quantrs2-ml 0.1.3

Quantum Machine Learning module for QuantRS2
Documentation 
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//! # QuantumAdvancedDiffusionConfig - Trait Implementations
//!
//! This module contains trait implementations for `QuantumAdvancedDiffusionConfig`.
//!
//! ## Implemented Traits
//!
//! - `Default`
//!
//! 🤖 Generated with [SplitRS](https://github.com/cool-japan/splitrs)

use super::*;
use crate::error::{MLError, Result};
use scirs2_core::ndarray::*;
use scirs2_core::random::prelude::*;
use scirs2_core::{Complex32, Complex64};
use std::f64::consts::PI;

use super::types::QuantumAdvancedDiffusionConfig;

impl Default for QuantumAdvancedDiffusionConfig {
    fn default() -> Self {
        Self {
            data_dim: 32,
            num_qubits: 16,
            num_timesteps: 1000,
            noise_schedule: QuantumNoiseSchedule::QuantumCosine {
                s: 0.008,
                entanglement_preservation: 0.9,
                decoherence_rate: 0.01,
            },
            denoiser_architecture: DenoisingArchitecture::QuantumUNet {
                depth: 4,
                base_channels: 32,
                quantum_skip_connections: true,
            },
            quantum_enhancement_level: 0.5,
            use_quantum_attention: true,
            enable_entanglement_monitoring: true,
            adaptive_denoising: true,
            use_quantum_fourier_features: true,
            error_mitigation_strategy: ErrorMitigationStrategy::AdaptiveMitigation,
        }
    }
}