Welcome to MRChem’s documentation!

MRChem is a numerical real-space code for molecular electronic structure calculations within the self-consistent field (SCF) approximations of quantum chemistry (Hartree-Fock and Density Functional Theory). The code is divided in two main parts: the MultiResolution Computation Program Package (MRCPP), which is a general purpose numerical mathematics library based on multiresolution analysis and the multiwavelet basis which provide low-scaling algorithms as well as rigorous error control in numerical computations, and the MultiResolution Chemistry (MRChem) program that uses the functionalities of MRCPP for computational chemistry applications.

The code is being developed at the Hylleraas Centre for Quantum Molecular Sciences at UiT - The Arctic University of Norway.

We are currently in the process of rewriting the code and making it publicly available, and the latest version (with limited functionality) can be found on GitHub. This is not a stable version, expect major changes in the future.

Features as of September 2018:

  • Wave functions:
    • Kohn-Sham DFT
      • Spin-polarized
      • Spin-unpolarized
      • LDA, GGA and hybrid functionals
    • Hartree-Fock
      • Restricted closed-shell
      • Unrestricted
  • Properties:
    • Ground state energy
    • Dipole moment
    • Explicit electric field
  • Parallel implementation:
    • Shared memory (OpenMP): ~20 cores
    • Distributed memory (MPI): ~50 cores
    • Hybrid scheme (MPI + OpenMP): ~500 cores
  • Current limitations on a single high-memory compute node (~1TB):
    • nano-Hartree accuracy: ~10 orbitals
    • micro-Hartree accuracy: ~50 orbitals
    • milli-Hartree accuracy: ~100 orbitals

Upcoming features:

  • Wave functions:
    • Meta-GGAs
  • Properties:
    • Quadrupole moment
    • Polarizability
    • Hyperpolarizability
    • Optical rotation
    • Magnetizability
    • NMR shielding constant
    • Spin-spin coupling constant
    • Hyperfine coupling constant
    • Magnetically induced currents
    • Geometry optimization
  • Parallelization:
    • Improved performance
    • Larger molecular systems
    • Weak scaling up to thousands of cores