Dear Sir,
Thanks for the tips. As you told, I have tried in other way also but I am
getting the same result which are very tedious. I don't know where is fault.
Now the code looks like
*import kwantimport scipy.sparse.linalg as slaimport matplotlib.pyplot as
pltimport tinyarrayimport numpy as npfrom numpy import cos, sin, piimport
cmathfrom cmath import expsigma_0 = tinyarray.array([[1, 0], [0,
1]])sigma_x = tinyarray.array([[0, 1], [1, 0]])sigma_y =
tinyarray.array([[0, -1j], [1j, 0]])sigma_z = tinyarray.array([[1, 0], [0,
-1]])def make_system(a=1, L=30, W=10, H=10, t=1.0, t_x=1.0, t_y=1.0,
t_z=1.0, lamda=0.1, beta=1.05): def onsite(site): return (t_z *
cos(beta) + 2 * t) * sigma_z def hoppingx(site0, site1):
return (-0.5 * t * sigma_z - 0.5 * 1j * t_x * sigma_x) def
hoppingy(site0, site1): return -0.5 * t * sigma_z - 0.5 * 1j * t_y *
sigma_y def hoppingz(site0, site1, B): y = site1.pos[1]
return (-0.5 * t_z * sigma_z - 0.5 * 1j * lamda * sigma_0) * exp(2 * pi *
1j * B * a * (y-40)) syst = kwant.Builder() lat =
kwant.lattice.cubic(a) syst[(lat(z, y, x) for z in range(H) for y in
range(W) for x in range(L))] = onsite syst[kwant.builder.HoppingKind((1,
0, 0), lat, lat)] = hoppingz syst[kwant.builder.HoppingKind((0, 1, 0),
lat, lat)] = hoppingy syst[kwant.builder.HoppingKind((0, 0, 1), lat,
lat)] = hoppingx
lead1=kwant.Builder(kwant.TranslationalSymmetry((0,-a,0)))
lead1[(lat(z,y,x) for z in range(H)for y in range(W)for x in
range(L))]=onsite lead1[kwant.builder.HoppingKind((1, 0, 0), lat, lat)]
= hoppingz lead1[kwant.builder.HoppingKind((0, 1, 0), lat, lat)] =
hoppingy lead1[kwant.builder.HoppingKind((0, 0, 1), lat, lat)] =
hoppingx syst.attach_lead(lead1) syst.attach_lead(lead1.reversed())
lead2=kwant.Builder(kwant.TranslationalSymmetry((-a,0,0)))
lead2[(lat(z,y,x) for z in range(H)for y in range(W)for x in
range(L))]=onsite lead2[kwant.builder.HoppingKind((1, 0, 0), lat, lat)]
= hoppingz lead2[kwant.builder.HoppingKind((0, 1, 0), lat, lat)] =
hoppingy lead2[kwant.builder.HoppingKind((0, 0, 1), lat, lat)] =
hoppingx syst.attach_lead(lead2) syst.attach_lead(lead2.reversed())
syst = syst.finalized() return systdef analyze_system(syst, Bfields):
syst = make_system() kwant.plot(syst) energies = [] for B in
Bfields: #print(B) ham_mat =
syst.hamiltonian_submatrix(params=dict(B=B), sparse=True) ev, evec =
sla.eigsh(ham_mat.tocsc(), k=20, sigma=0) energies.append(ev)
#print (energies) plt.figure() plt.plot(Bfields, energies)
plt.xlabel("magnetic field [${10^-3 h/e}$]") plt.ylabel("energy [t]")
plt.ylim(0, 0.11) plt.show()def main(): syst = make_system()
analyze_system(syst, [B * 0.00002 for B in range(101)])main()*
Naveen
Department of Physics & Astrophysics
University of Delhi
New Delhi-110007
On Sun, Sep 8, 2019, 17:37 Abbout Adel <abbout.a...@gmail.com> wrote:
> Dear Naveen,
>
> Your program works fine. You have just a small problem of plotting. You
> can solve that by changing "plt.show" by "plt.show()".
>
> Think about putting print (B) inside the loop when you debug your
> program. That will help you for example to see if the program is running
> well, and you can detect what may be wrong.
> Think also about returning Energies in your function. This way you can try
> potting the result outside the function you called. Don't hesitate to put
> some extra lines in your program to follow the progress when you think that
> there is a problem.
>
>
> I hope this helps.
