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g2c_curves • Show schema
{'Lhash': '639284731750073843', 'abs_disc': 448, '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]],[7,[1,-1,7,-7]]]', 'bad_primes': [2, 7], 'class': '448.a', 'cond': 448, 'disc_sign': 1, 'end_alg': 'Q x Q', 'eqn': '[[-7,0,0,0,1],[0,1,0,1]]', 'g2_inv': "['6080953884912/7','155007628668/7','-1306723104']", 'geom_aut_grp_id': '[4,2]', 'geom_aut_grp_label': '4.2', 'geom_aut_grp_tex': 'C_2^2', 'geom_end_alg': 'CM x Q', 'globally_solvable': 1, 'has_square_sha': True, 'hasse_weil_proved': True, 'igusa_clebsch_inv': "['828','16635','5308452','56']", 'igusa_inv': "['828','17476','-853888','-253107460','448']", 'is_gl2_type': True, 'is_simple_base': False, 'is_simple_geom': False, 'label': '448.a.448.1', 'leading_coeff': {'__RealLiteral__': 0, 'data': '0.2164663601475456895859403663284466809402159513646999589', 'prec': 190}, 'locally_solvable': True, 'modell_images': ['2.45.1', '3.2160.5'], 'mw_rank': 0, 'mw_rank_proved': True, 'non_solvable_places': [], 'num_rat_pts': 2, 'num_rat_wpts': 0, 'real_geom_end_alg': 'C x R', 'real_period': {'__RealLiteral__': 0, 'data': '7.7927889653116448250938531878', 'prec': 100}, 'regulator': {'__RealLiteral__': 0, 'data': '1.0', 'prec': 10}, 'root_number': 1, 'st_group': 'N(U(1)xSU(2))', 'st_label': '1.4.C.2.1a', 'st_label_components': [1, 4, 2, 2, 1, 0], 'tamagawa_product': 1, 'torsion_order': 6, 'torsion_subgroup': '[6]', 'two_selmer_rank': 1, 'two_torsion_field': ['8.0.3211264.1', [1, -4, 8, -8, 7, -8, 8, -4, 1], [8, 9], False]} -
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], ['2.0.4.1', [1, 0, 1], -1]], 'factorsRR_base': ['RR', 'RR'], 'factorsRR_geom': ['RR', 'CC'], 'fod_coeffs': [1, 0, 1], 'fod_label': '2.0.4.1', 'is_simple_base': False, 'is_simple_geom': False, 'label': '448.a.448.1', 'lattice': [[['1.1.1.1', [0, 1], [0, 0]], [['1.1.1.1', [0, 1], -1], ['1.1.1.1', [0, 1], -1]], ['RR', 'RR'], [2, -1], 'N(G_{1,3})'], [['2.0.4.1', [1, 0, 1], [0, 1]], [['1.1.1.1', [0, 1], -1], ['2.0.4.1', [1, 