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g2c_curves • Show schema
{'Lhash': '1485522947594584328', 'abs_disc': 200000, 'analytic_rank': 1, '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]],[5,[1]]]', 'bad_primes': [2, 5], 'class': '50000.a', 'cond': 50000, 'disc_sign': 1, 'end_alg': 'Q', 'eqn': '[[0,0,0,0,0,2],[1]]', 'g2_inv': "['0','0','0']", 'geom_aut_grp_id': '[10,2]', 'geom_aut_grp_label': '10.2', 'geom_aut_grp_tex': 'C_{10}', 'geom_end_alg': 'CM', 'globally_solvable': 1, 'has_square_sha': True, 'hasse_weil_proved': False, 'igusa_clebsch_inv': "['0','0','0','8']", 'igusa_inv': "['0','0','0','0','200000']", 'is_gl2_type': False, 'is_simple_base': True, 'is_simple_geom': True, 'label': '50000.a.200000.1', 'leading_coeff': {'__RealLiteral__': 0, 'data': '1.94552380244044184081059275666158353753990681960292', 'prec': 173}, 'locally_solvable': True, 'modell_images': ['2.36.1', '3.1296.1'], 'mw_rank': 1, 'mw_rank_proved': True, 'non_solvable_places': [], 'num_rat_pts': 5, 'num_rat_wpts': 1, 'real_geom_end_alg': 'C x C', 'real_period': {'__RealLiteral__': 0, 'data': '11.847756438961456265004469216', 'prec': 100}, 'regulator': {'__RealLiteral__': 0, 'data': '0.821051568904', 'prec': 47}, 'root_number': -1, 'st_group': 'F_{ac}', 'st_label': '1.4.D.4.1a', 'st_label_components': [1, 4, 3, 4, 1, 0], 'tamagawa_product': 5, 'torsion_order': 5, 'torsion_subgroup': '[5]', 'two_selmer_rank': 1, 'two_torsion_field': ['5.1.50000.1', [-2, 0, 0, 0, 0, 1], [5, 3], False]} -
g2c_endomorphisms • Show schema
{'factorsQQ_base': [['1.1.1.1', [0, 1], -1]], 'factorsQQ_geom': [['4.0.125.1', [1, -1, 1, -1, 1], -1]], 'factorsRR_base': ['RR'], 'factorsRR_geom': ['CC', 'CC'], 'fod_coeffs': [1, -1, 1, -1, 1], 'fod_label': '4.0.125.1', 'is_simple_base': True, 'is_simple_geom': True, 'label': '50000.a.200000.1', 'lattice': [[['1.1.1.1', [0, 1], [0, 0, 0, 0]], [['1.1.1.1', [0, 1], -1]], ['RR'], [1, -1], 'F_{ac}'], [['2.2.5.1', [-1, -1, 1], [0, 0, -1, 1]], [['2.2.5.1', [-1, -1, 1], -1]], ['RR', 'RR'], [1, -1], 'F_{ab}'], [['4.0.125.1', [1, -1, 1, -1, 1], [0, 1, 0, 0]], [['4.0.125.1', [1, -1, 1, -1, 1], -1]], ['CC', 'CC'], [1, -1], 'F']], 'ring_base': [1, -1], 'ring_geom': [1, -1], 'spl_fod_coeffs': [1, -1, 1, -1, 1], 'spl_fod_gen': [0, 1, 0, 0], 'spl_fod_label': '4.0.125.1', 'st_group_base': 'F_{ac}', 'st_group_geom': 'F'} -
g2c_ratpts • Show schema
