Docs (#87)

* new docs * new citation and figures * version changed * citation * docs minor changes in index * change authors --------- Co-authored-by: annamariadziubyna <[email protected]>
euro-hpc-pl · Oct 9, 2024 · d9c42f7 · d9c42f7
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diff --git a/Project.toml b/Project.toml
@@ -1,8 +1,10 @@
 name = "SpinGlassPEPS"
 uuid = "2c514f87-1261-494e-8566-326879aaf4fe"
-version = "1.3.0"
+version = "1.4.0"
 
 [deps]
+Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
+DocumenterTools = "35a29f4d-8980-5a13-9543-d66fff28ecb8"
 Reexport = "189a3867-3050-52da-a836-e630ba90ab69"
 SpinGlassEngine = "0563570f-ea1b-4080-8a64-041ac6565a4e"
 SpinGlassExhaustive = "a894d7c4-7f54-4100-9d77-d00d924adeb3"
@@ -11,9 +13,9 @@ SpinGlassTensors = "7584fc6a-5a23-4eeb-8277-827aab0146ea"
 
 [compat]
 Reexport = "1.0"
-SpinGlassEngine = "1.4.0"
+SpinGlassEngine = "1.5.0"
 SpinGlassExhaustive = "1.0.0"
-SpinGlassNetworks = "1.2.0"
+SpinGlassNetworks = "1.3.0"
 SpinGlassTensors = "1.1.3"
 julia = "1.10"
 

diff --git a/docs/src/algorithm.md b/docs/src/algorithm.md
@@ -16,7 +16,7 @@ We assume that graph $\mathcal{E}$ forms a quasi-2D lattice. In real life applic
 ```@raw html
 <img src="../images/lattice.png" width="200%" class="center"/>
 ```
-In order to adress this three types of geometries using tensor networks, we represent the problem as a clustered Hamiltonian. To that end we group together sets of variables. In this framework Ising problem translates to:
+In order to adress this three types of geometries using tensor networks, we represent the problem as a Potts Hamiltonian. To that end we group together sets of variables. In this framework Ising problem translates to:
 ```math
 H(\underline{x}_{\bar{N}}) = \sum_{\langle m,n\rangle \in \mathcal{F}} E_{x_m x_n} + \sum_{n=1}^{\bar{N}} E_{x_n}
 ```

diff --git a/docs/src/images/algorithm.png b/docs/src/images/algorithm.png
diff --git a/docs/src/images/clustering.png b/docs/src/images/clustering.png
diff --git a/docs/src/images/lattice.png b/docs/src/images/lattice.png
diff --git a/docs/src/index.md b/docs/src/index.md
@@ -1,5 +1,5 @@
 ```@meta
-Author = "Krzysztof Domino, Bartłomiej Gardas, Konrad Jałowiecki, Łukasz Pawela, Marek Rams, Anna Dziubyna, Tomasz Śmierzchalski"
+Author = "Tomasz Śmierzchalski, Anna M. Dziubyna, Konrad Jałowiecki, Zakaria Mzaouali, Łukasz Pawela, Bartłomiej Gardas and Marek M. Rams"
 ```
 
 # Welcome to SpinGlassPEPS.jl documentation!
@@ -19,24 +19,26 @@ using Pkg;
 Pkg.add("SpinGlassPEPS")
 ```
 The package `SpinGlassPEPS.jl` includes:
+* `SpinGlassEngine.jl` - Package containing the solver itself and tools focused on finding and operating on excitations. 
+* `SpinGlassNetworks.jl` - Package containing all tools needed to construct an Ising graph from a given instance and create Potts Hamiltonian.
 * `SpinGlassTensors.jl` - Package containing all necessary functionalities for creating and operating on tensors. It allows the use of both CPU and GPU.
-* `SpinGlassNetworks.jl` - Package containing all tools needed to construct a tensor network from a given instance.
-* `SpinGlassEngine.jl` - Package containing the solver itself and tools focused on finding and operating on droplets. 
+
 ```@raw html
 <img src="images/algorithm.png" width="200%" class="center"/>
 ```
 
 ## Our goals
 
-`SpinGlassPEPS.jl` was created to heuristically solve Ising-type optimization problems defined on quasi-2D lattices or Random Markov Fields (RMF) on 2D rectangular lattices. This package combines advanced heuristics to address optimization challenges and employs tensor network contractions to compute conditional probabilities to identify the most probable states according to the Gibbs distribution. `SpinGlassPEPS.jl` is a tool for reconstructing the low-energy spectrum of Ising spin glass Hamiltonians and RMF Hamiltonians. Beyond energy computations, the package offers insights into spin configurations, associated probabilities, and retains the largest discarded probability during the branch and bound optimization procedure. Notably, `SpinGlassPEPS.jl` goes beyond ground states, introducing a unique feature for identifying and analyzing spin glass droplets — collective excitations crucial for understanding system dynamics beyond the fundamental ground state configurations. 
+`SpinGlassPEPS.jl` was created to heuristically solve Ising-type optimization problems defined on quasi-2D lattices or Random Markov Fields (RMF) on 2D rectangular lattices. This package combines advanced heuristics to address optimization challenges and employs tensor network contractions to compute conditional probabilities to identify the most probable states according to the Gibbs distribution. `SpinGlassPEPS.jl` is a tool for reconstructing the low-energy spectrum of Ising spin glass Hamiltonians and RMF Hamiltonians. Beyond energy computations, the package offers insights into spin configurations, associated probabilities, and retains the largest discarded probability during the branch and bound optimization procedure. Notably, `SpinGlassPEPS.jl` goes beyond ground states, introducing a feature for identifying and analyzing spin glass droplets — collective excitations crucial for understanding system dynamics beyond the fundamental ground state configurations. 
 ```@raw html
 <img src="images/result.png" width="200%" class="center"/>
 ```
 
 ## Citing SpinGlassPEPS.jl
 If you use `SpinGlassPEPS.jl` for academic research and wish to cite it, please use the following paper:
 
-K. Jałowiecki, K. Domino, A. M. Dziubyna, M. M. Rams, B. Gardas and Ł. Pawela, *“SpinGlassPEPS.jl: software to emulate quantum annealing processors”*
+Tomasz Śmierzchalski, Anna M. Dziubyna, Konrad Jałowiecki, Zakaria Mzaouali, Łukasz Pawela, Bartłomiej Gardas and Marek M. Rams, 
+*“SpinGlassPEPS.jl: low-energy solutions for near-term quantum annealers"*
 
 ## Contributing
 Contributions are always welcome: