def approx_solve(fname, gammas=[0.], k=-1, adj=None):
''' '''
# process the QCADesigner file
try:
cells, spacing, zones, J, _ = parse_qca_file(fname, one_zone=True)
except:
print('Failed to process QCA file: {0}'.format(fname))
return None
# convert J to specified adjacency
J = convert_adjacency(cells, spacing, J, adj=adj)
# normalize J
J /= np.max(np.abs(J))
# group each type of cell: normal = NORMAL or OUTPUT
drivers, fixeds, normals, outputs = [], [], [], []
for i, c in enumerate(cells):
if c['cf'] == CELL_FUNCTIONS['QCAD_CELL_INPUT']:
drivers.append(i)
elif c['cf'] == CELL_FUNCTIONS['QCAD_CELL_FIXED']:
fixeds.append(i)
else:
if c['cf'] == CELL_FUNCTIONS['QCAD_CELL_OUTPUT']:
outputs.append(i)
normals.append(i)
print(fixeds)
# map from output cell labels to indices in normals list
output_map = {i: n for n, i in enumerate(normals) if i in outputs}
J_d = J[drivers, :][:, normals] # matrix for mapping drivers to h
J_f = J[fixeds, :][:, normals] # matrix for mapping fixed cells to h
J_n = J[normals, :][:, normals] # J internal to set of normal cells
P_f = [(cells[i]['pol'] if 'pol' in cells[i] else 0.)
for i in fixeds] # polarization of fixed cells
h0 = np.dot(P_f, J_f).reshape([
-1,
]) # h contribution from fixed cells
# for each polarization, solve for all gammas
for pol in gen_pols(len(drivers)):
h = h0 + np.dot(pol, J_d)
for gamma in gammas:
t = time()
e_vals, e_vecs, modes = rp_solve(h, J_n, gam=gamma, verbose=True)
print('\n')
print(e_vals[0:2], time() - t)
if False:
t = time()
e_vals, e_vecs = solve(h,
J_n,
gamma=gamma,
minimal=False,
exact=False)
print(e_vals[0:2], time() - t)
def load_qca(fname):
cells, spacing, zones, J, feedback = parse_qca_file(fname, one_zone=True)
J = convert_adjacency(cells, spacing, J, adj='full')
J = -J / np.max(np.abs(J))
if SAVE_COEF:
fname = os.path.splitext(os.path.basename(fname))[0]
fname += os.path.extsep + 'coef'
to_coef(fname, J)
return J
def load_qca(fname):
cells, spacing, zones, J, feedback = parse_qca_file(fname, one_zone=True)
J = convert_adjacency(cells, spacing, J, adj="full")
J = -J / np.max(np.abs(J))
if SAVE_COEF:
fname = os.path.splitext(os.path.basename(fname))[0]
fname += os.path.extsep + "coef"
to_coef(fname, J)
return J
def exact_solve(fname, gammas = [0.], k=-1, adj=None):
'''Exactly solve the first k eigenstates for a QCA circuit for all possible
input configurations and all specified transverse fields. Assumes all cells
have the same transverse field.'''
