repo name change

titaschanda · Dec 27, 2023 · 561f68b · 561f68b
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diff --git a/Project.toml b/Project.toml
@@ -1,4 +1,4 @@
-name = "TeNLib"
+name = "TenNetLib"
 uuid = "1ce00845-9e1b-4798-bd63-033d15ad4ca9"
 authors = ["Titas Chanda"]
 version = "0.1.0"
@@ -11,8 +11,10 @@ Printf = "de0858da-6303-5e67-8744-51eddeeeb8d7"
 
 [compat]
 DataStructures = "0.18"
-ITensors = "0.3"
-julia = "1"
+ITensors = "0.3.43"
+LinearAlgebra = "1.7"
+Printf = "1.7"
+julia = "1.7"
 
 [extras]
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"

diff --git a/docs/Project.toml b/docs/Project.toml
@@ -3,8 +3,7 @@ DataStructures = "864edb3b-99cc-5e75-8d2d-829cb0a9cfe8"
 Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
 DocumenterTools = "35a29f4d-8980-5a13-9543-d66fff28ecb8"
 ITensors = "9136182c-28ba-11e9-034c-db9fb085ebd5"
-TeNLib = "1ce00845-9e1b-4798-bd63-033d15ad4ca9"
+TenNetLib = "1ce00845-9e1b-4798-bd63-033d15ad4ca9"
 
 [compat]
-Documenter = "1.2"
-julia = "1.7"
+Documenter = "1.2"
diff --git a/docs/make.jl b/docs/make.jl
@@ -1,11 +1,11 @@
 push!(LOAD_PATH,"../src/")
 
 using ITensors, DataStructures
-using Documenter, TeNLib
+using Documenter, TenNetLib
 
 ############################################################################
 
-sitename = "TeNLib.jl"
+sitename = "TenNetLib.jl"
 
 settings = Dict(
     :pages =>
@@ -44,7 +44,7 @@ settings = Dict(
         ],
     :format => Documenter.HTML(
         prettyurls = get(ENV, "CI", nothing) == "true",
-        description = "A Tensor Network Library (TeNLib.jl) built on top of ITensors.jl for quantum many-body problems.",
+        description = "A Tensor Network Library (TenNetLib.jl) built on top of ITensors.jl for quantum many-body problems.",
         assets=["assets/favicon.ico"]),    
     :doctest => true,
     :checkdocs => :none,
@@ -64,7 +64,7 @@ if get(ENV, "GITHUB_EVENT_NAME", nothing) == "workflow_dispatch"
 end
 
 deploydocs(;
-  repo="github.com/titaschanda/TeNLib.jl.git",
+  repo="github.com/titaschanda/TenNetLib.jl.git",
   devbranch="main",
   push_preview=true,
   deploy_config=Documenter.GitHubActions(),

diff --git a/docs/src/base/couplingmodel.md b/docs/src/base/couplingmodel.md
@@ -1,6 +1,6 @@
 # `CouplingModel`
 
-TeNLib.jl degines as struct, called the `CouplingModel`, to store the Hamiltonian terms. 
+TenNetLib.jl degines as struct, called the `CouplingModel`, to store the Hamiltonian terms. 
 In case of MPS based algorithms, `CouplingModel` can replace `MPO` without modifying
 rest of the code. For Tree Tensor Network (TTN) codes, only `CouplingModel` can be used.
 Different elements of `CouplingModel` are contracted in parallel.

diff --git a/docs/src/base/fermions.md b/docs/src/base/fermions.md
@@ -1,6 +1,6 @@
 # Dealing with Fermions
 
-TeNLib.jl uses the following function to teat fermionic operators.
+TenNetLib.jl uses the following function to teat fermionic operators.
 
 ```@docs
 bosonize(oppair::Vector{Pair{String, Int}},sites::Vector{Index{T}}) where T

diff --git a/docs/src/base/global.md b/docs/src/base/global.md
@@ -1,6 +1,6 @@
 # Controlling global behaviors
 
-TeNLib.jl provides following functions to control global behaviors for Tensor Network simulations.
+TenNetLib.jl provides following functions to control global behaviors for Tensor Network simulations.
 
