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g2c_curves • Show schema
{'Lhash': '2144824398837815815', 'abs_disc': 36864, '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]],[3,[1,0,-1]]]', 'bad_primes': [2, 3], 'class': '9216.a', 'cond': 9216, 'disc_sign': 1, 'end_alg': 'Q x Q', 'eqn': '[[0,1,0,1,0,1],[]]', 'g2_inv': "['6436343/36','2859245/288','-10051/64']", 'geom_aut_grp_id': '[8,3]', 'geom_aut_grp_label': '8.3', 'geom_aut_grp_tex': 'D_4', 'geom_end_alg': 'M_2(Q)', 'globally_solvable': 1, 'has_square_sha': True, 'hasse_weil_proved': True, 'igusa_clebsch_inv': "['46','-44','-72','144']", 'igusa_inv': "['92','470','-684','-70957','36864']", 'is_gl2_type': True, 'is_simple_base': False, 'is_simple_geom': False, 'label': '9216.a.36864.1', 'leading_coeff': {'__RealLiteral__': 0, 'data': '1.1726821492513199112852472471443314740427762311261715155', 'prec': 190}, 'locally_solvable': True, 'modell_images': ['2.360.1', '3.1080.10'], 'mw_rank': 0, 'mw_rank_proved': True, 'non_solvable_places': [], 'num_rat_pts': 2, 'num_rat_wpts': 2, 'real_geom_end_alg': 'M_2(R)', 'real_period': {'__RealLiteral__': 0, 'data': '9.3814571940105592902819779772', 'prec': 100}, 'regulator': {'__RealLiteral__': 0, 'data': '1.0', 'prec': 10}, 'root_number': 1, 'st_group': 'J(E_1)', 'st_label': '1.4.E.2.1b', 'st_label_components': [1, 4, 4, 2, 1, 1], 'tamagawa_product': 2, 'torsion_order': 4, 'torsion_subgroup': '[2,2]', 'two_selmer_rank': 2, 'two_torsion_field': ['2.0.3.1', [1, -1, 1], [2, 1], 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]], 'factorsRR_base': ['RR', 'RR'], 'factorsRR_geom': ['M_2(RR)'], 'fod_coeffs': [1, 0, 1], 'fod_label': '2.0.4.1', 'is_simple_base': False, 'is_simple_geom': False, 'label': '9216.a.36864.1', '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], 'J(E_1)'], [['2.0.4.1', [1, 0, 1], [0, 1]], [['1.1.1.1', [0, 1], 1]], ['M_2(RR)'], [4, 0], 'E_1']], 'ring_base': [2, -1], 'ring_geom': [4, 0], 'spl_facs_coeffs': [[[112], [640]], [[112], [-640]]], 'spl_facs_condnorms': [96, 96], 'spl_facs_labels': ['96.a3', '96.b3'], 'spl_fod_coeffs': [0, 1], 'spl_fod_gen': [0, 0], 'spl_fod_label': '1.1.1.1', 'st_group_base': 'J(E_1)', 'st_group_geom': 'E_1'} -
