Tutorials and learning paths

PyQED is broad, so the safest route is to start with one small, inspectable workflow and follow its linked guide, example, and test. The paths below do not imply that every combination of options is supported.

Quantum chemistry

  1. Run the native RHF Five-minute quickstart.

  2. Read Quantum Chemistry for molecule construction and solver families.

  3. Read Backends and Integral Representations before selecting dense, packed, RI, or factorized electron-repulsion data.

  4. Continue to MP2 and COMP2 or CASCI and CASSCF.

  5. Inspect examples/qchem/sa_casscf_factor.py and its corresponding focused tests before scaling the problem.

GW and response calculations are separate advanced paths; begin with GW and BSE or TDDFT and Ehrenfest Dynamics and use their documented conventions.

Grid and wavepacket dynamics

  1. Read the representation overview in Discrete Variable Representation.

  2. Run examples/dvr/fedvr_harmonic_oscillator.py. It prints computed eigenvalues beside the analytic harmonic-oscillator sequence.

  3. Compare grid families with examples/dvr/fedvr_vs_sine_quartic.py.

  4. Move to examples/dvr/gwp_sddvr_2d_independent_ho.py only after the one-dimensional smoke case is understood.

Nonadiabatic and geometric dynamics

  1. Read Geometric Quantum Dynamics and Nonadiabatic Molecular Dynamics.

  2. Start with examples/namd/ehrenfest.py or examples/namd/ldrfg_avoided_crossing.py.

  3. Treat ab initio and sparse-grid scripts as research workflows: inspect their optional dependencies, cached inputs, grid convergence, and output paths before execution.

Open systems and spectroscopy

  1. Read Open quantum dynamics and HEOM and structured baths for open-system conventions.

  2. Use examples/heom.py as an entry point, then inspect focused tests for the exact solver path being used.

  3. For spectroscopy, read Nonlinear molecular spectroscopy and inspect examples/signals/absorption.py before the larger examples/2DES.py workflow.

Floquet and light–matter models

Read Floquet and Polariton, then inspect examples/floquet/two_level_system.py and examples/floquet/RiceMele.py. These are model-specific entry points; verify units and gauge conventions before adapting them.

How to turn an example into research evidence

For every path:

  • pin the PyQED release or Git commit;

  • keep the exact input and random seed;

  • record units, basis/grid, solver tolerances, dependencies, and threads;

  • establish convergence with respect to the relevant numerical controls; and

  • use the Benchmarks and validation manifest for results presented as validation or performance evidence.