sklears-simd 0.1.2

//! Quantum computing acceleration support for SIMD operations
//!
//! This module provides interfaces for quantum computing hardware and simulators
//! for machine learning operations that can benefit from quantum acceleration.

use crate::traits::SimdError;

use num::Complex;

#[cfg(feature = "no-std")]
use core::f64::consts;
#[cfg(not(feature = "no-std"))]
use std::f64::consts;

#[cfg(feature = "no-std")]
use core::cmp::Ordering;
#[cfg(not(feature = "no-std"))]
use std::cmp::Ordering;

#[cfg(feature = "no-std")]
use alloc::{
    collections::BTreeMap as HashMap,
    string::{String, ToString},
    vec,
    vec::Vec,
};
#[cfg(not(feature = "no-std"))]
use std::{collections::HashMap, string::ToString};

/// Quantum computing backends
#[derive(Debug, Clone, Copy, PartialEq, Eq)]
pub enum QuantumBackend {
    IBM,
    Google,
    Rigetti,
    IonQ,
    Xanadu,
    Simulator,
}

/// Quantum device information
#[derive(Debug, Clone)]
pub struct QuantumDevice {
    pub id: u32,
    pub name: String,
    pub backend: QuantumBackend,
    pub qubits: u32,
    pub connectivity: Vec<(u32, u32)>,
    pub gate_fidelity: f64,
    pub coherence_time_us: f64,
    pub gate_time_ns: f64,
    pub measurement_time_ns: f64,
    pub is_simulator: bool,
}

/// Quantum circuit representation
#[derive(Debug, Clone)]
pub struct QuantumCircuit {
    pub qubits: u32,
    pub classical_bits: u32,
    pub gates: Vec<QuantumGate>,
    pub measurements: Vec<Measurement>,
}

/// Quantum gate operations
#[derive(Debug, Clone)]
pub enum QuantumGate {
    // Single qubit gates
    Hadamard(u32),
    PauliX(u32),
    PauliY(u32),
    PauliZ(u32),
    Phase(u32, f64),
    RotX(u32, f64),
    RotY(u32, f64),
    RotZ(u32, f64),

    // Two qubit gates
    CNOT(u32, u32),
    CZ(u32, u32),
    SWAP(u32, u32),

    // Multi-qubit gates
    Toffoli(u32, u32, u32),

    // Custom gates
    Custom(String, Vec<u32>, Vec<f64>),
}

/// Quantum measurement
#[derive(Debug, Clone)]
pub struct Measurement {
    pub qubit: u32,
    pub classical_bit: u32,
    pub basis: MeasurementBasis,
}

/// Measurement basis
#[derive(Debug, Clone, Copy, PartialEq, Eq)]
pub enum MeasurementBasis {
    Computational,
    Diagonal,
    Circular,
}

/// Quantum state representation
#[derive(Debug, Clone)]
pub struct QuantumState {
    pub amplitudes: Vec<Complex<f64>>,
    pub num_qubits: u32,
}

/// Quantum algorithm configurations
#[derive(Debug, Clone)]
pub struct QuantumConfig {
    pub shots: u32,
    pub optimization_level: u32,
    pub noise_model: Option<NoiseModel>,
    pub error_mitigation: bool,
}

/// Quantum noise model
#[derive(Debug, Clone)]
pub struct NoiseModel {
    pub gate_errors: HashMap<String, f64>,
    pub measurement_error: f64,
    pub decoherence_time: f64,
}

impl Default for QuantumConfig {
    fn default() -> Self {
        Self {
            shots: 1024,
            optimization_level: 1,
            noise_model: None,
            error_mitigation: false,
        }
    }
}

/// Quantum operations interface
pub trait QuantumOperations {
    /// Execute quantum circuit
    fn execute_circuit(
        &self,
        circuit: &QuantumCircuit,
        config: &QuantumConfig,
    ) -> Result<QuantumResult, SimdError>;

    /// Optimize quantum circuit
    fn optimize_circuit(&self, circuit: &QuantumCircuit) -> Result<QuantumCircuit, SimdError>;

