Software

The tensor4all software ecosystem is organized by status and workflow. For new users today, we recommend xfac for C++ and Python workflows, and the stable Julia packages for Julia workflows.

Software map

Status	Library	Best for
Use now	xfac / Python tutorials	C++ and Python workflows; original TCI implementation
Use now	TensorCrossInterpolation.jl	Core TCI algorithms in Julia
Use now	QuanticsTCI.jl	Convenient QTCI interface in Julia
Use now	QuanticsGrids.jl	Quantics grids and coordinate transformations
Use now	InterpolativeQTT.jl	Multiscale interpolative QTT construction in Julia
Active development	tensor4all-rs	Next-generation Rust implementation
Active development	Tensor4all.jl	Julia frontend for tensor4all-rs
Maintenance	Quantics.jl	Existing QTT workflows built on ITensors.jl
Maintenance	FastMPOContractions.jl	Existing MPO contraction workflows
Maintenance	TCIITensorConversion.jl	Historical ITensors conversion package

Use now: C++ and Python

xfac is the original C++ implementation of tensor cross interpolation in the tensor4all ecosystem. It includes Python bindings and remains the recommended current path for C++ and Python users.

• Documentation: xfac readthedocs
• Python tutorials: tutorial-python
• Source: tensor4all/xfac

Use now: Julia

These Julia packages are the current recommended route for Julia users.

• TensorCrossInterpolation.jl provides the core TCI algorithms.
• QuanticsTCI.jl provides a convenient interface for quantics TCI, built on TensorCrossInterpolation.jl and QuanticsGrids.jl.
• QuanticsGrids.jl provides quantics grids and coordinate transformations.
• InterpolativeQTT.jl implements multiscale interpolative construction of quantized tensor trains.

For Julia examples, see the Julia tutorials.

Active development: Rust and future Julia frontend

tensor4all-rs is the next-generation Rust implementation for TCI, quantics tensor trains, tree tensor networks, and language-binding infrastructure. Tensor4all.jl is the Julia frontend for this Rust stack.

This stack is under active development. It may eventually unify or replace parts of the current Julia ecosystem, but new users who need a stable workflow today should start with xfac or the stable Julia packages above.

Maintenance and legacy packages

These packages are useful for existing workflows, but they are not the primary recommendation for new users.

• Quantics.jl provides a high-level QTT interface built on ITensors.jl.
• FastMPOContractions.jl supports existing MPO contraction workflows.
• TCIITensorConversion.jl is historical. Its conversion functionality has been absorbed into TensorCrossInterpolation.jl as an extension.

Experimental repositories

Some old T4A****.jl repositories were used for experiments. They are not recommended for new users and are not planned as maintained public libraries.