docs: update the citation of deepmd-kit v3 (deepmodeling#4738)

<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit

- **Documentation**
- Updated all references and citations for the DeePMD-kit v3 paper from
the previous arXiv preprint to the formal journal publication in the
Journal of Chemical Theory and Computation, including updated DOI,
volume, issue, and page numbers.
- Enhanced citation entries with a detailed abstract and corrected
bibliographic metadata.
- Updated citation badges and links in documentation to reference the
published article.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->

---------

Signed-off-by: Jinzhe Zeng <jinzhe.zeng@ustc.edu.cn>

Author: njzjz

CITATIONS.bib

@@ -40,7 +40,7 @@ @article{Zeng_JChemPhys_2023_v159_p054801
   doi          = {10.1063/5.0155600},
 }
 
-@article{Zeng_arXiv_2025_p2502.19161,
+@article{Zeng_JChemTheoryComput_2025_v21_p4375,
   annote       = {general purpose},
   author       = {
     Jinzhe Zeng and Duo Zhang and Anyang Peng and Xiangyu Zhang and Sensen He
@@ -59,10 +59,31 @@ @article{Zeng_arXiv_2025_p2502.19161
     {DeePMD-kit v3: A Multiple-Backend Framework for Machine Learning
     Potentials}
   },
-  journal      = {arXiv},
+  journal      = {J. Chem. Theory Comput.},
   year         = 2025,
-  pages        = {2502.19161},
-  doi          = {10.48550/arXiv.2502.19161},
+  volume       = 21,
+  number       = 9,
+  pages        = {4375--4385},
+  doi          = {10.1021/acs.jctc.5c00340},
+  abstract     = {
+    In recent years, machine learning potentials (MLPs) have become
+    indispensable tools in physics, chemistry, and materials science, driving
+    the development of software packages for molecular dynamics (MD)
+    simulations and related applications. These packages, typically built on
+    specific machine learning frameworks, such as TensorFlow, PyTorch, or JAX,
+    face integration challenges when advanced applications demand communication
+    across different frameworks. The previous TensorFlow-based implementation
+    of the DeePMD-kit exemplified these limitations. In this work, we introduce
+    DeePMD-kit version 3, a significant update featuring a multibackend
+    framework that supports TensorFlow, PyTorch, JAX, and PaddlePaddle
+    backends, and demonstrate the versatility of this architecture through the
+    integration of other MLP packages and of differentiable molecular force
+    fields. This architecture allows seamless back-end switching with minimal
+    modifications, enabling users and developers to integrate DeePMD-kit with
+    other packages using different machine learning frameworks. This innovation
+    facilitates the development of more complex and interoperable workflows,
+    paving the way for broader applications of MLPs in scientific research.
+  },
 }
 
