Python derivative 예제들

예제 #1

파일: topology.py 프로젝트: joselado/pygra

def operator_berry_bands(hin,k=[0.,0.],operator=None,delta=0.00001):
  """Calculates the Berry curvature using an arbitrary operator"""
  h = multicell.turn_multicell(hin) # turn to multicell form
  dhdx = multicell.derivative(h,k,order=[1,0]) # derivative
  dhdy = multicell.derivative(h,k,order=[0,1]) # derivative
  hkgen = h.get_hk_gen() # get generator
  hk = hkgen(k) # get hamiltonian
  (es,ws) = lg.eigh(hkgen(k)) # initial waves
  ws = np.conjugate(np.transpose(ws)) # transpose the waves
  from berry_curvaturef90 import berry_curvature_bands as bcb90
  if operator is None: operator = np.identity(dhdx.shape[0],dtype=np.complex)
  bs = bcb90(dhdx,dhdy,ws,es,operator,delta) # berry curvatures
  return (es,bs*np.pi*np.pi*8) # normalize so the sum is 2pi Chern

예제 #2

def operator_berry_bands(hin, k=[0., 0.], operator=None, delta=0.00001):
    """Calculates the Berry curvature using an arbitrary operator"""
    h = multicell.turn_multicell(hin)  # turn to multicell form
    dhdx = multicell.derivative(h, k, order=[1, 0])  # derivative
    dhdy = multicell.derivative(h, k, order=[0, 1])  # derivative
    hkgen = h.get_hk_gen()  # get generator
    hk = hkgen(k)  # get hamiltonian
    (es, ws) = lg.eigh(hkgen(k))  # initial waves
    ws = np.conjugate(np.transpose(ws))  # transpose the waves
    from berry_curvaturef90 import berry_curvature_bands as bcb90
    if operator is None:
        operator = np.identity(dhdx.shape[0], dtype=np.complex)
    bs = bcb90(dhdx, dhdy, ws, es, operator, delta)  # berry curvatures
    return (es, bs * np.pi * np.pi * 8)  # normalize so the sum is 2pi Chern

예제 #3

파일: effective.py 프로젝트: joselado/pygra

def effective2d(hin,k0 = 0.0,ewindow = [-1.0,1.0]):
  """Calculates the effective Hamiltonian for a 2d system"""
  h = multicell.turn_multicell(hin) # multicell form
  hkgen = h.get_hk_gen() # get hamiltonian generator
  (es,ws) = lg.eigh(hkgen(k0)) # initial waves
  ws = np.transpose(ws) # transpose the waves
  wf0 = [] # list to store waves
  for i in range(len(es)): # loop over energies
    if ewindow[0]<ewindow[1]: # check whether in window
      wf0.append(ws[i]) # store this wave
  # now calculate the effective Hamiltonian 
  raise
  for order in orders: # loop over orders
    dh = multicell.derivative(h,k0,order=order) # derivative of the hamiltonian

예제 #4

def effective2d(hin, k0=0.0, ewindow=[-1.0, 1.0]):
    """Calculates the effective Hamiltonian for a 2d system"""
    h = multicell.turn_multicell(hin)  # multicell form
    hkgen = h.get_hk_gen()  # get hamiltonian generator
    (es, ws) = lg.eigh(hkgen(k0))  # initial waves
    ws = np.transpose(ws)  # transpose the waves
    wf0 = []  # list to store waves
    for i in range(len(es)):  # loop over energies
        if ewindow[0] < ewindow[1]:  # check whether in window
            wf0.append(ws[i])  # store this wave
    # now calculate the effective Hamiltonian
    raise
    for order in orders:  # loop over orders
        dh = multicell.derivative(h, k0,
                                  order=order)  # derivative of the hamiltonian