cs = ["darkturquoise", "darkorange", "limegreen", "crimson"]
for j, (c, S) in enumerate(zip(cs, Skey)):
sim = select(L, S, IC, V="H", BC="0")
h5file = sim["h5file"]
d = h5file["cut_half"][:]
for ti, rho in enumerate(d[100:101]):
spec, vecs = eigh(rho)
fig, axs = plt.subplots(1, 2, figsize=(6, 3))
print(renyi_entropy(rho))
axs[0].set_title("spectrum")
axs[0].semilogy(spec, color=c, marker="o")
axs[1].set_title("column vector magnitude")
axs[1].imshow(np.abs(vecs), cmap="gist_gray_r")
fig.suptitle("$T_{%d}$"%S)
multipage("figures/figure4/eigenRDM.pdf")
plt.close("all")
print("done")
if __name__ == "__main__":
L = 18
IC = "c1_f0"
Skey = [13, 14, 1, 6]
cs = ["darkturquoise", "darkorange", "limegreen", "crimson"]
fig, axs = plt.subplots(1, 1, figsize=(4, 3), sharex=False)
fig2, axs2 = plt.subplots(1, 1, figsize=(3, 2), sharex=True)
fig2.subplots_adjust(left=0.2, bottom=0.2, hspace=0.1)
fig3s = []
for j, (c, S) in enumerate(zip(cs, Skey)):
sim = select(L, S, IC, V="H", BC="0")
for t in [10, 50, 100, 500, 1000]:
fig, axs = plt.subplots(1, 8, figsize=(4.75, 0.8))
for col, R in enumerate(Rkey):
sim = select(L=18, S=R, IC="c1_f0", V="H", BC="0")
if sim is None:
print("No sim!")
L = sim["L"]
h5file = sim["h5file"]
Ms = h5file["MI"]
M = Ms[t]
draw_MI(M, axs[col], layout=layout)
axs[col].set_title(r"$T_{%d}$" % R)
for col, statestr in enumerate(["C6-3", "GHZ", "W", "R"]):
state = make_state(L, statestr)
M = ms.get_MI(state, order=1)
draw_MI(M, axs[4 + col], layout=layout)
if statestr[0] == "C":
axs[4 + col].set_title(ket("C"))
else:
axs[4 + col].set_title(ket(statestr))
C = ms.network_clustering(M)
Y = ms.network_disparity(M)
print(statestr, " C:", C, " Y:", Y)
fig.subplots_adjust(wspace=0.4, top=0.7, left=0.05, right=1, bottom=0)
plot_fname = f"figures/figure3/{layout}_layout_medclip.pdf"
print(plot_fname)
multipage(plot_fname, clip=False)
ax2.set_ylabel('$\\overline{S}_{\\ell}$')
ax2.xaxis.set_major_locator(MaxNLocator(integer=True))
ax4.plot(ells,
sbd,
color=lines[IC]['c'],
marker=lines[IC]['m'],
label=lines[IC]['name'])
ax4.set_xlabel('$\\ell$')
ax4.set_ylabel('$\\Delta S_{\\ell}$')
ax4.xaxis.set_major_locator(MaxNLocator(integer=True))
ax3.semilogx(sb[:, int(L / 2)],
color=lines[IC]['c'],
lw=1,
label=lines[IC]['name'])
ax3.set_ylabel('$S_{L/2}$')
ax3.set_xlabel('Iteration')
sb_avg = np.array(sb_avg)
sb_std = np.array(sb_std)
fig0.suptitle('$\\langle \\sigma_z \\rangle$')
fig.suptitle('$S_{\\ell}$')
ax4.legend(framealpha=0.5)
ax3.legend(framealpha=0.5)
ax2.legend(framealpha=0.5)
fig0.tight_layout()
fig0.subplots_adjust(top=0.99)
fig.tight_layout()
fig.subplots_adjust(top=0.99)
qca.multipage(plot_fname)
print('plot saved to ', plot_fname)
def simple_plot(plot_fname):
figa, axa = plt.subplots(1, 1, figsize=(1.5, 1.3))
for o, (color, S) in enumerate(zip(cs, Skey)):
for IC in ICkey:
sb_avg = []
sb_std = []
sb_res = []
ns = []
for L in Lkey:
ells = np.arange(L - 1)
dells = np.linspace(0, L - 2, 100)
sim = select(L, S, IC, "H", "1-00")
if sim is None:
print("No sim!")