 @article{Lu_CompPhysCommun_2021_v259_p107624,

README.md

@@ -36,7 +36,9 @@ If you use this code in any future publications, please cite the following publi
 - Jinzhe Zeng, Duo Zhang, Denghui Lu, Pinghui Mo, Zeyu Li, Yixiao Chen, Marián Rynik, Li'ang Huang, Ziyao Li, Shaochen Shi, Yingze Wang, Haotian Ye, Ping Tuo, Jiabin Yang, Ye Ding, Yifan Li, Davide Tisi, Qiyu Zeng, Han Bao, Yu Xia, Jiameng Huang, Koki Muraoka, Yibo Wang, Junhan Chang, Fengbo Yuan, Sigbjørn Løland Bore, Chun Cai, Yinnian Lin, Bo Wang, Jiayan Xu, Jia-Xin Zhu, Chenxing Luo, Yuzhi Zhang, Rhys E. A. Goodall, Wenshuo Liang, Anurag Kumar Singh, Sikai Yao, Jingchao Zhang, Renata Wentzcovitch, Jiequn Han, Jie Liu, Weile Jia, Darrin M. York, Weinan E, Roberto Car, Linfeng Zhang, Han Wang. "DeePMD-kit v2: A software package for deep potential models." J. Chem. Phys. 159 (2023): 054801.
   [![doi:10.1063/5.0155600](https://img.shields.io/badge/DOI-10.1063%2F5.0155600-blue)](https://doi.org/10.1063/5.0155600)
   [![Citations](https://citations.njzjz.win/10.1063/5.0155600)](https://badge.dimensions.ai/details/doi/10.1063/5.0155600)
-- Jinzhe Zeng, Duo Zhang, Anyang Peng, Xiangyu Zhang, Sensen He, Yan Wang, Xinzijian Liu, Hangrui Bi, Yifan Li, Chun Cai, Chengqian Zhang, Yiming Du, Jia-Xin Zhu, Pinghui Mo, Zhengtao Huang, Qiyu Zeng, Shaochen Shi, Xuejian Qin, Zhaoxi Yu, Chenxing Luo, Ye Ding, Yun-Pei Liu, Ruosong Shi, Zhenyu Wang, Sigbjørn Løland Bore, Junhan Chang, Zhe Deng, Zhaohan Ding, Siyuan Han, Wanrun Jiang, Guolin Ke, Zhaoqing Liu, Denghui Lu, Koki Muraoka, Hananeh Oliaei, Anurag Kumar Singh, Haohui Que, Weihong Xu, Zhangmancang Xu, Yong-Bin Zhuang, Jiayu Dai, Timothy J. Giese, Weile Jia, Ben Xu, Darrin M. York, Linfeng Zhang, Han Wang. "DeePMD-kit v3: A Multiple-Backend Framework for Machine Learning Potentials." [arXiv:2502.19161](https://arxiv.org/abs/2502.19161).
+- Jinzhe Zeng, Duo Zhang, Anyang Peng, Xiangyu Zhang, Sensen He, Yan Wang, Xinzijian Liu, Hangrui Bi, Yifan Li, Chun Cai, Chengqian Zhang, Yiming Du, Jia-Xin Zhu, Pinghui Mo, Zhengtao Huang, Qiyu Zeng, Shaochen Shi, Xuejian Qin, Zhaoxi Yu, Chenxing Luo, Ye Ding, Yun-Pei Liu, Ruosong Shi, Zhenyu Wang, Sigbjørn Løland Bore, Junhan Chang, Zhe Deng, Zhaohan Ding, Siyuan Han, Wanrun Jiang, Guolin Ke, Zhaoqing Liu, Denghui Lu, Koki Muraoka, Hananeh Oliaei, Anurag Kumar Singh, Haohui Que, Weihong Xu, Zhangmancang Xu, Yong-Bin Zhuang, Jiayu Dai, Timothy J. Giese, Weile Jia, Ben Xu, Darrin M. York, Linfeng Zhang, Han Wang. "DeePMD-kit v3: A Multiple-Backend Framework for Machine Learning Potentials." J. Chem. Theory Comput. 21 (2025): 4375-4385.
+  [![doi:10.1021/acs.jctc.5c00340](https://img.shields.io/badge/DOI-10.1021%2Facs.jctc.5c00340-blue)](https://doi.org/10.1021/acs.jctc.5c00340)
+  [![Citations](https://citations.njzjz.win/10.1021/acs.jctc.5c00340)](https://badge.dimensions.ai/details/doi/10.1021/acs.jctc.5c00340)
 
 In addition, please follow [the bib file](CITATIONS.bib) to cite the methods you used.
 
@@ -77,7 +79,7 @@ See [our v2 paper](https://doi.org/10.1063/5.0155600) for details of all feature
 - The DPA-2 model.
 - Plugin mechanisms for external models.
 
-See [our v3 paper](https://doi.org/10.48550/arXiv.2502.19161) for details of all features until v3.0.
+See [our v3 paper](https://doi.org/10.1021/acs.jctc.5c00340) for details of all features until v3.0.
 