 ```@docs
 Float64_threshold

diff --git a/docs/src/base/graph.md b/docs/src/base/graph.md
@@ -1,6 +1,6 @@
 # The `Graph` object
 
-TeNLib.jl defines its own undirected graph object, the `Graph`. Currently only used for the Tree
+TenNetLib.jl defines its own undirected graph object, the `Graph`. Currently only used for the Tree
 Tensor Network (TTN) codes.
 
 ```@docs

diff --git a/docs/src/base/opstrings.md b/docs/src/base/opstrings.md
@@ -1,7 +1,7 @@
 # `OpStrings`
 
-TeNLib.jl provides an alternative, called `OpStrings`, to ITensors.jl's `OpSum` to automatically
-construct Hamiltonains / operators. TeNLib.jl's own `CouplingModel` is built from `OpStrings` and
+TenNetLib.jl provides an alternative, called `OpStrings`, to ITensors.jl's `OpSum` to automatically
+construct Hamiltonains / operators. TenNetLib.jl's own `CouplingModel` is built from `OpStrings` and
 is not compatible with `OpSum`.
 
 ## `OpString`
@@ -10,7 +10,7 @@ is not compatible with `OpSum`.
 
 ```@docs
 OpString
-TeNLib.coefficient(opstr::OpString)
+TenNetLib.coefficient(opstr::OpString)
 operators(opstr::OpString)
 minsite(opstr::OpString)
 maxsite(opstr::OpString)

diff --git a/docs/src/index.md b/docs/src/index.md
@@ -1,29 +1,29 @@
-# TeNLib.jl
+# TenNetLib.jl
 
-A Tensor Network Library (TeNLib.jl) built on top of [ITensors.jl](https://github.com/ITensor/ITensors.jl) for quantum many-body problems.
+A Tensor Network Library (TenNetLib.jl) built on top of [ITensors.jl](https://github.com/ITensor/ITensors.jl) for quantum many-body problems.
 
 | **Build Status** | **Documentation** |
 |:----------------:|:-----------------:|
-| [![Build Status](https://github.com/titaschanda/TeNLib.jl/actions/workflows/CI.yml/badge.svg?branch=main)](https://github.com/titaschanda/TeNLib.jl/actions/workflows/CI.yml?query=branch%3Amain) | [![Build Status](https://github.com/titaschanda/TeNLib.jl/actions/workflows/documentation.yml/badge.svg?branch=main)](https://github.com/titaschanda/TeNLib.jl/actions/workflows/documentation.yml?query=branch%3Amain) |
+| [![Build Status](https://github.com/titaschanda/TenNetLib.jl/actions/workflows/CI.yml/badge.svg?branch=main)](https://github.com/titaschanda/TenNetLib.jl/actions/workflows/CI.yml?query=branch%3Amain) | [![Build Status](https://github.com/titaschanda/TenNetLib.jl/actions/workflows/documentation.yml/badge.svg?branch=main)](https://github.com/titaschanda/TenNetLib.jl/actions/workflows/documentation.yml?query=branch%3Amain) |
 
-The source code for TeNLib.jl can be found on [GitHub](https://github.com/titaschanda/TeNLib.jl)
+The source code for TenNetLib.jl can be found on [GitHub](https://github.com/titaschanda/TenNetLib.jl)
 
-The documentation for TeNLib.jl can be found [**here**](https://titaschanda.github.io/TeNLib.jl/dev/).
+The documentation for TenNetLib.jl can be found [**here**](https://titaschanda.github.io/TenNetLib.jl/dev/).
 
 This library requires Julia 1.7+.
 
 ## Overview
 
-TeNLib.jl features widely-used Tensor Network (TN) codes, designed with a **multi-layered abstraction**
+TenNetLib.jl features widely-used Tensor Network (TN) codes, designed with a **multi-layered abstraction**
 to cater to diverse user needs. The library provides users with varying levels of control over their computations.
-Currently, TeNLib.jl presents an array of functionalities for:
+Currently, TenNetLib.jl presents an array of functionalities for:
 * *(a)* **Finite-size Matrix-Product States (MPS)**: Different variants of Density Matrix Renormalization Group (DMRG) and Time Dependent Variational Principle (TDVP) (including subspace expansion) methods.
 * *(b)* **Tree Tensor Network (TTN)**: Variational search for the ground state and first few excited states.
 
