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g2c_curves • Show schema
{'Lhash': '1336698070319187516', 'abs_disc': 776, '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,[1,1,1]],[97,[1,-13,83,97]]]', 'bad_primes': [2, 97], 'class': '388.a', 'cond': 388, 'disc_sign': 1, 'end_alg': 'Q', 'eqn': '[[0,1,2,0,-1],[1,1,0,1]]', 'g2_inv': "['59049/776','-22599/388','7209/194']", 'geom_aut_grp_id': '[2,1]', 'geom_aut_grp_label': '2.1', 'geom_aut_grp_tex': 'C_2', 'geom_end_alg': 'Q', 'globally_solvable': 1, 'has_square_sha': True, 'hasse_weil_proved': False, 'igusa_clebsch_inv': "['36','1569','-13743','99328']", 'igusa_inv': "['9','-62','356','-160','776']", 'is_gl2_type': False, 'is_simple_base': True, 'is_simple_geom': True, 'label': '388.a.776.1', 'leading_coeff': {'__RealLiteral__': 0, 'data': '0.1982006890788402079094610010913380998860510457153074278', 'prec': 190}, 'locally_solvable': True, 'modell_images': ['2.10.1', '3.80.1'], 'mw_rank': 0, 'mw_rank_proved': True, 'non_maximal_primes': [2, 3, 7], 'non_solvable_places': [], 'num_rat_pts': 6, 'num_rat_wpts': 0, 'real_geom_end_alg': 'R', 'real_period': {'__RealLiteral__': 0, 'data': '29.135501294589510562690767160', 'prec': 100}, 'regulator': {'__RealLiteral__': 0, 'data': '1.0', 'prec': 10}, 'root_number': 1, 'st_group': 'USp(4)', 'st_label': '1.4.A.1.1a', 'st_label_components': [1, 4, 0, 1, 1, 0], 'tamagawa_product': 3, 'torsion_order': 21, 'torsion_subgroup': '[21]', 'two_selmer_rank': 0, 'two_torsion_field': ['6.2.49664.1', [-1, 0, 0, -2, 3, -2, 1], [6, 13], 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': ['RR'], 'fod_coeffs': [0, 1], 'fod_label': '1.1.1.1', 'is_simple_base': True, 'is_simple_geom': True, 'label': '388.a.776.1', 'lattice': [[['1.1.1.1', [0, 1], [0]], [['1.1.1.1', [0, 1], -1]], ['RR'], [1, -1], 'USp(4)']], 'ring_base': [1, -1], 'ring_geom': [1, -1], 'spl_fod_coeffs': [0, 1], 'spl_fod_gen': [0], 'spl_fod_label': '1.1.1.1', 'st_group_base': 'USp(4)', 'st_group_geom': 'USp(4)'} -
g2c_ratpts • Show schema
{'label': '388.a.776.1', 'mw_gens': [[[[0, 1], [0, 1], [1, 1]], [[-1, 1], [-2, 1], [0, 1], [0, 1]]]], 'mw_gens_v': True, 'mw_heights': [], 'mw_invs': [21], 'num_rat_pts': 6, 'rat_pts': [[-1, 0, 1], [-1, 1, 1], [0, -1, 1], [0, 0, 1], [1, -1, 0], [1, 0, 0]], 'rat_pts_v': True} - g2c_galrep • Show schema
- g2c_tamagawa • Show schema
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g2c_plots • Show schema
