Update publications and ASE links in documentation (#1147)

Author: mfherbst

README.release_notes

@@ -9,3 +9,5 @@ Note that this release increases the minor version and contains a number of brea
 - The `kgrid_from_maximal_spacing` and `kgrid_from_minimal_n_kpoints` functions are now depreacted and will be removed. Instead all places in DFTK accepting an explicit `kgrid` now also accept values `KgridDensity` and `KgridMinimalNumber`, which achieve the same behaviour: a kgrid of at least the given density or at least the given total number of reducible k-points. For example to construct a PlaneWaveBasis with a k-point density of `0.2` per bohr, use `PlaneWaveBasis(model; kgrid=KgridDensity(0.2/u"bohr"))`. The actual number of k-points is then determined by looking at the atomistic system contained in the `model`. This change is done, such that `DFTKCalculator` objects can be constructed using `KgridDensity`, which will make the number of k-points adapt automatically to the structure on which the DFT calculation is invoked.
 
 - The `kshift` argument in `PlaneWaveBasis` is now deprecated. Use the `MonkhorstPack` data structure to request a shifted kgrid in DFTK.
+
+- `plot_bandstructure(basis)` no longer works. Instead first compute the bands along a k-line using `bands = compute_bands(basis)` then call `plot_bandstructure(bands)` afterwards.

docs/src/ecosystem/atomistic_simulation_environment.md

@@ -1,6 +1,6 @@
 # Atomistic simulation environment (ASE)
 
-The [atomistic simulation environment](https://wiki.fysik.dtu.dk/ase/index.html),
+The [atomistic simulation environment](https://ase-lib.org/).
 or ASE for short,
 is a popular Python package to simplify the process of setting up,
 running and analysing results from atomistic simulations across different simulation codes.

docs/src/ecosystem/atomscalculators.jl

@@ -3,7 +3,7 @@
 # [AtomsCalculators.jl](https://github.com/JuliaMolSim/AtomsCalculators.jl) is an interface
 # for doing standard computations (energies, forces, stresses, hessians) on atomistic
 # structures. It is very much inspired by the calculator objects in the
-# [atomistic simulation environment](https://wiki.fysik.dtu.dk/ase/index.html).
+# [atomistic simulation environment](https://ase-lib.org/).
 #
 # DFTK by default ships a datastructure called a [`DFTKCalculator`](@ref),
 # which implements the AtomsCalculators interface. A `DFTKCalculator`

docs/src/guide/tutorial.jl

@@ -62,9 +62,13 @@ positions = [ones(3)/8, -ones(3)/8]
 
 ## 2. Select model and basis
 model = model_DFT(lattice, atoms, positions; functionals=LDA())
-kgrid = [4, 4, 4]     # k-point grid (Regular Monkhorst-Pack grid)
+
+kgrid = KgridSpacing(0.3 / u"bohr")  # Regular k-point grid (Monkhorst-Pack grid)
+##                                      with spacing 0.3/bohr between k-points
+## kgrid = [4, 4, 4]                    Alternative: Number of k-points per dimension
 Ecut = 7              # kinetic energy cutoff
 ## Ecut = 190.5u"eV"  # Could also use eV or other energy-compatible units
+
 basis = PlaneWaveBasis(model; Ecut, kgrid)
 ## Note the implicit passing of keyword arguments here:
 ## this is equivalent to PlaneWaveBasis(model; Ecut=Ecut, kgrid=kgrid)
@@ -107,15 +111,19 @@ plot(x, scfres.ρ[:, 1, 1, 1], label="", xlabel="x", ylabel="ρ", marker=2)
 # We can get the Cartesian forces (in Hartree / Bohr):
 compute_forces_cart(scfres)
 # As expected, they are numerically zero in this highly symmetric configuration.
-# We could also compute a band structure,
-plot_bandstructure(scfres; kline_density=10)
-# or plot a density of states, for which we increase the kgrid a bit
-# to get smoother plots:
-bands = compute_bands(scfres, MonkhorstPack(6, 6, 6))
-plot_dos(bands; temperature=1e-3, smearing=Smearing.FermiDirac())
-# Note that directly employing the `scfres` also works, but the results
-# are much cruder:
+# We could also compute a band structure: we compute the bands along
+# a k-point line (determined automatically) and plot the result:
+bands1 = compute_bands(scfres; kline_density=10)
+plot_bandstructure(bands1)
+# Next we want to plot a density of states.
+# We can use the `scfres` directly, but the resulting DOS is quite sharp:
 plot_dos(scfres; temperature=1e-3, smearing=Smearing.FermiDirac())
+# To get a better result we first increase the kgrid to get a better
+# discretisation of the Brillouin zone, then re-do the plot:
+bands2 = compute_bands(scfres, MonkhorstPack(6, 6, 6))
+plot_dos(bands2; temperature=1e-3, smearing=Smearing.FermiDirac())
+# Note, that some other codes would refer to the functionality
+# we provide with compute_bands` as "performing a NSCF calculation".
 
