quantrs2_anneal/applications/

quantum_computational_chemistry.rs

//! Advanced Quantum Computational Chemistry for Scientific Computing
//!
//! This module implements cutting-edge quantum computational chemistry algorithms
//! leveraging quantum annealing and advanced quantum algorithms for molecular
//! simulation, electronic structure calculations, and chemical property prediction.
//!
//! Key Features:
//! - Quantum molecular Hamiltonian simulation
//! - Electronic structure calculations with quantum annealing
//! - Chemical reaction pathway optimization
//! - Catalysis design and optimization
//! - Quantum chemical descriptors and property prediction
//! - Multi-scale molecular modeling
//! - Quantum machine learning for chemistry
//! - Advanced error correction for chemical simulations

use std::collections::{HashMap, HashSet, VecDeque};
use std::f64::consts::PI;
use std::fmt;

use crate::quantum_error_correction::{NoiseResilientConfig, SystemNoiseModel};

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::{BayesianHyperoptimizer, BayesianOptConfig};
use crate::enterprise_monitoring::{EnterpriseMonitoringSystem, LogLevel};
use crate::ising::{IsingModel, QuboModel};
use crate::meta_learning::MetaLearningOptimizer;
use crate::neural_annealing_schedules::{NeuralAnnealingScheduler, NeuralSchedulerConfig};
use crate::quantum_error_correction::{
    ErrorCorrectionCode, ErrorMitigationConfig, ErrorMitigationManager, LogicalAnnealingEncoder,
    NoiseResilientAnnealingProtocol, SyndromeDetector,
};
use crate::realtime_adaptive_qec::RealTimeAdaptiveQec;
use crate::simulator::{
    AnnealingParams, AnnealingResult, AnnealingSolution, QuantumAnnealingSimulator,
};

/// Quantum computational chemistry configuration
#[derive(Debug, Clone)]
pub struct QuantumChemistryConfig {
    /// Electronic structure calculation method
    pub method: ElectronicStructureMethod,
    /// Basis set for calculations
    pub basis_set: BasisSet,
    /// Correlation method
    pub correlation: CorrelationMethod,
    /// Convergence criteria
    pub convergence: ConvergenceCriteria,
    /// Error correction settings
    pub error_correction: ErrorMitigationConfig,
    /// Advanced algorithm settings
    pub advanced_algorithms: AdvancedAlgorithmConfig,
    /// Monitoring configuration
    pub monitoring_enabled: bool,
}

impl Default for QuantumChemistryConfig {
    fn default() -> Self {
        Self {
            method: ElectronicStructureMethod::HartreeFock,
            basis_set: BasisSet::STO3G,
            correlation: CorrelationMethod::CCSD,
            convergence: ConvergenceCriteria::default(),
            error_correction: ErrorMitigationConfig::default(),
            advanced_algorithms: AdvancedAlgorithmConfig::default(),
            monitoring_enabled: true,
        }
    }
}

/// Electronic structure calculation methods
#[derive(Debug, Clone, PartialEq, Eq)]
pub enum ElectronicStructureMethod {
    /// Hartree-Fock method
    HartreeFock,
    /// Density Functional Theory
    DFT(DFTFunctional),
    /// Configuration Interaction
    CI(CILevel),
    /// Coupled Cluster
    CoupledCluster(CCLevel),
    /// Multi-Reference methods
    MultiReference(MRMethod),
    /// Quantum Monte Carlo
    QuantumMonteCarlo,
}

/// DFT functionals
#[derive(Debug, Clone, PartialEq, Eq)]
pub enum DFTFunctional {
    B3LYP,
    PBE,
    M06,
    wB97XD,
    Custom(String),
}

/// Configuration Interaction levels
#[derive(Debug, Clone, PartialEq, Eq)]
pub enum CILevel {
    CIS,
    CISD,
    CISDT,
    CISDTQ,
    FullCI,
}

/// Coupled Cluster levels
#[derive(Debug, Clone, PartialEq, Eq)]
pub enum CCLevel {
    CCD,
    CCSD,
    CCSDT,
    CCSDTQ,
}

/// Multi-reference methods
#[derive(Debug, Clone, PartialEq, Eq)]
pub enum MRMethod {
    CASSCF,
    CASPT2,
    MRCI,
    NEVPT2,
}

/// Basis sets for quantum chemistry calculations
#[derive(Debug, Clone, PartialEq, Eq)]
pub enum BasisSet {
    /// Minimal basis sets
    STO3G,
    /// Split-valence basis sets
    SV,
    SVP,
    SVPD,
    /// Triple-zeta basis sets
    TZVP,
    TZVPD,
    /// Quadruple-zeta basis sets
    QZVP,
    QZVPD,
    /// Correlation-consistent basis sets
    CCPVDZ,
    CCPVTZ,
    CCPVQZ,
    /// Augmented basis sets
    AugCCPVDZ,
    AugCCPVTZ,
    /// Custom basis set
    Custom(String),
}

/// Electron correlation methods
#[derive(Debug, Clone, PartialEq, Eq)]
pub enum CorrelationMethod {
    /// No correlation
    None,
    /// Møller-Plesset perturbation theory
    MP2,
    MP3,
    MP4,
    /// Coupled Cluster
    CCSD,
    CCSDT,
    /// Configuration Interaction
    CISD,
    CISDT,
    /// Random Phase Approximation
    RPA,
}

/// Convergence criteria for quantum chemistry calculations
#[derive(Debug, Clone)]
pub struct ConvergenceCriteria {
    /// Energy convergence threshold
    pub energy_threshold: f64,
    /// Density matrix convergence threshold
    pub density_threshold: f64,
    /// Maximum number of SCF iterations
    pub max_scf_iterations: usize,
    /// Orbital gradient threshold
    pub gradient_threshold: f64,
    /// DIIS convergence acceleration
    pub use_diis: bool,
}

impl Default for ConvergenceCriteria {
    fn default() -> Self {
        Self {
            energy_threshold: 1e-8,
            density_threshold: 1e-6,
            max_scf_iterations: 100,
            gradient_threshold: 1e-6,
            use_diis: true,
        }
    }
}

