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g2c_curves • Show schema
{'Lhash': '1864262080683034445', 'abs_disc': 373248, 'analytic_rank': 1, 'analytic_rank_proved': True, 'analytic_sha': 1, 'aut_grp_id': '[4,2]', 'aut_grp_label': '4.2', 'aut_grp_tex': 'C_2^2', 'bad_lfactors': '[[2,[1]],[3,[1]]]', 'bad_primes': [2, 3], 'class': '20736.k', 'cond': 20736, 'disc_sign': -1, 'end_alg': 'Q x Q', 'eqn': '[[2],[0,0,0,1]]', 'g2_inv': "['6400000/3','440000/9','-32000/81']", 'geom_aut_grp_id': '[24,8]', 'geom_aut_grp_label': '24.8', 'geom_aut_grp_tex': 'C_3:D_4', 'geom_end_alg': 'M_2(CM)', 'globally_solvable': 1, 'has_square_sha': True, 'hasse_weil_proved': True, 'igusa_clebsch_inv': "['40','45','555','6']", 'igusa_inv': "['240','1320','-2560','-589200','373248']", 'is_gl2_type': True, 'is_simple_base': False, 'is_simple_geom': False, 'label': '20736.k.373248.1', 'leading_coeff': {'__RealLiteral__': 0, 'data': '1.36224221131018051806837289623428662771175912046036', 'prec': 173}, 'locally_solvable': True, 'modell_images': ['2.180.4', '3.8640.8'], 'mw_rank': 1, 'mw_rank_proved': True, 'non_solvable_places': [], 'num_rat_pts': 6, 'num_rat_wpts': 0, 'real_geom_end_alg': 'M_2(C)', 'real_period': {'__RealLiteral__': 0, 'data': '12.512277055780378059680634351', 'prec': 100}, 'regulator': {'__RealLiteral__': 0, 'data': '0.326617338771', 'prec': 47}, 'root_number': -1, 'st_group': 'D_{2,1}', 'st_label': '1.4.F.4.2c', 'st_label_components': [1, 4, 5, 4, 2, 2], 'tamagawa_product': 12, 'torsion_order': 6, 'torsion_subgroup': '[6]', 'two_selmer_rank': 2, 'two_torsion_field': ['4.0.576.1', [4, 0, -2, 0, 1], [4, 2], True]} -
g2c_endomorphisms • Show schema
{'factorsQQ_base': [['1.1.1.1', [0, 1], -1], ['1.1.1.1', [0, 1], -1]], 'factorsQQ_geom': [['2.0.3.1', [1, -1, 1], 1]], 'factorsRR_base': ['RR', 'RR'], 'factorsRR_geom': ['M_2(CC)'], 'fod_coeffs': [4, 0, 2, 0, 1], 'fod_label': '4.0.576.2', 'is_simple_base': False, 'is_simple_geom': False, 'label': '20736.k.373248.1', 'lattice': [[['1.1.1.1', [0, 1], [0, 0, 0, 0]], [['1.1.1.1', [0, 1], -1], ['1.1.1.1', [0, 1], -1]], ['RR', 'RR'], [2, -1], 'D_{2,1}'], [['2.2.8.1', [-2, 0, 1], [0, 0, 0, '1/2']], [['1.1.1.1', [0, 1], 1]], ['M_2(RR)'], [4, 0], 'C_{2,1}'], [['2.0.24.1', [6, 0, 1], [0, -2, 0, '-1/2']], [['1.1.1.1', [0, 1], 1]], ['M_2(RR)'], [12, 0], 'C_{2,1}'], [['2.0.3.1', [1, -1, 1], [0, 0, '-1/2', 0]], [['2.0.3.1', [1, -1, 1], -1], ['2.0.3.1', [1, -1, 1], -1]], ['CC', 'CC'], [4, -1], 'C_2'], [['4.0.576.2', [4, 0, 2, 0, 1], [0, 