Tahun lalu (2020), sehubungan dengan pandemi, kami mengadakan konferensi ilmiah online tentang kimia komputasi , dan kami membuat logo untuk itu, yang secara halus, biasa saja. Di bawah potongan adalah cerita tentang bagaimana kami memompanya untuk konferensi tahun (2021) ini menggunakan sejumlah kecil mekanika kuantum, metode Monte Carlo, Python dan Gnuplot.
Sedikit latar belakang
2020, virus korona mendapatkan momentum, pembatasan diberlakukan, dan untuk mempertahankan tingkat diskusi ilmiah, meningkatkan kerja sama ilmiah di antara ilmuwan berbahasa Rusia yang tersebar di seluruh dunia, dan untuk kebaikan lainnya, kami menyelenggarakan simposium mini tentang kimia komputasi online .
Tapi apa konferensi tanpa logo? Dan setelah mengumpulkan semua kemungkinan artistik (dari kata "buruk") dari panitia penyelenggara konferensi, sebuah logo dibuat di Inkscape :
. , d- . - Firefly, , , , . , . : ψ, , . , . to Pimp My Ride Logo.
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- ψ ( ), (x,y,z)=r. . r0, r1, r2, ..., rN, N - . ψn=ψ(rn). , Python :
rn rtrial, (xn,yn,zn) rn -δ +δ, δ — , ,
pacc = |ψtrial|2/|ψn|2, q 0 1, pacc q: pacc<q, (rn+1=rn), , (rn+1=rtrial),
, , -0.1⋅δ +0.1⋅δ.
, , . 10% , , , . .
. d- :
r — r, , . , . , , :
, , .
Python
import numpy as np
import random as rnd
DXYZ = 4.0
dxyz = 0.1*DXYZ
def getWFN(R, a=0.05, b=0.9, R0=1.0):
return (a*(R[1])**3 + b*R[0]*R[1])*np.exp(-np.sqrt(np.dot(R,R))/R0)
Npts = 40000
N2ignore = Npts/10
outf = open("wfn.dat", "w")
outfp = open("wfn_pos.dat", "w")
outfn = open("wfn_neg.dat", "w")
genNewXYZ = lambda xyz, shift: xyz + np.array([rnd.uniform(-shift,shift) for q in range(0,3)])
XYZ = np.array([1.0,1.0,0.0])
Psi = getWFN(XYZ, DXYZ)
for i in range(0,Npts):
trialXYZ = genNewXYZ(XYZ, DXYZ)
trialPsi = getWFN(trialXYZ)
if i % N2ignore == 0:
print("step #%i" % (i))
Ptrial = rnd.random()
Ptest = trialPsi**2/Psi**2
Accepted = False
if Ptrial < Ptest:
Psi = trialPsi
XYZ = trialXYZ
Accepted = True
if i>N2ignore:
r2save = XYZ
if not Accepted:
r2save = genNewXYZ(XYZ, dxyz)
outf.write(" %15.10f %15.10f %15.10f %15.5e\n" % tuple(list(r2save)+[Psi]))
if Psi > 0.0:
outfp.write(" %15.10f %15.10f %15.10f %15.5e\n" % tuple(list(r2save)+[Psi]))
else:
outfn.write(" %15.10f %15.10f %15.10f %15.5e\n" % tuple(list(r2save)+[Psi]))
:
Python
import numpy as np
import random as rnd
DXYZ = 0.5
dxyz = 0.1*DXYZ
def getWFN(R, a=1.0, b=0.5, X0=0.2, Y0=0.5, Z0=0.2):
if R[1]<0.:
return (a*(R[1])**3 + b*R[1])*np.exp(-np.abs(R[0])/X0 - np.abs(R[1])/Y0 - np.abs(R[2])/Z0)
else:
return 0.0
Npts = 20000
N2ignore = Npts/10
outf = open("body.dat", "w")
genNewXYZ = lambda xyz, shift: xyz + np.array([rnd.uniform(-shift,shift) for q in range(0,3)])
XYZ = np.array([0.0,-0.2,0.0])
Psi = getWFN(XYZ, DXYZ)
for i in range(0,Npts):
trialXYZ = genNewXYZ(XYZ, DXYZ)
trialPsi = getWFN(trialXYZ)
if i % N2ignore == 0:
print("step #%i" % (i))
Ptrial = rnd.random()
Ptest = trialPsi**2/Psi**2
Accepted = False