 
 ## Installation
 
-Currently, TeNLib.jl is not registered on Julia General Registry. To install the library (along with ITensors.jl), you can use the following steps:
+Currently, TenNetLib.jl is not registered on Julia General Registry. To install the library (along with ITensors.jl), you can use the following steps:
 
 ```
 $ julia
@@ -32,7 +32,7 @@ julia> ]
 
 pkg> add ITensors
 
-pkg> add https://github.com/titaschanda/TeNLib.jl
+pkg> add https://github.com/titaschanda/TenNetLib.jl
 ```
 
 ## Found an issue or bug?
@@ -42,8 +42,8 @@ pkg> add https://github.com/titaschanda/TeNLib.jl
 
 
 If you find bugs or a mistakes of any kind, please let us know by adding an issue to the
-[GitHub issue tracker](https://github.com/titaschanda/TeNLib.jl/issues).
-You are also welcome to submit a [pull request](https://github.com/titaschanda/TeNLib.jl/pulls).
+[GitHub issue tracker](https://github.com/titaschanda/TenNetLib.jl/issues).
+You are also welcome to submit a [pull request](https://github.com/titaschanda/TenNetLib.jl/pulls).
 
 
 ## Future functionality?
@@ -55,7 +55,7 @@ Here is a list for future additions in the decreasing order of priority. Any hel
 * Real-time evolution method using PEPS and TTN.
 
 Also, please feel free to ask about a new feature by adding a new request to the
-[GitHub issue tracker](https://github.com/titaschanda/TeNLib.jl/issues) labelled
+[GitHub issue tracker](https://github.com/titaschanda/TenNetLib.jl/issues) labelled
 `feature request`. Note that submitting a pull request, providing the needed changes to
 introduced your requested feature, will speed up the process.
 
@@ -67,7 +67,7 @@ The following code is for a simple DMRG run at **the highest level of abstractio
 
 ```
 using ITensors
-using TeNLib
+using TenNetLib
 
 let
     N = 32
@@ -99,7 +99,7 @@ The following code is for a simple TDVP run at **the highest level of abstractio
 
 ```
 using ITensors
-using TeNLib
+using TenNetLib
 
 let
     N = 32
@@ -141,7 +141,7 @@ Here we use `OpStrings` and `CouplingModel` instead of `OpSum` and `MPO`.
 
 ```
 using ITensors
-using TeNLib
+using TenNetLib
 
 let
     N = 32

diff --git a/docs/src/mps/dmrg.md b/docs/src/mps/dmrg.md
@@ -4,7 +4,7 @@ Functions to perfom (and control) DMRG runs.
 
 ## `DMRGParams`
 
-TeNLib.jl defines a struct, called  `DMRGParams`, to control DMRG simulations.
+TenNetLib.jl defines a struct, called  `DMRGParams`, to control DMRG simulations.
 
 ```@docs
 DMRGParams

diff --git a/docs/src/mps/example_dmrg.md b/docs/src/mps/example_dmrg.md
@@ -6,7 +6,7 @@ A straight-forward DMRG can be performed as follows.
 
 ```
 using ITensors
-using TeNLib
+using TenNetLib
 
 let
     N = 32

diff --git a/docs/src/mps/example_tdvp.md b/docs/src/mps/example_tdvp.md
@@ -8,7 +8,7 @@ with step `dt`, `time_step` should be `-im * dt`.
 
