quantrs2-anneal 0.1.3

//! Materials Science Lattice Optimization with Advanced Quantum Algorithms
//!
//! This module implements cutting-edge materials science optimization using quantum annealing
//! with advanced algorithms including infinite-depth QAOA, Zeno annealing, and adiabatic
//! shortcuts. It addresses fundamental materials problems including crystal structure
//! optimization, defect analysis, magnetic lattice systems, and phase transitions.
//!
//! Key Features:
//! - Crystal lattice structure optimization
//! - Magnetic lattice systems (Ising, Heisenberg, XY models)
//! - Defect formation energy minimization
//! - Phase transition analysis with quantum algorithms
//! - Phonon lattice dynamics optimization
//! - Multi-scale materials modeling integration
//! - Advanced quantum error correction for materials simulations

use std::collections::{HashMap, VecDeque};
use std::fmt;

use crate::advanced_quantum_algorithms::{
    AdiabaticShortcutsOptimizer, AdvancedAlgorithmConfig, AdvancedQuantumAlgorithms,
    AlgorithmSelectionStrategy, InfiniteDepthQAOA, InfiniteQAOAConfig, QuantumZenoAnnealer,
    ShortcutsConfig, ZenoConfig,
};
use crate::applications::{
    ApplicationError, ApplicationResult, IndustrySolution, OptimizationProblem,
};
use crate::bayesian_hyperopt::{optimize_annealing_parameters, BayesianHyperoptimizer};
use crate::ising::IsingModel;
use crate::neural_annealing_schedules::{NeuralAnnealingScheduler, NeuralSchedulerConfig};
use crate::non_stoquastic::{HamiltonianType, NonStoquasticHamiltonian};
use crate::quantum_error_correction::{
    ErrorCorrectionCode, ErrorMitigationConfig, ErrorMitigationManager, LogicalAnnealingEncoder,
    NoiseResilientAnnealingProtocol, SyndromeDetector,
};
use crate::simulator::{AnnealingParams, QuantumAnnealingSimulator};
use std::fmt::Write;

/// Crystal lattice types
#[derive(Debug, Clone, Copy, PartialEq, Eq)]
pub enum LatticeType {
    /// Simple cubic lattice
    SimpleCubic,
    /// Body-centered cubic (BCC)
    BodyCenteredCubic,
    /// Face-centered cubic (FCC)
    FaceCenteredCubic,
    /// Hexagonal close-packed (HCP)
    HexagonalClosePacked,
    /// Diamond cubic structure
    Diamond,
    /// Graphene honeycomb lattice
    Graphene,
    /// Perovskite structure
    Perovskite,
    /// Custom lattice with defined coordination
    Custom {
        coordination: usize,
        dimension: usize,
    },
}

/// Lattice site position
#[derive(Debug, Clone, Copy, PartialEq, Eq, Hash)]
pub struct LatticePosition {
    pub x: i32,
    pub y: i32,
    pub z: i32,
}

impl LatticePosition {
    #[must_use]
    pub const fn new(x: i32, y: i32, z: i32) -> Self {
        Self { x, y, z }
    }

    #[must_use]
    pub fn distance(&self, other: &Self) -> f64 {
        let dx = f64::from(self.x - other.x);
        let dy = f64::from(self.y - other.y);
        let dz = f64::from(self.z - other.z);
        dz.mul_add(dz, dx.mul_add(dx, dy * dy)).sqrt()
    }

    #[must_use]
    pub fn neighbors(&self, lattice_type: LatticeType) -> Vec<Self> {
        match lattice_type {
            LatticeType::SimpleCubic => {
                vec![
                    Self::new(self.x + 1, self.y, self.z),
                    Self::new(self.x - 1, self.y, self.z),
                    Self::new(self.x, self.y + 1, self.z),
                    Self::new(self.x, self.y - 1, self.z),
                    Self::new(self.x, self.y, self.z + 1),
                    Self::new(self.x, self.y, self.z - 1),
                ]
            }
            LatticeType::Graphene => {
                // Honeycomb lattice neighbors
                vec![
                    Self::new(self.x + 1, self.y, self.z),
                    Self::new(self.x, self.y + 1, self.z),
                    Self::new(self.x - 1, self.y + 1, self.z),
                ]
            }
            _ => {
                // Default to simple cubic
                self.neighbors(LatticeType::SimpleCubic)
            }
        }
    }
}

/// Atomic species in the lattice
#[derive(Debug, Clone, PartialEq)]
pub struct AtomicSpecies {
    pub symbol: String,
    pub atomic_number: u32,
    pub mass: f64,
    pub magnetic_moment: Option<f64>,
    pub charge: f64,
    pub radius: f64,
}

impl AtomicSpecies {
    #[must_use]
    pub const fn new(symbol: String, atomic_number: u32, mass: f64) -> Self {
        Self {
            symbol,
            atomic_number,
            mass,
            magnetic_moment: None,
            charge: 0.0,
            radius: 1.0,
        }
    }

