🎉 Release new version v.0.4.7

CITATION.bib

@@ -0,0 +1,12 @@
+@article{HUO2025107189,
+title = {A high-performance backend-agnostic Material Point Method solver in Julia},
+journal = {Computers and Geotechnics},
+volume = {183},
+pages = {107189},
+year = {2025},
+issn = {0266-352X},
+doi = {https://doi.org/10.1016/j.compgeo.2025.107189},
+url = {https://www.sciencedirect.com/science/article/pii/S0266352X25001387},
+author = {Zenan Huo and Yury Alkhimenkov and Michel Jaboyedoff and Yury Podladchikov and Ludovic Räss and Emmanuel Wyser and Gang Mei},
+keywords = {MPM, Julia language, Heterogeneous computing, Effective memory throughput}
+}

Project.toml

@@ -1,7 +1,7 @@
 name = "MaterialPointSolver"
 uuid = "dc4aa359-7d89-437d-91bb-f4b330c522c1"
 authors = ["Zenan Huo <zenan.huo@outlook.com>"]
-version = "0.4.6"
+version = "0.4.7"
 
 [deps]
 Adapt = "79e6a3ab-5dfb-504d-930d-738a2a938a0e"

README.md

@@ -3,7 +3,7 @@
 [![CI](https://github.com/LandslideSIM/MaterialPointSolver.jl/actions/workflows/ci.yml/badge.svg)](https://github.com/LandslideSIM/MaterialPointSolver.jl/actions/workflows/ci.yml) 
 [![Stable](https://img.shields.io/badge/docs-stable-blue.svg?logo=quicklook)](https://landslidesim.github.io/MaterialPointSolver.jl/stable/)
 [![Dev](https://img.shields.io/badge/docs-dev-red.svg?logo=quicklook)](https://landslidesim.github.io/MaterialPointSolver.jl/dev/)
-[![Version](https://img.shields.io/badge/version-v0.4.6-pink)]()
+[![Version](https://img.shields.io/badge/version-v0.4.7-pink)]()
 
 [![](https://img.shields.io/badge/NVIDIA-CUDA-green.svg?logo=nvidia)](https://developer.nvidia.com/cuda-toolkit)
 [![](https://img.shields.io/badge/AMD-ROCm-red.svg?logo=amd)](https://www.amd.com/en/products/software/rocm.html)
@@ -107,4 +107,5 @@ This project is sponsored by [Risk Group | Université de Lausanne](https://wp.u
 
 * [✍️ [code]: MPM-Julia](https://github.com/vinhphunguyen/MPM-Julia) is the code for the paper: Sinai, V.P. Nguyen, C.T. Nguyen and S. Bordas. Programming the Material Point Method in Julia. Advances in Engineering Software,105: 17--29, 2017.
 
-* [[✍️ code]: jump](https://github.com/vinhphunguyen/jump) is for the theory of the MPM described in the book 'The Material Point Method: Theory, Implementations and Applications (Scientific Computation) 1st ed. 2023 Edition'. [https://link.springer.com/book/10.1007/978-3-031-24070-6](https://link.springer.com/book/10.1007/978-3-031-24070-6)
+* [✍️ [code]: jump](https://github.com/vinhphunguyen/jump) is for the theory of the MPM described in the book 'The Material Point Method: Theory, Implementations and Applications (Scientific Computation) 1st ed. 2023 Edition'. 
+[https://link.springer.com/book/10.1007/978-3-031-24070-6](https://link.springer.com/book/10.1007/978-3-031-24070-6)

docs/src/introduction/getstarted.md

@@ -44,12 +44,17 @@ using oneAPI
 If you find ***MaterialPointSolver.jl*** useful or have used it in your research, please cite it as follows:
 
 ```bib
-@article{index,
-  title={Here is the title},
-  author={authors},
-  journal={journal},
-  year={year}
-}
+@article{HUO2025107189,
+title = {A high-performance backend-agnostic Material Point Method solver in Julia},
+journal = {Computers and Geotechnics},
+volume = {183},
+pages = {107189},
+year = {2025},
+issn = {0266-352X},
+doi = {https://doi.org/10.1016/j.compgeo.2025.107189},
+url = {https://www.sciencedirect.com/science/article/pii/S0266352X25001387},
+author = {Zenan Huo and Yury Alkhimenkov and Michel Jaboyedoff and Yury Podladchikov and Ludovic Räss and Emmanuel Wyser and Gang Mei},
+keywords = {MPM, Julia language, Heterogeneous computing, Effective memory throughput}
 ```
 
 ::: warning