minor edits to readme (#58)

Author: Wang-Shengtao

CITATION.bib

@@ -1,12 +1,17 @@
-@misc{https://doi.org/10.48550/arxiv.2205.03718,
-  doi = {10.48550/ARXIV.2205.03718},
-  url = {https://arxiv.org/abs/2205.03718},
-  author = {Liu, Jin-Guo and Gao, Xun and Cain, Madelyn and Lukin, Mikhail D. and Wang, Sheng-Tao},
-  keywords = {Statistical Mechanics (cond-mat.stat-mech), FOS: Physical sciences, FOS: Physical sciences},
-  title = {Computing solution space properties of combinatorial optimization problems via generic tensor networks},
-  publisher = {arXiv},
-  year = {2022},
-  copyright = {Creative Commons Attribution 4.0 International}
+@ARTICLE{Liu2022Computing,
+       author = {{Liu}, Jin-Guo and {Gao}, Xun and {Cain}, Madelyn and {Lukin}, Mikhail D. and {Wang}, Sheng-Tao},
+        title = "{Computing solution space properties of combinatorial optimization problems via generic tensor networks}",
+      journal = {arXiv e-prints},
+     keywords = {Condensed Matter - Statistical Mechanics},
+         year = 2022,
+        month = may,
+          eid = {arXiv:2205.03718},
+        pages = {arXiv:2205.03718},
+archivePrefix = {arXiv},
+       eprint = {2205.03718},
+ primaryClass = {cond-mat.stat-mech},
+       adsurl = {https://ui.adsabs.harvard.edu/abs/2022arXiv220503718L},
+      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
 }
 
 @article{Ebadi_2022,

README.md

@@ -11,7 +11,7 @@ The *solution space properties* include
 * The number of solutions at certain sizes,
 * The enumeration/sampling of solutions at certain sizes.
 
-The solvable problems include [Independent set problem](https://queracomputing.github.io/GenericTensorNetworks.jl/dev/generated/IndependentSet/), [Maximal independent set problem](https://queracomputing.github.io/GenericTensorNetworks.jl/dev/generated/MaximalIS/), [Spin-glass problem](https://queracomputing.github.io/GenericTensorNetworks.jl/dev/generated/SpinGlass/), [Cutting problem](https://queracomputing.github.io/GenericTensorNetworks.jl/dev/generated/MaxCut/), [Vertex matching problem](https://queracomputing.github.io/GenericTensorNetworks.jl/dev/generated/Matching/), [Binary paint shop problem](https://queracomputing.github.io/GenericTensorNetworks.jl/dev/generated/PaintShop/), [Coloring problem](https://queracomputing.github.io/GenericTensorNetworks.jl/dev/generated/Coloring/), [Dominating set problem](https://queracomputing.github.io/GenericTensorNetworks.jl/dev/generated/DominatingSet/), [Set packing problem](https://queracomputing.github.io/GenericTensorNetworks.jl/dev/generated/SetPacking/), [Satisfiability problem](https://queracomputing.github.io/GenericTensorNetworks.jl/dev/generated/Satisfiability/) and [Set covering problem](https://queracomputing.github.io/GenericTensorNetworks.jl/dev/generated/SetCovering/).
+The types of problems that can be solved using this package include [Independent set problem](https://queracomputing.github.io/GenericTensorNetworks.jl/dev/generated/IndependentSet/), [Maximal independent set problem](https://queracomputing.github.io/GenericTensorNetworks.jl/dev/generated/MaximalIS/), [Spin-glass problem](https://queracomputing.github.io/GenericTensorNetworks.jl/dev/generated/SpinGlass/), [Cutting problem](https://queracomputing.github.io/GenericTensorNetworks.jl/dev/generated/MaxCut/), [Vertex matching problem](https://queracomputing.github.io/GenericTensorNetworks.jl/dev/generated/Matching/), [Binary paint shop problem](https://queracomputing.github.io/GenericTensorNetworks.jl/dev/generated/PaintShop/), [Coloring problem](https://queracomputing.github.io/GenericTensorNetworks.jl/dev/generated/Coloring/), [Dominating set problem](https://queracomputing.github.io/GenericTensorNetworks.jl/dev/generated/DominatingSet/), [Set packing problem](https://queracomputing.github.io/GenericTensorNetworks.jl/dev/generated/SetPacking/), [Satisfiability problem](https://queracomputing.github.io/GenericTensorNetworks.jl/dev/generated/Satisfiability/) and [Set covering problem](https://queracomputing.github.io/GenericTensorNetworks.jl/dev/generated/SetCovering/).
 
