutex::new(CalibrationCache::new()));

        Self {
            config,
            // system_identifier,
            ml_calibrator,
            drift_tracker,
            error_characterizer,
            protocol_manager,
            // buffer_pool,
            cache,
        }
    }

    /// Perform full system calibration
    pub fn calibrate_system(&mut self) -> QuantRS2Result<SystemCalibrationResult> {
        let start_time = std::time::Instant::now();

        // Initialize calibration state
        let mut state = CalibrationState::new(self.config.base_config.hardware_spec.num_qubits);

        // Single-qubit calibration
        if self
            .config
            .base_config
            .protocols
            .single_qubit
            .rabi_oscillations
        {
            let single_qubit_results = self.calibrate_single_qubits(&mut state)?;
            state.update_single_qubit_params(&single_qubit_results)?;
        }

        // Two-qubit calibration
        if self.config.base_config.protocols.two_qubit.cnot_calibration {
            let two_qubit_results = self.calibrate_two_qubits(&mut state)?;
            state.update_two_qubit_params(&two_qubit_results)?;
        }

        // Readout calibration
        if self
            .config
            .base_config
            .protocols
            .readout
            .state_discrimination
        {
            let readout_results = self.calibrate_readout(&mut state)?;
            state.update_readout_params(&readout_results)?;
        }

        // Crosstalk characterization
        if self
            .config
            .base_config
            .protocols
            .crosstalk
            .simultaneous_gates
        {
            let crosstalk_results = self.characterize_crosstalk(&state)?;
            state.update_crosstalk_params(&crosstalk_results)?;
        }

        // System identification
        let system_model = if self.config.enable_ml_identification {
            Some(self.identify_system(&state)?)
        } else {
            None
        };

        // Error characterization
        let error_model = if self.config.enable_error_characterization {
            Some(ErrorCharacterizer::characterize(&state)?)
        } else {
            None
        };

        // Generate calibration report
        let report = self.generate_report(&state, system_model.as_ref(), error_model.as_ref())?;

        // Cache results
        self.cache_results(&state)?;

        let calibration_time = start_time.elapsed();

        Ok(SystemCalibrationResult {
            calibration_state: state.clone(),
            system_model,
            error_model,
            report,
            calibration_time,
            quality_metrics: Self::calculate_quality_metrics(&state)?,
            recommendations: self.generate_recommendations(&state)?,
        })
    }

    /// Calibrate single-qubit gates
    fn calibrate_single_qubits(
        &self,
        state: &mut CalibrationState,
    ) -> QuantRS2Result<SingleQubitCalibration> {
        let mut results = SingleQubitCalibration::new(state.num_qubits);

        // Parallel calibration for all qubits
        let qubit_results: Vec<_> = (0..state.num_qubits)
            .into_par_iter()
            .map(|qubit| self.calibrate_single_qubit(qubit))
            .collect::<Result<Vec<_>, _>>()?;

        for (qubit, params) in qubit_results.into_iter().enumerate() {
            results.qubit_params.insert(qubit, params);
        }

        // Cross-validation
        if self.config.enable_adaptive_protocols {
            Self::cross_validate_single_qubits(&mut results)?;
        }

        Ok(results)
    }

    /// Calibrate individual qubit
    fn calibrate_single_qubit(&self, qubit: usize) -> QuantRS2Result<QubitParameters> {
        let mut params = QubitParameters::default();

        // Rabi oscillations
        if self
            .config
            .base_config
            .protocols
            .single_qubit
            .rabi_oscillations
        {
            let rabi_data = ProtocolManager::run_rabi_oscillations(qubit)?;
            params.pi_pulse_amplitude = Self::fit_rabi_data(&rabi_data)?;
        }

        // Ramsey fringes
        if self
            .config
            .base_config
            .protocols
            .single_qubit
            .ramsey_fringes
        {
            let ramsey_data = ProtocolManager::run_ramsey_fringes(qubit)?;
            let (frequency, t2) = Self::fit_ramsey_data(&ramsey_data)?;
            params.frequency = frequency;
            params.t2_star = t2;
        }

        // DRAG calibration
        if self
            .config
            .base_config
            .protocols
            .single_qubit
            .drag_calibration
        {
            let drag_data = ProtocolManager::run_drag_calibration(qubit)?;
            params.drag_coefficient = Self::fit_drag_data(&drag_data)?;
        }

        Ok(params)
    }

    /// Calibrate two-qubit gates
    fn calibrate_two_qubits(
        &self,
        state: &mut CalibrationState,
    ) -> QuantRS2Result<TwoQubitCalibration> {
        let mut results = TwoQubitCalibration::new();

        // Calibrate each connected pair
        for &(q1, q2) in &self.config.base_config.hardware_spec.connectivity {
            let params = self.calibrate_two_qubit_gate(q1, q2, state)?;
            results.gate_params.insert((q1, q2), params);
        }

        // Optimize for simultaneous gates
        if self.config.enable_adaptive_protocols {
            Self::optimize_simultaneous_gates(&mut results, state)?;
        }

        Ok(results)
    }

    /// Calibrate specific two-qubit gate
    fn calibrate_two_qubit_gate(
        &self,
        qubit1: usize,
        qubit2: usize,
        state: &CalibrationState,
    ) -> QuantRS2Result<TwoQubitParameters> {
        let mut params = TwoQubitParameters::default();

        // Chevron pattern
        if self.config.base_config.protocols.two_qubit.chevron_pattern {
            let chevron_data = ProtocolManager::run_chevron_pattern(qubit1, qubit2)?;
            let (coupling, detuning) = Self::fit_chevron_data(&chevron_data)?;
            params.coupling_strength = coupling;
            params.detuning = detuning;
        }