0, 1], -1]], ['RR', 'CC'], [8, -1], 'G_{1,3}']], 'ring_base': [2, -1], 'ring_geom': [8, -1], 'spl_facs_coeffs': [[[33], [189]], [[505], [-11341]]], 'spl_facs_condnorms': [32, 14], 'spl_facs_labels': ['32.a1', '14.a4'], 'spl_fod_coeffs': [0, 1], 'spl_fod_gen': [0, 0], 'spl_fod_label': '1.1.1.1', 'st_group_base': 'N(G_{1,3})', 'st_group_geom': 'G_{1,3}'} -
g2c_ratpts • Show schema
{'label': '448.a.448.1', 'mw_gens': [[[[1, 1], [0, 1], [0, 1]], [[0, 1], [0, 1], [0, 1], [-1, 1]]]], 'mw_gens_v': True, 'mw_heights': [], 'mw_invs': [6], 'num_rat_pts': 2, 'rat_pts': [[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': '448.a.448.1', 'plot': 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4AoVjffbLa8POmmm8wpYcC28uXLq0GDBlq7du1RH5Oenq5gMFhgA4BURQFEsYtGpVNPlb7%2B2qwbzDFm2Jabm6vVq1erWrVqtqMAgCtQAFHsgkHzecCSJaXXX5emTLGdCH7Tv39/zZ8/X%2BvXr9fixYt1zTXXKB6Pq2vXrrajAYArUACREE2bSsOHm3Hv3tK6dXbzwF%2B%2B/fZb3XDDDTrjjDPUsWNHpaWl6aOPPlLt2rVtRwMAV%2BAiECTMvn3SJZeYi0GaNJHef99cLQx4QTweVygU4iIQACmJI4BImJIlzSohFStKH39s5goEAAD2UQCRULVqSU8/bcYjRkgffGA3DwAAoAAiCa6/3swNmJdnbllgAQAAuyiASIrx46VTTpHWr5fuust2GgAA/I0CiKQIBs10MIGANHmyNGOG7UQAAPgXBRBJ06KFNGCAGd92m/TDD3bzAADgVxRAJNXw4dI550hbtkg9e7JKCAAANlAAkVTp6WZqmNKlpTffNGPATaLRqMLhsCKRiO0oAJAwTAQNK0aMkIYMMXMErlghVa9uOxFQEBNBA0hlHAGEFQMGSJGI9MsvnAoGACDZKICwolQpczVwWpo0a5Y0dartRAAA%2BAcFENaEw9IDD5hx377S5s128wAA4BcUQFg1YIDUsKG0davUr5/tNAAA%2BAMFEFaVLi09%2B6xUooQ5DTxnju1EAACkPgogrItEpN69zfjPf5Z27bKbBwCAVEcBhCv89a9StWrSunXSY4/ZTgMAQGqjAMIVgkHp8cfNeMQIaeNGu3kAAEhlFEC4RqdOZr3gnTulQYNspwEAIHVRAOEagYD05JPm9tVXpY8/tp0IAIDURAGEqzRqJHXpYsYDB7JCCAAAiUABhOs8%2BKBZIWTePOndd22nAQAg9VAA4Tq1akl33GHGw4ZxFBDJFY1GFQ6HFYlEbEcBgIQJOA5/vcJ9Nm2S6tSRcnOluXOlVq1sJ4LfxONxhUIhxWIxBYNB23EAoFhxBBCuVK2a1L27GT/6qN0sAACkGgogXKtfP3NF8NtvS198YTsNAACpgwII1zr9dOnyy8140iS7WQAASCUUQLjabbeZ25dekvbutZsFAIBUQQGEq112mVSlirR5s7kYBAAAnDgKIFytdGmpY0cznjHDbhYAAFIFBRCud%2BWV5nb2bLs5AABIFRRAuF6rVlLJktJXX0nffWc7DQAA3kcBhOtlZEj165vxf/9rNwsAAKmAAghPaNDA3K5ebTcHAACpgAIIT6hTx9xu3Gg3BwAAqYACCE%2BoXNnc/vyz3RxIfdFoVOFwWJFIxHYUAEgYCiA8oXRpc7tnj