using solve_bvp to solve Schrödinger equation











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Hi I'm trying to sove the Schrödinger equation for a infinite square well with a barrior using solve_bvp but I don't understand how to do two things with solve_bvp. one is setting the range, the x axis I am trying to give it goes from -b to b but it is solving for 0 to b, I had previously tried solving with solve_ivp but I was running into the same problem. the other problem I have is how to set the boundary condition, I need to take into account the first and second derivative, but I'm a bit lost because I cannot understand the documentation very well. I was following an example found here, but it wasn't giving me the correct results so I'm trying to rewrite it. I'm also discussing the problem on another site but that one is a bit more general than what I'm trying to solve here.



this is the code that I'm trying to get to work



from scipy.integrate import solve_bvp
from pylab import *
import numpy as np

## dimentions _
## | : | | Vmax
## | ___:___ | | _
## |___| |___| _| Vmin _|- Vb
##-B -A 0 A B*Alpha
## ______/|______/
## Po Pf

Vmax = 55
Vmin = 0
Vb = 50
A = 1
B = 4
alpha = 1
Po = -A-B
Pf = A+B*alpha
psi_b = array([0,1]) # Wave function boundry [first dir, secound dir]

N = 1000 #steps
psi = np.zeros([N,2])
x = linspace(Po, Pf, N) # x-axis


def V(z):
'''
#Potential function in the finite square well.
'''
val=
for i in z:
if -A <=i <= A:
val.append( Vb)
elif i<=Po:
val.append( Vmax)
elif i>=Pf:
val.append(Vmax)
else:
val.append(Vmin)
return val

def boundary_conditions(psi_Po, psi_pf):
return (psi_b)

def SE(z, p, E):
state0 = p[1]
state1 = 1.0*(V(z) - E)*p[0]
return np.array([state0, state1])

def Wave_function(energy,psi):
y_ = np.zeros((2, x.size))
psi = solve_bvp(SE(x, psi, y_), boundary_conditions, x, y_)
print(len(psi.y))
return psi.y

def pltPotentail():
plot(x,V(x))

def main():
en = linspace(0, Vb, 10) # vector of energies where we look for the stable states
figure(1)
pltPotentail()
Wave_function(0,psi)
show()
if __name__ == "__main__":
main()









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    up vote
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    down vote

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    Hi I'm trying to sove the Schrödinger equation for a infinite square well with a barrior using solve_bvp but I don't understand how to do two things with solve_bvp. one is setting the range, the x axis I am trying to give it goes from -b to b but it is solving for 0 to b, I had previously tried solving with solve_ivp but I was running into the same problem. the other problem I have is how to set the boundary condition, I need to take into account the first and second derivative, but I'm a bit lost because I cannot understand the documentation very well. I was following an example found here, but it wasn't giving me the correct results so I'm trying to rewrite it. I'm also discussing the problem on another site but that one is a bit more general than what I'm trying to solve here.



    this is the code that I'm trying to get to work



    from scipy.integrate import solve_bvp
    from pylab import *
    import numpy as np

    ## dimentions _
    ## | : | | Vmax
    ## | ___:___ | | _
    ## |___| |___| _| Vmin _|- Vb
    ##-B -A 0 A B*Alpha
    ## ______/|______/
    ## Po Pf

    Vmax = 55
    Vmin = 0
    Vb = 50
    A = 1
    B = 4
    alpha = 1
    Po = -A-B
    Pf = A+B*alpha
    psi_b = array([0,1]) # Wave function boundry [first dir, secound dir]

    N = 1000 #steps
    psi = np.zeros([N,2])
    x = linspace(Po, Pf, N) # x-axis


    def V(z):
    '''
    #Potential function in the finite square well.
    '''
    val=
    for i in z:
    if -A <=i <= A:
    val.append( Vb)
    elif i<=Po:
    val.append( Vmax)
    elif i>=Pf:
    val.append(Vmax)
    else:
    val.append(Vmin)
    return val

    def boundary_conditions(psi_Po, psi_pf):
    return (psi_b)

    def SE(z, p, E):
    state0 = p[1]
    state1 = 1.0*(V(z) - E)*p[0]
    return np.array([state0, state1])

    def Wave_function(energy,psi):
    y_ = np.zeros((2, x.size))
    psi = solve_bvp(SE(x, psi, y_), boundary_conditions, x, y_)
    print(len(psi.y))
    return psi.y

    def pltPotentail():
    plot(x,V(x))

    def main():
    en = linspace(0, Vb, 10) # vector of energies where we look for the stable states
    figure(1)
    pltPotentail()
    Wave_function(0,psi)
    show()
    if __name__ == "__main__":
    main()









    share|improve this question


























      up vote
      0
      down vote

      favorite









      up vote
      0
      down vote

      favorite











      Hi I'm trying to sove the Schrödinger equation for a infinite square well with a barrior using solve_bvp but I don't understand how to do two things with solve_bvp. one is setting the range, the x axis I am trying to give it goes from -b to b but it is solving for 0 to b, I had previously tried solving with solve_ivp but I was running into the same problem. the other problem I have is how to set the boundary condition, I need to take into account the first and second derivative, but I'm a bit lost because I cannot understand the documentation very well. I was following an example found here, but it wasn't giving me the correct results so I'm trying to rewrite it. I'm also discussing the problem on another site but that one is a bit more general than what I'm trying to solve here.