if Ptrial < Ptest:
Psi = trialPsi
XYZ = trialXYZ
Accepted = True
if i>N2ignore:
r2save = XYZ
if not Accepted:
r2save = genNewXYZ(XYZ, dxyz)
outf.write(" %15.10f %15.10f %15.10f %15.5e\n" % tuple(list(r2save)+[Psi]))
, s-:
Python
import numpy as np
import random as rnd
DXYZ = 0.9
dxyz = 0.1*DXYZ
def getWFN(R, a=1.0, b=0.5, X0=0.3, Y0=0.5, Z0=0.3):
return np.exp(-np.abs(R[0])/X0 - np.abs(R[1])/Y0 - np.abs(R[2])/Z0)
Npts = 10000
N2ignore = Npts/10
outf = open("head.dat", "w")
genNewXYZ = lambda xyz, shift: xyz + np.array([rnd.uniform(-shift,shift) for q in range(0,3)])
XYZ = np.array([0.0,-0.2,0.0])
Psi = getWFN(XYZ, DXYZ)
for i in range(0,Npts):
trialXYZ = genNewXYZ(XYZ, DXYZ)
trialPsi = getWFN(trialXYZ)
if i % N2ignore == 0:
print("step #%i" % (i))
Ptrial = rnd.random()
Ptest = trialPsi**2/Psi**2
Accepted = False
if Ptrial < Ptest:
Psi = trialPsi
XYZ = trialXYZ
Accepted = True
if i>N2ignore:
r2save = XYZ
if not Accepted:
r2save = genNewXYZ(XYZ, dxyz)
outf.write(" %15.10f %15.10f %15.10f %15.5e\n" % tuple(list(r2save)+[Psi]))
, , :
Python
import numpy as np
import random as rnd
DXYZ = 0.9
dxyz = 0.1*DXYZ
def getWFN(R, a=1.0, b=0.5, X0=0.4, Y0=0.68, Z0=0.3):
if R[1]<0.:
return (a*(R[1])**3 + b*R[1])*np.exp(-np.abs(R[0])/X0 - np.abs(R[1])/Y0 - np.abs(R[2])/Z0)
else:
return 0.0
Npts = 1000
N2ignore = Npts/10
outf = open("body_fire.dat", "w")
genNewXYZ = lambda xyz, shift: xyz + np.array([rnd.uniform(-shift,shift) for q in range(0,3)])
XYZ = np.array([0.0,-0.2,0.0])
Psi = getWFN(XYZ, DXYZ)
for i in range(0,Npts):
trialXYZ = genNewXYZ(XYZ, DXYZ)
trialPsi = getWFN(trialXYZ)
if i % N2ignore == 0:
print("step #%i" % (i))
Ptrial = rnd.random()
Ptest = trialPsi**2/Psi**2
Accepted = False
if Ptrial < Ptest:
Psi = trialPsi
XYZ = trialXYZ
Accepted = True
if i>N2ignore:
r2save = XYZ
if not Accepted:
r2save = genNewXYZ(XYZ, dxyz)
outf.write(" %15.10f %15.10f %15.10f %15.5e\n" % tuple(list(r2save)+[Psi]))
(xn, yn, zn, ψn) n=0,1,2,..., . Gnuplot multiplot. (set view map). , : https://github.com/Gnuplotting/gnuplot-palettes.
inferno, — ylrd, . - : plasma, parula, — prgn.
Plasma — , - , . Parula , , ... , , , . prgn, : , , . Inkscape .
Gnuplot
#set terminal pngcairo size 1500,1500 transparent
set terminal pngcairo size 1500,1500 background rgb '#080045'
set output "ff_v2.png"
set multiplot
set view map
set size ratio 1
unset colorbox
unset border
unset key
unset xtics
unset ytics
XMax = 7.
set xrange [-XMax:XMax]
set yrange [-XMax:XMax]
set pm3d depthorder hidden3d 1
set hidden3d
set style fill transparent solid 0.35 noborder
set style circle radius 0.02
load 'prgn.pal'
#load 'plasma.pal'
#load 'parula.pal'
splot 'wfn_pos.dat' u 2:1:3:4 w p pt 7 ps 2 lc palette
splot 'wfn_neg.dat' u 2:1:3:4 w p pt 7 ps 2 lc palette
load 'inferno.pal'
splot 'body.dat' u 1:2:3:4 w l lc palette
splot 'head.dat' u 1:2:3:4 w l lc palette
load 'ylrd.pal'
splot 'body_fire.dat' u 1:2:3:(-$4) w l lw 3 lc palette
P.S.
, - , . , , YouTube .