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g2c_curves • Show schema
{'Lhash': '1531489402338985866', 'abs_disc': 995328, 'analytic_rank': 0, '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.e', '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.e.995328.1', 'leading_coeff': {'__RealLiteral__': 0, 'data': '3.1732761692612779570148285115537764432670308075405640570', 'prec': 190}, 'locally_solvable': True, 'modell_images': ['2.90.3', '3.540.7'], 'mw_rank': 0, 'mw_rank_proved': True, 'non_solvable_places': [], 'num_rat_pts': 2, 'num_rat_wpts': 2, 'real_geom_end_alg': 'M_2(R)', 'real_period': {'__RealLiteral__': 0, 'data': '6.3465523385225559140296570231', 'prec': 100}, 'regulator': {'__RealLiteral__': 0, 'data': '1.0', 'prec': 10}, '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': 1, '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.e.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.e.995328.1', 'mw_gens': [[[[0, 1], [1, 1]], [[0, 1], [0, 1], [0, 1], [0, 1]]]], 'mw_gens_v': True, 'mw_heights': [], 'mw_invs': [2], 'num_rat_pts': 2, 'rat_pts': [[0, 0, 1], [1, 0, 0]], 'rat_pts_v': True} - g2c_galrep • Show schema
- g2c_tamagawa • Show schema
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g2c_plots • Show schema
{'label': '331776.e.995328.1', 'plot': 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3frw5cSMqypZyAcAxCIAAwsaJE2bT5ZUrTVu/3jzX11D37iboXXqp%2Bdm/P1uyAEBjEQAB2ObkSTPC9/775w58PXuaoOcLfezBBwDNRwAEEDKnTpnAt3KltGLF2ad0e/Y0Qc/XLrqIwAcALY0ACKDVVFebUb333zeBb80as3K3odRUE/QmTCDwAUCoEAAdhpNAEM5qaqQPPzRh7/33peJi81xfQykpJuz5Wp8%2BBD4ACDVOAnEoTgJBOKirk7ZskZYvN4GvsDB44%2BXOnU3Q%2B9a3zAgfizYAwH6MAAI4b5Yl7d7tD3zvvy8dOhTYJznZLNjwhb4hQwh8ABBuCIAAvtYXX5ig9957Jvh9%2Bmng%2B%2B3amY2Xv/Ut00aMYONlAAh3BEAAASorzVTue%2B%2BZ9vHHge%2B3aWPO0r3sMhP4MjM5Wg0AnIYACLhcTY1ZqesLfGvWmGsNDR9uAt9ll5kTN9q3t6dWAEDLIAACLmNZ0s6d0rJlpq1YIXm9gX3S06WJE/2hr3Nne2oFALQOAiDgAkeOmOf3li41raws8P2OHc107uWXm%2BB30UX21AkACA0CIBCBTp82p2wsXSotWSJt2GBG/nxiY6Vx46RJk0zoY%2BEGALgLARCIEHv2mLC3ZIlZtXvmtO6gQSbwTZrEc3wA4HYEQIfhJBD4nDghFRRI775r2o4dge936mRG93yhLzXVnjoBAOGHk0AcipNA3MeyTMh75x3TCgoCz9WNjpbGjpWuvFK64gpp5EgpKsq%2BegEA4YsRQCCMHT9uVun6Qt%2BePYHv9%2BplAt%2BVV5rVuklJ9tQJAHAWAiAQZnbtkt56S3r7bWnlysBRvthYc%2BrG5MmmDRzIMWsAgMYjAAI2O31aKiqS3nzTBL8zn%2BVLS5OuusoEvgkTpA4d7KkTABA5CICADQ4dMiN8b75ptmppuGI3JsaM8l11lWmM8gEAWhoBEAgBy5K2bJH%2B/nfT1q4N3Jeva1cT9qZMMSt3eZYPANCaCIBAK/FN7b7xhmlnLuAYPly6%2BmrTMjJYsQsACB0CINCCvF6zJ9/rr5sp3qNH/e/FxZmVutdcY0Jfz5721QkAcDcCINBMBw6YwPfaa%2BYEjupq/3tdupiwN3Wqmdrl9A0AQDggADoMJ4GEh127pFdfNW3NmsDn%2Bfr1k6ZNM6Fv7FjO2AUAhB9OAnEoTgIJLcuStm6VXn5ZeuUVadOmwPfHjDGhb9o0s2oXAIBwxgggcA6WJZWWmtD30kvS9u3%2B96KjpfHjpeuvN6GPc3YBAE5CAAQasCzpww%2Blv/3NtN27/e/FxkqTJpnQN3Wq1KmTfXUCANAcBEC4nm%2Bk769/Na1h6IuPN/vzffvbZo8%2BZtsBAJGAAAjX2rpVWrzYtJ07/dfbtjVh74YbTPjj6DUAQKRh69kW8sQTTyg9PV3x8fEaNWqUioqKztl34cKF8ng8Qe3UqVMhrNid9u6V5s2Thg2TBg%2BWHnrIhL/4eDO1u3ixOabtb3%2BTvvMdwh8AIDIxAtgC/vKXv2jWrFl64oknlJ2drT/84Q%2BaPHmytm7dqt69e5/1dxITE7W94aoCSfHx8aEo13UOHTJTu3/%2Bs7R6tf96mzbSFVdIN91knulLSLCvRgAAQoltYFpAZmamRo4cqd///vf11wYOHKhp06Zp3rx5Qf0XLlyoWbNm6WjDYyIaiW1gvt7Jk2Zz5kWLzMkcNTXmuscjTZgg3XyzNH26dMEF9tYJAIAdGAFspurqam3cuFH33XdfwPVJkyZpdcPhpjMcO3ZMaWlpqq2t1fDhw/XQQw9pxIgRrV1uRKurM2fvPvecmcKtrPS/N3KkdOut0o03Sj162FcjAADhgADYTIcPH1Ztba26desWcL1bt246cODAWX9nwIABWrhwoYYOHSqv16vf/va3ys7O1qZNm9SvX7%2Bz/k5VVZWqqqrqX3u93pb7Eg63e7f07LMm%2BO3d67%2BelibdcosJfmzODACAHwGwhXg8noDXlmUFXfPJyspSVlZW/evs7GyNHDlSv/vd7zR//vyz/s68efM0d%2B7clivY4Y4fN5szP/OMVFDgv56YaFbv3n67lJMjRbHMCQCAIATAZurcubOio6ODRvsOHjwYNCp4LlFRUcrIyNDOhnuRnOH%2B%2B%2B/X7Nmz6197vV716tWraUU7lGVJGzZIf/yjWa3rm%2BL1eKTLL5e%2B%2B11zKkfbtraWCQBA2CMANlNsbKxGjRqlZcuW6brrrqu/vmzZMl177bXn9RmWZam0tFRDhw49Z5%2B4uDjFxcU1u14n%2Buor6YUXpAULpI8%2B8l/v00eaOdOM9rksCwMA0CwEwBYwe/Zs3XbbbRo9erTGjh2rp556SmVlZbrrrrskSbfffrtSU1PrVwTPnTtXWVlZ6tevn7xer%2BbPn6/S0lLl5%2Bfb%2BTXCimVJa9dKTz5ptnDxbZEYH29O5fi3f5Py8szoHwAAaBwCYAu48cYb9eWXX%2BrBBx9UeXm5hgwZorfffltpaWmSpLKyMkU1eBjt6NGjuuOOO3TgwAElJSVpxIgRKiws1JgxY%2Bz6CmHj2DGzdcsTT0ibN/uvDx0q3XGHWdCRnGxffQAARAL2AXSoSNsHcPt2KT/frOb1LXCOjzfbttx1l5SZyWgfAAAthRFA2KauzmzSPH%2B%2BtGSJ/3q/ftIPfiDNmCF17GhffQAARCoCIELu%2BHEz0vfb30o7dphrHo909dXSv/%2B7NHEi27cAANCaCIAImfJy6fHHpd//3qzslaSkJOl735Puvlu66CJ76wMAwC0IgGh127dLjzwiPf%2B8VF1trvXpI/3nf5q9%2BxISbC0PAADXIQA6TH5%2BvvLz81VbW2t3Kd9owwZp3jzptdfMti6SNG6cdM890tSpUnS0vfUBAOBWrAJ2qHBeBVxUJD30kLRsmf/a1KnSvfdK2dn21QUAAAxGANFiVq6U5s41PyUzwnfLLdJ//Zc0aJCdlQEAgIYIgGi24mLpv//bH/zatJH%2B9V9N8EtPt7U0AABwFgRANNmHH0o//an0zjvmdWysOaLtvvs4mxcAgHBGAESj7d4tPfCAtHixeR0TI82cacJg79721gYAAL4ZARDn7cgRs7gjP186fdps3nzzzdKDD5ptXQAAgDMQAPGNTp82mzfPmePfwPmKK6Sf/1waPtzW0gAAQBMQAPG13n9f%2Bo//kLZsMa%2BHDJEefVSaNMneugAAQNNx4irOqrzcTO9edpkJf506mVHA0lLCHwAATkcAdJj8/HwNGjRIGRkZrfL5dXUm6A0YYBZ5REWZc3p37pTuuovTOwAAiAScBOJQrXESyI4dZv%2B%2BVavM64wM6cknpZEjW%2BTjAQBAmGAEEKqrkx57TLrkEhP%2BOnSQ5s%2BX1qwh/AEAEIlYBOJy%2B/ZJt9/uP8Xj8sulBQuktDRbywIAAK2IEUAXe/lladgwE/7at5f%2B8AdpyRLCHwAAkY4RQBeqrpZ%2B/GPp8cfN6zFjpEWLpL597a0LAACEBiOALrN/vzR%2BvD/83XuvVFxM%2BAMAwE0YAXSRdeukadOkAwek5GTphRekKVPsrgoAAIQaI4Au8dJL0qWXmvA3ZIj0wQeEPwAA3IoA6AK/%2B530ne9Ip05JV18trV4t9eljd1UAAMAuBECHacxJIJYlPfSQOcvXssyJHq%2B9JiUkhKBQAAAQtjgJxKHO5ySQ//kfEwAl6cEHpZ/%2BVPJ4QlgkAAAISywCiVDz5vnD36OPSrNn21sPAAAIH0wBR6Cnn5Z%2B8hPzz488QvgDAACBCIARZvly6c47zT//5CfSPffYWw8AAAg/BMAIsnevWe1bWyvdcov0v/9rd0UAACAcEQAjxOnT0k03SUeOSBkZ0h//yIIPAABwdgTACPF//2dO%2BkhOlv72Nyk%2B3u6KAABAuCIARoCPPzYBUJKefFJKS7O3HgAAEN4IgA5nWWaj55oa6dprpRtvtLsiAAAQ7giADnPmSSDvvSetWCHFxUmPPWZzcQAAwBE4CcShfCeBjBlTofXrEzV7ttnwGQAA4JsQAB3KFwClCsXGJurTT6WUFLurAgAATsAUcAS44QbCHwAAOH8EQIeqrfX/84wZ9tUBAACchwDoUJs2mZ8JCdKll9paCgAAcBgCoNOUlUl3362BUy6UJC2NvlJt/v6KvTUBAABHYRGIk%2BzcKeXkSAcPyivJLAGREiXpwQel//5vW8sDAADOQAB0kmuvld54Q5KCA2BUlPTJJ1J6un31AQAAR4ixuwAnsyxLlZWVIfmzqj7/XLFvvinPP197z/ipujrpqaek%2B%2B8PST0AADhdQkKCPB7PN3eMQIwANoN/Lz4AAOA0FRUVSkxMtLsMWxAAm6E5I4AZGRnasGHDefevOnJEsYMGyXPypCQz8tdL0j79cwpYkh5%2BWLr77latI5I/w%2Bv1qlevXtq3b1%2Bz/oUQDt8lXD6De9ryn8E9bfnP4J62/Ge0xD0Nxfdw8wggU8DN4PF4mvwXOzo6unG/m5go3XqrtGBB4OV/NrVrJ915p%2BnXmnVE%2BGdIUmJiYrM%2BJ1y%2BS7h8hsQ9benPkLinLf0ZEve0pT9Dat49DafvEYnYBsYmdzdypE6S9MtfSqNGBV%2BPjZVeeEHq2DE0dUTwZ7SEcPku4fIZLSFcvku4fEZLCJfvEi6f0RLC5buEy2eEQw3h8D3CFVPATnPqlPTii9oy7zkN2blSf%2Bp2p2YW/Vjq18/uyhzP90ynm58JaWnc05bHPW153NOWxz0Nf9Fz5syZY3cRaISYGGnECO0afbWefvoRvV29XP/vf3soNtbuwiJDdHS0Lr30UsXE8HRES%2BGetjzuacvjnrY87ml4YwTQoSoqvEpONjsBLl6cqBtvtLsiAADgFDwD6FANFy0984x9dQAAAOchAEaAJUukrVvtrgIAADgFAdDhrrnG/HzoIXvrAAAAzkEAdLj/%2Bi/zc/Fiaf16e2sBAADOQAB0mPz8fA0aNEgZGRmSpKFDpRkzzHs/%2BIFUU2NjcQ7wxBNPKD09XfHx8Ro1apSKiorO2XfLli2aPn26LrzwQnk8Hj322GMhrNQ5GnNPFyxYoNzcXF1wwQW64IILNHHiRK3nv1yCNOaevvLKKxo9erSSk5PVvn17DR8%2BXM8//3wIq3WGxtzThhYvXiyPx6Np06a1coXO0pj7uXDhQnk8nqB26tSpEFaMMxEAHebuu%2B/W1q1bA462%2BfnPpeRk6cMPpV/8wsbiwtxf/vIXzZo1Sw888IBKSkqUm5uryZMnq6ys7Kz9T5w4oYsuukg///nPlZKSEuJqnaGx93TlypW6%2BeabtWLFCq1Zs0a9e/fWpEmTtH///hBXHr4ae087duyoBx54QGvWrNHmzZs1c%2BZMzZw5U0uWLAlx5eGrsffU59NPP9U999yj3NzcEFXqDE25n4mJiSovLw9o8fHxIawaQSw4UkVFhSXJqqiosCzLsp57zrIky4qJsaw1a2wuLkyNGTPGuuuuuwKuDRgwwLrvvvu%2B8XfT0tKs3/zmN61VmmM1555almXV1NRYCQkJ1rPPPtsa5TlSc%2B%2BpZVnWiBEjrJ/%2B9KctXZpjNeWe1tTUWNnZ2dYf//hHa8aMGda1117b2mU6RmPv5zPPPGMlJSWFojQ0AiOAEeLWW6UbbzRTwDfcIB04YHdF4aW6ulobN27UpEmTAq5PmjRJq1evtqkqZ2uJe3rixAmdPn1aHZtwjGEkau49tSxLy5cv1/bt25WXl9daZTpKU%2B/pgw8%2BqC5duuh73/tea5foKE29n8eOHVNaWpp69uypq6%2B%2BWiUlJa1dKr4B23NHCI9HeuopadMm6R//kKZNk1askNq2tbuy8HD48GHV1taqW7duAde7deumA6TlJmmJe3rfffcpNTVVEydObI0SHaep97SiokKpqamqqqpSdHS0nnjiCV1%2B%2BeWtXa4jNOWerlq1Sk8//bRKS0tDUaKjNOV%2BDhgwQAsXLtTQoUPl9Xr129/%2BVtnZ2dq0aZP6cYypbQiAESQxUXr9dSkrS1q3Trr5Zumll8zpcTA8DXfQlhkxOfMaGqep9/SXv/ylXnzxRa1cuZJngc7Q2HuakJCg0tJSHTt2TMuXL9fs2bN10UUX6dJLL23lSp3jfO9pZWWlbr31Vi1YsECdO3cOVXmO05i/o1lZWcrKyqp/nZ2drZEjR%2Bp3v/ud5s%2Bf36p14tyIBhHm4oul116TJk0yYfC735WefVaKjra7Mnt17txZ0dHRQf%2BFevDgwaD/ksX5ac49/dWvfqWHH35Y7733noYNG9aaZTpKU%2B9pVFSU%2BvbtK0kaPny4tm3bpnnz5hEA1fjkccF0AAAbuUlEQVR7umvXLu3du1fX%2BDZZlVRXVydJiomJ0fbt29WnT5/WLTqMtcS/S6OiopSRkaGdO3e2Rok4TzwDGIHy8qS//tWM/C1aZEKg27eHiY2N1ahRo7Rs2bKA68uWLdO4ceNsqsrZmnpPH3nkET300EN69913NXr06NYu01Fa6u%2BpZVmqqqpq6fIcqbH3dMCAAfroo49UWlpa36ZOnaoJEyaotLRUvXr1ClXpYakl/o5alqXS0lJ17969NUrE%2BbJv/Qma48xVwGfzt79ZVnS0WR183XWWdfJkCAsMQ4sXL7batGljPf3009bWrVutWbNmWe3bt7f27t1rWZZl3XbbbQGr2KqqqqySkhKrpKTE6t69u3XPPfdYJSUl1s6dO%2B36CmGnsff0F7/4hRUbG2u99NJLVnl5eX2rrKy06yuEncbe04cffthaunSptWvXLmvbtm3Wo48%2BasXExFgLFiyw6yuEncbe0zOxCjhQY%2B/nnDlzrHfffdfatWuXVVJSYs2cOdOKiYmx1q1bZ9dXgGVZBECHOp8AaFmW9dprlhUba0Lg%2BPGWdeRIaOoLV/n5%2BVZaWpoVGxtrjRw50iooKKh/b/z48daMGTPqX%2