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g2c_curves • Show schema
{'Lhash': '1467175788107318733', 'abs_disc': 30000, 'analytic_rank': 0, '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,[1,1,2]],[3,[1,1,3,3]],[5,[1,-2,1]]]', 'bad_primes': [2, 3, 5], 'class': '600.b', 'cond': 600, 'disc_sign': 1, 'end_alg': 'Q x Q', 'eqn': '[[-3,0,1,0,1],[0,1,0,1]]', 'g2_inv': "['81000000','563400','-595008']", 'geom_aut_grp_id': '[4,2]', 'geom_aut_grp_label': '4.2', 'geom_aut_grp_tex': 'C_2^2', 'geom_end_alg': 'Q x Q', 'globally_solvable': 1, 'has_square_sha': True, 'hasse_weil_proved': True, 'igusa_clebsch_inv': "['600','18744','4690524','120000']", 'igusa_inv': "['300','626','-198336','-14973169','30000']", 'is_gl2_type': True, 'is_simple_base': False, 'is_simple_geom': False, 'label': '600.b.30000.1', 'leading_coeff': {'__RealLiteral__': 0, 'data': '0.2598840782939821510919747178657407910403080325085854330', 'prec': 190}, 'locally_solvable': True, 'modell_images': ['2.180.3', '3.90.1'], 'mw_rank': 0, 'mw_rank_proved': True, 'non_solvable_places': [], 'num_rat_pts': 4, 'num_rat_wpts': 2, 'real_geom_end_alg': 'R x R', 'real_period': {'__RealLiteral__': 0, 'data': '8.3162905054074288349431909717', 'prec': 100}, 'regulator': {'__RealLiteral__': 0, 'data': '1.0', 'prec': 10}, 'root_number': 1, 'st_group': 'SU(2)xSU(2)', 'st_label': '1.4.B.1.1a', 'st_label_components': [1, 4, 1, 1, 1, 0], 'tamagawa_product': 8, 'torsion_order': 16, 'torsion_subgroup': '[2,8]', 'two_selmer_rank': 2, 'two_torsion_field': ['4.0.144.1', [1, 0, -1, 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': [['1.1.1.1', [0, 1], -1], ['1.1.1.1', [0, 1], -1]], 'factorsRR_base': ['RR', 'RR'], 'factorsRR_geom': ['RR', 'RR'], 'fod_coeffs': [0, 1], 'fod_label': '1.1.1.1', 'is_simple_base': False, 'is_simple_geom': False, 'label': '600.b.30000.1', 'lattice': [[['1.1.1.1', [0, 1], [0]], [['1.1.1.1', [0, 1], -1], ['1.1.1.1', [0, 1], -1]], ['RR', 'RR'], [2, -1], 'G_{3,3}']], 'ring_base': [2, -1], 'ring_geom': [2, -1], 'spl_facs_coeffs': [[[21], [81]], [[241], [-3689]]], 'spl_facs_condnorms': [40, 15], 'spl_facs_labels': ['40.a2', '15.a6'], 'spl_fod_coeffs': [0, 1], 'spl_fod_gen': [0], 'spl_fod_label': '1.1.1.1', 'st_group_base': 'G_{3,3}', 'st_group_geom': 'G_{3,3}'} -
