Merge branch 'develop' into out_mat_dh

Author: xuan112358

.gitignore

@@ -17,7 +17,6 @@ STRU_READIN_ADJUST.cif
 build
 dist
 .idea
-toolchain.tar.gz
 time.json
 *.pyc
 __pycache__

Dockerfile.intel

@@ -44,6 +44,9 @@ RUN source /opt/intel/oneapi/setvars.sh && \
     ln -s /usr/local/include/elpa_openmp-$ELPA_VER/elpa /usr/local/include/ && \
     cd /tmp && rm -rf elpa-$ELPA_VER
 
+RUN cd /tmp && git clone https://github.com/Tencent/rapidjson.git && cp -r rapidjson/include/rapidjson /usr/include/ \
+    && rm -rf rapidjson
+
 RUN wget https://download.pytorch.org/libtorch/cpu/libtorch-cxx11-abi-shared-with-deps-2.0.0%2Bcpu.zip \
         --no-check-certificate --quiet -O libtorch.zip && \
     unzip -q libtorch.zip -d /opt  && rm libtorch.zip

README.md

@@ -12,7 +12,7 @@
 
 # About ABACUS
 
-ABACUS (Atomic-orbital Based Ab-initio Computation at UStc) is an open-source package based on density functional theory (DFT). The package utilizes both plane wave and numerical atomic basis sets with the usage of norm-conserving pseudopotentials to describe the interactions between nuclear ions and valence electrons. ABACUS supports LDA, GGA, meta-GGA, and hybrid functionals. Apart from single-point calculations, the package allows geometry optimizations and ab-initio molecular dynamics with various ensembles. The package also provides a variety of advanced functionalities for simulating materials, including the DFT+U, VdW corrections, and implicit solvation model, etc. In addition, ABACUS strives to provide a general infrastructure to facilitate the developments and applications of novel machine-learning-assisted DFT methods (DeePKS, DP-GEN, DeepH, DeePTB etc.) in molecular and material simulations.
+ABACUS (**A**tomic-orbital **B**ased **A**b-initio **C**omputation at **US**tc) is an open-source package based on density functional theory (DFT). The package utilizes both plane wave and numerical atomic basis sets with the usage of pseudopotentials to describe the interactions between nuclear ions and valence electrons. ABACUS supports LDA, GGA, meta-GGA, and hybrid functionals. Apart from single-point calculations, the package allows geometry optimizations and ab-initio molecular dynamics with various ensembles. The package also provides a variety of advanced functionalities for simulating materials, including the DFT+U, VdW corrections, and implicit solvation model, etc. In addition, ABACUS strives to provide a general infrastructure to facilitate the developments and applications of novel machine-learning-assisted DFT methods (DeePKS, DP-GEN, DeepH, DeePTB etc.) in molecular and material simulations.
 
 # Online Documentation
 For detailed documentation, please refer to [our documentation website](https://abacus.deepmodeling.com/).

docs/CITATIONS.md

@@ -4,10 +4,18 @@ The following references are required to be cited when using ABACUS. Specificall
 
 - **For general purpose:**
 
+    *For LCAO basis:*
+
     Mohan Chen, G. C. Guo, and Lixin He. "Systematically improvable optimized atomic basis sets for ab initio calculations." Journal of Physics: Condensed Matter 22.44 (2010): 445501.
 
     Pengfei Li, et al. "Large-scale ab initio simulations based on systematically improvable atomic basis." Computational Materials Science 112 (2016): 503-517.
 