B/Zs8eSFNTGjx8f%2BsLDWGPuaVpa2lnv6c9%2B9rPQFx7GGnNPH3jgAatv375WfHy8dcEFF1hjx461Fi9ebEPV4a0x9/RMBMBgjbmfs2bNsnr37m3FxsZaXbp0sSZNmmStXr3ahqrRkMeyLMuesUc0RX5%2BvvLz81VbW6sdO3aooqJCiYmJX/s7K1aYVcFer9S/v/T3v0ssvAIAwL0IgA7l9XqVlJR0XgFQkj76SJoyRdq3z5wasnixdMUVISgUAACEHRaBuMTQodL69WaLmKNHpcmTpYcekv65uA0AALgIAdBFUlKklSul739fsizpf/5HuvJKTg0BAMBtCIAuExdnTgxZuNCcErJsmTRsmPTmm3ZXBgAAQoUA6FIzZkgffGDC36FD0jXXSHfcIVVW2l0ZAABobQRAFxs0yBwZN3u2eb1ggTRkiLR0qb11AQCA1kUAdLn4eOnRR82zgenpUlmZWR08Y4Z0%2BLDd1QEAgNZAAIQkafx4afNm6Uc/kjwe6bnnpAEDpD/9iZXCAABEGgIg6nXoIM2fL61ebbaN%2BfJL6Xvfk3JypI0b7a4OAAC0FAKgw%2BTn52vQoEHKyMhotT8jK8sEvl/9yoTCNWukjAyzfcwXX7TaHwsAAEKEk0AcqrEngTTV/v3SvfdKf/6zeZ2QIN13nzRrltSuXav9sQAAoBUxAoivlZoqLVokFRdLo0ebbWIeeMCcKfzMM1Jtrd0VAgCAxiIA4rxkZ5stY154QerdW/rsM%2Blf/9XsI/jKK%2BZkEQAA4AwEQJy3qCjplluk7dvN84EdO0pbt0rTp5tnBN9%2BmyAIAIATEADRaPHx0o9/LO3eLf30p2ahyMaN0pQp0tix0jvvEAQBAAhnBEA0WVKS9NBDJgjec485W3jdOumqq8yI4Ouvs4cgAADhiACIZuvSRXrkEWnPHjMy2K6dGRGcNs08I/jCC1JNjd1VAgAAH7aBcahQbQPTFIcOSb/5jZSfL3m95lpamjlz%2BHvfk9q3t7c%2BAADcjgDoUOEcAH2OHpWeeEJ67DETCiWzcOQHP5Duvlvq3t3e%2BgAAcCumgB0mFCeBtJTkZOknP5E%2B/dQEwT59pCNHpP/7P%2BnCC6UZM6SSErurBADAfRgBdCgnjACeqbbWLAx59FFz3rBPbq70n/8pXXutFBNjX30AALgFAdChnBgAG1q3zkwNv/SSf4FIr17SXXdJ//ZvUteu9tYHAEAkIwA6lNMDoM9nn0m//7301FPS4cPmWps20g03mGcFs7Mlj8feGgEAiDQEQIeKlADoc%2BqU9Ne/mpXD69f7rw8ZIt15p3TrreaZQgAA0HwEQIeKtADY0AcfmFHBF1%2BUTp4019q2lb7zHemOO8xpI4wKAgDQdKwCbibLsjRnzhz16NFDbdu21aWXXqotW7Z87e/MmTNHHo8noKWkpISo4vA3erT09NPS559L8%2BdLgwebIPjss2ZKePBgs5Dk4EG7KwUAwJkIgM30y1/%2BUr/%2B9a/1%2BOOPa8OGDUpJSdHll1%2BuysrKr/29wYMHq7y8vL599NFHIarYOZKTpR/9SProI2nVKum73zWnjGzbZo6eS02VrrtOeuMN6fRpu6sFAMA5CIDNYFmWHnvsMT3wwAO6/vrrNWTIED377LM6ceKE/vznP3/t78bExCglJaW%2BdenSJURVO4/HI40bJz3zjFReLj35pDRmjFk9/NprZvuYnj3NMXSbN9tdLQAA4Y8A2Ax79uzRgQMHNGnSpPprcXFxGj9%2BvFY33OjuLHbu3KkePXooPT1dN910k3bv3v21/auqquT1egOaGyUmmkUh69aZkcHZs82WMQcPSr/%2BtXTJJdKIEeafDxywu1oAAMITAbAZDvwzYXTr1i3gerdu3erfO5vMzEw999xzWrJkiRYsWKADBw5o3Lhx%2BvLLL8/5O/PmzVNSUlJ969WrV8t8CQcbMsQ8C/jZZ2aD6euuM1vIlJaa0cDUVOnKK6UXXpCOHbO7WgAAwgcBsBEWLVqkDh061LfT/3zwzHPGklTLsoKuNTR58mRNnz5dQ4cO1cSJE/XWW29Jkp599tlz/s7999%2BvioqK%2BrZv374W%2BEaRoU0baepU6ZVXzBRxfr6UlSXV1UlLlki33SZ16ybdcov01ls8LwgAAAdvNcLUqVOVmZlZ/7qqqkqSGQns3r17/fWDBw8GjQp%2Bnfbt22vo0KHauXPnOfvExcUpLi6uCVW7S6dO0g9/aNrOndKiRWYEcNcu6c9/Nq1TJ7PR9M03Szk5UhT/GQQAcBn%2Br68REhIS1Ldv3/o2aNAgpaSkaNmyZfV9qqurVVBQoHHjxp3351ZVVWnbtm0BIRLN16%2BfNGeOCYJr15oVxV27Sl9%2BaRaSjB8v9e5tniNcu1ZiR0wAgFsQAJvB4/Fo1qxZevjhh/Xqq6/q448/1ne/%2B121a9dO//Iv/1Lf77LLLtPjjz9e//qee%2B5RQUGB9uzZo3Xr1unb3/62vF6vZsyYYcfXiHgej5SZafYU3L9fWrpUmjlTSkoyr3/zG7O5dHq6dO%2B9ZiNqwiAAIJIRAJvp3nvv1axZs/TDH/5Qo0eP1v79%2B7V06VIlJCTU99m1a5cO%2Bw66lfTZZ5/p5ptvVv/%2B/XX99dcrNjZWa9euVVpamh1fwVViYqTLL5f%2B9Cfpiy/M4pGbb5bat5c%2B/VR65BEpI0Pq08eEwQ0bCIMAgMjDUXAOFclHwdnh5Enp7belv/zFLBQ5ccL/Xu/e0re/LU2fbhaX8MwgAMDpCIAORQBsPcePS%2B%2B8I/31ryYUHj/uf69HD7PdzPXXS3l5ZkQRAACnIQA6FAEwNE6elN59V3rpJenNN6WG%2B2937Gi2n7nuOjOt3LatfXUCANAYBECHIgCGXlWV9N57Zr/B1183q4l92rUzm05PmyZNmWLCIQAA4YoA6DD5%2BfnKz89XbW2tduzYQQC0SU2NVFzsD4NlZf73oqPN9PC115p24YW2lQkAwFkRAB2KEcDwYVnShx9Kr71m2scfB74/dKiZKp46VRo9mkUkAAD7EQAdigAYvnbvNqOCr79uRglra/3vpaSYKeJrrpEmTjTbzwAAEGoEQIciADrDkSNmW5k33jDnEldW%2Bt%2BLi5O%2B9S3p6qtNKGQbSABAqBAAHYoA6DzV1VJBgfT3v5u2d2/g%2B0OGmCA4ZYo5mYQtZgAArYUA6FAEQGezLGnrVhME33pLWr1aqqvzv5%2BcLF1xhXTVVWZ1cdeu9tUKAIg8BECHIgBGliNHzH6Db71lfh454n/P4zGLRyZPNi0jw6w0BgCgqQiADkUAjFy1tdK6dSYMvv22VFoa%2BH6nTtKkSWZk8IorpG7d7KkTAOBcBECHIgC6R3m5GRV85x1p6VKpoiLw/ZEj/WFw7FipTRt76gQAOAcB0KEIgO5UUyOtWeMPhCUlge8nJEiXXWbC4KRJ0kUX2VMnACC8EQAdigAISfriCzMq%2BO675ufhw4Hv9%2BtnguCkSdKECSYgAgBAAHQYjoLDudTVmRNJliwxbc0aM2LoExNjpogvv9wEwtGjWUwCAG5FAHQoRgDxTbxeacUKEwaXLZM%2B%2BSTw/eRksxH15ZebdtFFZsUxACDyEQAdigCIxtq920wTL1smvf%2B%2BdPRo4Pvp6eZ4uokTTTDs3NmeOgEArY8A6FAEQDRHTY20caMJg0uXBk8XezzS8OH%2BQJiTI7VrZ1%2B9AICWRQB0KAIgWtKxY%2BaYuvfeM%2B3jjwPfj401zw9OnGhWGWdkcFQdADgZAdChCIBoTQcOSMuXmzC4fLm0b1/g%2Bx06SJdeaqaKv/UtaehQKSrKllIBAE1AAHQoAiBCxbKknTtNEFy%2B3CwsaXhUnWSeF5wwwR8I%2B/VjQQkAhDMCoEMRAGGXujpzPN3y5WYxSVGRdPx4YJ/UVBMEfaEwLc2eWgEAZ0cAdCgCIMJFdbW0fr0Jg%2B%2B/bxaUVFcH9klP9wfCCROkHj3sqRUAYBAAHYoAiHB14oS0erUJgytWSBs2SLW1gX0uvtg8QzhhgvmZkmJHpQDgXgRAh%2BEkEDhNZaVUXOwPhCUlZhq5oQEDTBD0tW7dbCgUAFyEAOhQjADCqY4elQoLTRhcuVLatMksNGlo4EB/GMzLY4QQAFoaAdChCICIFEeOmEC4cqVpmzcHB8L%2B/U0YHD/eNJ4hBIDmIQA6FAEQkep8AmG/fv4wOH681KuXHZUCgHMRAB2KAAi3%2BOorfyAsKDBb0Jz5b630dH8YzMszr9mHEADOjQDoUARAuNXRo2ZRSUGBaR9%2BGLzKuGdPEwR9gbB/fwIhADREAHQoAiBgVFZKq1b5A%2BGGDVJNTWCfrl2l3Fx/IBwyRIqOtqdeAAgHBECHIgACZ3fihNmMurDQtLVrpVOnAvskJUk5OSYM5uVJI0dKsbH21AsAdiAAOhQBEDg/VVVmVNAXCFevNqOGDbVtK40da8Jgbq6UlSW1a2dPvQAQCgRAhyIAAk1TU2MWkvgCYVGRWXncUEyMNHq0CYN5edK4cVLHjvbUCwCtgQDoMJwEArSsujpp2zZ/GCwslPbvD%2B43dKgJhDk55mfPnqGvFQBaCgHQoRgBBFqHZUl795ow6Gvbtwf3S0/3h8HcXFYaA3AWAqBDEQCB0Dl4MDAQlpYGn2fcubM/EObkSCNGSG3a2FMvAHwTAqBDEQAB%2B3i9ZqVxUZHZk3DduuCVxu3amcUkOTmmjR0rdehgT70AcCYCoEMRAIHwUVUlbdxowqCvffVVYJ/oaGn48MBRwm7d7KkXAAiADkUABMKXb2GJb8q4uFgqKwvu17evf4QwJ0e6%2BGKeIwQQGgRAG7zyyiv6wx/%2BoI0bN%2BrLL79USUmJhg8f3qjPIAACzrJvn390sKhI%2Bvjj4DONfc8R5uRI2dlsUA2g9RAAbfD8889rz5496tGjh77//e8TAAEXOnrUbErtC4Xr15up5Ibi46XMTH8gHDtWSk62p14AkYUAaKO9e/cqPT2dAAig/jnCVav8ofDMDao9HrMfYXa2aTk5Uu/eTBsDaDwCoI0aEwCrqqpU1WB4wOv1qlevXgRAIELV1Zn9B4uL/aFw167gfj17%2BsNgdrY0bJhZcAIAX4cAaKPGBMA5c%2BZo7ty5QdcJgIB7HDgQOEJYUiLV1gb26dDBTBX7AmFmJtvPAAhGAGxlixYt0p133ln/%2Bp133lFubq4kRgABNM/x4%2BbZQd8o4Zo1Zo/Chnzbz/imjbOzpdRUe%2BoFED4IgK2ssrJSX3zxRf3r1NRUtW3bVhLPAAJoWbW1ZnVxw1HCffuC%2B6Wl%2BUcIs7OlwYOZNgbchgBoIwIggNa2b58JhL5QuHlz8DF2iYnSuHGm5eRIY8ZI7dvbUy%2BA0CAA2uDIkSMqKyvT559/rilTpmjx4sXq37%2B/UlJSlJKScl6fQQAE0BSVldLatf5QuHatdOxYYJ/oaHOWccNp4x497KkXQOsgANpg4cKFmjlzZtD1n/3sZ5ozZ855fQYBEEBLqKmRPvrIP0K4apX02WfB/S68MDAQMm0MOBsB0KEIgABaS1mZPxCuXn3uaeOxY/2BMDOTaWPASQiADkUABBAqXq%2B0bp0/EJ5r2pjVxoBzEAAdigAIwC4Np4197VyrjbOz/YtLhgxh2hgIFwRAhyIAAggnZWVmdNAXCDdtCp42TkiQsrICp40TEuypF3A7AqDD5OfnKz8/X7W1tdqxYwcBEEBYqqw008YNVxtXVgb2iYqSLrkkcNq4Vy976gXchgDoUIwAAnCS2lr/tPHq1eZ5wrKy4H69egUGwqFDpZiY0NcLRDoCoEMRAAE43WefBU4bl5ae/WzjzEwTBnNyzBQy08ZA8xEAHYoACCDSHDtmzjb2BcKznW0cFSUNG2YWlvhGCXv3ljwee2oGnIoA6FAEQACRrrZW2rIlcLXx3r3B/Xr2DAyEl1zCtDHwTQiADkUABOBGn38e%2BBxhSUnwtHH79maq2Lf9TFaW2bgagB8B0KEIgAAgHT8ePG1cURHYJyrKLCZpuLiEaWO4HQHQoQiAABCsri542njPnuB%2BPXsGBsJhw5g2hrsQAB2KAAgA5%2Bfzz/1Txr7VxjU1gX06dAjcpJrVxoh0BECHIgACQNOcOW28evW5Vxvn5LBJNSITAdChCIAA0DLOXG1cXCx9%2Bmlwv969AwMhZxvDyQiADsNRcADQ%2BvbvDwyEpaXBZxsnJkpjx/pDYWam1K6dPfUCjUUAdChGAAEgdI4dM%2BcZN1xtfOxYYJ%2BYGGnECBMIfaGwWzd76gW%2BCQHQoQiAAGCfmhpp8%2BbAUcL9%2B4P79e3rD4M5OVL//mw/g/BAAHQoAiAAhA/LksrK/CuNi4uljz821xvq3NlsUJ2bawLhyJFSbKw9NcPdCIAORQAEgPB29KiZKi4uNm39eunUqcA%2B8fHSmDH%2BaeOxY6XkZHvqhbsQAB2KAAgAzlJdLW3c6B8hXLVKOnw4sI/HY04t8QXCnBy2n0HrIAA6FAEQAJzNsqTt2/0jhMXF0q5dwf1828/k5Jip40GDzD6FQHMQAB2KAAgAkae83D9C6Nt%2BprY2sM8FF/gXleTkSKNHS3Fx9tQL5yIAOhQBEAAin2/7GV8gXLNGOnEisE9cnHmOMDfXv0l1UpI99cI5CIAORQAEAPc5fdqMCvoCYVGRdOhQYB%2BPx3%2BMXW6uaT162FMvwhcB0GE4CQQA4GNZ0o4dgYHwbM8Rpqf7w2BurnTxxexH6HYEQIdiBBAAcDbl5f4wWFwsbdoUfIxdly5mhDAvz/wcPtycZAL3IAA6FAEQAHA%2BvF5p9Wp/KFy3TqqqCuzToYPZgzAvz4wQjhkjtW1rT70IDQKgQxEAAQBNUVUlffCBCYNFRWbVcUVFYJ82baSMDP%2BUcXY2G1RHGgKgQxEAAQAtoa7OHFvnC4SFhWYauSHfwhLfCGFurpSSYk%2B9aBkEQIciAAIAWoNlSbt3BwbCTz4J7tevX2AgTE9nYYmTEAAdigAIAAiVAwdMEPSFws2bTVBsKDXVHwjHj5cGDiQQhjMCoEMRAAEAdjl61Dw76AuFGzZINTWBfTp39q80zsszK42jo%2B2pF8EIgA5FAAQAhIsTJ8yJJYWFpq1dK508GdgnMVEaN86MDublmSPsYmPtqRcEQMciAAIAwlV1tbRxoz8Qnm2lcdu2UlaWPxBmZbH1TCgRAB2Gk0AAAE5TW2ueG/QFwsJC6fDhwD5t2pj9B31TxtnZUkKCPfW6AQHQoRgBBAA4lWVJ27b5w2BBgfT554F9oqOlkSP9I4S5uexF2JIIgA5FAAQARArf1jMFBaYVFUl79gT28XikSy4xgdAXCjt1sqfeSEAAdCgCIAAgkpWV%2BUcHCwulHTuC%2BwwZEhgIu3ULfZ1ORQB0KAIgAMBNysv9gbCgQNq6NbjPwIHSj34k/eAHoa/PaWLsLgAAAOCbdO8u3XijaZJ06FBgINy82TxXePy4vXU6RZTdBTjdK6%2B8oiuuuEKdO3eWx%2BNRaWnpN/7OwoUL5fF4gtqpU6dCUDEAAM7XpYs0fbo0f760aZNZVfzqq%2BYavhkjgM10/PhxZWdn64YbbtD3v//98/69xMREbd%2B%2BPeBafHx8S5cHAIArdOokTZtmdxXOQQBspttuu02StHfv3kb9nsfjUUpKSitUBAAA8PWYArbJsWPHlJaWpp49e%2Brqq69WSUnJ1/avqqqS1%2BsNaAAAAE1BALTBgAEDtHDhQr3xxht68cUXFR8fr%2BzsbO3cufOcvzNv3jwlJSXVt169eoWwYgAAEEnYBqYRFi1apDvvvLP%2B9TvvvKPc3FxJZgo4PT1dJSUlGj58eKM%2Bt66uTiNHjlReXp7mz59/1j5VVVWqqqqqf%2B31etWrVy%2B2gQEAAI3GM4CNMHXqVGVmZta/Tk1NbZHPjYqKUkZGxteOAMbFxSkuLq5F/jwAAOBuBMBGSEhIUEIrnExtWZZKS0s1dOjQFv9sAACAMxEAm%2BnIkSMqKyvT5/88xdq3tUtKSkr9Kt/bb79dqampmjdvniRp7ty5ysrKUr9%2B/eT1ejV//nyVlpYqPz/fni8BAABchUUgzfTGG29oxIgRmjJliiTppptu0ogRI/Tkk0/W9ykrK1N5eXn966NHj%2BqOO%2B7QwIEDNWnSJO3fv1%2BFhYUaM2ZMyOsHAADuwyIQh%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%2BFlpd7KKQAAAAASUVORK5CYII%3D'}
Genus 2 curve data - 331776.e.995328.1