> Regards,
> Adel
>
> On Thu, Sep 5, 2019 at 7:32 PM Naveen Yadav <naveengunwa...@gmail.com>
> wrote:
>
>> Dear Sir,
>>
>> I am trying to plot the energy as a function of magnetic field for a 3D
>> case, but I am getting tedious results. The system is infinite in two
>> directions and has some width in the third direction. Please have a look at
>> the code attached below. I tried a lot but failed. Is the code correct or I
>> am wrong somewhere.
>> Thank you.
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>> *import kwantimport scipy.sparse.linalg as slaimport matplotlib.pyplot as
>> pltimport tinyarrayimport numpy as npfrom numpy import cos, sin, piimport
>> cmathfrom cmath import expsigma_0 = tinyarray.array([[1, 0], [0,
>> 1]])sigma_x = tinyarray.array([[0, 1], [1, 0]])sigma_y =
>> tinyarray.array([[0, -1j], [1j, 0]])sigma_z = tinyarray.array([[1, 0], [0,
>> -1]])def make_system(a=1, L=30, W=10, H=10, t=1.0, t_x=1.0, t_y=1.0,
>> t_z=1.0, lamda=0.1, beta=1.05): def onsite(site): return (t_z *
>> cos(beta) + 2 * t) * sigma_z def hoppingx(site0, site1):
>> return (-0.5 * t * sigma_z - 0.5 * 1j * t_x * sigma_x) def
>> hoppingy(site0, site1): return -0.5 * t * sigma_z - 0.5 * 1j * t_y *
>> sigma_y def hoppingz(site0, site1, B): y = site1.pos[1]
>> return (-0.5 * t_z * sigma_z - 0.5 * 1j * lamda * sigma_0) * exp(2 * pi *
>> 1j * B * a * (y-40)) syst = kwant.Builder() lat =
>> kwant.lattice.cubic(a) syst[(lat(z, y, x) for z in range(H) for y in
>> range(W) for x in range(L))] = onsite syst[kwant.builder.HoppingKind((1,
>> 0, 0), lat, lat)] = hoppingz syst[kwant.builder.HoppingKind((0, 1, 0),
>> lat, lat)] = hoppingy syst[kwant.builder.HoppingKind((0, 0, 1), lat,
>> lat)] = hoppingx
>> lead1=kwant.Builder(kwant.TranslationalSymmetry((0,-a,0)))
>> lead1[(lat(z,y,x) for z in range(H)for y in range(W)for x in
>> range(L))]=onsite lead1[kwant.builder.HoppingKind((1, 0, 0), lat, lat)]
>> = hoppingz lead1[kwant.builder.HoppingKind((0, 1, 0), lat, lat)] =
>> hoppingy lead1[kwant.builder.HoppingKind((0, 0, 1), lat, lat)] =
>> hoppingx syst.attach_lead(lead1) syst.attach_lead(lead1.reversed())
>> lead2=kwant.Builder(kwant.TranslationalSymmetry((-a,0,0)))
>> lead2[(lat(z,y,x) for z in range(H)for y in range(W)for x in
>> range(L))]=onsite lead2[kwant.builder.HoppingKind((1, 0, 0), lat, lat)]
>> = hoppingz lead2[kwant.builder.HoppingKind((0, 1, 0), lat, lat)] =
>> hoppingy lead2[kwant.builder.HoppingKind((0, 0, 1), lat, lat)] =
>> hoppingx syst.attach_lead(lead2) syst.attach_lead(lead2.reversed())
>> syst = syst.finalized() return systdef analyze_system(): syst =
>> make_system() kwant.plot(syst) Bfields = np.linspace(0, 0.002, 100)
>> energies = [] for B in Bfields: ham_mat =
>> syst.hamiltonian_submatrix(params=dict(B=B), sparse=True) ev, evec =
>> sla.eigsh(ham_mat.tocsc(), k=20, sigma=0) energies.append(ev)
>> #print(energies) plt.figure() plt.plot(Bfields, energies)
>> plt.xlabel("magnetic field [${10^-3 h/e}$]") plt.ylabel("energy [t]")
>> plt.ylim(0, 0.11) plt.showdef main(): syst = make_system()
>> analyze_system()main()*
>>
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>>
>> --
>>
>>
>> With Best Regards
>> NAVEEN YADAV
>> Ph.D Research Scholar
>> Deptt. Of Physics & Astrophysics
>> University Of Delhi.
>>
>
>
> --
> Abbout Adel
>
