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g2c_curves • Show schema
{'Lhash': '479308955823773820', 'abs_disc': 995328, 'analytic_rank': 1, 'analytic_rank_proved': False, 'analytic_sha': 1, 'aut_grp_id': '[2,1]', 'aut_grp_label': '2.1', 'aut_grp_tex': 'C_2', 'bad_lfactors': '[[2,[1]],[3,[1]]]', 'bad_primes': [2, 3], 'class': '331776.g', 'cond': 331776, 'disc_sign': 1, 'end_alg': 'Q', 'eqn': '[[0,3,0,-3,0,1],[]]', 'g2_inv': "['20511149/4','5926527/32','-14297/64']", 'geom_aut_grp_id': '[8,3]', 'geom_aut_grp_label': '8.3', 'geom_aut_grp_tex': 'D_4', 'geom_end_alg': 'M_2(Q)', 'globally_solvable': 1, 'has_square_sha': True, 'hasse_weil_proved': False, 'igusa_clebsch_inv': "['58','28','856','16']", 'igusa_inv': "['348','4374','-1836','-4942701','995328']", 'is_gl2_type': False, 'is_simple_base': True, 'is_simple_geom': False, 'label': '331776.g.995328.1', 'leading_coeff': {'__RealLiteral__': 0, 'data': '2.446247875092303389128401197786137138566810328698', 'prec': 167}, 'locally_solvable': True, 'modell_images': ['2.90.3', '3.540.7'], 'mw_rank': 1, 'mw_rank_proved': True, 'non_solvable_places': [], 'num_rat_pts': 4, 'num_rat_wpts': 2, 'real_geom_end_alg': 'M_2(R)', 'real_period': {'__RealLiteral__': 0, 'data': '6.3465523385225559140296570231', 'prec': 100}, 'regulator': {'__RealLiteral__': 0, 'data': '0.770890317959', 'prec': 47}, 'root_number': -1, 'st_group': 'J(E_4)', 'st_label': '1.4.E.8.3a', 'st_label_components': [1, 4, 4, 8, 3, 0], 'tamagawa_product': 2, 'torsion_order': 2, 'torsion_subgroup': '[2]', 'two_selmer_rank': 2, 'two_torsion_field': ['4.0.432.1', [3, 0, -3, 0, 1], [4, 3], False]} -
g2c_endomorphisms • Show schema
{'factorsQQ_base': [['1.1.1.1', [0, 1], -1]], 'factorsQQ_geom': [['1.1.1.1', [0, 1], 1]], 'factorsRR_base': ['RR'], 'factorsRR_geom': ['M_2(RR)'], 'fod_coeffs': [9, 0, 0, 0, 3, 0, 0, 0, 1], 'fod_label': '8.0.47775744.1', 'is_simple_base': True, 'is_simple_geom': False, 'label': '331776.g.995328.1', 'lattice': [[['1.1.1.1', [0, 1], [0, 0, 0, 0, 0, 0, 0, 0]], [['1.1.1.1', [0, 1], -1]], ['RR'], [1, -1], 'J(E_4)'], [['2.0.4.1', [1, 0, 1], [0, 0, '-2/3', 0, 0, 0, '-1/9', 0]], [['2.0.4.1', [1, 0, 1], -1]], ['CC'], [1, -1], 'E_4'], [['2.0.3.1', [1, -1, 1], [0, 0, 0, 0, '-1/3', 0, 0, 0]], [['1.1.1.1', [0, 1], -1]], ['RR'], [1, -1], 'J(E_2)'], [['2.2.12.1', [-3, 0, 1], [0, 0, 0, 0, 0, 0, '1/3', 0]], [['1.1.1.1', [0, 1], -1]], ['RR'], [1, -1], 'J(E_2)'], [['4.0.144.1', [1, 0, -1, 0, 1], [0, 0, '-1/3', 0, 0, 