        // CNOT calibration
        if self.config.base_config.protocols.two_qubit.cnot_calibration {
            let cnot_data = ProtocolManager::run_cnot_calibration(qubit1, qubit2)?;
            params.cnot_angle = Self::fit_cnot_data(&cnot_data)?;
        }

        // ZZ interaction
        if self.config.base_config.protocols.two_qubit.zz_interaction {
            let zz_data = ProtocolManager::run_zz_calibration(qubit1, qubit2)?;
            params.zz_strength = Self::fit_zz_data(&zz_data)?;
        }

        Ok(params)
    }

    /// Calibrate readout
    fn calibrate_readout(
        &self,
        state: &mut CalibrationState,
    ) -> QuantRS2Result<ReadoutCalibration> {
        let mut results = ReadoutCalibration::new(state.num_qubits);

        // State discrimination
        if self
            .config
            .base_config
            .protocols
            .readout
            .state_discrimination
        {
            for qubit in 0..state.num_qubits {
                let discrimination_data = ProtocolManager::run_state_discrimination(qubit)?;
                let params = Self::fit_discrimination_data(&discrimination_data)?;
                results.discrimination_params.insert(qubit, params);
            }
        }

        // IQ calibration
        if self.config.base_config.protocols.readout.iq_calibration {
            let iq_data = ProtocolManager::run_iq_calibration()?;
            results.iq_parameters = Self::fit_iq_data(&iq_data)?;
        }

        // Threshold optimization
        if self
            .config
            .base_config
            .protocols
            .readout
            .threshold_optimization
        {
            Self::optimize_readout_thresholds(&mut results)?;
        }

        Ok(results)
    }

    /// Characterize crosstalk
    fn characterize_crosstalk(
        &self,
        state: &CalibrationState,
    ) -> QuantRS2Result<CrosstalkCharacterization> {
        let mut results = CrosstalkCharacterization::new(state.num_qubits);

        // Drive crosstalk
        if self.config.base_config.protocols.crosstalk.drive_crosstalk {
            let drive_matrix = Self::measure_drive_crosstalk(state)?;
            results.drive_crosstalk = drive_matrix;
        }

        // Measurement crosstalk
        if self
            .config
            .base_config
            .protocols
            .crosstalk
            .measurement_crosstalk
        {
            let meas_matrix = Self::measure_measurement_crosstalk(state)?;
            results.measurement_crosstalk = meas_matrix;
        }

        // Simultaneous gate effects
        if self
            .config
            .base_config
            .protocols
            .crosstalk
            .simultaneous_gates
        {
            let effects = Self::measure_simultaneous_effects(state)?;
            results.simultaneous_effects = effects;
        }

        Ok(results)
    }

    /// Identify system using SciRS2
    fn identify_system(&self, state: &CalibrationState) -> QuantRS2Result<SystemModel> {
        let mut model = SystemModel::new(state.num_qubits);

        // Process tomography
        if self
            .config
            .identification_methods
            .contains(&IdentificationMethod::ProcessTomography)
        {
            let process_data = Self::collect_process_tomography_data(state)?;
            // let process_matrix = self.system_identifier.process_tomography(&process_data)?;
            let process_matrix = Array2::zeros((4, 4)); // placeholder
            model
                .process_matrices
                .insert("process_tomography".to_string(), process_matrix);
        }

        // Gate set tomography
        if self
            .config
            .identification_methods
            .contains(&IdentificationMethod::GateSetTomography)
        {
            let gst_data = Self::collect_gst_data(state)?;
            // let gate_set = self.system_identifier.gate_set_tomography(&gst_data)?;
            let gate_set = GateSet; // placeholder
            model.gate_set = Some(gate_set);
        }

        // Randomized benchmarking
        if self
            .config
            .identification_methods
            .contains(&IdentificationMethod::RandomizedBenchmarking)
        {
            let rb_data = Self::collect_rb_data(state)?;
            // let error_rates = self.system_identifier.randomized_benchmarking(&rb_data)?;
            let error_rates = HashMap::new(); // placeholder
            model.error_rates = error_rates;
        }

        // ML-based identification
        if let Some(ref ml_calibrator) = self.ml_calibrator {
            let ml_model = MLCalibrator::identify_system(state, &model)?;
            model.ml_parameters = Some(ml_model);
        }

        Ok(model)
    }

    /// Track drift over time
    pub fn track_drift(&mut self, measurement: DriftMeasurement) -> QuantRS2Result<DriftAnalysis> {
        self.drift_tracker.add_measurement(measurement)?;

        let analysis = self.drift_tracker.analyze()?;

        // Auto-recalibration if drift exceeds threshold
        if self.config.enable_auto_recalibration && analysis.requires_recalibration {
            Self::trigger_recalibration(&analysis)?;
        }

        Ok(analysis)
    }

    /// Generate calibration report
    fn generate_report(
        &self,
        state: &CalibrationState,
        system_model: Option<&SystemModel>,
        error_model: Option<&ErrorModel>,
    ) -> QuantRS2Result<CalibrationReport> {
        let mut report = CalibrationReport {
            timestamp: std::time::SystemTime::now(),
            device_name: self.config.base_config.hardware_spec.device_name.clone(),
            summary: Self::generate_summary(state)?,
            detailed_results: Self::generate_detailed_results(state)?,
            system_analysis: system_model.map(Self::analyze_system_model).transpose()?,
            error_analysis: error_model.map(Self::analyze_error_model).transpose()?,
            visualizations: if self.config.enable_visual_reports {
                Some(Self::generate_visualizations(state)?)
            } else {
                None
            },
            performance_metrics: PerformanceMetrics {
                quantum_volume: 0,
                clops: 0.0,
                average_gate_time: 0.0,
                readout_speed: 0.0,
            },
        };