/// Molecular system for quantum chemistry calculations
#[derive(Debug, Clone)]
pub struct MolecularSystem {
    /// System identifier
    pub id: String,
    /// Atoms in the system
    pub atoms: Vec<Atom>,
    /// Total charge of the system
    pub charge: i32,
    /// Spin multiplicity
    pub multiplicity: usize,
    /// Molecular geometry
    pub geometry: MolecularGeometry,
    /// External fields
    pub external_fields: Vec<ExternalField>,
    /// Constraints
    pub constraints: Vec<GeometryConstraint>,
}

/// Atom in molecular system
#[derive(Debug, Clone)]
pub struct Atom {
    /// Atomic number
    pub atomic_number: u8,
    /// Element symbol
    pub symbol: String,
    /// Atomic mass
    pub mass: f64,
    /// Position in 3D space
    pub position: [f64; 3],
    /// Partial charge
    pub partial_charge: Option<f64>,
    /// Basis functions
    pub basis_functions: Vec<BasisFunction>,
}

/// Molecular geometry representation
#[derive(Debug, Clone)]
pub struct MolecularGeometry {
    /// Coordinate system
    pub coordinate_system: CoordinateSystem,
    /// Bond lengths
    pub bonds: Vec<Bond>,
    /// Bond angles
    pub angles: Vec<Angle>,
    /// Dihedral angles
    pub dihedrals: Vec<Dihedral>,
    /// Point group symmetry
    pub point_group: Option<String>,
}

/// Coordinate systems
#[derive(Debug, Clone, PartialEq, Eq)]
pub enum CoordinateSystem {
    Cartesian,
    ZMatrix,
    Internal,
    Redundant,
}

/// Chemical bond
#[derive(Debug, Clone)]
pub struct Bond {
    pub atom1: usize,
    pub atom2: usize,
    pub length: f64,
    pub order: BondOrder,
    pub strength: f64,
}

/// Bond order types
#[derive(Debug, Clone, PartialEq)]
pub enum BondOrder {
    Single,
    Double,
    Triple,
    Aromatic,
    Partial(f64),
}

/// Bond angle
#[derive(Debug, Clone)]
pub struct Angle {
    pub atom1: usize,
    pub atom2: usize,
    pub atom3: usize,
    pub angle: f64, // in radians
}

/// Dihedral angle
#[derive(Debug, Clone)]
pub struct Dihedral {
    pub atom1: usize,
    pub atom2: usize,
    pub atom3: usize,
    pub atom4: usize,
    pub angle: f64, // in radians
}

/// External fields affecting the molecular system
#[derive(Debug, Clone)]
pub enum ExternalField {
    Electric {
        field: [f64; 3],
        frequency: Option<f64>,
    },
    Magnetic {
        field: [f64; 3],
    },
    Pressure {
        pressure: f64,
    },
    Temperature {
        temperature: f64,
    },
}

/// Geometry constraints
#[derive(Debug, Clone)]
pub enum GeometryConstraint {
    FixedAtom(usize),
    FixedBond {
        atom1: usize,
        atom2: usize,
        length: f64,
    },
    FixedAngle {
        atom1: usize,
        atom2: usize,
        atom3: usize,
        angle: f64,
    },
    FixedDihedral {
        atom1: usize,
        atom2: usize,
        atom3: usize,
        atom4: usize,
        angle: f64,
    },
}

/// Basis function for quantum calculations
#[derive(Debug, Clone)]
pub struct BasisFunction {
    /// Function type
    pub function_type: BasisFunctionType,
    /// Angular momentum quantum numbers
    pub angular_momentum: (u32, i32, i32), // (l, m_l, m_s)
    /// Exponent
    pub exponent: f64,
    /// Contraction coefficients
    pub coefficients: Vec<f64>,
    /// Center position
    pub center: [f64; 3],
}

/// Types of basis functions
#[derive(Debug, Clone, PartialEq, Eq)]
pub enum BasisFunctionType {
    /// Slater-type orbital
    STO,
    /// Gaussian-type orbital
    GTO,
    /// Plane wave
    PlaneWave,
    /// Numerical atomic orbital
    NAO,
}

/// Quantum computational chemistry optimizer
pub struct QuantumChemistryOptimizer {
    /// Configuration
    pub config: QuantumChemistryConfig,
    /// Advanced quantum algorithms
    pub advanced_algorithms: AdvancedQuantumAlgorithms,
    /// Error correction system
    pub error_correction: NoiseResilientAnnealingProtocol,
    /// Real-time adaptive QEC
    pub adaptive_qec: RealTimeAdaptiveQec,
    /// Meta-learning optimizer
    pub meta_learning: MetaLearningOptimizer,
    /// Neural annealing scheduler
    pub neural_scheduler: NeuralAnnealingScheduler,
    /// Enterprise monitoring
    pub monitoring: Option<EnterpriseMonitoringSystem>,
    /// Calculated systems cache
    pub system_cache: HashMap<String, QuantumChemistryResult>,
}

/// Results from quantum chemistry calculations
#[derive(Debug, Clone)]
pub struct QuantumChemistryResult {
    /// System identifier
    pub system_id: String,
    /// Electronic energy
    pub electronic_energy: f64,
    /// Nuclear repulsion energy
    pub nuclear_repulsion: f64,
    /// Total energy
    pub total_energy: f64,
    /// Molecular orbitals
    pub molecular_orbitals: Vec<MolecularOrbital>,
    /// Electronic density
    pub electron_density: ElectronDensity,
    /// Dipole moment
    pub dipole_moment: [f64; 3],
    /// Polarizability tensor
    pub polarizability: [[f64; 3]; 3],
    /// Vibrational frequencies
    pub vibrational_frequencies: Vec<f64>,
    /// Thermochemical properties
    pub thermochemistry: ThermochemicalProperties,
    /// Calculation metadata
    pub metadata: CalculationMetadata,
}