g2c_ratpts • Show schema
{'label': '9216.a.36864.1', 'mw_gens': [[[[1, 1], [-1, 1], [1, 1]], [[0, 1], [0, 1], [0, 1], [0, 1]]], [[[1, 1], [1, 1], [1, 1]], [[0, 1], [0, 1], [0, 1], [0, 1]]]], 'mw_gens_v': True, 'mw_heights': [], 'mw_invs': [2, 2], 'num_rat_pts': 2, 'rat_pts': [[0, 0, 1], [1, 0, 0]], 'rat_pts_v': True} - g2c_galrep • Show schema
- g2c_tamagawa • Show schema
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g2c_plots • Show schema
{'label': '9216.a.36864.1', 'plot': 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ADVUEmJOT/XE/ZWrpQOHPB9JzJSSkw0gS811czhi4mxp14AzkIABIBq4MwZKTtbWrXKBL5Vq6QjR3zfiYoyq3Q9ga9/f6lOHXvqBeBsBEAAsMHp09L69SborVwprV4tHT/u%2B07t2ibkpaZKAwaYffiio%2B2pF0BoIQACQBDk50tr1pjAt2qV9MUXUkGB7zuxsWbe3oAB5urVS6pRw556AYQ2AiAAVIGDB6XMTG/gy86Wzj3BsUkTKSXFG/i6deNoNQDBQQB0GM4CBqofz5YsnrCXmSl9/33Z99q08Qa%2BlBTp8sulsLBgVwsAnAXsWJwFDNinuFj67jvfHr59%2B8q%2B16WLb%2BBr2TL4tQLA%2BdADCAAX4VmwkZlprtWrpdxc33ciI6XevU3QS042W7Jccok99QLAxRAAAeAcR46YBRuewLd%2BvVRY6PtO3bpmha4n8PXta1btAoATEAABuJplSbt2ecNeZqa0cWPZ95o2NUEvOdmEvu7dTa8fADgR//oC4CrFxdK33/oGvr17y753%2BeXewJecLF12GQs2AIQOAiCAkHbihLRunXfu3po1Zk%2B%2B0iIjpYQEb9hLSjJbtABAqCIAAggpBw6YoLd6tQl9WVnmmLXSYmLM/D1P4GP%2BHgC3IQACcCzLMvvtecLe6tXStm1l32vZ0vTqeQIfGy4DcDsCIADHKCiQvvzSN/AdOeL7TliY1LWrb%2BBr1Yr5ewBQGgEQQLV1%2BLB3O5bVq034O/f83Fq1pD59vHP3%2BveX6te3p14AcAoCIIBqwbKk7dt95%2B9t3lz2vSZNTNDz9PAlJEg1agS/XgBwMgKgw3AWMEJFUZGUne17usZPP5V9r0MHb%2B8e27EAQGBwFrBDcRYwnCY3V/r8c2/YW7dOOnnS952aNc1xap6wd%2BWVUqNG9tQLAKGMHkAAVWL3bt/Nlr/91gzzltaggXc4NylJSkyUoqPtqRcA3IQACKDSiovN8Wmlh3Nzcsq%2Bd%2BmlvqtzO3aUwsODXy8AuB0BEIDfTp0yQ7irV0urVpmVunl5vu9EREg9evjO34uLs6deAIAvAiCAizp82LsyNzPTbMdSVOT7Tt26ZgsWT9jr29fcAwBUPwRAAD4sS9q50wS9VasuvB1LXJx3KDc5WbriCnOmLgCg%2BuNf1wHy8ssv69lnn9X%2B/fvVpUsXPf/880pJSTnvu9OnT9eECRPK3D916pSimQGPICspkb77zhv2Vq2S9u4t%2B16nTt7h3JQUqW1btmMBAKciAAbAe%2B%2B9p4kTJ%2Brll19WUlKS/vnPf2r48OHatGmTWrVqdd7vqVevnrZs2eJzj/CHYCgokDZsMEFv1SoztHvsmO87kZFSr14m6HlCH9uxAEDoYB/AAOjbt68SEhL0yiuvnL3XqVMnjR07VlOnTi3z/vTp0zVx4kQdO/dvXT%2BwDyDKKz9fWrtWWrnSBL4vvpBOn/Z9p25dqV8/E/hSUsz8vdq17akXAFD16AGspMLCQm3YsEGPPPKIz/20tDStWbPmgt93/PhxtW7dWsXFxerRo4f%2B8pe/qGfPnhd8v6CgQAWlDkHNO3fJJfBvR46YodyMDBP6srLMNi2lNW7s7d1LSTGrdZm/BwDuwb/yK%2BnQoUMqLi5W06ZNfe43bdpUBw4cOO/3dOzYUdOnT1e3bt2Ul5enF154QUlJSfr666/Vvn37837P1KlTNWXKlIDXD%2Bfbv98EPc/13Xdl32nd2tu7N2CAOV6N%2BXsA4F4EwAAJO%2BdvU8uyytzz6Nevn/r163f2c1JSkhISEvTSSy/pxRdfPO/3PProo5o0adLZz3l5eYqPjw9A5XCanBzTu%2Bfp4du6tew7HTuaoDdggAl9F5iKCgBwKQJgJTVq1EgRERFlevsOHjxYplfwQsLDw5WYmKit5/ub/N%2BioqIUFRVVqVrhPJ4tWTIypBUrzNedO33fCQuTunf3DXxNmthQLADAMQiAlVSzZk316tVLixcv1rXXXnv2/uLFizVmzJhy/QzLspSdna1u3bpVVZlwCMuSduwwYc9z7d7t%2B05EhJSQIA0caAJfcrJUv37wawUAOBcBMAAmTZqk22%2B/Xb1791b//v316quvKicnR/fff78k6Y477lCLFi3OrgieMmWK%2BvXrp/bt2ysvL08vvviisrOzlZ6ebmczYJMdO6Tlyy8c%2BCIjpcREKTXVhL4rr5RiYmwoFAAQMgiAAXDTTTfp8OHDevzxx7V//3517dpV8%2BbNU%2BvWrSVJOTk5Ci914v2xY8d077336sCBA4qNjVXPnj21cuVK9enTx64mIIh27zaBz3Pt2uX7vEYNqU8f38BXp44tpQIAQhT7ADoU%2BwA6x08/ecPesmXStm2%2BzyMjTeAbOFAaNMicp0vgAwBUJXoAgQDLzTWLNZYuNdfGjb7Pw8Ol3r1N2Bs0yJyyUbeuPbUCANyJAAhU0unT0po13sC3fr05X7e07t2lwYPNNWCARKctAMBOBEDATyUl0jffSIsXS0uWmOPVTp3yfad9e2nIEBP4Bg3iHF0AQPVCAATKYe9eadEicy1dKv38s%2B/zZs1M4Bs61Hxlj24AQHVGAATO4%2BRJM4/PE/o2bfJ9XqeOWbQxdKg0bJjUuTNHqwEAnIMA6DDp6elKT09XcXGx3aWEFMsyIW/BAnOtWiUVFHifexZupKWZwNevn1Szpn31AgBQGWwD41BsA1N5eXlmDt/8%2BSb07dnj%2Bzw%2BXrrqKhP6hgyRGja0p04AAAKNHkC4hqeXb948c2VmSmfOeJ9HR5vNl6%2B%2B2lwdOjCsCwAITQRAhLTTp80GzHPmSHPnlj11o317afhwc6WmSrVq2VMnAADBRABEyNm/34S9zz4zQ7wnT3qfRUWZbVlGjDBXu3b21QkAgF0IgHA8yzKnbXz6qTR7trRune/zli2lkSPNNXgwx6wBAEAAhCMVF5vTNz75xFw//uj7PDFRGj1auuYacwoHc/kAAPAiAMIxCgvNJsyzZpnevtKbMUdFmT35xowxoS8uzr46AQCo7giAqNZOnTIbMX/4oZnTl5vrfVa/vjRqlAl9V10l1a1rX50AADgJARDVzunTZl%2B%2B9983oe/4ce%2BzuDhp7FjpuuvMqt0aNeyrEwAApyIAolooKjI9fTNnmuHd/Hzvs/h4adw46frrpf79zakcAACg4giAsE1JidmM%2Bd13pQ8%2BkI4c8T5r2VK64QbpxhulPn0IfQAABBIB0GFC4SzgTZukt94ywS8nx3u/aVMT%2BMaPN2ftEvoAAKganAXsUE47C/jQIWnGDOmNN6QNG7z369Uzw7