Installation

This page walks you through setting up a Julia environment for working with MPSKit.jl, and ends with a small snippet you can run to check that everything works.

Prerequisites

You need a working installation of Julia, version 1.10 or later. If you don't have Julia yet, install it via juliaup or download it directly from julialang.org. This tutorial assumes you are comfortable starting the Julia REPL and typing commands into it, but does not assume any prior experience with Julia's package manager.

Set up a project environment

Before installing any packages, create a dedicated environment for this tutorial. Working in a fresh, named environment (rather than the global default environment) keeps the exact package versions you use here reproducible, and avoids clashes with other projects on your machine.

Start Julia, enter the package manager by pressing ], and activate a new environment:

pkg> activate mpskit-tutorial

Julia will create the environment the first time you add a package to it.

Install the packages

With the environment activated, install MPSKit.jl and the packages used throughout this documentation:

pkg> add MPSKit TensorKit TensorOperations MPSKitModels TensorKitTensors Plots

• MPSKit provides the matrix product state and operator types, together with the ground-state, time-evolution, and bond-dimension algorithms.

• TensorKit supplies the tensor backend (TensorMaps and vector spaces) that MPSKit is built on; installing it alongside MPSKit also gives access to truncation-scheme constructors such as truncrank, which TensorKit re-exports from MatrixAlgebraKit.

• TensorOperations provides the @tensor macro used to contract tensors by hand.

• MPSKitModels collects pre-defined Hamiltonians (such as the transverse-field Ising model) and lattices for common physical models.

• TensorKitTensors provides ready-made local operators, such as the Pauli operators.

• Plots is used to visualize results in several of the how-to guides and examples; it is optional if you only intend to run computations without plotting.

MPSKit.jl is registered in Julia's General registry, so pkg> add fetches it directly; you do not need to add any custom registries.

First using is slow

The first time you load these packages with using, Julia precompiles them, which can take a minute or two. Subsequent loads in the same environment are much faster.

Verify your setup

Once the packages have finished installing, exit the package manager (backspace) and run the following in the same environment to check that MPSKit, TensorKit, and MPSKitModels work together.

using MPSKit, TensorKit, MPSKitModels

H = transverse_field_ising(FiniteChain(8); J = 1.0, g = 0.5)
ψ = FiniteMPS(8, ℂ^2, ℂ^8)

8-site FiniteMPS(ComplexF64, TensorKit.ComplexSpace) with maximal dimension 8 and center 17/2:
┌─[8]─ ℂ^2
│ ℂ^2
├─[7]─ ℂ^2
│ ℂ^4
├─[6]─ ℂ^2
│ ℂ^8
├─[5]─ ℂ^2
│ ℂ^8
├─[4]─ ℂ^2
│ ℂ^8
├─[3]─ ℂ^2
│ ℂ^4
├─[2]─ ℂ^2
│ ℂ^2
└─[1]─ ℂ^2

If this runs without error and prints a FiniteMPS, your environment is ready.

From here, continue with Your first ground state, which uses this same Hamiltonian and initial state to find the ground state of the transverse-field Ising model with DMRG.

Troubleshooting

• Long precompilation on first use: this is expected the first time you using a package (or after updating one), especially for a large dependency stack; it is not a sign that anything is wrong.

• Version resolver conflicts: if pkg> add reports that it cannot find a compatible set of versions, try creating a fresh environment (as above) rather than adding these packages to an existing environment that already has other constraints.