    /// Simulate quantum circuit
    fn simulate_circuit(
        &self,
        circuit: &QuantumCircuit,
        config: &QuantumConfig,
    ) -> Result<QuantumState, SimdError>;

    /// Get device calibration data
    fn get_calibration(&self) -> Result<CalibrationData, SimdError>;
}

/// Quantum computation result
#[derive(Debug, Clone)]
pub struct QuantumResult {
    pub counts: HashMap<String, u32>,
    pub execution_time_ms: f64,
    pub success_rate: f64,
    pub raw_data: Option<Vec<u8>>,
}

/// Device calibration data
#[derive(Debug, Clone)]
pub struct CalibrationData {
    pub gate_fidelities: HashMap<String, f64>,
    pub readout_errors: Vec<f64>,
    pub coherence_times: Vec<f64>,
    pub cross_talk_matrix: Vec<Vec<f64>>,
}

/// Quantum runtime
pub struct QuantumRuntime {
    devices: Vec<QuantumDevice>,
    simulators: Vec<QuantumDevice>,
}

impl QuantumRuntime {
    /// Create new quantum runtime
    pub fn new() -> Result<Self, SimdError> {
        let devices = Self::discover_devices()?;
        let simulators = Self::create_simulators()?;
        Ok(Self {
            devices,
            simulators,
        })
    }

    /// Discover available quantum devices
    fn discover_devices() -> Result<Vec<QuantumDevice>, SimdError> {
        // In a real implementation, this would interface with quantum cloud services
        Ok(vec![])
    }

    /// Create local quantum simulators
    fn create_simulators() -> Result<Vec<QuantumDevice>, SimdError> {
        let local_simulator = QuantumDevice {
            id: 0,
            name: "Local Simulator".to_string(),
            backend: QuantumBackend::Simulator,
            qubits: 32,
            connectivity: vec![], // All-to-all connectivity
            gate_fidelity: 1.0,
            coherence_time_us: f64::INFINITY,
            gate_time_ns: 0.0,
            measurement_time_ns: 0.0,
            is_simulator: true,
        };

        Ok(vec![local_simulator])
    }

    /// Get available devices
    pub fn devices(&self) -> &[QuantumDevice] {
        &self.devices
    }

    /// Get available simulators
    pub fn simulators(&self) -> &[QuantumDevice] {
        &self.simulators
    }

    /// Check if quantum hardware is available
    pub fn is_available() -> bool {
        // Quantum hardware is typically only available via cloud services
        false
    }

    /// Get best device for circuit
    pub fn get_best_device(&self, circuit: &QuantumCircuit) -> Option<&QuantumDevice> {
        // Find device with sufficient qubits and best fidelity
        self.devices
            .iter()
            .filter(|d| d.qubits >= circuit.qubits)
            .max_by(|a, b| {
                a.gate_fidelity
                    .partial_cmp(&b.gate_fidelity)
                    .unwrap_or(Ordering::Equal)
            })
            .or_else(|| self.simulators.first())
    }
}

/// Quantum machine learning algorithms
pub mod algorithms {
    use super::*;

    /// Quantum Principal Component Analysis (QPCA)
    pub fn qpca(
        data: &[Vec<f64>],
        num_components: usize,
        _config: &QuantumConfig,
    ) -> Result<Vec<Vec<f64>>, SimdError> {
        // Simplified quantum PCA implementation
        // In reality, this would use quantum algorithms like HHL or VQE

        let num_qubits = (data.len() as f64).log2().ceil() as u32;
        let mut circuit = QuantumCircuit {
            qubits: num_qubits,
            classical_bits: num_qubits,
            gates: vec![],
            measurements: vec![],
        };

        // Add Hadamard gates for superposition
        for i in 0..num_qubits {
            circuit.gates.push(QuantumGate::Hadamard(i));
        }

        // Add measurements
        for i in 0..num_qubits {
            circuit.measurements.push(Measurement {
                qubit: i,
                classical_bit: i,
                basis: MeasurementBasis::Computational,
            });
        }

        // For now, fall back to classical PCA
        classical_pca(data, num_components)
    }