{'label': '388.a.776.1', 'plot': 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fgz9u2FC69FLpsstsHCYiCwEQAEKHABjlNm2yIHhoK6q3MC7O9tVt21Y64YRgMExNjcHeQseRsrKkd96xy8Fdu0qDBkmVKhU45auvpJdekt56S8rODt69bVs7feBAJgxHCgIgAIQOATAG5eZaCPxjMPz998LPr1UrGAbzg%2BFxx0nly4e3bjft3Su9/74tJTNtmnToEoKnnGJB8IILWLbHTQTA0HAcW5t0zx5re/day8mxlptr//737w%2B2Awfsfnl5BR/L57MPlnFxwbVOy5cPtsTEYKtY0VqlSrawe8x96ASiDAHQIxxHWrfu8FC4ZMnhf9QlKSHBLhkf2lPYtq1UrVr4aw%2B3LVukt9%2BWXntNmjkzOFM7Ls42F7noIql/fwvOCB8CoP1b3LHD/o1u3Rps27fb/Kft260nOztbCgSs7dgh7dxpbdcua4W958PJ57PJa1WqWEtKkpKTrfn9UtWq1qpVk2rUsD2/a9SwlpJitzNeFygdAqDH7d5tCynnB8J58%2Bzrzp2Fn9%2Bw4eGXkP/0p9j9Y7xmjfTmm9Ibb0izZgVvzw%2BDF15oYZCewbIXqwEwN1fasCHYNm60tmmTtHlz8OvmzRb8Ctvg5ljFx1tvXIUK1kuXkGAtvwevXDlr%2Bb18cXEFe%2B7y8oItv6dw3z5rubnWcnKsh3HPnsKHphxr3Skp9iGsdm0bxpLf6tYNtnr1Coz6AHAIAiAOk5cnrVhRMBD%2B%2BKP022%2BFn1%2B5cnD2cf7XNm3sU30sWbHCxgq%2B%2BaY0Z07w9rg4G2J4wQUWBuvVc6/GWBZtATAvz8LbmjXS2rUF27p1Ntt/3TrrwSupChWsVyy/VasW7DWrWtV60ZKT7T2Y36pUsfdqfqtY0cJeOO3fbx8683si83smd%2BwI9ljm92Ju22Zt61YLvvktECjZ76xWTWrQINgaNpQaNbLWuLHNDYvVD7DAkRAAUWzbtx9%2BCfnnn%2B0TfmH%2B9KeCwbBNG6lp09j4Y7t8uV0mfustafbsgj876SRbX3DAAKlJE3fqi0WRFgCzs%2B1D0apVwbZ6dbCtXVv83rry5Qv2ZNWqVbDVrGktJcUug3q5Vysnx8Yzb9pkbePGgj2o69ZZW7vWwubRJCRYGGzSxP5mNW1qrVkz%2B551VhGrCIAolf37bRzhoaHwp5/sD3BhKlWyxavz90Ru08a%2Bj%2BbxdL/9ZpON335b%2Buabgj9r397C4Pnn28QaHLtwBkDHsd6nlSut53flSmu//RZsh84aL4rPZ4Gufn3rGa5XL3hpsm5d631KTbVQx6SI0HIce43WrLG2enUwqOe/hqtX22XrI6lbV2re3FqLFlLLlvb1T3/y1kQ5xB4CIMrE778XXK9w/nxpwYKiN%2BioVcuCYOvWNvmkdWtbi69q1WMsYP9%2B6d13pSlT7Jeecop0xRVlPotl7Vr7lZMnSzNmFBxs36qVjRm88ELWGSyRBQukF15QYOlS%2BT/8UNkzZyq5a9dSP%2Bzu3Rbuli%2B3r4e2lSuLd6mxenXrPWrY0Fr%2BJcb69e24Th1CQiTbv9/CYf7r/uuv9u/h119tq85t24q%2Bb7ly1lP45z9ba9nS3uMtW9JriOhAAETYHDggLV1acD/k%2BfPtD25R/wrr1rWwlN/y/9impByhxyQ7W%2BrZs%2BCsDcm6WT7%2BWOrYMaTPqyibN0vvvWe9g599VvByYFqadPHF0iWXWM8CivDgg9Jtt0mSApL8krIlJf/jH9L99x/xrnl51hO9fHnhrahF1A9Vq5ZdGmzc2Fr%2BuLH8MWT8jz62bd1qf7OWLrUrHflt8eIjX15u3NjCYP6H2datLRh6YiF%2BRA0CIFyXvyfyzz9bW7DA2po1Rd%2BnenX7g3rcccFLMi1a2CfyxL8MkV5%2BufA71qtnH/XD3C2zbZs0dapdJv7vfwuGwfR024pu0CBvLLNTbDNm2FTr/ykQACXpvfe0%2B8x%2BB3vxfv3VWn5PzooVRY9Pzef3B8d%2BNWlSsDVq5O2xdihaXp719i9aZGuuLlpkf8MWLrQPfoWJi7MPe23aBMdEt21rYZHL/3ADARARKzs7%2BEd14UL7Q/vLL3Z5rigp%2Bl1rVE%2BJyi36pDfesMX8XLJ9u12dfv116dNPg2OQKlSwrehuvZXxgpLsNXrrrYPf/jEATk/oqdNy/3vEh4iPtyD3pz8FW9OmwZBXvXpZPgF40e%2B/Bz/ELlgQ/GBb1Gzv5ORgGMxfXqtNG3oLUfYIgKXgOI527Njhdhmes3u3jc9ZssQuzSxbFmxpO79Vlnod8f4v1bpVWZ3/qfr1bbzWoYPza9e20BAumzdbxnnlFQu5kvUG3HSTNGpUeGtxy759NjB/%2BfLgZIsVK6T7szqqSe7Sg%2BcFJDWQtFoWANertlpqiZKTg5do//Sn4HHjxjYOr1y5cD8joCDHsRnKCxbY%2Bzw/GC5eXPhMcZ/Prmgcf3zBxgeW0EtKSpLPo12wBMBSyJ%2BVCAAAok%2BkLCvlBgJgKRzaA5ienq7vv/%2B%2B2Pctyfll9diBQEANGjTQ6tWri/UGiJrn2K2brWBdCCc%2BXp89uVDLdqQWWB5i3Tr7hF7yLbL2q2rVckpODi60W6lScL/T/F0