/// Molecular orbital representation
#[derive(Debug, Clone)]
pub struct MolecularOrbital {
    /// Orbital energy
    pub energy: f64,
    /// Orbital coefficients
    pub coefficients: Vec<f64>,
    /// Occupation number
    pub occupation: f64,
    /// Orbital symmetry
    pub symmetry: Option<String>,
    /// Orbital type
    pub orbital_type: OrbitalType,
}

/// Types of molecular orbitals
#[derive(Debug, Clone, PartialEq, Eq)]
pub enum OrbitalType {
    Core,
    Valence,
    Virtual,
    HOMO,
    LUMO,
}

/// Electron density representation
#[derive(Debug, Clone)]
pub struct ElectronDensity {
    /// Grid points
    pub grid_points: Vec<[f64; 3]>,
    /// Density values at grid points
    pub density_values: Vec<f64>,
    /// Density matrix
    pub density_matrix: Vec<Vec<f64>>,
    /// Mulliken charges
    pub mulliken_charges: Vec<f64>,
    /// Electrostatic potential
    pub electrostatic_potential: Vec<f64>,
}

/// Thermochemical properties
#[derive(Debug, Clone)]
pub struct ThermochemicalProperties {
    /// Zero-point vibrational energy
    pub zero_point_energy: f64,
    /// Thermal energy correction
    pub thermal_energy: f64,
    /// Enthalpy
    pub enthalpy: f64,
    /// Entropy
    pub entropy: f64,
    /// Free energy
    pub free_energy: f64,
    /// Heat capacity
    pub heat_capacity: f64,
    /// Temperature for calculations
    pub temperature: f64,
}

/// Calculation metadata
#[derive(Debug, Clone)]
pub struct CalculationMetadata {
    /// Calculation method used
    pub method: ElectronicStructureMethod,
    /// Basis set used
    pub basis_set: BasisSet,
    /// SCF convergence achieved
    pub scf_converged: bool,
    /// Number of SCF iterations
    pub scf_iterations: usize,
    /// CPU time
    pub cpu_time: f64,
    /// Wall time
    pub wall_time: f64,
    /// Memory usage
    pub memory_usage: usize,
    /// Error correction applied
    pub error_correction_applied: bool,
}

/// Chemical reaction representation
#[derive(Debug, Clone)]
pub struct ChemicalReaction {
    /// Reaction identifier
    pub id: String,
    /// Reactant molecules
    pub reactants: Vec<MolecularSystem>,
    /// Product molecules
    pub products: Vec<MolecularSystem>,
    /// Transition state
    pub transition_state: Option<MolecularSystem>,
    /// Catalysts
    pub catalysts: Vec<MolecularSystem>,
    /// Reaction conditions
    pub conditions: ReactionConditions,
    /// Reaction mechanism
    pub mechanism: ReactionMechanism,
}

/// Reaction conditions
#[derive(Debug, Clone)]
pub struct ReactionConditions {
    /// Temperature
    pub temperature: f64,
    /// Pressure
    pub pressure: f64,
    /// Solvent
    pub solvent: Option<String>,
    /// pH
    pub ph: Option<f64>,
    /// Concentration
    pub concentrations: HashMap<String, f64>,
}

/// Reaction mechanism
#[derive(Debug, Clone)]
pub struct ReactionMechanism {
    /// Elementary steps
    pub steps: Vec<ElementaryStep>,
    /// Rate constants
    pub rate_constants: Vec<f64>,
    /// Activation energies
    pub activation_energies: Vec<f64>,
    /// Pre-exponential factors
    pub pre_exponential_factors: Vec<f64>,
}

/// Elementary reaction step
#[derive(Debug, Clone)]
pub struct ElementaryStep {
    /// Step identifier
    pub id: String,
    /// Reactants in this step
    pub reactants: Vec<String>,
    /// Products in this step
    pub products: Vec<String>,
    /// Transition state for this step
    pub transition_state: Option<String>,
    /// Step type
    pub step_type: StepType,
}

/// Types of elementary steps
#[derive(Debug, Clone, PartialEq, Eq)]
pub enum StepType {
    Association,
    Dissociation,
    Substitution,
    Elimination,
    Addition,
    Rearrangement,
    ElectronTransfer,
    ProtonTransfer,
}

/// Catalysis optimization problem
#[derive(Debug, Clone)]
pub struct CatalysisOptimization {
    /// Target reaction
    pub reaction: ChemicalReaction,
    /// Catalyst candidates
    pub catalyst_candidates: Vec<MolecularSystem>,
    /// Optimization objectives
    pub objectives: Vec<CatalysisObjective>,
    /// Constraints
    pub constraints: Vec<CatalysisConstraint>,
    /// Screening parameters
    pub screening_params: CatalysisScreeningParams,
}

/// Catalysis optimization objectives
#[derive(Debug, Clone)]
pub enum CatalysisObjective {
    /// Minimize activation energy
    MinimizeActivationEnergy,
    /// Maximize turnover frequency
    MaximizeTurnoverFrequency,
    /// Maximize selectivity
    MaximizeSelectivity,
    /// Minimize cost
    MinimizeCost,
    /// Maximize stability
    MaximizeStability,
}

/// Catalysis constraints
#[derive(Debug, Clone)]
pub enum CatalysisConstraint {
    /// Maximum cost constraint
    MaxCost(f64),
    /// Minimum stability
    MinStability(f64),
    /// Environmental constraints
    Environmental(Vec<String>),
    /// Synthesis constraints
    SynthesisComplexity(f64),
}

/// Catalysis screening parameters
#[derive(Debug, Clone)]
pub struct CatalysisScreeningParams {
    /// Maximum number of candidates to evaluate
    pub max_candidates: usize,
    /// Accuracy threshold
    pub accuracy_threshold: f64,
    /// Use machine learning screening
    pub use_ml_screening: bool,
    /// Active learning enabled
    pub active_learning: bool,
}

impl QuantumChemistryOptimizer {
    /// Create new quantum chemistry optimizer
    pub fn new(config: QuantumChemistryConfig) -> ApplicationResult<Self> {
        let advanced_algorithms = AdvancedQuantumAlgorithms::new();
        let error_correction = NoiseResilientAnnealingProtocol::new(
            AnnealingParams::new(),
            SystemNoiseModel::default(),
            NoiseResilientConfig::default(),
        )?;
        let adaptive_qec = RealTimeAdaptiveQec::new(Default::default());
        let meta_learning = MetaLearningOptimizer::new(Default::default());
        let neural_scheduler = NeuralAnnealingScheduler::new(NeuralSchedulerConfig::default())
            .map_err(|e| ApplicationError::ConfigurationError(e))?;

        let monitoring = if config.monitoring_enabled {
            Some(crate::enterprise_monitoring::create_example_enterprise_monitoring()?)
        } else {
            None
        };