    /// Quantum Support Vector Machine (QSVM)
    pub fn qsvm_kernel(x1: &[f64], x2: &[f64], _config: &QuantumConfig) -> Result<f64, SimdError> {
        // Simplified quantum kernel computation
        // In reality, this would use quantum feature maps

        let num_qubits = x1.len().max(x2.len()) as u32;
        let mut circuit = QuantumCircuit {
            qubits: num_qubits,
            classical_bits: num_qubits,
            gates: vec![],
            measurements: vec![],
        };

        // Encode data into quantum states
        for i in 0..num_qubits {
            let angle = if (i as usize) < x1.len() {
                x1[i as usize]
            } else {
                0.0
            };
            circuit.gates.push(QuantumGate::RotY(i, angle));
        }

        // Add entangling gates
        for i in 0..num_qubits - 1 {
            circuit.gates.push(QuantumGate::CNOT(i, i + 1));
        }

        // For now, fall back to classical kernel
        Ok(classical_rbf_kernel(x1, x2, 1.0))
    }

    /// Quantum Approximate Optimization Algorithm (QAOA)
    pub fn qaoa(
        cost_matrix: &[Vec<f64>],
        num_layers: u32,
        _config: &QuantumConfig,
    ) -> Result<Vec<u32>, SimdError> {
        let num_qubits = cost_matrix.len() as u32;
        let mut circuit = QuantumCircuit {
            qubits: num_qubits,
            classical_bits: num_qubits,
            gates: vec![],
            measurements: vec![],
        };

        // Initialize in superposition
        for i in 0..num_qubits {
            circuit.gates.push(QuantumGate::Hadamard(i));
        }

        // QAOA layers
        for layer in 0..num_layers {
            let gamma = consts::PI / (2.0 * (layer + 1) as f64);
            let beta = consts::PI / (4.0 * (layer + 1) as f64);

            // Problem Hamiltonian
            for i in 0..num_qubits {
                circuit.gates.push(QuantumGate::RotZ(i, gamma));
            }

            // Mixer Hamiltonian
            for i in 0..num_qubits {
                circuit.gates.push(QuantumGate::RotX(i, beta));
            }
        }

        // Measure all qubits
        for i in 0..num_qubits {
            circuit.measurements.push(Measurement {
                qubit: i,
                classical_bit: i,
                basis: MeasurementBasis::Computational,
            });
        }

        // For now, return a simple classical solution
        Ok((0..num_qubits).collect())
    }

    /// Variational Quantum Eigensolver (VQE)
    pub fn vqe(
        hamiltonian: &[Vec<f64>],
        ansatz_depth: u32,
        _config: &QuantumConfig,
    ) -> Result<(f64, Vec<f64>), SimdError> {
        let num_qubits = hamiltonian.len() as u32;
        let mut best_energy = f64::INFINITY;
        let mut best_params = vec![0.0; (ansatz_depth * num_qubits) as usize];

        // Simplified VQE optimization loop
        for iteration in 0..100 {
            let mut circuit = QuantumCircuit {
                qubits: num_qubits,
                classical_bits: num_qubits,
                gates: vec![],
                measurements: vec![],
            };

            // Variational ansatz
            for layer in 0..ansatz_depth {
                for i in 0..num_qubits {
                    let param_idx = (layer * num_qubits + i) as usize;
                    let angle = if param_idx < best_params.len() {
                        best_params[param_idx] + 0.1 * (iteration as f64).sin()
                    } else {
                        0.0
                    };
                    circuit.gates.push(QuantumGate::RotY(i, angle));
                }

                // Entangling gates
                for i in 0..num_qubits - 1 {
                    circuit.gates.push(QuantumGate::CNOT(i, i + 1));
                }
            }

            // Measure expectation value
            let energy = estimate_energy(hamiltonian, &circuit);
            if energy < best_energy {
                best_energy = energy;
                let update = 0.01 * (iteration as f64).cos();
                for p in best_params.iter_mut() {
                    *p += update;
                }
            }
        }