u33GI2aI6IsK9GAADcgh5AVJkzZ6SFC6X//V%2BzmKOoyNyPjDSncNx2m1nFGx1tb50AALgNARABt3On9K9/SdOnS3v3eu8nJEh33WWGeBs3tqk4AABAAERgnDljzt995RWzmtczseCSS6Tbb5cmTJCuuMLeGgEAgEEARKUcPCi99pr0j39Ie/Z47w8dKt1zj9mkOSrKvvoAAEBZBEBUyFdfSS%2B8YPbtKyw09xo1kn71K%2Bnee6V27eytDwAAXBgBEOVWUiLNmSP99a9SRob3ft%2B%2B0gMPmH37WNABAED1RwDERRUWSm%2B/LT37rPT99%2BZeZKQJfBMnmo2aAQCAcxAAcUGnTpn5fc88413NGxsr3Xef9H/%2BjzmtAwAAOA8BEGWcOmUWdTz9tPTTT%2BZeXJw0aZIJfzEx9tYHAAAqhwCIs4qKzP59Tzwh7dtn7rVuLT3yiNnGhdW8AACEBgKgw1TFWcCWJX30kfToo9K2beZeq1bSn/4k3XmnVLNmwP5RAACgGuAsYIcK1FnAX35pFnKsXm0%2BN2ligt%2B999LjBwBAqKIH0KUOHZL%2B8Acz5GtZUu3a0sMPm4s5fgAAhDYCoMtYlvTWW2ZBx%2BHD5t6tt5oFHy1a2FsbAAAIDgKgi%2BzebY5nW7jQfO7WTXr5ZSk52d66AABAcIXbXQCC4913TeBbuNDM7Zs6VdqwgfAHAIAb0QMY4k6cMMe0vfGG%2Bdy3r/nfHTrYWxcAALAPPYAhbPt2qV8/E/jCw6XHHpMyMwl/AAC4HT2AISojQ7r2WunoUalZM2nmTCk11e6qAABAdUAPYAh6/30pLc2Evz59zFw/wh8AAPAgAIaYN9%2BUxo%2BXCgulceOkFSuk5s3trgoAAFQnBMAQMnOmdNddZq%2B/e%2B%2BV3ntPqlXL7qoAAEB1QwB0mPT0dHXu3FmJiYk%2B9zMypDvuMOHvvvukf/xDioiwqUgAAFCtcRawQ5U%2BCzg3t5569jQne9xwg%2BkJDCfaAwCACyAmOFxJiXTbbSb8JSR4t3wBAAC4EKKCw02bJq1cKdWta1b/MucPAABcDAHQ4Z580nydOlVq187eWgAAgDMwB9ChPHMApVx17lxP33zDog8AAFA%2B9AA6VHGx93//4Q%2BEPwAAUH4EQKfJyZEeeEAlbdpIkhaFX60bI2fZWxMAAHAUhoCdZOtWKTlZOnhQeZLMALBUT5Ief1z6859tLQ8AADgDAdBJxoyRZs%2BWpLIBMDxc2rZNatvWvvoAAIAjRNpdgJNZlqX8/Pyg/LMK9u1TzTlzFPbvz3nnfFVJifTqq9KjjwalHgAAnC4mJkZhYWEXfzEE0QNYCd6VuAAAwGlyc3NVr149u8uwBQGwEsrTA5iYmKj169eX%2B2de6P2CI0dUs3NnhZ06Jcn0/MVL2q1/DwFL0lNPSQ88EJBaAlV3Zd/Ny8tTfHy8du/eXe4/pG5oZ1XW7e/7Tm1nVf3sqv496%2B/7Tm1ndfk97uR2OvXPpr/vV6adbu4BZAi4EsLCwi76ByUiIsKv/7q44Pv16pkz3157zff2vy/Vri3dd595LwC1BKzuAPxsSapXr16V/HyntrMq6/b3fae2s6r/P6yq37P%2Bvu/Udlan3%2BOSM9vp1D%2Bb/r5f1X%2BnhCq2galiD/xCj5zf7z/zjNSrV9n7NWtKb78tNWwYsFoCWnclf7a/3NDOqqzb3/ed2s6q/v%2BwKn%2B2G9pZnX6P%2B6u6tLO6tLGq36/qv1NCFUPATnP6tDRjhnLS31DrDRl6Ovx%2B3b9ukur1am93ZVXCM88y1Odp0M7Q4YY2SrQz1NBO94mYPHnyZLuLgB8iI6WePVUwdqSee%2B5ZLbGWqnGH5urf3%2B7Cqk5ERIQGDhyoyMjQnrFAO0OHG9oo0c5QQzvdhR5Ahyp9FnDTpvW0bZtUt67dVQEAACdgDqDDtW0r/fSTRD8uAAAoLwKgwz39tPn6t79Jq1bZWwsAAHAGAqDDXXWVdNdd5iCQm26S9u2zuyIAAFDdEQBDwEsvSZ07S/v3S6NGSUE6nQ4AADgUATAE1K0rzZ4tNW4sffWVCYEnTthdVfm9/PLLatu2raKjo9WrVy%2Bt%2BoWx7I0bN2rcuHFq06aNwsLC9Pzzzwex0srxp52vvfaaUlJS1KBBAzVo0EBDhw7VunXrglhtxfnTzlmzZql3796qX7%2B%2B6tSpox49euitt94KYrUV408bS5s5c6bCwsI0duzYKq4wMPxp5/Tp0xUWFlbmOn36dBArrhh/fz2PHTumBx54QHFxcYqOjlanTp00b968IFVbcf60c%2BDAgef99Rw5cmQQK64Yf389n3/%2BeXXo0EG1atVSfHy8fvvb3zri922lWXCUv//971anTp2syy%2B/3JJk5ebmnn22fr1l1atnWZJlJSdb1tGjNhZaTjNnzrRq1Khhvfbaa9amTZushx56yKpTp461a9eu876/bt066%2BGHH7ZmzJhhNWvWzPrb3/4W5Iorxt923nLLLVZ6erqVlZVlbd682ZowYYIVGxtr7dmzJ8iV%2B8ffdi5fvtyaNWuWtWnTJmvbtm3W888/b0VERFgLFiwIcuXl528bPXbu3Gm1aNHCSklJscaMGROkaivO33a%2B/vrrVr169az9%2B/f7XNWdv%2B0sKCiwevfubY0YMcLKzMy0du7caa1atcrKzs4OcuX%2B8bedhw8f9vl1/O6776yIiAjr9ddfD27hfvK3nW%2B//bYVFRVlvfPOO9aOHTushQsXWnFxcdbEiRODXHnwEQAdKjc3t0wAtCzL%2Bvxzy4qNNSGwWzfLysmxqcBy6tOnj3X//ff73OvYsaP1yCOPXPR7W7du7ZgAWJl2WpZlnTlzxoqJibHeeOONqigvYCrbTsuyrJ49e1p/%2BtOfAl1awFSkjWfOnLGSkpKsf/3rX9add97piADobztff/11KzY2NhilBZS/7XzllVesSy%2B91CosLAxGeQFT2T%2Bbf/vb36yYmBjr%2BPHjVVFewPjbzgceeMAaPHiwz71JkyZZycnJVVbnbMPAAAAgAElEQVRjdcEQcIjp10/KyJCaNZO%2B/VZKTJRWr7a7qvMrLCzUhg0blJaW5nM/LS1Na9assamqwAtEO0%2BePKmioiI1vMhxf3aqbDsty9LSpUu1ZcsWDRgwoKrKrJSKtvHxxx9X48aNdffdd1d1iQFR0XYeP35crVu3VsuWLXXNNdcoKyurqkutlIq0c/bs2erfv78eeOABNW3aVF27dtVTTz2l4uLiYJRcIYH4d9C0adM0fvx41alTpypKDIiKtDM5OVkbNmw4O8Xmxx9/1Lx58xwx1F1Z7t4GO0R17y598YWZC/jNN9LAgdKzz0oPPSSFhdldndehQ4dUXFyspk2b%2Btxv2rSpDhw4YFNVgReIdj7yyCNq0aKFhg4dWhUlBkRF25mbm6sWLVqooKBAERERevnllzVs2LCqLrdCKtLG1atXa9q0acrOzg5GiQFRkXZ27NhR06dPV7du3ZSXl6cXXnhBSUlJ%2Bvrrr9W%2BffU8qrIi7fzxxx%2B1bNky3XrrrZo3b562bt2qBx54QGfOnNF//dd/BaNsv1X230Hr1q3Td999p2nTplVViQFRkXaOHz9eP//8s5KTk2VZls6cOaNf//rXeuSRR4JRsq0IgCGqVSvT83f33dL770u//a20dKk0bZrUpInd1fkKOyeVWpZV5l4oqGg7n3nmGc2YMUMrVqxQdHR0VZUXMP62MyYmRtnZ2Tp%2B/LiWLl2qSZMm6dJLL9XAgQOruNKKK28b8/Pzddttt%2Bm1115To0aNglVewPjza9mvXz/169fv7OekpCQlJCTopZde0osvvlildVaWP%2B0sKSlRkyZN9OqrryoiIkK9evXSvn379Oyzz1bbAOhR0X8HTZs2TV27dlWfPn2qqrSA8qedK1as0JNPPqmXX35Zffv21bZt2/TQQw8pLi5Of/7zn4NRrm0IgCGsbl1p5kwpJUX6v/9XmjNH