pyscf/properties

Molecular and crystal electromagnetic properties

Python-based Simulations of Chemistry Framework

2024-09-23

• Stable release 2.7.0
• Changelog
• Documentation
• Installation
• Features

Installation

• Install stable release:

    pip install pyscf
  

• New features developed in recent years are available in the pyscf-forge package:

    pip install pyscf-forge
  

• Certain modules are maintained as extensions of PySCF, such as dispersion, dmrgscf, fciqmc, icmpspt, properties, semiempirical, shciscf ... (more on https://github.com/pyscf) can be installed using pip:

    pip install pyscf[all]
  

  An individual extension can be installed:

    pip install pyscf[dispersion]
  

• More details of custom installation can be found in installation manual

Citing PySCF

Base PySCF

The following paper should be cited in publications utilizing the PySCF program package:

Recent developments in the PySCF program package, Qiming Sun, Xing Zhang, Samragni Banerjee, Peng Bao, Marc Barbry, Nick S. Blunt, Nikolay A. Bogdanov, George H. Booth, Jia Chen, Zhi-Hao Cui, Janus J. Eriksen, Yang Gao, Sheng Guo, Jan Hermann, Matthew R. Hermes, Kevin Koh, Peter Koval, Susi Lehtola, Zhendong Li, Junzi Liu, Narbe Mardirossian, James D. McClain, Mario Motta, Bastien Mussard, Hung Q. Pham, Artem Pulkin, Wirawan Purwanto, Paul J. Robinson, Enrico Ronca, Elvira R. Sayfutyarova, Maximilian Scheurer, Henry F. Schurkus, James E. T. Smith, Chong Sun, Shi-Ning Sun, Shiv Upadhyay, Lucas K. Wagner, Xiao Wang, Alec White, James Daniel Whitfield, Mark J. Williamson, Sebastian Wouters, Jun Yang, Jason M. Yu, Tianyu Zhu, Timothy C. Berkelbach, Sandeep Sharma, Alexander Yu. Sokolov, and Garnet Kin-Lic Chan, J. Chem. Phys., 153, 024109 (2020). doi:10.1063/5.0006074

Density functional calculations

As PySCF does not implement density functionals, instead employing external libraries to handle their evaluation, these libraries should also be cited in publications employing PySCF for density functional calculations.

If your calculation employed Libxc, cite

Recent developments in libxc — A comprehensive library of functionals for density functional theory, Susi Lehtola, Conrad Steigemann, Micael J.T. Oliveira, and Miguel A.L. Marques, SoftwareX 7, 1 (2018). doi:10.1016/j.softx.2017.11.002

If your calculation employed XCFun, cite

Arbitrary-order density functional response theory from automatic differentiation, Ulf Ekström, Lucas Visscher, Radovan Bast, Andreas J. Thorvaldsen, and Kenneth Ruud, J. Chem. Theory Comput. 6, 1971 (2010). doi:10.1021/ct100117s

Bug reports and feature requests

Please submit tickets on the issues page.

properties's Issues

NMR example does not run

Dear devs,
I believe the example given in https://github.com/pyscf/properties/blob/master/examples/04-nmr.py does not run.
I get the following error, which to me indicates that the program refers to an old scipy version (the sym_pos option of the scipy.linalg.solve routine does not exist anymore and seems replaced by the assume_a="sym" option):

  File "/home/yannick/miniconda3/envs/envtmp/lib/python3.11/site-packages/pyscf/lib/linalg_helper.py", line 1465, in cho_solve
    return scipy.linalg.solve(a, b, sym_pos=True)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
TypeError: solve() got an unexpected keyword argument 'sym_pos'

The following compressed script reproduces the error:

script.zip
Please let me know if I am clear and if you need more data.

NMR does not run

Dear devs,
example does not run. I get the following error message:

Traceback (most recent call last):
  File "/home/yannick/script_erreur/./pyscf-properties/examples/04-nmr.py", line 18, in <module>
    nmr.RKS(mf).kernel()
  File "/home/yannick/script_erreur/pyscf-properties/pyscf/prop/nmr/rhf.py", line 287, in kernel
    return self.shielding(mo1)
  File "/home/yannick/script_erreur/pyscf-properties/pyscf/prop/nmr/rhf.py", line 297, in shielding
    self.mo10, self.mo_e10 = self.solve_mo1()
  File "/home/yannick/script_erreur/pyscf-properties/pyscf/prop/nmr/rks.py", line 151, in solve_mo1
    return rhf_nmr.solve_mo1(nmrobj, mo_energy, mo_coeff, mo_occ,
  File "/home/yannick/script_erreur/pyscf-properties/pyscf/prop/nmr/rhf.py", line 197, in solve_mo1
    h1 = lib.einsum('xpq,pi,qj->xij', nmrobj.get_fock(dm0),
  File "/home/yannick/script_erreur/pyscf-properties/pyscf/prop/nmr/rks.py", line 124, in get_fock
    h1 -= get_vxc_giao(ni, mol, mf.grids, mf.xc, dm0,
  File "/home/yannick/script_erreur/pyscf-properties/pyscf/prop/nmr/rks.py", line 57, in get_vxc_giao
    for ao, mask, weight, coords \
  File "/home/yannick/script_erreur/pyscf/pyscf/dft/numint.py", line 2673, in _block_loop
    assert blksize % BLKSIZE == 0
AssertionError

The attached file allows for the reproduction of this problem, provided that the necessary dependencies for pyscf are installed.
nmr_error.zip

Let me know if you need more info or if I did somethig wrong.
Yannick

About the implementation of SSC

Hi all,

I'm trying to understand how you implemented the SSC property, for example, for the restricted Hartree-Fock theory.
What is the theory you use to calculate it? Can you recommend me some papers that show the equations and methods that you use in the program (in addition to those of Helgaker et. al that is in the head of the header)?
For example, how do you use the CPHF method in this response?

Thank you very much for the help in advance,
Best regards

Daniel