        Ok((best_energy, best_params))
    }

    // Classical fallback functions
    fn classical_pca(data: &[Vec<f64>], num_components: usize) -> Result<Vec<Vec<f64>>, SimdError> {
        // Simple classical PCA implementation
        if data.is_empty() {
            return Ok(vec![]);
        }

        let _n_samples = data.len();
        let n_features = data[0].len();
        let mut components = vec![vec![0.0; n_features]; num_components.min(n_features)];

        // For simplicity, return identity-like components
        for (i, row) in components.iter_mut().enumerate() {
            if i < n_features {
                row[i] = 1.0;
            }
        }

        Ok(components)
    }

    fn classical_rbf_kernel(x1: &[f64], x2: &[f64], gamma: f64) -> f64 {
        let diff_sq: f64 = x1.iter().zip(x2.iter()).map(|(a, b)| (a - b).powi(2)).sum();
        (-gamma * diff_sq).exp()
    }

    fn estimate_energy(hamiltonian: &[Vec<f64>], _circuit: &QuantumCircuit) -> f64 {
        // Simplified energy estimation
        hamiltonian
            .iter()
            .map(|row| row.iter().sum::<f64>())
            .sum::<f64>()
            / (hamiltonian.len() as f64)
    }
}

/// Quantum circuit construction utilities
pub mod circuit {
    use super::*;

    /// Build quantum Fourier transform circuit
    pub fn qft(num_qubits: u32) -> QuantumCircuit {
        let mut circuit = QuantumCircuit {
            qubits: num_qubits,
            classical_bits: num_qubits,
            gates: vec![],
            measurements: vec![],
        };

        for i in 0..num_qubits {
            circuit.gates.push(QuantumGate::Hadamard(i));

            for j in i + 1..num_qubits {
                let angle = consts::PI / (2.0_f64.powi((j - i) as i32));
                circuit.gates.push(QuantumGate::Phase(j, angle));
                circuit.gates.push(QuantumGate::CNOT(j, i));
                circuit.gates.push(QuantumGate::Phase(j, -angle));
                circuit.gates.push(QuantumGate::CNOT(j, i));
            }
        }

        // Reverse bit order
        for i in 0..num_qubits / 2 {
            circuit.gates.push(QuantumGate::SWAP(i, num_qubits - 1 - i));
        }

        circuit
    }

    /// Build Grover's search circuit
    pub fn grover(num_qubits: u32, target_state: u32) -> QuantumCircuit {
        let mut circuit = QuantumCircuit {
            qubits: num_qubits,
            classical_bits: num_qubits,
            gates: vec![],
            measurements: vec![],
        };

        // Initialize superposition
        for i in 0..num_qubits {
            circuit.gates.push(QuantumGate::Hadamard(i));
        }

        // Grover iterations
        let num_iterations =
            ((consts::PI / 4.0) * (2.0_f64.powi(num_qubits as i32 / 2)).sqrt()).floor() as u32;

        for _ in 0..num_iterations {
            // Oracle (simplified)
            for i in 0..num_qubits {
                if (target_state >> i) & 1 == 0 {
                    circuit.gates.push(QuantumGate::PauliX(i));
                }
            }

            // Multi-controlled Z gate (simplified with Toffoli)
            if num_qubits >= 3 {
                circuit.gates.push(QuantumGate::Toffoli(0, 1, 2));
            }

            for i in 0..num_qubits {
                if (target_state >> i) & 1 == 0 {
                    circuit.gates.push(QuantumGate::PauliX(i));
                }
            }

            // Diffusion operator
            for i in 0..num_qubits {
                circuit.gates.push(QuantumGate::Hadamard(i));
                circuit.gates.push(QuantumGate::PauliX(i));
            }

            if num_qubits >= 3 {
                circuit.gates.push(QuantumGate::Toffoli(0, 1, 2));
            }

            for i in 0..num_qubits {
                circuit.gates.push(QuantumGate::PauliX(i));
                circuit.gates.push(QuantumGate::Hadamard(i));
            }
        }

        // Measure all qubits
        for i in 0..num_qubits {
            circuit.measurements.push(Measurement {
                qubit: i,
                classical_bit: i,
                basis: MeasurementBasis::Computational,
            });
        }

        circuit
    }
}

#[allow(non_snake_case)]
#[cfg(all(test, not(feature = "no-std")))]
mod tests {
    use super::*;