g2c_ratpts • Show schema
{'label': '600.b.30000.1', 'mw_gens': [[[[-1, 1], [0, 1], [1, 1]], [[0, 1], [-1, 1], [0, 1], [0, 1]]], [[[7, 2], [-1, 2], [1, 1]], [[2, 1], [1, 1], [0, 1], [0, 1]]]], 'mw_gens_v': True, 'mw_heights': [], 'mw_invs': [2, 8], 'num_rat_pts': 4, 'rat_pts': [[-1, 1, 1], [1, -1, 0], [1, -1, 1], [1, 0, 0]], 'rat_pts_v': True} - g2c_galrep • Show schema
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g2c_tamagawa • Show schema
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id: 121337
{'label': '600.b.30000.1', 'local_root_number': 1, 'p': 2, 'tamagawa_number': 2} -
id: 121338
{'cluster_label': 'c4c2_1~2_0', 'label': '600.b.30000.1', 'local_root_number': 1, 'p': 3, 'tamagawa_number': 1} -
id: 121339
{'cluster_label': 'c2c2_1c2_1_0', 'label': '600.b.30000.1', 'local_root_number': 1, 'p': 5, 'tamagawa_number': 4}
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id: 121337
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g2c_plots • Show schema
{'label': '600.b.30000.1', 'plot': 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UWjUWVmZtqOAwAlihFAJEzFitKcOWbJuL/9TZo3z3YiAAAgUQCRYOGw9NBDZrtvX2nzZrt5AAAABRBJMGyY1KyZFI2ySggAAG5AAUTClS4tzZ4tlS8vLVnCKiEAANhGAURSNGwojR1rtu%2B7T9qwwW4eAAD8jAKIpOnXT2rdWvr1V%2Bm226S8PNuJAADwJwogkiYtTXr2WXN18LJlHAoGAMAWCiCS6pRTCg4FDx0qbdxoNQ48LDs7W%2BFwWBkZGapWrZquu%2B46ffHFF7ZjAYArUACRdHffLbVqZSaK7tOHq4KRGMuWLVPfvn313nvvacmSJdq3b5%2BuuOIK7dy503Y0ALCOlUBgxRdfSOecI8Xj0nPPSbfcYjsRvO77779XtWrVtGzZMl188cVH/H5WAgHgZYwAwoqGDQsmiL7nHunHH%2B3mgfdFo1FJUuXKlYt8Ph6PKxaLFboBgFdRAGHNvfdKjRpJP/xgzgcEEsVxHA0ePFitWrXSWWedVeT3ZGdnKxgM5t%2BysrKSnBIAkodDwLDq3/825wPu377wQrt54E19%2B/bVwoUL9a9//Ut16tQp8nvi8bji8Xj%2B/VgspqysLA4BA/AkRgBhVcuWZk5AyawVnJtrNw%2B8p3///nrllVe0dOnSQ5Y/SUpPT1dmZmahGwB4FQUQ1o0dK1WqJK1eLU2bZjsNvMJxHPXr10/z58/X22%2B/rZNPPtl2JABwDQogrKtaVXrkEbM9YoT0889288Ab%2Bvbtqzlz5mjevHnKyMhQTk6OcnJytGvXLtvRAMA6zgGEK%2BzbZ6aF%2BewzafBg6bHHbCdCqgsEAkU%2BPmPGDN16661HfD3TwADwMgogXOONN6R27aSyZc08gfXr204EP6MAAvAyDgHDNdq2lS67TNqzxxwKBgAAiUEBhGsEAgXrBM%2BdK61ZYzcPAABeRQGEqzRpInXqZNYHfvhh22kAAPAmCiBcZ%2BRI8/XFF6XPP7ebBQAAL6IAwnXOPlvq0MGMAo4fbzsNAADeQwGEK%2B1fG3juXCknx24WAAC8hgIIV2rRQmre3FwRzOogAACULAogXKt/f/N12jTWCEbyRCIRhUIhhcNh21EAIGGYCBquFY9LtWtLP/4oLVpkJokGkoWJoAF4GSOAcK30dKlrV7M9Z47dLAAAeAkFEK52883m6yuvSLt3280CAIBXUADhas2aSXXqSDt2SG%2B9ZTsNAADeQAGEqwUC0jXXmO033rCbBQAAr6AAwvUuv9x8XbrUbg4AALyCAgjXa9XKfF2zRopG7WYBAMALKIBwvWrVpNOy4qqrr/Xp8pjtOAAApDwKINzt11%2BlIUO0aksNfa36an5NFemGG6T1620nAwAgZTERNNxr3z7pssukZcsOfq56den996V69ZKfC77ARNAAvIwRQLjXSy8VXf4kaetWacyY5OYBAMAjKIBwrxdeOPzzzz%2BfnBwAAHgMBRDudaRLfnfskDiDASUsEokoFAopHA7bjgIACUMBhHs1aXL45887z8wUDZSgvn376rPPPtPKlSttRwGAhKEAwr369JHKlj308wMGJC8LAAAeQgGEe516qjnPr1y5g58bPFjq0SP5mQAA8ACmgYH7bdumCY1m6KQf1uri66vplNE9pEaNbKeCxzENDJBadu0yE0c0aiRlZdlO434UQLjetm1m2j9J%2Bv576aST7OaBP1AAAfdbt056/XVze%2BcdafduacIEacgQ28ncr7TtAMCRvP66%2BXruuZQ/APCzeNyM8i1aZG7r1hV%2Bvk4dqTTN5qiwm%2BB68%2BaZr9ddZzcHACD5cnKkhQul116TliyRdu4seK5MGalVK%2Bmqq6QrrzSHf5kc4uhQAOFq//uf%2BQ9ekm65xW4WAEDiOY70ySfSK69Ir74qrVhR%2BPmaNU3hu%2Boqs1ooZ2gUDwUQrjZunPkwuOoqc1EwAMB79u2T3n1Xevllc9u4sfDzTZtK114rXX21dP75jPKVBAogXGvtWmnGDLM9fLjdLACAkrVrlznCM3%2B%2BGen76aeC58qVM6N77dtL11xjRv1QsiiAcKW8POnuu6XcXKlDB%2BnCC20nAgAcrx07zPl8L71kLuI48Hy%2BKlXMKF%2BHDtLll0sVK9rL6QcUQLhSJGIu6S9fXnriCdtpAADFtX27uYDjxRfNrA67dxc8l5Uldexobq1acQVvMrGr4Toffijde6/ZHj9eOvlku3kAAMdm1y4z0vfCC%2BbrgaXvtNOk6683t6ZNOZ/PFgogXOW778x0L3v2mHM/%2Bva1nQh%2BE4lEFIlElJubazsKkFL27pXeekuaO1dasMAc7t3vtNOkzp2lG26QzjmH0ucGrAQC1/j5Z%2BmSS6SPP5bOOEN67z0pGLSdCn7FSiDAkTmO9MEH0nPPmdG%2B778veK5ePenGG6UuXcxE/pQ%2Bd2EEEK7wyy9mEs%2BPPzbLvi1aRPkDALf69ltT%2BmbNkj7/vODxqlXNSF/XrlKLFpQ%2BN6MAwrqtW035W73aXAW2ZAnn/QGA2%2BzZYyZnfvZZafFiM1uDZKZsue46qVs3c/VumTJ2c%2BLoUABh1eefm4k9N2yQqlUz5a9xY9upAAD7ffGFNH26Ge374YeCx1u1km691ZzXx1kSqYcCCGsWLTKHCaJR6ZRTpDfekBo0sJ0KALB3r7mQY%2BpUaenSgsdr1jSl77bbzIUdSF0UQCTdvn3Sww9Ljzxi7rdsKf397%2BbcEQCAPVu3Sn/%2Bs/T009KWLeaxtDSzHOcdd5ivzNXnDfzPiKTauNGcJ/Kvf5n7d90lTZwolS1rNRYA%2BNrq1WbS/eefN6N/krkg7/bbpTvvlOrWtZsPJY8CiKRwHOkvf5EGDzazwmdkmL8yb7rJdjIA8CfHkd58U/rTn8z8ffs1by4NGGAmauaPc%2B%2BiACLh/vc/qU%2Bfgg%2BYli2l2bPNeX8AgOTKzZXmz5fGjDEjf5JUqpS5mOOee6RmzezmQ3JQAJEwu3ZJ48ZJY