{ "cells": [ { "cell_type": "markdown", "source": [ "# Performing a convergence study\n", "\n", "This example shows how to perform a convergence study to find an appropriate\n", "discretisation parameters for the Brillouin zone (`kgrid`) and kinetic energy\n", "cutoff (`Ecut`), such that the simulation results are converged to a desired\n", "accuracy tolerance.\n", "\n", "Such a convergence study is generally performed by starting with a\n", "reasonable base line value for `kgrid` and `Ecut` and then increasing these\n", "parameters (i.e. using finer discretisations) until a desired property (such\n", "as the energy) changes less than the tolerance.\n", "\n", "This procedure must be performed for each discretisation parameter. Beyond\n", "the `Ecut` and the `kgrid` also convergence in the smearing temperature or\n", "other numerical parameters should be checked. For simplicity we will neglect\n", "this aspect in this example and concentrate on `Ecut` and `kgrid`. Moreover\n", "we will restrict ourselves to using the same number of $k$-points in each\n", "dimension of the Brillouin zone.\n", "\n", "As the objective of this study we consider bulk platinum. For running the SCF\n", "conveniently we define a function:" ], "metadata": {} }, { "outputs": [], "cell_type": "code", "source": [ "using DFTK\n", "using LinearAlgebra\n", "using Statistics\n", "using PseudoPotentialData\n", "\n", "function run_scf(; a=5.0, Ecut, nkpt, tol)\n", " pseudopotentials = PseudoFamily(\"cp2k.nc.sr.lda.v0_1.largecore.gth\")\n", " atoms = [ElementPsp(:Pt, pseudopotentials)]\n", " position = [zeros(3)]\n", " lattice = a * Matrix(I, 3, 3)\n", "\n", " model = model_DFT(lattice, atoms, position;\n", " functionals=LDA(), temperature=1e-2)\n", " basis = PlaneWaveBasis(model; Ecut, kgrid=(nkpt, nkpt, nkpt))\n", " println(\"nkpt = $nkpt Ecut = $Ecut\")\n", " self_consistent_field(basis; is_converged=ScfConvergenceEnergy(tol))\n", "end;" ], "metadata": {}, "execution_count": 1 }, { "cell_type": "markdown", "source": [ "Moreover we define some parameters. To make the calculations run fast for the\n", "automatic generation of this documentation we target only a convergence to\n", "1e-2. In practice smaller tolerances (and thus larger upper bounds for\n", "`nkpts` and `Ecuts` are likely needed." ], "metadata": {} }, { "outputs": [], "cell_type": "code", "source": [ "tol = 1e-2 # Tolerance to which we target to converge\n", "nkpts = 1:7 # K-point range checked for convergence\n", "Ecuts = 10:2:24; # Energy cutoff range checked for convergence" ], "metadata": {}, "execution_count": 2 }, { "cell_type": "markdown", "source": [ "As the first step we converge in the number of $k$-points employed in each\n", "dimension of the Brillouin zone …" ], "metadata": {} }, { "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "nkpt = 1 Ecut = 17.0\n", "n Energy log10(ΔE) log10(Δρ) Diag Δtime\n", "--- --------------- --------- --------- ---- ------\n", " 1 -26.49622281284 -0.22 8.0 110ms\n", " 2 -26.59233656940 -1.02 -0.63 2.0 158ms\n", " 3 -26.61290867394 -1.69 -1.41 2.0 33.9ms\n", " 4 -26.61326615223 -3.45 -2.13 2.0 31.5ms\n", "nkpt = 2 Ecut = 17.0\n", "n Energy log10(ΔE) log10(Δρ) Diag Δtime\n", "--- --------------- --------- --------- ---- ------\n", " 1 -25.79261308699 -0.09 5.2 86.2ms\n", " 2 -26.23307917121 -0.36 -0.70 2.0 56.2ms\n", " 3 -26.23823144216 -2.29 -1.32 2.0 68.0ms\n", " 4 -26.23848096839 -3.60 -2.32 1.0 48.0ms\n", "nkpt = 3 Ecut = 17.0\n", "n Energy log10(ΔE) log10(Δρ) Diag Δtime\n", "--- --------------- --------- --------- ---- ------\n", " 1 -25.78404837737 -0.09 5.0 79.2ms\n", " 2 -26.24025048195 -0.34 -0.80 2.0 57.1ms\n", " 3 -26.25080534270 -1.98 -1.65 2.2 61.3ms\n", " 4 -26.25104937780 -3.61 -2.22 1.0 46.1ms\n", "nkpt = 4 Ecut = 17.0\n", "n Energy log10(ΔE) log10(Δρ) Diag Δtime\n", "--- --------------- --------- --------- ---- ------\n", " 1 -25.91216018156 -0.11 5.2 186ms\n", " 2 -26.29428038427 -0.42 -0.77 2.0 116ms\n", " 3 -26.30833081937 -1.85 -1.74 2.2 147ms\n", " 4 -26.30842515507 -4.03 -2.66 1.0 91.4ms\n", "nkpt = 5 Ecut = 17.0\n", "n Energy log10(ΔE) log10(Δρ) Diag Δtime\n", "--- --------------- --------- --------- ---- ------\n", " 1 -25.90303612261 -0.11 4.0 154ms\n", " 2 -26.26717129897 -0.44 -0.72 2.0 115ms\n", " 3 -26.28543617491 -1.74 -1.64 2.1 156ms\n", " 4 -26.28571178256 -3.56 -2.28 1.0 346ms\n", "nkpt = 6 Ecut = 17.0\n", "n Energy log10(ΔE) log10(Δρ) Diag Δtime\n", "--- --------------- --------- --------- ---- ------\n", " 1 -25.87574090843 -0.10 5.0 319ms\n", " 2 -26.27389455410 -0.40 -0.77 1.9 208ms\n", " 3 -26.28808182713 -1.85 -1.71 2.2 228ms\n", " 4 -26.28818803673 -3.97 -2.62 1.0 162ms\n", "nkpt = 7 Ecut = 17.0\n", "n Energy log10(ΔE) log10(Δρ) Diag Δtime\n", "--- --------------- --------- --------- ---- ------\n", " 1 -25.89625074297 -0.11 3.5 249ms\n", " 2 -26.27883476796 -0.42 -0.75 2.0 187ms\n", " 3 -26.29413133618 -1.82 -1.74 2.1 206ms\n", " 4 -26.29420603226 -4.13 -2.65 1.0 145ms\n" ] }, { "output_type": "execute_result", "data": { "text/plain": "5" }, "metadata": {}, "execution_count": 3 } ], "cell_type": "code", "source": [ "function converge_kgrid(nkpts; Ecut, tol)\n", " energies = [run_scf(; nkpt, tol=tol/10, Ecut).energies.total for nkpt in nkpts]\n", " errors = abs.(energies[1:end-1] .- energies[end])\n", " iconv = findfirst(errors .< tol)\n", " (; nkpts=nkpts[1:end-1], errors, nkpt_conv=nkpts[iconv])\n", "end\n", "result = converge_kgrid(nkpts; Ecut=mean(Ecuts), tol)\n", "nkpt_conv = result.nkpt_conv" ], "metadata": {}, "execution_count": 3 }, { "cell_type": "markdown", "source": [ "… and plot the obtained convergence:" ], "metadata": {} }, { "outputs": [ { "output_type": "execute_result", "data": { "text/plain": "Plot{Plots.GRBackend() n=1}", "image/png": 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suggested $k$-point grid." ], "metadata": {} }, { "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "nkpt = 5 Ecut = 10\n", "n Energy log10(ΔE) log10(Δρ) Diag Δtime\n", "--- --------------- --------- --------- ---- ------\n", " 1 -25.57872512129 -0.16 3.8 71.9ms\n", " 2 -25.77769551126 -0.70 -0.77 1.9 62.2ms\n", " 3 -25.78625859012 -2.07 -1.84 2.0 55.0ms\n", " 4 -25.78631683642 -4.23 -2.92 1.0 39.8ms\n", "nkpt = 5 Ecut = 12\n", "n Energy log10(ΔE) log10(Δρ) Diag Δtime\n", "--- --------------- --------- --------- ---- ------\n", " 1 -25.78654140009 -0.12 3.5 72.4ms\n", " 2 -26.07741828524 -0.54 -0.72 2.0 51.7ms\n", " 3 -26.09341840274 -1.80 -1.68 2.1 58.5ms\n", " 4 -26.09373823994 -3.50 -2.34 1.0 47.6ms\n", " 5 -26.09375339053 -4.82 -2.69 1.2 44.1ms\n", "nkpt = 5 Ecut = 14\n", "n Energy log10(ΔE) log10(Δρ) Diag Δtime\n", "--- --------------- --------- --------- ---- ------\n", " 1 -25.86811691876 -0.11 3.8 57.8ms\n", " 2 -26.20928967215 -0.47 -0.72 2.0 43.6ms\n", " 3 -26.22669884375 -1.76 -1.65 2.1 46.4ms\n", " 