 ```
 using ITensors
-using TeNLib
+using TenNetLib
 
 let
     N = 32
@@ -83,7 +83,7 @@ For time-dependent Hamiltonian, [`updateH!`](@ref updateH!(engine::TDVPEngine, H
 
 ```
 using ITensors
-using TeNLib
+using TenNetLib
 
 function makeHt(sites, t)
 

diff --git a/docs/src/mps/measure.md b/docs/src/mps/measure.md
@@ -1,8 +1,8 @@
 # Measuring the MPS
 
 ```@docs
-TeNLib.entropy(psi::MPS, bond::Int)
-TeNLib.entropy(psi::MPS; kwargs...)
+TenNetLib.entropy(psi::MPS, bond::Int)
+TenNetLib.entropy(psi::MPS; kwargs...)
 measure(::Type{T}, psi::MPS, opten::ITensor) where T <: Union{ComplexF64, Float64}
 measure(::Type{T}, psi::MPS, opstr::String, pos::Int) where T <: Union{ComplexF64, Float64}
 measure(::Type{T}, psi::MPS, opstr::String; kwargs...) where T <: Union{ComplexF64, Float64}

diff --git a/docs/src/mps/state_envs.md b/docs/src/mps/state_envs.md
@@ -1,6 +1,6 @@
 # `StateEnvs`: A container to store the MPS and its environments
 
-At the lowest-level of abstraction, TeNLib.jl defines `StateEnvs` to hold an MPS and its
+At the lowest-level of abstraction, TenNetLib.jl defines `StateEnvs` to hold an MPS and its
 environments to be modified in place.
 
 Skip this part if you want to avoid lower-level abstraction.
@@ -23,7 +23,7 @@ updateH!(sysenv::StateEnvs{ProjCouplingModel_MPS}, H::CouplingModel, Ms::Vector{
 nsite(sysenv::StateEnvs)
 set_nsite!(sysenv::StateEnvs, nsite::Int)
 position!(sysenv::StateEnvs, pos::Int)
-TeNLib.product(sysenv::StateEnvs, v::ITensor)
+TenNetLib.product(sysenv::StateEnvs, v::ITensor)
 Base.copy(sysenv::StateEnvs)
 Base.length(sysenv::StateEnvs)
 ```
diff --git a/docs/src/mps/sweep.md b/docs/src/mps/sweep.md
@@ -1,13 +1,13 @@
 # Sweeping through the MPS
 
-At a lower level of abstraction, TeNLib.jl allows to control each fullsweep
+At a lower level of abstraction, TenNetLib.jl allows to control each fullsweep
 (left-to-right and right-to-left) manually to update `StateEnvs`.
 
 Skip this part if you want to avoid lower-level abstraction.
 
 ## `SweepData`
 
-TeNLib.jl defines a struct, called  `SweepData`, to store essential data after each fullsweep.
+TenNetLib.jl defines a struct, called  `SweepData`, to store essential data after each fullsweep.
 
 ```@docs
 SweepData
@@ -22,7 +22,7 @@ fullsweep!(sysenv::StateEnvs, solver, nsite::Int, swdata::SweepData; kwargs...)
 
 ## Perform a dynamical fullsweep
 
-TeNLib.jl defines the following function to dynamically decide whether to perform single- or
+TenNetLib.jl defines the following function to dynamically decide whether to perform single- or
 two-site update at each bond, depending on the entropy growth at the previous halfsweep.
 
 ```@docs

diff --git a/docs/src/mps/tdvp.md b/docs/src/mps/tdvp.md
@@ -2,7 +2,7 @@
 
 ## `TDVPEngine`
 
-TeNLib.jl defines a struct, called `TDVPEngine`, to store essential data during TDVP sweeps.
+TenNetLib.jl defines a struct, called `TDVPEngine`, to store essential data during TDVP sweeps.
 
 ```@docs
 TDVPEngine

diff --git a/docs/src/mps/update_site.md b/docs/src/mps/update_site.md
@@ -1,6 +1,6 @@
 # Perform local updates
 
-At the lowest-level of abstraction, TeNLib.jl allows for updating the `StateEnvs` for each sites/bonds manually.
+At the lowest-level of abstraction, TenNetLib.jl allows for updating the `StateEnvs` for each sites/bonds manually.
 