90cSH29evXSqlWrtGTJEttRACBhKIDwhJ07zW25cnZzAACQCiiA8IT9079kZtrNAQBAKqAAwhOWLze3Z5xhNwcAAKmAAgjXy82VPvzQjJs2tZsFAIBUQAGE673zjvTrr1L16tLZZ9tOAwCA91EA4XoTJ5rbTp2kQMBuFgAAUgEFEK720UfS7NlSiRLSHXfYTgMAQGqgAMK19u6Vevc2465dpdNOs5sHAIBUQQGEaz30kPTJJ1LFitKIEbbTAACQOiiAcKWZM6UHHzTj8eOlrCy7eQAASCUUQLjOggXmgg/HMZ/7u%2Bkm24kAAEgtFEC4yrvvSpdfbpZ%2Bu/xy6cknbScCAHjB5s3SrFnS%2BvW2k3gDBRCuMXmyKX07dkht2khvvCGVLm07FfwmGo0qHA4rEonYjgLgKLZvl%2BbPl0aPlq69Vqpd2ywVeuWV0owZttN5Q8BxHMd2CPjbrl3S3XdLEyaYr6%2B7TpoyRUpPt5sL/haPxxUKhRSLxRQMBm3HAXwrL09avdpMC/bRR9LixdLKleb%2BgwUCZrnQO%2B9k2rDCKGU7APzts8%2Bkzp3NrSQNHSo98ICZ9w8A4D%2B//GKK3ocfmm3xYikeP/xxNWpITZoc2Bo3lvi3WuFRAGHFrl3SyJFm27NHqlpVevFF6bLLbCcDACSL40gbNkjvvy998IHZVq409x%2BsXDkpEpEuuMCsCd%2B0qZSdbSVyyqAAIqkcR3rrLalfP%2BnLL819f/yj9Mwz5vMbAIDUlZcnrVplPr%2B3cKEpft99d/jjTjtNuvBCqVkzc3v22VIpGkux4n8nkmbxYmnQIGnePPN1dra5yvfqq1njFwBSUV6etHy5%2Bb0/b56Z5uunnwo%2BplQpc/r2oouk5s1N6eOAQOJRAJFw//2vmdT5rbfM1%2Bnp0l/%2BIg0eLGVk2M0GACg%2BjiOtWSO99570n/%2BY0ndo4StXzpS8Fi3M1rSpuQ/JRQFEQjiONHeuuUR/9mxzX4kSUpcu0vDhUq1advMBAIrH5s1mDtd//9vcHnpKt3x5U/RatZJatjRH%2B5jiyz4KIIrVrl3Sa6%2BZU7vLlpn7SpaUbrhBuu8%2Bc4k%2BAMC79u41V%2Bf%2B61/SO%2B9IS5cW/H56ujnC17q1dMkl0vnnU/jciAKIYrFunTRpkvS3v0lbt5r7ypaVunc3c/zVqWM3HwDg%2BG3ZIr39tllpY/ZsKRYr%2BP1zz5UuvdRsF11kfv/D3SiAOG6//ipNny49//yBCzskqWZN6c9/lm67TapUyVo8AMAJWLtW%2Bsc/pJkzpUWLCk68XLmy1Lat9Ic/mJWbuGjDeyiAKJJ9%2B0zZe/lls1Tb9u3m/kDA/CLo2VO64gou1wcAr3EcMwffG29I06ZJK1YU/H7DhtJVV5nf8ZGI%2BXgPvIu/pk%2BA4zjatm2b7RgJl5cnLVlifiHMmGE%2B8LvfKaeYz/fddJM58ieZI4OA1%2BTm5io3Nzf/6/3v7fiRliAAUsjatab0TZ8uffHFgftLljQXb1x%2Budn2/46XzJrtqSAjI0MBn85DxlrAJ2D/WqEAAMB7/LzWNwXwBBztCGAkEtGSJUsK9RrxeFw1a9bUN998U6g/hEV57aI%2BvnHjizV8%2BALNmmWu7Dp47qYKFcy/AK%2B%2B2lzVlZbm3f1M1GsXdR%2BLmiWR/0%2BK8ngv7%2BexHnvoEcBNmzapSZMmWrVqlapXr57ULMl8bTe9N4v6eK/up6335t69ZqqWKVPMhRz7P9NXooT5vX7NNeb3/LGOa3hhP4vy2n4%2BAsgp4BMQCASO%2BIevZMmSRf4XRTAYLNRzivrav/X4r746cGXXl18u1k03ped/r1Il83mPq682V3aVKXNiWSR7%2B5ms15YKv49Ffe1E5/bDfh7Pn9mMjAxf7Kcb3ptFfbxX9zPZ781vvzWzNDz3nLRp04HHRSLSxo0Pafny%2B1S1avFn8ervIL%2BgACZAr169XPPahz5%2