    #[must_use]
    pub const fn with_magnetic_moment(mut self, moment: f64) -> Self {
        self.magnetic_moment = Some(moment);
        self
    }

    #[must_use]
    pub const fn with_charge(mut self, charge: f64) -> Self {
        self.charge = charge;
        self
    }
}

/// Lattice site with atom and properties
#[derive(Debug, Clone)]
pub struct LatticeSite {
    pub position: LatticePosition,
    pub species: Option<AtomicSpecies>,
    pub occupation: bool,
    pub spin: Option<[f64; 3]>, // Spin vector [x, y, z]
    pub defect_type: Option<DefectType>,
    pub local_energy: f64,
}

impl LatticeSite {
    #[must_use]
    pub const fn new(position: LatticePosition) -> Self {
        Self {
            position,
            species: None,
            occupation: false,
            spin: None,
            defect_type: None,
            local_energy: 0.0,
        }
    }

    #[must_use]
    pub fn with_species(mut self, species: AtomicSpecies) -> Self {
        self.species = Some(species);
        self.occupation = true;
        self
    }

    #[must_use]
    pub const fn with_spin(mut self, spin: [f64; 3]) -> Self {
        self.spin = Some(spin);
        self
    }

    #[must_use]
    pub fn with_defect(mut self, defect: DefectType) -> Self {
        self.defect_type = Some(defect);
        self
    }
}

/// Types of lattice defects
#[derive(Debug, Clone, PartialEq)]
pub enum DefectType {
    /// Vacancy (missing atom)
    Vacancy,
    /// Interstitial (extra atom)
    Interstitial(AtomicSpecies),
    /// Substitutional defect (wrong atom type)
    Substitutional(AtomicSpecies),
    /// Grain boundary
    GrainBoundary,
    /// Dislocation
    Dislocation { burgers_vector: [f64; 3] },
    /// Surface defect
    Surface,
}

/// Materials lattice system
#[derive(Debug, Clone)]
pub struct MaterialsLattice {
    pub lattice_type: LatticeType,
    pub dimensions: [usize; 3],      // Grid dimensions
    pub lattice_constants: [f64; 3], // Lattice constants a, b, c
    pub sites: HashMap<LatticePosition, LatticeSite>,
    pub temperature: f64,
    pub external_field: Option<[f64; 3]>, // External magnetic/electric field
}

impl MaterialsLattice {
    #[must_use]
    pub fn new(lattice_type: LatticeType, dimensions: [usize; 3]) -> Self {
        let mut sites = HashMap::new();

        // Initialize lattice sites
        for x in 0..(dimensions[0] as i32) {
            for y in 0..(dimensions[1] as i32) {
                for z in 0..(dimensions[2] as i32) {
                    let pos = LatticePosition::new(x, y, z);
                    sites.insert(pos, LatticeSite::new(pos));
                }
            }
        }

        Self {
            lattice_type,
            dimensions,
            lattice_constants: [1.0, 1.0, 1.0],
            sites,
            temperature: 300.0, // Room temperature in K
            external_field: None,
        }
    }

    pub const fn set_lattice_constants(&mut self, constants: [f64; 3]) {
        self.lattice_constants = constants;
    }

    pub fn add_atom(
        &mut self,
        position: LatticePosition,
        species: AtomicSpecies,
    ) -> ApplicationResult<()> {
        if let Some(site) = self.sites.get_mut(&position) {
            site.species = Some(species);
            site.occupation = true;
            Ok(())
        } else {
            Err(ApplicationError::InvalidConfiguration(format!(
                "Position {position:?} not found in lattice"
            )))
        }
    }

    pub fn create_defect(
        &mut self,
        position: LatticePosition,
        defect: DefectType,
    ) -> ApplicationResult<()> {
        if let Some(site) = self.sites.get_mut(&position) {
            site.defect_type = Some(defect);
            match &site.defect_type {
                Some(DefectType::Vacancy) => {
                    site.occupation = false;
                    site.species = None;
                }
                Some(DefectType::Interstitial(species)) => {
                    site.species = Some(species.clone());
                    site.occupation = true;
                }
                Some(DefectType::Substitutional(species)) => {
                    site.species = Some(species.clone());
                    site.occupation = true;
                }
                _ => {}
            }
            Ok(())
        } else {
            Err(ApplicationError::InvalidConfiguration(format!(
                "Position {position:?} not found in lattice"
            )))
        }
    }

    #[must_use]
    pub fn calculate_total_energy(&self) -> f64 {
        let mut total_energy = 0.0;

        for (pos, site) in &self.sites {
            // Local site energy
            total_energy += site.local_energy;

            // Interaction energy with neighbors
            let neighbors = pos.neighbors(self.lattice_type);
            for neighbor_pos in neighbors {
                if let Some(neighbor_site) = self.sites.get(&neighbor_pos) {
                    if site.occupation && neighbor_site.occupation {
                        total_energy += self.interaction_energy(site, neighbor_site);
                    }
                }
            }

            // Defect formation energy
            if let Some(ref defect) = site.defect_type {
                total_energy += self.defect_energy(defect);
            }
        }

        total_energy / 2.0 // Avoid double counting
    }

    fn interaction_energy(&self, site1: &LatticeSite, site2: &LatticeSite) -> f64 {
        let mut energy = 0.0;

        // Electrostatic interaction
        if let (Some(ref species1), Some(ref species2)) = (&site1.species, &site2.species) {
            let distance = site1.position.distance(&site2.position) * self.lattice_constants[0];
            let k_coulomb = 8.99e9; // Coulomb constant (simplified)
            energy += k_coulomb * species1.charge * species2.charge / distance;
        }

        // Magnetic interaction
        if let (Some(spin1), Some(spin2)) = (site1.spin, site2.spin) {
            let j_exchange = -1.0; // Exchange coupling (simplified)
            energy += j_exchange
                * spin1[2].mul_add(spin2[2], spin1[0].mul_add(spin2[0], spin1[1] * spin2[1]));
        }

        energy
    }

    const fn defect_energy(&self, defect: &DefectType) -> f64 {
        match defect {
            DefectType::Vacancy => 2.0,           // Formation energy for vacancy
            DefectType::Interstitial(_) => 3.0,   // Formation energy for interstitial
            DefectType::Substitutional(_) => 0.5, // Substitution energy
            DefectType::GrainBoundary => 1.0,
            DefectType::Dislocation { .. } => 5.0,
            DefectType::Surface => 0.8,
        }
    }

    #[must_use]
    pub fn calculate_order_parameter(&self) -> f64 {
        let mut magnetization = [0.0, 0.0, 0.0];
        let mut count = 0;

        for site in self.sites.values() {
            if let Some(spin) = site.spin {
                magnetization[0] += spin[0];
                magnetization[1] += spin[1];
                magnetization[2] += spin[2];
                count += 1;
            }
        }

        if count > 0 {
            let mag = magnetization[2].mul_add(
                magnetization[2],
                magnetization[0].mul_add(magnetization[0], magnetization[1] * magnetization[1]),
            );
            mag.sqrt() / f64::from(count)
        } else {
            0.0
        }
    }
}

/// Materials optimization objectives
#[derive(Debug, Clone)]
pub enum MaterialsObjective {
    /// Minimize total lattice energy
    MinimizeEnergy,
    /// Maximize structural stability
    MaximizeStability,
    /// Minimize defect density
    MinimizeDefects,
    /// Optimize magnetic properties
    OptimizeMagnetism,
    /// Minimize formation energy
    MinimizeFormationEnergy,
    /// Maximize order parameter
    MaximizeOrder,
    /// Multi-objective optimization
    MultiObjective(Vec<(Self, f64)>),
}

/// Materials science optimization problem
#[derive(Debug, Clone)]
pub struct MaterialsOptimizationProblem {
    pub lattice: MaterialsLattice,
    pub objectives: Vec<MaterialsObjective>,
    pub constraints: Vec<MaterialsConstraint>,
    pub qec_framework: Option<String>,
    pub advanced_config: AdvancedAlgorithmConfig,
    pub neural_config: Option<NeuralSchedulerConfig>,
}

/// Materials-specific constraints
#[derive(Debug, Clone)]
pub enum MaterialsConstraint {
    /// Stoichiometry constraint
    Stoichiometry { elements: HashMap<String, f64> },
    /// Charge neutrality
    ChargeNeutrality,
    /// Maximum defect density
    MaxDefectDensity(f64),
    /// Temperature range
    TemperatureRange { min: f64, max: f64 },
    /// Magnetic moment conservation
    MagneticMomentConservation,
    /// Structural stability
    StructuralStability { min_coordination: usize },
}

impl MaterialsOptimizationProblem {
    #[must_use]
    pub fn new(lattice: MaterialsLattice) -> Self {
        Self {
            lattice,
            objectives: vec![MaterialsObjective::MinimizeEnergy],
            constraints: vec![],
            qec_framework: None,
            advanced_config: AdvancedAlgorithmConfig {
                enable_infinite_qaoa: true,
                enable_zeno_annealing: true,
                enable_adiabatic_shortcuts: true,
                enable_counterdiabatic: true,
                selection_strategy: AlgorithmSelectionStrategy::ProblemSpecific,
                track_performance: true,
            },
            neural_config: None,
        }
    }

    #[must_use]
    pub fn with_quantum_error_correction(mut self, config: String) -> Self {
        self.qec_framework = Some(config);
        self
    }