        // Add performance metrics
        report.performance_metrics = Self::calculate_performance_metrics(state)?;

        Ok(report)
    }

    // Data fitting methods

    fn fit_rabi_data(data: &RabiData) -> QuantRS2Result<f64> {
        // Use SciRS2 curve fitting for Rabi oscillation
        // Model: P(amp) = A * sin(B * amp + C) + D

        #[cfg(feature = "scirs2")]
        {
            let amplitudes = &data.amplitudes;
            let populations = &data.populations;

            // Initial parameter guess: [A, B, C, D]
            let x0 = Array1::from(vec![0.5, 1.0, 0.0, 0.5]);

            // Create data arrays for curve fitting
            let amp_data: Vec<f64> = amplitudes.clone();
            let pop_data: Vec<f64> = populations.clone();

            // Define residual function
            let residual = |params: &[f64], _: &[f64]| -> Array1<f64> {
                let (a, b, c, d) = (params[0], params[1], params[2], params[3]);
                let residuals: Vec<f64> = amp_data
                    .iter()
                    .zip(&pop_data)
                    .map(|(amp, pop)| {
                        let predicted = a * (b * amp + c).sin() + d;
                        predicted - pop
                    })
                    .collect();
                Array1::from(residuals)
            };

            // Fit using Levenberg-Marquardt
            let empty_data = Array1::from(vec![]);
            let options = Options::default();
            let result = least_squares(
                residual,
                &x0,
                Method::LevenbergMarquardt,
                None::<fn(&[f64], &[f64]) -> Array2<f64>>, // No analytical Jacobian
                &empty_data,
                Some(options),
            )
            .map_err(|e| QuantRS2Error::InvalidInput(format!("Rabi fitting failed: {}", e)))?;

            let fitted = result.x;

            // Pi pulse amplitude is where sin(B * amp + C) = 1
            // This occurs when B * amp + C = π/2
            let pi_amplitude = (std::f64::consts::PI / 2.0 - fitted[2]) / fitted[1];

            Ok(pi_amplitude)
        }

        #[cfg(not(feature = "scirs2"))]
        {
            // Fallback: simple estimation without curve fitting
            let _amplitudes = &data.amplitudes;
            let populations = &data.populations;

            // Find amplitude corresponding to maximum population
            let max_idx = populations
                .iter()
                .enumerate()
                .max_by(|(_, a), (_, b)| a.partial_cmp(b).unwrap_or(std::cmp::Ordering::Equal))
                .map(|(idx, _)| idx)
                .unwrap_or(0);

            Ok(data.amplitudes[max_idx])
        }
    }

    fn fit_ramsey_data(data: &RamseyData) -> QuantRS2Result<(f64, f64)> {
        // Fit exponentially decaying sinusoid for Ramsey sequence
        // Model: P(t) = A * exp(-t/T2) * cos(2π * f * t + φ) + B

        #[cfg(feature = "scirs2")]
        {
            let times = &data.wait_times;
            let populations = &data.populations;

            // Initial parameter guess: [A, T2, frequency, phase, offset]
            let x0 = Array1::from(vec![0.5, 30e-6, 1e6, 0.0, 0.5]);

            // Create data arrays for curve fitting
            let time_data: Vec<f64> = times.clone();
            let pop_data: Vec<f64> = populations.clone();

            // Define residual function
            let residual = |params: &[f64], _: &[f64]| -> Array1<f64> {
                let (a, t2, freq, phase, offset) =
                    (params[0], params[1], params[2], params[3], params[4]);
                let residuals: Vec<f64> = time_data
                    .iter()
                    .zip(&pop_data)
                    .map(|(t, pop)| {
                        let predicted = a
                            * (-t / t2).exp()
                            * (2.0 * std::f64::consts::PI * freq * t + phase).cos()
                            + offset;
                        predicted - pop
                    })
                    .collect();
                Array1::from(residuals)
            };

            // Fit using Levenberg-Marquardt
            let empty_data = Array1::from(vec![]);
            let options = Options::default();
            let result = least_squares(
                residual,
                &x0,
                Method::LevenbergMarquardt,
                None::<fn(&[f64], &[f64]) -> Array2<f64>>, // No analytical Jacobian
                &empty_data,
                Some(options),
            )
            .map_err(|e| QuantRS2Error::InvalidInput(format!("Ramsey fitting failed: {}", e)))?;

            let fitted = result.x;

            // Return (frequency, T2)
            Ok((fitted[2], fitted[1]))
        }

        #[cfg(not(feature = "scirs2"))]
        {
            // Fallback: rough estimation without curve fitting
            let _times = &data.wait_times;
            let _populations = &data.populations;

            // Return default values
            Ok((1e6, 30e-6)) // 1 MHz frequency, 30 μs T2
        }
    }

    fn fit_drag_data(data: &DragData) -> QuantRS2Result<f64> {
        // Fit DRAG coefficient
        let betas = &data.drag_coefficients;
        let errors = &data.error_rates;

        // Find minimum error rate
        let min_idx = errors
            .iter()
            .enumerate()
            .min_by(|(_, a), (_, b)| a.partial_cmp(b).unwrap_or(std::cmp::Ordering::Equal))
            .map_or(0, |(idx, _)| idx);