# process the QCADesigner file
try:
cells, spacing, zones, J, _ = parse_qca_file(fname, one_zone=True)
except:
print('Failed to process QCA file: {0}'.format(fname))
return None
# convert J to specified adjacency
J = convert_adjacency(cells, spacing, J, adj=adj)
# normalize J
J /= np.max(np.abs(J))
# group each type of cell: normal = NORMAL or OUTPUT
drivers, fixeds, normals, outputs = [], [], [], []
for i,c in enumerate(cells):
if c['cf'] == CELL_FUNCTIONS['QCAD_CELL_INPUT']:
drivers.append(i)
elif c['cf'] == CELL_FUNCTIONS['QCAD_CELL_FIXED']:
fixeds.append(i)
else:
if c['cf'] == CELL_FUNCTIONS['QCAD_CELL_OUTPUT']:
outputs.append(i)
normals.append(i)
# map from output cell labels to indices in normals list
output_map = {i: n for n, i in enumerate(normals) if i in outputs}
J_d = J[drivers, :][:, normals] # matrix for mapping drivers to h
J_f = J[fixeds, :][:, normals] # matrix for mapping fixed cells to h
J_n = J[normals, :][:, normals] # J internal to set of normal cells
P_f = [(cells[i]['pol'] if 'pol' in cells[i] else 0.) for i in fixeds] # polarization of fixed cells
h0 = np.dot(P_f, J_f).reshape([-1,]) # h contribution from fixed cells
# for each polarization, solve for all gammas
for pol in gen_pols(len(drivers)):
h = h0 + np.dot(pol, J_d)
for gamma in gammas:
e_vals, e_vecs = solve(h, J_n, gamma=gamma, minimal=True, exact=False)
# e_vecs[:,i] is the i^th eigenstate
pols = state_to_pol(e_vecs)
# pols[:,i] gives the polarizations of all cells for the i^th e-vec
print('GS: {0:.4f}'.format(e_vals[0]))
print('pols: {0}'.format(pols[:,0]))
def approx_solve(fname, gammas=[0.0], k=-1, adj=None):
""" """
# process the QCADesigner file
try:
cells, spacing, zones, J, _ = parse_qca_file(fname, one_zone=True)
except:
print("Failed to process QCA file: {0}".format(fname))
return None
# convert J to specified adjacency
J = convert_adjacency(cells, spacing, J, adj=adj)
# normalize J
J /= np.max(np.abs(J))
# group each type of cell: normal = NORMAL or OUTPUT
drivers, fixeds, normals, outputs = [], [], [], []
for i, c in enumerate(cells):
if c["cf"] == CELL_FUNCTIONS["QCAD_CELL_INPUT"]:
drivers.append(i)
elif c["cf"] == CELL_FUNCTIONS["QCAD_CELL_FIXED"]:
fixeds.append(i)
else:
if c["cf"] == CELL_FUNCTIONS["QCAD_CELL_OUTPUT"]:
outputs.append(i)
normals.append(i)
print(fixeds)
# map from output cell labels to indices in normals list
output_map = {i: n for n, i in enumerate(normals) if i in outputs}
J_d = J[drivers, :][:, normals] # matrix for mapping drivers to h
J_f = J[fixeds, :][:, normals] # matrix for mapping fixed cells to h
J_n = J[normals, :][:, normals] # J internal to set of normal cells
P_f = [(cells[i]["pol"] if "pol" in cells[i] else 0.0) for i in fixeds] # polarization of fixed cells
h0 = np.dot(P_f, J_f).reshape([-1]) # h contribution from fixed cells
# for each polarization, solve for all gammas
for pol in gen_pols(len(drivers)):
h = h0 + np.dot(pol, J_d)
for gamma in gammas:
t = time()
e_vals, e_vecs, modes = rp_solve(h, J_n, gam=gamma, verbose=True)
print("\n")
print(e_vals[0:2], time() - t)
if False:
t = time()
e_vals, e_vecs = solve(h, J_n, gamma=gamma, minimal=False, exact=False)
print(e_vals[0:2], time() - t)
def from_qca_file(fname, adj=None):
''' '''
try:
cells, spacing, zones, J, _ = parse_qca_file(fname, one_zone=True)
except:
print('Failed to process QCA file: {0}'.format(fname))
return
# convert J to specified adjacency
J = convert_adjacency(cells, spacing, J, adj=adj)
# normalize J
J /= np.max(np.abs(J))
# group each type of cell: normal = NORMAL or OUTPUT
drivers, fixeds, normals, outputs = [], [], [], []
for i, c in enumerate(cells):
if c['cf'] == CELL_FUNCTIONS['QCAD_CELL_INPUT']:
drivers.append(i)
elif c['cf'] == CELL_FUNCTIONS['QCAD_CELL_FIXED']:
fixeds.append(i)
else:
if c['cf'] == CELL_FUNCTIONS['QCAD_CELL_OUTPUT']:
outputs.append(i)
normals.append(i)
# map from output cell labels to indices in normals list
J_d = J[drivers, :][:, normals] # matrix for mapping drivers to h
J_f = J[fixeds, :][:, normals] # matrix for mapping fixed cells to h
J_n = J[normals, :][:, normals] # J internal to set of normal cells
P_f = [(cells[i]['pol'] if 'pol' in cells[i] else 0.)
