quantrs2_ml/

circuit_integration.rs

//! Circuit integration for quantum machine learning
//!
//! This module provides seamless integration between quantum ML algorithms
//! and the QuantRS2 circuit module, enabling efficient execution of
//! quantum circuits on various backends.

use crate::error::{MLError, Result};
use scirs2_core::ndarray::{Array1, Array2};
use scirs2_core::Complex64;
use quantrs2_circuit::prelude::*;
use quantrs2_core::prelude::*;
use quantrs2_sim::prelude::StateVectorSimulator;
use std::collections::HashMap;

/// Quantum circuit executor for ML applications
pub struct QuantumMLExecutor<const N: usize> {
    /// Circuit builder
    circuit_builder: CircuitBuilder<N>,
    /// Parameter mapping
    parameter_map: HashMap<String, usize>,
    /// Simulator backend
    simulator: Option<StateVectorSimulator>,
    /// Device backend
    device: Option<String>,
}

impl<const N: usize> QuantumMLExecutor<N> {
    /// Create a new quantum ML executor
    pub fn new() -> Self {
        Self {
            circuit_builder: CircuitBuilder::new(),
            parameter_map: HashMap::new(),
            simulator: None,
            device: None,
        }
    }

    /// Set simulator backend
    pub fn with_simulator(mut self, simulator: StateVectorSimulator) -> Self {
        self.simulator = Some(simulator);
        self
    }

    /// Set device backend
    pub fn with_device(mut self, device: impl Into<String>) -> Self {
        self.device = Some(device.into());
        self
    }

    /// Add a quantum layer to the circuit
    pub fn add_layer(&mut self, layer: &dyn QuantumLayer<N>) -> Result<()> {
        layer.apply_to_circuit(&mut self.circuit_builder)?;
        Ok(())
    }

    /// Register a parameter
    pub fn register_parameter(&mut self, name: impl Into<String>, index: usize) {
        self.parameter_map.insert(name.into(), index);
    }

    /// Execute circuit with given parameters
    pub fn execute(&self, parameters: &[f64]) -> Result<Array1<f64>> {
        let circuit = self.circuit_builder.clone().build();

        if let Some(ref simulator) = self.simulator {
            let state = simulator.run(&circuit)?;
            Ok(state.amplitudes().iter().map(|c| c.norm_sqr()).collect())
        } else {
            Err(MLError::InvalidConfiguration(
                "No simulator or device backend configured".to_string(),
            ))
        }
    }

    /// Execute circuit and compute expectation value
    pub fn expectation_value(&self, parameters: &[f64], observable: &PauliString) -> Result<f64> {
        let circuit = self.circuit_builder.clone().build();

        if let Some(ref simulator) = self.simulator {
            let state = simulator.run(&circuit)?;
            // Simplified expectation value calculation
            Ok(0.0) // Placeholder
        } else {
            Err(MLError::InvalidConfiguration(
                "No simulator backend configured".to_string(),
            ))
        }
    }

    /// Compute gradients using parameter shift rule
    pub fn compute_gradients(
        &self,
        parameters: &[f64],
        observable: &PauliString,
    ) -> Result<Array1<f64>> {
        let shift = std::f64::consts::PI / 2.0;
        let mut gradients = Array1::zeros(parameters.len());

        for i in 0..parameters.len() {
            // Forward shift
            let mut params_plus = parameters.to_vec();
            params_plus[i] += shift;
            let val_plus = self.expectation_value(&params_plus, observable)?;

            // Backward shift
            let mut params_minus = parameters.to_vec();
            params_minus[i] -= shift;
            let val_minus = self.expectation_value(&params_minus, observable)?;

            // Parameter shift gradient
            gradients[i] = (val_plus - val_minus) / 2.0;
        }

        Ok(gradients)
    }
}

/// Trait for quantum layers in ML circuits
pub trait QuantumLayer<const N: usize> {
    /// Apply the layer to a circuit builder
    fn apply_to_circuit(&self, builder: &mut CircuitBuilder<N>) -> Result<()>;

    /// Get the number of parameters for this layer
    fn num_parameters(&self) -> usize;

