quantrs2_tytan/sampler/hardware/

azure_quantum.rs

//! Azure Quantum Sampler Implementation
//!
//! This module provides integration with Microsoft Azure Quantum
//! for solving optimization problems using various quantum and quantum-inspired solvers.

use scirs2_core::ndarray::{Array, Ix2};
use scirs2_core::random::{thread_rng, Rng};
use std::collections::HashMap;

use quantrs2_anneal::QuboModel;

use super::super::{SampleResult, Sampler, SamplerError, SamplerResult};

/// Azure Quantum solver types
#[derive(Debug, Clone)]
pub enum AzureSolver {
    /// Microsoft QIO - Simulated Annealing
    SimulatedAnnealing,
    /// Microsoft QIO - Parallel Tempering
    ParallelTempering,
    /// Microsoft QIO - Tabu Search
    TabuSearch,
    /// Microsoft QIO - Population Annealing
    PopulationAnnealing,
    /// Microsoft QIO - Substrate Monte Carlo
    SubstrateMonteCarlo,
    /// IonQ quantum computer
    IonQ,
    /// Quantinuum (Honeywell) quantum computer
    Quantinuum,
    /// Rigetti quantum computer
    Rigetti,
}

/// Azure Quantum Sampler Configuration
#[derive(Debug, Clone)]
pub struct AzureQuantumConfig {
    /// Azure subscription ID
    pub subscription_id: String,
    /// Resource group name
    pub resource_group: String,
    /// Workspace name
    pub workspace_name: String,
    /// Solver to use
    pub solver: AzureSolver,
    /// Timeout in seconds
    pub timeout: u64,
    /// Additional solver-specific parameters
    pub solver_params: HashMap<String, String>,
}

impl Default for AzureQuantumConfig {
    fn default() -> Self {
        Self {
            subscription_id: String::new(),
            resource_group: String::new(),
            workspace_name: String::new(),
            solver: AzureSolver::SimulatedAnnealing,
            timeout: 300,
            solver_params: HashMap::new(),
        }
    }
}

/// Azure Quantum Sampler
///
/// This sampler connects to Microsoft Azure Quantum to solve QUBO problems
/// using various quantum and quantum-inspired optimization solvers.
pub struct AzureQuantumSampler {
    config: AzureQuantumConfig,
}

impl AzureQuantumSampler {
    /// Create a new Azure Quantum sampler
    ///
    /// # Arguments
    ///
    /// * `config` - The Azure Quantum configuration
    #[must_use]
    pub const fn new(config: AzureQuantumConfig) -> Self {
        Self { config }
    }

    /// Create a new Azure Quantum sampler with workspace details
    ///
    /// # Arguments
    ///
    /// * `subscription_id` - Azure subscription ID
    /// * `resource_group` - Resource group name
    /// * `workspace_name` - Workspace name
    #[must_use]
    pub fn with_workspace(
        subscription_id: &str,
        resource_group: &str,
        workspace_name: &str,
    ) -> Self {
        Self {
            config: AzureQuantumConfig {
                subscription_id: subscription_id.to_string(),
                resource_group: resource_group.to_string(),
                workspace_name: workspace_name.to_string(),
                ..Default::default()
            },
        }
    }

    /// Set the solver to use
    #[must_use]
    pub const fn with_solver(mut self, solver: AzureSolver) -> Self {
        self.config.solver = solver;
        self
    }

    /// Set the timeout
    #[must_use]
    pub const fn with_timeout(mut self, timeout: u64) -> Self {
        self.config.timeout = timeout;
        self
    }

    /// Add a solver-specific parameter
    #[must_use]
    pub fn with_param(mut self, key: String, value: String) -> Self {
        self.config.solver_params.insert(key, value);
        self
    }
}

impl Sampler for AzureQuantumSampler {
    fn run_qubo(
        &self,
        qubo: &(Array<f64, Ix2>, HashMap<String, usize>),
        shots: usize,
    ) -> SamplerResult<Vec<SampleResult>> {
        // Extract matrix and variable mapping
        let (matrix, var_map) = qubo;

        // Get the problem dimension
        let n_vars = var_map.len();

        // Validate problem size based on solver
        match self.config.solver {
            AzureSolver::IonQ => {
                if n_vars > 29 {
                    return Err(SamplerError::InvalidParameter(
                        "IonQ currently supports up to 29 qubits".to_string(),
                    ));
                }
            }
            AzureSolver::Quantinuum => {
                if n_vars > 20 {
                    return Err(SamplerError::InvalidParameter(
                        "Quantinuum currently supports up to 20 qubits for this application"
                            .to_string(),
                    ));
                }
            }
            AzureSolver::Rigetti => {
                if n_vars > 40 {
                    return Err(SamplerError::InvalidParameter(
                        "Rigetti currently supports up to 40 qubits".to_string(),
                    ));
                }
            }
            _ => {
                // QIO solvers can handle larger problems
                if n_vars > 10000 {
                    return Err(SamplerError::InvalidParameter(
                        "Problem size exceeds Azure QIO limits".to_string(),
                    ));
                }
            }
        }

        // Map from indices back to variable names
        let idx_to_var: HashMap<usize, String> = var_map
            .iter()
            .map(|(var, &idx)| (idx, var.clone()))
            .collect();

        // Convert ndarray to a QuboModel
        let mut qubo_model = QuboModel::new(n_vars);