8dK8bhZ1/eRR6RBg8yHDQAgeXJzpb/%2B1XwO75%2B7r2JFc27foEFm4mb4BwUQJc5xzKLf998vff21eeyKK6QpU6RTT7WbDQD8xnGkl16SHnpIWrvWPFapkjRwoNS/v5l/Ff5DATwOjuNo%2B/bttmO4yvLl5kNm5Upzv3Zt6Y9/NJOEBgJSLGY3H3Ao8Xhc8Xg8//7%2B/7ZjvGmRwv75T/OZvGqVuV%2BpktSvn9S7d8HcfX5%2Bi2dkZCjg0%2BVKWAv4OOxfKxQAAKQeP6/1TQE8DsUZAYzFYsrKytLmzZuL/aYLh8NauX%2BILcmv/%2B1r//tfc57fwoXmflqa1L27NGyYVKNGyf7bx7vvbO634309%2By3x%2B%2B23I4BbtmxRs2bN9Nlnn6l27doJ//dL8rU2X2/7M87v%2B23p0pUaP16KRMycq2lpUq9e0tChR55rNVX3%2B/HsOz%2BPAHII%2BDgEAoFi/4eamZlZ7NeWKlXquP5iOZ7X73/t8uVSdrb02mvm8UDATOkyatThV/M43uxS8fedzf12vK9nv9nbbxkZGVb%2B/VTe75K9zzjbv7fN/fbrr23UvHmmNm8299u1kx5/XDrjjKN7fSrvd%2Bn49p0fUQBTUN%2B%2Bfa28Pi9PuuiiP%2Bmiiwomck5Lk268UXrwQSkUSty/XRJs7beSeD37zc6/fbxsZrf9elv/tu3f28Z%2B%2B/FHczHHN99MkSTVry9NmiRde%2B2x/ZxU3u84dhwCTrL95w2m0nkHO3eaefsmTpS%2B/NI8VqaMOdQ7dGjy1u9NxX3nBuy34vnmm2/yDyvVqVPHdpyUwfuteIq73954Q%2BrZU8rJMX%2BQDxlijsRUqJC4rG7De654GAFMsvT0dI0cOVLp6em2oxzR%2BvVm6pZnn5V%2B%2BcU8Fgyaq8cGDpRq1UpunlTad27Cfiue/fuL/XZseL8Vz7Hutz17pD/8QXrsMXP/zDOlWbOkcDiBIV2K91zxMAKIQvbtkxYtkqZOlRYvNvNHSdJpp5lDDD17mmXcAK9jVAFutWWL9Pvfm2m3JDOty/jxZrJ94GgxAghJZsLmZ581t2%2B%2BKXj8yivNh0u7dubwAgDAno8%2Bktq3l7791hyRmTnTzLMKHCsKoI/t3i29/LIpfUuWFIz2ValiRvp69zYjfwAA%2BxYvlq6/3pyXfeaZ5vM7Wedgw3sogD7jONL775uLOp5/vuDcPkn63e%2Bk22%2BXOnWSOJUCANxj/nypSxdp717pssuk//s/MwIIFBcF0CfWr5fmzZOee05at67g8awsqUcP6dZbWacXANzo5ZfNdFv79pmvs2dLZcvaToVUx1ldCTJ//ny1bdtWJ510kgKBgFavXn3E18ycOVOBQOCg2%2B7du4uVISdHeuopqUULcyj3oYdM%2BatQQbr5ZnPY96uvpEcecX/5K87%2B9BPHcTRq1CjVqlVL5cuX1yWXXKI1a9Yc9jWjRo066L1Wo6jlW4DfmDJlik4%2B%2BWSVK1dOTZo00bvvvnvI7y3pzzWv%2Bec//6lrr71WtWrVUiAQ0IIFC37zvNS5syl/t9wizZ3rr/J3pP3zW%2B%2B8806R77fPP/88SYlTBwUwQXbu3KmWLVtq7Nixx/S6zMxMbdmypdCtXLlyR/36H3%2BUnnnGHCKoXVsaMEB67z1zAcfll5tpAnJypDlzzPeUKnWsv5kdxd2ffjF%2B/Hg9/vjjmjx5slauXKkaNWro8ssvP%2BJShY0aNSr0Xvvkk0%2BSlBip6q9//asGDRqk4cOHa9WqVbrooovUrl07bdq06ZCvOd7PNS/buXOnzjnnHE2ePPmg59avNxd47Nljvs6YkTqf2SXlcPvncL744otC77cGnCx5EA4BJ0i3bt0kSRs3bjym1xVnFOaHH8whghdflN56y/yluF%2BzZlLXruYvyJo1j%2BnHukpx96cfOI6jiRMnavjw4erUqZMkadasWapevbrmzZun3r17H/K1pUuXZtQPx%2BTxxx9Xr169dPvtt0uSJk6cqMWLF2vq1KnKzs4u8jWMLh9au3bt1K5du4Me37XLnI/988/mc3zePKm0D/8f%2B1