1, 0, 0]], [['2.0.3.1', [1, -1, 1], 1]], ['M_2(CC)'], [16, -1], 'C_1']], 'ring_base': [2, -1], 'ring_geom': [16, -1], 'spl_facs_coeffs': [[[0], [-108]], [[0], [-864]]], 'spl_facs_condnorms': [576, 36], 'spl_facs_labels': ['576.e4', '36.a4'], 'spl_fod_coeffs': [0, 1], 'spl_fod_gen': [0, 0, 0, 0], 'spl_fod_label': '1.1.1.1', 'st_group_base': 'D_{2,1}', 'st_group_geom': 'C_1'} -
g2c_ratpts • Show schema
{'label': '20736.k.373248.1', 'mw_gens': [[[[1, 1], [1, 1], [0, 1]], [[-1, 1], [0, 1], [0, 1], [0, 1]]], [[[-1, 1], [0, 1], [1, 1]], [[0, 1], [-2, 1], [0, 1], [0, 1]]]], 'mw_gens_v': True, 'mw_heights': [{'__RealLiteral__': 0, 'data': '0.32661733877148842826007676858836', 'prec': 113}], 'mw_invs': [0, 6], 'num_rat_pts': 6, 'rat_pts': [[-1, -1, 1], [-1, 2, 1], [1, -2, 1], [1, -1, 0], [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': '20736.k.373248.1', 'plot': 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CzuWSHnhAev55KSFBevll6Wc/k4qL7a4MAABIBEA0oTFjpDlzpDZtpMWLpfx86euv7a4KAAAQANGkfvYz6bPPzJyBmzZJAwdKr71md1UAADgbARBNrlcvEwLPPVcqLZUuvVS6%2B26pstLuygAAcCYCIJpF27bSe%2B9Jv/%2B9eT15spkyZudOe%2BsCAMCJCIBoNgkJ0rRp0qxZUsuW5vnAk06SvvjC7soAAHAWAiCa3dVXm1vCxxxjngscNEj6058kZqQEAKB5EABhixNOkL78Uho1ykwefcstZn/XLrsrAwAg9hEAYRuPR/rXv6Tp06XEROnNN6W%2BfaX58%2B2uDACA2EYAhK1cLul3vzPzBObmSlu2mKlj7rxTKiuzuzoAAGITARAR4aSTpKVLpV/9yjwLOHWqdOqp0jff2F0ZAACxhwCIiNG6tVlH%2BPXXpXbtzKohp5wiPfywVFFhd3UAAMQOAiAizsiR0sqV0vDhZoDIPfdI/ftLy5fbXRkAALGBAIiIlJ5uBoXMnCmlpUlffWV6AydOlPbts7s6AACiGwEQEcvlkq65RvruO7N8XGWl9Mgj0vHHm1VFgKZQUFCgvLw85efn210KADQZl2Ux/S6iw9tvS2PHmpHCkpk3cNo0KSfH3roQm3w%2Bnzwej7xer9xut93lAEBY0QOIqDF8uLRqlTRhghQfbwaLHHus9MAD3BYGAKA%2BCICIKq1bS489Ji1bJg0eLB04IE2aZILgrFlSVZXdFQIAEPkIgIhKffpI8%2BZJr7xibgFv3myeF8zPlz780O7qAACIbARARC2XS7r8cnNbePJkKTXVjBY%2B91zpvPOkJUvsrhAAgMhEAETUa9nSTA/zww/SuHFSixbSBx%2BYlURGjDC3iwEAQBABEDGjQwfpT3%2BS1qyRRo%2BW4uLMyOGTTjIDSL74wu4KAQCIDARAxJxu3aQXXjDzB151lQmC77xjVhM591xp7lyz3jAAAE5FAETM6tVLmj3bBMHRo6WEBDNAZMgQqV8/6cUXpbIyu6sEAKD5MRE0HGPjRjNx9N/%2BFpw3MCNDuvFG0zIz7a0PkYWJoAHEMgIgHGfXLunpp6Unn5S2bjXvJSRII0dKN90knXWWuW0MZyMAAohlBEA4Vnm59NprJgh%2B%2Bmnw/R49pDFjzG3jzp3tqw/2IgACiGUEQEDSN99If/2reWbQ5zPvuVzSOeeYCaZHjjTzDNayfr00fbo0Z455ff750u9%2BJ3Xv3qy1o2kQAAHEMgIgUENpqfTqq9KMGdLChcH3W7aUhg2TrrhCuuACqeXyxdLQodLevbVP4HabQHjaac1bOMKOAAgglhEAgTqsX2/WF541S1q7Nvh%2BSitLa%2BNylVmyLvQHc3Ol1atNFyKiFgEQQCwjAAJHYFlmibmXX5b%2B%2BU%2Bp%2B6Z5mqefHf5D8%2BdLgwc3S31oGgRAALGMsY7AEbhc0sknS3/8o7Rhg/T8vRuO%2BJllb2yofpYQAIBIQwAE6sHlkroN7nLE4yZM76K2bc2jgBMnSv/9rwiEUaKgoEB5eXnKz8%2B3uxQAaDLcAgbqq6pK6tnTPCQYQrHnGA1s/73W/VD7GcC4OKlvX2nQIOn000047NqVRwUjFbeAAcQyAiDQEB9/LP3851JJSe33W7eW3ntPGjRImzZJ8%2BaZtnChVFh46Gk6dJDy86VTTjGtXz%2BpUydCYSQgAAKIZQRAoKHWrpWeeMLc35XM/DC33GJ6B0P48Ufpk0%2BkRYukxYul5cvNZNQHa9fO9BSecILUp4/Uu7eUlxdiHkI0KQIggFhGAARscuCACYFLlkhLl5q2apVUWRn6%2BM6dpeOOk3r1Mq1nT9O6dDFL2SG8CIAAYhkBEIggBw5I335rVib55huzv3KlVFRU92cSEkwI7NbNtJwc07p0kbKzzS3lpKTmu4ZYQQAEEMsIgEAU2LXL9A6uWRNsa9eacSgHDhz58x06mCCYlSVlZkoZGVJ6erB16GBa27ZSfHzTX080IAACiGUEQCCKVVVJW7eaILhhg9lu3Gja5s2m%2Bf1Hfz6XS2rTxjyH2K6dlJYWbG3amOZ2Sx6P2aammnEvgW1KitSqVWyESAIggFhGAARimGVJO3eaASg//mjC4rZt0vbtphUVScXF0o4d0u7d4fu%2BSUkmCLZqZdZRDrTkZPO1wDYxMbhNTJRatDAtISG4Hx9vXsfHH9ri4g5tLlfdTTp0vy779vl09dUezZ7tVatWhwbAgz8b6nsc3ELVW/NaAteZkBBsB/95BP6sYiFkA7APARCAJDMiedcuExh37jT7u3aZYLh7t%2BT11m4%2Bn7R3r2klJVJpqQmcscMnySPJKynyegDj4oIBOtACITs5uXbwbtUq2DubkmJazd7bQAv07Ho85pg4lgoAYhYBEEBYWJZ5HrG01LR9%2B0zbv9%2B0AweCze8PtrKyYCsvr90qKkyrrKzdKirM7e9QzbLqboE66/pbr%2Bb7FRU%2BLVniUX6%2BVwkJdQfAmuetef6DW6C2qipzDTVrDnV9FRW1/wyqqsLwQ6qHuDgTBgO3/9PSzDOigdaundS%2BfXDboYPUsaMJksxjCUQ%2BAiAAhBBpzwBWVgaDcSAw1wzSfn8wYAcCdyCAB8J4IJyXlppe25KSYC9uoFfX5zOBs6GSkkwQDAwwysgItsxMMxApMBgpMTF8fz4A6ofZwwAgCgSeFUxObtrvY1kmNHq90p49wRZ4JCDQdu6Ufvop2HbsMCHT7w8OQDqSjh3N6PTOnU3LzjatSxfTOnUyzz2GzYYN0vvvm/0hQ8xajIBD0QMIACFEWg9gNNi3zwwqKi4ODjTats0MNioqMvuBgUhlZUc%2Bn8tlQmBOjslqXbuauS67dpW6dzdh8agmQff7pRtukGbPDt5Lj4uTrr5aeuaZpk/VQAQiAAJACATApmNZptcwMDp9yxbTNm0yPYeB7ZFCYny8CYfdu0s9egTbMceYbUrK/x143XXS88%2BHPsmYMXV/DYhhBEAACIEAaK%2BqKtOTuHGjuXNbsxUWmu2R5rjMzJROy/5R/1zSVQlWHQ82JiSYk3XqFM7ygYjHM4AAgIgTFxccPNK//6FfrzkJ%2Bvr10g8/mLZunWm7d5tbzS23zVeCDjOqpaJC70%2BcJ%2Bvq/1GvXubZQ6a/gRMQAAGghoKCAhUUFKiystLuUnAYcXHBwSNnnnno13ftMkGwfGacVHD4c73wYpz%2B8aLZT06WcnOlXr1MO/bY4H5qavivA7ALt4ABIARuAceIHTvMaJE67heXxyfp%2BiGbtWRDB/3ww%2BGfO8zKqh0KA1t6DRGNCIAAEAIBMIZMmCA9/njor40fX/21igrzOOCaNaatXh3c37697tMHeg1r9hb26mXe4z8dRCoCIACEQACMIZWV0sSJUkGBmatGMmvkjR0rPfLIUS2svGePCYQ1Q%2BGaNeY28%2BF6DTMygmEwcGu5Z08zcpmJsGEnAiAAhEAAjEF79kgLFpj9wYPNGneNFOg1PDgYHqnXMC7OzGnYs6dpxxwT3HbtGuYJsIEQCIAAEAIBEI3l9Urffx8MhN9/b9ratWY5vroE5jesObdhjx6m17B7dwajIDwIgAAQAgEQTcWyzBQ1gTC4dm1w%2Bpp168xSfIfTrp0JgoFVUWq2nBypVaumvwZEPwIgAIRAAIQdLMvMbxiY07DmHIfr15s1mI%2BkfXsTBLt0Ca6tHFhnOTvbPJd4VEvoIaYRAAEgBAIgIpHPZ1ZCWb%2B%2B9qooGzaYVVN8viOfIzDJdufOZgGUQMvKMqunZGaa/bQ0sx4zYhMBEABCIAAiGu3ZY4Lgxo3BdZUDaytv3mx6FysOszBKTYmJUnq6CYTp6bVbx47BbYcOUtu2RzWYGhGEAAgAIRAAEYsqK83o5B9/PLRt22YC4rZtZiWV%2BnC5zLOJHTqYW9Dt25vXgW2gtW0bbGlpUlJS01wnjowACAAhEADhZH6/VFRUu23fHmzFxcG2e3fDv