    /// Get parameter names
    fn parameter_names(&self) -> Vec<String>;
}

/// Parameterized quantum circuit layer
#[derive(Debug, Clone)]
pub struct ParameterizedLayer {
    /// Qubits this layer acts on
    qubits: Vec<usize>,
    /// Gate sequence
    gates: Vec<ParameterizedGate>,
}

impl ParameterizedLayer {
    /// Create a new parameterized layer
    pub fn new(qubits: Vec<usize>) -> Self {
        Self {
            qubits,
            gates: Vec::new(),
        }
    }

    /// Add a rotation gate
    pub fn add_rotation(
        mut self,
        qubit: usize,
        axis: RotationAxis,
        parameter_name: impl Into<String>,
    ) -> Self {
        self.gates.push(ParameterizedGate::Rotation {
            qubit,
            axis,
            parameter: parameter_name.into(),
        });
        self
    }

    /// Add an entangling gate
    pub fn add_entangling(mut self, control: usize, target: usize) -> Self {
        self.gates
            .push(ParameterizedGate::Entangling { control, target });
        self
    }
}

impl<const N: usize> QuantumLayer<N> for ParameterizedLayer {
    fn apply_to_circuit(&self, builder: &mut CircuitBuilder<N>) -> Result<()> {
        for gate in &self.gates {
            match gate {
                ParameterizedGate::Rotation {
                    qubit,
                    axis,
                    parameter,
                } => {
                    match axis {
                        RotationAxis::X => {
                            builder.rx(*qubit, 0.0)?;
                        } // Placeholder value
                        RotationAxis::Y => {
                            builder.ry(*qubit, 0.0)?;
                        }
                        RotationAxis::Z => {
                            builder.rz(*qubit, 0.0)?;
                        }
                    }
                }
                ParameterizedGate::Entangling { control, target } => {
                    builder.cnot(*control, *target)?;
                }
            }
        }
        Ok(())
    }

    fn num_parameters(&self) -> usize {
        self.gates
            .iter()
            .filter(|g| matches!(g, ParameterizedGate::Rotation { .. }))
            .count()
    }

    fn parameter_names(&self) -> Vec<String> {
        self.gates
            .iter()
            .filter_map(|g| match g {
                ParameterizedGate::Rotation { parameter, .. } => Some(parameter.clone()),
                _ => None,
            })
            .collect()
    }
}

/// Parameterized gate types
#[derive(Debug, Clone)]
enum ParameterizedGate {
    Rotation {
        qubit: usize,
        axis: RotationAxis,
        parameter: String,
    },
    Entangling {
        control: usize,
        target: usize,
    },
}

/// Rotation axis for parameterized gates
#[derive(Debug, Clone, Copy)]
pub enum RotationAxis {
    X,
    Y,
    Z,
}

/// Hardware-aware circuit compiler
pub struct HardwareAwareCompiler {
    /// Target device topology
    topology: DeviceTopology,
    /// Gate fidelities
    gate_fidelities: HashMap<String, f64>,
    /// Connectivity constraints
    connectivity: Array2<bool>,
}

impl HardwareAwareCompiler {
    /// Create a new hardware-aware compiler
    pub fn new(topology: DeviceTopology) -> Self {
        let num_qubits = topology.num_qubits();
        let connectivity = Array2::from_elem((num_qubits, num_qubits), false);

        Self {
            topology,
            gate_fidelities: HashMap::new(),
            connectivity,
        }
    }

    /// Set gate fidelity
    pub fn set_gate_fidelity(&mut self, gate: impl Into<String>, fidelity: f64) {
        self.gate_fidelities.insert(gate.into(), fidelity);
    }

    /// Compile circuit for target device
    pub fn compile<const N: usize>(&self, circuit: &Circuit<N>) -> Result<Circuit<N>> {
        // Placeholder - would implement device-specific compilation
        Ok(circuit.clone())
    }

    /// Route circuit considering connectivity constraints
    pub fn route_circuit<const N: usize>(&self, circuit: &Circuit<N>) -> Result<Circuit<N>> {
        // Placeholder - would implement SABRE routing or similar
        Ok(circuit.clone())
    }

    /// Optimize circuit for device characteristics
    pub fn optimize_for_device<const N: usize>(&self, circuit: &Circuit<N>) -> Result<Circuit<N>> {
        // Placeholder - would apply device-specific optimizations
        Ok(circuit.clone())
    }
}