    #[must_use]
    pub fn with_neural_annealing(mut self, config: NeuralSchedulerConfig) -> Self {
        self.neural_config = Some(config);
        self
    }

    #[must_use]
    pub fn add_objective(mut self, objective: MaterialsObjective) -> Self {
        self.objectives.push(objective);
        self
    }

    #[must_use]
    pub fn add_constraint(mut self, constraint: MaterialsConstraint) -> Self {
        self.constraints.push(constraint);
        self
    }

    /// Solve using infinite-depth QAOA
    pub fn solve_with_infinite_qaoa(&self) -> ApplicationResult<MaterialsLattice> {
        println!("Starting materials optimization with infinite-depth QAOA");

        let (ising_model, variable_map) = self.to_ising_model()?;

        let qaoa_config = InfiniteQAOAConfig {
            max_depth: 50,
            initial_depth: 3,
            optimization_tolerance: 1e-8,
            ..Default::default()
        };

        let mut qaoa = InfiniteDepthQAOA::new(qaoa_config);
        let result = qaoa.solve(&ising_model).map_err(|e| {
            ApplicationError::OptimizationError(format!("Infinite QAOA failed: {e:?}"))
        })?;

        let solution = result
            .map_err(|e| ApplicationError::OptimizationError(format!("QAOA solver error: {e}")))?;

        self.solution_to_lattice(&solution, &variable_map)
    }

    /// Solve using Quantum Zeno annealing
    pub fn solve_with_zeno_annealing(&self) -> ApplicationResult<MaterialsLattice> {
        println!("Starting materials optimization with Quantum Zeno annealing");

        let (ising_model, variable_map) = self.to_ising_model()?;

        let zeno_config = ZenoConfig {
            measurement_frequency: 2.0,
            total_evolution_time: 20.0,
            evolution_time_step: 0.05,
            ..Default::default()
        };

        let mut zeno_annealer = QuantumZenoAnnealer::new(zeno_config);
        let result = zeno_annealer.solve(&ising_model).map_err(|e| {
            ApplicationError::OptimizationError(format!("Zeno annealing failed: {e:?}"))
        })?;

        let solution = result
            .map_err(|e| ApplicationError::OptimizationError(format!("Zeno solver error: {e}")))?;

        self.solution_to_lattice(&solution, &variable_map)
    }

    /// Solve using adiabatic shortcuts
    pub fn solve_with_adiabatic_shortcuts(&self) -> ApplicationResult<MaterialsLattice> {
        println!("Starting materials optimization with adiabatic shortcuts");

        let (ising_model, variable_map) = self.to_ising_model()?;

        let shortcuts_config = ShortcutsConfig::default();
        let mut shortcuts_optimizer = AdiabaticShortcutsOptimizer::new(shortcuts_config);

        let result = shortcuts_optimizer.solve(&ising_model).map_err(|e| {
            ApplicationError::OptimizationError(format!("Adiabatic shortcuts failed: {e:?}"))
        })?;

        let solution = result.map_err(|e| {
            ApplicationError::OptimizationError(format!("Shortcuts solver error: {e}"))
        })?;

        self.solution_to_lattice(&solution, &variable_map)
    }

    /// Solve with quantum error correction
    pub fn solve_with_error_correction(&self) -> ApplicationResult<MaterialsLattice> {
        if let Some(ref qec_framework) = self.qec_framework {
            println!("Starting noise-resilient materials optimization");

            let (ising_model, variable_map) = self.to_ising_model()?;

            // Use error mitigation for lattice optimization
            let error_config = ErrorMitigationConfig::default();
            let mut error_manager = ErrorMitigationManager::new(error_config).map_err(|e| {
                ApplicationError::OptimizationError(format!(
                    "Failed to create error manager: {e:?}"
                ))
            })?;

            // First perform standard annealing
            let params = AnnealingParams::default();
            let annealer = QuantumAnnealingSimulator::new(params.clone()).map_err(|e| {
                ApplicationError::OptimizationError(format!("Failed to create annealer: {e:?}"))
            })?;
            let annealing_result = annealer.solve(&ising_model).map_err(|e| {
                ApplicationError::OptimizationError(format!("Annealing failed: {e:?}"))
            })?;

            // Convert simulator result to error mitigation format
            let error_mitigation_result =
                crate::quantum_error_correction::error_mitigation::AnnealingResult {
                    solution: annealing_result
                        .best_spins
                        .iter()
                        .map(|&x| i32::from(x))
                        .collect(),
                    energy: annealing_result.best_energy,
                    num_occurrences: 1,
                    chain_break_fraction: 0.0,
                    timing: std::collections::HashMap::new(),
                    info: std::collections::HashMap::new(),
                };