0, '-2/9', 0]], [['2.0.4.1', [1, 0, 1], -1]], ['CC'], [1, -1], 'E_2'], [['4.0.1728.1', [12, 0, -6, 0, 1], [0, 1, 0, '-2/3', 0, 0, 0, '-1/9']], [['2.2.8.1', [-2, 0, 1], -1]], ['RR', 'RR'], [1, -1], 'J(E_1)'], [['4.0.1728.1', [12, 0, -6, 0, 1], [0, 0, 0, '1/3', 0, '-1/3', 0, '-1/9']], [['2.2.8.1', [-2, 0, 1], -1]], ['RR', 'RR'], [1, -1], 'J(E_1)'], [['4.2.6912.1', [-3, 0, 0, 0, 1], [0, -1, 0, 0, 0, '-1/3', 0, 0]], [['1.1.1.1', [0, 1], -1], ['1.1.1.1', [0, 1], -1]], ['RR', 'RR'], [2, -1], 'J(E_1)'], [['4.2.6912.1', [-3, 0, 0, 0, 1], [0, 0, 0, '1/3', 0, 0, 0, '2/9']], [['1.1.1.1', [0, 1], -1], ['1.1.1.1', [0, 1], -1]], ['RR', 'RR'], [2, -1], 'J(E_1)'], [['8.0.47775744.1', [9, 0, 0, 0, 3, 0, 0, 0, 1], [0, 1, 0, 0, 0, 0, 0, 0]], [['1.1.1.1', [0, 1], 1]], ['M_2(RR)'], [4, 0], 'E_1']], 'ring_base': [1, -1], 'ring_geom': [4, 0], 'spl_facs_coeffs': [[[144, 0, 160, 0], [0, -3456, 0, -1792]], [[144, 0, 160, 0], [0, 3456, 0, 1792]]], 'spl_facs_condnorms': [2304, 2304], 'spl_fod_coeffs': [-3, 0, 0, 0, 1], 'spl_fod_gen': [0, 0, 0, '1/3', 0, 0, 0, '2/9'], 'spl_fod_label': '4.2.6912.1', 'st_group_base': 'J(E_4)', 'st_group_geom': 'E_1'} -
g2c_ratpts • Show schema
{'label': '331776.g.995328.1', 'mw_gens': [[[[-1, 1], [1, 1]], [[-1, 1], [0, 1], [0, 1], [0, 1]]], [[[0, 1], [1, 1]], [[0, 1], [0, 1], [0, 1], [0, 1]]]], 'mw_gens_v': True, 'mw_heights': [{'__RealLiteral__': 0, 'data': '0.7708903179586090232191398862300', 'prec': 110}], 'mw_invs': [0, 2], 'num_rat_pts': 4, 'rat_pts': [[0, 0, 1], [1, -1, 1], [1, 0, 0], [1, 1, 1]], 'rat_pts_v': True} - g2c_galrep • Show schema
- g2c_tamagawa • Show schema
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g2c_plots • Show schema
{'label': '331776.g.995328.1', 'plot': 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pWmTSP8If4QAAEAOAyFhbaVy7HHSlOmSMnJ0siR0pdfSr/8JZs6Iz4xBAwAwCF6%2B23pppukr7%2B26x49bK7fCSe4WxdwMPQAAgBQSStX2ty%2Bs86y8Ne4se3pt3Ah4Q/eQAAEAKCCtm%2BXbr3V9vSbOVOqUcPO8v36a%2Bmaa6QkfqvCIxgCBgDgIAoLpaeflu69V9q61e47%2B2zpkUds7h/gNQRAAADKUVpqCzv%2B8Afpu%2B/svvbtpYcftuFfwKvorPaY3NxcZWVlKTs72%2B1SACBhOY707rt2Xu%2Bll1r4a9JEevZZaflywh%2B8L%2BA4juN2Eai8cDisYDCoUCikzMxMt8sBgITx0UfS6NHS3Ll2XaeOdPvt0i232NtAImAIGAAASUuWSHffLb35pl2npEg33mjDv40bu1sbUNUIgAAAX1u82BZ3zJpl18nJtqL3rrukVq1cLQ2oNgRAAIDvOI60YIF0//3S7Nl2X3KydOWVFvzatnW3PqC6EQABAL5RWiq98Yb0l7/YXD/Jgt%2BQITbv7%2Bij3a0PiBUCIAAg4e3aJU2YIP31r9KKFXZfaqp07bW2wKN1a3frA2KNAAgASFg//WQbOD/zjLR5s90XDErDhkkjR0pNm7pbH%2BAWAiAAIKE4jvTBB1JurvTqq1Jxsd3fqpV0003SdddJ7J4FvyMAAgASwvbt0sSJ1tv3xRfR%2B3v1km6%2BWRo0yM7uBUAABAB4WGmptHCh9Pzz1tu3a5fdn54uXX65lJMjde7sbo1APCIAAgA8Z%2BVKW9Txz39K338fvb99e%2Bn666WrrpLq1nWvPiDeEQABAJ7w44/SlCnS5Ml2akdERoZ0ySXSr34lde0qBQLu1Qh4BQEQABC3Vq2SXntNmjpV%2BvDD6P3JyVLfvrZ/3%2BDBUq1arpUIeBIBEPAgx5F275Z27Ii2/Hxp505ru3ZZKyiw9ysokAoLrRUV2arISCstlUpK7NZx9v%2B3kpKiLTnZJtFHWs2a1lJSbE%2B1lBQpLc1aerrd1qplLT1dql3bWp069r701GBfpaXWu/fGG9LMmdKnn%2B79eM%2Be0qWXShddJDVp4k6NQCIgAAIuKiqyvck2bbK2ZUu0bd1qbds2W90YCkVbOGyhzctq1LChuzp17DYzM9qCQWt160ZbvXrRVr%2B%2B3aamuvxJOI40d65NSGvaVDrnHEvEqJS1a6X33pPeflt6553ofn2S/eHRu7f0y19KF1wgNW/uXp1AIiEAAtWgoMA2oP3xR/vltnattG6dtfXro23r1sP/t2rVshAV6WmL9LZFeuDS0qy3rWyL9OAlJ1sr28sX6ZVznGgr20tYtvewqCjas1hYGO1xjLRIT2R%2BfvS2sNCev7jYwu22bYf%2BudeubWGwQQOpYcPobdnWqFG0NWxYhfls2TLpssuix0pI1iX1zDO23wjK9eOPtnJ3wQLLz2W/hJL9EdC/v3TeedKAAfa6AqhaAcc50KAP4l04HFYwGFQoFFImO5rG3I4dtvJw1aro7Q8/SKtXS2vWSBs2VPy5kpLsF1yjRnsHmUhPV/361gMW6RGL9JJlZFgASk6urs%2ByehQX7z10nZdnLRy2VranMxSy3s/t26NhcetWuz7U/7nq1ZMaNz5wa9IketukiX2dDzhMvX691KGDddXuq2ZNSzbduh1agQkmP19avlz697%2BlxYvt/N3Vq/d%2Bn6QkqUsXqV8/6cwzpR496EgFqhs9gEA58vKkr7%2B2tnKl9M030rff2u3GjQf/%2BNRU6cgjbciqWbNoa9rUWiRkNGhgvwD9okaN6LDuoSottXC4devew%2BabN%2B/fyg6vl5ZGg%2BS%2BvU4Hkpq6dyBs3Nheu/OWPqvuBwp/knWLPvSQrVrwkdJS%2ByPoyy9tE%2BbPPrNO0hUr7LGykpKkE06QTjlF6tPHWr167tQN%2BBU9gB5FD2DV2bRJ%2Bs9/7BfXl19KX31lbe3an/%2B4evXsAPmjjrLbli3tqKmWLS34NWzIIod4UlJigXHTJgvwZduGDfvf7thR/nMtVC/10gflPr4zuY6GXpC33/BzpHc30tLTq%2BETrUb5%2BTZ8%2B8MP1uv93Xf2R1Hkj6TIJsz7OuIIKTtbOvlkqXt3u61TJ6alA9gHPYAek5ubq9zcXJV4fQWAC3bvtqD36afWO/H559Y2bSr/Yxo3lo45RvrFL6Sjj462Nm3YZNZrkpOjYSwr6%2BDvv3NnNAxGWuS6weQkaXP5H1tUkqRXXjn4v5GeHl3QUq9edLFLZBFMZKg/slgmsoo6Ms8zLS26%2BjqyIjsyr7PsXM7IHM7i4r3nau7caaEuPz86/B7pIY30nkY%2B959%2BsqH3n5OSIrVrZ5sxd%2BxovXydO1sABBBf6AH0KHoAf15eng0/ffKJtHSpvf3VVwdeORsIWA9eVpa1Y4%2BNNoalcEB/%2BYs0alS5D6/qfpmmXzJpz/BzJExt3hwdrvbq33B16lhPd6tW9odQ27b2R1G7dvZzxFm7gDcQAD2KABhVWGg9eosX20TzJUss7B3oO7tBA%2Bn446VOnax16GChr3bt2NcND9uyxbq41q3b/7G0NFvpcMIJ5X6441iPW2S7n0ivW2TBS9ntfsLhvfd6jKyo3rUrusfjoYjs1RjZlzEjI7rQKLKyulGj6BzIZs1sPmsweGj/HoD4QgD0KD8HwI0b7USASPv44wP/EjzySOnEE211YefO1po3Z14eqshXX9kxFB9/HL2vTRvp2WftiIoYcZzoljxFRdazWFKy9x9AkWHhyObdbMINgADoUX4KgD/8IM2bZ/uGLVxoE873Va%2BeTSzv2tVuTzqJUwIQI0uX2jflEUfYslaSFQAPIAB6VCIHwJ9%2BslMB5syx4Ldq1f7v0769HQnVo4etKjzmGH7vAgBQUUzXhevy8%2B00gNmzrf33v3s/npxsPXp9%2BtiRUD17sjgDAIDDQQBEzDmOTZ%2BaNUt6800b1o0cDyZZT96JJ0qnn26tZ0/2DAMAoCoRABETRUUW9KZPl954wzaQLeuoo%2Bzsz/79pdNOs1WIAACgehAAUW127pTeekt6/XULfWU3kU1JkU49VTrnHOmss2yjZebwAQAQGwRAVKmdO21o95VXpH/9y64jGjWSzjvPWt%2B%2BDOsCAOAWAiAOW3Gx9M470qRJNsRb9gzVVq2kCy6QBg2yFbvJye7VCQAADAEQh2z5cmn8eGnyZNucOeKoo6SLLpIuvtgWczC0CwBAfCEAolK2bZMmTpT%2B9jfp00%2Bj9zdqJF16qXTZZVK3boQ%2BAADiGQEQB%2BU4ds7uM89IL79s549KtpDj/POlq6%2B21bs1a7pbJwAAqBgCIMpVUGCB74knpE8%2Bid7fsaN03XXSlVeyXQsAAF5EAMR%2BtmyRnn5aGjtW2rDB7ktNlS65RLrxRjtvlyFeAAC8iwCIPdaulR5%2BWBo3Lrp9S/PmUk6O9OtfSw0bulsfAACoGgRA6McfpTFjbGFH5Ei2E06Qbr/dVvMytw8AgMRCAPSxzZulBx6QnnrK5vtJUu/e0ujRtqiDYV4AABITAdBjcnNzlZubq5KSkkN%2Bjt27pccft/AXDtt9vXtL995rx7MBAIDEFnAcx3G7CFReOBxWMBhUKBRSZmZmhT9u5kxp5Ejpu%2B/s%2BoQTpL/8hR4/AAD8hB5An1i7Vho%2BXJo2za6bNbN5f1deKSUluVsbAACILX71JzjHsePasrIs/NWoId1xh7RihXTVVYQ/AAD8iB7ABLZtm23fMnWqXZ98sq307djR3boAAIC76P9JUEuXSp07W/irWdOGez/8kPAHAADoAUxIr7xi5/Pu3i21aWPXJ57odlUAACBe0AOYYB591I5s271bGjDAzvAl/AEAgLIIgAnkgQekW26xt2%2B%2BWZo%2BXapb192aAABA/CEAJoixY%2B0ED0n685%2BtJzA52d2aAABAfGIOYAJ4803pppvs7Xvuke6809VyAABAnKMH0ON%2B%2Bsk2c3Yc2/Llj390uyIAABDvCIAe99vfSlu32kKPJ5/kODcAAHBwnAXsUZGzgKWQatbM1PLldtoHAADAwdADmAB%2B8xvCHwAAqDgCoNesXi3l5Kik5VGSpDd1lu5q/5q7NQEAAE9hCNhLVq6UevWSNm5UWJINAEuZknTvvdJdd7laHgAA8AYCoJecf740Y4Yk7R8Ak5Kkb76RWrd2rz4AAOAJ7AN4GBzHUV5eXkz%2BrYKfflLKG28ossg3vM%2BtSkulceOkUaNiUg8AAF6XkZGhgE%2B3z6AH8DBEV%2BICAACvCYVCyszMdLsMVxAAD0NFegCzs7O1ZMmSw/63CrZuVUpWlgK7dkmynr8Wktbof0PAkh0GnJNz2P%2BWVHV1x/K5vVhzOBxWixYttGbNmmr5T4ivdWyeuzpfRy9%2BPbz43F79WazO5/ZizZV9Hf3cA8gQ8GEIBAIH/QZLTk6umv9MMjPtyI/nntv77v811aol3XCDvV8VqLK6Y/jcXqw5IjMz01NfE69%2Brb34Onr16%2BHV5/baz2J1PrcXa46ortcxkbANTDXLqaIeOUnS//2fHfmxr5QUacIEqX79KvunqrTuGD23F2uubnytY/fc1cWrXw%2BvPnd18eLXw4s1o%2BIYAvaa3bulyZO1ftx4HbFogR7QjfrlzN%2Bq3bnHuF0ZDkFkHqmf56EkAl5H7%2BM1TAy8jhWXfM8999zjdhGohBo1pM6dtev8c/XQQw/pPb2n9UXNdPHFbheGQ5WcnKxTTz1VNWowI8PLeB29j9cwMfA6Vgw9gB4V%2BSsnEAjJcTL1zjtSv35uVwUAALyAOYAed/31djt0qLRpk7u1AAAAbyAAetzdd0vt2klr10oXXSQVFLhdEQAAiHcEQI%2BrXVuaOlXKyJDmz7edYoqL3a4KAADEMwJgAmjf3kJgSor06qvSZZfREwgAAMpHAEwQ/fpZ%2BIuEwHPOkbZtc7sqSNJTTz2l1q1bKy0tTSeeeKIWLlxY7vuOHz9egUBgv7Z79%2B4YVoyKWrBggc477zw1a9ZMgUBA06ZNc7sklKOyr9W8efMO%2BLP41VdfxahiVMaYMWOUnZ2tjIwMNW7cWIMGDdKKFSvcLiuuEQATyHnnSW%2B8IdWpI82ZI3XtKv3nP25X5W8vv/yyRo4cqdGjR2vZsmXq3bu3zj77bK1evbrcj8nMzNS6dev2amlpaTGsGhWVn5%2Bv448/XmPHjnW7FBzEob5WK1as2Otn8Zhj2HM1Hs2fP185OTlatGiRZs%2BereLiYvXv31/5%2Bflulxa32AbGo35us8tPP5UGDpRWr7YT4saOla65RvLpcYeu6tq1q7p06aKnn356z33HHXecBg0apDFjxuz3/uPHj9fIkSO1ffv2WJaJKhAIBPT6669r0KBBbpeCg6jIazVv3jyddtpp2rZtm%2BrWrRvD6lAVNm3apMaNG2v%2B/Pk65ZRT3C4nLtEDmICOP176%2BGOpb19p507p2mtthTDbxMRWYWGhPvnkE/Xv33%2Bv%2B/v3768PP/yw3I/bsWOHWrVqpSOPPFLnnnuuli1bVt2lAihH586ddcQRR%2BiMM87Q3Llz3S4HFRQKhSRJ9avwiNREQwBMUI0aSW%2B9JT3wgB0eMnWqlJUlTZwo0ecbG5s3b1ZJSYmaNGmy1/1NmjTR%2BvXrD/gxxx57rMaPH68ZM2Zo8uTJSktLU8%2BePbVy5cpYlAzgf4444giNGzdOU6dO1WuvvaZ27drpjDPO0IIFC9wuDQfhOI5uueUW9erVSx06dHC7nLjFOSkJLDlZGjVKOuss6eqrpc8/t21iXnhBevJJ6bjj3K7QHwL7jL07jrPffRHdunVTt27d9lz37NlTXbp00ZNPPqknnniiWusEENWuXTu1a9duz3X37t21Zs0aPfzwwwwpxrnhw4frs88%2B0/vvv%2B92KXGNHkAf6NzZhoTvu09KS5Pee0/q1Em6%2BWZp82a3q0tcDRs2VHJy8n69fRs3btyvV7A8SUlJys7OpgcQiAPdunXjZzHOjRgxQjNmzNDcuXN15JFHul1OXCMA%2BkRKijR6tK0KPv982yz6iSektm1tmHjHDrcrTDwpKSk68cQTNXv27L3unz17tnr06FGh53AcR8uXL9cRRxxRHSUCqIRly5bxsxinHMfR8OHD9dprr2nOnDlq3bq12yXFPYaAfaZNG2naNOndd6XbbrMVw6NHS489Jt1xh3TjjXa6CKrGLbfcoiFDhuikk05S9%2B7dNW7cOK1evVrDhg2TJF111VVq3rz5nhXBf/rTn9StWzcdc8wxCofDeuKJJ7R8%2BXLl5ua6%2BWmgHDt27NA333yz5/r777/X8uXLVb/Zy1RiAAAZVklEQVR%2BfbVs2dLFyrCvg71Wo0aN0tq1a/Xiiy9Kkh577DEdddRRat%2B%2BvQoLCzVhwgRNnTpVU6dOdetTwM/IycnRpEmTNH36dGVkZOwZeQkGg0pPT3e5ujjlwFPGjh3rHHfccc4vfvELR5ITCoUO%2BblKShxnwgTHadvWcWxpiOM0bOg4993nOFu3VmHRPpebm%2Bu0atXKSUlJcbp06eLMnz9/z2N9%2BvRxrr766j3XI0eOdFq2bOmkpKQ4jRo1cvr37%2B98%2BOGHLlSNipg7d64jab9W9jVFfDjYa3X11Vc7ffr02fP%2BDz74oNO2bVsnLS3NqVevntOrVy/nX//6lzvF46AO9NpKcl544QW3S4tb7APoUT%2B3D2BlFRVJ//yndP/90nff2X116ki//rXNE2zVqgoKBgAAcYM5gFDNmrZX4IoV0oQJUocONifw0UdtyPjCC6X589k%2BBgCAREEPoEdVZQ/gvhzH9hB85BGbKxjRvr00bJhtJcPG%2BAAAeBcB0KOqMwCW9cUXdpTcP/9pp4pIUnq6nSzyq19JvXtzxBwAAF5DAPSoWAXAiO3bLQSOG2ehMKJNG%2Bmqq6QhQ%2BxtAAAQ/wiAHhXrABjhONKiRdLzz0svv7z3/oHdu0uXXSZdfLFUwX2OAQCACwiAHuVWACwrP196/XXrGXz3Xam01O5PSpJOPdWC4KBBhEEAAOINAdCj4iEAlrVunfUITp4s/fvf0fuTkqRevaTBgy0MHnWUayUCAID/IQB6VLwFwLK%2B/1565RXp1VftDOKyOnaUBg6Uzj1Xys6WkpPdqREAAD8jAHpUPAfAsn74wY6ee/11aeHC6DCxJDVsKJ11lnT22VK/flKjRu7VCQCAnxAAPcorAbCsLVukWbOkmTOlt9%2BWwuHoY4GA1KWLBcF%2B/aQePaS0NPdqBQAgkREAPcqLAbCsoiLpgw%2BkN9%2B0Tac/%2B2zvx1NTpZ49pdNPtwUl2dlSSoorpQIAkHAIgB7l9QC4r3XrbCXx7Nl2u27d3o%2Bnp9s2M717W%2Bva1c4rBgAAlUcA9KhEC4BlOY701VfSnDnS3Ll2DvHmzXu/T3KydPzxNlTcvbvUrZvUujWnkgAAUBEEQI9K5AC4L8eRvvzSFpFE2po1%2B79fw4bSySdby86WTjpJatw49vXCR/LybO%2BjlSulpk2lK66wWwCIcwRAj/JTADyQNWukDz%2B0tmiRtGyZzSvcV/PmtrikSxepc2fphBOkli3pKUQVmDXLjr4pu5qpZk3poYekm2%2Bu8n/OcaTCQjuTe%2BdOadcuafduqaDA7i8slIqLpZISa5H/2QMB248zOVmqUcPm0qam2iKr9HSpdm2bTlGrFj8XgJ8QAD3K7wFwX7t3S8uX2ybUH38sLVkirVgR/SVYVjAodepkrUMHqX17a/Xrx75ueNS339o3z%2B7dB3581izb32gfu3bZdIYtW6xt3Rpt27fv3UIhy5Z5eXbk4o4dFvCqS1KSlJkp1atnrWFDa40bW6fmEUfYH1RHHml/RKWnV18tAKofAdCjCIAHl5dnPYORtny5DSUfqKdQsl9yWVnSccdJxx5rrV07%2B6WXlBTb2hHnbr1VeuSRch9e0bKv7jtltjZtkjZtstC3ebP13FWF5GQLYGlp1puXkmKtRg1rSUnR71nHsf03S0rse7%2BoyHoNd%2B%2BO9iQeym%2BBJk1s3m3bttIxx9jPSuRnhnAIxD8CoEcRAA9NYaEtMPn0U%2Bnzz6UvvpD%2B8x9p9eryPyY9XTr6aGvHHGO/8Nq2tV9%2BLVrYqB8Sg%2BNYz9uGDdLGjXZbtkXuG7u0u7oULCr3efJVS3WUf8DHatSQGjSwVr9%2BtNWrJ9WtG22ZmdGWkWHDtLVrW6vK7znHsSAYDtvnvm2b9Uhu2WLhdcMGaf16W5m/dq1Nv9ixo/znS0qS2rSxHvYTTrCpF126SM2aVV3NAA4fAdBjcnNzlZubq5KSEn399dcEwCqSl2e9g//9r7WvvrIh5G%2B//flht%2BRkGxI76iipVSsbGmvZ0oLhkUfabWYmc6vctGuX9vTEbdpkIW7jxujbkWAXebuw8ODP%2Ba7O0BmaU%2B7j%2BekN9NSfNqtRIxtGjdw2bOj97wfHsZD4/ffSd9/Zz8jKlfYz89//2mMH0qyZLdDq1s32%2BDzpJDZ7B9xEAPQoegBjo6hIWrXKfsF98421b7%2B1tmqVDaUdTO3a9suvWTObR9W0qbUmTaw1bmwBoVEjhs5%2BTmmp9VJFeqgiLTKfbsuW6Py6zZujQ6/5B%2B6I%2B1kZGfa6RF6jsq9VkybS8R8%2BraMf%2BU35TzBsmPT004f%2ByXqU41iI/uIL29x9%2BXJp6VILhmWPgZRsyLprV6lPH%2Bm00zj9B4g1AqBHEQDdV1pqQ2OrVln74QcbSl6zJtrK6w0pT61a0aHByG1kUn4waK3ssOC%2BQ4O1a9ucsHjpYSoujq5azc%2BP3ubnRxc35OVFW2QYMtIiiyG2bbPbfUNERdWsGQ3ZjRpZkNu3lQ15Bw3i%2BfnWnfXll/s/1qCBrUJq3frQik1A%2BfkWBBcvlj76yE4B2rBh7/dJS5NOOUU680xbP3PssfHzfQwkIgKgRxEAvWHnTps39dNPNocq0tavj84riwxNlrc4pbICgegCgUgru1CgZk1rycl7t6Qk%2B9jIL13HibbIIoKyLbKgoKjIhk0LCqKLCyKtpKRqPqey0tMtEEdCctn5dJFh1oYN7b5I4KuWYddNm2y7l1dftS9CICCdcYb02GO2rBzlchzrTZ8/3zZ7nzt3/9N/WreWzj1XGjjQegmZawtULQKgRxEAE4vjWO9XZAgzMrS5bZu1fbcGiWwPEulFy8%2Bv2Nw1twQC1rtZq1a0x7JOHWuRnsyMDAtqkZ7OYNAWQwSD0V7QunXjcJhw82brAm7SxCZ9otIim72/846dDT5//t7TK%2BrWtSB44YVS//72Bw2Aw0MA9CgCIPZVVBTd1iPSIhsFl90sONJrV3bT4NJSa5Eev4jIJsKBwN69hTVqRHsSIy3S0xjZZDiy0XCkN5LhPFRUfr6dCT5jhjRzpnW2RmRmSoMHS5dfLp1%2Bun0vAqg8AqBHEQAB%2BEFJiZ348%2Bqr0tSpNqUiokkTC4JXX21ngwOoOAKgRxEAAfhNaaktIHnpJenll22aRMQJJ0i/%2BpUdx1yvnns1Al5BAPQoAiAAPysqsvmC//iHDRNH5sCmpUkXX2w78XTrxtQDoDwEQI8iAAKA2bJFmjhR%2Btvf7ISfiOOPl4YPt2HiWrXcqw%2BIRwRAjyIAAsDeHMf2Gnz2WRsm3r3b7q9XT7r%2Beiknh4XaQAQB0KMIgABQvq1bpRdekHJz7dg6yVawX3KJdNttdkYx4GdJbhcAAEBVq19fuvVWO8Zx2jTbTLqkRJo0SerSRerXT3rvvb23PQL8hAAIAEhYycnS%2BedL8%2BZJn3xi8wGTk22fwb597Tzi6dMP/ZhBwKsIgAAAX%2BjSxRaLfPONLQ5JT7djmwcNsm1kXn2VIAj/IAACAHzlqKOkJ5%2B0E/xGjbJjCD//XLroIls5PHUqQRCJjwAIAPClxo2lBx6wIPjHP9oxc198YWcOn3SSNGsWcwSRuAiAAABfq19f%2BtOfLAjedZdUp460bJk0YIB0yinS%2B%2B%2B7XSFQ9QiAAADI9gu8917bNua22%2BxUkfffl3r3lgYOlL780u0KgapDAAQAoIyGDaWHHpK%2B/dY2kE5OtuPmOna06/Xr3a4QOHwEQI/Jzc1VVlaWsrOz3S4FABJas2Z2qsh//iMNHmwLQ557Tjr6aOn%2B%2B6Vdu9yuEDh0nATiUZwEAgCx9f77trn0v/9t1y1bWk/hRRdJgYC7tQGVRQ8gAAAV0KuXtGiR7SXYooW0erUdLXfqqdKnn7pdHVA5BEAAACooELDTRL76SrrnHttMesEC22R6xAhp%2B3a3KwQqhgAIAEAl1aol3X23BcGLLrL5gWPHSr/4hfSPf7B/IOIfARAAgEPUsqX0yivSe%2B9Jxx0nbdokXXON1KePLR4B4hUBEACAw3T66dLy5dKDD1rv4MKFdr7w6NGsFkZ8IgACAFAFUlKkO%2B6wDaMHDpSKi%2B2ouY4drYcQiCcEQAAAqlCrVtL06dJrr0nNm9uG0n37StdeK23d6nZ1gCEAAgBQDQYPtt7AnBxbPfzCC1JWlgVDwG0EQAAAqklmpq0Ofv99WySyYYN0wQXSxRdLGze6XR38jAAIAEA169FDWrbMFoUkJ0tTpkjt29st4AYCIAAAMZCaKt13nx0l16mTtHmz9QRecom9DcQSARAAgBjq0kVaskS66y7rDXzlFalDB2nmTLcrg58QAAEAiLGUFOnee%2B1s4awsmxs4cKD0619LeXluVwc/IADGWFFRkX73u9%2BpY8eOql27tpo1a6arrrpKP/30k9ulAQBi7KSTpE8%2BkW691VYK/%2B1vtoH0Rx%2B5XRkSHQEwxnbu3KmlS5fqrrvu0tKlS/Xaa6/p66%2B/1sCBA90uDQDggrQ06eGHpTlz7Gi5776TevWys4aLi92uDokq4DgcWe22JUuW6OSTT9YPP/ygli1bVuhjwuGwgsGgQqGQMjMzq7lCAEAshEK2b%2BDEiXbdvbs0YYLUpo27dSHx0AMYB0KhkAKBgOrWrVvu%2BxQUFCgcDu/VAACJJRi0wDdpkr390Uc2JDxpktuVIdEQAF22e/du/f73v9fll1/%2Bsz15Y8aMUTAY3NNatGgRwyoBALF02WXSp59KPXvaopArrpCGDpV27HC7MiQKAmA1mzhxourUqbOnLVy4cM9jRUVFuvTSS1VaWqqnnnrqZ59n1KhRCoVCe9qaNWuqu3QAgItatZLmzZP%2B%2BEcpKUkaP94WjXz6qduVIREwB7Ca5eXlacOGDXuumzdvrvT0dBUVFeniiy/Wd999pzlz5qhBgwaVel7mAAKAfyxYIF1%2BubR2rW0o/eij0rBhtnIYOBQEQBdEwt/KlSs1d%2B5cNWrUqNLPQQAEAH/ZskW65hrpjTfs%2BpJLpHHj7LxhoLIYAo6x4uJiXXjhhfr44481ceJElZSUaP369Vq/fr0KCwvdLg8AEKcaNJBmzLAtY2rUkF5%2B2YaEP/vM7crgRfQAxtiqVavUunXrAz42d%2B5cnXrqqRV6HnoAAcC/PvrIegDXrLF9BHNzpWuvdbsqeAkB0KMIgADgb1u2SEOGSG%2B%2BadfXXiuNHSulp7tbF7yBIWAAADyoQQObD3jffbZK%2BO9/t21jvv/e7crgBQRAAAA8KilJGj1aevttqWFDadky6cQT7Rr4OQRAAAA8rm9faelS6eSTpW3bpLPPlu6/XyotdbsyxCsCIAAACaBFC9sv8PrrJceR7rxTuvBCiZNDcSAEQAAAEkRqqvTss9Jzz0kpKdLrr0vdukkrV7pdGeINARAAgARz3XXWG9ismfTf/0rZ2dJbb7ldFeIJARAAgATUtav0ySdSjx5SKCQNGGCbSLP5GyQCIAAACatpU2nOHOsRLC2Vbr/djpPbvdvtyuA2AiAAAAksNdXODH7iCSk5WXrxRenUU6X1692uDG4iAAIAkOACAWnECJsHWK%2BetHixzQtcvtztyuAWAiAAAD7Rt6%2BFv3btpB9/tJNDpk93uyq4gQAIAICPHHOMtGiR1K%2BftHOnNHgwi0P8iAAIAIDP1K0r/etf0o03WvC7/XbbQLqoyO3KECsEQI/Jzc1VVlaWsrOz3S4FAOBhNWtKubnS44/bmcJ/%2B5sdIbd9u9uVIRYCjkOnrxeFw2EFg0GFQiFlZma6XQ4AwMPeeEO69FIpP1/KypJmzZJatXK7KlQnegABAPC5c8%2BVFi60k0O%2B/NI2kf74Y7erQnUiAAIAAHXubCuEO3WSNmyQ%2BvSxnkEkJgIgAACQJB15pPUE9u9vK4TPP1969lm3q0J1IAACAIA9MjOt52/oUDs%2BbtgwafRotolJNARAAACwl5o1peefl%2B6%2B264feMDOEGabmMRBAAQAAPsJBKR77rHtYSJnCJ93nrRjh9uVoSoQAAEAQLl%2B9StpxgypVi3p7bel00%2BXNm1yuyocLgIgAAD4WeecI82ZIzVoIC1ZYmcIr1rldlU4HARAAABwUF27Sh98YBtEr1wp9eghffaZ21XhUBEAAQBAhbRrZyGwQwdp3TrbK/D9992uCoeCAAgAACqseXNpwQIbBt6%2B3fYMnDXL7apQWQRAAABQKfXqSe%2B8Iw0YIO3aZRtGT5rkdlWoDAIgAACotFq1pNdfl664Qioulq68UnrqKberQkURAAEAwCGpWdP2B8zJsZNCcnKkMWPcrgoVQQAEAACHLClJevJJ6c477foPf5B%2B/3uOjot3BEAAAHBYAgHpz3%2BWHn7Yrh980HoDS0vdrQvlIwACAIAqceut0rPPWiB8%2Bmlp6FCbH4j4QwAEAABV5vrrpQkToucHX365VFjodlXYFwHQY3Jzc5WVlaXs7Gy3SwEA4IAuv1x69VUpJUWaMkW64AJp9263q0JZAcdhmqYXhcNhBYNBhUIhZWZmul0OAAD7eestafBgC3/9%2B9u2MbVquV0VJHoAAQBANTnrLDslpHZt2zj6nHOkHTvcrgoSARAAAFSj006T3n5bysiQ5s%2B3UBgOu10VCIAAAKBa9ewpzZ4tBYPSBx9IZ54phUJuV%2BVvBEAAAFDtunaV5syxc4QXLbI5gdu3u12VfxEAAQBATHTpYiGwQQPp3/%2BW%2BvWTtm1zuyp/IgACAICYOeEEC4ENG0off0wIdAsBEAAAxFSnTtEQ%2BMknUt%2B%2BhMBYIwACAICY69hRmjtXatRIWrqUnsBYIwACAABXdOiwd0/gmWeyMCRWCIAAAMA1ZUPgkiUWAtknsPoRAAEAgKs6dpTefVeqX99WB599tpSX53ZViY0ACAAAXHf88RYC69aVPvxQGjBAys93u6rERQAEAABxoXPn6IkhCxdKAwdKu3a5XVViIgACAIC4cdJJ0ltvSXXq2NzAX/5SKihwu6rEQwAEAABxpVs3adYsqVYtC4OXXCIVFbldVWIhAAIAgLjTu7c0Y4aUmipNny4NGSKVlLhdVeIgAAIAgLh0xhnS1KlSzZrSyy9Lv/61VFrqdlWJgQDoMbm5ucrKylJ2drbbpQAAUO0GDJBeeklKTpZeeEG6%2BWbJcdyuyvsCjsOX0YvC4bCCwaBCoZAyMzPdLgcAgGo1YYJ01VUW/kaNkh54wO2KvI0eQAAAEPeuvFJ66il7e8wY6S9/cbceryMAAgAATxg2THroIXt71KhoIETlEQABAIBn3HabdOed9nZOjg0No/IIgAAAwFPuvVcaMcLevuYaaeZMV8vxJAIgAADwlEBAeuyx6N6AF10kzZ/vdlXeQgAEAACek5Qk/f3vdl5wQYF03nnS0qVuV%2BUdBEAAAOBJNWrYBtGnnirl5UlnnSV9/bXbVXkDARAAAHhWWpodFdeli7Rpk9S/vxQOu11V/CMAAgAAT8vMlN58U2rXzk4K4XyEg6vhdgEAAACHq3FjadkyKT3d7Uq8gR5AAACQEAh/FUcABAAA8BkCIAAAgM8QAAEAAHyGAOiyG264QYFAQI899pjbpQAAAJ8gALpo2rRpWrx4sZo1a%2BZ2KQAAwEcIgC5Zu3athg8frokTJ6pmzZpulwMAAHyEfQBdUFpaqiFDhuj2229X%2B/btK/QxBQUFKigo2HMdZptzAABwiOgBdMGDDz6oGjVq6Kabbqrwx4wZM0bBYHBPa9GiRTVWCAAAEhkBsJpNnDhRderU2dPmz5%2Bvxx9/XOPHj1cgEKjw84waNUqhUGhPW7NmTTVWDQAAElnAcRzH7SISWV5enjZs2LDnesqUKRo9erSSkqLZu6SkRElJSWrRooVWrVpVoecNh8MKBoMKhULK5NBDAABQCQTAGNuyZYvWrVu3131nnnmmhgwZoqFDh6pdu3YVeh4CIAAAOFQsAomxBg0aqEGDBnvdV7NmTTVt2rTC4Q8AAOBwMAcQAADAZ%2BgBjAMVnfcHAABQFegBBAAA8BkCIAAAgM8QAAEAAHyGAAgAAOAzBEAAAACfIQACAAD4DAEQAADAZwiAAAAAPkMABAAA8BkCIAAAgM8QAAEAAHyGAAgAAOAzBEAAAACfIQB6TG5urrKyspSdne12KQAAwKMCjuM4bheByguHwwoGgwqFQsrMzHS7HAAA4CH0AAIAAPgMARAAAMBnCIAAAAA%2BQwAEAADwGQIgAACAzxAAAQAAfIZtYDzKcRzl5eUpIyNDgUDA7XIAAICHEAABAAB8hiFgAAAAnyEAAgAA%2BAwBEAAAwGcIgAAAAD5DAAQAAPAZAiAAAIDPEAABAAB8hgAIAADgMwRAAAAAnyEAAgAA%2BAwBEAAAwGcIgAAAAD5DAAQAAPAZAiAAAIDPEAABAAB8hgAIAADgMwRAAAAAnyEAAgAA%2BAwBEAAAwGcIgAAAAD5DAAQAAPAZAiAAAIDPEAABAAB8hgAIAADgMwRAAAAAnyEAAgAA%2BAwBEAAAwGcIgAAAAD5DAAQAAPAZAiAAAIDPEAABAAB8hgAIAADgMwRAAAAAnyEAAgAA%2BAwBEAAAwGcIgAAAAD5DAAQAAPAZAiAAAIDPEAABAAB8hgAIAADgMwRAAAAAnyEAAgAA%2BAwBEAAAwGcIgAAAAD5DAAQAAPAZAiAAAIDPEAABAAB8hgAIAADgMwRAAAAAnyEAAgAA%2BMz/AzmY4at%2BhheRAAAAAElFTkSuQmCC'}
Genus 2 curve data - 331776.g.995328.1