continue
S = sim["S"]
L = sim["L"]
IC = sim["IC"]
h5file = sim["h5file"]
sb = h5file["sbond-2"][:]
sba = np.mean(sb[100:], axis=0)
sbd = np.std(sb[100:], axis=0)
sb_avg += [sba[L // 2]]
sb_std += [sbd[L // 2]]
axa.set_xlabel("$\\ell$")
axa.set_ylabel("Iteration")
# axa.label_outer()
func, popt, pcov = fit_page(sba)
sb_res += [(func(ells) - sba) ** 2]
if L in (18,):
ls = lss[L]
axa.fill_between(
ells,
sba + sbd,
sba - sbd,
facecolor=color,
alpha=0.4,
zorder=o
)
axa.scatter(
ells,
sba,
color=color,
marker="o",
s=2,
zorder=o
)
axa.plot(
dells,
func(dells),
color=color,
ls=ls,
lw=1,
label="$R={}$".format(S),
zorder=o
)
axa.set_xlabel("$\\ell$")
axa.set_ylabel("$\\overline{S}_{\\ell}$")
axa.xaxis.set_major_locator(MaxNLocator(integer=True))
axa.set_xticks([0, 8, 16])
axa.set_xticklabels(["$1$", "$9$", "$17$"])
axa.set_yticks([0, 4, 8])
figa.subplots_adjust(left=0.35, bottom=0.32, top=1, right=0.95)
#axa.legend(
# loc=2,
# fontsize=8,
# handlelength=1,
# labelspacing=0.2,
# handletextpad=0.2,
# frameon=False,
#)
qca.multipage(plot_fname, clip=False)
ax3.set_ylabel("RSS", fontsize=9, labelpad=-11)
ax3.set_xlabel("$L$")
ax3.set_yticks([0, 0.4])
ax3.set_xticks([10, 14, 18])
ax.set_yticks([0, 4, 8])
ax.set_xticks([0, 4, 8, 12, 16])
ax.set_xlim(right=17)
ax.set_ylim(top=11)
ax.legend(
loc=2,
fontsize=9,
handlelength=1,
labelspacing=0.2,
handletextpad=0.2,
frameon=False,
)
axins1.set_xticks([1, 1000])
axins1.set_xticklabels([0, 3])
axins1.set_yticks([0, 8])
axins1.set_xlabel(r" $\log(t)$", fontsize=9, labelpad=-6)
axins1.set_ylabel("$S_{L/2}$", fontsize=9, labelpad=-2)
axins1.tick_params(axis="both", labelsize=9)
axins1.axvline(100, color="k", lw=0.5)
axins1.patch.set_alpha(1)
qca.multipage(plot_fname, clip=False)
print("plot saved to ", plot_fname)
plt.close("all")
simple_plot("figures/figure4/pagecurves-simple_V1.pdf")
axs[1].imshow(np.abs(A), cmap="gray_r")
axs[0].grid(True)
axs[1].grid(True)
axs[0].set_xticks([0, 5, 10, 15])
axs[1].set_xticks([0, 5, 10, 15])
axs[2].plot(eigsH2, 'o', ms=9)
axs[2].plot(eigsA, 'o')
axs[0].set_title('hamiltonian:\n R={}, V={}'.format(
R, V),
color='C0')
axs[1].set_title('symmetry:\n R={}, V={}'.format(
R2, B),
color='C1')
axs[2].set_title('spectra')
if make:
multipage(
"figures/hamiltonian/symmetries/rule{}_symm.pdf".format(R))
#plt.show()
plt.close("all")
#U = expm(-1j * dt * H)
#eigs = eigvalsh(H)
#eigs = np.sort(eigs)
#np.save("eigs/R{}_V{}_L{}.npy".format(R, V, L), eigs)
#UHviz(U, H, R)
#spectrum_viz(eigs)
##time_evolve(U)
#multipage("figures/hamiltonian/rule{}_continuous.pdf".format(R))
#plt.close('all')
#print()