Conventions

This page collects important conventions that apply across the entire tensor4all-rs codebase.

Dense Layout (Column-Major)

tensor4all-rs uses column-major (Fortran order) dense linearization internally. Flat dense buffers, reshape/flatten semantics, the C API, and the HDF5 layer are all defined in terms of column-major ordering.

This matches Julia, ITensors.jl, and tenferro-rs. When exchanging dense data with NumPy, use order="F" when you need explicit control over flattening or reshaping.

Indexing

Sites are 0-indexed in Rust (unlike ITensors.jl, which is 1-indexed).
Exception: tensor4all-quanticstci grid indices are 1-indexed, following the Julia convention for compatibility with QuanticsTCI.jl.

Truncation Tolerance

tensor4all-rs uses rtol (relative tolerance). ITensors.jl uses cutoff. The conversion is:

rtol = sqrt(cutoff)

Library	Parameter	Conversion
tensor4all-rs	`rtol`	—
ITensors.jl	`cutoff`	`rtol = √cutoff`

Example: ITensors.jl cutoff=1e-10 corresponds to rtol=1e-5 in tensor4all-rs.

ITensors.jl Type Correspondence

ITensors.jl	tensor4all-rs
`Index{Int}`	`Index<Id, NoSymmSpace>`
`ITensor`	`TensorDynLen`
`Dense`	`Storage::StructuredF64/C64`
`Diag`	`Storage::StructuredF64/C64` (diagonal `axis_classes`)
`A * B`	`a.contract(&b)`

Scalar Types

tensor4all-rs supports two scalar types:

f64 — double-precision real
Complex64 — double-precision complex (from the num-complex crate)

Generic APIs handle both types. Prefer writing generic code over scalar-specific variants (*_f64 / *_c64) in library and test code. The C API uses scalar-specific names at the FFI boundary where generic dispatch is not available.