Struct TQStrongEntanglingLayer 

pub struct TQStrongEntanglingLayer { /* private fields */ }

Strong entangling layer (from TorchQuantum) Pattern: (RX -> RY -> RZ -> CNOT) * n_blocks with varying entanglement patterns Each block has different CNOT ranges for stronger entanglement

Implementations

impl TQStrongEntanglingLayer

pub fn new(config: TQLayerConfig) -> Self

Trait Implementations

impl TQModule for TQStrongEntanglingLayer

fn forward(&mut self, qdev: &mut TQDevice) -> Result<()>

Execute the forward pass on the quantum device

fn parameters(&self) -> Vec<TQParameter>

Get all trainable parameters

fn n_wires(&self) -> Option<usize>

Get number of wires this module operates on

fn set_n_wires(&mut self, n_wires: usize)

Set number of wires

fn is_static_mode(&self) -> bool

Check if module is in static mode

fn static_on(&mut self)

Enable static mode for graph optimization

fn static_off(&mut self)

Disable static mode

fn name(&self) -> &str

Module name for debugging

fn zero_grad(&mut self)

Zero gradients of all parameters

fn forward_with_input( &mut self, qdev: &mut TQDevice, _x: Option<&Array2<f64>>, ) -> Result<()>

Execute forward pass with optional input data (for encoders)

fn get_unitary(&self) -> Option<Array2<CType>>

Get the unitary matrix representation (if available)

fn train(&mut self, _mode: bool)

Set training mode

fn training(&self) -> bool

Check if in training mode