DFTK: The Density-functional toolkit

DFTK v0.6.0

Diff since v0.5.15

Note that this release increases the minor version and contains a number of breaking changes:

• The self_consistent_field and potential_mixing SCF functions now check convergence in the density by default. This means that self_consistent_field(basis; tol=1e-6) now converges until the change in density between subsequent steps is below 1e-6. Before it used to converge until the change in energy was less than tol. To recover the old behaviour use self_consistent_field(basis; is_converged=DFTK.ScfConvergenceEnergy(tol)). (#800)

• The load_lattice, load_atoms and load_positions functions are now deprecated and will be removed in DFTK 0.6.1. Users are advised to use AtomsIO for the purpose of loading structures from external files. See https://docs.dftk.org/v0.6/examples/atomsbase/ and https://github.com/mfherbst/AtomsIO.jl for examples.

• Instead of using NLSolve's Anderson acceleration we have switched to a built-in implementation, which we found more stable in practice. (#791) The NLSolve-been approach has been removed completely.

• The deprecated G_to_r and r_to_G functions for FFTs have now been removed in favour of ifft, fft and similar. (#804)

• The deprecated n_bands and n_ep_extra arguments from self_consistent_field have now been removed. (#804)

Closed issues:

• Struct for atoms (#118)
• GPU discussion (#350)
• SCF default tolerance should be on the density (#780)
• Run GPU CI only after activation (#803)

Merged pull requests:

• Bugfix for computations of δψ and supercells (#775) (@epolack)
• Switch default scf solver to builtin Anderson (#791) (@epolack)
• Add developper documentation for GPU computations (#793) (@GVigne)
• Correct PW parameterization comment (#795) (@epolack)
• Add GPU CI via gitlab (#796) (@mfherbst)
• Switch to density tolerance by default (#800) (@mfherbst)
• Make cigpu badge a link to ci pipelines in gitlab (#801) (@carstenbauer)
• Rely on AtomsIO for structure parsing (#802) (@mfherbst)
• Remove deprecated features (#804) (@mfherbst)