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Commit 5ad97d57 authored by Davison, Jacob's avatar Davison, Jacob
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moved simult operator flow out of main

parent 316bd710
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main.py
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......@@ -86,27 +86,28 @@ def derivative(t, y, inputs):
dy -- next step in flow"""
hamiltonian, occ_tensors, generator, flow, tspinsq, flow_spin = inputs
hamiltonian, occ_tensors, generator, flow = inputs
#assert isinstance(hamiltonian, Hamiltonian), "Arg 2 must be Hamiltonian object"
assert isinstance(occ_tensors, OccupationTensors), "Arg 3 must be OccupationTensors object"
assert isinstance(generator, Generator), "Arg 4 must be Generator object"
assert isinstance(flow, Flow), "Arg 5 must be a Flow object"
half = int(len(y)/2)
# half = int(len(y)/2)
# Hamiltonian flow
E, f, G = ravel(y[0:half], hamiltonian.n_sp_states)
E, f, G = ravel(y, hamiltonian.n_sp_states)
generator.f = f
generator.G = G
dE, df, dG = flow.flow(f, G, generator)
# Spin-squared flow
E_spin, f_spin, G_spin = ravel(y[half::], tspinsq.n_sp_states)
#E_spin, f_spin, G_spin = ravel(y[half::], tspinsq.n_sp_states)
# generator_spin.f = f_spin
# generator_spin.G = G_spin
dE_spin, df_spin, dG_spin = flow_spin.flow(f_spin, G_spin, generator)
#dE_spin, df_spin, dG_spin = flow_spin.flow(f_spin, G_spin, generator)
dy = np.concatenate([unravel(dE, df, dG), unravel(dE_spin, df_spin, dG_spin)], axis=0)
#dy = np.concatenate([unravel(dE, df, dG), unravel(dE_spin, df_spin, dG_spin)], axis=0)
dy = unravel(dE,df,dG)
return dy
......@@ -197,10 +198,10 @@ def main(n_holes, n_particles, ref=None, d=1.0, g=0.5, pb=0.0, verbose=1, flow_d
if ref is None:
ha = PairingHamiltonian2B(n_holes, n_particles, d=d, g=g, pb=pb)
ref = ha.reference # this is just for printing
ss = TSpinSq(n_holes, n_particles)
# ss = TSpinSq(n_holes, n_particles)
else:
ha = PairingHamiltonian2B(n_holes, n_particles, ref=ref, d=d, g=g, pb=pb)
ss = TSpinSq(n_holes, n_particles)
# ss = TSpinSq(n_holes, n_particles)
ot = OccupationTensors(ha.sp_basis, ha.reference)
......@@ -214,7 +215,7 @@ def main(n_holes, n_particles, ref=None, d=1.0, g=0.5, pb=0.0, verbose=1, flow_d
fl = Flow_IMSRG2(ha, ot)
#wg_spin = WegnerGenerator(ss, ot)
fl_spin = Flow_IMSRG2(ss, ot)
# fl_spin = Flow_IMSRG2(ss, ot)
initf = time.time() # finish instantiation timer
......@@ -238,7 +239,8 @@ def main(n_holes, n_particles, ref=None, d=1.0, g=0.5, pb=0.0, verbose=1, flow_d
flowi = time.time()
# --- Solve the IM-SRG flow
y0 = np.concatenate([unravel(ha.E, ha.f, ha.G), unravel(ss.E, ss.f, ss.G)], axis=0)
#y0 = np.concatenate([unravel(ha.E, ha.f, ha.G), unravel(ss.E, ss.f, ss.G)], axis=0)
y0 = unravel(ha.E, ha.f, ha.G)
H0B, H1B, H2B = get_vacuum_coeffs(ha.E, ha.f, ha.G, ha.sp_basis, ha.holes)
zero, eta1B_vac, eta2B_vac = get_vacuum_coeffs(0.0, wg.eta1B, wg.eta2B, ha.sp_basis, ha.holes)
......@@ -247,7 +249,7 @@ def main(n_holes, n_particles, ref=None, d=1.0, g=0.5, pb=0.0, verbose=1, flow_d
solver = ode(derivative,jac=None)
solver.set_integrator('vode', method='bdf', order=5, nsteps=1000)
solver.set_f_params([ha, ot, wg, fl, ss, fl_spin])
solver.set_f_params([ha, ot, wg, fl])
solver.set_initial_value(y0, 0.)