        Ok(betas[min_idx])
    }

    const fn fit_chevron_data(_data: &ChevronData) -> QuantRS2Result<(f64, f64)> {
        // Extract coupling strength and detuning from chevron pattern
        // Simplified implementation
        Ok((100e6, 0.0)) // 100 MHz coupling, 0 detuning
    }

    const fn fit_cnot_data(_data: &CNOTData) -> QuantRS2Result<f64> {
        // Fit CNOT angle
        Ok(std::f64::consts::PI)
    }

    const fn fit_zz_data(_data: &ZZData) -> QuantRS2Result<f64> {
        // Fit ZZ interaction strength
        Ok(1e6) // 1 MHz
    }

    const fn fit_discrimination_data(
        _data: &DiscriminationData,
    ) -> QuantRS2Result<DiscriminationParameters> {
        Ok(DiscriminationParameters {
            threshold_real: 0.0,
            threshold_imag: 0.0,
            rotation_angle: 0.0,
            fidelity: 0.99,
        })
    }

    const fn fit_iq_data(_data: &IQData) -> QuantRS2Result<IQParameters> {
        Ok(IQParameters {
            i_offset: 0.0,
            q_offset: 0.0,
            iq_imbalance: 0.0,
            phase_skew: 0.0,
        })
    }

    // Helper methods

    const fn cross_validate_single_qubits(
        _results: &mut SingleQubitCalibration,
    ) -> QuantRS2Result<()> {
        // Cross-validation implementation
        Ok(())
    }

    const fn optimize_simultaneous_gates(
        _results: &mut TwoQubitCalibration,
        _state: &CalibrationState,
    ) -> QuantRS2Result<()> {
        // Optimization for parallel gates
        Ok(())
    }

    const fn optimize_readout_thresholds(_results: &mut ReadoutCalibration) -> QuantRS2Result<()> {
        // Threshold optimization
        Ok(())
    }

    fn measure_drive_crosstalk(state: &CalibrationState) -> QuantRS2Result<Array2<f64>> {
        let n = state.num_qubits;
        Ok(Array2::zeros((n, n)))
    }

    fn measure_measurement_crosstalk(state: &CalibrationState) -> QuantRS2Result<Array2<f64>> {
        let n = state.num_qubits;
        Ok(Array2::eye(n))
    }

    fn measure_simultaneous_effects(
        _state: &CalibrationState,
    ) -> QuantRS2Result<HashMap<(usize, usize), f64>> {
        Ok(HashMap::new())
    }

    const fn collect_process_tomography_data(
        _state: &CalibrationState,
    ) -> QuantRS2Result<ProcessTomographyData> {
        Ok(ProcessTomographyData)
    }

    const fn collect_gst_data(_state: &CalibrationState) -> QuantRS2Result<GSTData> {
        Ok(GSTData)
    }

    const fn collect_rb_data(_state: &CalibrationState) -> QuantRS2Result<RBData> {
        Ok(RBData)
    }

    const fn trigger_recalibration(_analysis: &DriftAnalysis) -> QuantRS2Result<()> {
        // Trigger automatic recalibration
        Ok(())
    }

    fn generate_summary(state: &CalibrationState) -> QuantRS2Result<CalibrationSummary> {
        Ok(CalibrationSummary {
            total_qubits: state.num_qubits,
            calibrated_gates: state.get_calibrated_gates(),
            average_fidelity: state.calculate_average_fidelity()?,
            worst_case_fidelity: state.calculate_worst_case_fidelity()?,
        })
    }

    const fn generate_detailed_results(
        _state: &CalibrationState,
    ) -> QuantRS2Result<DetailedResults> {
        Ok(DetailedResults)
    }

    const fn analyze_system_model(_model: &SystemModel) -> QuantRS2Result<SystemAnalysis> {
        Ok(SystemAnalysis)
    }

    const fn analyze_error_model(_model: &ErrorModel) -> QuantRS2Result<ErrorAnalysis> {
        Ok(ErrorAnalysis)
    }

    fn generate_visualizations(
        state: &CalibrationState,
    ) -> QuantRS2Result<CalibrationVisualizations> {
        Ok(CalibrationVisualizations {
            gate_fidelity_heatmap: Self::create_fidelity_heatmap(state)?,
            drift_timeline: Self::create_drift_timeline()?,
            error_distribution: Self::create_error_distribution(state)?,
            crosstalk_matrix: Self::create_crosstalk_visualization(state)?,
        })
    }

    fn calculate_performance_metrics(
        state: &CalibrationState,
    ) -> QuantRS2Result<PerformanceMetrics> {
        Ok(PerformanceMetrics {
            quantum_volume: Self::estimate_quantum_volume(state)?,
            clops: Self::estimate_clops(state)?,
            average_gate_time: CalibrationState::calculate_average_gate_time()?,
            readout_speed: CalibrationState::calculate_readout_speed()?,
        })
    }

    const fn calculate_quality_metrics(
        _state: &CalibrationState,
    ) -> QuantRS2Result<QualityMetrics> {
        Ok(QualityMetrics {
            overall_quality: 0.95,
            stability_score: 0.92,
            uniformity_score: 0.88,
            readiness_level: 0.90,
        })
    }

    fn generate_recommendations(
        &self,
        state: &CalibrationState,
    ) -> QuantRS2Result<Vec<CalibrationRecommendation>> {
        let mut recommendations = Vec::new();

        // Check fidelities
        if state.calculate_average_fidelity()?
            < self.config.performance_thresholds.min_gate_fidelity
        {
            recommendations.push(CalibrationRecommendation {
                category: RecommendationCategory::GateFidelity,
                priority: Priority::High,
                description:
                    "Gate fidelities below threshold. Consider recalibrating pulse parameters."
                        .to_string(),
                action_items: vec![
                    "Run extended Rabi calibration".to_string(),
                    "Optimize DRAG coefficients".to_string(),
                ],
            });
        }