VypWTpkx5W%2Beff8HBXRNyc603M39rr/Xr7Wu%2BmjUf1rJlGUetoKSvo1Q2r01env33POusm3XDDU9oyZLguLz164983woVrMfu0AkXpyx6Vq3H33bwnD/2AOruu6Vbbil13SU9tywfO1rfk154jiU5vzTvyfzewvxVFPJXUihqIf46dezScbt21k44oeCyWpH4HEN9bmke28s9gFwcKQWfz3fwH358fHyJPkWU5PyyfGxJSk5OLtb5UfMcH39c6tWr8DVn7r5bA65vUejdDhywmaFdulyoJ554S%2BvX2x/i/AVnN2%2B28T2//27jeXL/N8xw%2B3ZrR3eVXnzx6Gc1by4NHiy9%2Buq7Sk6%2BtzgPLKn4r6MUmtdm0yYbw/jdd9IPP1jmti0EJ%2BjOOw9/nOrVCy6y26yZNHLkZfr664mqU6eQgfB7hkkLJ9svOPR5Skpu3VoaMcIGUJXhc3TjsaXoe0964Tkey/nH%2Bp70%2B20c8IUXBn%2B%2Bfbs0d6691%2B699wPVqXOOliyxD1fr10vTpgXPrV/fFjvo2FHas%2BdU7duXrBo1ildzuJ5jqOso63%2BvsYgAGCI33nhjmZ1flo9dlo/r2nM89VRp5kzp3nvlfPSRfHl5OtC6teL//ndLVkWIj7dxgBkZ3dW375F/v%2BPY3qaPPTZe/ftfqUDAevJ27rRevd277ee5uTbGZ/9%2B6dtvZ6lTp07y%2BaxXMCHBegqTky0c1aljY9jy/y5Vr35tif6blERpXptPP5XuuUf66qvDzy1fXqpRY6u6dKmutLTgArrNm6vQ/wHt3HmS6tYt4hdXrGi/7N57pRdfPNg9mnP11dJDD9n/JUtQd6jOLevHLqs6Sno%2Bz7H054fysatWlU47zVqFCr/pxhvtb868ebY15ezZ9nXx4uDi1%2B%2B%2BK0nPKyXFetfT04OtffvCt%2BuMlNcykl73WMUlYA%2BLtK21ykJg0ybVq11ba2P5OYbxdfzyS8vX%2BX81TjjBrrh36GCXn1q2LKNJFwcOaM3ixWrQqpVWr16t%2BvXrl8EvcZ8n3pM8xzK1Y4f1Es6eHWzLlh1%2Bns9na6p26hQMhccfLyUmFu/3eOF1jHX0AHpYYmKiRo4cqcTivuOjUKLfr1ti/TmG8XWcPTsY/u6/35asCcuSivHxSqxZU5J4LaMcz7FsJSXZh7Ju3YK3bdsW7CX8/ntrq1cHl9iaMMHOS0iwD3WdOgWDYYsWhe/f7oXXMdbRAwig2AIBqWtXG5gu2VijK6%2B0K%2BtlvaMJPQ5A6GzYEAyDs2bZ18LWKvT7LQjmh8JOnWy4CqIfARBAieTkSOPGSY8%2BahNB8nXsKJ1/vrWyCIMEQKDsOI6txZkfBr/7ziad7Nlz%2BLn160udO1sY7NzZhoBUqRL%2BmlE6BEAAx2TvXtvr%2BMUXba/j/B1NJBtb1K%2Bf1KePdPLJoVnQmgAIhNe%2BfbZgdX4gnDXLLhn/cbmsuDjb3zw/FHbqZPsfswh7ZCMAAii1jRttxuHbb0vTp9us53zVqtmqPL17Sz172m4rx4IACLhv504bSzhrVrCtXn34eRUrWs9g587BYNiwIfseR5JChnYilkyePFm9evVSSkqKfD6f5hWxQPKhJkyYIJ/Pd1jbW9i6ehHuWJ5/pHIcR/fcc4/q1q2rihUrqnv37lqwYMER73PPPfcc9jqmpqaGvLbataVrr5WysmydxEmTpEGDLPxt22b7Hl9%2BuZSaav9T%2BMc/bKWe3CNs2VzAr79asowBTz/9tJo0aaIKFSqoQ4cO%2BuKLL4o8N5beizNnzlTfvn1Vt25d%2BXw%2BvWtrlESlkj6X6dOnF/o6Llq0KEwVh86TT47Rrbem61//StLMmbXUvv15mjlzmd59V7rjDun0020pqz17bNWARx6xbb0bN7axg/362QSyrKzirp%2BKskIAjHG7du1Sly5d9MADD5TofsnJyVq/fn2BVqFChTKqsuwc6/OPRA8%2B%2BKAeffRRPfXUU/r%2B%2B%2B%2BVmpqqHj16HHU/6latWhV4HefPn1%2Bmdfr9Fv4mTbIxgl9%2Baf9jaN/efv7DD9KYMTZLsUYN6dxzpaeesn2dD7sesWyZdMYZtmr0uefabb162XWpKPTGG29o%2BPDhuvPOOzV37lx17dpVZ599tlatWlXkfWLpvdi2bVs99dRTbpdSasf6XBYvXlzgdWxe1jOnysCMGTN044036ttvv1VWVpb279%2Bvyy47Q2eeuUujR9twkG3bbL/j8eOl66%2B39365cnal4P33pX/%2B064GVKtmS0cNGSJlZlrPYrE/FKL0HHjCihUrHEnO3Llzj3ru%2BPHjHb/fH4aqwqckzz8S5eXlOampqc4DDzxw8La9e/c6fr/fefbZZ4u838iRI522bduGo8RiWb/ecV5%2B2XEuucRxatZ0HIt8wdaokeP85S%2BO8%2BabjrN10UbHqVfv4A%2BzJUf/%2B%2BrUqOE4v/3m9tMpsU6dOjnXXXddgdtatmzp3H777YWeH4vvRcdxHEnOlClT3C4jJIrzXD7//HNHkrNt27YwVRU%2BmzZtciQ5M2bMOOJ5u3c7zldfOc6jjzrOwIGO06TJ4e9/yXESEhync2fHGTbMcSZOdJwlSxwnLy9MT8Zj6AFEoXbu3KlGjRqpfv36OuecczR37ly3S/K0FStWaMOGDerZs%2BfB2xITE9WtWzd9/fXXR7zv0qVLVbduXTVp0kQDBw7U8uXLy7rcIqWm5m9zZ8tQzJ5tvYHdu9t6gr/9Jj33nF0yerzlM9LatYU/0JYtNhU5iuTm5mrOnDkFXkNJ6tmz5xFfQ96LsaNdu3aqU6eOzjjjDH3%2B%2BedulxMS2dnZkqTq1asf8byKFW1C2N/%2BJr32ms043rRJ%2BuAD29b7rLNsR6TcXJtw8uST0mWX2TqENWpYx/9dd1kP4saN4XhmsY85OjhMy5YtNWHCBLVp00aBQECPP/64unTpoh9//DEqL1nEgg0bNkiSav9hBkXt2rX1W1G7xEvq3LmzXn75ZbVo0UIbN27Ufffdp5NPPlkLFixQjeJuDlpG4uJsPGCHDtLtt0u7dkkzZtjYoKws6dwFRx5X5bz7rnyPPhqmakvv999/14EDBwp9DfNf3z/ivRgb6tSpo%2Beee04dOnRQTk6OXnnlFZ1xxhmaPn26Tj31VLfLO2aO42jEiBE65ZRT1Lp16xLfv2ZNWymgT5/8x7PhvvkzjmfNsqVotm2TPvnEWr6GDQsuWN2hQ%2BFb2%2BEI3O6CROhMnDjRqVy58sE2c%2BbMgz8rzSXQAwcOOG3btnWGDRsWynJDrqyevxv%2B%2BFymT5/uSHLWrVtX4LxrrrnG6dWrV7Efd%2BfOnU7t2rWdRx55JNQlh1xui7QC14YKXAKWnHVxdZ3LL3ecV16xS8uRbu3atY4k5%2Buvvy5w%2B3333eccd9xxxXqMaHkvHo08dgm4MOecc47Tt2/fMqgofG644QanUaNGzurVq8vsd%2BTkOM7s2Y7z9NOOc8UVjpOW5jg%2B3%2BGXjn0%2Bx2nVys756KMyKyem0AMYQ/r166fOnTsf/L5evXohedy4uDilp6dr6dKlIXm8slJWz98Nf3wuOTk5kqwnsM4hy/Bv2rTpsB6lI6lcubLatGkT8a%2BlJJU//VRpycIif/5/ed318svSyy/b923a2MDyHj1sv%2BKKFcNUaDGlpKQoPj7%2BsN6%2BkryG0fJexNGdeOKJmjj%2B45hTAAAgAElEQVRxottlHLNhw4Zp6tSpmjlzZpnuzZ2QELxScP31dlsgYFvb5fcS5m9tt2CBtSZNpLPPLrOSYgYBMIYkJSUpqQz6wB3H0bx589SmTZuQP3YoldXzd8Mfn4vjOEpNTVVWVpbatWsnycaUzZgxQ2PHji324%2Bbk5OiXX35R165dQ15zyN18s21SWsiSJ065cmo%2BbrhuW22Xi%2BfOlebPt/bII7ahfdeuNm6oRw/b5N7t9ccSEhLUoUMHZWVlqX///gdvz8rK0rn5M5yPIlreizi6uXPnFvgwFy0cx9GwYcM0ZcoUTZ8%2BXU2aNAl7DcnJ0mmnWcu3YUMwDBL%2BiocAGOO2bt2qVatWad26dZJsGQJJSk1NPbge3OWXX6569eppzJgxkqRRo0bpxBNPVPPmzRUIBPTEE09o3rx5yszMdOdJlEJxnn808Pl8Gj58uEaPHq3mzZurefPmGj16tCpVqqRBgwYdPO%2BMM85Q//79ddNNN0mSMjIy1LdvXzVs2FCbNm3Sfffdp0AgoCFDhrj1VIrvz3%2BW3nnHZo0cuklpUpJ8//mPOl2Yrk6SHnjA1h789FMbI5SVJa1ZY99/%2BqndJTXVgmB%2BIKxVy5VnpBEjRmjw4MHq2LGjTjrpJD333HNatWqVrrvuOkmx/V7cuXOnli1bdvD7FStWaN68eapevboaNmzoYmUld7Tncscdd2jt2rV6%2BX/d0%2BPGjVPjxo3VqlUr5ebmauLEiXrnnXf0zjvvuPUUjtmNN96oV199Ve%2B9956SkpIO9mj7/X5VdLHbPTXV1hjs18%2B1EqKPu1egUdbGjx/v6H9jpw5tI0eOPHhOt27dnCFDhhz8fvjw4U7Dhg2dhIQEp2bNmk7Pnj0PG7cULYrz/KNFXl6eM3LkSCc1NdVJTEx0Tj31VGf%2B/PkFzmnUqFGB53bxxRc7derUccqXL%2B/UrVvXGTBggLNgwYIwV15Ke/Y4zsSJTvadd9oYwD%2BMg/yjvDzHWbjQccaNc5zevR2nUqXDxwu1b%2B84d9zhONOnO05ubpiex/9kZmY6jRo1chISEpz27dsXWD4jlt%2BL%2BUuh/LEd%2BnyjxdGey5AhQ5xu3bodPH/s2LFO06ZNnQoVKjjVqlVzTjnlFOfDDz90p/hSKux5S3LGjx/vdmkoIbaCAxAVjnUruJwc6auvrHfwv/%2BV/rgZTFKS7V5w9tm2FEWjRiEuHAAiEAEQQFQI1V7AGzcGw%2BB//2uXjw/VsqWFwbPPtnGEUbjpBgAcFQEQQFQIVQA8VF6eTSCZNs3C4DffSAcOBH9eqZLtRHf22VLv3vQOAogdBEAAUaEsAuAfbd9uE0c%2B%2Bkj6%2BGNp/fqCP2/VyoJgnz5Sly62vykARCMCIICoEI4AeCjHkX780XoHP/zQegfz8oI/r1rVZhWfc471ELq8sQoAlAgBEEBUCHcA/KOtW%2B0y8UcfWSjcsiX4s7g42%2Bf0nHOkvn1tBRu31x0EgCMhAAKICm4HwEMdOGCLzr7/vvUO/vRTwZ83bWrrkZ17LpeKAUQmAiCAqBBJAfCPfvtN%2BuADC4Sffy7l5gZ/Vr269Qz262fLzFSu7F6dAJCPAAggKkRyADzUjh22zMzUqdY7eOil4goVbCeS886zQJiS4l6dALyNAAggKkRLADzU/v22CPV771lbvjz4s7g46dRTpQEDpP79pfr13asTgPcQAAFEhWgMgIdyHOnnn6UpU6z9cUeSzp2lCy6Qzj9fatLEnRoBeAcBEEBEy8zMVGZmpg4cOKAlS5ZEbQD8oxUrLAhOnix9/bUFxHzt20sXXmitaVP3agQQuwiAAKJCtPcAHsn69RYG335bmjGj4HqD7dtLF11kjZ5BAKFCAAQQFWI5AB5q82YLg2%2B9ZTOKD92arlMnaeBAC4P16rlXI4DoRwAEEBW8EgAP9fvv0jvvSG%2B%2BKU2fHuwZ9PlsAskll9hl4urVXS0TQBQiAAKICl4MgIfauNF6BV9/3WYW5ytXztYXvOwyW1qmYkX3agQQPQiAAKKC1wPgoVatsiD46qu2X3G%2BpCSbRTx4sNS9uy01AwCFIQACiAoEwMItXChNmmRhcOXK4O0NGliv4JAh0nHHuVYegAhFAAQQFQiAR5aXZ5eGJ06U3nhDys4O/qxzZ%2BmKK2wCSdWqrpUIIIIQAAFEBQJg8e3da/sSv/SS9PHHwZnEFSrYziNXXSWddhqXiAEvIwACiAoEwGOzcaP1Co4fLy1YELy9SRMLgldcwTZ0gBcRAAFEBQJg6TiONHu29OKLNl4wELDb4%2BKkPn2koUOl3r2l%2BHh36wQQHgRAAFGBABg6u3fb%2BoLPPy998UXw9vr1LQhefTULTQOxjgAIICoQAMvGokUWBF96SdqyxW6Lj5fOPVe64Qbp9NNt4WkAsYUACCAqEADL1t690uTJ0jPPSF9%2BGby9ZUsLgkOGSPxnB2IHARBAVCAAhs/PP1sQfPllaedOu61KFZswctNNrCsIxAIWAQAQ0TIzM5WWlqb09HS3S/GM1q2lzExp7VrpqaekP//ZguBTT1mPYO/e0ief2MQSANGJHkAAUYEeQPc4jvTZZ9ITT0gffBAMfmlp0ogR0qWX2hqDAKIHARBAVCAARoZly6Qnn7TlZPIvD9eqZZeGb7hBqlHD3foAFA8BEEBUIABGluxsmz38xBPS6tV2W8WKtoTMLbdIjRu7Wh6Ao2AMIACgxPx%2BKSND%2BvVXW1i6XTtpzx4bJ9ismXTZZdL8%2BW5XCaAoBEAAwDErX1665BJpzhwpK0s680zbe3jSJOn446V%2B/aTvvnO7SgB/RAAEAJSaz2fhLyvLwuAFF9ht778vnXii1KOHNHOm21UCyEcABACEVPv20ltvSb/8YmsHlisnffqp1K2b1L279PnnblcIgAAIACgTxx0njR8vLV0qXXedXS6eMcO2l%2Bve3Y4BuIMACAAoU40b284iy5dLN94oJSRY%2BOve3S4bf/ON2xUC3kMABACERf36Nkv411%2Bl66%2B3HsHPPpNOPlk65xzpxx/drhDwDgIgACCs6teXnn7aLg1fdZUUHy99%2BKF0wgnSoEEWEAGULQIgAMAVjRpJ//mPtHChdPHFdttrr9new8OGSZs3u1sfEMsIgAAAV7VoIb3%2BuvTDD1KvXtK%2BfXapuGlT6f77pd273a4QiD0EQABARGjXTvr4YxsX2KGDtGOH9M9/2mziV16R8vLcrhCIHQRAABEtMzNTaWlpSk9Pd7sUhMnpp0uzZtluIg0bSmvWSJdfLnXuLH31ldvVAbHB5ziO43YRAHA0gUBAfr9f2dnZSk5OdrschMnevdK4cdLo0dYjKEkDB0oPPig1aOBubUA0owcQABCxKlSQbr/dZgwPHWrby73%2Bul0Wvu8%2BC4gASo4ACACIeLVrS889Z/sMd%2B0q7dkj3XWX1Lq19NFHblcHRB8CIAAgarRrZ7uITJok1a1rawb26SOdd570229uVwdEDwIgACCq%2BHy2YPSiRVJGhlSunPTee1Jamo0N3LfP7QqByEcABABEpaQk6aGHpHnzpFNPtfUCb7vNlpD59lu3qwMiGwEQABDVWrWSpk%2BXxo%2BXatSQ5s%2B3/YWHDQvOHAZQEAEQABD1fD7piivssvDll0uOY7uJtGolTZvmdnVA5CEAAgBiRkqK9NJLUlaW1KSJtHq11Lu3NGSItHWr29UBkYMACACIOWeeaZeC//Y36x18%2BWXrDZw61e3KgMhAAARQ5q644gr5fL4C7cQTT3S7LMS4ypWlRx%2B17eNatpQ2bJDOPdd6A7dvd7s6wF0EQABhcdZZZ2n9%2BvUH20es3oswOekkae5cWzImvzewTRvp00/drgxwDwEQQFgkJiYqNTX