        // Set linear and quadratic terms
        for i in 0..n_vars {
            if matrix[[i, i]] != 0.0 {
                qubo_model.set_linear(i, matrix[[i, i]])?;
            }

            for j in (i + 1)..n_vars {
                if matrix[[i, j]] != 0.0 {
                    qubo_model.set_quadratic(i, j, matrix[[i, j]])?;
                }
            }
        }

        // Initialize the Azure Quantum client
        #[cfg(feature = "azure_quantum")]
        {
            // TODO: Implement actual Azure Quantum API integration
            // This would involve:
            // 1. Authenticate with Azure
            // 2. Submit job to selected solver
            // 3. Poll for completion
            // 4. Retrieve and process results

            let _azure_result = "placeholder";
        }

        // Placeholder implementation - simulate Azure Quantum behavior
        let mut results = Vec::new();
        let mut rng = thread_rng();

        // Different solvers have different characteristics
        let unique_solutions = match self.config.solver {
            AzureSolver::SimulatedAnnealing => shots.min(50),
            AzureSolver::ParallelTempering => shots.min(100),
            AzureSolver::TabuSearch => shots.min(30),
            AzureSolver::PopulationAnnealing => shots.min(200),
            AzureSolver::SubstrateMonteCarlo => shots.min(150),
            AzureSolver::IonQ | AzureSolver::Quantinuum | AzureSolver::Rigetti => {
                // Quantum hardware typically provides many measurement samples
                shots.min(1000)
            }
        };

        for _ in 0..unique_solutions {
            let assignments: HashMap<String, bool> = idx_to_var
                .values()
                .map(|name| (name.clone(), rng.gen::<bool>()))
                .collect();

            // Calculate energy
            let mut energy = 0.0;
            for (var_name, &val) in &assignments {
                let i = var_map[var_name];
                if val {
                    energy += matrix[[i, i]];
                    for (other_var, &other_val) in &assignments {
                        let j = var_map[other_var];
                        if i < j && other_val {
                            energy += matrix[[i, j]];
                        }
                    }
                }
            }

            // Simulate measurement counts
            let occurrences = match self.config.solver {
                AzureSolver::IonQ | AzureSolver::Quantinuum | AzureSolver::Rigetti => {
                    // Quantum solvers return actual shot counts
                    rng.gen_range(1..=(shots / unique_solutions + 10))
                }
                _ => {
                    // Classical solvers return occurrence frequencies
                    1
                }
            };

            results.push(SampleResult {
                assignments,
                energy,
                occurrences,
            });
        }

        // Sort by energy (best solutions first)
        results.sort_by(|a, b| {
            a.energy
                .partial_cmp(&b.energy)
                .unwrap_or(std::cmp::Ordering::Equal)
        });

        // Limit results to requested number
        results.truncate(shots.min(100));

        Ok(results)
    }

    fn run_hobo(
        &self,
        hobo: &(
            Array<f64, scirs2_core::ndarray::IxDyn>,
            HashMap<String, usize>,
        ),
        shots: usize,
    ) -> SamplerResult<Vec<SampleResult>> {
        use scirs2_core::ndarray::Ix2;

        // For HOBO problems, convert to QUBO if possible
        if hobo.0.ndim() <= 2 {
            // If it's already 2D, just forward to run_qubo
            let qubo_matrix = hobo.0.clone().into_dimensionality::<Ix2>().map_err(|e| {
                SamplerError::InvalidParameter(format!(
                    "Failed to convert HOBO to QUBO dimensionality: {e}"
                ))
            })?;
            let qubo = (qubo_matrix, hobo.1.clone());
            self.run_qubo(&qubo, shots)
        } else {
            // Azure Quantum doesn't directly support higher-order problems
            Err(SamplerError::InvalidParameter(
                "Azure Quantum doesn't support HOBO problems directly. Use a quadratization technique first.".to_string()
            ))
        }
    }
}

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

    #[test]
    fn test_azure_quantum_config() {
        let config = AzureQuantumConfig::default();
        assert_eq!(config.timeout, 300);
        assert!(matches!(config.solver, AzureSolver::SimulatedAnnealing));
    }

    #[test]
    fn test_azure_quantum_sampler_creation() {
        let sampler =
            AzureQuantumSampler::with_workspace("test-subscription", "test-rg", "test-workspace")
                .with_solver(AzureSolver::ParallelTempering)
                .with_timeout(600)
                .with_param("temperature".to_string(), "0.5".to_string());

        assert_eq!(sampler.config.subscription_id, "test-subscription");
        assert_eq!(sampler.config.resource_group, "test-rg");
        assert_eq!(sampler.config.workspace_name, "test-workspace");
        assert_eq!(sampler.config.timeout, 600);
        assert!(matches!(
            sampler.config.solver,
            AzureSolver::ParallelTempering
        ));
    }

    #[test]
    fn test_azure_solver_types() {
        let solvers = [
            AzureSolver::SimulatedAnnealing,
            AzureSolver::ParallelTempering,
            AzureSolver::TabuSearch,
            AzureSolver::PopulationAnnealing,
            AzureSolver::SubstrateMonteCarlo,
            AzureSolver::IonQ,
            AzureSolver::Quantinuum,
            AzureSolver::Rigetti,
        ];

        assert_eq!(solvers.len(), 8);
    }
}