D750iqVaumSpUqJSCRdzAC6DI7duxQvXr1VKdOHV1zzTVatWpVkd%2BXkyM9/bQZ1atRw1y8sXixKX/nniuNGWP%2Benz/fTNpcyqXPxzeV199pZycHF1xxRX5j6Wnp6t169Zavn%2BisENYt26datWqpZNPPlldunTRhg0bEh3X9SKRiEKhkMJ%2BnFH3CPbs2aMPP/yw0HtNkq644orDvteO9nMNBYYNkz7%2BWKpa1VwAwhx/x%2Ba8885TzZo11aZNGy1dutR2HFfy4d8T7nXGGWdo5syZaty4sWKxmJ588km1bNlS//3vf9WgQQOtXy8tWCD9/e9mAtADp/A%2B5xzphhvM7fTT7f0OSL6cnBxJUvXq1Qs9Xr16dX399deHfN0FF1yg2bNn6/TTT9fWrVv16KOP6sILL9SaNWtUpUqVhGZ2s759%2B6pv3775E0GjwA8//KDc3Nwi32v734e/daTPNRzsP/8xa/lK5rSd2rXt5kklNWvW1LRp09SkSRPF43E999xzatOmjd555x1dfPHFtuO5CgWwBMydO7fQYbbXX39dF1100TH/nObNm6t58%2Bb591u0aKlQ6BbdfPN67drVQJ9%2BWvj7mzUzhwiuv95b8/WV1P70qt/un4ULF0oyh9kO5DjOQY8d6MDDKo0bN1aLFi106qmnatasWRo8eHAJp4aXHMt77befay1bttT555%2Bvp556SpP2txzky8szqy45jpmdoRhHP32tYcOGatiwYf79Fi1aaPPmzZowYQIF8DcogCWgffv2uuCCC/Lv1z6OP9d27ZLeflt69VXp1VfT9N138/KfK1VKat1a6thR6tDBTOHiRSW5P73ot/snHo9LMiOBNQ841r9t27aDRmoOp2LFimrcuLHWHThPEHCAk046SaVKlTpotO9Y3mtpaWkKh8O8zw7hvfdq6cMPzZKb48bZTuMNzZs315w5c2zHcB0KYAnIyMhQxnEskPvtt9LChdJrr0n/%2BIcpgfulpe1UVtZaPfJIU119tVS5cgkEdrnj3Z9e99v94ziOatSooSVLlui8886TZM7VWrZsmcYdw/%2BDxONxrV27ltFWHFLZsmXVpEkTLVmyRB07dsx/fMmSJerQocNR/QzHcbR69Wo1btw4UTFT2vz55rD4oEFStWqWw3jEqlWrCv1xDIMCmCA//fSTNm3apO%2B%2B%2B06SuSRdkmrUqKGTTqqh99%2BX%2BvR5Rdu2NdW2bbUKvbZGjX266KJf9Msvz%2Bntt0fob397W82aJf1XcJWqTLEVAAAUlklEQVTD7U%2B/X10YCAQ0aNAgjRkzRg0aNFCDBg00ZswYVahQQV27ds3/vjZt2qhjx47q16%2BfJOnee%2B/Vtddeq7p162rbtm169NFHFYvF1KNHD1u/ClLA4MGD1a1bNzVt2lQtWrTQtGnTtGnTJvXp00eS1L17d9WuXTv/iuDRo0erefPmatCggWKxmCZNmqTVq1crEonY/DVcY8eOHfrf//73/%2B811fr1J6ps2Tx16vSdpDo2o7lC4f1jLnpbvXq1KleurLp162rYsGH69ttvNXv2bEnmqvT69eurUaNG2rNnj%2BbMmaOXXnpJL730kq1fwb0cJMSMGTMcSQfcqjtSd6dRo0%2BcE090HHOGh7kFAo7TvLnjXHjha06NGlc6ZcqUdapWrepcccUVzvLly23/Kq5w8P40t5EjR9qO5gp5eXnOyJEjnRo1ajjp6enOxRdf7HzyySeFvqdevXqF9teNN97o1KxZ0ylTpoxTq1Ytp1OnTs6aNWuSnNy9otGoI8mJRqO2o7hOJBJx6tWr55QtW9Y5//zznWXLluU/17p1a6dHjx759wcNGuTUrVvXKVuWz7WiLF269IDPtCf%2B//8vzC20D/2s8P4puO3fPz169HBat26d//3jxo1zTj31VKdcuXLOiSee6LRq1cpZuHChnfAuF3CcA68lRSIMGSI9/njhx048UWrbVrrqKunKK82l/gDcY/9VwNFoVJmZmbbjwAdOOcWszrRggTnPG0gkDgEnwf4Lks4/31zR1a6ddMEF/pzUEwBwsE2bTPkrXVpq08Z2GvgBFSQJunQxf80dwwWZAAA/2LtXmjdP5SbM0sf6XjknnKkTVt4lXXqp7WTwOA4BA0AROASMhIvHpWuuMdM//NaoUdLIkUmPBP9gKTgAAGx4/PGiy59kCuCKFUmNA3%2BhAAIAYMO0aYd/fvr05OSAL1EAAQBItrw8aePGw3/P%2BvVJiQJ/ogACwAEikYhCoZDC4bDtKPCytDTpSKtT1GEiaCQOF4EAQBG4CAQJ9%2BCD0h//eOjnly6VLrkkaXHgL4wAAgBgw9ChZoLYotx1F%2BUPCUUBBADAhowMadkyaexY/VLrTP2gKvok2EqaN0%2BaMsV2Ongch4ABoAgcAkYyrVwpNWtmlgXdulUKBGwngtcxAggAgGWNG5tl4L7/Xvr6a9tp4AcUQAAALCtXTmrSxGwvW2Y3C/yBAggAgAu0aWO%2BLl5sNwf8gQIIAIALtGtnvr7%2BurR3r90s8D4KIAAALtCihVS9uvTLL4deIhgoKRRAAABcoFQp6fe/N9tz5tjNAu%2BjAAIA4BLdu5uv8%2BdLP/9sNwu8jQIIAIBLhMNmSpjdu6XZs22ngZdRAAHgAJFIRKFQSOFw2HYU%2BFAgYFaBk6TJk6W8PLt54F2sBAIARWAlENiyY4eUlWUuBvn736XrrrOdCF7ECCAAAC5ywgkFo4DZ2RLDNEgECiAAAC4zcKBZHWTFCmnJEttp4EUUQAAAXKZ6dalPH7M9ciSjgCh5FEAAAFxo6FCpfHnpvfek116znQZeQwEEAMCFatSQBgww28OGSbm5dvPAWyiAAAC41AMPSCeeKK1ZIz37rO008BIKIAAALlWpkvTQQ2Z7xAgpFrObB95BAQTgKXv37tXQoUPVuHFjVaxYUbVq1VL37t313Xff2Y4GFMvdd0sNGkhbt0qPPmo7DbyCAgjAU3799Vd99NFHGjFihD766CPNnz9fX375pdq3b287GlAsZctKTzxhtidOlD7/3G4eeAMrgQDwvJUrV6pZs2b6%2BuuvVbdu3aN6DSuBwG2uuUZauFBq08bMDRgI2E6EVMYIIADPi0ajCgQCqlSpku0oQLFNmiSlp0tvvSW98ILtNEh1FEAAnrZ792498MAD6tq162FH8uLxuGKxWKEb4CannCINH26277lH%2Bvlnu3mQ2iiAAFLa3LlzdcIJJ%2BTf3n333fzn9u7dqy5duigvL09Tpkw57M/Jzs5WMBjMv2VlZSU6OnDM7r9fOuMMc0HI/ffbToNUxjmAAFLa9u3btXXr1vz7tWvXVvny5bV371517txZGzZs0Ntvv60qVaoc9ufE43HF4/H8%2B7FYTFlZWZwDCNd5913p4ovN9ttvS5deajcPUhMFEIDn7C9/69at09KlS1W1atVj/hlcBAI3u%2Bsu6emnpVNPlT7%2BWKpQwXYipBoOAQPwlH379un3v/%2B9PvjgA82dO1e5ubnKyclRTk6O9uzZYzseUCLGjZPq1JHWr5cefNB2GqQiRgABeMrGjRt18sknF/nc0qVLdckllxzVz2EEEG63aJF09dVmOph335VatrSdCKmEAggARaAAIhX07CnNnGlWClm9mkPBOHocAgYAIEU98YRUu7a0bp00bJjtNEglFEAAAFJUpUrSM8%2BY7UmTzFXBwNGgAAIAkMKuvFLq3dts9%2BwpRaN28yA1UAABAEhxEyaYlUI2bZIGDLCdBqmAAggAQIo74QRp9mwpLc18fekl24ngdhRAAAA8oGVL6YEHzPadd0rffWc3D9yNAggAgEeMHCmdf77000/SrbdKeXm2E8GtKIAAcIBIJKJQKKRwOGw7CnDMypaV5s6VypeXliwxVwYDRWEiaAAoAhNBI5VNnSrdfbcphCtXSmefbTsR3IYRQAAAPKZPH%2Bmaa6Q9e6SuXaVdu2wngttQAAEA8JhAQPrLX6Tq1aU1a6T77rOdCG5DAQQAwIOqVZNmzTLbkYj06qt288BdKIAAAHhU27bSPfeY7dtuY2oYFKAAAgDgYdnZ0rnnSj/8IHXvztQwMCiAAAB4WHq69PzzUoUK0ltvmWXjAAogAAAed8YZ0pNPmu3hw6UVK%2BzmgX0UQAAAfKBXL%2BmGG6R9%2B6SbbpJiMduJYBMFEAAAHwgEpGnTpLp1pQ0bzETR8C8KIAAAPlGpkjRvnlSqlFkybvZs24lgCwUQAAAfadlSGjXKbN99t7RundU4sIQCCACAzwwbJrVuLe3cKXXpIsXjthMh2SiAAHCASCSiUCikcDhsOwqQMKVKSXPmSJUrSx99JP3hD7YTIdkCjuM4tkMAgNvEYjEFg0FFo1FlZmbajgMkxCuvSB06mO1Fi6R27ezmQfIwAggAgE%2B1by/172%2B2e/SQtmyxmwfJQwEEAMDHxo%2BXzj5b%2Bv57lorzEwogAAA%2BVq6c9MILZqm4f/xD%2BtOfbCdCMlAAAQDwuTPPlCZNMtsPPii9/77dPEg8CiAAANBtt0mdO5ul4rp2laJR24mQSBRAAACQv1Rc/foFS8UxT4h3UQABAIAkKRgsWCpu3jyWivMyCiAAAMjXooU0erTZ7tuXpeK8igIIAAAKeeAB6ZJLCpaK27PHdiKUNAogAAAo5LdLxQ0fbjsRShoFEAAAHKR2benZZ832hAnSm2/azYOSRQEEgANEIhGFQiGFw2HbUQDrOnSQ7rrLbHfvLm3bZjcPSk7AcbjIGwB%2BKxaLKRgMKhqNKjMz03YcwJpdu6RwWFqzRrr6aunVV82UMUhtjAACAIBDKl9eev55KT1dWrhQmjzZdiKUBAogAAA4rMaNC9YIvu8%2B6ZNP7ObB8aMAAgCAI%2BrXzxwCjselm24yh4aRuiiAAADgiAIBc1Vw9ermfMD777edCMeDAggAAI5KtWrSzJlme/JkadEiq3FwHCiAAADgqF15pTRwoNnu2VPautVuHhQPBRAAAByTsWPNhSHbtkm9eklMKJd6KIAAPK13794KBAKaOHGi7SiAZ5QrJ82dWzA1zNSpthPhWFEAAXjWggUL9P7776tWrVq2owCe07ixNG6c2R4yRFq71m4eHBsKIABP%2Bvbbb9WvXz/NnTtXZcqUsR0H8KT%2B/aUrrpB275Zuvlnas8d2IhwtCiAAz8nLy1O3bt103333qVGjRrbjAJ6VlibNmCFVqSKtWiU99JDtRDhaFEAAnjNu3DiVLl1aAwYMOOrXxONxxWKxQjcAR1arljR9utkeP1765z/t5sHRoQACSGlz587VCSeckH9btmyZnnzySc2cOVOBY1ixPjs7W8FgMP%2BWlZWVwNSAt3TsaKaEcRype3cpGrWdCEcScBwu3gaQurZv366tB0xE9uKLL2r48OFKSyv4%2BzY3N1dpaWnKysrSxo0bi/w58Xhc8Xg8/34sFlNWVpai0agyMzMTlh/wiu3bpXPOkb76ypTAWbNsJ8LhUAABeMqPP/6oLVu2FHqsbdu26tatm3r27KmGDRse1c%2BJxWIKBoMUQOAY/Pvf0sUXS3l50v/9n3T99bYT4VBK2w4AACWpSpUqqlKlSqHHypQpoxo1ahx1%2BQNQPC1bSkOHStnZUu/e0oUXSjVr2k6FonAOIAAAKDGjRknnnSf9%2BKN0%2B%2B2sEuJWHAIGgCJwCBgovjVrpCZNpHhcevppMxoId2EEEAAAlKhGjaQxY8z2kCHS%2BvV28%2BBgFEAAAFDiBg2SWreWdu6UevSQcnNtJ8KBKIAAAKDEpaVJM2dKGRnm6uDHHrOdCAeiAAIAgISoX1%2BaONFsjxghffqp1Tg4AAUQAAAkTM%2Be0jXXSHv2mAmi9%2B61nQgSBRAAACRQICBNmyZVriytWiU9%2BqjtRJAogAAAIMFq1pSmTDHbf/yj9OGHdvOAAggAAJKgc2fphhvM1cA9epg5AmEPBRAADhCJRBQKhRQOh21HATwlEDCjgNWqmYmiR42yncjfWAkEAIrASiBAYixYIHXsaKaJ%2Bc9/pGbNbCfyJ0YAAQBA0lx3ndS1q5SXJ916q7R7t%2B1E/kQBBAAASfXUU1KNGtLatdLIkbbT%2BBMFEAAAJFXlytLTT5vtCROkFSvs5vEjCiAAAEi6Dh2km282h4J79uSq4GSjAAIAACuefFKqXl367DNp9GjbafyFAggAAKyoUqVggujx45kgOpkogAAAwJpOncwk0bm50m23mTWDkXgUQAAAYNXkyWY08OOPpbFjbafxBwogAACwqmpVMzWMJD36qPTpp3bz%2BAEFEAAAWNeli3TttdLevVKvXuaQMBKHAggAAKwLBKSpU6XMTDMv4KRJthN5GwUQAA4QiUQUCoUUDodtRwF8p3ZtMzG0JA0fLm3YYDePlwUcx3FshwAAt4nFYgoGg4pGo8rMzLQdB/ANx5F%2B9zvpnXekyy6T3nzTjA6iZDECCAAAXCMQkKZPl8qVk/7xD2nWLNuJvIkCCAAAXOW00wpWBhk8WNq61W4eL6IAAgAA1xk8WDrvPOnnn6WBA22n8R4KIAAAcJ3SpaVnnpHS0qS//lVauNB2Im%2BhAAIAAFc6/3zpnnvM9t13Szt22M3jJRRAAADgWqNHS/XrS5s2SSNG2E7jHRRAAADgWhUrSk8/bbYnTZI%2B%2BMBuHq%2BgAAIAAFdr21a66SYpL0%2B6805p3z7biVIfBRAAALjeE09IlSpJq1ZJTz1lO03qowACAADXq15dGj/ebI8YYc4JRPFRAAEAQEro1Utq1UrauVPq3992mtRGAQQAACkhLc1cEFK6tPTKK9LLL9tOlLoogABwgEgkolAopHA4bDsKgCI0aiTdd5/Z7t%2BfuQGLK%2BA4jmM7BAC4TSwWUzAYVDQaVWZmpu04AA7w66/SWWdJX30lDRkiTZhgO1HqYQQQAACklAoVpMmTzfbEidLHH9vNk4oogAAAIOVcdZXUqZOUmyvddZeZIxBHjwIIAABS0pNPmpVCli%2BXZs60nSa1UAABAEBKqlNHGjXKbN9/v/Tjj1bjpBQKIAAASFkDB5oLQn78UfrDH2ynSR0UQAAAkLLKlJGmTDHb06dLK1bYzZMqKIAAACClXXSR1L275DjS3XebC0NweBRAAJ60du1atW/fXsFgUBkZGWrevLk2sXgo4Fnjx0vBoLR1q/T117bTuF9p2wEAoKStX79erVq1Uq9evTR69GgFg0GtXbtW5cqVsx0NQIJUry4tWiSdc465MhiHx0ogADynS5cuKlOmjJ577rli/wxWAgHgZRwCBuApeXl5WrhwoU4//XS1bdtW1apV0wUXXKAFCxYc9nXxeFyxWKzQDQC8igIIwFO2bdumHTt2aOzYsbryyiv15ptvqmPHjurUqZOWLVt2yNdlZ2crGAzm37KyspKYGgCSi0PAAFLa3Llz1bt37/z7Cxcu1CWXXKKbbrpJ8%2BbNy3%2B8ffv2qlixop5//vkif048Hlc8Hs%2B/H4vFlJWVxSFgAJ7ERSAAUlr79u11wQUX5N%2BvWrWqSpcurVAoVOj7zjzzTP3rX/865M9JT09Xenp6wnICgJtQAAGktIyMDGVkZBR6LBwO64svvij02Jdffql69eolMxoAuBYFEIDn3Hfffbrxxht18cUX69JLL9Ubb7yhV199Ve%2B8847taADgCpwDCMCTnn32WWVnZ%2Bubb75Rw4YNNXr0aHXo0OGoX880MAC8jAIIAEWgAALwMqaBAQAA8BkKIAAAgM9QAAEAAHyGAggAAOAzFEAAAACfoQACAAD4DAUQAADAZyiAAHCASCSiUCikcDhsOwoAJAwTQQNAEZgIGoCXMQIIAADgMxRAAAAAn6EAAgAA%2BAwFEAAAwGcogAAAAD5DAQQAAPAZCiAAAIDPMA8gABTBcRxt375dGRkZCgQCtuMAQImiAAIAAPgMh4ABAAB8hgIIAADgMxRAAAAAn6EAAgAA%2BAwFEAAAwGcogAAAAD5DAQQAAPAZCiAAAIDPUAABAAB8hgIIAADgMxRAAAAAn6EAAgAA%2BAwFEAAAwGcogAAAAD5DAQQAAPAZCiAAAIDPUAABAAB8hgIIAADgMxRAAAAAn6EAAgAA%2BAwFEAAAwGcogAAAAD5DAQQAAPAZCiAAAIDPUAABAAB8hgIIAADgMxRAAAAAn6EAAgAA%2BAwFEAAAwGcogAAAAD5DAQQAAPAZCiAAAIDPUAABAAB8hgIIAADgMxRAAAAAn6EAAgAA%2BAwFEAAAwGcogAAAAD5DAQQAAPAZCiAAAIDPUAABAAB8hgIIAADgMxRAAAAAn6EAAgAA%2BAwFEAAAwGcogAAAAD5DAQQAAPAZCiAAAIDPUAABAAB8hgIIAADgM/8PBoH5MW1rY%2BsAAAAASUVORK5CYII%3D'}
Genus 2 curve data - 600.b.30000.1