        Ok(Self {
            config,
            advanced_algorithms,
            error_correction,
            adaptive_qec,
            meta_learning,
            neural_scheduler,
            monitoring,
            system_cache: HashMap::new(),
        })
    }

    /// Calculate electronic structure
    pub fn calculate_electronic_structure(
        &mut self,
        system: &MolecularSystem,
    ) -> ApplicationResult<QuantumChemistryResult> {
        if let Some(monitoring) = &self.monitoring {
            monitoring.log(
                LogLevel::Info,
                &format!(
                    "Starting electronic structure calculation for system {}",
                    system.id
                ),
                None,
            )?;
        }

        // Check cache first
        if let Some(cached_result) = self.system_cache.get(&system.id) {
            return Ok(cached_result.clone());
        }

        // Convert molecular system to quantum problem
        let (qubo_model, _) = self.molecular_system_to_qubo(system)?;

        // Apply error correction
        let corrected_model = self.error_correction.encode_problem(&qubo_model)?;

        // Optimize using advanced algorithms
        let optimization_result = self
            .advanced_algorithms
            .optimize_problem(&corrected_model)?;

        // Convert back to chemistry result
        let chemistry_result = self.interpret_quantum_result(system, &optimization_result)?;

        // Cache result
        self.system_cache
            .insert(system.id.clone(), chemistry_result.clone());

        if let Some(monitoring) = &self.monitoring {
            monitoring.log(
                LogLevel::Info,
                &format!(
                    "Completed electronic structure calculation for system {}",
                    system.id
                ),
                None,
            )?;
        }

        Ok(chemistry_result)
    }

    /// Optimize catalysis design
    pub fn optimize_catalysis(
        &mut self,
        problem: &CatalysisOptimization,
    ) -> ApplicationResult<CatalysisOptimizationResult> {
        use std::time::Instant;
        let start_time = Instant::now();

        if let Some(monitoring) = &self.monitoring {
            monitoring.log(
                LogLevel::Info,
                &format!(
                    "Starting catalysis optimization for reaction {}",
                    problem.reaction.id
                ),
                None,
            )?;
        }

        let mut best_catalyst = None;
        let mut best_score = f64::NEG_INFINITY;
        let mut evaluated_candidates = Vec::new();

        // Screen catalyst candidates
        for (i, candidate) in problem.catalyst_candidates.iter().enumerate() {
            if i >= problem.screening_params.max_candidates {
                break;
            }

            // Calculate reaction energetics with this catalyst
            let energetics =
                self.calculate_reaction_energetics(&problem.reaction, Some(candidate))?;

            // Evaluate objectives
            let score = self.evaluate_catalysis_objectives(&problem.objectives, &energetics)?;

            evaluated_candidates.push(CatalystEvaluation {
                catalyst: candidate.clone(),
                energetics,
                score,
                meets_constraints: self.check_catalysis_constraints(
                    &problem.constraints,
                    candidate,
                    score,
                )?,
            });

            if score > best_score {
                best_score = score;
                best_catalyst = Some(candidate.clone());
            }
        }

        if let Some(monitoring) = &self.monitoring {
            monitoring.log(
                LogLevel::Info,
                &format!(
                    "Completed catalysis optimization, evaluated {} candidates",
                    evaluated_candidates.len()
                ),
                None,
            )?;
        }

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

        Ok(CatalysisOptimizationResult {
            best_catalyst,
            best_score,
            evaluated_candidates,
            optimization_time,
        })
    }

    /// Calculate reaction energetics
    pub fn calculate_reaction_energetics(
        &mut self,
        reaction: &ChemicalReaction,
        catalyst: Option<&MolecularSystem>,
    ) -> ApplicationResult<ReactionEnergetics> {
        let mut reactant_energies = Vec::new();
        let mut product_energies = Vec::new();

        // Calculate energies for reactants
        for reactant in &reaction.reactants {
            let result = self.calculate_electronic_structure(reactant)?;
            reactant_energies.push(result.total_energy);
        }

        // Calculate energies for products
        for product in &reaction.products {
            let result = self.calculate_electronic_structure(product)?;
            product_energies.push(result.total_energy);
        }

        // Calculate transition state energy if available
        let transition_state_energy = if let Some(ts) = &reaction.transition_state {
            Some(self.calculate_electronic_structure(ts)?.total_energy)
        } else {
            None
        };

        // Calculate catalyst binding energies if present
        let catalyst_binding_energy = if let Some(cat) = catalyst {
            Some(self.calculate_electronic_structure(cat)?.total_energy)
        } else {
            None
        };

        let total_reactant_energy: f64 = reactant_energies.iter().sum();
        let total_product_energy: f64 = product_energies.iter().sum();
        let reaction_energy = total_product_energy - total_reactant_energy;

        let activation_energy = if let Some(ts_energy) = transition_state_energy {
            ts_energy - total_reactant_energy
        } else {
            // Estimate activation energy using Bell-Evans-Polanyi relation
            0.3f64.mul_add(reaction_energy.abs(), 20.0) // kcal/mol
        };

        // Estimate reaction entropy using empirical formula
        // ΔS ≈ R * ln(n_products/n_reactants) + contribution from reaction type
        let gas_constant = 8.314; // J/(mol·K)
        let n_reactants = reaction.reactants.len() as f64;
        let n_products = reaction.products.len() as f64;

        // Base entropy change from stoichiometry
        let stoichiometric_entropy = gas_constant * (n_products / n_reactants).ln();

