quantrs2_tytan/sampler/hardware/

ibm_quantum.rs

//! IBM Quantum Sampler Implementation
//!
//! This module provides integration with IBM Quantum (IBM Q) systems
//! for solving optimization problems using quantum annealing approaches.

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};

/// IBM Quantum backend types
#[derive(Debug, Clone)]
pub enum IBMBackend {
    /// IBM Quantum simulator
    Simulator,
    /// IBM Quantum hardware - specific backend name
    Hardware(String),
    /// IBM Quantum hardware - any available backend
    AnyHardware,
}

/// IBM Quantum Sampler Configuration
#[derive(Debug, Clone)]
pub struct IBMQuantumConfig {
    /// IBM Quantum API token
    pub api_token: String,
    /// Backend to use for execution
    pub backend: IBMBackend,
    /// Maximum circuit depth allowed
    pub max_circuit_depth: usize,
    /// Optimization level (0-3)
    pub optimization_level: u8,
    /// Number of shots per execution
    pub shots: usize,
    /// Use error mitigation techniques
    pub error_mitigation: bool,
}

impl Default for IBMQuantumConfig {
    fn default() -> Self {
        Self {
            api_token: String::new(),
            backend: IBMBackend::Simulator,
            max_circuit_depth: 100,
            optimization_level: 1,
            shots: 1024,
            error_mitigation: true,
        }
    }
}

/// IBM Quantum Sampler
///
/// This sampler connects to IBM Quantum systems to solve QUBO problems
/// using variational quantum algorithms like QAOA.
pub struct IBMQuantumSampler {
    config: IBMQuantumConfig,
}

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

    /// Create a new IBM Quantum sampler with API token
    ///
    /// # Arguments
    ///
    /// * `api_token` - The IBM Quantum API token
    #[must_use]
    pub fn with_token(api_token: &str) -> Self {
        Self {
            config: IBMQuantumConfig {
                api_token: api_token.to_string(),
                ..Default::default()
            },
        }
    }

    /// Set the backend to use
    #[must_use]
    pub fn with_backend(mut self, backend: IBMBackend) -> Self {
        self.config.backend = backend;
        self
    }

    /// Enable or disable error mitigation
    #[must_use]
    pub const fn with_error_mitigation(mut self, enabled: bool) -> Self {
        self.config.error_mitigation = enabled;
        self
    }

    /// Set the optimization level
    #[must_use]
    pub fn with_optimization_level(mut self, level: u8) -> Self {
        self.config.optimization_level = level.min(3);
        self
    }
}

impl Sampler for IBMQuantumSampler {
    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 for IBM Quantum
        if n_vars > 127 {
            return Err(SamplerError::InvalidParameter(
                "IBM Quantum currently supports up to 127 qubits".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 IBM Quantum client
        #[cfg(feature = "ibm_quantum")]
        {
            // TODO: Implement actual IBM Quantum API integration
            // This would involve:
            // 1. Create QAOA circuit for the QUBO problem
            // 2. Optimize circuit parameters
            // 3. Submit to IBM Quantum backend
            // 4. Process measurement results

            let _ibm_result = "placeholder";
        }

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

        // Simulate quantum measurements with error mitigation
        let effective_shots = if self.config.error_mitigation {
            shots * 2 // More shots for error mitigation
        } else {
            shots
        };

        // Generate diverse solutions (simulating QAOA behavior)
        let unique_solutions = (effective_shots / 10).max(1).min(100);

        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 = rng.gen_range(1..=(effective_shots / unique_solutions + 10));

            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)
        });

        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 {
            // IBM Quantum doesn't directly support higher-order problems
            Err(SamplerError::InvalidParameter(
                "IBM Quantum doesn't support HOBO problems directly. Use a quadratization technique first.".to_string()
            ))
        }
    }
}

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

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

    #[test]
    fn test_ibm_quantum_sampler_creation() {
        let sampler = IBMQuantumSampler::with_token("test_token")
            .with_backend(IBMBackend::Simulator)
            .with_error_mitigation(true)
            .with_optimization_level(2);

        assert_eq!(sampler.config.api_token, "test_token");
        assert_eq!(sampler.config.optimization_level, 2);
        assert!(sampler.config.error_mitigation);
    }

    #[test]
    fn test_ibm_quantum_backend_types() {
        let simulator = IBMBackend::Simulator;
        let hardware = IBMBackend::Hardware("ibmq_lima".to_string());
        let any = IBMBackend::AnyHardware;

        // Test that backends can be cloned
        let _sim_clone = simulator;
        let _hw_clone = hardware;
        let _any_clone = any;
    }
}