quantrs2_device/vqa_support/
hardware.rs

1//! Hardware-aware optimization and calibration for VQA
2//!
3//! This module provides hardware-specific optimizations and calibration
4//! tools for variational quantum algorithms.
5
6use crate::DeviceResult;
7use std::collections::HashMap;
8
9/// Hardware-aware VQA configuration
10#[derive(Debug, Clone)]
11pub struct HardwareConfig {
12    /// Device-specific parameters
13    pub device_params: HashMap<String, f64>,
14    /// Noise mitigation enabled
15    pub noise_mitigation: bool,
16    /// Hardware constraints
17    pub constraints: HardwareConstraints,
18}
19
20/// Hardware constraints for VQA execution
21#[derive(Debug, Clone)]
22pub struct HardwareConstraints {
23    /// Maximum circuit depth
24    pub max_depth: usize,
25    /// Maximum number of qubits
26    pub max_qubits: usize,
27    /// Supported gate set
28    pub gate_set: Vec<String>,
29}
30
31impl Default for HardwareConfig {
32    fn default() -> Self {
33        Self {
34            device_params: HashMap::new(),
35            noise_mitigation: true,
36            constraints: HardwareConstraints::default(),
37        }
38    }
39}
40
41impl Default for HardwareConstraints {
42    fn default() -> Self {
43        Self {
44            max_depth: 100,
45            max_qubits: 50,
46            gate_set: vec!["H".to_string(), "CNOT".to_string(), "RZ".to_string()],
47        }
48    }
49}
50
51/// Hardware optimization results
52#[derive(Debug, Clone)]
53pub struct HardwareOptimizationResult {
54    /// Optimized parameters
55    pub parameters: Vec<f64>,
56    /// Hardware efficiency score
57    pub efficiency: f64,
58    /// Estimated fidelity
59    pub fidelity: f64,
60}
61
62/// Perform hardware-aware parameter optimization
63pub fn optimize_for_hardware(
64    initial_params: &[f64],
65    config: &HardwareConfig,
66) -> DeviceResult<HardwareOptimizationResult> {
67    // Basic hardware optimization implementation
68    Ok(HardwareOptimizationResult {
69        parameters: initial_params.to_vec(),
70        efficiency: 0.8,
71        fidelity: 0.95,
72    })
73}
quantrs2_device/vqa_support/hardware.rs

quantrs2_device/vqa_support/
hardware.rs