        // Additional entropy contribution from molecular complexity
        // More atoms typically correlate with higher entropy
        let reactant_atoms: usize = reaction.reactants.iter().map(|r| r.atoms.len()).sum();
        let product_atoms: usize = reaction.products.iter().map(|p| p.atoms.len()).sum();
        let complexity_entropy = 0.5 * (product_atoms as f64 - reactant_atoms as f64);

        let reaction_entropy = stoichiometric_entropy + complexity_entropy;

        Ok(ReactionEnergetics {
            reactant_energies,
            product_energies,
            transition_state_energy,
            catalyst_binding_energy,
            reaction_energy,
            activation_energy,
            reaction_enthalpy: reaction_energy, // Simplified
            reaction_entropy,
        })
    }

    /// Private helper methods
    fn molecular_system_to_qubo(
        &self,
        system: &MolecularSystem,
    ) -> ApplicationResult<(QuboModel, HashMap<String, usize>)> {
        let n_atoms = system.atoms.len();
        let n_basis = system
            .atoms
            .iter()
            .map(|a| a.basis_functions.len())
            .sum::<usize>();

        // Create QUBO model with variables for molecular orbitals
        let mut qubo = QuboModel::new(n_basis);
        let mut variable_mapping = HashMap::new();

        // Add electronic structure terms
        for i in 0..n_basis {
            // Kinetic energy terms
            qubo.set_linear(i, -1.0)?;
            variable_mapping.insert(format!("orbital_{i}"), i);

            // Electron-electron repulsion
            for j in (i + 1)..n_basis {
                qubo.set_quadratic(i, j, 0.5)?;
            }
        }

        // Add nuclear-electron attraction terms
        for (atom_idx, atom) in system.atoms.iter().enumerate() {
            for i in 0..n_basis {
                let attraction = -f64::from(atom.atomic_number) / (atom_idx + 1) as f64;
                qubo.add_linear(i, attraction)?;
            }
        }

        Ok((qubo, variable_mapping))
    }

    fn interpret_quantum_result(
        &self,
        system: &MolecularSystem,
        result: &AnnealingResult<AnnealingSolution>,
    ) -> ApplicationResult<QuantumChemistryResult> {
        let n_atoms = system.atoms.len();
        let n_basis = system
            .atoms
            .iter()
            .map(|a| a.basis_functions.len())
            .sum::<usize>();

        // Extract molecular orbitals from solution
        let solution = result
            .as_ref()
            .map_err(|e| ApplicationError::OptimizationError(e.to_string()))?;
        let mut molecular_orbitals = Vec::new();
        for i in 0..n_basis {
            let occupation = if i < solution.best_spins.len() {
                if solution.best_spins[i] == 1 {
                    2.0
                } else {
                    0.0
                }
            } else {
                0.0
            };

            molecular_orbitals.push(MolecularOrbital {
                energy: -1.0 * i as f64, // Simplified
                coefficients: vec![1.0; n_basis],
                occupation,
                symmetry: None,
                orbital_type: if i < n_atoms / 2 {
                    OrbitalType::Core
                } else if i < n_atoms {
                    OrbitalType::Valence
                } else {
                    OrbitalType::Virtual
                },
            });
        }

        // Calculate electron density
        let electron_density = ElectronDensity {
            grid_points: vec![[0.0, 0.0, 0.0]; 100],
            density_values: vec![1.0; 100],
            density_matrix: vec![vec![0.0; n_basis]; n_basis],
            mulliken_charges: vec![0.0; n_atoms],
            electrostatic_potential: vec![0.0; 100],
        };

        // Calculate properties
        let electronic_energy = solution.best_energy;
        let nuclear_repulsion = self.calculate_nuclear_repulsion(system);
        let total_energy = electronic_energy + nuclear_repulsion;

        Ok(QuantumChemistryResult {
            system_id: system.id.clone(),
            electronic_energy,
            nuclear_repulsion,
            total_energy,
            molecular_orbitals,
            electron_density,
            dipole_moment: [0.0, 0.0, 0.0],
            polarizability: [[0.0; 3]; 3],
            vibrational_frequencies: vec![],
            thermochemistry: ThermochemicalProperties {
                zero_point_energy: 0.0,
                thermal_energy: 0.0,
                enthalpy: total_energy,
                entropy: 0.0,
                free_energy: total_energy,
                heat_capacity: 0.0,
                temperature: 298.15,
            },
            metadata: CalculationMetadata {
                method: self.config.method.clone(),
                basis_set: self.config.basis_set.clone(),
                scf_converged: true,
                scf_iterations: 1,
                cpu_time: 1.0,
                wall_time: 1.0,
                memory_usage: 1024,
                error_correction_applied: true,
            },
        })
    }

    fn calculate_nuclear_repulsion(&self, system: &MolecularSystem) -> f64 {
        let mut repulsion = 0.0;

        for (i, atom1) in system.atoms.iter().enumerate() {
            for (j, atom2) in system.atoms.iter().enumerate() {
                if i < j {
                    let dx = atom1.position[0] - atom2.position[0];
                    let dy = atom1.position[1] - atom2.position[1];
                    let dz = atom1.position[2] - atom2.position[2];
                    let distance = dz.mul_add(dz, dx.mul_add(dx, dy * dy)).sqrt();

                    if distance > 1e-10 {
                        repulsion +=
                            f64::from(atom1.atomic_number * atom2.atomic_number) / distance;
                    }
                }
            }
        }

        repulsion
    }

    fn evaluate_catalysis_objectives(
        &self,
        objectives: &[CatalysisObjective],
        energetics: &ReactionEnergetics,
    ) -> ApplicationResult<f64> {
        let mut total_score = 0.0;

        for objective in objectives {
            let score = match objective {
                CatalysisObjective::MinimizeActivationEnergy => {
                    -energetics.activation_energy / 100.0 // Normalize
                }
                CatalysisObjective::MaximizeTurnoverFrequency => {
                    // TOF ∝ exp(-Ea/RT)
                    let rt = 0.592; // kcal/mol at 298K
                    (-energetics.activation_energy / rt).exp()
                }
                CatalysisObjective::MaximizeSelectivity => {
                    // Simplified selectivity based on activation energy difference
                    1.0 / (1.0 + energetics.activation_energy.abs())
                }
                CatalysisObjective::MinimizeCost => {
                    // Cost estimate based on catalyst binding energy
                    // Higher binding energy often correlates with rare/expensive catalytic elements
                    let cost_estimate = energetics.catalyst_binding_energy.unwrap_or(1.0).abs();
                    // Normalize to 0-1 range for objective function (lower is better)
                    -cost_estimate / 100.0 // Negative because we minimize
                }
                CatalysisObjective::MaximizeStability => {
                    // Stability related to binding energy
                    energetics.catalyst_binding_energy.unwrap_or(0.0).abs() / 10.0
                }
            };
            total_score += score;
        }

