Struct VidalTensorTrain 

pub struct VidalTensorTrain<T: TTScalar> { /* private fields */ }

Vidal Tensor Train representation

Stores the tensor train in Vidal canonical form where:

• Site tensors are stored separately from singular values
• Singular values are stored as diagonal matrices between sites

This form is useful for algorithms that need to apply local operations and maintain canonical form efficiently.

Examples

use tensor4all_simplett::{TensorTrain, AbstractTensorTrain, VidalTensorTrain};

// Build a simple tensor train and convert to Vidal form.
let tt = TensorTrain::<f64>::constant(&[2, 3], 1.0);
let vidal = VidalTensorTrain::from_tensor_train(&tt).unwrap();

assert_eq!(vidal.len(), 2);

// Converting back preserves tensor train values.
let tt2 = vidal.to_tensor_train();
let val = tt2.evaluate(&[0, 1]).unwrap();
assert!((val - 1.0).abs() < 1e-12);

// The sum is also preserved: 1.0 * 2 * 3 = 6.0
assert!((tt2.sum() - 6.0).abs() < 1e-10);

Implementations

impl<T: TTScalar + Scalar + Default> VidalTensorTrain<T>

pub fn from_tensor_train(tt: &TensorTrain<T>) -> Result<Self>

where T: ComplexFloat + BackendLinalgScalar + Copy + 'static, <T as TensorScalar>::Real: TensorScalar + ToPrimitive,

Create a VidalTensorTrain from a regular TensorTrain

pub fn from_tensor_train_with_partition( tt: &TensorTrain<T>, partition: Range<usize>, ) -> Result<Self>

where T: ComplexFloat + BackendLinalgScalar + Copy + 'static, <T as TensorScalar>::Real: TensorScalar + ToPrimitive,

Create a VidalTensorTrain with a specific partition

pub fn new( tensors: Vec<Tensor3<T>>, singular_values: Vec<DiagMatrix>, ) -> Result<Self>

Create a VidalTensorTrain with given tensors and singular values

pub fn singular_values(&self, i: usize) -> &DiagMatrix

Get the singular values between sites i and i+1

pub fn all_singular_values(&self) -> &[DiagMatrix]

Get all singular value matrices

pub fn partition(&self) -> &Range<usize>

Get the partition range

pub fn site_tensors_mut(&mut self) -> &mut [Tensor3<T>]

Get mutable access to site tensors

pub fn singular_values_mut(&mut self, i: usize) -> &mut DiagMatrix

Get mutable access to singular values

pub fn to_tensor_train(&self) -> TensorTrain<T>

Convert to a regular TensorTrain

Trait Implementations

impl<T: TTScalar + Scalar + Default> AbstractTensorTrain<T> for VidalTensorTrain<T>

fn len(&self) -> usize

Number of sites (core tensors) in the tensor train.

fn site_tensor(&self, i: usize) -> &Tensor3<T>

Borrow the rank-3 core tensor at site i.

fn site_tensors(&self) -> &[Tensor3<T>]

Borrow all core tensors as a slice.

fn is_empty(&self) -> bool

Returns true if the tensor train has zero sites.

fn link_dims(&self) -> Vec<usize>

Bond dimensions at every link (length = len() - 1).

fn link_dim(&self, i: usize) -> usize

Bond dimension at the link between site i and site i+1.

fn site_dims(&self) -> Vec<usize>

Physical (site) dimensions for every site.

fn site_dim(&self, i: usize) -> usize

Physical (site) dimension at site i.

fn rank(&self) -> usize

Maximum bond dimension across all links.

fn evaluate(&self, indices: &[LocalIndex]) -> Result<T>

Evaluate the tensor train at a given index set

fn sum(&self) -> T

Sum over all indices of the tensor train

fn norm2(&self) -> f64

Squared Frobenius norm: sum_i |T[i]|^2.

fn norm(&self) -> f64

Frobenius norm: sqrt(sum_i |T[i]|^2).

fn log_norm(&self) -> f64

Logarithm of the Frobenius norm: ln(norm()).

impl<T: Clone + TTScalar> Clone for VidalTensorTrain<T>

fn clone(&self) -> VidalTensorTrain<T>

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl<T: Debug + TTScalar> Debug for VidalTensorTrain<T>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.