To install this package, you can use the following steps:

$ julia

julia> ]

pkg> add ITensorTDVP

• The applyexp Krylov exponentiation solver backend has been removed, and solver_backend="applyexp" option for tdvp now just calls exponentiate from KrylovKit.jl. They were in many ways the same but exponentiate has more advanced features like restarts. Using solver_backend="applyexp" now prints a warning to that effect. To remove the warning, don't specify the solver_backend keyword argument. Alternatively, you can set it to "exponentiate", though specifying it is now superfluous since there is now only one solver_backend available and the solver_backend keyword argument may be removed in future minor releases.

• svd_alg now doesn't specify a default value, so the default value is set by the svd function in ITensors/NDTensors. This fixes an issue using ITensorTDVP.jl and GPU backends, where the default value being set in ITensorTDVP.jl wasn't compatible with the options available in some GPU backends like CUDA.
• More generally, keyword arguments are handled better throughout the package, so default values are handled more systematically and keyword arguments are listed or forwarded more explicitly, so it should catch more mistakes like passing an incorrect keyword argument name.

This package is effectively a generalization of the DMRG code in ITensors.jl, using the MPS/MPO types from that package. It provides a general MPS "solver" interface which allows us to implement a variety of MPS/MPO optimization/solver functionality like DMRG (ITensorTDVP.dmrg), TDVP (ITensorTDVP.tdvp), linear solving (ITensorTDVP.linsolve/KrylovKit.linsolve), DMRG-X (ITensorTDVP.dmrg_x), etc. while sharing most of the code across those different functions. Therefore, it effectively supercedes the DMRG functionality in ITensors.jl (dmrg), and provides its own ITensorTDVP.dmrg function that is essentially the same as the dmrg function from ITensors.jl (though for now it only outputs the state, while ITensors.dmrg outputs the energy and the state, likely we will make the interface more similar to ITensors.dmrg in future versions of the code). This package is fairly stable and appropriate for general use. The primary missing feature is a lack of modern subspace expansion tools for methods like TDVP and 1-site DMRG. However, 2-site TDVP or TEBD is often sufficient for performing subspace expansion (except when it's not).

However, note that future developments, including modern subspace expansion tools, are being developed in our next-generation tensor network library ITensorNetworks.jl. The goal of that package is to provide contraction, optimization, and evolution tools for general tensor networks, as well as methods like DMRG, TDVP, and linear solving for tree tensor networks, and the eventual goal is to replace this package which is limited to solvers for just MPS/MPO (linear/path graph) tensor networks. However, ITensorNetworks.jl is under heavy development and is not meant for general usage at the moment, except for those who are brave enough to handle missing features and breaking interfaces. Basically, for the average user who wants stable and reliable code, if you need to use MPS-based TDVP or linear solving, you should use this package for the time being.