 ## Installation
 <p>
@@ -22,7 +22,7 @@ GenericTensorNetworks is a &nbsp;
     </a>
     &nbsp; package. To install GenericTensorNetworks,
     please <a href="https://docs.julialang.org/en/v1/manual/getting-started/">open
-    Julia's interactive session (known as REPL)</a> and press <kbd>]</kbd> key in the REPL to use the package mode, then type
+    Julia's interactive session (known as REPL)</a> and press the <kbd>]</kbd> key in the REPL to use the package mode, and then type:
 </p>
 
 ```julia
@@ -31,11 +31,11 @@ pkg> add GenericTensorNetworks
 
 To update, just type `up` in the package mode.
 
-We recommend you to use **Julia version >= 1.7**, otherwise your program can suffer from significant (exponential in tensor dimension) overheads when permuting the dimensions of a large tensor.
-If you have to use an older version Julia, you can overwrite the `LinearAlgebra.permutedims!` by adding the following patch to your own project.
+We recommend that you use **Julia version >= 1.7**; otherwise, your program may suffer from significant (exponential in the tensor dimension) overheads when permuting the dimensions of a large tensor.
+If you have to use an older version of Julia, you can overwrite the `LinearAlgebra.permutedims!` by adding the following patch to your own project.
 
 ```julia
-# only required when your Julia version < 1.7
+# only required when your Julia version is < 1.7
 using TensorOperations, LinearAlgebra
 function LinearAlgebra.permutedims!(C::Array{T,N}, A::StridedArray{T,N}, perm) where {T,N}
     if isbitstype(T)
@@ -48,15 +48,15 @@ end
 
 ## Supporting and Citing
 
-Much of the software in this ecosystem was developed as part of academic research.
-If you would like to help support it, please star the repository as such metrics may help us secure funding in the future.
-If you use our software as part of your research, teaching, or other activities, we would be grateful if you could cite our work.
+Much of the software in this ecosystem was developed as a part of an academic research project.
+If you would like to help support it, please star the repository.
+If you use our software as part of your research, teaching, or other activities, we would like to request you to cite our [work](https://arxiv.org/abs/2205.03718). 
 The
 [CITATION.bib](https://github.com/QuEraComputing/GenericTensorNetworks.jl/blob/master/CITATION.bib) file in the root of this repository lists the relevant papers.
 
 ## Questions and Contributions
 
 You can
-* Post a question on [Julia Discourse forum](https://discourse.julialang.org/), pin the package maintainer wih `@1115`.
-* Discuss in the `#graphs` channel of the [Julia Slack](https://julialang.org/community/), ping the package maintainer with `@JinGuo Liu`.
-* Open an [issue](https://github.com/QuEraComputing/GenericTensorNetworks.jl/issues) if you encounter any problems, or have any feature request.
+* Post a question on [Julia Discourse forum](https://discourse.julialang.org/) and ping the package maintainer with `@1115`.
+* Discuss in the `#graphs` channel of the [Julia Slack](https://julialang.org/community/) and ping the package maintainer with `@JinGuo Liu`.
+* Open an [issue](https://github.com/QuEraComputing/GenericTensorNetworks.jl/issues) if you encounter any problems, or have any feature request.