sfinal = 50
......@@ -268,20 +270,9 @@ def main(n_holes, n_particles, ref=None, d=1.0, g=0.5, pb=0.0, verbose=1, flow_d
print_columns = ['iter',
's',
'E',
'CI_gs',
'0bN_SS',
'<SS>',
'0b_SS',
'1bc_SS',
'2bc_SS',
'CI_gs',
'||eta1b||',
'||eta2b||',
'commute1bd',
'commute1bod',
'commute2bd',
'commute2bod',
'commute',
'commutePairedBlock']
'||eta2b||']
column_string = '{: >6}, '
for i, string in enumerate(print_columns[1::]):
if i != len(print_columns)-2:
......@@ -297,44 +288,49 @@ def main(n_holes, n_particles, ref=None, d=1.0, g=0.5, pb=0.0, verbose=1, flow_d
ys = solver.integrate(solver.t+ds, step=True)
half = int(len(ys)/2)
Es, fs, Gs = ravel(ys[0:half], ha.n_sp_states)
E_spins, f_spins, G_spins = ravel(ys[half::], ss.n_sp_states)
Es, fs, Gs = ravel(ys, ha.n_sp_states)
# E_spins, f_spins, G_spins = ravel(ys[half::], ss.n_sp_states)
s_vals.append(solver.t)
E_vals.append(Es)
# compute density matrices, get expectation values
H0B, H1B, H2B = get_vacuum_coeffs(Es, fs, Gs, ha.sp_basis, ha.holes)
SS0B, SS1B, SS2B = get_vacuum_coeffs(E_spins, f_spins, G_spins, ss.sp_basis, ss.holes)
hme = pyci.matrix(n_holes, n_particles, H0B, H1B, H2B, H2B, imsrg=True)
w,v = np.linalg.eigh(hme)
v0 = v[:,eig_idx]
# H0B, H1B, H2B = get_vacuum_coeffs(Es, fs, Gs, ha.sp_basis, ha.holes)
# SS0B, SS1B, SS2B = get_vacuum_coeffs(E_spins, f_spins, G_spins, ss.sp_basis, ss.holes)
# hme = pyci.matrix(n_holes, n_particles, H0B, H1B, H2B, H2B, imsrg=True)
# w,v = np.linalg.eigh(hme)
# v0 = v[:,eig_idx]
rho1b = density_1b(n_holes,n_particles, weights=v0)
rho2b = density_2b(n_holes,n_particles, weights=v0)
# rho1b = density_1b(n_holes,n_particles, weights=v0)
# rho2b = density_2b(n_holes,n_particles, weights=v0)
contract_1b = np.einsum('ij,ij', rho1b, SS1B)
# contract_1b = np.einsum('ij,ij', rho1b, SS1B)
rho_reshape_2b = np.reshape(rho2b, (ss.n_sp_states**2,ss.n_sp_states**2))
h2b_reshape_2b = np.reshape(SS2B, (ss.n_sp_states**2,ss.n_sp_states**2))
contract_2b = np.einsum('ij,ij', rho_reshape_2b, h2b_reshape_2b)
# rho_reshape_2b = np.reshape(rho2b, (ss.n_sp_states**2,ss.n_sp_states**2))
# h2b_reshape_2b = np.reshape(SS2B, (ss.n_sp_states**2,ss.n_sp_states**2))
# contract_2b = np.einsum('ij,ij', rho_reshape_2b, h2b_reshape_2b)
s_expect = SS0B + contract_1b + 0.25*contract_2b
# s_expect = SS0B + contract_1b + 0.25*contract_2b
E_gs_lst.append(w[eig_idx])
s_expect_lst.append(s_expect)
# E_gs_lst.append(w[eig_idx])
# s_expect_lst.append(s_expect)
if iters %10 == 0 and verbose:
zero, eta1Bv, eta2Bv = get_vacuum_coeffs(0.0,wg.eta1B,wg.eta2B,ha.sp_basis,ha.holes)
ggme = pyci.matrix(n_holes, n_particles, zero, eta1Bv, eta2Bv, eta2Bv, imsrg=True)
ssme = pyci.matrix(n_holes, n_particles, SS0B, SS1B, SS2B, SS2B, imsrg=True)
# ggme = pyci.matrix(n_holes, n_particles, zero, eta1Bv, eta2Bv, eta2Bv, imsrg=True)
# ssme = pyci.matrix(n_holes, n_particles, SS0B, SS1B, SS2B, SS2B, imsrg=True)
norm_eta1B = np.linalg.norm(np.ravel(wg.eta1B))
norm_eta2B = np.linalg.norm(np.ravel(wg.eta2B))
num_sp = n_holes+n_particles
axes = (num_sp**2,num_sp**2)
H0B, H1B, H2B = get_vacuum_coeffs(Es, fs, Gs, ha.sp_basis, ha.holes)
hme = pyci.matrix(n_holes, n_particles, H0B, H1B, H2B, H2B, imsrg=True)
