VQEWithAutodiff

Struct VQEWithAutodiff 

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pub struct VQEWithAutodiff {
    pub ansatz: ParametricCircuit,
    pub hamiltonian: PauliOperatorSum,
    pub context: AutoDiffContext,
    pub history: Vec<VQEIteration>,
    pub convergence: ConvergenceCriteria,
}
Expand description

VQE algorithm with automatic differentiation

Fields§

§ansatz: ParametricCircuit

Parametric ansatz circuit

§hamiltonian: PauliOperatorSum

Hamiltonian observable

§context: AutoDiffContext

Autodiff context

§history: Vec<VQEIteration>

Optimization history

§convergence: ConvergenceCriteria

Convergence criteria

Implementations§

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impl VQEWithAutodiff

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pub fn new( ansatz: ParametricCircuit, hamiltonian: PauliOperatorSum, initial_params: Vec<f64>, gradient_method: GradientMethod, ) -> Self

Create new VQE instance

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pub const fn with_convergence(self, convergence: ConvergenceCriteria) -> Self

Set convergence criteria

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pub fn evaluate_energy(&mut self) -> Result<f64>

Evaluate energy for current parameters

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pub fn compute_gradient(&mut self) -> Result<Vec<f64>>

Compute gradient for current parameters

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pub fn step(&mut self, learning_rate: f64) -> Result<VQEIteration>

Perform one VQE optimization step using gradient descent

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pub fn optimize(&mut self, learning_rate: f64) -> Result<VQEResult>

Run VQE optimization until convergence

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pub fn optimize_with_optirs( &mut self, config: OptiRSConfig, ) -> Result<VQEResult>

Run VQE optimization using OptiRS optimizers (Adam, SGD, RMSprop, etc.)

This method provides state-of-the-art optimization using OptiRS’s advanced machine learning optimizers, which typically converge faster and more robustly than basic gradient descent.

§Arguments
  • config - OptiRS optimizer configuration
§Returns
  • VQEResult - Optimization result with optimal parameters and energy
§Example
use quantrs2_sim::autodiff_vqe::*;
use quantrs2_sim::optirs_integration::*;

let mut vqe = VQEWithAutodiff::new(...);
let config = OptiRSConfig {
    optimizer_type: OptiRSOptimizerType::Adam,
    learning_rate: 0.01,
    ..Default::default()
};
let result = vqe.optimize_with_optirs(config)?;

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