            // Apply error mitigation to improve the result
            let mitigation_result = error_manager
                .apply_mitigation(&ising_model, error_mitigation_result, &params)
                .map_err(|e| {
                    ApplicationError::OptimizationError(format!("Error mitigation failed: {e:?}"))
                })?;

            let solution = &mitigation_result.mitigated_result.solution;

            self.solution_to_lattice(&solution, &variable_map)
        } else {
            Err(ApplicationError::InvalidConfiguration(
                "Quantum error correction not enabled".to_string(),
            ))
        }
    }

    /// Optimize lattice using Bayesian hyperparameter optimization
    pub fn optimize_lattice_parameters(&self) -> ApplicationResult<HashMap<String, f64>> {
        println!("Optimizing lattice parameters with Bayesian optimization");

        let objective = |params: &[f64]| -> f64 {
            // params[0] = temperature, params[1] = lattice constant, params[2] = field strength
            let temperature = params[0];
            let lattice_constant = params[1];
            let field_strength = params[2];

            // Simplified lattice energy calculation
            let thermal_energy = temperature * 0.001; // kT term
            let strain_energy = (lattice_constant - 1.0).powi(2) * 10.0; // Strain penalty
            let field_energy = field_strength * 0.1; // External field contribution

            // Return total energy to minimize
            thermal_energy + strain_energy + field_energy
        };

        let best_params = optimize_annealing_parameters(objective, Some(40)).map_err(|e| {
            ApplicationError::OptimizationError(format!("Bayesian optimization failed: {e:?}"))
        })?;

        let mut result = HashMap::new();
        result.insert("optimal_temperature".to_string(), best_params[0]);
        result.insert("optimal_lattice_constant".to_string(), best_params[1]);
        result.insert("optimal_field_strength".to_string(), best_params[2]);

        Ok(result)
    }

    /// Convert to Ising model representation
    fn to_ising_model(&self) -> ApplicationResult<(IsingModel, HashMap<String, usize>)> {
        let total_sites = self.lattice.sites.len();
        let mut ising = IsingModel::new(total_sites);
        let mut variable_map = HashMap::new();

        // Map lattice sites to Ising variables
        let site_positions: Vec<_> = self.lattice.sites.keys().copied().collect();
        for (i, pos) in site_positions.iter().enumerate() {
            variable_map.insert(format!("site_{}_{}_{}_{}", pos.x, pos.y, pos.z, i), i);
        }

        // Add bias terms based on local energies and objectives
        for (i, (pos, site)) in self.lattice.sites.iter().enumerate() {
            let mut bias = site.local_energy;

            // Add objective-specific bias terms
            for objective in &self.objectives {
                match objective {
                    MaterialsObjective::MinimizeEnergy => {
                        bias += site.local_energy;
                    }
                    MaterialsObjective::MinimizeDefects => {
                        if site.defect_type.is_some() {
                            bias += 10.0; // Penalty for defects
                        }
                    }
                    MaterialsObjective::OptimizeMagnetism => {
                        if let Some(spin) = site.spin {
                            let spin_magnitude = spin[2]
                                .mul_add(spin[2], spin[0].mul_add(spin[0], spin[1] * spin[1]))
                                .sqrt();
                            bias -= spin_magnitude; // Encourage magnetic order
                        }
                    }
                    _ => {
                        // Default energy contribution
                        bias += 0.1;
                    }
                }
            }

            ising
                .set_bias(i, bias)
                .map_err(|e| ApplicationError::OptimizationError(e.to_string()))?;
        }

        // Add coupling terms for neighbor interactions
        for (i, (pos1, site1)) in self.lattice.sites.iter().enumerate() {
            let neighbors = pos1.neighbors(self.lattice.lattice_type);
            for neighbor_pos in neighbors {
                if let Some((j, (_, site2))) = self
                    .lattice
                    .sites
                    .iter()
                    .enumerate()
                    .find(|(_, (pos, _))| **pos == neighbor_pos)
                {
                    if i < j {
                        // Avoid double counting
                        let coupling = self.lattice.interaction_energy(site1, site2);
                        ising
                            .set_coupling(i, j, coupling)
                            .map_err(|e| ApplicationError::OptimizationError(e.to_string()))?;
                    }
                }
            }
        }

        Ok((ising, variable_map))
    }

    /// Convert Ising solution back to lattice configuration
    fn solution_to_lattice(
        &self,
        solution: &[i32],
        variable_map: &HashMap<String, usize>,
    ) -> ApplicationResult<MaterialsLattice> {
        let mut optimized_lattice = self.lattice.clone();

        // Update lattice configuration based on solution
        for (pos, site) in &mut optimized_lattice.sites {
            if let Some(&var_index) =
                variable_map.get(&format!("site_{}_{}_{}_0", pos.x, pos.y, pos.z))
            {
                if var_index < solution.len() {
                    let spin_value = solution[var_index];

                    // Update spin configuration
                    if site.spin.is_some() {
                        let spin_direction = if spin_value > 0 { 1.0 } else { -1.0 };
                        site.spin = Some([0.0, 0.0, spin_direction]);
                    }