+    Peize Lin, Xinguo Ren, Xiaohui Liu, Lixin He. Ab initio electronic structure calculations based on numerical atomic orbitals: Basic fomalisms and recent progresses. Wiley Interdisciplinary Reviews: Computational Molecular Science, 2024, 14(1): e1687.
+
+    *For LCAO and PW basis:*
+
+    Weiqing Zhou, Deye Zheng, Qianrui Liu, et al. ABACUS: An Electronic Structure Analysis Package for the AI Era. arXiv preprint arXiv:2501.08697, 2025.
+
 - **If Stochastic DFT is used:**
 
     Qianrui Liu, and Mohan Chen. "Plane-Wave-Based Stochastic-Deterministic Density Functional Theory for Extended Systems." <https://arxiv.org/abs/2204.05662>.

docs/DevelopingTeam.md

@@ -4,5 +4,5 @@ The current development team consists the following research groups/affiliations
 - University of Science and Technology of China (Dr. Lixin He)
 - Peking University (Dr. Mohan Chen)
 - Institute of Physics, Chinese Academy of Sciences (Dr. Xinguo Ren)
-- Beijing AI for Science Institute
-- Institute of Artificial Intelligence, Hefei Comprehensive National Science Center. 
+- Beijing AI for Science Institute (Dr. Daye Zheng)
+- Institute of Artificial Intelligence, Hefei Comprehensive National Science Center (Dr. Lixin He). 

docs/advanced/input_files/input-main.md

@@ -3541,11 +3541,7 @@ These variables are used to control berry phase and wannier90 interface paramete
 - **Description**:
   `td_lcut1` is the lower bound of the interval in the length gauge RT-TDDFT, where $x$ is the fractional coordinate:
   $$
-    E(x)=
-    \begin{cases}
-        E_0, & \mathtt{cut1}\leqslant x \leqslant \mathtt{cut2} \\
-        -E_0\left(\dfrac{1}{\mathtt{cut1}+1-\mathtt{cut2}}-1\right), & \text{$0<x<\mathtt{cut1}$ or $\mathtt{cut2}<x<1$}
-    \end{cases}
+    E(x)=\begin{cases}E_0, & \mathtt{cut1}\leqslant x \leqslant \mathtt{cut2} \\-E_0\left(\dfrac{1}{\mathtt{cut1}+1-\mathtt{cut2}}-1\right), & 0 < x < \mathtt{cut1~~or~~cut2} < x < 1 \end{cases}
   $$
 - **Default**: 0.05
 
@@ -3555,11 +3551,7 @@ These variables are used to control berry phase and wannier90 interface paramete
 - **Description**:
   `td_lcut2` is the upper bound of the interval in the length gauge RT-TDDFT, where $x$ is the fractional coordinate:
   $$
-    E(x)=
-    \begin{cases}
-        E_0, & \mathtt{cut1}\leqslant x \leqslant \mathtt{cut2} \\
-        -E_0\left(\dfrac{1}{\mathtt{cut1}+1-\mathtt{cut2}}-1\right), & \text{$0<x<\mathtt{cut1}$ or $\mathtt{cut2}<x<1$}
-    \end{cases}
+    E(x)=\begin{cases}E_0, & \mathtt{cut1}\leqslant x \leqslant \mathtt{cut2} \\-E_0\left(\dfrac{1}{\mathtt{cut1}+1-\mathtt{cut2}}-1\right), & 0 < x < \mathtt{cut1~~or~~cut2} < x < 1 \end{cases}
   $$
 - **Default**: 0.95
 

docs/community/faq.md

@@ -109,7 +109,7 @@ write(cs_stru, cs_atoms, format='abacus', pp=pp, basis=basis)
 
 ABACUS applies the density difference between two SCF steps (labeled as `DRHO` in the screen output) as the convergence criterion, which is considered as a more robust choice compared with the energy difference. `DRHO` is calculated via `DRHO = |rho(G)-rho_previous(G)|^2`. Note that the energy difference between two SCF steps (labed as `EDIFF`) is also printed out in the screen output.
 