      this is the code that I'm trying to get to work



      from scipy.integrate import solve_bvp
      from pylab import *
      import numpy as np

      ## dimentions _
      ## | : | | Vmax
      ## | ___:___ | | _
      ## |___| |___| _| Vmin _|- Vb
      ##-B -A 0 A B*Alpha
      ## ______/|______/
      ## Po Pf

      Vmax = 55
      Vmin = 0
      Vb = 50
      A = 1
      B = 4
      alpha = 1
      Po = -A-B
      Pf = A+B*alpha
      psi_b = array([0,1]) # Wave function boundry [first dir, secound dir]

      N = 1000 #steps
      psi = np.zeros([N,2])
      x = linspace(Po, Pf, N) # x-axis


      def V(z):
      '''
      #Potential function in the finite square well.
      '''
      val=
      for i in z:
      if -A <=i <= A:
      val.append( Vb)
      elif i<=Po:
      val.append( Vmax)
      elif i>=Pf:
      val.append(Vmax)
      else:
      val.append(Vmin)
      return val

      def boundary_conditions(psi_Po, psi_pf):
      return (psi_b)

      def SE(z, p, E):
      state0 = p[1]
      state1 = 1.0*(V(z) - E)*p[0]
      return np.array([state0, state1])

      def Wave_function(energy,psi):
      y_ = np.zeros((2, x.size))
      psi = solve_bvp(SE(x, psi, y_), boundary_conditions, x, y_)
      print(len(psi.y))
      return psi.y

      def pltPotentail():
      plot(x,V(x))

      def main():
      en = linspace(0, Vb, 10) # vector of energies where we look for the stable states
      figure(1)
      pltPotentail()
      Wave_function(0,psi)
      show()
      if __name__ == "__main__":
      main()









      share|improve this question















      Hi I'm trying to sove the Schrödinger equation for a infinite square well with a barrior using solve_bvp but I don't understand how to do two things with solve_bvp. one is setting the range, the x axis I am trying to give it goes from -b to b but it is solving for 0 to b, I had previously tried solving with solve_ivp but I was running into the same problem. the other problem I have is how to set the boundary condition, I need to take into account the first and second derivative, but I'm a bit lost because I cannot understand the documentation very well. I was following an example found here, but it wasn't giving me the correct results so I'm trying to rewrite it. I'm also discussing the problem on another site but that one is a bit more general than what I'm trying to solve here.



      this is the code that I'm trying to get to work



      from scipy.integrate import solve_bvp
      from pylab import *
      import numpy as np

      ## dimentions _
      ## | : | | Vmax
      ## | ___:___ | | _
      ## |___| |___| _| Vmin _|- Vb
      ##-B -A 0 A B*Alpha
      ## ______/|______/
      ## Po Pf

      Vmax = 55
      Vmin = 0
      Vb = 50
      A = 1
      B = 4
      alpha = 1
      Po = -A-B
      Pf = A+B*alpha
      psi_b = array([0,1]) # Wave function boundry [first dir, secound dir]

      N = 1000 #steps
      psi = np.zeros([N,2])
      x = linspace(Po, Pf, N) # x-axis


      def V(z):
      '''
      #Potential function in the finite square well.
      '''
      val=
      for i in z:
      if -A <=i <= A:
      val.append( Vb)
      elif i<=Po:
      val.append( Vmax)
      elif i>=Pf:
      val.append(Vmax)
      else:
      val.append(Vmin)
      return val

      def boundary_conditions(psi_Po, psi_pf):
      return (psi_b)

      def SE(z, p, E):
      state0 = p[1]
      state1 = 1.0*(V(z) - E)*p[0]
      return np.array([state0, state1])

      def Wave_function(energy,psi):
      y_ = np.zeros((2, x.size))
      psi = solve_bvp(SE(x, psi, y_), boundary_conditions, x, y_)
      print(len(psi.y))
      return psi.y

      def pltPotentail():
      plot(x,V(x))

      def main():
      en = linspace(0, Vb, 10) # vector of energies where we look for the stable states
      figure(1)
      pltPotentail()
      Wave_function(0,psi)
      show()
      if __name__ == "__main__":
      main()






      python scilab






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      edited Nov 21 at 19:45

























      asked Nov 21 at 17:24









      user169808

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