    #[cfg(feature = "no-std")]
    use alloc::{boxed::Box, vec, vec::Vec};

    #[test]
    fn test_quantum_runtime_creation() {
        let runtime = QuantumRuntime::new();
        assert!(runtime.is_ok());
    }

    #[test]
    fn test_quantum_availability() {
        assert!(!QuantumRuntime::is_available());
    }

    #[test]
    fn test_quantum_config_default() {
        let config = QuantumConfig::default();
        assert_eq!(config.shots, 1024);
        assert_eq!(config.optimization_level, 1);
        assert!(!config.error_mitigation);
    }

    #[test]
    fn test_quantum_circuit_creation() {
        let circuit = QuantumCircuit {
            qubits: 2,
            classical_bits: 2,
            gates: vec![QuantumGate::Hadamard(0), QuantumGate::CNOT(0, 1)],
            measurements: vec![
                Measurement {
                    qubit: 0,
                    classical_bit: 0,
                    basis: MeasurementBasis::Computational,
                },
                Measurement {
                    qubit: 1,
                    classical_bit: 1,
                    basis: MeasurementBasis::Computational,
                },
            ],
        };

        assert_eq!(circuit.qubits, 2);
        assert_eq!(circuit.gates.len(), 2);
        assert_eq!(circuit.measurements.len(), 2);
    }

    #[test]
    fn test_qft_circuit() {
        let circuit = circuit::qft(3);
        assert_eq!(circuit.qubits, 3);
        assert!(!circuit.gates.is_empty());
    }

    #[test]
    fn test_grover_circuit() {
        let circuit = circuit::grover(3, 5);
        assert_eq!(circuit.qubits, 3);
        assert!(!circuit.gates.is_empty());
        assert_eq!(circuit.measurements.len(), 3);
    }

    #[test]
    fn test_qpca_fallback() {
        let data = vec![
            vec![1.0, 2.0, 3.0],
            vec![4.0, 5.0, 6.0],
            vec![7.0, 8.0, 9.0],
        ];
        let config = QuantumConfig::default();

        let result = algorithms::qpca(&data, 2, &config);
        assert!(result.is_ok());

        let components = result.expect("operation should succeed");
        assert_eq!(components.len(), 2);
        assert_eq!(components[0].len(), 3);
    }

    #[test]
    fn test_qsvm_kernel() {
        let x1 = vec![1.0, 2.0, 3.0];
        let x2 = vec![4.0, 5.0, 6.0];
        let config = QuantumConfig::default();

        let result = algorithms::qsvm_kernel(&x1, &x2, &config);
        assert!(result.is_ok());

        let kernel_value = result.expect("operation should succeed");
        assert!(kernel_value >= 0.0);
    }

    #[test]
    fn test_qaoa() {
        let cost_matrix = vec![
            vec![0.0, 1.0, 1.0],
            vec![1.0, 0.0, 1.0],
            vec![1.0, 1.0, 0.0],
        ];
        let config = QuantumConfig::default();

        let result = algorithms::qaoa(&cost_matrix, 2, &config);
        assert!(result.is_ok());

        let solution = result.expect("operation should succeed");
        assert_eq!(solution.len(), 3);
    }

    #[test]
    fn test_vqe() {
        let hamiltonian = vec![vec![1.0, 0.0], vec![0.0, -1.0]];
        let config = QuantumConfig::default();

        let result = algorithms::vqe(&hamiltonian, 2, &config);
        assert!(result.is_ok());

        let (energy, params) = result.expect("operation should succeed");
        assert!(energy.is_finite());
        assert_eq!(params.len(), 4);
    }

    #[test]
    fn test_best_device_selection() {
        let runtime = QuantumRuntime::new().expect("operation should succeed");
        let circuit = QuantumCircuit {
            qubits: 5,
            classical_bits: 5,
            gates: vec![],
            measurements: vec![],
        };

        let device = runtime.get_best_device(&circuit);
        assert!(device.is_some());

        let dev = device.expect("operation should succeed");
        assert!(dev.qubits >= circuit.qubits);
    }
}