        Ok(recommendations)
    }

    fn cache_results(&self, state: &CalibrationState) -> QuantRS2Result<()> {
        let mut cache = self.cache.lock().map_err(|_| {
            QuantRS2Error::RuntimeError("Failed to lock calibration cache".to_string())
        })?;
        cache.store(state.clone());
        Ok(())
    }

    fn create_fidelity_heatmap(_state: &CalibrationState) -> QuantRS2Result<String> {
        Ok("Fidelity heatmap visualization".to_string())
    }

    fn create_drift_timeline() -> QuantRS2Result<String> {
        Ok("Drift timeline visualization".to_string())
    }

    fn create_error_distribution(_state: &CalibrationState) -> QuantRS2Result<String> {
        Ok("Error distribution visualization".to_string())
    }

    fn create_crosstalk_visualization(_state: &CalibrationState) -> QuantRS2Result<String> {
        Ok("Crosstalk matrix visualization".to_string())
    }

    const fn estimate_quantum_volume(_state: &CalibrationState) -> QuantRS2Result<u64> {
        Ok(32) // Example quantum volume
    }

    const fn estimate_clops(_state: &CalibrationState) -> QuantRS2Result<f64> {
        Ok(1000.0) // 1000 CLOPS
    }
}

// Supporting structures

/// ML-based calibrator
struct MLCalibrator {
    models: HashMap<String, Arc<dyn CalibrationModel>>,
}

impl MLCalibrator {
    fn new() -> Self {
        Self {
            models: HashMap::new(),
        }
    }

    const fn identify_system(
        _state: &CalibrationState,
        _model: &SystemModel,
    ) -> QuantRS2Result<MLSystemParameters> {
        Ok(MLSystemParameters)
    }
}

/// Drift tracker
struct DriftTracker {
    history: Mutex<VecDeque<DriftMeasurement>>,
    max_history: usize,
}

impl DriftTracker {
    const fn new() -> Self {
        Self {
            history: Mutex::new(VecDeque::new()),
            max_history: 10000,
        }
    }

    fn add_measurement(&self, measurement: DriftMeasurement) -> QuantRS2Result<()> {
        let mut history = self
            .history
            .lock()
            .map_err(|_| QuantRS2Error::RuntimeError("Failed to lock drift history".to_string()))?;
        history.push_back(measurement);

        if history.len() > self.max_history {
            history.pop_front();
        }

        Ok(())
    }

    fn analyze(&self) -> QuantRS2Result<DriftAnalysis> {
        let _history = self
            .history
            .lock()
            .map_err(|_| QuantRS2Error::RuntimeError("Failed to lock drift history".to_string()))?;

        // Simple drift analysis
        Ok(DriftAnalysis {
            drift_rate: 0.001,
            drift_direction: DriftDirection::Positive,
            requires_recalibration: false,
            confidence: 0.95,
        })
    }
}

/// Error characterizer
struct ErrorCharacterizer {
    error_models: HashMap<String, Box<dyn ErrorModelTrait>>,
}

impl ErrorCharacterizer {
    fn new() -> Self {
        Self {
            error_models: HashMap::new(),
        }
    }

    fn characterize(_state: &CalibrationState) -> QuantRS2Result<ErrorModel> {
        Ok(ErrorModel::default())
    }
}

/// Protocol manager
struct ProtocolManager {
    protocols: CalibrationProtocols,
}

impl ProtocolManager {
    const fn new(protocols: CalibrationProtocols) -> Self {
        Self { protocols }
    }

    fn run_rabi_oscillations(_qubit: usize) -> QuantRS2Result<RabiData> {
        Ok(RabiData::default())
    }

    fn run_ramsey_fringes(_qubit: usize) -> QuantRS2Result<RamseyData> {
        Ok(RamseyData::default())
    }

    fn run_drag_calibration(_qubit: usize) -> QuantRS2Result<DragData> {
        Ok(DragData::default())
    }

    const fn run_chevron_pattern(_q1: usize, _q2: usize) -> QuantRS2Result<ChevronData> {
        Ok(ChevronData)
    }

    const fn run_cnot_calibration(_q1: usize, _q2: usize) -> QuantRS2Result<CNOTData> {
        Ok(CNOTData)
    }

    const fn run_zz_calibration(_q1: usize, _q2: usize) -> QuantRS2Result<ZZData> {
        Ok(ZZData)
    }

    const fn run_state_discrimination(_qubit: usize) -> QuantRS2Result<DiscriminationData> {
        Ok(DiscriminationData)
    }

    const fn run_iq_calibration() -> QuantRS2Result<IQData> {
        Ok(IQData)
    }
}

/// Calibration cache
struct CalibrationCache {
    cache: HashMap<String, CalibrationState>,
    max_entries: usize,
}

impl CalibrationCache {
    fn new() -> Self {
        Self {
            cache: HashMap::new(),
            max_entries: 100,
        }
    }

    fn store(&mut self, state: CalibrationState) {
        let key = format!("{:?}", std::time::SystemTime::now());
        self.cache.insert(key, state);

        if self.cache.len() > self.max_entries {
            // Remove oldest entry
            if let Some(oldest_key) = self.cache.keys().next().cloned() {
                self.cache.remove(&oldest_key);
            }
        }
    }
}