0/LliYIpqWZWXkC2zZtJI/n0OZ2B7epqabR89gwBEAACIEACByd8nLpp59M27EjuL9zZ3AbaLt2mcC4Z49UVRWe75%2BSIrVubUJh69bSuHHSmDHhOXcsYxwQAABosBYtgoNHjlZVlZkncffuYNuzp3bzeoNbn89sA/s%2BnwmekplTsbQ0OPF2fW9fOxUBEAAANKu4uOCt34Y6cEDau7d28/nMcns4MgIgAACIOsnJpnXoYHcl0YkA2AiWZWnv3r12lwEgDPx%2Bv/x%2Bf/XrwO%2B272gmVgMQlVJTU%2BVy6GSHDAJphMBD4gAAIPo4eZAXPYCNkJqaqtzcXC1ZsuSojvf5fMrOztbmzZuP%2Bj%2B4/Pz8oz5/fY9vynNzrfbVw7U27PiDewC3bdumU089Vd999506derU7PU057lj%2Bed6MK7Vvnoi8VpTU1OPup5YQwBsBJfLpfj4%2BHr/68Htdh/1Z%2Bp7/voc35TnDuBam78erjV8x0vmH3qRUA8/1/AdL3GtdtQTidfq1Nu/EgGw0caOHXvEYxYvlj74QEpISJT0K732WoIyMsycRTVbauqhC3QfzfkbenxTnrshuNbwHM%2B1hu/4%2BuJaw3M81xq%2B4%2BuLa3UOngFsBlOnSnfeeXTHpqQcOvN5YFb0QEtLCy6jU3PrdkfOwt1OmkSXa41NW7Zsqb6l1LlzZ7vLaVJO%2BrlyrbHJSdcaLvQANoMTTpBuuEHas6dSX3%2B9Th079lRJSVz1nEU%2Bn1l2RwpOaLl1a/2/T3y8CYMHr7/Yvn1wfcYOHUzr2NG0lJTwXmtAUlKS7r//fiU5YKFHrjU2Ba7RKdfqpJ8r1xp7nHSt4UIPYIQoKzt0tvPALOgHt5ozp%2B/aZdqBAw37vq1aBcNgerqUkRHcZmYGt5mZZr4lwCnoUQAQywiAMWL//mAYDKy5ePB6jDt21G7799fve6SlSVlZpnXqFGydO5uWnW16HCPlNjTQGARAALGMAOhQliWVlEjFxaZt3262RUW127ZtptWYHeOwkpNNGOzSpXbLyTGtSxeJHnpEAwIggFhGAMQRWZa59bx1a7D9%2BGOwbdkibd5sAuSRuFzmdnLXrqZ162Za9%2B5mm51tnmUE7EYABBDLCIAIG7/fBMLNm6VNm4LbjRuDbd%2B%2Bw5%2BjRQvTU9ijR7Adc4xp3bvzHCKaDwEQQCyLs7sApygvL9cdd9yhPn36KCUlRVlZWfrlL3%2BprQ0Z7hshXn/9dQ0dOlTt27eXy%2BXSqlXL1b27NHiwdM010l13SX/9q/Tee9J335lbztOn/0NSvqTLJN0u6SlJ/9Uxx1QpMVEqL5fWrZPmzJH%2B8hfp1lulESOk3r3NgJUuXaRzzpFuukl67DHp7bel1avNIJpI%2BXNYvny5fcWEgWVZmjRpkrKystSyZUudddZZWrly5WE/M2nSJLlcrlotIyOjmSrG0fjLX/6ibt26KTk5WSeffLI%2B/vjjOo994YUXDvl5ulwuHWjoaLMIsHDhQg0bNkxZWVlyuVx688037S6p0ep7TfPnzw/5c129enUzVRx%2BU6ZMqV7Ro2PHjrr44ou1Zs0au8uKCkwD00z27dunr776Svfee6/69u2r3bt3a/z48Ro%2BfLi%2B/PJLu8trkNLSUg0cOFCXXXaZbrjhhiMe73JJbrdfbvf3WrPmnVpfy8iIU2Wlub38ww%2B127p1pvl8pldx82bpo49qnzsuztxS7tVLys0128B%2Bp05NOzClvn8Oke7RRx/VtGnT9MILLyg3N1cPPfSQzjvvPK1Zs%2Bawyyb17t1bH3zwQfXreO7lR4xXXnlF48eP11/%2B8hcNHDhQTz/9tC644AJ999136tKlS8jPuN3uQ/5HmhzFXfClpaXq27evxowZo0suucTucsKiode0Zs2aWr3aHTp0aIrymsWCBQs0duxY5efnq6KiQnfffbeGDBmi7777TilNNc9ZjCAANhOPx6O5c%2BfWeu/Pf/6zTj31VG3atKnOv4Qj2TXXXCNJ2rBhQ70%2BV1fvUHy8eQYwO1s666zaX7MsM5J57VoTBteulb7/3rS1a83cievXm/bee7U/m5ISDIXHHls7HDb674dPP9U1a9dKkralpTXyZPazLEtPPPGE7r77bo0aNUqS9Pe//13p6el66aWXdOONN9b52YSEBHr9ItS0adN03XXX6frrr5ckPfHEE5ozZ46eeuopTZkyJeRnYq0X94ILLtAFF1xgdxlh1dBr6tixo9q0adMEFTW///73v7Vez5gxQx07dtTSpUt15pln2lRVdCAA2sjr9crlcsXML%2BLRKikpUU5OjioWZQhmAAAcnElEQVQrK3XiiSfqwQcfVL9%2B/Q77GZcrOIn1gAG1v2ZZZqRyIBCuWRPcrl9vwuGyZaYdLDs7GAwDrVevo%2Bg13LNHGjVKmjev%2Bq1MSR9Iitu796