quantrs2_tytan/sampler/hardware/

amazon_braket.rs

//! Amazon Braket Sampler Implementation
//!
//! This module provides integration with Amazon Braket
//! for solving optimization problems using various quantum devices and simulators.

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};

/// Amazon Braket device types
#[derive(Debug, Clone)]
pub enum BraketDevice {
    /// Local simulator (SV1)
    LocalSimulator,
    /// State vector simulator (managed)
    StateVectorSimulator,
    /// Tensor network simulator (managed)
    TensorNetworkSimulator,
    /// IonQ trapped ion device
    IonQDevice,
    /// Rigetti superconducting device
    RigettiDevice(String),
    /// Oxford Quantum Circuits (OQC) device
    OQCDevice,
    /// D-Wave quantum annealer
    DWaveAdvantage,
    /// D-Wave 2000Q
    DWave2000Q,
}

/// Amazon Braket Sampler Configuration
#[derive(Debug, Clone)]
pub struct AmazonBraketConfig {
    /// AWS region
    pub region: String,
    /// S3 bucket for results
    pub s3_bucket: String,
    /// S3 prefix for results
    pub s3_prefix: String,
    /// Device to use
    pub device: BraketDevice,
    /// Maximum parallel tasks
    pub max_parallel: usize,
    /// Poll interval in seconds
    pub poll_interval: u64,
}

impl Default for AmazonBraketConfig {
    fn default() -> Self {
        Self {
            region: "us-east-1".to_string(),
            s3_bucket: String::new(),
            s3_prefix: "braket-results".to_string(),
            device: BraketDevice::LocalSimulator,
            max_parallel: 10,
            poll_interval: 5,
        }
    }
}

/// Amazon Braket Sampler
///
/// This sampler connects to Amazon Braket to solve QUBO problems
/// using various quantum devices and simulators.
pub struct AmazonBraketSampler {
    config: AmazonBraketConfig,
}

impl AmazonBraketSampler {
    /// Create a new Amazon Braket sampler
    ///
    /// # Arguments
    ///
    /// * `config` - The Amazon Braket configuration
    #[must_use]
    pub const fn new(config: AmazonBraketConfig) -> Self {
        Self { config }
    }

    /// Create a new Amazon Braket sampler with S3 bucket
    ///
    /// # Arguments
    ///
    /// * `s3_bucket` - S3 bucket for results
    /// * `region` - AWS region
    #[must_use]
    pub fn with_s3(s3_bucket: &str, region: &str) -> Self {
        Self {
            config: AmazonBraketConfig {
                s3_bucket: s3_bucket.to_string(),
                region: region.to_string(),
                ..Default::default()
            },
        }
    }

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

    /// Set the maximum number of parallel tasks
    #[must_use]
    pub const fn with_max_parallel(mut self, max_parallel: usize) -> Self {
        self.config.max_parallel = max_parallel;
        self
    }

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

impl Sampler for AmazonBraketSampler {
    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 device
        match &self.config.device {
            BraketDevice::LocalSimulator | BraketDevice::StateVectorSimulator => {
                if n_vars > 34 {
                    return Err(SamplerError::InvalidParameter(
                        "State vector simulators support up to 34 qubits".to_string(),
                    ));
                }
            }
            BraketDevice::TensorNetworkSimulator => {
                if n_vars > 50 {
                    return Err(SamplerError::InvalidParameter(
                        "Tensor network simulator supports up to 50 qubits".to_string(),
                    ));
                }
            }
            BraketDevice::IonQDevice => {
                if n_vars > 29 {
                    return Err(SamplerError::InvalidParameter(
                        "IonQ device supports up to 29 qubits".to_string(),
                    ));
                }
            }
            BraketDevice::RigettiDevice(_) => {
                if n_vars > 40 {
                    return Err(SamplerError::InvalidParameter(
                        "Rigetti devices support up to 40 qubits".to_string(),
                    ));
                }
            }
            BraketDevice::OQCDevice => {
                if n_vars > 8 {
                    return Err(SamplerError::InvalidParameter(
                        "OQC device supports up to 8 qubits".to_string(),
                    ));
                }
            }
            BraketDevice::DWaveAdvantage => {
                if n_vars > 5000 {
                    return Err(SamplerError::InvalidParameter(
                        "D-Wave Advantage supports up to 5000 variables".to_string(),
                    ));
                }
            }
            BraketDevice::DWave2000Q => {
                if n_vars > 2000 {
                    return Err(SamplerError::InvalidParameter(
                        "D-Wave 2000Q supports up to 2000 variables".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 Amazon Braket client
        #[cfg(feature = "amazon_braket")]
        {
            // TODO: Implement actual Amazon Braket API integration
            // This would involve:
            // 1. Create Braket circuit or annealing problem
            // 2. Submit task to selected device
            // 3. Poll S3 for results
            // 4. Process and return measurements

            let _braket_result = "placeholder";
        }

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

        // Different devices have different characteristics
        let unique_solutions = match &self.config.device {
            BraketDevice::DWaveAdvantage | BraketDevice::DWave2000Q => {
                // Quantum annealers return many diverse solutions
                shots.min(1000)
            }
            BraketDevice::LocalSimulator | BraketDevice::StateVectorSimulator => {
                // Simulators can efficiently generate solutions
                shots.min(500)
            }
            BraketDevice::TensorNetworkSimulator => shots.min(300),
            _ => {
                // Hardware devices return measurement samples
                shots.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 = match &self.config.device {
                BraketDevice::DWaveAdvantage | BraketDevice::DWave2000Q => {
                    // Annealers return occurrence counts
                    rng.gen_range(1..=(shots / unique_solutions + 20))
                }
                _ => {
                    // Other devices return shot counts
                    rng.gen_range(1..=(shots / unique_solutions + 5))
                }
            };

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

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

    #[test]
    fn test_amazon_braket_config() {
        let config = AmazonBraketConfig::default();
        assert_eq!(config.region, "us-east-1");
        assert_eq!(config.s3_prefix, "braket-results");
        assert_eq!(config.max_parallel, 10);
        assert!(matches!(config.device, BraketDevice::LocalSimulator));
    }

    #[test]
    fn test_amazon_braket_sampler_creation() {
        let sampler = AmazonBraketSampler::with_s3("my-bucket", "us-west-2")
            .with_device(BraketDevice::IonQDevice)
            .with_max_parallel(20)
            .with_poll_interval(10);

        assert_eq!(sampler.config.s3_bucket, "my-bucket");
        assert_eq!(sampler.config.region, "us-west-2");
        assert_eq!(sampler.config.max_parallel, 20);
        assert_eq!(sampler.config.poll_interval, 10);
        assert!(matches!(sampler.config.device, BraketDevice::IonQDevice));
    }

    #[test]
    fn test_braket_device_types() {
        let devices = [
            BraketDevice::LocalSimulator,
            BraketDevice::StateVectorSimulator,
            BraketDevice::TensorNetworkSimulator,
            BraketDevice::IonQDevice,
            BraketDevice::RigettiDevice("Aspen-M-3".to_string()),
            BraketDevice::OQCDevice,
            BraketDevice::DWaveAdvantage,
            BraketDevice::DWave2000Q,
        ];

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

    #[test]
    fn test_braket_device_limits() {
        // Test that devices have different qubit limits
        let sv_device = BraketDevice::StateVectorSimulator;
        let tn_device = BraketDevice::TensorNetworkSimulator;
        let dwave_device = BraketDevice::DWaveAdvantage;

        // Different devices have different characteristics
        assert!(matches!(sv_device, BraketDevice::StateVectorSimulator));
        assert!(matches!(tn_device, BraketDevice::TensorNetworkSimulator));
        assert!(matches!(dwave_device, BraketDevice::DWaveAdvantage));
    }
}