                    // Update occupation based on solution
                    site.occupation = spin_value > 0;
                }
            }
        }

        // Recalculate local energies
        let positions: Vec<_> = optimized_lattice.sites.keys().copied().collect();
        for pos in positions {
            let local_energy = self.calculate_local_energy(&pos, &optimized_lattice);
            if let Some(site) = optimized_lattice.sites.get_mut(&pos) {
                site.local_energy = local_energy;
            }
        }

        Ok(optimized_lattice)
    }

    fn calculate_local_energy(&self, pos: &LatticePosition, lattice: &MaterialsLattice) -> f64 {
        let mut energy = 0.0;

        if let Some(site) = lattice.sites.get(pos) {
            // Self energy
            if let Some(ref defect) = site.defect_type {
                energy += lattice.defect_energy(defect);
            }

            // Neighbor interactions
            let neighbors = pos.neighbors(lattice.lattice_type);
            for neighbor_pos in neighbors {
                if let Some(neighbor_site) = lattice.sites.get(&neighbor_pos) {
                    energy += lattice.interaction_energy(site, neighbor_site) / 2.0;
                    // Half to avoid double counting
                }
            }
        }

        energy
    }
}

impl OptimizationProblem for MaterialsOptimizationProblem {
    type Solution = MaterialsLattice;
    type ObjectiveValue = f64;

    fn description(&self) -> String {
        format!(
            "Materials science lattice optimization: {:?} lattice, dimensions {:?}, {} sites",
            self.lattice.lattice_type,
            self.lattice.dimensions,
            self.lattice.sites.len()
        )
    }

    fn size_metrics(&self) -> HashMap<String, usize> {
        let mut metrics = HashMap::new();
        metrics.insert("total_sites".to_string(), self.lattice.sites.len());
        metrics.insert("x_dimension".to_string(), self.lattice.dimensions[0]);
        metrics.insert("y_dimension".to_string(), self.lattice.dimensions[1]);
        metrics.insert("z_dimension".to_string(), self.lattice.dimensions[2]);

        let occupied_sites = self.lattice.sites.values().filter(|s| s.occupation).count();
        metrics.insert("occupied_sites".to_string(), occupied_sites);

        let defect_sites = self
            .lattice
            .sites
            .values()
            .filter(|s| s.defect_type.is_some())
            .count();
        metrics.insert("defect_sites".to_string(), defect_sites);

        metrics
    }

    fn validate(&self) -> ApplicationResult<()> {
        if self.lattice.sites.is_empty() {
            return Err(ApplicationError::DataValidationError(
                "Lattice must have at least one site".to_string(),
            ));
        }

        let total_sites =
            self.lattice.dimensions[0] * self.lattice.dimensions[1] * self.lattice.dimensions[2];
        if total_sites > 10_000 {
            return Err(ApplicationError::ResourceLimitExceeded(
                "Lattice too large for current implementation".to_string(),
            ));
        }

        // Validate constraints
        for constraint in &self.constraints {
            match constraint {
                MaterialsConstraint::ChargeNeutrality => {
                    let total_charge: f64 = self
                        .lattice
                        .sites
                        .values()
                        .filter_map(|s| s.species.as_ref().map(|sp| sp.charge))
                        .sum();
                    if total_charge.abs() > 1e-6 {
                        return Err(ApplicationError::ConstraintViolation(format!(
                            "Charge neutrality violated: total charge = {total_charge}"
                        )));
                    }
                }
                MaterialsConstraint::MaxDefectDensity(max_density) => {
                    let defect_count = self
                        .lattice
                        .sites
                        .values()
                        .filter(|s| s.defect_type.is_some())
                        .count();
                    let defect_density = defect_count as f64 / self.lattice.sites.len() as f64;
                    if defect_density > *max_density {
                        return Err(ApplicationError::ConstraintViolation(format!(
                            "Defect density {defect_density} exceeds maximum {max_density}"
                        )));
                    }
                }
                _ => {
                    // Other constraints would be validated here
                }
            }
        }

        Ok(())
    }

    fn to_qubo(&self) -> ApplicationResult<(crate::ising::QuboModel, HashMap<String, usize>)> {
        // Convert Ising model to QUBO
        let (ising, variable_map) = self.to_ising_model()?;
        let qubo = ising.to_qubo();
        Ok((qubo, variable_map))
    }

    fn evaluate_solution(
        &self,
        solution: &Self::Solution,
    ) -> ApplicationResult<Self::ObjectiveValue> {
        Ok(solution.calculate_total_energy())
    }