Bxw6zFM/s2WYOp4M/7yGlq04dqV07sz5vixbHvpjDzftp67WLyk25/bCfidzHor6%2BV/fTTX8OvbqfyXhvOo65cnfsWPPZ7X37zP1Vq5oJ%2Bbt3l8JhKRo9qdDlr6hZvPo7yC84BWzZ/s8RJupzCPv2mUk6331XmjPHLLy9e/eB75csadZevOIKs4XDiVmXN9H76QZ%2B2EfJP/v57bff5p9mqlGjhu04CeOXn6cf9tPsY0W9/PJ2jRtXTosXH/hey5bSHXdIHTqYj/B4mR9%2BlsnAEUDL0tPTNXToUKWnp//2gwvBcaRVq8w6jHPnmilbfv654GNq1Towf1Pr1sf%2BvEdxKe79dCM/7KPkr/08%2BDZV%2Bennmcr7mZcnvfVWWVWtmqObbzYL66anSzffLN11l9SggeWAxSjVf5bJwhFAj8vLM/M2LVggzZ9vCt%2BPPxZ8TDBo1mDcP0t7vXqJOcoHpBKOMsALHMdctDdokPTZZ%2Ba%2BYFDq3Vu6804maMbRcQTQY/bskT79VFq40Gzvv1/wal3JLMHTvLn0u9%2BZI3yNGzMxMwCkmlWrpL59zcd7JFP8%2BvUzR/wqVrSbDe5HLXC5n382i24vWiR98IG0eLG0c2fBx5QrZxbebtnSHOlr0sT7n/EAABzZzp3S8OHS44%2BbqV3S0qQ%2BfaTBg1l%2BE4VHAXSRvDxp9WpT%2BPZvq1cf/rhKlcxi2y1amO2886TSpZOfFwCQXB99ZK7iXbvWfN2unfTEE9Kpp9rNBe%2BhAFr0ww/Sxx%2Bbo3qLF5vxkVadqlvXHOFr3twUvzPOMBN3AgD8IS9PeuQR6YEHzOwO2dnSxImmAALHgxqRJNu2mYs0HntMuu46s4ZuVpZ58z78sJmmJR6XSpbM1YUX5mrQIOnNN826u198IU2eLN16q3TWWe4tf9OnT1fbtm1VpUoVBQIBLVu27DefM3nyZAUCgcO2Xbt2JSFx8Tqe/Xcrx3E0bNgwZWdnq2zZsmrVqpVWrlx5zOcMGzbssJ9jVlZWkhLjWCZMmKA6deqoTJkyaty4sRYuXHjUx6bSe1KSFixYoKuuukrZ2dkKBAL6xz/%2BYTtSkW3bJrVvLw0ZYspfmTLT9f33FZWXd%2Bx9mTdv3hF/lp9//nmSkhevkSNHKhKJKCMjQyeffLLat2%2BvNWvW2I7lWS6tEqllyBAz1UqrVtI990h//7v09ddSIOCofPmv1arVeg0blqMXX/xMjRtfot27m2vkSFMOizJBp207duxQ8%2BbN9cgjjxTpecFgUJs2bSqwlTl02REPON79d6PRo0drzJgxGj9%2BvJYsWaKsrCxdeumlR1z68GD169cv8HNcvnx5khLjaF5//XX17dtXQ4YM0dKlS9WiRQtddtll2rhx41GfkyrvScm8Lxs2bKjx48fbjnJcNm0yH/V56y2pdOl9uuKK6Zo6VZJihX6NNWvWFPhZ1q1bN2F5E2n%2B/Pnq1auXPvroI82ZM0d79%2B5VmzZttGPHDtvRPIlTwElQo4a5VL9GDXOBRiRibs8/P6BgsPZBj8zSWWeNVZMmTbRx40bVqlXLWubj0blzZ0nShg0bivS8VDlSdLz77zaO42js2LEaMmSIOnbsKEl68cUXlZmZqVdeeUU9e/Y86nNLlSqVEj/LVDJmzBjdcsst6tGjhyRp7Nixmj17tiZOnKiRI0ce8Tmp8p6UpMsuu0yXXXaZ7RjH5bvvzIGDdevMdC4zZ5ZUkyYdi/w6J598siqmwGXB77zzToGvX3jhBZ188sn65JNPdPHFF1tK5V0cAUyCG26QcnKkb76Rpk0z8zVdcom5ZP9QsVhMgUAgJd6shbV9%2B3bVrl1bNWrU0JVXXqmlS5fajuRr69evV05Ojtq0aZN/X3p6ulq2bKlFixYd87lr165Vdna26tSpo06dOumrr75KdNxiF41GFQ6HFYlEbEc5Ybt379Ynn3xS4GcpSW3atDnmz5L3pH0//WTmbV23znxkaNEic%2BDgeDRq1EjVqlVT69atNXfu3GLNaVMsZo6CVuLS5%2BNCAUyCihULNxnnrl27NGjQIN14442%2BmXj2zDPP1OTJkzVz5ky9%2BuqrKlOmjJo3b661%2By9xQ9Ll5ORIkjIP%2BUObmZmZ/70jadq0qaZMmaLZs2fr2WefVU5Ojpo1a6atW7cmNG9x69Wrl1atWqUlS5bYjnLCtmzZon379hXpZ8l70r69e81nxVevNmeO5s07vqt8q1WrpkmTJmnatGmaPn26zjjjDLVu3VoLFiwo9szJ5jiO%2BvXrp4suukhnn3227TieRAFMoqlTp6pChQr528EfxN6zZ486deqkvLw8TZgwwWLKwjnWvhTFBRdcoJtvvlkNGzZUixYt9H//93%2BqV6%2Bexo0bV8yJi1dx7b8bHLove/bskWROAx7McZzD7jvYZZddpquvvloNGjTQ73//e82aNUuSOX0Mu4rys/TqezKVPPyw9J//SOXLS7NmSbVr//ZzjuSMM87QrbfeqvPOO08XXnihJkyYoCuuuEKPPfZY8Qa2oHfv3vrss8/06quv2o7iWXwGMInatWunpk2b5n9dvXp1Sab8XXfddVq/fr3ee%2B89Txz9O9q%2BnKgSJUooEom4/mhDovbfhkP3JTc3V5I5ElitWrX8%2Bzdv3nzYkaRjKV%2B%2BvBo0aOD6n2Uqq1KlikqWLHnY0b6i/Cy98p5MFStWSA89ZMaTJknnnFO8r3/BBRfo5ZdfLt4XTbI%2Bffpo5syZWrBggWrUqGE7jmdRAJMoIyNDGRkZBe7bX/7Wrl2ruXPnqnLlypbSFc2R9qU4OI6jZcuWqYHLVy5P1P7bcOi%2BOI6jrKwszZkzR40aNZJkPks2f/58jRo1qtCvm5ubq9WrV6tFixbFnhmFk5aWpsaNG2vOnDnq0KFD/v1z5szRH//4x0K9hlfek6ni7rvNKeD27aUbbyz%2B11%2B6dGmBf9h5ieM46tOnj2bMmKF58%2BapTp06tiN5GgXQor179%2Bqaa67Rp59%2Bqn8H%2BUJGAAAUMUlEQVT%2B85/at29f/r/UK1WqpDSPref2008/aePGjfr%2B%2B%2B8lKX9%2BpqysrPwrCrt06aLq1avnX304fPhwXXDBBapbt67i8bieeuopLVu2TNFo1M5OnIDC7L8XBAIB9e3bVyNGjFDdunVVt25djRgxQuXKldONB/2N1Lp1a3Xo0EG9e/eWJPXv319XXXWVatWqpc2bN%2Buhhx5SPB5X165dbe0KJPXr10%2BdO3fW%2BeefrwsvvFCTJk3Sxo0bdfvtt0tK7fekZC5oWbduXf7X69ev17Jly1SpUiXXzbTw8cfSv/9t1m5//PHDv/9b%2B3Lvvffqu%2B%2B%2B05QpUySZK75POeUU1a9fX7t379bLL7%2BsadOmadq0acnapWLVq1cvvfLKK3rzzTeVkZGR//dlKBRS2bJlLafzIAfWrF%2B/3pF0xG3u3Lm24xXZCy%2B8cMR9GTp0aP5jWrZs6XTt2jX/6759%2Bzq1atVy0tLSnKpVqzpt2rRxFi1alPzwxaAw%2B%2B8VeXl5ztChQ52srCwnPT3dufjii53ly5cXeEzt2rUL7Nv111/vVKtWzSldurSTnZ3tdOzY0Vm5cmWSkxefWCzmSHJisZjtKCcsGo06tWvXdtLS0pzzzjvPmT9/fv73Uvk96TiOM3fu3CO%2BLw/eZ7fo1s1xJMfp0uXI3/%2BtfenatavTsmXL/MePGjXKOe2005wyZco4J510knPRRRc5s2bNSvyOJMjR/r584YUXbEfzpIDjOE7CWyYAeEw8HlcoFFIsFvPE53LhbXv2SFWqmBWhFi40y34CicRVwAAAWLZkiSl/VaqYtd%2BBRKMAAgBg2X//a24vvNC9670jtfDHDAAAy7780tyGw3ZzwD8ogAAAWPbjj%2Ba2CFNtAieEAggAgGW7d5vb9HS7OeAfFEAAACzbX/x27bKbA/5BAQSAg0SjUYXDYUUiEdtR4CNVqpjbzZvt5oB/UAAB4CC9evXSqlWrtGTJEttR4COnnGJuD1roA0goCiAAAJbVr29u//c/uzngHxRAAAAsO/98c7tunfTDD3azwB8ogAAAWFapktSwoRm/%2B67dLPAHCiAAAC5w%2BeXm9s037eaAP1AAAQBwgY4dze0//ylt3243C1IfBRAAABdo3FiqW1fauVP6%2B99tp0GqowACAOACgYDUvbsZP/203SxIfRRAAABcont3KS1N%2Bvhj6aOPbKdBKqMAAgDgEiefLN10kxmPHm03C1IbBRAAABfp39/czpghrVhhNwtSFwUQAAAXCYelq6824%2BHD7WZB6qIAAsBBotGowuGwIpGI7SjwsaFDzUUhb7whffqp7TRIRQHHcRzbIQDAbeLxuEKhkGKxmILBoO048KGbb5amTpVat5bmzDGFECguHAEEAMCFHnrIXBH8n/9Is2bZToNUQwEEAMCFTjlF6tvXjPv1k3bvthoHKYYCCACASw0ZImVmSmvXSmPG2E6DVEIBBADApYLBA/MB/vWv0saNdvMgdVAAAQBwsc6dpRYtpF9/lfr0sZ0GqYICCACAiwUC0sSJUqlS0syZ0vTpthMhFVAAAQBwufr1pYEDzbh3b%2BmXX%2BzmgfdRAAEA8ID77pPq1ZM2bTqwXBxwvCiAAAB4QJky0nPPmVPCzz8v/fvfthPByyiAAAB4RIsW5hSwJPXoIcXjdvPAuyiAAAB4yMiR0qmnSt98YyaIBo4HBRAAAA8pX1564YUDp4JZJg7HgwIIAAeJRqMKh8OKRCK2owBHdfHFB5aJ69FD2rLFbh54T8BxHMd2CABwm3g8rlAopFgspmAwaDsOcJidO6XGjaXVq6VrrpH%2B7//MUUGgMDgCCACAB5UtK730kpkg%2Bo03zBgoLAogAAAe1bixNGyYGffpI23YYDMNvIQCCACAhw0cKDVrZqaE6dxZ2rfPdiJ4AQUQAAAPK1VKevllKSNDev996ZFHbCeCF1AAAQDwuDp1pPHjzXjoUOnjj%2B3mgftRAAEASAGdO0vXX29OAd94o7Rtm%2B1EcDMKIAAAKSAQkJ5%2BWqpZU/ryS%2BnOO20ngptRAAGknG7duikQCBTYLrjgAtuxgISrWNF8HrBECWnyZOn1120ngltRAAGkpD/84Q/atGlT/vb222/bjgQkxcUXS4MHm3HPntLXX9vNA3eiAAJISenp6crKysrfKlWqZDsSkDQPPCBdcIEUi5nPA%2B7dazsR3IYCCCAlzZs3TyeffLLq1aunW2%2B9VZs3b7YdCUia0qWlV16RgkFp0SLpr3%2B1nQhuw1rAAFLO66%2B/rgoVKqh27dpav3697r//fu3du1effPKJ0tPTj/ic3Nxc5ebm5n8dj8dVs2ZN1gKGp736qjkCWKKENG%2Be1KKF7URwCwogAE%2BbOnWqevbsmf/1v/71L7U45G%2B5TZs2qXbt2nrttdfUsWPHI77OsGHDNHz48MPupwDC67p1k1580Vwd/L//SSedZDsR3IACCMDTtm3bph9%2B%2BCH/6%2BrVq6ts2bKHPa5u3brq0aOHBg4ceMTX4QggUtW2bdJ550nr1klXXy39/e9myhj4WynbAQDgRGRkZCgjI%2BOYj9m6dau%2B%2BeYbVatW7aiPSU9PP%2BrpYcDLMjLMqeBmzaRp06Rnn5Vuu812KtjGRSAAUsr27dvVv39/ffjhh9qwYYPmzZunq666SlWqVFGHDh1sxwOsOP986eGHzbhvX2n1art5YB8FEEBKKVmypJYvX64//vGPqlevnrp27ap69erpww8//M0jhUAqu/tu6dJLpZ07pU6dpF27bCeCTXwGEACOIB6PKxQK8RlApJScHOmcc6QffzRLxT35pO1EsIUjgAAA%2BERWllkiTpKeekqaNctqHFhEAQQAwEcuv1y66y4z7tZN2rTJahxYQgEEAMBnRo2SGjaUtmyRunaV8vJsJ0KyUQABAPCZ9HQzNUzZstKcOdKYMbYTIdkogAAA%2BNBZZ0ljx5