<jupyter_start><jupyter_text>The scaling of operational entanglement with the partition size<jupyter_code>import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline 
%config InlineBackend.figure_format = 'retina'

data = np.loadtxt('200k_alpha2.dat')

#partition size
l = np.concatenate((data[0:6:1,0],data[7:20:3,0],data[22::4,0]),axis=0)
#the variance
sigma2 = np.concatenate((data[0:6:1,5],data[7:20:3,5],data[22::4,5]),axis=0)
#Second Renyi spatial entanglement entropy
S2 = np.concatenate((data[0:6:1,3],data[7:20:3,3],data[22::4,3]),axis=0)
#Second Renyi spatial entropy of the probability distribution P_n
H2 = np.concatenate((data[0:6:1,6],data[7:20:3,6],data[fd00:c2b6:b24b:be67:2827:688d:e6a1:6a3b,6]),axis=0)
#Second Renyi operational entanglement entropy
Sop2 = np.concatenate((data[0:6:1,10],data[7:20:3,10],data[fd00:c2b6:b24b:be67:2827:688d:e6a1:6a3b,10]),axis=0)
# chord length
lc=np.log(200000/np.pi*np.sin(l/200000*np.pi))
plt.style.reload_library()

with plt.style.context('aps.mplstyle'):
    figpn = plt.figure()
    #Principal Plot
    axpn= figpn.add_subplot(111)
    axpn.set_xlabel(r'$\ln(\sigma^2)$')
    axpn.plot(np.log(sigma2),S2-Sop2,ms=4.0, mew=0.7, color='#e95c47',marker='s',    mfc='None',linewidth = 1.0,linestyle='None',label=r'$\Delta S_{2}$')
    axpn.plot(np.log(sigma2),H2,ms=4.0, mew=0.7, color='#4173b3',marker='o',    mfc='None',linewidth = 1.0,linestyle='None',label=r'$H_{2}$')


    axpn.legend(loc=(0.7,0.4),frameon=False, numpoints=1)
    axpn.set_xlim(-1.43,0.37)
    axpn.set_ylim(0.6,1.45)
    axpn.text(-.6,.8,r'$N=10^5$')



    left, bottom, width, height = [0.27, 0.59, 0.25, 0.25]
    #Inset Plot
    axpn1 = figpn.add_axes([left,bottom,width,height])
    
    axpn1.plot(lc[::5], sigma2[::5], mec='#000000',ms=3.0, mew=0.7, marker='o',mfc='#000000',linewidth = 0.7,linestyle='-',color='#000000')
    axpn1.set_xlabel(r'$\ln(\ell_c)$', labelpad=0.1)
    axpn1.set_ylabel(r'$\sigma^2$', labelpad=0.1)
    axpn1.set_yticks([0.25,0.75,1.25])
    axpn1.set_xticks([1,5,10])
    axpn1.set_xlim(-2,12.5)
    axpn1.set_ylim(.1,1.51)
    axpn1.tick_params(labelsize=7)



    plt.savefig('FiniteSizeScalingofDS2.pdf')
    plt.savefig('FiniteSizeScalingofDS2.png')
    plt.show()<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.21041023378914867, 'fraction_numerical': 0.11248345831495368, 'mean_word_length': 5.8108108108108105, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '244718', 'license': 'MIT', 'n_tokens_mistral': 1138, 'n_tokens_neox': 1038, 'n_words': 115, 'path': 'FiniteSizeScalingofDS2/FiniteSizeScalingofDS2.ipynb', 'repo_name': 'DelMaestroGroup/AccessibleEntanglementFreeFermions', 'size': '2199'}