/// Device topology representation
#[derive(Debug, Clone)]
pub struct DeviceTopology {
    /// Number of qubits
    num_qubits: usize,
    /// Qubit connectivity graph
    edges: Vec<(usize, usize)>,
    /// Qubit properties
    qubit_properties: Vec<QubitProperties>,
}

impl DeviceTopology {
    /// Create a new device topology
    pub fn new(num_qubits: usize) -> Self {
        Self {
            num_qubits,
            edges: Vec::new(),
            qubit_properties: vec![QubitProperties::default(); num_qubits],
        }
    }

    /// Add connectivity edge
    pub fn add_edge(mut self, q1: usize, q2: usize) -> Self {
        self.edges.push((q1, q2));
        self
    }

    /// Get number of qubits
    pub fn num_qubits(&self) -> usize {
        self.num_qubits
    }

    /// Check if two qubits are connected
    pub fn are_connected(&self, q1: usize, q2: usize) -> bool {
        self.edges.contains(&(q1, q2)) || self.edges.contains(&(q2, q1))
    }

    /// Get neighbors of a qubit
    pub fn neighbors(&self, qubit: usize) -> Vec<usize> {
        self.edges
            .iter()
            .filter_map(|(q1, q2)| {
                if *q1 == qubit {
                    Some(*q2)
                } else if *q2 == qubit {
                    Some(*q1)
                } else {
                    None
                }
            })
            .collect()
    }
}

/// Qubit properties for device characterization
#[derive(Debug, Clone)]
pub struct QubitProperties {
    /// T1 relaxation time (microseconds)
    pub t1: f64,
    /// T2 dephasing time (microseconds)
    pub t2: f64,
    /// Single-qubit gate fidelity
    pub single_gate_fidelity: f64,
    /// Readout fidelity
    pub readout_fidelity: f64,
}

impl Default for QubitProperties {
    fn default() -> Self {
        Self {
            t1: 100.0, // 100 μs
            t2: 50.0,  // 50 μs
            single_gate_fidelity: 0.999,
            readout_fidelity: 0.98,
        }
    }
}

/// Backend integration for multiple simulators
pub struct BackendManager {
    /// Available backends
    backends: HashMap<String, StateVectorSimulator>,
    /// Current backend
    current_backend: Option<String>,
}

impl BackendManager {
    /// Create a new backend manager
    pub fn new() -> Self {
        Self {
            backends: HashMap::new(),
            current_backend: None,
        }
    }

    /// Register a simulator backend
    pub fn register_backend(&mut self, name: impl Into<String>, backend: StateVectorSimulator) {
        self.backends.insert(name.into(), backend);
    }

    /// Set current backend
    pub fn set_backend(&mut self, name: impl Into<String>) -> Result<()> {
        let name = name.into();
        if self.backends.contains_key(&name) {
            self.current_backend = Some(name);
            Ok(())
        } else {
            Err(MLError::InvalidConfiguration(format!(
                "Backend '{}' not found",
                name
            )))
        }
    }

    /// Execute circuit on current backend
    pub fn execute_circuit<const N: usize>(
        &self,
        circuit: &Circuit<N>,
        parameters: &[f64],
    ) -> Result<Array1<Complex64>> {
        if let Some(ref backend_name) = self.current_backend {
            if let Some(backend) = self.backends.get(backend_name) {
                let state = backend.run(circuit)?;
                Ok(state.amplitudes().to_vec().into())
            } else {
                Err(MLError::InvalidConfiguration(
                    "Current backend not available".to_string(),
                ))
            }
        } else {
            Err(MLError::InvalidConfiguration(
                "No backend selected".to_string(),
            ))
        }
    }

    /// List available backends
    pub fn list_backends(&self) -> Vec<String> {
        self.backends.keys().cloned().collect()
    }
}

/// Circuit optimization for ML workloads
pub struct MLCircuitOptimizer {
    /// Optimization passes (using concrete types for now)
    passes: Vec<OptimizationPassType>,
}

/// Enum of optimization passes
pub enum OptimizationPassType {
    ParameterConsolidation(ParameterConsolidationPass),
    MLGateFusion(MLGateFusionPass),
}

impl MLCircuitOptimizer {
    /// Create a new ML circuit optimizer
    pub fn new() -> Self {
        Self { passes: Vec::new() }
    }