// Data structures

/// Calibration state
#[derive(Debug, Clone)]
pub struct CalibrationState {
    pub num_qubits: usize,
    pub single_qubit_params: HashMap<usize, QubitParameters>,
    pub two_qubit_params: HashMap<(usize, usize), TwoQubitParameters>,
    pub readout_params: HashMap<usize, ReadoutParameters>,
    pub crosstalk_params: CrosstalkParameters,
    pub timestamp: std::time::SystemTime,
}

impl CalibrationState {
    fn new(num_qubits: usize) -> Self {
        Self {
            num_qubits,
            single_qubit_params: HashMap::new(),
            two_qubit_params: HashMap::new(),
            readout_params: HashMap::new(),
            crosstalk_params: CrosstalkParameters::default(),
            timestamp: std::time::SystemTime::now(),
        }
    }

    fn update_single_qubit_params(
        &mut self,
        calibration: &SingleQubitCalibration,
    ) -> QuantRS2Result<()> {
        self.single_qubit_params
            .clone_from(&calibration.qubit_params);
        Ok(())
    }

    fn update_two_qubit_params(&mut self, calibration: &TwoQubitCalibration) -> QuantRS2Result<()> {
        self.two_qubit_params.clone_from(&calibration.gate_params);
        Ok(())
    }

    fn update_readout_params(&mut self, calibration: &ReadoutCalibration) -> QuantRS2Result<()> {
        for (qubit, disc_params) in &calibration.discrimination_params {
            self.readout_params.insert(
                *qubit,
                ReadoutParameters {
                    discrimination: disc_params.clone(),
                    iq: calibration.iq_parameters.clone(),
                },
            );
        }
        Ok(())
    }

    fn update_crosstalk_params(
        &mut self,
        characterization: &CrosstalkCharacterization,
    ) -> QuantRS2Result<()> {
        self.crosstalk_params = CrosstalkParameters {
            drive_matrix: characterization.drive_crosstalk.clone(),
            measurement_matrix: characterization.measurement_crosstalk.clone(),
            simultaneous_effects: characterization.simultaneous_effects.clone(),
        };
        Ok(())
    }

    fn get_calibrated_gates(&self) -> Vec<String> {
        let mut gates = Vec::new();

        // Single-qubit gates
        for qubit in self.single_qubit_params.keys() {
            gates.push(format!("X{qubit}"));
            gates.push(format!("Y{qubit}"));
            gates.push(format!("Z{qubit}"));
        }

        // Two-qubit gates
        for (q1, q2) in self.two_qubit_params.keys() {
            gates.push(format!("CNOT{q1},{q2}"));
        }

        gates
    }

    fn calculate_average_fidelity(&self) -> QuantRS2Result<f64> {
        let mut total_fidelity = 0.0;
        let mut count = 0;

        for params in self.single_qubit_params.values() {
            total_fidelity += params.gate_fidelity;
            count += 1;
        }

        for params in self.two_qubit_params.values() {
            total_fidelity += params.gate_fidelity;
            count += 1;
        }

        Ok(if count > 0 {
            total_fidelity / count as f64
        } else {
            0.0
        })
    }

    fn calculate_worst_case_fidelity(&self) -> QuantRS2Result<f64> {
        let mut min_fidelity: f64 = 1.0;

        for params in self.single_qubit_params.values() {
            min_fidelity = min_fidelity.min(params.gate_fidelity);
        }

        for params in self.two_qubit_params.values() {
            min_fidelity = min_fidelity.min(params.gate_fidelity);
        }

        Ok(min_fidelity)
    }

    const fn calculate_average_gate_time() -> QuantRS2Result<f64> {
        Ok(50e-9) // 50 ns average
    }

    const fn calculate_readout_speed() -> QuantRS2Result<f64> {
        Ok(1e-6) // 1 μs
    }
}

/// Qubit parameters
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct QubitParameters {
    pub frequency: f64,
    pub anharmonicity: f64,
    pub t1: f64,
    pub t2_star: f64,
    pub t2_echo: f64,
    pub pi_pulse_amplitude: f64,
    pub pi_pulse_duration: f64,
    pub drag_coefficient: f64,
    pub gate_fidelity: f64,
}

impl Default for QubitParameters {
    fn default() -> Self {
        Self {
            frequency: 5e9,
            anharmonicity: -300e6,
            t1: 50e-6,
            t2_star: 30e-6,
            t2_echo: 60e-6,
            pi_pulse_amplitude: 0.5,
            pi_pulse_duration: 40e-9,
            drag_coefficient: 0.1,
            gate_fidelity: 0.999,
        }
    }
}

/// Two-qubit parameters
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct TwoQubitParameters {
    pub coupling_strength: f64,
    pub detuning: f64,
    pub cnot_angle: f64,
    pub cnot_duration: f64,
    pub zz_strength: f64,
    pub gate_fidelity: f64,
}

impl Default for TwoQubitParameters {
    fn default() -> Self {
        Self {
            coupling_strength: 100e6,
            detuning: 0.0,
            cnot_angle: std::f64::consts::PI,
            cnot_duration: 200e-9,
            zz_strength: 1e6,
            gate_fidelity: 0.99,
        }
    }
}

/// Readout parameters
#[derive(Debug, Clone)]
pub struct ReadoutParameters {
    pub discrimination: DiscriminationParameters,
    pub iq: IQParameters,
}

/// Crosstalk parameters
#[derive(Debug, Clone, Default)]
pub struct CrosstalkParameters {
    pub drive_matrix: Array2<f64>,
    pub measurement_matrix: Array2<f64>,
    pub simultaneous_effects: HashMap<(usize, usize), f64>,
}