j/LCJNYWGhioqKNGTIkOr3kpKSNHjwYC1atOiwAXDt2rXKyspSUlKS%2Bvfvr8mTJ6t79%2B7NUTYOo6ysTEuXLtWdBy1HNGTIEC1atKjOzzXk9xTRoV%2B/fjpw4IDy8vJ0zz336Oyzz7a7pLDxer2SpLZt29pcSeQjANrkwIEDuvPOO3XVVVc56gHzY489Vi%2B88IL69Okjn8%2Bn6dOna%2BDAgfr666/Vs2fPBp3T5QrOT3hwz2F5ubmNvGZN7bZ6tZkfMXBLucadS0mmZzAQDA%2B%2BpZySIunaa2uFv4BzJO25//5D71FHiaKiIklSenp6rffT09O1cePGOj/Xv39/zZw5U7m5udq%2BfbseeughDRgwQCtXrlS7du2atGYc3k8//aTKysqQP9PAz/tgTfF7CvtlZmbqmWee0cknnyy/368XX3xR55xzjubPnx8TvWWWZWnChAkaNGiQjj/%2BeLvLiXwWmsSsWbOslJSU6rZw4cLqr5WVlVkjRoyw%2BvXrZ3m9XhurPHqHu57CwkJLkrVs2bJ6n7eystLq27evNW7cuHCWe1R27LCsTz6xrOees6z//V/LGjbMsnJzLSs%2B3rJMv2Lo1lMLrUq56jygyuWyrLVrm/16GuLgn%2Bv8%2BfMtSdbWrVtrHXf99ddbQ4cOPerzlpSUWOnp6dZjjz0W7pKbjdfrtSRFze9oXX788UdLkrVo0aJa7z/00ENWr169juocdv6eNgVJ1htvvGF3GWHV0Gu66KKLrGHDhjVBRc3vt7/9rZWTk2Nt3rzZ7lKiAj2ATWT48OHq379/9etOnTpJMqOBL7/8chUWFuqjjz6Kmt6/uq6nseLi4pSfn6%2B1//ccXXNq3960gQNrvx/oNVy9Ong7ObC/c6d0mgoVp7pnT3JZlmbfvFi%2BEcdUT2HTpUtkzm948M/V/38zfhcVFSkzM7P6/eLi4kN6kA4nJSVFffr0seXnitrat2%2Bv%2BPj4Q3r76vMztfP3FE3rtNNO06xZs%2Bwuo9HGjRunt99%2BWwsXLlTnzp3tLicqEACbSGpq6iEjJgPhb%2B3atZo3b15U3RoLdT3hYFmWli9frj59%2BoT93A3VokXwecCD7dwp/fSXZOm%2Bw5/jjTkt9dqc2ufs1s3Ma9i9u2mB/W7dpNatw3sNR%2Bvgn6tlWcrIyNDcuXOrn/cqKyvTggULNHXq1KM%2Br9/v16pVq3TGGWeEveamVlBQoIKCAlVWVtpdSlgkJibq5JNP1ty5czVy5Mjq9%2BfOnasRI0Yc1Tki8fcU4bFs2bJa/9iLNpZlady4cXrjjTc0f/58devWze6SogYBsJlUVFTo0ksv1VdffaV///vfqqysrP4Xedu2bZWYmGhzhfW3a9cubdq0qXouw8CUERkZGdWjB3/5y1%2BqU6dO1SMNH3jgAZ122mnq2bOnfD6f/vSnP2n58uUqKCiw5yLqqV07qd0t50tTU8zokhAOJLRSm1EnacieA9q8OVk//GDmKQwMUgmlfXsTBHNygqukBJbOy8mRPJ4mu6RaXC6Xxo8fr8mTJ6tnz57q2bOnJk%2BerFatWumqq66qPu6cc87RyJEjdfPNN0uSbrvtNg0bNkxdunRRcXGxHnroIfl8Po0ePbp5Cg%2BjsWPHauzYsdUTQceCCRMm6JprrtEpp5yi008/Xc8884w2bdqkm266SVLs/Z6GUlJSonXr1lW/Liws1PLly9W2bduonIVBOvI1TZw4UT/%2B%2BKNmzpwpyYz%2B7tq1q3r37q2ysjLNmjVLr732ml577TW7LqHRxo4dq5deeklvvfWWUlNTq/%2B/6vF41LJlS5uri3D23oF2jsBzcqHavHnz7C6vQWbMmBHyeu6///7qYwYPHmyNHj26%2BvX48eOtLl26WImJiVaHDh2sIUOGHPJsUlR46KE6nwGceNCfQ0WFZW3caFkffmhZzzxjWXfeaVmXXWZZp5xiWWlph3/eMNBSUy2rd2/LOv98y7rhBsuaNMmy/vY3y3r3Xcv6%2BmvL%2Bukny6qqCs%2BlVVVVWffff7%2BVkZFhJSUlWWeeeaa1YsWKWsfk5OTU%2BjlfccUVVmZmptWiRQsrKyvLGjVqlLVy5crwFGSTWHkGMKCgoMDKycmxEhMTrZNOOslasGBB9ddi9ve0hnnz5oX8%2B6rmdUebI13T6NGjrcGDB1cfP3XqVKtHjx5WcnKylZaWZg0aNMj6z3/%2BY0/xYVLX/1dnzJhhd2kRj6XggIaaPl2aOtXMQSOZYch33CH97nf1Oo3XKxUWmrZxo7Rhg2mBZfR27Tq68yQmmnWWMzKCLT3dtI4dzbZ9ezOVTtu2ZvJs1I2l4ADEMgIg0BgVFdLXX5v9vn2lhPA/VVFSIm3ZElxfecsWs%2BZyYLt1q5kkuz7i4kwIbNcu2Nq2NS0tzbQ2bcyt5zZtJLfb7LvdUmqqeaYx1hEAAcQyAiAQA8rKTEdkoBUVSdu3127FxdKOHabHsbGSk83AldRUs23d2syP2KpV7daypWnJyWablGRacrLZJibWbi1amJaQENyPjzev4%2BOD%2B3FxZj8u7tDmcgVbYxAAAcQyAiDgMOXlpsdw587gdudOc6t59%2B5g27PHNK/XrMPs9UoHDthdff0dHAgPDod1BUXL8qm83KMWLbxyuQ4NgAd/LtT3OLgdHFYDITYQbmuG3EA7OBDXDMwHB%2BpA2E5ODgbwQDAPbAPBPTXVvMejAIAzEQABHLXychMG9%2B41t6YD25ISad8%2BMzB63z7T9u832wMHzP6BA5LfH9wGWlmZaeXlh7aKCtMqK02rqmrOq/VJ8kjySordHsDU1OAt/sAt/zZtzGMAgccC2rYNzpvZoYN5pjQlpfG9rADsQwAEEDUsq3YYDNUON546cI7D/a0X%2BNrevT717u3RypVepabWHQBrnrfm%2BQ9ugdqqqg6tP3BNgRYIvjVDcHl57bBcM0QHgnWg7d8fDOCBVlJiAnpg29hpDlu2DA4yCgw6ysoy62h37hxsMTKTDhBzCIAAEEIsPwNoWSYo%2BnzB5vWaFrj9H3gUYNeu2o8MFBfX71EAt9vMZxmY3zIwEXpgMvRWrZrqKgEcDgEQAEKI5QDYWCUlJghu324GHBUVmcFHW7eatmWLabt3H/lcnTtLubmmHXuslJdnWlYWt5iBpkQABIAQCICNV1oanM9y40Yz1%2BX69Wa7bp3paaxLmzZS797SCSeYGZZOPFHq04ceQyBcCIAAEAIBsOn99JO0dq1ZInH1atO%2B%2B0764YfQzyjGxUnHHSedcopp/fubcFivlTQDqbNNm7BcAxCtCIAAEAIB0D5%2Bv7RmjbRihfTNN9Ly5aYVFx96bFKSdPLJ0oAB0qBBprVrF%2BKk77wjPfyw9Pnn5vWpp0r33CMNG9ak1wJEKgIgAIRAAIw8W7dKS5dKS5ZIX35pslyopRKPP1466yzp7LNNS3vrBelXvzp0%2BLfLJT3/vHTttc1QPRBZCIAAEAIBMPJZlrmFvHix9Omn0iefSKtW1T6mpeuAtsZ3VpuKnaFP0q6dGbGSnNz0BQMRhAAIACEQAKPTjh3SggXS/PnSRx9Jx6x6W29rxOE/9Oab0ogjHAPEGBYBAoAaCgoKlJeXp/z8fLtLQQN06CBdeqn05JNmQMkL0448F81Hr%2B9RUVEzFAdEEHoAASAEegBjxNdfmzlkDuNELdOKuBN15pnSlVeaABlyIAkQQ%2BgBBADErr59pTPOqPPLm7sOUtKpJ6qqytw2vukms6zd8OHSv/5Vv1VPgGhCAAQAxLbZs81SIwfLzVX2wpf0%2BedmcupHHzWdhRUVZtaYyy4zK5KMG2c6EoFYwi1gAAiBW8Axxu%2BXXn1Veu898/qCC0zCS0o65NBVq6SZM6UXX5R%2B/DH4fn6%2B6SG88kpWJEH0IwACQAgEQFRWSh98ID33nBkoXF5u3m/TRrruOmnsWKlbN3trBBqKAAgAIRAAUVNxsTRjhvT00%2BZ2sWSWprv4YunWW81KJEA0IQACQAgEQIRSWWnuIv/5z9L77wffHzBAuvNO6cILTTAEIh3/mQIAcJTi46WLLpLmzJG%2B/dbcCk5MlBYtMiOHTzxReuUVExSBSEYABACgAXr3lv72N2nDBun226XUVGnFCjNIpE8fEwSrquyuEgiNAAgAQCNkZkpTp0obN0oPPGAGiaxaZYJgv37S22%2BbdYuBSEIABAAgDNLSpPvuMz2CDzwgeTzSN9%2BYZYYHDTK3iYFIQQAEACCMPB4TBNevNwNDWrY04W/gQOmSS6QffrC7QoAACABAk2jbVpoyRVq3Trr%2BejM6%2BPXXpbw86Y47JJ/P7grhZARAAACaUFaW9OyzZjm5IUOksjKz7FyvXtKsWTwfCHsQAAEAaAbHHy/9979mneFjjpGKiqRrrpF%2B9jMzaARoTgRAAACaictl5hH89lvp4YfN84Hz50t9%2B5rnBv1%2BuyuEUxAAAQBoZklJ0l13Sd99ZwJhebn04INmIulPP7W7OjgBARAAaigoKFBeXp7y8/PtLgUO0LWrmSfw1VeljAxp9WrpjDOk8eOlffvsrg6xjLWAASAE1gJGc9u9W7r1VmnGDPO6Z0/p73%2BXTj/d3roQm%2BgBBAAgAqSlSc8/L733ntSpk7R2rZlA%2Bu67zS1iIJwIgAAARJDzzzeDRP7nf8xawpMnSwMGmEAIhAsBEACACNOmjfTii9I//2l6Br/80qwrPHOm3ZUhVhAAAQCIUJddZtYTHjxYKi2VRo82rbTU7soQ7QiAAABEsM6dpQ8/lP7wB7Oc3MyZUn6%2BmUIGaCgCIAAAES4%2BXrr3XmnePCkz06wccuqp0iuv2F0ZohUBEACAKHHmmdKyZWb5uNJS6corpQkTpIoKuytDtCEAAgAQRdLTpTlzpDvvNK8ff1waOlT66Sd760J0IQACABBlEhKkKVOk116TWreWPvrI3BL%2B9lu7K0O0IAACABClRo2SFi%2BWuneXCgvNqiH//rfdVSEaEAABAIhixx8vffGFdNZZUkmJNHy4NH26xEKvOBwCIAAAUa5dO%2Bn996UbbjDBb/x4adw4qbLS7soQqQiAAADEgBYtpKeflh591LwuKDC3iPfts7cuRCYCIAAAMcLlkv73f6VXX5WSkqS33zZTxjBCGAcjAAIAEGMuvdSsHpKWJn3%2BuTRokLRxo91VIZIQAAGghoKCAuXl5Sk/P9/uUoBGGThQ%2BvRTKTtbWrPGvGb5OAS4LItxQgBwMJ/PJ4/HI6/XK7fbbXc5QINt2WImiv7uOzNY5L33zFrCcDZ6AAEAiGGdO0sLF5qJonfuNM8ELlxod1WwGwEQAIAY166d9MEHwbkCzz9fmjvX7qpgJwIgAAAOkJoqvfuu9POfS/v3S8OGSf/5j91VwS4EQAAAHKJlS%2BmNN6SRIyW/32zfecfuqmAHAiAAAA6SmCi98op02WVSebl0ySWEQCciAAIA4DAtWkgvvSRdcUUwBHI72FkIgAAAOFBCgjRrVrAncNQos54wnIEACACAQyUkSLNnm2cBy8qkiy%2BWFiywuyo0BwIgAAAO1qKF9PLLwdHBF10kffGF3VWhqREAAQBwuMRE6bXXzCTRgXkCv/3W7qrQlAiAAABAycnSW29Jp50m7d4tDRkirV9vd1VoKgRAADHn2muvlcvlqtVOO%2B00u8sCIl7r1mY08PHHS9u2mRBYVGR3VWgKBEAAMen888/Xtm3bqtu7775rd0lAVGjb1owG7tZN%2BuEH82ygz2d3VQg3AiCAmJSUlKSMjIzq1rZtW7tLAqJGZqYJgR07SsuWmSliysrsrgrhRAAEEJPmz5%2Bvjh07Kjc3VzfccIOKi4vtLgmIKsccY9YOTkmRPvxQGjNGqqqyuyqEi8uyLMvuIgAgnF555RW1bt1aOTk5Kiws1L333quKigotXbpUSUlJIT/j9/vl9/urX/t8PmVnZ8vr9crtdjdX6UDEmTPHTA1TUSFNnChNnmx3RQgHAiCAqDZ79mzdeOON1a/fe%2B89nXHGGbWO2bZtm3JycvTyyy9r1KhRIc8zadIkPfDAA4e8TwAEpBdeMD2AkvT009Kvf21rOQgDAiCAqLZ3715t3769%2BnWnTp3UsmXLQ47r2bOnrr/%2Bet1xxx0hz0MPIHB4DzwgTZokxcebkcJDh9pdERojwe4CAKAxUlNTlZqaethjdu7cqc2bNyszM7POY5KSkuq8PQxAuu8%2BMy/gzJlm/eDFi6Xeve2uCg3FIBAAMaWkpES33XabFi9erA0bNmj%2B/PkaNmyY2rdvr5EjR9pdHhC1XC7pmWekM8%2BU9u41zwUytip6EQABxJT4%2BHitWLFCI0aMUG5urkaPHq3c3FwtXrz4iD2FAA4vKUl6/XUzQnjDBjM9TI0nJxBFeAYQAELw%2BXzyeDw8AwiEsHq1WTLO65WuvVZ6/nnTQ4joQQ8gAACol2OPlf75TykuzowQfuIJuytCfREAAQBAvQ0ZIj32mNm/7TZp7lx760H9EAABAECD3HKLuQVcVSVdcYUZJYzoQAAEAAAN4nJJTz0lnXqqtHu3NHKkVFpqd1U4GgRAAADQYMnJ0muvSenp0jffSDfcIDG8NPIRAAEAQKN07mwGhSQkSP/4h/TnP9tdEY6EAAgAABrtzDOlP/7R7N96q7Rokb314PAIgAAAICxuuUW68kqposIsF8dKIZGLAAgAAMLC5ZKefdbME7h1q3T11VJlpd1VIRQCIAAACJvWrc2gkFatpA8%2BkB580O6KEAoBEAAAhFVenvT002b/D3%2BQPvzQ3npwKAIgANRQUFCgvLw85efn210KENX%2B53%2Bk6683U8JcfbW0fbvdFaEml2UxWw8AHMzn88nj8cjr9crtdttdDhCV9u83k0R/%2B6107rnSnDlm/WDYjx8DAABoEi1bmvkBA88DPvqo3RUhgAAIAACazHHHBSeGvuce6bPP7K0HBgEQAAA0qTFjzPyAlZXSVVdJPp/dFYEACAAAmpTLJf31r1LXrlJhoTR2rN0VgQAIAACanMcjzZ5tBoHMmmXWDIZ9CIAAAKBZDBgg3Xuv2f/Nb6SNG%2B2tx8kIgAAAoNncc4902mmS1yuNHi1VVdldkTMRAAEAQLNJSDC3gFNSpAULpGnT7K7ImQiAAACgWfXoIT3%2BuNm/%2B25pxQp763EiAiAAAGh2118vXXSRVFYmXXON2aL5EAABAECzc7mkZ5%2BV2rWTvv5aevBBuytyFgIgAACwRUaG9NRTZn/KFGnJEnvrcRICIAAAsM1llwVXCRk9WjpwwO6KnIEACAAAbPXkk1J6urRqlTRpkt3VOAMBEAAA2KpdO7NUnCT98Y/cCm4OBEAAAGC7iy%2BWfvELMzH0mDGS3293RbGNAAgANRQUFCgvL0/5%2Bfl2lwI4zp/%2BJHXsKK1cKT38sN3VxDaXZVmW3UUAQKTx%2BXzyeDzyer1yu912lwM4xquvSpdfblYMWbpUOuEEuyuKTfQAAgCAiHHppdLIkVJFhXTddWaL8CMAAgCAiOFySQUFUps20pdfStOn211RbCIAAgCAiJKZaUYDS9J990mFhfbWE4sIgAAAIOJcd5101lnSvn3STTdJjFgILwIgAACIOC6X9PTTUlKS9P770j/%2BYXdFsYUACAAAIlJurnTPPWb/97%2BXdu%2B2t55YQgAEAAAR6/bbpeOOk4qLpTvusLua2EEABAAAESsx0dwKlqRnn5UWLbK3nlhBAAQAABHtjDOkX/3K7N90k1Rebm89sYAACAAAIt7UqVK7dtKKFWbJODQOARAAAES89u1NCJSkSZOkH3%2B0tZyoRwAEAABRYcwY6fTTpZISMyoYDUcABAAAUSEuTnrqKbN99VXpgw/srih6EQABAEDU6NtXGjvW7N98s1RWZm890YoACAAAosof/iB17CitWSNNn253NdGJAAgANRQUFCgvL0/5%2Bfl2lwKgDm3aBAeE/OEP0tat9tYTjVyWxfLKAHAwn88nj8cjr9crt9ttdzkADlJVJQ0cKH32mXT11dKsWXZXFF3oAQQAAFEnLk76858ll0uaPVv69FO7K4ouBEAAABCVTjkluELI735negVxdAiAAAAgak2eLLnd0ldfSTNm2F1N9CAAAgCAqNWxo3T//Wb/rrskn8/eeqIFARAAAES1m2%2BWcnOl4mLp4YftriY6EAABAEBUS0yUHnvM7D/xhLR%2Bvb31RIMEuwsAAABorAsvlC69VOrfX%2BrUye5qIh8BEAAARD2Xy6wPjKPDLWAAAACHIQACAAA4DAEQAADAYQiAAAAADkMABAAAcBgCIAAAgMMQAAEAAByGAAgANRQUFCgvL0/5%2Bfl2lwIATcZlWZZldxEAEGl8Pp88Ho%2B8Xq/cbrfd5QBAWNEDCAAA4DAEQAAAAIchAAIAADgMARAAAMBhCIAAAAAOQwAEAABwGAIgAACAwxAAAQAAHIYACAAA4DAEQAAAAIchAAIAADgMARBAVHn99dc1dOhQtW/fXi6XS8uXLz/kGL/fr3Hjxql9%2B/ZKSUnR8OHDtWXLFhuqBYDIRAAEEFVKS0s1cOBAPfLII3UeM378eL3xxht6%2BeWX9cknn6ikpEQXXXSRKisrm7FSAIhcLsuyLLuLAID62rBhg7p166Zly5bpxBNPrH7f6/WqQ4cOevHFF3XFFVdIkrZu3ars7Gy9%2B%2B67Gjp06FGd3%2BfzyePxyOv1yu12N8k1AIBd6AEEEFOWLl2q8vJyDRkypPq9rKwsHX/88Vq0aJGNlQFA5EiwuwAACKeioiIlJiYqLS2t1vvp6ekqKiqq83N%2Bv19%2Bv7/6tc/na7IaAcBu9AACiFizZ89W69atq9vHH3/c4HNZliWXy1Xn16dMmSKPx1PdsrOzG/y9ACDSEQABRKzhw4dr%2BfLl1e2UU0454mcyMjJUVlam3bt313q/uLhY6enpdX5u4sSJ8nq91W3z5s2Nrh8AIhW3gAFErNTUVKWmptbrMyeffLJatGihuXPn6vLLL5ckbdu2Td9%2B%2B60effTROj%2BXlJSkpKSkRtULANGCAAggquzatUubNm3S1q1bJUlr1qyRZHr%2BMjIy5PF4dN111%2BnWW29Vu3bt1LZtW912223q06ePzj33XDtLB4CIwS1gAFHl7bffVr9%2B/XThhRdKkq688kr169dPf/3rX6uPefzxx3XxxRfr8ssv18CBA9WqVSu98847io%2BPt6tsAIgozAMIACEwDyCAWEYPIAAAgMMQAAEAAByGAAgAAOAwBEAAAACHIQACAAA4DKOAASAEy7K0d%2B9epaamHnYJOQCIRgRAAAAAh%2BEWMAAAgMMQAAEAAByGAAgAAOAwBEAAAACHIQACAAA4DAEQAADAYQiAAAAADkMABAAAcBgCIAAAgMMQAAEAAByGAAgAAOAwBEAAAACHIQACAAA4DAEQAADAYQiAAAAADkMABAAAcBgCIAAAgMMQAAEAAByGAAgAAOAwBEAAAACHIQACAAA4DAEQAADAYQiAAAAADkMABAAAcBgCIAAAgMMQAAEAAByGAAgAAOAwBEAAAACHIQACAAA4DAEQAADAYQiAAAAADkMABAAAcBgCIAAAgMMQAAEAAByGAAgAAOAwBEAAAACHIQACAAA4DAEQAADAYQiAAAAADkMABAAAcBgCIAAAgMMQAAEAAByGAAgAAOAwBEAAAACHIQACAAA4DAEQAADAYQiAAAAADkMABAAAcBgCIAAAgMMQAAEAABzm/wOGf96XXKdo3wAAAABJRU5ErkJggg%3D%3D'}
Genus 2 curve data - 20736.k.373248.1