Simplify docs

Author: mtfishman

docs/settings.jl

@@ -21,7 +21,6 @@ settings = Dict(
       ["Index" => "IndexType.md", "ITensor" => "ITensorType.md", "QN" => "QN.md"],
     "Frequently Asked Questions" => [
       "Programming Language (Julia, C++, ...) FAQs" => "faq/JuliaAndCpp.md",
-      "Quantum Number (QN) FAQs" => "faq/QN.md",
       "ITensor Development FAQs" => "faq/Development.md",
       "Julia Package Manager FAQs" => "faq/JuliaPkg.md",
       "High-Performance Computing FAQs" => "faq/HPC.md",
@@ -33,7 +32,6 @@ settings = Dict(
       "Contraction sequence optimization" => "ContractionSequenceOptimization.md",
       "HDF5 File Formats" => "HDF5FileFormats.md",
     ],
-    "Developer Guide" => "DeveloperGuide.md",
   ],
   :format => Documenter.HTML(; assets=["assets/favicon.ico"], prettyurls=false),
   :doctest => true,

docs/src/ContractionSequenceOptimization.md

@@ -2,7 +2,7 @@
 
 When contracting a tensor network, the sequence of contraction makes a big difference in the computational cost. However, the complexity of determining the optimal sequence grows exponentially with the number of tensors, but there are many heuristic algorithms available for computing optimal sequences for small networks[^1][^2][^3][^4][^5][^6]. ITensors.jl provides some functionality for helping you find the optimal contraction sequence for small tensor network, as we will show below.
 
-The algorithm in ITensors.jl currently uses a modified version of[^1] with simplifications for outer product contractions similar to those used in [TensorOperations.jl](https://github.com/Jutho/TensorOperations.jl).
+The algorithm in ITensors.jl currently uses a modified version of[^1] with simplifications for outer product contractions and is based on the implementation in [TensorOperations.jl](https://github.com/Jutho/TensorOperations.jl).
 
 [^1]: [Faster identification of optimal contraction sequences for tensor networks](https://arxiv.org/abs/1304.6112)
 [^2]: [Improving the efficiency of variational tensor network algorithms](https://arxiv.org/abs/1310.8023)

docs/src/DeveloperGuide.md

@@ -1,12 +1,10 @@
 # Next Steps
 
-* Try one of the [Tutorials](@ref dmrg_tutorial) in the next section of the ITensor documentation
-
 * Browse the [Code Examples](@ref itensor_examples).
 
 * Read the [ITensor Paper](https://www.scipost.org/SciPostPhysCodeb.4) for a long-form introduction to the design and main features of the ITensor library
 
-* Read the [Advanced ITensor Usage Guide](@ref advanced_usage_guide)
+* Refer to the [ITensorMPS.jl documentation](https://itensor.github.io/ITensorDocs/ITensorMPS) for information on running finite MPS/MPO calculations such as DMRG.
 
 * More Julia language tutorials and resources
     - [From zero to Julia!](https://techytok.com/from-zero-to-julia/)

docs/src/faq/QN.md

@@ -5,25 +5,26 @@ tensor network algorithms.
 
 | **Documentation**|**Citation**|
 |:----------------:|:----------:|
-|[![docs](https://img.shields.io/badge/docs-latest-blue.svg)](https://itensor.github.io/ITensors.jl/dev/)|[![SciPost](https://img.shields.io/badge/SciPost-10.21468-blue.svg)](https://scipost.org/SciPostPhysCodeb.4) [![arXiv](https://img.shields.io/badge/arXiv-2007.14822-b31b1b.svg)](https://arxiv.org/abs/2007.14822)|
+|[![Stable](https://img.shields.io/badge/docs-stable-blue.svg)](https://itensor.github.io/ITensorDocs/ITensors/stable/) [![Dev](https://img.shields.io/badge/docs-dev-blue.svg)](https://itensor.github.io/ITensorDocs/ITensors/dev/)|[![SciPost](https://img.shields.io/badge/SciPost-10.21468-blue.svg)](https://scipost.org/SciPostPhysCodeb.4) [![arXiv](https://img.shields.io/badge/arXiv-2007.14822-b31b1b.svg)](https://arxiv.org/abs/2007.14822)|
 
 |**Version**|**Download Statistics**|**Style Guide**|**License**|
 |:---------:|:---------------------:|:-------------:|:---------:|
 |[![version](https://juliahub.com/docs/ITensors/version.svg)](https://juliahub.com/ui/Packages/ITensors/P3pqL)|[![ITensor Downloads](https://img.shields.io/badge/dynamic/json?url=http%3A%2F%2Fjuliapkgstats.com%2Fapi%2Fv1%2Fmonthly_downloads%2FITensors&query=total_requests&suffix=%2Fmonth&label=Downloads)](http://juliapkgstats.com/pkg/ITensors)|[![Code Style: Blue](https://img.shields.io/badge/code%20style-blue-4495d1.svg)](https://github.com/invenia/BlueStyle)|[![license](https://img.shields.io/badge/License-Apache_2.0-blue.svg)](https://github.com/ITensor/ITensors.jl/blob/main/LICENSE)|
 
-The source code for ITensor can be found [on Github](https://github.com/ITensor/ITensors.jl).
+The source code for ITensors.jl can be found [on Github](https://github.com/ITensor/ITensors.jl).
 
-Additional documentation can be found on the ITensor website [itensor.org](https://itensor.org/).
+Additional documentation can be found on the ITensor website [itensor.org](https://itensor.org).
 
 An ITensor is a tensor whose interface
 is independent of its memory layout. ITensor indices are
 objects which carry extra information and which
 'recognize' each other (compare equal to each other).
 
-The ITensor library also includes composable and extensible
-algorithms for optimizing and transforming tensor networks, such as
-matrix product state and matrix product operators, such as
-the DMRG algorithm.
+The [ITensorMPS.jl library](https://github.com/ITensor/ITensorMPS.jl)
+includes composable and extensible algorithms for optimizing and transforming
+tensor networks, such as matrix product state and matrix product operators, such as
+the DMRG algorithm. If you are looking for information on running finite MPS/MPO
+calculations such as DMRG, take a look at the [ITensorMPS.jl documentation](https://itensor.github.io/ITensorDocs/ITensorMPS).
 
 Development of ITensor is supported by the Flatiron Institute, a division of the Simons Foundation.
 
@@ -46,7 +47,7 @@ Development of ITensor is supported by the Flatiron Institute, a division of the
 - March 25, 2022: ITensors.jl v0.3 has been released. The main breaking change is that we no longer support versions of Julia below 1.6. Julia 1.6 is the long term support version of Julia (LTS), which means that going forward versions below Julia 1.6 won't be as well supported with bug fixes and improvements. Additionally, Julia 1.6 introduced many improvements including syntax improvements that we would like to start using with ITensors.jl, which becomes challenging if we try to support Julia versions below 1.6. See [here](https://www.oxinabox.net/2021/02/13/Julia-1.6-what-has-changed-since-1.0.html) and [here](https://julialang.org/blog/2021/03/julia-1.6-highlights/) for some nice summaries of the Julia 1.6 release.
 
 -  Jun 09, 2021: ITensors.jl v0.2 has been released, with a few breaking changes as well as a variety of bug fixes
-and new features. Take a look at the [upgrade guide](https://itensor.github.io/ITensors.jl/stable/UpgradeGuide_0.1_to_0.2.html)
+and new features. Take a look at the [upgrade guide](https://itensor.github.io/ITensorDocs/ITensors/dev/UpgradeGuide_0.1_to_0.2.html)
 for help upgrading your code.
 
 ## Installation