 # !!! info "Where to go from here"
 #     - **Background on DFT:**

docs/src/publications.md

@@ -20,7 +20,11 @@ The current DFTK reference paper to cite is
 
 Additionally the following publications describe DFTK or one of its algorithms:
 
-- M. Herbst, B. Sun.
+- N. F. Schmitz, B. Ploumhans and M. F. Herbst.
+  [*Algorithmic differentiation for plane-wave DFT: materials design, error control and learning model parameters.*](https://arxiv.org/abs/2509.07785) (2025).
+  ([Supplementary material and computational scripts](https://github.com/niklasschmitz/ad-dfpt)).
+
+- M. F. Herbst, B. Sun.
   [*Efficient Krylov methods for linear response in plane-wave electronic structure calculations.*](https://arxiv.org/abs/2505.02319) (2025).
   ([Supplementary material and computational scripts](https://github.com/bonans/inexact_Krylov_response)).
 
@@ -57,6 +61,9 @@ Additionally the following publications describe DFTK or one of its algorithms:
 The following publications report research employing DFTK as a core component.
 Feel free to drop us a line if you want your work to be added here.
 
+- D. Petersheim, J.-F. Pietschmann, J. Püschel, K. Ruess.
+  [*Neural Network Acceleration of Iterative Methods for Nonlinear Schrödinger Eigenvalue Problems*](https://arxiv.org/abs/2507.16349) (2025).
+
 - A. Levitt, D. Lundholm, N. Rougerie.
   [*Magnetic Thomas-Fermi theory for 2D abelian anyons*](https://arxiv.org/abs/2504.13481) (2025).
 

docs/src/tricks/gpu.jl

@@ -38,10 +38,10 @@ nothing  # hide
 #
 # **Nvidia GPUs.**
 # Supported via [CUDA.jl](https://github.com/JuliaGPU/CUDA.jl).
-# Right now `Libxc` only supports CUDA 11,
-# so we need to explicitly request the 11.8 CUDA runtime:
+# If you install the CUDA package, all required Nvidia cuda libraries
+# will be automatically downloaded. So literally, the only thing
+# you have to do is:
 using CUDA
-CUDA.set_runtime_version!(v"11.8")  # Note: This requires a restart of Julia
 architecture = DFTK.GPU(CuArray)
 
 # **AMD GPUs.** Supported via [AMDGPU.jl](https://github.com/JuliaGPU/AMDGPU.jl).
@@ -71,8 +71,8 @@ scfres = self_consistent_field(basis; tol=1e-6)
 compute_forces(scfres)
 
 # !!! warning "GPU performance"
-#     Our current (February 2025) benchmarks show DFTK to have reasonable performance
-#     on Nvidia / CUDA GPUs with a 50-fold to 100-fold speed-up over single-threaded
+#     Our current (May 2025) benchmarks show DFTK to have reasonable performance
+#     on Nvidia / CUDA GPUs with up to a 100-fold speed-up over single-threaded
 #     CPU execution. However, support on AMD GPUs has been less benchmarked and
-#     there are likely rough edges. Overall this feature is relatively new
-#     and we appreciate any experience reports or bug reports.
+#     there are likely rough edges. Since GPU support in DFTK is relatively new
+#     we appreciate any experience reports or bug reports.