rx4MHSJ5/YzYPkogACAOBTt94qdegg7dlj1gzescN2IiQLBRAAAJ8KBMzKINWrS198YSaJhj9QAAHgINFoVOFwWJFIxHYUICkqV5ZeesmUweeek6ZPt50IycBE0ABwBEwEDb8ZNMhcHXzSSdJnn0k1athOhETiCCAAANCDD0qNG0s//8zUMH5AAQQAAEpLk155RSpXTnrvPenxx20nQiJRAAEAgCSpXr0D6wMPGSItXWo3DxKHAggAAPLdcovUvr2ZGuamm6SdO20nQiJQAAEAQL79U8NkZUmrV0sDBthOhESgAAIAgAKqVJEmTzbj8eOld96xGgcJQAEEAACHadtW6tPHjP/0J2nLFrt5ULwogAAA4IhGjTJrBufkSLfdJjFzcOqgAAIAgCMqW1aaOlUqXVqaMUN68UXbiVBcKIAAAOCoGjUyk0RL0p13Shs2WI2DYkIBBAAAx3TPPVLz5tK2bVKXLtK%2BfbYT4URRAAEAwDGVLClNmSJVqCAtXCiNGWM7EU4UBRAADhKNRhUOhxWJRGxHAVzl1FOlJ54w4/vuk1assJsHJybgOFzTAwCHisfjCoVCisViCgaDtuMAruA4Urt20j//KZ17rrR4sVlDGN7DEUAAAFAo%2B1cJqVxZWrbswMUh8B4KIAAAKLSsLGniRDN%2B5BHp44/t5sHxoQACAIAiufZa6YYbzNXAXbpIO3faToSiogACAIAiGz9eqlZNWrNGGjLEdhoUFQUQAAAUWaVK5vOAkjR2rJkeBt5BAQQAAMfliiukP/3JXB38pz9JO3bYToTCogACAIDj9sQTUo0a0pdfSvfeazsNCosCCAAAjlsoJD3/vBmPGyfNn283DwqHAggAAE5ImzbSrbeacffunAr2AgogAAA4YY89JtWsKX31lTR4sO00%2BC0UQAAAcMKCwQNXBY8bx1XBbkcBBICDRKNRhcNhRSIR21EAz2nbVrrlFnNV8C23SL/%2BajsRjibgOI5jOwQAuE08HlcoFFIsFlMwGLQdB/CMX36R6teXvv9e6t9fevRR24lwJBwBBAAAxaZiRemZZ8x4zBjWCnYrCiAAAChWV14p3XSTlJdnrgrOzbWdCIeiAAIAgGI3dqxUtaq0cqU0cqTtNDgUBRAAABS7KlWk8ePNeMQIacUKu3lQEAUQAAAkxLXXSu3aSXv2SD16SPv22U6E/SiAAAAgIQIBacIEM0fg4sUHjgjCPgogAABImOrVpdGjzXjIEOnrr%2B3mgUEBBAAACXXrrVKLFmaN4DvuMBNFwy4KIAAASKgSJaRJk6S0NOlf/5Jee812IlAAAQBAwp15pnTffWbct6/000928/gdBRAAACTFwIFSOCxt3iwNGGA7jb9RAAEAQFKkpR1YJu7556UFC%2Bzm8TMKIAAcJBqNKhwOKxKJ2I4CpKSLLpJ69jTjnj1ZJs6WgONwLQ4AHCoejysUCikWiykYDNqOA6SUn3%2BWzjpL%2BuEH6cEHpfvvt53IfzgCCAAAkuqkk6QnnjDjhx%2BW1q61m8ePKIAAACDpOnWSLr3UnAL%2B85%2BZGzDZKIAAACDp9i8Tl54uvfsucwMmGwUQAABYcfrpZnk4SerXT4rF7ObxEwogAACwZsAAqV49KSfnwETRSDwKIAAAsCY93ZwKlsztp5/azeMXFEAAAGBV69bmopC8POmOO8wtEosCCMBTpk%2BfrrZt26pKlSoKBAJatmzZYY/Jzc1Vnz59VKVKFZUvX17t2rXTt99%2BayEtgMJ6/HEpI0P6%2BGPpuedsp0l9FEAAnrJjxw41b95cjzzyyFEf07dvX82YMUOvvfaa3n//fW3fvl1XXnml9u3bl8SkAIoiO9tMCi1J994rbdliN0%2BqYyUQAJ60YcMG1alTR0uXLtW5556bf38sFlPVqlX10ksv6frrr5ckff/996pZs6befvtttW3btlCvz0ogQPLt3Sudd560fLl0663SpEm2E6UujgACSCmffPKJ9uzZozZt2uTfl52drbPPPluLFi2ymAzAbylVSopGzfi558zpYCQGBRBASsnJyVFaWppOOumkAvdnZmYqJyfnqM/Lzc1VPB4vsAFIvhYtpM6dzcogvXtzQUiiUAABuNbUqVNVoUKF/G3hwoXH/VqO4ygQCBz1%2ByNHjlQoFMrfatasedz/LQAnZvRoKRiUliyR/vY322lSEwUQgGu1a9dOy5Yty9/OP//833xOVlaWdu/erZ9//rnA/Zs3b1ZmZuZRn3fvvfcqFovlb998880J5wdwfLKypOHDzfjee6VD3s4oBhRAAK6VkZGh008/PX8rW7bsbz6ncePGKl26tObMmZN/36ZNm7RixQo1a9bsqM9LT09XMBgssAGwp1cvKRw2VwM/8IDtNKmnlO0AAFAUP/30kzZu3Kjvv/9ekrRmzRpJ5shfVlaWQqGQbrnlFt19992qXLmyKlWqpP79%2B6tBgwb6/e9/bzM6gCIoXVoaN85MEj1hgrkq%2BJxzbKdKHRwBBOApM2fOVKNGjXTFFVdIkjp16qRGjRrp6aefzn/ME088ofbt2%2Bu6665T8%2BbNVa5cOb311lsqWbKkrdgAjsMll0hXX20uBLnzTnNhCIoH8wACwBEwDyDgDl9/LZ15prRrl/T669J119lOlBo4AggAAFyrdm1p0CAzvuce6ddf7eZJFRRAAADgavfcI9WqJW3cKD36qO00qYECCAAAXK1cuQPFb9QoiVmaThwFEAAAuN6115pVQnbulAYOtJ3G%2ByiAAADA9QIB6cknze2rr0os7X1iKIAAAMATGjWSunc34759WSf4RFAAAQCAZzz0kJSRYdYJnjrVdhrvogACwEGi0ajC4bAikYjtKACOICtLGjzYjO%2B9V9qxw24er2IiaAA4AiaCBtxr1y7prLOkDRukoUOlYcNsJ/IejgACAABPKVNGGj3ajB99VPruO7t5vIgCCAAAPOeaa6Tmzc3KIEOG2E7jPRRAAADgOYGANGaMGU%2BZIi1dajeP11AAAQCAJzVpIt1wg%2BQ40t13m1sUDgUQAAB41siRUnq6NHeuNGuW7TTeQQEEAACeVbu2dNddZjxggLR3r908XkEBBAAAnjZ4sFS5srR6tfT887bTeAMFEAAAeFooJD3wgBkPHSpt3243jxdQAAEAgOfdfrt02mnSmWdKW7faTuN%2BpWwHAAAAOFFpadIHH0gnn2ymiMGxUQABAEBKyMy0ncA7OAUMAADgMxRAADhINBpVOBxWJBKxHQUAEibgOMybDQCHisfjCoVCisViCgaDtuMAQLHiCCAAAIDPUAABAAB8hgIIAADgMxRAAAAAn6EAAgAA%2BAwFEAAAwGcogAAAAD5DAQQAAPAZCiAAAIDPUAABAAB8hgIIAADgMxRAAAAAn6EAAsBBotGowuGwIpGI7SgAkDABx3Ec2yEAwG3i8bhCoZBisZiCwaDtOABQrDgCCAAA4DMUQAAAAJ%2BhAAIAAPgMBRAAAMBnKIAAAAA%2BQwEEAADwGaaBAYAjcBxH27ZtU0ZGhgKBgO04AFCsKIAAAAA%2BwylgAAAAn6EAAgAA%2BAwFEAAAwGcogAAAAD5DAQQAAPAZCiAAAIDPUAABAAB8hgIIAADgMxRAAAAAn6EAAgAA%2BAwFEAAAwGcogAAAAD5DAQQAAPAZCiAAAIDPUAABAAB8hgIIAADgMxRAAAAAn6EAAgAA%2BAwFEAAAwGcogAAAAD5DAQQAAPAZCiAAAIDPUAABAAB8hgIIAADgMxRAAAAAn6EAAgAA%2BAwFEAAAwGcogAAAAD5DAQQAAPAZCiAAAIDPUAABAAB8hgIIAADgMxRAAAAAn6EAAgAA%2BAwFEAAAwGcogAAAAD5DAQQAAPAZCiAAAIDPUAABAAB8hgIIAADgMxRAAAAAn6EAAgAA%2BAwFEAAAwGcogAAAAD5DAQQAAPAZCiAAAIDPUAABAAB8hgIIAADgMxRAAAAAn6EAAgAA%2BMz/A3Dvb/IdC0wIAAAAAElFTkSuQmCC'}
Genus 2 curve data - 448.a.448.1