4 -26.22700683213 -3.51 -2.29 1.0 30.6ms\n", " 5 -26.22702540241 -4.73 -2.67 1.1 33.5ms\n", "nkpt = 5 Ecut = 16\n", "n Energy log10(ΔE) log10(Δρ) Diag Δtime\n", "--- --------------- --------- --------- ---- ------\n", " 1 -25.89739755582 -0.11 4.0 140ms\n", " 2 -26.25750588653 -0.44 -0.72 2.0 107ms\n", " 3 -26.27559557448 -1.74 -1.65 2.1 114ms\n", " 4 -26.27587559648 -3.55 -2.29 1.0 84.1ms\n", " 5 -26.27589251535 -4.77 -2.69 1.0 83.3ms\n", "nkpt = 5 Ecut = 18\n", "n Energy log10(ΔE) log10(Δρ) Diag Δtime\n", "--- --------------- --------- --------- ---- ------\n", " 1 -25.90595596209 -0.11 4.1 143ms\n", " 2 -26.27276495544 -0.44 -0.72 2.0 106ms\n", " 3 -26.29101700489 -1.74 -1.64 2.2 126ms\n", " 4 -26.29128601834 -3.57 -2.29 1.0 82.4ms\n", " 5 -26.29130327946 -4.76 -2.69 1.0 112ms\n", "nkpt = 5 Ecut = 20\n", "n Energy log10(ΔE) log10(Δρ) Diag Δtime\n", "--- --------------- --------- --------- ---- ------\n", " 1 -25.90859517574 -0.11 4.0 142ms\n", " 2 -26.27703098050 -0.43 -0.72 2.0 104ms\n", " 3 -26.29532779943 -1.74 -1.64 2.3 117ms\n", " 4 -26.29558675868 -3.59 -2.28 1.0 88.4ms\n", " 5 -26.29560492317 -4.74 -2.70 1.0 117ms\n", "nkpt = 5 Ecut = 22\n", "n Energy log10(ΔE) log10(Δρ) Diag Δtime\n", "--- --------------- --------- --------- ---- ------\n", " 1 -25.90925442621 -0.11 4.0 160ms\n", " 2 -26.27822851988 -0.43 -0.73 2.0 119ms\n", " 3 -26.29617887456 -1.75 -1.65 2.2 132ms\n", " 4 -26.29641976381 -3.62 -2.31 1.0 89.9ms\n", " 5 -26.29643485241 -4.82 -2.70 1.2 98.6ms\n", "nkpt = 5 Ecut = 24\n", "n Energy log10(ΔE) log10(Δρ) Diag Δtime\n", "--- --------------- --------- --------- ---- ------\n", " 1 -25.90938405562 -0.11 4.1 143ms\n", " 2 -26.27826346980 -0.43 -0.73 2.0 113ms\n", " 3 -26.29625175155 -1.75 -1.64 2.2 114ms\n", " 4 -26.29649519193 -3.61 -2.30 1.0 82.1ms\n", " 5 -26.29651079827 -4.81 -2.70 1.2 88.1ms\n" ] }, { "output_type": "execute_result", "data": { "text/plain": "18" }, "metadata": {}, "execution_count": 5 } ], "cell_type": "code", "source": [ "function converge_Ecut(Ecuts; nkpt, tol)\n", " energies = [run_scf(; nkpt, tol=tol/100, Ecut).energies.total for Ecut in Ecuts]\n", " errors = abs.(energies[1:end-1] .- energies[end])\n", " iconv = findfirst(errors .< tol)\n", " (; Ecuts=Ecuts[1:end-1], errors, Ecut_conv=Ecuts[iconv])\n", "end\n", "result = converge_Ecut(Ecuts; nkpt=nkpt_conv, tol)\n", "Ecut_conv = result.Ecut_conv" ], "metadata": {}, "execution_count": 5 }, { "cell_type": "markdown", "source": [ "… and plot it:" ], "metadata": {} }, { "outputs": [ { "output_type": "execute_result", "data": { "text/plain": "Plot{Plots.GRBackend() n=1}", "image/png": 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settings, namely …" ], "metadata": {} }, { "outputs": [], "cell_type": "code", "source": [ "tol = 1e-4 # Tolerance to which we target to converge\n", "nkpts = 1:20 # K-point range checked for convergence\n", "Ecuts = 20:1:50;" ], "metadata": {}, "execution_count": 7 }, { "cell_type": "markdown", "source": [ "…one obtains the following two plots for the convergence in `kpoints` and `Ecut`." ], "metadata": {} }, { "cell_type": "markdown", "source": [ "\n", "" ], "metadata": {} } ], "nbformat_minor": 3, "metadata": { "language_info": { "file_extension": ".jl", "mimetype": "application/julia", "name": "julia", "version": "1.11.4" }, "kernelspec": { "name": "julia-1.11", "display_name": "Julia 1.11.4", "language": "julia" } }, "nbformat": 4 }