    fn is_feasible(&self, solution: &Self::Solution) -> bool {
        // Check basic feasibility constraints
        for constraint in &self.constraints {
            match constraint {
                MaterialsConstraint::ChargeNeutrality => {
                    let total_charge: f64 = solution
                        .sites
                        .values()
                        .filter_map(|s| s.species.as_ref().map(|sp| sp.charge))
                        .sum();
                    if total_charge.abs() > 1e-6 {
                        return false;
                    }
                }
                MaterialsConstraint::MaxDefectDensity(max_density) => {
                    let defect_count = solution
                        .sites
                        .values()
                        .filter(|s| s.defect_type.is_some())
                        .count();
                    let defect_density = defect_count as f64 / solution.sites.len() as f64;
                    if defect_density > *max_density {
                        return false;
                    }
                }
                _ => {
                    // Other constraints
                }
            }
        }

        true
    }
}

impl IndustrySolution for MaterialsLattice {
    type Problem = MaterialsOptimizationProblem;

    fn from_binary(problem: &Self::Problem, binary_solution: &[i8]) -> ApplicationResult<Self> {
        let solution_i32: Vec<i32> = binary_solution.iter().map(|&x| i32::from(x)).collect();
        let variable_map = HashMap::new(); // Simplified
        problem.solution_to_lattice(&solution_i32, &variable_map)
    }

    fn summary(&self) -> HashMap<String, String> {
        let mut summary = HashMap::new();
        summary.insert(
            "lattice_type".to_string(),
            format!("{:?}", self.lattice_type),
        );
        summary.insert("dimensions".to_string(), format!("{:?}", self.dimensions));
        summary.insert("total_sites".to_string(), self.sites.len().to_string());
        summary.insert(
            "temperature".to_string(),
            format!("{:.2} K", self.temperature),
        );
        summary.insert(
            "total_energy".to_string(),
            format!("{:.6}", self.calculate_total_energy()),
        );
        summary.insert(
            "order_parameter".to_string(),
            format!("{:.6}", self.calculate_order_parameter()),
        );

        let occupied_sites = self.sites.values().filter(|s| s.occupation).count();
        summary.insert("occupied_sites".to_string(), occupied_sites.to_string());

        let defect_sites = self
            .sites
            .values()
            .filter(|s| s.defect_type.is_some())
            .count();
        summary.insert("defect_sites".to_string(), defect_sites.to_string());

        summary
    }

    fn metrics(&self) -> HashMap<String, f64> {
        let mut metrics = HashMap::new();
        metrics.insert("total_energy".to_string(), self.calculate_total_energy());
        metrics.insert(
            "order_parameter".to_string(),
            self.calculate_order_parameter(),
        );
        metrics.insert("temperature".to_string(), self.temperature);

        let occupied_fraction =
            self.sites.values().filter(|s| s.occupation).count() as f64 / self.sites.len() as f64;
        metrics.insert("occupation_fraction".to_string(), occupied_fraction);

        let defect_density = self
            .sites
            .values()
            .filter(|s| s.defect_type.is_some())
            .count() as f64
            / self.sites.len() as f64;
        metrics.insert("defect_density".to_string(), defect_density);

        metrics
    }

    fn export_format(&self) -> ApplicationResult<String> {
        let mut output = String::new();

        output.push_str("# Materials Science Lattice Configuration\n");
        let _ = writeln!(output, "Lattice Type: {:?}", self.lattice_type);
        let _ = writeln!(output, "Dimensions: {:?}", self.dimensions);
        let _ = writeln!(output, "Lattice Constants: {:?}", self.lattice_constants);
        let _ = writeln!(output, "Temperature: {:.2} K", self.temperature);
        let _ = write!(
            output,
            "Total Energy: {:.6}\n",
            self.calculate_total_energy()
        );
        let _ = write!(
            output,
            "Order Parameter: {:.6}\n",
            self.calculate_order_parameter()
        );

        if let Some(field) = self.external_field {
            let _ = writeln!(output, "External Field: {field:?}");
        }

        output.push_str("\n# Site Details\n");
        for (pos, site) in &self.sites {
            if site.occupation {
                let _ = write!(output, "Site ({}, {}, {}): ", pos.x, pos.y, pos.z);

                if let Some(ref species) = site.species {
                    let _ = write!(output, "{} ", species.symbol);
                }

                if let Some(spin) = site.spin {
                    let _ = write!(
                        output,
                        "spin=({:.3}, {:.3}, {:.3}) ",
                        spin[0], spin[1], spin[2]
                    );
                }

                if let Some(ref defect) = site.defect_type {
                    let _ = write!(output, "defect={defect:?} ");
                }

                let _ = write!(output, "energy={:.6}", site.local_energy);
                output.push('\n');
            }
        }

        Ok(output)
    }
}

/// Create benchmark materials science problems
pub fn create_benchmark_problems(
    size: usize,
) -> ApplicationResult<
    Vec<Box<dyn OptimizationProblem<Solution = MaterialsLattice, ObjectiveValue = f64>>>,
> {
    let mut problems = Vec::new();

    let dimensions = match size {
        s if s <= 10 => [4, 4, 1], // 2D 4x4 lattice
        s if s <= 50 => [5, 5, 2], // 3D 5x5x2 lattice
        _ => [8, 8, 2],            // 3D 8x8x2 lattice
    };