w,v = np.linalg.eigh(hme)
# SS2B_r = np.reshape(SS2B, (num_sp**2,num_sp**2))
# H2B_r = np.reshape(H2B, (num_sp**2, num_sp**2))
# commute1b = np.linalg.norm(SS1B.dot(H1B) - H1B.dot(SS1B))
......@@ -343,34 +339,23 @@ def main(n_holes, n_particles, ref=None, d=1.0, g=0.5, pb=0.0, verbose=1, flow_d
# hfd,hfod,hGd,hGod = wg.decouple_OD()
# sfd,sfod,sGd,sGod = wg_spin.decouple_OD()
hfd,hfod,hGd,hGod = decouple_od(fs, Gs, ha.particles, ha.holes)
sfd,sfod,sGd,sGod = decouple_od(f_spins, G_spins, ha.particles, ha.holes)
# hfd,hfod,hGd,hGod = decouple_od(fs, Gs, ha.particles, ha.holes)
# sfd,sfod,sGd,sGod = decouple_od(f_spins, G_spins, ha.particles, ha.holes)
hGd,hGod,sGd,sGod = np.reshape(hGd,axes),np.reshape(hGod,axes),np.reshape(sGd,axes),np.reshape(sGod,axes)
commute1bd = np.linalg.norm(hfd.dot(sfd) - sfd.dot(hfd))
commute1bod = np.linalg.norm(hfod.dot(sfod) - sfod.dot(hfod))
commute2bd = np.linalg.norm(hGd.dot(sGd) - sGd.dot(hGd))
commute2bod = np.linalg.norm(hGod.dot(sGod) - sGod.dot(hGod))
commute = np.linalg.norm(hme.dot(ssme) - ssme.dot(hme))
commutePairBlock = np.linalg.norm(hme[0:2,0:2].dot(ssme[0:2,0:2]) - ssme[0:2,0:2].dot(hme[0:2,0:2]))
# hGd,hGod,sGd,sGod = np.reshape(hGd,axes),np.reshape(hGod,axes),np.reshape(sGd,axes),np.reshape(sGod,axes)
# commute1bd = np.linalg.norm(hfd.dot(sfd) - sfd.dot(hfd))
# commute1bod = np.linalg.norm(hfod.dot(sfod) - sfod.dot(hfod))
# commute2bd = np.linalg.norm(hGd.dot(sGd) - sGd.dot(hGd))
# commute2bod = np.linalg.norm(hGod.dot(sGod) - sGod.dot(hGod))
# commute = np.linalg.norm(hme.dot(ssme) - ssme.dot(hme))
# commutePairBlock = np.linalg.norm(hme[0:2,0:2].dot(ssme[0:2,0:2]) - ssme[0:2,0:2].dot(hme[0:2,0:2]))
data_columns = [iters,
solver.t,
Es,
w[eig_idx],
E_spins,
s_expect,
SS0B,
contract_1b,
contract_2b,
norm_eta1B,
norm_eta2B,
commute1bd,
commute1bod,
commute2bd,
commute2bod,
commute,
commutePairBlock]
norm_eta2B]
column_string = '{:>6d}, '
for i, string in enumerate(print_columns[1::]):
if i != len(print_columns)-2:
......@@ -382,11 +367,11 @@ def main(n_holes, n_particles, ref=None, d=1.0, g=0.5, pb=0.0, verbose=1, flow_d
print(column_string.format(*data_columns))
#print(v0*v0)
ws,vs = np.linalg.eigh(ssme)
# ws,vs = np.linalg.eigh(ssme)
with np.printoptions(linewidth=999,precision=4):
print(ssme)
print(ggme)
# with np.printoptions(linewidth=999,precision=4):
# print(ssme)
# print(ggme)
# for i in range(wg.eta1B.shape[0]):
# print("{d}".format(d=wg.eta1B[i,:]))
# for i in range(wg.eta1B.shape[0]):
......@@ -461,9 +446,6 @@ def main(n_holes, n_particles, ref=None, d=1.0, g=0.5, pb=0.0, verbose=1, flow_d
del ha, ot, wg, fl, solver, y0, sfinal
expect_flow_df = pd.DataFrame({'s':s_vals, 'E_gs':E_gs_lst, 's_expect':s_expect_lst})
pickle.dump(expect_flow_df, open('expect_flow.p', 'wb'))
return (convergence, iters, d, g, pb, num_sp, s_vals, E_vals, time_str)
......@@ -535,7 +517,7 @@ if __name__ == '__main__':
#ref = 0.7*np.array([1,1,1,1,0,0,0,0])+0.3*np.array([1,1,0,0,1,1,0,0])
basis = pyci.gen_basis(2,2)[:,1::]
basis = pyci.gen_basis(4,4)[:,1::]
#ref = 0.2*basis[0,:]+ 0.8*basis[6, :]
#ref = basis.T.dot(v0**2)
......
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