-**4. Why EDIFF is much slower than DRHO?
+**4. Why EDIFF is much slower than DRHO?**
 
 For metaGGA calculations, it is normal because in addition to charge density, kinetic density also needs to be considered in metaGGA calculations. In this case, you can try set `mixing_tau = true`. If you find EDIFF is much slower than DRHO for non-metaGGA calculations, please start a new issue to us.
 

docs/index.rst

@@ -10,7 +10,7 @@ ABACUS Documentation
 ABACUS (Atomic-orbital Based Ab-initio Computation at UStc) is
 an open-source computer code package based on density functional
 theory (DFT). The package utilizes both plane wave and numerical
-atomic basis sets with the usage of norm-conserving pseudopotentials
+atomic basis sets with the usage of pseudopotentials
 to describe the interactions between nuclear ions and valence electrons.
 ABACUS supports LDA, GGA, meta-GGA, and hybrid functionals. Apart from
 single-point calculations, the package allows geometry optimizations

docs/quick_start/easy_install.md

@@ -1,6 +1,6 @@
 # Easy Installation
 
-This guide helps you install ABACUS with basic features. **For DeePKS, DeePMD and Libxc support, or building with `make`, please refer to [the advanced installation guide](../advanced/install.md)** after going through this page. We recommend building ABACUS with `cmake` to avoid dependency issues. We recommend compiling ABACUS(and possibly its requirements) from the source code using the latest compiler for the best performace. You can try [toolchain](#install-requirements-by-toolchain) to install ABACUS and dependencies in a source-code compilation way with convience. You can also deploy ABACUS **without building** by [Docker](#container-deployment) or [conda](#install-by-conda). Please note that ABACUS only supports Linux; for Windows users, please consider using [WSL](https://learn.microsoft.com/en-us/windows/wsl/) or docker.
+This guide helps you install ABACUS with basic features. **For DeePKS, DeePMD and Libxc support, or building with `make`, please refer to [the advanced installation guide](../advanced/install.md)** after going through this page. We recommend building ABACUS with `cmake` to avoid dependency issues. We recommend compiling ABACUS (and possibly its requirements) from the source code using the latest compiler for the best performace. You can try [toolchain](#install-requirements-by-toolchain) to install ABACUS and dependencies in a source-code compilation way with convience. You can also deploy ABACUS **without building** by [Docker](#container-deployment) or [conda](#install-by-conda). Please note that ABACUS only supports Linux; for Windows users, please consider using [WSL](https://learn.microsoft.com/en-us/windows/wsl/) or docker.
 
 ## Get ABACUS source code
 
@@ -79,7 +79,7 @@ git remote -v
 
 # Replace "origin" with "upstream" or the remote name corresponding to deepmodeling/abacus-develop if necessary
 git fetch origin
-git checkout v3.8.4 # Replace the tag with the latest version
+git checkout v3.x.x # Replace the tag with the latest version, like v3.10.0
 git describe --tags # Verify if the tag has been successfully checked out
 ```
 
@@ -192,6 +192,8 @@ OMP_NUM_THREADS=4 mpirun -n 4 abacus
 
 In this case, the total thread count is 16.
 
+> Notice: If the MPI library you are using is OpenMPI, which is commonly the case, when you set the number of processes to 1 or 2, OpenMPI will default to `--bind-to core`. This means that no matter how many threads you set, these threads will be restricted to run on 1 or 2 CPU cores. Therefore, setting a higher number of OpenMP threads might result in slower program execution. Hence, when using `mpirun -n` set to 1 or 2, it is recommended to set `--bind-to none` to avoid performance degradation. For example:`OMP_NUM_THREADS=6 mpirun --bind-to none -n 1 abacus`. The detailed binding strategy of OpenMPI can be referred to at https://docs.open-mpi.org/en/v5.0.x/man-openmpi/man1/mpirun.1.html#quick-summary.
+
 ABACUS will try to determine the number of threads used by each process if `OMP_NUM_THREADS` is not set. However, it is **required** to set `OMP_NUM_THREADS` before running `mpirun` to avoid potential performance issues.
 
 Please refer to [hands-on guide](./hands_on.md) for more instructions.

docs/quick_start/hands_on.md

@@ -4,7 +4,7 @@
 
 ### A quick LCAO example
 
-ABACUS is well known for its support of LCAO (Linear Combination of Atomic Orbital) basis set in calculating periodic condensed matter systems, so it's a good choice to start from a LCAO example of self-consistent field (SCF) calculation. Here, FCC MgO has been chosen as a quick start example. The default name of a structure file in ABACUS is `STRU`. The `STRU` file for FCC MgO in a LCAO calculation is shown below:
+ABACUS is well known for its support of LCAO (Linear Combination of Atomic Orbital) basis set in calculating periodic condensed matter systems. It's a good choice to start from a LCAO example of self-consistent field (SCF) calculation. Here, FCC MgO has been chosen as a quick start example. The default name of a structure file in ABACUS is `STRU`. The `STRU` file for FCC MgO in a LCAO calculation is shown below:
 
 ```
 #This is the atom file containing all the information
@@ -48,11 +48,10 @@ Next, the `INPUT` file is required, which sets all key parameters to direct ABAC
 ```
 INPUT_PARAMETERS
 suffix                  MgO
-ntype                   2
 pseudo_dir              ./
 orbital_dir		./
 ecutwfc                 100             # Rydberg
-scf_thr                 1e-4		# Rydberg
+scf_thr                 1e-6		    # SCF criterion
 basis_type              lcao            
 calculation             scf		# this is the key parameter telling abacus to do a scf calculation
 ```
@@ -71,7 +70,7 @@ Gamma
 After all the above input files have been set, one should be able to run the first quick example. The simplest way is to use the command line, e.g.:
 
 ```
-mpirun -np 2 abacus
+OMP_NUM_THREADS=1 mpirun -np 2 abacus
 ```
 
 The main output information is stored in the file `OUT.MgO/running_scf.log`, which starts with
@@ -138,10 +137,9 @@ The `INPUT` file follows as:
 ```
 INPUT_PARAMETERS
 suffix                  MgO
-ntype                   2
 pseudo_dir              ./
 ecutwfc                 100             # Rydberg
-scf_thr                 1e-4		# Rydberg
+scf_thr                 1e-6		    # SCF criterion
 basis_type              pw              # changes the type of basis set
 calculation             scf		# this is the key parameter telling abacus to do a scf calculation
 ```
@@ -201,12 +199,11 @@ The `INPUT` is provided as follows:
 ```
 INPUT_PARAMETERS
 suffix                  MgO
-ntype                   2
 nelec                   0.0
 pseudo_dir              ./
 orbital_dir             ./
 ecutwfc                 100             # Rydberg
-scf_thr                 1e-4		# Rydberg
+scf_thr                 1e-6		# SCF criterion
 basis_type              lcao 
 calculation             cell-relax	# this is the key parameter telling abacus to do a optimization calculation
 force_thr_ev		0.01		# the threshold of the force convergence, in unit of eV/Angstrom
@@ -223,11 +220,10 @@ The `INPUT` is provided as follows:
 ```
 INPUT_PARAMETERS
 suffix                  MgO
-ntype                   2
 nelec                   0.0
 pseudo_dir              ./
 ecutwfc                 100             # Rydberg
-scf_thr                 1e-4		# Rydberg
+scf_thr                 1e-6		# SCF criterion
 basis_type              pw
 calculation             cell-relax	# this is the key parameter telling abacus to do a optimization calculation
 force_thr_ev		0.01		# the threshold of the force convergence, in unit of eV/Angstrom
@@ -236,4 +232,4 @@ relax_nmax		100		# the maximal number of ionic iteration steps
 out_stru		1
 ```
 
-Use the same `KPT`, `STRU`, and pseudopotential files as in the above SCF-PW examples. The final optimized structure can be found in `STRU_NOW.cif` and `OUT.MgO/running_cell-relax.log`.
+Use the same `KPT`, `STRU`, and pseudopotential files as in the above SCF-PW examples. The final optimized structure can be found in `STRU_NOW.cif` and `STRU_ION_D` with different format.