 ## Install and use DeePMD-kit
 

deepmd/utils/summary.py

@@ -42,7 +42,7 @@ class SummaryPrinter(ABC):
         "Please read and cite:",
         "Wang, Zhang, Han and E, Comput.Phys.Comm. 228, 178-184 (2018)",
         "Zeng et al, J. Chem. Phys., 159, 054801 (2023)",
-        "Zeng et al, arxiv:2502.19161",
+        "Zeng et al, J. Chem. Theory Comput., 21, 4375-4385 (2025)",
         "See https://deepmd.rtfd.io/credits/ for details.",
     )
 

doc/credits.rst

@@ -13,7 +13,7 @@ Cite DeePMD-kit and methods
 
    Wang_ComputPhysCommun_2018_v228_p178
    Zeng_JChemPhys_2023_v159_p054801
-   Zeng_arXiv_2025_p2502.19161
+   Zeng_JChemTheoryComput_2025_v21_p4375
 
 - If GPU version is used,
 

source/lmp/pair_deepmd.cpp

@@ -83,9 +83,8 @@ static const char cite_user_deepmd_package[] =
     "  pages  =   054801,\n"
     "  doi =      {10.1063/5.0155600},\n"
     "}\n"
-    "@Article{Zeng_arXiv_2025_p2502.19161,\n"
-    "  annote       = {general purpose},\n"
-    "    author =   {Jinzhe Zeng and Duo Zhang and Anyang Peng and Xiangyu "
+    "@Article{Zeng_JChemTheoryComput_2025_v21_p4375,\n"
+    "  author =   {Jinzhe Zeng and Duo Zhang and Anyang Peng and Xiangyu "
     "Zhang and Sensen\n"
     "             He and Yan Wang and Xinzijian Liu and Hangrui Bi and Yifan "
     "Li and Chun\n"
@@ -110,10 +109,12 @@ static const char cite_user_deepmd_package[] =
     "    title =    {{DeePMD-kit v3: A Multiple-Backend Framework for Machine "
     "Learning\n"
     "             Potentials}},\n"
-    "    journal =  {arXiv},\n"
-    "    year =     2025,\n"
-    "    pages =    {2502.19161},\n"
-    "    doi =      {10.48550/arXiv.2502.19161},\n"
+    "  journal =  {J. Chem. Theory Comput.},\n"
+    "  year =     2025,\n"
+    "  volume =   21,\n"
+    "  number =   9,\n"
+    "  pages =    {4375--4385},\n"
+    "  doi =      {10.1021/acs.jctc.5c00340},\n"
     "}\n\n";
 
 PairDeepMD::PairDeepMD(LAMMPS *lmp)

source/lmp/pair_deepspin.cpp

@@ -83,9 +83,8 @@ static const char cite_user_deepmd_package[] =
     "  pages  =   054801,\n"
     "  doi =      {10.1063/5.0155600},\n"
     "}\n"
-    "@Article{Zeng_arXiv_2025_p2502.19161,\n"
-    "  annote       = {general purpose},\n"
-    "    author =   {Jinzhe Zeng and Duo Zhang and Anyang Peng and Xiangyu "
+    "@Article{Zeng_JChemTheoryComput_2025_v21_p4375,\n"
+    "  author =   {Jinzhe Zeng and Duo Zhang and Anyang Peng and Xiangyu "
     "Zhang and Sensen\n"
     "             He and Yan Wang and Xinzijian Liu and Hangrui Bi and Yifan "
     "Li and Chun\n"
@@ -110,10 +109,12 @@ static const char cite_user_deepmd_package[] =
     "    title =    {{DeePMD-kit v3: A Multiple-Backend Framework for Machine "
     "Learning\n"
     "             Potentials}},\n"
-    "    journal =  {arXiv},\n"
-    "    year =     2025,\n"
-    "    pages =    {2502.19161},\n"
-    "    doi =      {10.48550/arXiv.2502.19161},\n"
+    "  journal =  {J. Chem. Theory Comput.},\n"
+    "  year =     2025,\n"
+    "  volume =   21,\n"
+    "  number =   9,\n"
+    "  pages =    {4375--4385},\n"
+    "  doi =      {10.1021/acs.jctc.5c00340},\n"
     "}\n\n";
 
 PairDeepSpin::PairDeepSpin(LAMMPS *lmp)