tensor4all-rs

A Rust implementation of tensor networks: TCI, Quantics Tensor Train, and Tree Tensor Networks.

Features

• ITensors.jl-like dynamic tensors: Flexible Index system with dynamic-rank Tensor
• Tensor Cross Interpolation: TCI2 algorithm for efficient high-dimensional function approximation
• Quantics Tensor Train: Binary encoding of continuous variables with transformation operators
• Tree Tensor Networks: Arbitrary topology with canonicalization, truncation, and contraction
• C API: Full functionality exposed for language bindings (Julia)

Quick Start

Add to your Cargo.toml:

[dependencies]
tensor4all-simplett = "0.1"

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

let tt = TensorTrain::<f64>::constant(&[2, 3, 4], 1.0);
let value = tt.evaluate(&[0, 1, 2]).unwrap();
assert!((value - 1.0).abs() < 1e-12);

let total = tt.sum();
assert!((total - 24.0).abs() < 1e-12);

let options = CompressionOptions {
    tolerance: 1e-10,
    max_bond_dim: 20,
    ..Default::default()
};
let compressed = tt.compressed(&options).unwrap();
assert!((compressed.sum() - 24.0).abs() < 1e-10);

Crate Overview

Crate	Description
tensor4all-core	Core types: Index, Tensor, contraction, SVD, QR
tensor4all-simplett	Simple TT/MPS with compression
tensor4all-itensorlike	ITensors.jl-like TensorTrain API
tensor4all-treetn	Tree tensor networks with arbitrary topology
tensor4all-tensorci	Tensor Cross Interpolation (TCI2)
tensor4all-quanticstci	High-level Quantics TCI interface
tensor4all-quanticstransform	Quantics transformation operators
tensor4all-treetci	Tree-structured cross interpolation
tensor4all-partitionedtt	Partitioned Tensor Train
tensor4all-hdf5	ITensors.jl-compatible HDF5 serialization
tensor4all-capi	C FFI for language bindings

Documentation

• User Guide — tutorials, architecture, conventions
• API Reference (rustdoc) — generated API documentation
• Julia Bindings — Tensor4all.jl wrapper
• Design Documents — architecture and design decisions

Acknowledgments

Inspired by ITensors.jl. We acknowledge fruitful discussions with M. Fishman and E. M. Stoudenmire at CCQ, Flatiron Institute.

Citation: If you use this code in research, please cite:

We used tensor4all-rs (https://github.com/tensor4all/tensor4all-rs), inspired by ITensors.jl.

M. Fishman, S. R. White, E. M. Stoudenmire, "The ITensor Software Library for Tensor Network Calculations", arXiv:2007.14822 (2020)

License

MIT License (see LICENSE-MIT)