    // Create different lattice types
    let lattice_types = [
        LatticeType::SimpleCubic,
        LatticeType::FaceCenteredCubic,
        LatticeType::Graphene,
    ];

    for (i, &lattice_type) in lattice_types.iter().enumerate() {
        let mut lattice = MaterialsLattice::new(lattice_type, dimensions);

        // Add some atoms and defects for realistic problems
        let fe_atom = AtomicSpecies::new("Fe".to_string(), 26, 55.845)
            .with_magnetic_moment(2.2)
            .with_charge(0.0);

        // Fill lattice with iron atoms
        for (pos, site) in &mut lattice.sites {
            if (pos.x + pos.y + pos.z) % 2 == 0 {
                // Checkerboard pattern
                site.species = Some(fe_atom.clone());
                site.occupation = true;
                site.spin = Some([0.0, 0.0, 1.0]); // Spin up
            }
        }

        // Add some defects
        if size > 10 {
            let defect_pos = LatticePosition::new(2, 2, 0);
            lattice.create_defect(defect_pos, DefectType::Vacancy).ok();
        }

        let mut problem = MaterialsOptimizationProblem::new(lattice);

        // Add different objectives for different problems
        match i {
            0 => problem = problem.add_objective(MaterialsObjective::MinimizeEnergy),
            1 => problem = problem.add_objective(MaterialsObjective::OptimizeMagnetism),
            2 => problem = problem.add_objective(MaterialsObjective::MinimizeDefects),
            _ => problem = problem.add_objective(MaterialsObjective::MaximizeStability),
        }

        // Note: Simplified for trait object compatibility
        problems.push(Box::new(problem)
            as Box<
                dyn OptimizationProblem<Solution = MaterialsLattice, ObjectiveValue = f64>,
            >);
    }

    Ok(problems)
}

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

    #[test]
    fn test_lattice_creation() {
        let lattice = MaterialsLattice::new(LatticeType::SimpleCubic, [3, 3, 3]);
        assert_eq!(lattice.sites.len(), 27);
        assert_eq!(lattice.dimensions, [3, 3, 3]);
    }

    #[test]
    fn test_atomic_species() {
        let fe_atom = AtomicSpecies::new("Fe".to_string(), 26, 55.845)
            .with_magnetic_moment(2.2)
            .with_charge(2.0);

        assert_eq!(fe_atom.symbol, "Fe");
        assert_eq!(fe_atom.atomic_number, 26);
        assert_eq!(fe_atom.magnetic_moment, Some(2.2));
        assert_eq!(fe_atom.charge, 2.0);
    }

    #[test]
    fn test_lattice_neighbors() {
        let pos = LatticePosition::new(1, 1, 1);
        let neighbors = pos.neighbors(LatticeType::SimpleCubic);
        assert_eq!(neighbors.len(), 6); // 6 neighbors in cubic lattice
    }

    #[test]
    fn test_defect_creation() {
        let mut lattice = MaterialsLattice::new(LatticeType::SimpleCubic, [2, 2, 2]);
        let pos = LatticePosition::new(0, 0, 0);

        let result = lattice.create_defect(pos, DefectType::Vacancy);
        assert!(result.is_ok());

        let site = lattice
            .sites
            .get(&pos)
            .expect("site should exist at position after defect creation");
        assert!(!site.occupation);
        assert!(site.defect_type.is_some());
    }

    #[test]
    fn test_energy_calculation() {
        let mut lattice = MaterialsLattice::new(LatticeType::SimpleCubic, [2, 2, 2]);

        let fe_atom = AtomicSpecies::new("Fe".to_string(), 26, 55.845);
        let pos = LatticePosition::new(0, 0, 0);

        lattice
            .add_atom(pos, fe_atom)
            .expect("should add Fe atom at position");

        let energy = lattice.calculate_total_energy();
        assert!(energy >= 0.0); // Basic sanity check
    }

    #[test]
    fn test_problem_validation() {
        let lattice = MaterialsLattice::new(LatticeType::SimpleCubic, [3, 3, 3]);
        let problem = MaterialsOptimizationProblem::new(lattice);

        assert!(problem.validate().is_ok());
    }

    #[test]
    fn test_ising_conversion() {
        let lattice = MaterialsLattice::new(LatticeType::SimpleCubic, [2, 2, 2]);
        let problem = MaterialsOptimizationProblem::new(lattice);

        let (ising, variable_map) = problem
            .to_ising_model()
            .expect("should convert lattice problem to Ising model");
        assert_eq!(ising.num_qubits, 8); // 2x2x2 = 8 sites
        assert!(!variable_map.is_empty());
    }
}