{'label': '50000.a.200000.1', 'mw_gens': [[[[-1, 1], [1, 1]], [[-2, 1], [0, 1], [0, 1], [0, 1]]], [[[0, 1], [1, 1]], [[0, 1], [0, 1], [0, 1], [0, 1]]]], 'mw_gens_v': True, 'mw_heights': [{'__RealLiteral__': 0, 'data': '0.82105156890403692051644696761615', 'prec': 113}], 'mw_invs': [0, 5], 'num_rat_pts': 5, 'rat_pts': [[0, -1, 1], [0, 0, 1], [1, -2, 1], [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': '50000.a.200000.1', 'plot': 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AUES7d0tz55qevm%2B/zX2%2BYkXplltM6OvcmaXa4LsIgAAcIz4%2BXvHx8crMXiIB8KKtW6VPPpHmzZPWrs19PiBA6tZN6ttXuvlmqVIl%2B2oECou1gAE4DmsBwxsyMswAjgULTPvpp9yveTxSp07S7bebpdoiI%2B2rEygOegABAPjTrl3S4sXSF19IS5bkDuSQzGCOrl1NL9%2BNN0pRUfbVCZQUARAA4Fq//iotXy599ZW0dGnuBM3ZqlaVevaUrrtOuuYaKSLCljKBUkcABAC4QmamtGmTWX931SqzDFtiYv7XBAVJbdtK3bubwNeypRQYaEu5QJkiAAIA/E5WlrR9u7R%2BvbRunRm0sW5d7koc2QICpBYtpC5dzOXdTp2ksDBbSga8igAIAHC0gwelzZtN797GjdIPP5h29OiZrw0Lk9q0kdq1kzp2NFsCH9yIAAgA8HknTpgBGtu3m8mWt241o3J/%2Bknav//sx4SESJdfbi7jtmoltW4tNW7MJV1AIgACcJING6RXX5UWLTL7Dz8sjRghNWpkb10oEcuSDh2SfvtN2rPHDMz45ZfctmuX9Pvv536PmBjpkkukpk2lyy4zwa9RI3NPH4AzMQ8gAGdYsMAssZCerhRJEZKSJYVXqmQCYbt2NheIbJYlHT9uQt3Bg6YdOCD98Yfprdu/X9q3T0pKkvbuNdu0tPO/b3i41KCBaRdfbAJekyZmy%2BTLQNEQAAH4vvR0qU4dkxqk/AFQMl0/mzbZV59DZWZKJ0%2BaH%2B/Jk/nb8ePmsuuJE2bgRHY7ejS3paaaefJSUqTkZOnIEbM9fNhMolxU1apJF14oRUebFhNjWt26Ur16ZkoWj6f0fw6AG9E5XgKWZSk1NdXuMuCjLMv8I5iWZtrJk2abnp7bMjJytxkZ0qlTpmVkmH%2Bcs/czM03Lysr/OHs/K8t8v4K2eVv2c9k1nl7z6c%2Bf7U/E4v7ZWNzjYnf%2BR/f9Gf4kEwDzbrV5s16/fql212hVvG9QRAX93Ap6nHeb3U7fz34u72eW/RkX1LJ/F87W8v4eZf9%2BZbfs37%2By/vM/KEiqXNkEt%2BxWrZpUo4ZUvbrZRkWZVTSioqTg4HO/H/%2B7RWkLCwuTx6V/VdADWALZy1EBAADncfNykgTAEiioBzAuLk7ffvttsd6zuMcW97iUlBRFR0drz549Rf6PwEnneeBAiurX76i5c79WcnKokpLM1cT9%2B819SX/8Ye5ROniwcPciFUdQkBmVWK6c6ekoX948zt6WK2deExQkrV%2B/Vh06tFZgoBmxGBSknMcBAaZlP877XEZGuqZPn6JBgwaofPlgeTzmeY8nt2XvS7nPSdJ7772rwYMH57vEVtDj002a9I6GDLm/yD%2BTwh530bbPdOfHfXL2UyRFS9qjPy8BS5oyYIX2RV5eat9TOvOc33nnbd1//wMFvuZcjydMiNewYcPO%2BNmfrWV/RunpJ/Tcc89qzJiXVKFChTM%2B77y/A3l/R7L3hw0boilTJikoKPd3LLtl/w6WL28eBwXl1uzt/7ZL8v%2Bh4n7PkhxX3GM5z7L7nsU9lh5AlKrY2Fht2bLFq8cW97jsXszi/BXkS%2BeZmWlGC27fLu3YYZZzSkzMHUVY0DQRBQkKkqpUMe2XXxLUuXMzRUSYZaDCw00LCzOtUiUpNNS0ihVzW4UKUteu7bRhw9cKCTH/UJf0PM/HXz7PM2RmmpvAdu%2BWdJZ7AFu1kgr5P307zrO4x5bk8yzu9yzJccU9lvMsu%2B9ZkuOKe6xd51nSY92GewDLwLBhw7x%2BbEm%2BZ3HZcZ4PPPAXbd5sJnvdvFnassXMA7Z9u7mn6dxOqG7dYF14YYBq1zb3HGXff1Sjhrk3KbuFheX2hsTHr9KwYc2KVe/DD9%2BtihWLfpxbPs9CHxcYKH3wgVmU9fRe9xo1pGnTSv97%2BtCx3v6enGfZHuvt7%2BmW8yzpsW5DD6DLlfQvtbKUnm5m81%2B71izntH69CX0FBb3gYNNJVL%2B%2B2darlzuKsHLlVNWtG%2B6T51mafPnzLBWJiVJ8vA4vXKgqW7Zo//Dhqv7UUybJ%2ByG//zz/xHn6F7ecp9PRA%2BhywcHBGjVqlILPN/zOCw4eNIuzr1wprV5tAt/Z7serVEm69FLTYmPNPGCNG5tpIwqa4T8trbzPnGdZ8qXPs0xcdJH0r3/p1JNPmp6/Z54xw0n9lN9/nn/iPP2LW87T6egBhG2OHZOWL5eWLJG%2B/NL09p2uShUpLs4s5dSypdSsmckARbmfDv6HHgYAKBl6AOFVv/wizZ9vFnVYvvzMHr4mTaROnaQOHczCDg0aMPErAACljQCIMrd9u/Thh9LcuWYp17xiYqTu3aVu3aSuXc1VPQAAULYIgCgTBw5Is2dLM2ZI332X%2B3xAgNSxo3T99VKvXubePXr4AADwLgIgSk1WlrmXb9Ik6T//yV0LNDBQuuoq6bbbpN69/fqefQAAHIFb6V3AsiyNHj1atWrVUoUKFdSlSxdt3rz5vMf99ttvuvvuu1W1alVVrFhRzZo107p16854XWqq9NZbpjevRw9zqTcjQ2rRQnrzTen336UvvpAGDy7b8Ffc88w2duxYeTweDR8%2BvOyKLAXFOc%2BxY8cqLi5OYWFhqlGjhm688Ub9/PPPXqoY5zJhwgTVrVtXISEhatmypVauXFngaydPnqxOnTqpcuXKqly5srp166a1a9d6sdriK8p55jVnzhx5PB7deOONZVxh6SjqeR45ckTDhg1TzZo1FRISoiZNmmjhwoVeqrb4inqeb7zxhho1aqQKFSooOjpajz76qE6ePOmlanFWFvzeyy%2B/bIWFhVkff/yxtXHjRuuOO%2B6watasaaWkpBR4zKFDh6yYmBjr3nvvtdasWWPt2rXLWrJkibV9%2B/ac1%2Bzda1lPP21ZERG5y9mHh1vWsGGW9f333jiz/IpzntnWrl1rXXTRRdZll11mPfLII16otviKc55XX321NXXqVGvTpk1WQkKC1atXL6tOnTrW0aNHvVh56UlOTrYkWcnJyXaXUiJz5syxypUrZ02ePNnasmWL9cgjj1ihoaHWL7/8ctbX33XXXVZ8fLy1YcMG68cff7QGDBhgRUREWL/%2B%2BquXKy%2Baop5ntsTERKt27dpWp06drN69e3up2uIr6nmmpaVZrVq1sq699lrrf//7n5WYmGitXLnSSkhI8HLlRVPU85w5c6YVHBxszZo1y9q1a5f1xRdfWDVr1rSGDx/u5cqRFwHQz2VlZVlRUVHWyy%2B/nPPcyZMnrYiICOvtt98u8LinnnrK6tix41m/9vvvlvXII5YVEpIb/Bo1sqwJEywrNbXUT6FQinuelmVZqampVsOGDa3FixdbnTt39ukAWJLzzGv//v2WJGv58uVlUWaZGT9%2BvNWkSRPr4osv9osA2Lp1a%2BuBBx7I91zjxo2tp59%2BulDHnzp1ygoLC7OmT59eFuWVmuKc56lTp6wOHTpY7777rtW/f39HBMCinufEiROtevXqWenp6d4or9QU9TyHDRtmXXnllfmee%2Byxxwr8NwbewSVgP7dr1y4lJSWpR48eOc8FBwerc%2BfOWr16dYHHzZ8/X61atdJtt92mGjVqqHnz5nrzzekaMcKstPHmm9LJk1KbNtKnn5ol2YYONZM026G45ymZpYN69eqlbt26lXWZJVaS88wrOTlZklSlSpVSr7EsDRs2TFu2bCn2QvG%2BJD09XevWrcv3WUpSjx49Cv1ZHj9%2BXBkZGT79ORb3PF944QVVr15dgwYNKusSS0VxznP%2B/Plq166dhg0bpsjISF166aUaM2aMMjMzvVFysRTnPDt27Kh169bl3K6wc%2BdOLVy4UL169SrzelEwBoH4uaSkJElSZGRkvucjIyP1yy%2B/FHjczp07NXHiRD322GN68sln9NprxzR8eOOcr7dtK73wgpm%2BxRdG8Rb3POfMmaP169c7JlAU9zzzsixLjz32mDp27KhLL7201GtE4Rw4cECZmZln/SyzP%2Bfzefrpp1W7dm2f/uOlOOe5atUqvffee0pISPBGiaWiOOe5c%2BdOLV26VH379tXChQu1bds2DRs2TKdOndLIkSO9UXaRFec8%2B/Tpoz/%2B%2BEMdO3aUZVk6deqUhg4dqqefftobJaMA9AD6mVmzZqlSpUo5LePPobie01KaZVlnPJdXVlaWWrRooV69xmjw4OaaM6ejpGqqUGGn5s83S7V1725f%2BCuN89yzZ48eeeQRzZw5UyEhIWVec3GU1ueZ10MPPaQffvhBs2fPLvV6UXTF/Sz/%2Bc9/avbs2Zo3b57P/v7mVdjzTE1N1d13363JkyerWrVq3iqv1BTl88zKylKNGjU0adIktWzZUn369NGzzz6riRMneqPUEinKeX711Vd66aWXNGHCBK1fv17z5s3TggUL9OKLL3qjVBSAHkA/c8MNN6hNmzY5%2B2l/LrWRlJSkmjVr5jy/f//%2BM/6CyysysqEOHx6jjh3NfpUqUvfuK7Rixd26/vrdZVN8EZTGea5bt0779%2B9Xy5Ytc57LzMzUihUrNH78eKWlpSmwoMWFvaS0Ps9sf/nLXzR//nytWLFCF154YekXjEKrVq2aAgMDz%2Bg1Kcxn%2Bcorr2jMmDFasmSJLrvssrIss8SKep47duxQYmKirr/%2B%2BpznsrKyJElBQUH6%2BeefVb9%2B/bItuhiK83nWrFlT5cqVy/f/mSZNmigpKUnp6ekqX758mdZcHMU5z%2Beee079%2BvXT4MGDJUlNmzbVsWPHNGTIED377LMKYG1PW/BT9zNhYWFq0KBBTouNjVVUVJQWL16c85r09HQtX75c7du3P%2Bt7LF0qHTr0lX76qYskaeBA6eefpZo1P9FFF/lGaCiN87zqqqu0ceNGJSQk5LRWrVqpb9%2B%2BSkhIsD38SaVznpL56/yhhx7SvHnztHTpUtWtW9cb5eMcypcvr5YtW%2Bb7LCVp8eLF5/ws//Wvf%2BnFF1/U559/rlatWpV1mSVW1PNs3LjxGf9d3nDDDeratasSEhIUHR3trdKLpDifZ4cOHbR9%2B/acgCtJW7duVc2aNX0y/EnFO8/jx4%2BfEfICAwNlmYGoZVYrzsOesSfwppdfftmKiIiw5s2bZ23cuNG68847z5g25Morr7TeeCPeevJJy/J4skf37rAGDZppbdu2zZo1a5ZVsWJFa%2BbMmTaeybkV9jzHjRtX4Hv4%2BihgyyreeQ4dOtSKiIiwvvrqK2vv3r057fjx43acQon52zQw7733nrVlyxZr%2BPDhVmhoqJWYmGhZlmX169cv38jKf/zjH1b58uWtuXPn5vscU%2B0afl9IRT3P0zllFHBRz3P37t1WpUqVrIceesj6%2BeefrQULFlg1atSw/v73v9t1CoVS1PMcNWqUFRYWZs2ePdvauXOntWjRIqt%2B/frW7bffbtcpwGIaGFfIysqyRo0aZUVFRVnBwcHWFVdcYW3cuDHfa2rXbmtdeOHunGld7rvPsj78cKF16aWXWsHBwVbjxo2tSZMm2XQGhVOY84yJibFGjRpV4Hs4IQAW5zwlnbVNnTrVu8WXEn8JgJZlWfHx8VZMTIxVvnx5q0WLFvmm5uncubPVv3//nP2YmJizfo7n%2Bp32FUU5z9M5JQBaVtHPc/Xq1VabNm2s4OBgq169etZLL71knTp1ystVF11RzjMjI8MaPXq0Vb9%2BfSskJMSKjo62HnzwQevw4cM2VI5sHsui/9XtVqyQbr1V%2BuMPKSJCmjpVuukmu6sCCpaSkqKIiAglJycrPDzc7nIAwHG4B9Dlpk41U7n88YfUrJm0fj3hDwAAf0cAdCnLMvP4DRxo1u29/XZp1SqpXj27KwMAAGWNAOhCWVnSI49Io0aZ/WeekWbPlipWtLcuAADgHcwD6DJZWdIDD0iTJ5tJnMePlx580O6qgMKJj49XfHy8Ty%2BVBQBOwCAQF7EsadgwaeJEKSBAmjZN6tfP7qqAomMQCACUDD2ALvK3v5nw5/FIM2ZIffvaXREAALAD9wC6xDvvSGPGmMdvv034AwDAzQiALrBkibn0K0nPPy8NGWJvPQAAwF4EQD%2BXmCjdcYeUmWnu93vuObsrAgAAdiMA%2BrH0dOm226RDh6S4OGnSJHP/HwAAcDcCoB979lnpu%2B%2BkKlWkuXOlkBC7KwIAAL6AAOinVqyQXn3VPJ4yRapTx956AACA7yAA%2BqETJ8wSb5YlDRok9e5td0UAAMCXEAD90N//Lu3YIdWuLb32mt3VAAAAX0MA9DPbt0uvvGIejxsnsUgCAAA4HQHQzzz1lBn9e/XV0o2eVihMAAAdkElEQVQ32l0NULri4%2BMVGxuruLg4u0sBAEdjLWA/smaN1LatWef3hx%2BkSy6xuyKgbLAWMACUDD2AfmTUKLO95x7CHwAAKBgB0E%2BsXy998YUUGMhqHwAA4NwIgH4ie%2BBHnz5SvXr21gIAAHwbAdAPJCVJH31kHj/2mL21AAAA30cA9ANTp0qnTknt2kktWthdDQAA8HUEQIezLGnaNPP4vvtsLQUAADgEAdDh1q%2BXtm6VKlSQbr3V7moAAIATEAAdbu5cs73uOikszN5aAACAMxAAHW7%2BfLO96SZ76wAAAM5BAHSwPXukLVvMyh/XXGN3NQAAwCkIgA62dKnZxsVJlSvbWwvgDawFDAClgwDoYCtXmm2XLraWAXjNsGHDtGXLFn377bd2lwIAjkYAdLA1a8y2XTt76wAAAM5CAHSokyelH380j1u1srcWAADgLARAh/rpJykzU6pSRapVy%2B5qAACAkxAAHeqnn8y2SRPJ47G3FgAA4CwEQIfatcts69e3tw4AAOA8BECH%2BvVXs42OtrcOAADgPARAh9q3z2yjouytA%2B5mWZZGjx6tWrVqqUKFCurSpYs2b958zmNGjx4tj8eTr0XxiwwAXkUAdKjDh822ShV764C7/fOf/9Rrr72m8ePH69tvv1VUVJS6d%2B%2Bu1NTUcx53ySWXaO/evTlt48aNXqoYACARAB0r%2B9/XsDB764B7WZalN954Q88%2B%2B6xuvvlmXXrppZo%2BfbqOHz%2BuDz744JzHBgUFKSoqKqdVr17dS1UDACQCoGOlpZltcLC9dcC9du3apaSkJPXo0SPnueDgYHXu3FmrV68%2B57Hbtm1TrVq1VLduXfXp00c7d%2B485%2BvT0tKUkpKSrwEAio8A6FCWZbYBfIKwSVJSkiQpMjIy3/ORkZE5XzubNm3aaMaMGfriiy80efJkJSUlqX379jp48GCBx4wdO1YRERE5LZrRTwBQIsQHh8oOfpmZ9tYB95g1a5YqVaqU0zIyMiRJntMmorQs64zn8urZs6duueUWNW3aVN26ddP//d//SZKmT59e4DEjRoxQcnJyTtuzZ08pnBEAuFeQ3QWgeCpUMNsTJ%2BytA%2B5xww03qE2bNjn7aX/eh5CUlKSaNWvmPL9///4zegXPJTQ0VE2bNtW2bdsKfE1wcLCCud8BAEoNPYAOlT344zyDLYFSExYWpgYNGuS02NhYRUVFafHixTmvSU9P1/Lly9W%2BfftCv29aWpp%2B/PHHfCESAFC2CIAOVbWq2R44YG8dcC%2BPx6Phw4drzJgx%2BuSTT7Rp0ybde%2B%2B9qlixou66666c11111VUaP358zv4TTzyh5cuXa9euXVqzZo1uvfVWpaSkqH///nacBgC4EpeAHSr7Cts57rUHytyTTz6pEydO6MEHH9Thw4fVpk0bLVq0SGF55ifasWOHDuT5S%2BXXX3/VnXfeqQMHDqh69epq27atvvnmG8XExNhxCgDgSh7Lyh5PCid59VXpiSekO%2B6Q5syxuxrAu1JSUhQREaHk5GSFh4fbXQ4AOA6XgB2qfn2z3b7d3joAAIDzEAAdqnFjs/3pJykry95aAACAsxAAHapBAykkRDp2jF5AAABQNARAhwoKki6/3Dz%2B7jt7awEAAM5CAHSw7Dl5z7PsKgAAQD4EQAfr3Nlsly2ztw4AAOAsBEAH69LFrAm8ZYvE0qhwg/j4eMXGxiouLs7uUgDA0ZgH0OHat5e%2B/lqaOFF64AG7qwG8g3kAAaBk6AF0uN69zXbuXHvrAAAAzkEAdLjbbjPbZcukvXvtrQUAADgDAdDh6tWT2rY1k0HPnGl3NQAAwAkIgH5g4ECznTyZVUEAAMD5EQD9wJ13SuHh0rZt0qJFdlcDAAB8HQHQD1SqlNsL%2BMor9tYCAAB8HwHQTwwfbpaH%2B/JLac0au6sBAAC%2BjADoJ2JipLvvNo9HjrS3FgAA4NsIgH7kueekcuXMfYBLlthdDQAA8FUEQD9Sr540dKh5/Oij0qlT9tYDAAB8EwHQz4wcKVWpIm3aJI0bZ3c1QOliLWAAKB2sBeyHJk%2BWhgyRQkOlzZvN/YGAP2EtYAAoGXoA/dCgQVKnTtKxY9KAAUwODQAA8iMA%2BqGAAGnKFKliRbNG8Guv2V0RAADwJQRAP9WggfT66%2BbxiBHSN9/YWw8AAPAdBEA/dt990m23mdHAt90m7dtnd0UAAMAXEAD9mMcjvfuu1KiR9Ouv0k03SSdP2l0VAACwGwHQz4WHS/PnSxdcIH39tdS/P4NCAABwOwKgC1x8sTRvnlkl5MMPpb/8RWLyHwAA3IsA6BJdu0ozZpjLwhMmSE8%2BSQgEAMCtCIAu0qeP9Pbb5vErr0iPP04IBADAjQiALjNkiOkBlMw0MYMHs2YwAABuQwB0oaFDzUTR2RNG9%2B4tpabaXRVwfqwFDAClg7WAXew//zGXhU%2BelC67zOxfdJHdVQHnx1rAAFAy9AC6WO/e0ldfSZGR0g8/SK1aSYsW2V0VAAAoawRAl2vTRvr2WxP%2BDh6UrrlGevZZKSPD7soAAEBZIQBC0dHSypXS/febUcFjxkgdO0o//2x3ZQAAoCwQACFJCgkxU8T8%2B99SRIS0dq3UrJmZLoZRwgAA%2BBcCIPK5/XZp40apWzczOOSvfzWXidessbsyAABQWgiAOEN0tBkMMnmyWUN4/XqpbVtp4EBp7167qwMAACVFAMRZeTxmkuiffpLuucc8N3Wq1LChNGqUlJJib30AAKD4CIA4p8hIafp0afVq0wt47Jj0wgtSvXrSyy8zgTQAAE5EAEShtGtnQuBHH0mNGpkpY0aMkGJipJEjpf377a4QAAAUFgEQhebxSLfeKm3aJM2YYYLg4cPSiy9KdepIgwZJGzbYXSUAADgfAiCKLChI6tdP2rzZ9Ai2bi2lpZl1hVu0MJeKp0yRjh61u1L4G9YCBoDSwVrAKDHLkr7%2BWho3Tpo7N3fewNBQ6ZZbpL59pSuvNMERKA2sBQwAJUMARKnat8%2BMFp4yRdq2Lff56tWlm282gbBLF6lcOdtKhB8gAAJAyRAAUSayewVnzpQ%2B/NAMGskWEWHWHO7VS7r6aqlGDfvqhDMRAAGgZAiAKHMZGdLSpdLHH0uffir98Uf%2BrzdvLl11ldS1q9SpkxQWZk%2BdcA4CIACUDAEQXpWZadYZXrBAWrhQSkjI//WAALMGcceOZuqZ1q2lunXNCGQgGwEQAEqGAAhbJSWZ3sEvv5SWLZN27TrzNdWqSS1bmhHGzZpJl18uNWggBQZ6v174BgIgAJQMARA%2B5ddfpVWrTPvmG9NDmJFx5utCQqTGjaVLLjHbxo2liy%2BW6tc3o4/h31IOHVJE1aoEQAAoJgIgfNrJk9IPP0jr1plJphMSzETUJ04UfExUlAmCdetKF11kJqmOjjatdm0zCIVLyvaZN2%2Be3nnnHa1bt04HDx7Uhg0b1KxZs8Id/MUX0ssvK%2BWrrxQhKbl7d4WPHi21b1%2BWJQOA3yEAwnEyM82l4s2bpR9/NO3nn820M4cOnf/40FCpZk3TIiNNq1HDTFVTrZppVatKVapIlStLFSsSGEvT%2B%2B%2B/r127dqlWrVq67777Ch8Ap02TBg6ULEspkgmAksLLlZM%2B%2BcQMKwcAFAoBEH7l0CFpxw4TEHftkhITpd27pT17TDtypOjvGRQkXXCB6TnMbmFhUni4VKlSbqtY0bTQUKlChdwWEpLbgoNNK18%2BfytXzgyAcZPExETVrVu3cAHw%2BHGpVi0pOVmS8gdAyXT3bt/uvh8iABQTARCucuyY9Pvv0t69ZgDKvn2m7d9vpqc5cMC0gwfNOsfZq5p4Q0CACYLlypnQWa6cGegSGGj2sx9nt4CA/FuPxzw%2B2za75d2Xznx8tu25HudV1F7S48eP68svl%2BiKKzorIiLinK/t%2BOsHenJD35z9MwKgpBHtl2tz1SuKVkQRnescz/fzKuhnfraW9/MrqJ3%2Be5D9O5J3e/rvU7lyZ/7xkf1HSXCw%2BSMl%2B4%2BWChXMHzTlytEDDvgjFueCq4SGSg0bmnY%2BlmUC4%2BHDpucwOdm0lBQpNTW3HTtm1j0%2Bdsx0VB07Zu5RPHHC3MOYvU1Ly99O/9MrKyv3a%2B5QUdINWrHi/K%2Bso/Nf2/959QH9t%2BRF4TSBgbm925Uqmf%2BGsnu9s3vCIyJyt5Urmx7z7Fsosm%2BnqFDB7jMBkBcBECiAx5P7D110dOm%2Bt2WZexnT003LyDDt1Kn8jzMzc7dna1lZpmU/tqz826ys3O%2BX92vZ4fP0x3m353p8rufy%2BuabbzRjxoyc/eHDh%2Bviiy%2BWJB04cEBPP/2URo4cpTp16pzzfapvaiS9ce7vddeLsepV89yvOZ%2BiXg85/fVn%2B3mdbXv647wt72eU9zPO%2B5lmP3%2B234lTp/K303%2Bvsn/n0tNz/%2BBITzd/pGS3Eydya8zMzP1jZ9%2B%2Bov188goNNffZVq9u7rnNvv%2B2Zk1zdT9vY6lIoOxxCRhAmUlNTdW%2BPKmhdu3aqvBnV1CR7gG0LDPnz48/SjrLJeArrzSTSaJUWJYJhSdOmF7t7J7t7N7uo0fz94Jn944nJ5ve8sOHTTt0yLTMzMJ/b4/HjOSvU8e0iy4yt3jWq2faRRcREIHSQA8ggDITFhamsNJY28/jkT76SOre3dzAmVeDBmaEMEqNx5N7X%2BAFF5TsvSzLBMPs%2B2uz77ndv9/ch5uUZO7L/f136bffTC/l3r2mrVlz5vsFBpoQePHFUqNGpsXGmlatWslqBdyEHkAAXnXo0CHt3r1bv//%2Bu3r16qU5c%2BaoUaNGioqKUlRU1LkPPnJEmj5dKQsXKmLRIiW/%2BabCBw82N6jB8bKyzGCsPXvM6P1ffjFt587cdq45QCMjpUsvlS67zKwa1Ly51KSJGQQDID8CIACvmjZtmgYMGHDG86NGjdLo0aML9R4sBedOlmV6BrduNe2nn0z78Ucz5dPZhISYQNiqlVlbvG1bMwiMGYPgdgRAAI5DAMTpjh6VtmyRNm40qwclJJiWknLmaytXltq1kzp0kDp1kuLiTFAE3IQACMBxCIAojKwsMzH8unXS2rWmrV9/5mXk4GATCLt2la66yvQUMtAE/o4ACMBxCIAorowM6fvvpVWrpP/9T1q58szpbcLCTBi8%2BmqpZ08zChnwNwRAAI5DAERpsSxzP%2BGyZdLSpaYdPJj/NU2aSNddJ11/vdS%2BvRmJDDgdARCA4xAAUVayssy9g198IX3%2BuekpzDuPYbVqUu/e0s03S926meX0ACciAAJwHAIgvOXIERMGFyww7ciR3K9dcIF0441Snz7m3kGmm4GTEAABOA4BEHbIyJBWrJDmzTMtKSn3