for i in fixeds] # polarization of fixed cells
h0 = np.dot(P_f, J_f).reshape([
-1,
]) # h contribution from fixed cells
# for each polarization, solve for gamma=0 and extimate remaining spectrum
for pol in gen_pols(len(drivers)):
h = h0 + np.dot(pol, J_d)
yield h, J_n
def main(fname):
try:
cells, spacing, zones, J, _ = parse_qca_file(fname, one_zone=True)
except:
print('Failed to process QCA file: {0}'.format(fname))
return None
# convert J to specified adjacency
J = 1.*(convert_adjacency(cells, spacing, J, adj=ADJ) != 0)
G = nx.Graph(J)
for k in G:
G.node[k]['w'] = 1./len(G[k])**2
pos = graphviz_layout(G)
nx.draw(G, pos=pos, with_labels=True)
plt.show()
chlebikova(G)
def main(fname):
try:
cells, spacing, zones, J, _ = parse_qca_file(fname, one_zone=True)
except:
print('Failed to process QCA file: {0}'.format(fname))
return None
# convert J to specified adjacency
J = 1. * (convert_adjacency(cells, spacing, J, adj=ADJ) != 0)
G = nx.Graph(J)
for k in G:
G.node[k]['w'] = 1. / len(G[k])**2
pos = graphviz_layout(G)
nx.draw(G, pos=pos, with_labels=True)
plt.show()
chlebikova(G)
def from_qca_file(fname, adj=None):
''' '''
try:
cells, spacing, zones, J, _ = parse_qca_file(fname, one_zone=True)
except:
print('Failed to process QCA file: {0}'.format(fname))
return
# convert J to specified adjacency
J = convert_adjacency(cells, spacing, J, adj=adj)
# normalize J
J /= np.max(np.abs(J))
# group each type of cell: normal = NORMAL or OUTPUT
drivers, fixeds, normals, outputs = [], [], [], []
for i,c in enumerate(cells):
if c['cf'] == CELL_FUNCTIONS['QCAD_CELL_INPUT']:
drivers.append(i)
elif c['cf'] == CELL_FUNCTIONS['QCAD_CELL_FIXED']:
fixeds.append(i)
else:
if c['cf'] == CELL_FUNCTIONS['QCAD_CELL_OUTPUT']:
outputs.append(i)
normals.append(i)
# map from output cell labels to indices in normals list
J_d = J[drivers, :][:, normals] # matrix for mapping drivers to h
J_f = J[fixeds, :][:, normals] # matrix for mapping fixed cells to h
J_n = J[normals, :][:, normals] # J internal to set of normal cells
P_f = [(cells[i]['pol'] if 'pol' in cells[i] else 0.) for i in fixeds] # polarization of fixed cells
h0 = np.dot(P_f, J_f).reshape([-1,]) # h contribution from fixed cells
# for each polarization, solve for gamma=0 and extimate remaining spectrum
for pol in gen_pols(len(drivers)):
h = h0 + np.dot(pol, J_d)
yield h, J_n
def compare_spectrum(fname, gmin=0.01, gmax=.5, adj='lim'):
''' '''
try:
cells, spacing, zones, J, _ = parse_qca_file(fname, one_zone=True)
except:
print('Failed ot process QCA file: {0}'.format(fname))
return None
# convert J to specified adjacency
J = convert_adjacency(cells, spacing, J, adj=adj)
# normalize J
J /= np.max(np.abs(J))
# group each type of cell: normal = NORMAL or OUTPUT
drivers, fixeds, normals, outputs = [], [], [], []
for i,c in enumerate(cells):
if c['cf'] == CELL_FUNCTIONS['QCAD_CELL_INPUT']:
drivers.append(i)
elif c['cf'] == CELL_FUNCTIONS['QCAD_CELL_FIXED']:
fixeds.append(i)
else:
if c['cf'] == CELL_FUNCTIONS['QCAD_CELL_OUTPUT']:
outputs.append(i)
normals.append(i)
# map from output cell labels to indices in normals list
output_map = {i: n for n, i in enumerate(normals) if i in outputs}
J_d = J[drivers, :][:, normals] # matrix for mapping drivers to h
J_f = J[fixeds, :][:, normals] # matrix for mapping fixed cells to h