 Skip this part if you want to avoid lower-level abstraction.
 

diff --git a/docs/src/ttn/example_optimize.md b/docs/src/ttn/example_optimize.md
@@ -6,7 +6,7 @@ A straight-forward TTN optimization can be performed as follows.
 
 ```
 using ITensors
-using TeNLib
+using TenNetLib
 
 let
     N = 32

diff --git a/docs/src/ttn/optimize_ttn.md b/docs/src/ttn/optimize_ttn.md
@@ -4,7 +4,7 @@ Functions to optimize TTN.
 
 ## `OptimizeParamsTTN`
 
-TeNLib.jl defines a struct, called  `OptimizeParamsTTN`, to control TTN optimizations.
+TenNetLib.jl defines a struct, called  `OptimizeParamsTTN`, to control TTN optimizations.
 
 ```@docs
 OptimizeParamsTTN

diff --git a/docs/src/ttn/state_envs_ttn.md b/docs/src/ttn/state_envs_ttn.md
@@ -1,6 +1,6 @@
 # `StateEnvsTTN`: A container to store the TTN and its environments
 
-Similar to the setup for MPS, tt the lowest-level of abstraction, TeNLib.jl defines
+Similar to the setup for MPS, tt the lowest-level of abstraction, TenNetLib.jl defines
 `StateEnvs` to hold a TTN and its environments to be modified in place.
 
 Skip this part if you want to avoid lower-level abstraction.
@@ -12,6 +12,6 @@ StateEnvsTTN(psi::TTN,M::CouplingModel,psis::Vector{TTN};  weight::Float64)
 getpsi(sysenv::StateEnvsTTN)
 getenv(sysenv::StateEnvsTTN)
 position!(sysenv::StateEnvsTTN, node::Int2; maxdim::Int = typemax(Int), mindim::Int = 1, cutoff::Float64 = Float64_threshold(), svd_alg::String = "divide_and_conquer", normalize::Bool = false, node_to_skip::Union{Int2, Nothing} = nothing)
-TeNLib.product(sysenv::StateEnvsTTN, v::ITensor)
+TenNetLib.product(sysenv::StateEnvsTTN, v::ITensor)
 Base.copy(sysenv::StateEnvsTTN)
 ```
diff --git a/docs/src/ttn/sweep_ttn.md b/docs/src/ttn/sweep_ttn.md
@@ -1,13 +1,13 @@
 # Sweeping through the TTN
 
-At a lower level of abstraction, TeNLib.jl allows to control each fullsweep
+At a lower level of abstraction, TenNetLib.jl allows to control each fullsweep
  manually to update `StateEnvsTTN`.
 
 Skip this part if you want to avoid lower-level abstraction.
 
 ## `SweepDataTTN`
 
-TeNLib.jl defines a struct, called  `SweepDataTTN`, to store essential data after each fullsweep.
+TenNetLib.jl defines a struct, called  `SweepDataTTN`, to store essential data after each fullsweep.
 
 ```@docs
 SweepDataTTN

diff --git a/docs/src/ttn/ttn.md b/docs/src/ttn/ttn.md
@@ -14,7 +14,7 @@ quantum correlations comapred to MPS. Moreover, simulations for systems with per
 TTNs have found their place for simulating 2D or pseudo-2D ladder/cylinder systems with PBC
 where the performance of MPS is not adequate.
 
-TeNLib.jl implements the unconstrained optimization for obtaining
+TenNetLib.jl implements the unconstrained optimization for obtaining
 ground as well as excited states as
 described in [Phys. Rev. B **90**, 125154 (2014)](https://journals.aps.org/prb/abstract/10.1103/PhysRevB.90.125154) and [SciPost Phys. Lect. Notes 8 (2019)] (https://scipost.org/10.21468/SciPostPhysLectNotes.8).
 
@@ -37,7 +37,7 @@ LinkTypeTTN
 ---
 
 !!! info
-    TeNLib.jl can automatically handle system-sizes that are not powers of 2. No special care is
+    TenNetLib.jl can automatically handle system-sizes that are not powers of 2. No special care is
     needed for such system-sizes.
 
 | TTN for system-size 12 | TTN for system-size 14|
@@ -48,7 +48,7 @@ LinkTypeTTN
 
 
 !!! info
-    The TTN codes defined in TeNLib.jl can readily work, without any changes,
+    The TTN codes defined in TenNetLib.jl can readily work, without any changes,
     **for any loop-free tensor networks**, e.g., Fork Tensor Networks.
 
 !!! tip