1YKtevbrbJcFDKlSwJWO%2B%2BEJq1kxas0bq0UMaPtx2FQG8hgAIICymT5%2BuWrVqqUWLFho6dKg2bdrkdknwoC5dbN3A66%2B37x9/XEpPl3780d26gHDzOY7juF0EgNj2xhtvqEqVKmrUqJFWrFihu%2B66S/v379ecOXOUmJhY6H1ycnKUk5Nz8PtAIKAGDRooOztbycnJ4SodMWzaNOnKK6WNG6WEBGnsWOnmm6U4ukbgAQRAACE1adIkXXvttQe/nzZtmrp27VrgnPXr16tRo0Z6/fXXNWDAgEIf55577tGoUaMOu50AiFDavFm6%2Bmrp/fft%2B969pQkTpJo1XS0LKHMEQAAhtWPHDm3cuPHg9/Xq1VPFihUPO6958%2Ba65pprdNtttxX6OPQAIlwcR3rmGWnECCknR6pTR5o4UTr9dLcrA8pOObcLABBbkpKSlJSUdMRztmzZotWrV6tOnTpFnpOYmFjk5WEglHw%2B6YYbpK5dpYsvln75xdYRvPtu6a67pPh4tysEQo%2BRDgDK1M6dO5WRkaFvvvlGK1eu1PTp09W3b1%2BlpKSof//%2BbpcHHNSmjTR7tnTVVdYrOGqU1KuXxHwlxCICIIAyFR8fr/nz5%2Bvcc89VixYtNGTIELVo0ULffPPNUXsKgXCrVEn6z3%2BkV16xhaQ/%2B0w64QTpyy/drgwILcYAAogKgUBAfr%2BfMYAIm19%2Bkc4/377Gx0sPPyz99a92yRiIdvQAAgBQiD//WZo1S7rkEunAAdtXeNAgadcutysDSo8ACABAEapUkSZNsgWjy5WTXn/dtpZbscLtyoDSIQACAHAEPp8tEP1//yfVqiXNny917MhewohuBEAAAIqha1fphx%2BkTp2krVuls86SnnjCZgwD0YYACABAMdWrJ82YIV1%2BuY0L/Otfpb/8RcrNdbsyoGQIgAAAlECFCrZd3MMP2%2BXhF16QevaUtmxxuzKg%2BAiAAACUkM8n3XKL9MEHUlKS9QqeeKK0ZInblQHFQwAEAOAY9e4tff211KiRtGyZzRCeOdPtqoCjIwACAFAKrVtL330nde5sk0N69JBee83tqoAjIwACiGiZmZlKS0tTenq626UARapd25aJGTDAJoQMGiSNHcsMYUQutoIDEBXYCg7RIC9PysiQHnvMvr/pJmncONtKDogk9AACABAicXHSo49aAPT5pKeekgYOlPbudbsyoCACIAAAITZ8uG0bl5Agvf22dPbZUiDgdlVAEAEQAIAycNFF0rRptkzM9OlS9%2B7Spk1uVwUYAiAAAGXk9NMt/NWsKc2da9vJrVrldlUAARAAgDLVvr305Ze2VuCSJdIpp7BgNNxHAAQAoIy1aGEh8LjjpNWrpVNPlebPd7sqeBkBEACAMKhf33YJadtW2rjRxgTOmeN2VfAqAiAAAGFSq5b0%2BefBXUPOOEP69lu3q4IXEQABAAijatWkTz6xsYDZ2VLPnrafMBBOBEAAAMIsOVn6%2BGPptNOkHTukXr1sjCAQLgRAAABcULmy9MEHdhl4507prLOkr75yuyp4BQEQAACXVKokvf%2B%2BhcBduywEcjkY4UAABADARRUrSlOn2qLR%2BT2B33/vdlWIdQRAAABcVqmShcBu3WxMYM%2Be0rx5bleFWEYABBDRMjMzlZaWpvT0dLdLAcpU/pjAk0%2BWtm%2BXevSQFi50uyrEKp/jOI7bRQDA0QQCAfn9fmVnZys5OdntcoAyk50tnXmmNHu2VKeO9MUXUtOmbleFWEMPIAAAEcTvtyViWreW1q%2B3MLh2rdtVIdYQAAEAiDA1athi0c2aSStX2pjALVvcrgqxhAAIAEAEqlNH%2BvRTqV49GwvYu7fNEgZCgQAIAECEatTIegJr1JBmzZIGDJByc92uCrGAAAgAQARLS5M%2B%2BshmCWdlSVdcIeXluV0Voh0BEACACNepk/TOO1K5ctJrr0kZGW5XhGhHAAQAIAr06iVNmGDHjz0mPfKIq%2BUgyhEAAQCIEpdeKj34oB1nZEhvvuluPYheBEAAAKJIRoY0bJgdDx5sC0UDJUUABAAgivh8dgm4f3%2BbEXzeedKSJW5XhWhDAAQAIMrEx0sTJ9rkkK1bbY3A3393uypEEwIgAABRqFIlaepUqXFj6ddfrUcwJ8ftqhAtCIAAAESp2rWlDz%2B0/YO//FIaOlRyHLerQjQgAAKIaJmZmUpLS1N6errbpQARKS1Neustuyz8yivSmDFuV4Ro4HMcPisAiHyBQEB%2Bv1/Z2dlKTk52uxwg4jz7rHT99XY8ebJdEgaKQg8gAAAx4LrrpJtusuPBg6WffnK3HkQ2AiAAADHiscekM8%2BUdu2S%2BvWTNm92uyJEKgIgAAAxolw56Y03pGbNpN9%2Bky66SNq3z%2B2qEIkIgAAAxJDq1aX33pOqVJGmT5duucXtihCJCIAAAMSYtDRbKFqSnnxSeukld%2BtB5CEAAgAQg849Vxo50o6vvVaaM8fdehBZCIAAAMSou%2B%2BW%2Bva1HUIGDGC7OAQRAAEAiFFxcdLLL9ukkFWrpEGDpAMH3K4KkYAACABADKtaVZoyxfYOzsqS7rnH7YoQCQiAAADEuNatpeeft%2BP77pM%2B%2BsjdeuA%2BAiAAAB4waJB0ww12PHiwrRMI7yIAAgDgEY8%2BKnXsKG3daotE5%2Ba6XRHcQgAEAMAjEhOlt96SqlWTZs2SbrvN7YrgFgIgAAAe0rixNGGCHY8bZ7uGwHsIgAAiWmZmptLS0pSenu52KUDM6NdPGjHCjq%2B80paIgbf4HMdx3C4CAI4mEAjI7/crOztbycnJbpcDRL3cXKlrV7sUfPLJtm9w%2BfJuV4VwoQcQAAAPSkiQXn9dSk6Wvv6a9QG9hgAIAIBHNWkivfCCHY8ZI/3f/7lbD8KHAAgAgIddeKF0zTWS49j6gFu2uF0RwoEACACAx40bJ7VsKa1bJ119tYVBxDYCIAAAHle5svTaazYu8L33pOeec7silDUCIAAA0AknSKNH2/Hf/iYtXuxuPShbBEAAACDJgt8ZZ0h79kiXXSbt2%2Bd2RSgrBEAAACBJiouTXnrJtoqbPVu69163K0JZIQACKJXJkyerV69eSklJkc/n07x58w47JycnR8OGDVNKSooqV66sfv36ac2aNS5UC%2BBo6tWTnn3WjkePlr791t16UDYIgABKZdeuXerSpYseeOCBIs8ZPny4pkyZotdff11ffvmldu7cqXPOOUcHDhwIY6UAiuuii6RLL5Xy8mxpmF273K4IocZWcABCYuXKlWrSpInmzp2rE0444eDt2dnZqlmzpl555RVdfPHFkqR169apQYMG%2Buijj9SrV69iPT5bwQHhtX271KaNtGaNdOON0lNPuV0RQokeQABlas6cOdq3b5969ux58La6deuqdevW%2Bvrrr12sDMCRVK0qvfiiHWdmSp9%2B6m49CC0CIIAytWHDBiUkJKhatWoFbq9du7Y2bNhQ5P1ycnIUCAQKNADh1aOHdMMNdnzVVVJ2trv1IHQIgACKbdKkSapSpcrB9sUXXxzzYzmOI5/PV%2BTPx4wZI7/ff7A1aNDgmH8XgGP34INS06bS6tXSiBFuV4NQIQACKLZ%2B/fpp3rx5B1vHjh2Pep/U1FTl5uZq27ZtBW7ftGmTateuXeT97rjjDmVnZx9sq1evLnX9AEqucmVp/HjJ57NLwh9/7HZFCAUCIIBiS0pKUrNmzQ62ihUrHvU%2BHTp0UPny5ZWVlXXwtvXr1%2Bvnn3/WySefXOT9EhMTlZycXKABcEfXrtLNN9vxNddwKTgWlHO7AADRbevWrVq1apXWrVsnSVr8v/2jUlNTlZqaKr/fr6uvvlq33HKLatSooerVqysjI0Nt2rTRmWee6WbpAEpg9Gjpgw%2BkX3%2BVMjKk5593uyKUBj2AAEpl6tSpateunfr06SNJGjhwoNq1a6dn81eSlfTYY4/pvPPO00UXXaQuXbqoUqVKev/99xUfH%2B9W2QBKqFKl4KzgF15gVnC0Yx1AAFGBdQCByHDTTbYsTOPG0vz5UpUqbleEY0EPIAAAKLYxY6SGDaWVK6U773S7GhwrAiAAACi2pCTpuefs%2BMkn2Ss4WhEAAQBAifTqJV1%2BueQ4Nis4N9ftilBSBEAAAFBijz4q1awpLVggjR3rdjUoKQIgAAAosRo1pHHj7Pi%2B%2B6T/rQCFKEEABAAAx%2BSSS6SzzrJLwNdea5eEER0IgAAA4Jj4fNIzz9gagTNmSBMmuF0RiosACAAAjlnjxtI999hxRob0%2B%2B9uVoPiIgACAIBSGT5cOv54aetW6dZb3a4GxUEABBDRMjMzlZaWpvT0dLdLAVCE8uWl/N0fJ0yQZs50tRwUA1vBAYgKbAUHRL5rr7VFotPSpHnzLBgiMtEDCAAAQmLMGFsbcOFC6bHH3K4GR0IABAAAIVG9uvTQQ3Y8apS0erW79aBoBEAAABAyl18udeki7d4t/e1vbleDohAAAQBAyPh80tNPS/Hx0jvvSFlZbleEwhAAAQBASB1/vHTTTXZ80022UwgiCwEQAACE3KhRUu3a0pIlwT2DETkIgAAAIOT8fmnsWDu%2B915p3Tp360FBBEAAAFAmBg%2BWTjpJ2rVL%2Bvvf3a4GhyIAAgCAMhEXJz35pE0MmTRJ%2BuortytCPgIgAAAoMx06SFddZcc33yzl5blbDwwBEAAAlKnRo6XkZOmHH6Tx492uBhIBEAAAlLFataS777bjf/xDCgTcrQcEQAAAEAbDhkktWkibNkn33%2B92NSAAAgCAMpeQID3yiB2PGyctX%2B5uPV5HAAQQ0TIzM5WWlqb09HS3SwFQSn36SD162M4gLAvjLp/jOI7bRQDA0QQCAfn9fmVnZys5OdntcgAco59/ltq2tdnAM2ZIp57qdkXeRA8gAAAIm9atpaFD7fiWW1gWxi0EQAAAEFb33islJUmzZ0uvvup2Nd5EAAQAAGFVq5Z0xx12/I9/SHv2uFuPFxEAAQBA2A0fLjVoIK1eLT3%2BuNvVeA8BEAAAhF3FirZDiCSNGSNt3uxuPV5DAAQAAK4YNEhq1852BvnXv9yuxlsIgAAAwBVxcdJDD9nxM89Iy5a5W4%2BXEAABAIBrzjhDOussaf9%2B6c473a7GOwiAAADAVWPHSj6f9Oab0vffu12NNxAAAQCAq44/Xho82I5vu01ij7KyRwAEAACuu/deKSFB%2Bvxz6ZNP3K4m9hEAAQCA6xo1km680Y5vv50t4soaARAAAESEf/zDtoibN8/GA6LsEAABRLTMzEylpaUpPT3d7VIAlLGUFOnWW%2B34rrukffvcrSeW%2BRyHoZYAIl8gEJDf71d2draSk5PdLgdAGdm5U2raVNq0Sfr3v6W//MXtimITPYAAACBiVKkSXA9w1Chpzx5364lVBEAAABBRrr1WathQWrfOdghB6BEAAQBARElMlO6%2B247HjJF27HC3nlhEAAQAABFnyBCpeXPp99%2Blxx93u5rYQwAEAAARp1w5Wxxakh5%2BWNq2zd16Yg0BEAAARKSLLpJat5ays6VHHnG7mthCAAQAABEpLi7YC/j443Y5GKFBAAQAABHrvPOk9u1tfcAHH3S7mthBAAQAABHL57P1ACUpM9MWiEbpEQABAEBE69NHSk%2BXdu%2BWxo51u5rYQAAEAAARzecLjgV85hlpwwZ364kFBEAAABDxevWSTjzRtoZjLGDpEQABAEDE8/mkkSPt%2BNln6QUsLQIgAACICr16SZ07Wy/gQw%2B5XU10IwACiGiZmZlKS0tTenq626UAcNmhvYDPPMOM4NLwOY7juF0EABxNIBCQ3%2B9Xdna2kpOT3S4HgEscx3oBv/9euvVWxgMeK3oAAQBA1PD5pLvvtuOnn2Z3kGNFAAQAAFGlTx%2BpXTtp1y7pscfcriY6EQABAEBU8fmku%2B6y4yeflLZtc7eeaEQABAAAUefcc6XWraUdOywEomQIgAAAIOrExUl33mnHjz9uQRDFRwAEAABR6cILpRYtpK1bbXFoFB8BEAAARKX4eOn22%2B34kUdsgWgUDwEQAABErcsukxo2lDZulMaPd7ua6EEABAAAUat8eVsQWrJFofftc7eeaEEABFAqkydPVq9evZSSkiKfz6d58%2BYddk737t3l8/kKtIEDB7pQLYBYdPXVUq1a0m%2B/Sa%2B95nY10YEACKBUdu3apS5duuiBBx444nlDhw7V%2BvXrD7Z///vfYaoQQKyrWFH629/seOxYKS/P3XqiQTm3CwAQ3QYPHixJWrly5RHPq1SpklJTU8NQEQAvuv56acwYadEiac4cKT3d7YoiGz2AAMJi0qRJSklJUatWrZSRkaEdR1m0KycnR4FAoEADgKL4/dKECdLixYS/4qAHEECZu/TSS9WkSROlpqbq559/1h133KEff/xRWVlZRd5nzJgxGjVqVBirBBDt%2Bvd3u4Lo4XMcx3G7CADRYdKkSbr22msPfj9t2jR17dpVkl0CbtKkiebOnasTTjjhiI8zZ84cdezYUXPmzFH79u0LPScnJ0c5OTkHvw8EAmrQoIGys7OVnJwcgmcDAN5FDyCAYuvXr586d%2B588Pt69eod0%2BO0b99e5cuX19KlS4sMgImJiUpMTDymxwcAHBkBEECxJSUlKSkpqdSPs2DBAu3bt0916tQJQVUAgJIiAAIola1bt2rVqlVat26dJGnx4sWSpNTUVKWmpurXX3/VpEmT1Lt3b6WkpGjhwoW65ZZb1K5dO3Xp0sXN0gHAs5gFDKBUpk6dqnbt2qlPnz6SpIEDB6pdu3Z69n87syckJOizzz5Tr169dNxxx%2Bnmm29Wz5499emnnyo%2BPt7N0gHAs5gEAiAqBAIB%2Bf1%2BJoEAQAjQAwgAAOAxBEAAAACPIQACAAB4DAEQAADAYwiAAAAAHkMABAAA8BgCIAAAgMcQAAEAADyGAAggomVmZiotLU3p6elulwIAMYOdQABEBXYCAYDQoQcQAADAYwiAAAAAHkMABAAA8BgCIAAAgMcQAAEAADyGAAgAAOAxBEAAAACPIQACAAB4DAEQAADAYwiAAAAAHkMABAAA8BgCIAAAgMcQAAEAADyGAAgAAOAxPsdxHLeLAICjcRxHO3bsUFJSknw%2Bn9vlAEBUIxQigTgAAAFLSURBVAACAAB4DJeAAQAAPIYACAAA4DEEQAAAAI8hAAIAAHgMARAAAMBjCIAAAAAeQwAEAADwGAIgAACAxxAAAQAAPIYACAAA4DEEQAAAAI8hAAIAAHgMARAAAMBjCIAAAAAeQwAEAADwGAIgAACAxxAAAQAAPIYACAAA4DEEQAAAAI8hAAIAAHgMARAAAMBjCIAAAAAeQwAEAADwGAIgAACAxxAAAQAAPIYACAAA4DEEQAAAAI8hAAIAAHgMARAAAMBjCIAAAAAeQwAEAADwGAIgAACAxxAAAQAAPIYACAAA4DEEQAAAAI8hAAIAAHgMARAAAMBjCIAAAAAeQwAEAADwGAIgAACAxxAAAQAAPIYACAAA4DEEQAAAAI8hAAIAAHgMARAAAMBjCIAAAAAeQwAEAADwGAIgAACAxxAAAQAAPIYACAAA4DH/D4I88yOKviuWAAAAAElFTkSuQmCC'}
Genus 2 curve data - 388.a.776.1