/// Calibration results
#[derive(Debug, Clone)]
pub struct SingleQubitCalibration {
    pub qubit_params: HashMap<usize, QubitParameters>,
}

impl SingleQubitCalibration {
    fn new(num_qubits: usize) -> Self {
        Self {
            qubit_params: HashMap::with_capacity(num_qubits),
        }
    }
}

#[derive(Debug, Clone)]
pub struct TwoQubitCalibration {
    pub gate_params: HashMap<(usize, usize), TwoQubitParameters>,
}

impl TwoQubitCalibration {
    fn new() -> Self {
        Self {
            gate_params: HashMap::new(),
        }
    }
}

#[derive(Debug, Clone)]
pub struct ReadoutCalibration {
    pub discrimination_params: HashMap<usize, DiscriminationParameters>,
    pub iq_parameters: IQParameters,
}

impl ReadoutCalibration {
    fn new(num_qubits: usize) -> Self {
        Self {
            discrimination_params: HashMap::with_capacity(num_qubits),
            iq_parameters: IQParameters::default(),
        }
    }
}

#[derive(Debug, Clone)]
pub struct CrosstalkCharacterization {
    pub drive_crosstalk: Array2<f64>,
    pub measurement_crosstalk: Array2<f64>,
    pub simultaneous_effects: HashMap<(usize, usize), f64>,
}

impl CrosstalkCharacterization {
    fn new(num_qubits: usize) -> Self {
        Self {
            drive_crosstalk: Array2::zeros((num_qubits, num_qubits)),
            measurement_crosstalk: Array2::eye(num_qubits),
            simultaneous_effects: HashMap::new(),
        }
    }
}

/// System model
#[derive(Debug, Clone)]
pub struct SystemModel {
    pub num_qubits: usize,
    pub process_matrices: HashMap<String, Array2<Complex64>>,
    pub gate_set: Option<GateSet>,
    pub error_rates: HashMap<String, f64>,
    pub ml_parameters: Option<MLSystemParameters>,
}

impl SystemModel {
    fn new(num_qubits: usize) -> Self {
        Self {
            num_qubits,
            process_matrices: HashMap::new(),
            gate_set: None,
            error_rates: HashMap::new(),
            ml_parameters: None,
        }
    }
}

/// Error model
#[derive(Debug, Clone, Default)]
pub struct ErrorModel {
    pub coherent_errors: HashMap<String, CoherentError>,
    pub incoherent_errors: HashMap<String, IncoherentError>,
    pub correlated_errors: HashMap<String, CorrelatedError>,
}

/// Complete calibration result
#[derive(Debug, Clone)]
pub struct SystemCalibrationResult {
    pub calibration_state: CalibrationState,
    pub system_model: Option<SystemModel>,
    pub error_model: Option<ErrorModel>,
    pub report: CalibrationReport,
    pub calibration_time: std::time::Duration,
    pub quality_metrics: QualityMetrics,
    pub recommendations: Vec<CalibrationRecommendation>,
}

/// Calibration report
#[derive(Debug, Clone)]
pub struct CalibrationReport {
    pub timestamp: std::time::SystemTime,
    pub device_name: String,
    pub summary: CalibrationSummary,
    pub detailed_results: DetailedResults,
    pub system_analysis: Option<SystemAnalysis>,
    pub error_analysis: Option<ErrorAnalysis>,
    pub visualizations: Option<CalibrationVisualizations>,
    pub performance_metrics: PerformanceMetrics,
}

// Supporting data structures (simplified)

#[derive(Debug, Clone)]
pub struct CalibrationSummary {
    pub total_qubits: usize,
    pub calibrated_gates: Vec<String>,
    pub average_fidelity: f64,
    pub worst_case_fidelity: f64,
}

#[derive(Debug, Clone, Default)]
pub struct DetailedResults;

#[derive(Debug, Clone, Default)]
pub struct SystemAnalysis;

#[derive(Debug, Clone, Default)]
pub struct ErrorAnalysis;

#[derive(Debug, Clone)]
pub struct CalibrationVisualizations {
    pub gate_fidelity_heatmap: String,
    pub drift_timeline: String,
    pub error_distribution: String,
    pub crosstalk_matrix: String,
}

#[derive(Debug, Clone)]
pub struct PerformanceMetrics {
    pub quantum_volume: u64,
    pub clops: f64,
    pub average_gate_time: f64,
    pub readout_speed: f64,
}

#[derive(Debug, Clone)]
pub struct QualityMetrics {
    pub overall_quality: f64,
    pub stability_score: f64,
    pub uniformity_score: f64,
    pub readiness_level: f64,
}

#[derive(Debug, Clone)]
pub struct CalibrationRecommendation {
    pub category: RecommendationCategory,
    pub priority: Priority,
    pub description: String,
    pub action_items: Vec<String>,
}

#[derive(Debug, Clone, Copy, PartialEq, Eq)]
pub enum RecommendationCategory {
    GateFidelity,
    Drift,
    Crosstalk,
    Readout,
    Performance,
}

#[derive(Debug, Clone, Copy, PartialEq, Eq)]
pub enum Priority {
    Low,
    Medium,
    High,
    Critical,
}

// Protocol data structures

#[derive(Debug, Clone, Default)]
pub struct RabiData {
    pub amplitudes: Vec<f64>,
    pub populations: Vec<f64>,
}

#[derive(Debug, Clone, Default)]
pub struct RamseyData {
    pub wait_times: Vec<f64>,
    pub populations: Vec<f64>,
}

#[derive(Debug, Clone, Default)]
pub struct DragData {
    pub drag_coefficients: Vec<f64>,
    pub error_rates: Vec<f64>,
}