J_n = J[normals, :][:, normals] # J internal to set of normal cells
P_f = [(cells[i]['pol'] if 'pol' in cells[i] else 0.) for i in fixeds] # polarization of fixed cells
h0 = np.dot(P_f, J_f).reshape([-1,]) # h contribution from fixed cells
gammas = np.linspace(gmin, gmax, STEPS)
for pol in gen_pols(len(drivers)):
h = h0 + np.dot(pol, J_d)
SP_E, RP_E = [], []
times = []
for gamma in gammas:
print(gamma)
t = time()
rp_vals, rp_vecs, modes = rp_solve(h, J_n, gam=gamma,
cache_dir=CACHE)
times.append(time()-t)
sp_vals, sp_vecs = solve(h, J_n, gamma=gamma)
SP_E.append(sp_vals)
RP_E.append(rp_vals)
LSP = min(len(x) for x in SP_E)
L = min(LSP, min(len(x) for x in RP_E))
SP_E = np.array([x[:L] for x in SP_E])
RP_E = np.array([x[:L] for x in RP_E])
plt.figure('spectrum')
plt.plot(gammas, SP_E, linewidth=2)
plt.plot(gammas, RP_E, 'x', markersize=8, markeredgewidth=2)
plt.xlabel('Gamma', fontsize=FS)
plt.ylabel('Energy', fontsize=FS)
plt.title('Circuit Spectrum', fontsize=FS)
plt.show(block=False)
plt.figure('runtimes')
plt.plot(gammas, times, 'b', linewidth=2)
plt.xlabel('Gammas', fontsize=FS)
plt.ylabel('Runtime (s)', fontsize=FS)
plt.title('RP-Solver runtime', fontsize=FS)
plt.show()
def compare_spectrum(fname, gmin=0.01, gmax=0.5, adj="lim"):
""" """
try:
cells, spacing, zones, J, _ = parse_qca_file(fname, one_zone=True)
except:
print("Failed ot process QCA file: {0}".format(fname))
return None
# convert J to specified adjacency
J = convert_adjacency(cells, spacing, J, adj=adj)
# normalize J
J /= np.max(np.abs(J))
# group each type of cell: normal = NORMAL or OUTPUT
drivers, fixeds, normals, outputs = [], [], [], []
for i, c in enumerate(cells):
if c["cf"] == CELL_FUNCTIONS["QCAD_CELL_INPUT"]:
drivers.append(i)
elif c["cf"] == CELL_FUNCTIONS["QCAD_CELL_FIXED"]:
fixeds.append(i)
else:
if c["cf"] == CELL_FUNCTIONS["QCAD_CELL_OUTPUT"]:
outputs.append(i)
normals.append(i)
# map from output cell labels to indices in normals list
output_map = {i: n for n, i in enumerate(normals) if i in outputs}
J_d = J[drivers, :][:, normals] # matrix for mapping drivers to h
J_f = J[fixeds, :][:, normals] # matrix for mapping fixed cells to h
J_n = J[normals, :][:, normals] # J internal to set of normal cells
P_f = [(cells[i]["pol"] if "pol" in cells[i] else 0.0) for i in fixeds] # polarization of fixed cells
h0 = np.dot(P_f, J_f).reshape([-1]) # h contribution from fixed cells
gammas = np.linspace(gmin, gmax, STEPS)
for pol in gen_pols(len(drivers)):
h = h0 + np.dot(pol, J_d)
SP_E, RP_E = [], []
times = []
for gamma in gammas:
print(gamma)
t = time()
rp_vals, rp_vecs, modes = rp_solve(h, J_n, gam=gamma, cache_dir=CACHE)
times.append(time() - t)
sp_vals, sp_vecs = solve(h, J_n, gamma=gamma)
SP_E.append(sp_vals)
RP_E.append(rp_vals)
LSP = min(len(x) for x in SP_E)
L = min(LSP, min(len(x) for x in RP_E))
SP_E = np.array([x[:L] for x in SP_E])
RP_E = np.array([x[:L] for x in RP_E])
plt.figure("spectrum")
plt.plot(gammas, SP_E, linewidth=2)
plt.plot(gammas, RP_E, "x", markersize=8, markeredgewidth=2)
plt.xlabel("Gamma", fontsize=FS)
plt.ylabel("Energy", fontsize=FS)
plt.title("Circuit Spectrum", fontsize=FS)
plt.show(block=False)
plt.figure("runtimes")
plt.plot(gammas, times, "b", linewidth=2)
plt.xlabel("Gammas", fontsize=FS)
plt.ylabel("Runtime (s)", fontsize=FS)
plt.title("RP-Solver runtime", fontsize=FS)
plt.show()
