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Hessian and Frequencies

Source access and public downloads

Repository paths identify files in the licensed engine source; they are not public downloads. For freely downloadable .oqp inputs and results, see Worked Examples.

Hessian workflows use input.runtype=hess and are controlled by hess. OpenQP supports native analytical Hessians for supported HF/DFT ground-state cases and numerical Hessians for broader workflows. The default [hess] type=auto selects the analytical Hessian wherever it applies and the numerical one otherwise; see hess.

Frequency, IR, Raman, and thermochemistry analysis are built from Hessian data when the selected workflow produces the required derivatives.

The generated .hess.json and .freq.molden files contain portable normal modes and, for supported bases, the SCF molecular orbitals needed to view MO surfaces and vibrational animation together. See Orbital and Vibrational Output.

In Python scripts, start from a compact HF, DFT, or MRSF-TDDFT theory setup and then select the Hessian workflow with job.workflow.hessian(...).

Analytical HF/DFT Hessian

.oqp:

dft/bhhlyp/6-31g* hess(S0,type=analytical,clean=true)
geom="h2o.xyz"

Python:

from oqp.openqp import OpenQP

job = OpenQP("h2o_dft_hess", silent=1)
job.molecule(geometry="water", charge=0, multiplicity=1)
job.theory.dft(functional="bhhlyp", basis="6-31g*")
job.workflow.hessian(type="analytical", state=0, clean=True)

mol = job.run()
hessian = mol.get_hess()

Canonical .oqp input:

rks/bhhlyp/6-31g* hess(S0,type=analytical,clean=true)
geom="molecule.xyz"

Runnable .oqp: examples/HESS/H2O_RHF-DFT_ANA_HESS.oqp.

Numerical HF/DFT Hessian

Set type=numerical to force the finite-difference path. Without type, auto uses the analytical Hessian for ground-state HF/DFT.

.oqp:

dft/bhhlyp/6-31g* hess(S0,clean=true)
geom="h2o.xyz"

Python:

from oqp.openqp import OpenQP

job = OpenQP("h2o_dft_num_hess", silent=1)
job.molecule(geometry="water", charge=0, multiplicity=1)
job.theory.dft(functional="bhhlyp", basis="6-31g*")
job.workflow.hessian(state=0, clean=True)
mol = job.run()

Canonical .oqp input:

rks/bhhlyp/6-31g* hess(S0,clean=true)
geom="molecule.xyz"

For a symmetric molecule, symmetry_unique=True can reduce the numerical finite-difference work to one displaced atom per symmetry-equivalent atom orbit. It is an opt-in feature and falls back to the full displacement set with an explanatory note whenever the current geometry or tolerance does not support a complete symmetry reconstruction.

Runnable .oqp: examples/HESS/H2O_RHF-DFT_NUM_HESS.oqp.

Numerical MRSF-TDDFT Hessian

MRSF-TDDFT Hessians use the numerical path in the documented examples. The MRSF state numbering follows the MRSF target-state list; state=1 is the lowest MRSF target state, which can be the multiconfigurational ground state.

.oqp:

mrsf(nstate=2)/bhhlyp/6-31g* hess(S0,clean=true)
geom="h2o.xyz"

Python:

from oqp.openqp import OpenQP

job = OpenQP("h2o_mrsf_hess", silent=1)
job.molecule(geometry="water", charge=0)
job.theory.mrsf(functional="bhhlyp", basis="6-31g*", nstate=2)
job.workflow.hessian(state=1, clean=True)

mol = job.run()

Canonical .oqp input:

mrsf(nstate=2)/bhhlyp/6-31g* hess(S0,clean=true)
geom="molecule.xyz"

Runnable .oqp: examples/HESS/H2O_BHHLYP-MRSFTDDFT_NUM_HESS.oqp.

Notes

  • HF/DFT ground-state Hessians use state=0.
  • TDHF/TDDFT Hessian target states use positive excited-state indices.
  • SF-TDDFT and MRSF-TDDFT use spin-flip/MRSF target-state ordering, where state 1 is the lowest target state.
  • hess.restart=True can continue a numerical Hessian workflow where the corresponding temporary files are available.
  • hess.read=True accepts only a current versioned .hess.json whose electronic-model configuration, state, atoms, geometry, and isotopic masses match the present job. Referenced file contents and the OpenQP binary are not content-fingerprinted, so regenerate the sidecar after changing either one. Unsigned legacy sidecars must be regenerated with read=False.
  • hess.clean=True removes temporary Hessian files where supported.

Scientific references

Vibrational and magnetic properties; Geometry optimization and reaction paths.