def expect_2s(self, op, n):
"""Computes the expectation value of a nearest-neighbour two-site operator.
The operator should be a q[n] x q[n + 1] x q[n] x q[n + 1] array
such that op[s, t, u, v] = <st|op|uv> or a function of the form
op(s, t, u, v) = <st|op|uv>.
Parameters
----------
o : ndarray or callable
The operator array or function.
n : int
The leftmost site number (operator acts on n, n + 1).
"""
A = self.get_A(n)
Ap1 = self.get_A(n + 1)
AA = tm.calc_AA(A, Ap1)
if callable(op):
op = sp.vectorize(op, otypes=[sp.complex128])
op = sp.fromfunction(op, (A.shape[0], Ap1.shape[0], A.shape[0], Ap1.shape[0]))
C = tm.calc_C_mat_op_AA(op, AA)
res = tm.eps_r_op_2s_C12_AA34(self.get_r(n + 1), C, AA)
return mm.adot(self.get_l(n - 1), res)
def expect_2s(self, op, n, AA=None):
"""Computes the expectation value of a nearest-neighbour two-site operator.
The operator should be a q[n] x q[n + 1] x q[n] x q[n + 1] array
such that op[s, t, u, v] = <st|op|uv> or a function of the form
op(s, t, u, v) = <st|op|uv>.
The state must be up-to-date -- see self.update()!
Parameters
----------
op : ndarray or callable
The operator array or function.
n : int
The leftmost site number (operator acts on n, n + 1).
Returns
-------
expval : floating point number
The expectation value (data type may be complex)
"""
A = self.A[n]
Ap1 = self.A[n + 1]
if AA is None:
AA = tm.calc_AA(A, Ap1)
if callable(op):
op = sp.vectorize(op, otypes=[sp.complex128])
op = sp.fromfunction(op, (A.shape[0], Ap1.shape[0], A.shape[0], Ap1.shape[0]))
C = tm.calc_C_mat_op_AA(op, AA)
res = tm.eps_r_op_2s_C12_AA34(self.r[n + 1], C, AA)
return m.adot(self.l[n - 1], res)
def expect_2s(self, op, n):
"""Computes the expectation value of a nearest-neighbour two-site operator.
The operator should be a q[n] x q[n + 1] x q[n] x q[n + 1] array
such that op[s, t, u, v] = <st|op|uv> or a function of the form
op(s, t, u, v) = <st|op|uv>.
The state must be up-to-date -- see self.update()!
Parameters
----------
op : ndarray or callable
The operator array or function.
n : int
The leftmost site number (operator acts on n, n + 1).
Returns
-------
expval : floating point number
The expectation value (data type may be complex)
"""
A = self.A[n]
Ap1 = self.A[n + 1]
AA = tm.calc_AA(A, Ap1)
if callable(op):
op = sp.vectorize(op, otypes=[sp.complex128])
op = sp.fromfunction(
op, (A.shape[0], Ap1.shape[0], A.shape[0], Ap1.shape[0]))
C = tm.calc_C_mat_op_AA(op, AA)
res = tm.eps_r_op_2s_C12_AA34(self.r[n + 1], C, AA)
return m.adot(self.l[n - 1], res)
def expect_2s(self, op, n):
"""Computes the expectation value of a nearest-neighbour two-site operator.
The operator should be a q[n] x q[n + 1] x q[n] x q[n + 1] array
such that op[s, t, u, v] = <st|op|uv> or a function of the form
op(s, t, u, v) = <st|op|uv>.
Parameters
----------
o : ndarray or callable
The operator array or function.
n : int
The leftmost site number (operator acts on n, n + 1).
"""
A = self.get_A(n)
Ap1 = self.get_A(n + 1)
AA = tm.calc_AA(A, Ap1)
if callable(op):
op = sp.vectorize(op, otypes=[sp.complex128])
op = sp.fromfunction(
op, (A.shape[0], Ap1.shape[0], A.shape[0], Ap1.shape[0]))
C = tm.calc_C_mat_op_AA(op, AA)
res = tm.eps_r_op_2s_C12_AA34(self.get_r(n + 1), C, AA)
return mm.adot(self.get_l(n - 1), res)
def expect_2s(self, op):
"""Computes the expectation value of a nearest-neighbour two-site operator.
The operator should be a q x q x q x q array
such that op[s, t, u, v] = <st|op|uv> or a function of the form
op(s, t, u, v) = <st|op|uv>.
The state must be up-to-date -- see self.update()!
Parameters
----------
op : ndarray or callable
The operator array or function.
Returns
-------
expval : floating point number
The expectation value (data type may be complex)
"""
if callable(op):
op = np.vectorize(op, otypes=[np.complex128])
op = np.fromfunction(op, (self.q, self.q, self.q, self.q))
C = tm.calc_C_mat_op_AA(op, self.AA)
res = tm.eps_r_op_2s_C12_AA34(self.r, C, self.AA)
return m.adot(self.l, res)