azVqSHfcId1zj9SypZlMG/BlBEAAjhEfH6/4%2BHhlZmZq69atBEDYJjPTDCL597/NIjUHDuR%2BLTZWuvdeEwYjI20rETgnAiAAx6EHEL4kI0NavFh6/33p00%2BlkyfN80FBZuDI/febVQyZfBq%2BhAAIwHEIgPBVycnShx9K772Xfy3jevWkBx6QBg6Uqla1rz4gGwEQgOMQAOEEmzZJkydL06ebYCiZFUfuvlt65BGzbjFgFwIgAMchAMJJjh%2BX5syRxo%2BXNmzIfb57d%2Bnxx6UePRg0Au/jjgQAAMpQxYrm0u%2B6dWblkVtvNfcDLl4sXXON1KyZ9MEH0qlTdlcKNyEAAgDgBR6P1LGjGTW8Y4e5DBwaKv3wg9S3r9SokblknJ5ud6VwAy4BA3AcLgHDXxw%2BLMXHS2%2B%2BmTuVTHS09Mwz0oABUnCwvfXBf9EDCACATSpXlv72NykxUXrtNalmTWnPHmnoUOnii6V33%2BXSMMoGARAAAJuFhkqPPirt3CmNGyfVqiXt3i3dd5%2BZWHrOHLNOMVBaCIAAAPiIkBDpoYek7dtNj2D16tK2bdKdd0pxcdKXX9pdIfwFARAAAB9ToYLpEdyxQ3r%2BeSksTFq/XurWTbr2WmnLFrsrhNMRAAE4Rnx8vGJjYxUXF2d3KYBXhIVJI0eaIPiXv5jl5T77TLrsMmnYMOngQbsrhFMxChiA4zAKGG61bZv05JNmzWHJDCJ58UWz3nBQkL21wVnoAQQAwCEaNpQ%2B%2BURautT0Ah4%2BbO4ZbNVKWrXK7urgJARAAAAcpmtXs7JIfLzpBfz%2BezPJ9KBBufMJAudCAAQAwIGCgqQHH5S2bjXBT5KmTJEaN5amTZO4wQvnQgAEAMDBqlUzE0avWiU1bWoGhgwYYEYMb99ud3XwVQRAAAD8QPv25rLwP/5h5hNcutQEwldflTIz7a4OvoYACACAnyhXzowS3rRJuuoq6eRJ6YknpA4dpB9/tLs6%2BBICIAAAfqZ%2BfWnxYmnyZCk8XFqzRmreXHrlFXoDYRAAAQDwQx6PNHiwtHmzdM01Ulqa9Ne/mhHEu3bZXR3sRgAEAMCPXXihtHCh6Q2sVElaudLMIchIYXcjAAIA4OeyewN/%2BMHMF3j0qBkpfPvt0qFDdlcHOxAAATgGawEDJVO3rvTVV9KYMWYewblzpcsvl1assLsyeBtrAQNwHNYCBkruu%2B%2Bku%2B4y6wsHBEgjR0p/%2B5sUGGh3ZfAGegABAHChVq2k9eul/v2lrCxp9Gipe3dp7167K4M3EAABAHCpSpXMYJD335dCQ6Vly8x0MUuX2l0ZyhoBEAAAl7v7brOKSNOm0r59pifwpZdMzyD8EwEQAACoUSMzYfTAgSb4/e1vUu/e0pEjdleGskAABAAAkqQKFaT33pPefVcKDpYWLDD3Cm7caHdlKG0EQAAAkM%2BgQdLq1VJMjLRjh9S2rfTRR3ZXhdJEAAQAAGdo0cLcF9i9u3T8uJk0%2BtlnuS/QXxAAAQDAWVWtapaRe%2BIJsz9mjHTjjVJKir11oeQIgAAAoEBBQdK//iXNnGnuC/zvf6X27aVdu%2ByuDCVBAAQAAOfVt6%2B0cqVUs6a0ebPUurX0v//ZXRWKiwAIwDFYCxiwV1yc9O235v7AAwekq66SZs2yuyoUB2sBA3Ac1gIG7HXsmHTPPdK8eWZ/9GizlrDHY2tZKAJ6AAEAQJGEhpppYf76V7M/erQ0YICUnm5rWSgCAiAAACiygADpn/%2BU3n5bCgyUpk%2BXevVihLBTEAABAECx3X%2B/GRkcGiotWSJdcYW0d6/dVeF8CIAAAKBEevaUli%2BXIiOl778308T8/LPdVeFcCIAAAKDEWrY0y8c1bCglJkodO5oRw/BNBEAAAFAq6tWTVq2SWrUy08R07SotXmx3VTgbAiCAYps3b56uvvpqVatWTR6PRwkJCec9Ztq0afJ4PGe0kydPeqFiAGWtenVp2TKzhvCxY2ZgyNy5dleF0xEAARTbsWPH1KFDB7388stFOi48PFx79%2B7N10JCQsqoSgDeVqmSGRhy661SRoZ0xx3SlCl2V4W8guwuAIBz9evXT5KUmJhYpOM8Ho%2BioqLKoCIAviI4WJozRxo6VJo8WRo0SEpNlR55xO7KINEDCMAGR48eVUxMjC688EJdd9112rBhwzlfn5aWppSUlHwNgO8LDJTeeUd64gmzP3y49Pe/21sTDAIgAK9q3Lixpk2bpvnz52v27NkKCQlRhw4dtG3btgKPGTt2rCIiInJadHS0FysGUBIej5kw%2Bvnnzf5zz0nPPCOxEK29WAsYQKHMmjVL999/f87%2BZ599pk6dOkkyl4Dr1q2rDRs2qFmzZkV636ysLLVo0UJXXHGF3nrrrbO%2BJi0tTWlpaTn7KSkpio6OZi1gwGFefTW3N/Cxx6RXXmH9YLtwDyCAQrnhhhvUpk2bnP3atWuXyvsGBAQoLi7unD2AwcHBCg4OLpXvB8A%2Bjz8uhYRIDz0kvfaaGSDy5puEQDsQAAEUSlhYmMLCwkr9fS3LUkJCgpo2bVrq7w3A9wwbJpUvb5aQGzdOOnVKio8nBHobARBAsR06dEi7d%2B/W77//Lkn6%2Bc%2B1n6KionJG%2Bd5zzz2qXbu2xo4dK0l6/vnn1bZtWzVs2FApKSl66623lJCQoPj4eHtOAoDX3XefVK6cNHCgNHGiuR8wPl4KYGSC1/CjBlBs8%2BfPV/PmzdWrVy9JUp8%2BfdS8eXO9/fbbOa/ZvXu39uZZGf7IkSMaMmSImjRpoh49eui3337TihUr1Lp1a6/XD8A%2B994rTZtmev7efttcFmZUgvcwCASA46SkpCgiIoJBIIAfmDHDhEHLMiHwrbe4HOwN9AACAADb3HOPWSXE45HGjzcDReiaKnsEQAAAYKt775UmTTKPX3%2BdeQK9gQAIAABsN3iwNGGCefzyy9KLL9pbj78jAAIAAJ8wdKiZH1CSRo0yE0ejbBAAAQCAz3j00dz1gp94wqwljNJHAATgGPHx8YqNjVVcXJzdpQAoQ888Iz31lHk8dKg0e7a99fgjpoEB4DhMAwP4v%2BxpYSZMkIKCpE8/lf6cchSlgB5AAADgczwes1Rc375mubhbb5VWrrS7Kv9BAAQAAD4pIECaOlW67jrp5EmzTUiwuyr/QAAEAAA%2Bq1w56cMPpU6dpJQU6ZprpB077K7K%2BQiAAADAp1WoIM2fL11%2BubRvn3T11WaL4iMAAgAAn3fBBdJnn0l165oewGuvlVJT7a7KuQiAAADAEWrWlL74QqpWTVq/XrrlFik93e6qnIkACAAAHKNhQ2nhQqliRWnxYrOEHBPaFR0BEAAAOEpcnDR3rhQYKL3/vvTcc3ZX5DwEQAAA4Dg9e0qTJpnHL72U%2BxiFQwAEAACONHCgNGqUefzgg2aQCAqHAAgAABxr1Cipf38pM1O6/XYmii4sAiAAx4iPj1dsbKzi4uLsLgWAj/B4zOXfK6%2BUjh41q4UcPmx3Vb7PY1mMnQHgLCkpKYqIiFBycrLCw8PtLgeADzhyxKwWMnCgNHy4CYYoWJDdBQAAAJTUBRdI330nBQfbXYkzcAkYAAD4BcJf4REAAQAAXIYACAAA4DIEQAAAAJchAAIAALgMARAAAMBlCIAAAAAuQwAEAABwGQIgAACAyxAAATgGawEDQOlgLWAAjsNawABQMvQAAgAAuAwBEAAAwGUIgAAAAC5DAAQAAHAZAiAAAIDLEAABAABchgAIAADgMgRAAAAAlyEAAgAAuAwBEAAAwGUIgAAcg7WAAaB0sBYwAMdhLWAAKBl6AAEAAFyGAAgAAOAyBEAAAACXIQACAAC4DAEQAADAZQiAAAAALkMABOA1GRkZeuqpp9S0aVOFhoaqVq1auueee/T777/bXRoAuAoBEIDXHD9%2BXOvXr9dzzz2n9evXa968edq6datuuOEGu0sDAFdhImgAtvr222/VunVr/fLLL6pTp06hjmEiaAAomSC7CwDgbsnJyfJ4PLrgggsKfE1aWprS0tJy9lNSUrxRGgD4LS4BA7DNyZMn9fTTT%2Buuu%2B46Z0/e2LFjFRERkdOio6O9WCUA%2BB8CIIAyM2vWLFWqVCmnrVy5MudrGRkZ6tOnj7KysjRhwoRzvs%2BIESOUnJyc0/bs2VPWpQOAX%2BMeQABlJjU1Vfv27cvZr127tipUqKCMjAzdfvvt2rlzp5YuXaqqVasW6X25BxAASoYACMCrssPftm3btGzZMlWvXr3I72FZllJTUxUWFiaPx1MGVQKAfyMAAvCaU6dO6ZZbbtH69eu1YMECRUZG5nytSpUqKl%2B%2BvI3VAYB7EAABeE1iYqLq1q171q8tW7ZMXbp08W5BAOBSBEAAAACXYRQwAACAyxAAAQAAXIYACAAA4DIEQAAAAJchAAIAALgMARAAAMBlCIAAAAAuQwAEAABwGQIgAACAyxAAAQAAXIYACAAA4DIEQAAAAJchAAIAALgMARAAAMBlCIAAAAAuQwAEAABwGQIgAACAyxAAAQAAXIYACAAA4DIEQAAAAJchAAIAALgMARAAAMBlCIAAAAAuQwAEAABwGQIgAACAyxAAAQAAXIYACAAA4DIEQAAAAJchAAIAALgMARAAAMBlCIAAAAAuQwAEAABwGQIgAACAyxAAAQAAXIYACAAA4DIEQAAAAJchAAIAALgMARAAAMBlCIAAAAAuQwAEAABwGQIgAACAyxAAAQAAXIYACAAA4DIEQAAAAJchAAIAALgMARAAAMBlCIAAAAAuQwAEAABwmf8H4aQ%2BjbzYBc8AAAAASUVORK5CYII%3D'}
Genus 2 curve data - 50000.a.200000.1