    /// Add optimization pass
    pub fn add_pass(mut self, pass: OptimizationPassType) -> Self {
        self.passes.push(pass);
        self
    }

    /// Optimize circuit for ML workloads
    pub fn optimize<const N: usize>(&self, circuit: &Circuit<N>) -> Result<Circuit<N>> {
        let mut optimized = circuit.clone();

        for pass in &self.passes {
            optimized = match pass {
                OptimizationPassType::ParameterConsolidation(p) => p.optimize(&optimized)?,
                OptimizationPassType::MLGateFusion(p) => p.optimize(&optimized)?,
            };
        }

        Ok(optimized)
    }
}

/// Trait for circuit optimization passes
pub trait OptimizationPass {
    fn optimize<const N: usize>(&self, circuit: &Circuit<N>) -> Result<Circuit<N>>;
}

/// Parameter consolidation pass
pub struct ParameterConsolidationPass;

impl OptimizationPass for ParameterConsolidationPass {
    fn optimize<const N: usize>(&self, circuit: &Circuit<N>) -> Result<Circuit<N>> {
        // Placeholder - would consolidate adjacent rotation gates
        Ok(circuit.clone())
    }
}

/// Gate fusion pass for ML circuits
pub struct MLGateFusionPass;

impl OptimizationPass for MLGateFusionPass {
    fn optimize<const N: usize>(&self, circuit: &Circuit<N>) -> Result<Circuit<N>> {
        // Placeholder - would fuse gates for better ML performance
        Ok(circuit.clone())
    }
}

/// Circuit analysis for ML applications
pub struct MLCircuitAnalyzer;

impl MLCircuitAnalyzer {
    /// Analyze circuit expressivity
    pub fn expressivity_analysis<const N: usize>(
        circuit: &Circuit<N>,
    ) -> Result<ExpressionvityMetrics> {
        Ok(ExpressionvityMetrics {
            parameter_count: 0, // Placeholder
            entangling_capability: 0.0,
            barren_plateau_susceptibility: 0.0,
        })
    }

    /// Analyze trainability
    pub fn trainability_analysis<const N: usize>(
        circuit: &Circuit<N>,
    ) -> Result<TrainabilityMetrics> {
        Ok(TrainabilityMetrics {
            gradient_variance: 0.0, // Placeholder
            parameter_shift_cost: 0.0,
            hardware_efficiency: 0.0,
        })
    }
}

/// Circuit expressivity metrics
#[derive(Debug, Clone)]
pub struct ExpressionvityMetrics {
    pub parameter_count: usize,
    pub entangling_capability: f64,
    pub barren_plateau_susceptibility: f64,
}

/// Circuit trainability metrics
#[derive(Debug, Clone)]
pub struct TrainabilityMetrics {
    pub gradient_variance: f64,
    pub parameter_shift_cost: f64,
    pub hardware_efficiency: f64,
}

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

    #[test]
    fn test_quantum_ml_executor() {
        let mut executor: QuantumMLExecutor<8> = QuantumMLExecutor::new();
        executor.register_parameter("theta1", 0);
        executor.register_parameter("theta2", 1);

        // Would add actual simulator in real implementation
        assert_eq!(executor.parameter_map.len(), 2);
    }

    #[test]
    fn test_parameterized_layer() {
        let layer = ParameterizedLayer::new(vec![0, 1])
            .add_rotation(0, RotationAxis::X, "theta1")
            .add_entangling(0, 1)
            .add_rotation(1, RotationAxis::Y, "theta2");

        assert_eq!(
            <ParameterizedLayer as QuantumLayer<8>>::num_parameters(&layer),
            2
        );
        assert_eq!(
            <ParameterizedLayer as QuantumLayer<8>>::parameter_names(&layer),
            vec!["theta1", "theta2"]
        );
    }

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

        assert!(topology.are_connected(0, 1));
        assert!(!topology.are_connected(0, 2));
        assert_eq!(topology.neighbors(1), vec![0, 2]);
    }

    #[test]
    fn test_backend_manager() {
        let mut manager = BackendManager::new();
        assert!(manager.list_backends().is_empty());

        let result = manager.set_backend("nonexistent");
        assert!(result.is_err());
    }
}