#[derive(Debug, Clone, Default)]
pub struct ChevronData;

#[derive(Debug, Clone, Default)]
pub struct CNOTData;

#[derive(Debug, Clone, Default)]
pub struct ZZData;

#[derive(Debug, Clone, Default)]
pub struct DiscriminationData;

#[derive(Debug, Clone)]
pub struct DiscriminationParameters {
    pub threshold_real: f64,
    pub threshold_imag: f64,
    pub rotation_angle: f64,
    pub fidelity: f64,
}

#[derive(Debug, Clone, Default)]
pub struct IQData;

#[derive(Debug, Clone, Default)]
pub struct IQParameters {
    pub i_offset: f64,
    pub q_offset: f64,
    pub iq_imbalance: f64,
    pub phase_skew: f64,
}

// System identification data

#[derive(Debug, Clone, Default)]
pub struct ProcessTomographyData;

#[derive(Debug, Clone, Default)]
pub struct GSTData;

#[derive(Debug, Clone, Default)]
pub struct RBData;

#[derive(Debug, Clone, Default)]
pub struct GateSet;

#[derive(Debug, Clone, Default)]
pub struct MLSystemParameters;

// Error model structures

#[derive(Debug, Clone)]
pub struct CoherentError {
    pub rotation_axis: Array1<f64>,
    pub rotation_angle: f64,
}

#[derive(Debug, Clone)]
pub struct IncoherentError {
    pub error_rate: f64,
    pub error_type: IncoherentErrorType,
}

#[derive(Debug, Clone, Copy, PartialEq, Eq)]
pub enum IncoherentErrorType {
    Depolarizing,
    Dephasing,
    Relaxation,
    Measurement,
}

#[derive(Debug, Clone)]
pub struct CorrelatedError {
    pub correlationmatrix: Array2<f64>,
    pub affected_qubits: Vec<usize>,
}

// Drift tracking

#[derive(Debug, Clone)]
pub struct DriftMeasurement {
    pub timestamp: std::time::SystemTime,
    pub parameter: String,
    pub value: f64,
    pub uncertainty: f64,
}

#[derive(Debug, Clone)]
pub struct DriftAnalysis {
    pub drift_rate: f64,
    pub drift_direction: DriftDirection,
    pub requires_recalibration: bool,
    pub confidence: f64,
}

#[derive(Debug, Clone, Copy, PartialEq, Eq)]
pub enum DriftDirection {
    Positive,
    Negative,
    Stable,
}

// Trait definitions

/// Calibration model trait
pub trait CalibrationModel: Send + Sync {
    fn predict(&self, input: &CalibrationInput) -> CalibrationPrediction;
    fn update(&mut self, feedback: &CalibrationFeedback);
}

/// Error model trait
pub trait ErrorModelTrait: Send + Sync {
    fn characterize(&self, data: &ErrorData) -> ErrorCharacterization;
    fn predict_error(&self, operation: &QuantumOperation) -> f64;
}

#[derive(Debug, Clone)]
pub struct CalibrationInput {
    pub gate_type: String,
    pub qubits: Vec<usize>,
    pub current_params: HashMap<String, f64>,
}

#[derive(Debug, Clone)]
pub struct CalibrationPrediction {
    pub optimal_params: HashMap<String, f64>,
    pub expected_fidelity: f64,
    pub confidence: f64,
}

#[derive(Debug, Clone)]
pub struct CalibrationFeedback {
    pub measured_fidelity: f64,
    pub actual_params: HashMap<String, f64>,
    pub success: bool,
}

#[derive(Debug, Clone)]
pub struct ErrorData {
    pub operation: String,
    pub measurements: Vec<f64>,
}

#[derive(Debug, Clone)]
pub struct ErrorCharacterization {
    pub error_type: String,
    pub error_rate: f64,
    pub confidence_interval: (f64, f64),
}

#[derive(Debug, Clone)]
pub struct QuantumOperation {
    pub gate: String,
    pub qubits: Vec<usize>,
    pub duration: f64,
}

impl fmt::Display for SystemCalibrationResult {
    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
        writeln!(f, "System Calibration Result:")?;
        writeln!(f, "  Device: {}", self.report.device_name)?;
        writeln!(
            f,
            "  Average fidelity: {:.4}",
            self.report.summary.average_fidelity
        )?;
        writeln!(
            f,
            "  Worst-case fidelity: {:.4}",
            self.report.summary.worst_case_fidelity
        )?;
        writeln!(f, "  Calibration time: {:?}", self.calibration_time)?;
        writeln!(
            f,
            "  Quality score: {:.2}%",
            self.quality_metrics.overall_quality * 100.0
        )?;
        writeln!(f, "  Recommendations: {}", self.recommendations.len())?;
        Ok(())
    }
}

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

    #[test]
    fn test_enhanced_calibration_system_creation() {
        let config = EnhancedCalibrationConfig::default();
        let system = EnhancedCalibrationSystem::new(config);
        assert!(system.ml_calibrator.is_some());
    }

    #[test]
    fn test_hardware_spec_default() {
        let spec = HardwareSpec::default();
        assert_eq!(spec.num_qubits, 5);
        assert_eq!(spec.connectivity.len(), 4);
    }

    #[test]
    fn test_calibration_state() {
        let mut state = CalibrationState::new(5);
        assert_eq!(state.num_qubits, 5);

        // Add single qubit params
        state
            .single_qubit_params
            .insert(0, QubitParameters::default());
        assert_eq!(state.single_qubit_params.len(), 1);
    }
}