        Ok(total_score / objectives.len() as f64)
    }

    fn check_catalysis_constraints(
        &self,
        constraints: &[CatalysisConstraint],
        catalyst: &MolecularSystem,
        score: f64,
    ) -> ApplicationResult<bool> {
        for constraint in constraints {
            match constraint {
                CatalysisConstraint::MaxCost(max_cost) => {
                    // Calculate catalyst cost based on atomic composition
                    // Rare elements (e.g., Pt, Pd, Rh) have higher costs
                    let cost = self.calculate_catalyst_cost(catalyst)?;
                    if cost > *max_cost {
                        return Ok(false);
                    }
                }
                CatalysisConstraint::MinStability(min_stability) => {
                    if score < *min_stability {
                        return Ok(false);
                    }
                }
                CatalysisConstraint::Environmental(requirements) => {
                    // Check environmental constraints
                    let env_score = self.calculate_environmental_impact(catalyst)?;
                    // Check if toxicity is acceptable (max toxicity = 5.0)
                    let max_acceptable_toxicity = 5.0;
                    if env_score > max_acceptable_toxicity
                        || !self.check_sustainability_requirements(catalyst, requirements)?
                    {
                        return Ok(false);
                    }
                }
                CatalysisConstraint::SynthesisComplexity(max_complexity) => {
                    // Calculate synthesis complexity
                    let complexity = self.calculate_synthesis_complexity(catalyst)?;
                    if complexity > *max_complexity {
                        return Ok(false);
                    }
                }
            }
        }
        Ok(true)
    }

    /// Calculate catalyst cost based on elemental composition
    fn calculate_catalyst_cost(&self, catalyst: &MolecularSystem) -> ApplicationResult<f64> {
        // Cost per gram for common catalytic elements (USD/g, approximate)
        let element_costs: HashMap<String, f64> = [
            ("H".to_string(), 0.001),
            ("C".to_string(), 0.05),
            ("N".to_string(), 0.01),
            ("O".to_string(), 0.01),
            ("Fe".to_string(), 0.1),
            ("Ni".to_string(), 1.0),
            ("Cu".to_string(), 0.5),
            ("Pd".to_string(), 50.0),
            ("Pt".to_string(), 100.0),
            ("Rh".to_string(), 150.0),
            ("Ru".to_string(), 20.0),
        ]
        .iter()
        .cloned()
        .collect();

        let mut total_cost = 0.0;
        for atom in &catalyst.atoms {
            let cost_per_gram = element_costs.get(&atom.symbol).unwrap_or(&1.0);
            total_cost += cost_per_gram;
        }

        Ok(total_cost)
    }

    /// Calculate environmental impact score
    fn calculate_environmental_impact(&self, catalyst: &MolecularSystem) -> ApplicationResult<f64> {
        // Toxicity scores for elements (0 = benign, 10 = highly toxic)
        let element_toxicity: HashMap<String, f64> = [
            ("H".to_string(), 0.0),
            ("C".to_string(), 0.0),
            ("N".to_string(), 1.0),
            ("O".to_string(), 0.0),
            ("Fe".to_string(), 1.0),
            ("Ni".to_string(), 3.0),
            ("Cu".to_string(), 2.0),
            ("Pd".to_string(), 2.0),
            ("Pt".to_string(), 2.0),
            ("Rh".to_string(), 3.0),
            ("Ru".to_string(), 3.0),
            ("Hg".to_string(), 9.0),
            ("Pb".to_string(), 8.0),
            ("Cd".to_string(), 8.0),
            ("As".to_string(), 9.0),
        ]
        .iter()
        .cloned()
        .collect();

        let mut max_toxicity = 0.0;
        for atom in &catalyst.atoms {
            let toxicity = element_toxicity.get(&atom.symbol).unwrap_or(&5.0);
            if *toxicity > max_toxicity {
                max_toxicity = *toxicity;
            }
        }

        Ok(max_toxicity)
    }

    /// Check sustainability requirements
    fn check_sustainability_requirements(
        &self,
        catalyst: &MolecularSystem,
        requirements: &Vec<String>,
    ) -> ApplicationResult<bool> {
        // Check if catalyst uses abundant elements
        let abundant_elements = ["H", "C", "N", "O", "Fe", "Si", "Al"];
        let total_atoms = catalyst.atoms.len();
        let abundant_count = catalyst
            .atoms
            .iter()
            .filter(|a| abundant_elements.contains(&a.symbol.as_str()))
            .count();

        // Check if specific requirements are met
        for req in requirements {
            if req == "no_heavy_metals" {
                let heavy_metals = ["Hg", "Pb", "Cd", "As"];
                if catalyst
                    .atoms
                    .iter()
                    .any(|a| heavy_metals.contains(&a.symbol.as_str()))
                {
                    return Ok(false);
                }
            }
        }

        // At least 70% should be from abundant elements for sustainability
        Ok(abundant_count as f64 / total_atoms as f64 > 0.7)
    }

    /// Calculate synthesis complexity
    fn calculate_synthesis_complexity(&self, catalyst: &MolecularSystem) -> ApplicationResult<f64> {
        // Complexity based on:
        // 1. Number of different elements
        // 2. Total number of atoms
        // 3. Structural complexity (estimated)

        let mut unique_elements = HashSet::new();
        for atom in &catalyst.atoms {
            unique_elements.insert(&atom.symbol);
        }

        let element_diversity = unique_elements.len() as f64;
        let size_factor = (catalyst.atoms.len() as f64).sqrt();

        // Simple complexity metric
        let complexity = element_diversity.mul_add(0.5, size_factor * 0.3);

        Ok(complexity)
    }
}

/// Reaction energetics
#[derive(Debug, Clone)]
pub struct ReactionEnergetics {
    /// Energies of reactants
    pub reactant_energies: Vec<f64>,
    /// Energies of products
    pub product_energies: Vec<f64>,
    /// Transition state energy
    pub transition_state_energy: Option<f64>,
    /// Catalyst binding energy
    pub catalyst_binding_energy: Option<f64>,
    /// Overall reaction energy
    pub reaction_energy: f64,
    /// Activation energy
    pub activation_energy: f64,
    /// Reaction enthalpy
    pub reaction_enthalpy: f64,
    /// Reaction entropy
    pub reaction_entropy: f64,
}

/// Catalyst evaluation result
#[derive(Debug, Clone)]
pub struct CatalystEvaluation {
    /// Catalyst system
    pub catalyst: MolecularSystem,
    /// Calculated energetics
    pub energetics: ReactionEnergetics,
    /// Overall score
    pub score: f64,
    /// Whether constraints are satisfied
    pub meets_constraints: bool,
}

/// Catalysis optimization result
#[derive(Debug, Clone)]
pub struct CatalysisOptimizationResult {
    /// Best catalyst found
    pub best_catalyst: Option<MolecularSystem>,
    /// Best score achieved
    pub best_score: f64,
    /// All evaluated candidates
    pub evaluated_candidates: Vec<CatalystEvaluation>,
    /// Optimization time
    pub optimization_time: f64,
}

/// Create example molecular systems for testing
pub fn create_example_molecular_systems() -> ApplicationResult<Vec<MolecularSystem>> {
    let mut systems = Vec::new();

    // Water molecule
    let water = MolecularSystem {
        id: "water".to_string(),
        charge: 0,
        multiplicity: 1,
        atoms: vec![
            Atom {
                atomic_number: 8,
                symbol: "O".to_string(),
                mass: 15.999,
                position: [0.0, 0.0, 0.0],
                partial_charge: Some(-0.834),
                basis_functions: vec![BasisFunction {
                    function_type: BasisFunctionType::GTO,
                    angular_momentum: (0, 0, 0),
                    exponent: 130.7093,
                    coefficients: vec![0.1543],
                    center: [0.0, 0.0, 0.0],
                }],
            },
            Atom {
                atomic_number: 1,
                symbol: "H".to_string(),
                mass: 1.008,
                position: [0.758, 0.0, 0.586],
                partial_charge: Some(0.417),
                basis_functions: vec![BasisFunction {
                    function_type: BasisFunctionType::GTO,
                    angular_momentum: (0, 0, 0),
                    exponent: 3.425_251,
                    coefficients: vec![0.1543],
                    center: [0.758, 0.0, 0.586],
                }],
            },
            Atom {
                atomic_number: 1,
                symbol: "H".to_string(),
                mass: 1.008,
                position: [-0.758, 0.0, 0.586],
                partial_charge: Some(0.417),
                basis_functions: vec![BasisFunction {
                    function_type: BasisFunctionType::GTO,
                    angular_momentum: (0, 0, 0),
                    exponent: 3.425_251,
                    coefficients: vec![0.1543],
                    center: [-0.758, 0.0, 0.586],
                }],
            },
        ],
        geometry: MolecularGeometry {
            coordinate_system: CoordinateSystem::Cartesian,
            bonds: vec![
                Bond {
                    atom1: 0,
                    atom2: 1,
                    length: 0.96,
                    order: BondOrder::Single,
                    strength: 460.0,
                },
                Bond {
                    atom1: 0,
                    atom2: 2,
                    length: 0.96,
                    order: BondOrder::Single,
                    strength: 460.0,
                },
            ],
            angles: vec![Angle {
                atom1: 1,
                atom2: 0,
                atom3: 2,
                angle: 104.5_f64.to_radians(),
            }],
            dihedrals: vec![],
            point_group: Some("C2v".to_string()),
        },
        external_fields: vec![],
        constraints: vec![],
    };
    systems.push(water);

    // Methane molecule
    let methane = MolecularSystem {
        id: "methane".to_string(),
        charge: 0,
        multiplicity: 1,
        atoms: vec![
            Atom {
                atomic_number: 6,
                symbol: "C".to_string(),
                mass: 12.011,
                position: [0.0, 0.0, 0.0],
                partial_charge: Some(-0.4),
                basis_functions: vec![BasisFunction {
                    function_type: BasisFunctionType::GTO,
                    angular_momentum: (0, 0, 0),
                    exponent: 71.6168,
                    coefficients: vec![0.1543],
                    center: [0.0, 0.0, 0.0],
                }],
            },
            Atom {
                atomic_number: 1,
                symbol: "H".to_string(),
                mass: 1.008,
                position: [0.629, 0.629, 0.629],
                partial_charge: Some(0.1),
                basis_functions: vec![BasisFunction {
                    function_type: BasisFunctionType::GTO,
                    angular_momentum: (0, 0, 0),
                    exponent: 3.425_251,
                    coefficients: vec![0.1543],
                    center: [0.629, 0.629, 0.629],
                }],
            },
            Atom {
                atomic_number: 1,
                symbol: "H".to_string(),
                mass: 1.008,
                position: [-0.629, -0.629, 0.629],
                partial_charge: Some(0.1),
                basis_functions: vec![BasisFunction {
                    function_type: BasisFunctionType::GTO,
                    angular_momentum: (0, 0, 0),
                    exponent: 3.425_251,
                    coefficients: vec![0.1543],
                    center: [-0.629, -0.629, 0.629],
                }],
            },
            Atom {
                atomic_number: 1,
                symbol: "H".to_string(),
                mass: 1.008,
                position: [-0.629, 0.629, -0.629],
                partial_charge: Some(0.1),
                basis_functions: vec![BasisFunction {
                    function_type: BasisFunctionType::GTO,
                    angular_momentum: (0, 0, 0),
                    exponent: 3.425_251,
                    coefficients: vec![0.1543],
                    center: [-0.629, 0.629, -0.629],
                }],
            },
            Atom {
                atomic_number: 1,
                symbol: "H".to_string(),
                mass: 1.008,
                position: [0.629, -0.629, -0.629],
                partial_charge: Some(0.1),
                basis_functions: vec![BasisFunction {
                    function_type: BasisFunctionType::GTO,
                    angular_momentum: (0, 0, 0),
                    exponent: 3.425_251,
                    coefficients: vec![0.1543],
                    center: [0.629, -0.629, -0.629],
                }],
            },
        ],
        geometry: MolecularGeometry {
            coordinate_system: CoordinateSystem::Cartesian,
            bonds: vec![
                Bond {
                    atom1: 0,
                    atom2: 1,
                    length: 1.09,
                    order: BondOrder::Single,
                    strength: 414.0,
                },
                Bond {
                    atom1: 0,
                    atom2: 2,
                    length: 1.09,
                    order: BondOrder::Single,
                    strength: 414.0,
                },
                Bond {
                    atom1: 0,
                    atom2: 3,
                    length: 1.09,
                    order: BondOrder::Single,
                    strength: 414.0,
                },
                Bond {
                    atom1: 0,
                    atom2: 4,
                    length: 1.09,
                    order: BondOrder::Single,
                    strength: 414.0,
                },
            ],
            angles: vec![],
            dihedrals: vec![],
            point_group: Some("Td".to_string()),
        },
        external_fields: vec![],
        constraints: vec![],
    };
    systems.push(methane);

    Ok(systems)
}

/// Create benchmark problems for quantum computational chemistry
pub fn create_benchmark_problems(
    num_problems: usize,
) -> ApplicationResult<
    Vec<Box<dyn OptimizationProblem<Solution = QuantumChemistryResult, ObjectiveValue = f64>>>,
> {
    let mut problems = Vec::new();
    let systems = create_example_molecular_systems()?;

    for i in 0..num_problems {
        let system = systems[i % systems.len()].clone();
        let problem = QuantumChemistryProblem {
            system,
            config: QuantumChemistryConfig::default(),
            objectives: vec![ChemistryObjective::MinimizeEnergy],
        };
        problems.push(Box::new(problem)
            as Box<
                dyn OptimizationProblem<Solution = QuantumChemistryResult, ObjectiveValue = f64>,
            >);
    }

    Ok(problems)
}

/// Quantum chemistry optimization problem
#[derive(Debug, Clone)]
pub struct QuantumChemistryProblem {
    pub system: MolecularSystem,
    pub config: QuantumChemistryConfig,
    pub objectives: Vec<ChemistryObjective>,
}

/// Chemistry optimization objectives
#[derive(Debug, Clone)]
pub enum ChemistryObjective {
    MinimizeEnergy,
    MaximizeStability,
    OptimizeGeometry,
    MinimizeInteractionEnergy,
}

impl OptimizationProblem for QuantumChemistryProblem {
    type Solution = QuantumChemistryResult;
    type ObjectiveValue = f64;

    fn description(&self) -> String {
        format!(
            "Quantum computational chemistry optimization for system: {}",
            self.system.id
        )
    }

    fn size_metrics(&self) -> HashMap<String, usize> {
        let mut metrics = HashMap::new();
        metrics.insert("atoms".to_string(), self.system.atoms.len());
        metrics.insert(
            "basis_functions".to_string(),
            self.system
                .atoms
                .iter()
                .map(|a| a.basis_functions.len())
                .sum(),
        );
        metrics
    }

    fn validate(&self) -> ApplicationResult<()> {
        if self.system.atoms.is_empty() {
            return Err(ApplicationError::InvalidConfiguration(
                "No atoms in molecular system".to_string(),
            ));
        }
        Ok(())
    }

    fn to_qubo(&self) -> ApplicationResult<(QuboModel, HashMap<String, usize>)> {
        let mut optimizer = QuantumChemistryOptimizer::new(self.config.clone())?;
        optimizer.molecular_system_to_qubo(&self.system)
    }

    fn evaluate_solution(
        &self,
        solution: &Self::Solution,
    ) -> ApplicationResult<Self::ObjectiveValue> {
        let mut score = 0.0;

        for objective in &self.objectives {
            let obj_score = match objective {
                ChemistryObjective::MinimizeEnergy => -solution.total_energy,
                ChemistryObjective::MaximizeStability => solution.total_energy.abs(),
                ChemistryObjective::OptimizeGeometry => solution.total_energy.abs() / 10.0,
                ChemistryObjective::MinimizeInteractionEnergy => -solution.electronic_energy,
            };
            score += obj_score;
        }

        Ok(score / self.objectives.len() as f64)
    }

    fn is_feasible(&self, solution: &Self::Solution) -> bool {
        solution.metadata.scf_converged && solution.total_energy.is_finite()
    }
}

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

    #[test]
    fn test_quantum_chemistry_optimizer_creation() {
        let config = QuantumChemistryConfig::default();
        let optimizer = QuantumChemistryOptimizer::new(config);
        assert!(optimizer.is_ok());
    }

    #[test]
    fn test_molecular_system_creation() {
        let systems =
            create_example_molecular_systems().expect("should create example molecular systems");
        assert_eq!(systems.len(), 2);
        assert_eq!(systems[0].id, "water");
        assert_eq!(systems[1].id, "methane");
    }

    #[test]
    fn test_benchmark_problems() {
        let problems = create_benchmark_problems(5).expect("should create benchmark problems");
        assert_eq!(problems.len(), 5);
    }

    #[test]
    fn test_quantum_chemistry_problem_validation() {
        let systems =
            create_example_molecular_systems().expect("should create molecular systems for test");
        let problem = QuantumChemistryProblem {
            system: systems[0].clone(),
            config: QuantumChemistryConfig::default(),
            objectives: vec![ChemistryObjective::MinimizeEnergy],
        };

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