6tpV%2Bsc/pOuus7s6qVGjRoqIiCjzX2YHDx4s819wTlaZdj733HN66qmntGTJEl1xxRVVWWalVbSd4eHhuuyyyyRJPXr00ObNmzV16tRqGQD9beP27du1c%2BdOjRo16uy9kpISSVJkZKS2bNmidu3aVW3RFRCIP5vh4eFKTEzU1q1bq6LEgKhIO%2BPi4lSjRg1FREScvdepUycdOHBAhYWFqlmzZpXWXBGV%2BfU8efKkZs6cqccff7wqSwyIirTzz3/%2Bs26//Xb9x3/8hySpW7duOnHihO6991798Y9/VHh46M6UC92WQZIZ8n3wQWn9eqlbN%2Bnnn6Vx46Trr7d/0%2BiaNWuqV69eWrx4sc/9xYsX68orr7SpqsCraDufffZZ/eUvf9GCBQvUu3fvqi6z0gL162lZlgoKCgJdXkD428aOHTvq22%2B/VXZ29tlr9OjRGjRokLKzsxUfHx%2Bs0v0SiF9Ly7KUnZ2tuLi4qigxICrSzqSkJG3btu1skJekH374QXFxcdUy/EmV%2B/V8//33VVBQoNtuu60qSwyIirTz5MmTZUJeRESELLNItspqrRbsWHmCyrvQKuBfcvq0Zf3hD5YVEWFWCderZ1nPP29ZRUVVWOhFeJbsT5s2zdq0aZM1ceJEq06dOtbOnTsty7Ks22%2B/3Wf1VkFBgZWVlWVlZWVZcXFx1sMPP2xlZWVZW7dutasJ5eJvO59%2B%2BmmrZs2a1ocffuizFUN%2Bfr5dTSgXf9v51FNPWYsWLbK2b99ubd682fqf//kfKzIy0nrttdfsasJF%2BdvGczllFbC/7Zw8ebK1YMECa/v27VZWVpY1YcIEKzIy0vriiy/sakK5%2BNvOnJwcq27dutaDDz5obdmyxZozZ47VpEkT64knnrCrCeVS0d%2B3ycnJ1k033RTscivM33Y%2B9thjVkxMjDVjxgzrxx9/tBYtWmS1a9fOuvHGG%2B1qQtAQAB2qIgHQIyvLsvr0MSFQsqyuXS1r8eIqKLKc0tPTrdatW1s1a9a0EhISrIyMjLPPUlNTrTvvvPPs5x07dliSylypqanBL9xP/rSzdevW523nY489FvzC/eRPO//4xz9al112mRUdHW01aNDA6t%2B/vzVz5kwbqvaPP208l1MCoGX5186JEydarVq1smrWrGk1btzYSktLs9asWWND1f7z99dzzZo1Vt%2B%2Bfa2oqCjr0ksvtZ588knrzJkzQa7af/62c8uWLZYka9GiRUGutHL8aWdRUZE1efJkq127dlZ0dLQVHx9v/eY3v7GOOmEj3UoKs6xQ7%2BMMTXl5eYqNjVVubq7q1avn9/cXF0v/%2Bpf0hz9IR46YeyNGSM88I3XpEuBiAQBAtcIcQJeKiJDuu0/aulX6z/%2BUIiOlefOkK66Q7rxT2rHD7goBAEBVIQC6XMOG0gsvSJs2mcUhJSXSm29KHTpI998v7dpld4UAACDQCIAOk56ers6dOysxMTGgP7d9e%2BnDD80G0sOGSUVF0j//ae7fc4%2B0bVtA/3EAAMBGzAF0qMrOAbyYVaukyZOlZcvM5/Bw6YYbpN//XurZM%2BD/OAAAEET0AOK8UlLMySGrV0vDh5uh4ffekxISpKFDzXzBUttgAQAAByEA4hddeaUJe1lZ0i23mMUjS5dKI0dKnTtLL78sHT9ud5UAAMAfDAE7VFUPAV/Irl3Siy9Kr70m5eebe7Gx0l13Sb/%2BtVk8AgAAqjcCoEPZFQA98vOl11%2BX/v53s5WMx%2BDBZvXwmDFSNT0VCQAA1yMAOpTdAdCjpERatMgMBc%2Bd650X2KSJ2U/w7rvpFQQAoLohADpUdQmApe3aZU4XmTZN2r/fez85WfrVr8wq4rp17asPAAAYBECHqo4B0KOoyPQGTpvmu1q4dm3p%2ButNz%2BDAgWZrGQAAEHwEQIeqzgGwtL17zckir7/uO1ewZUvp1lul226Tuna1rz4AANyIAOhQTgmAHpYlrV0rvfGG2U/w2DHvs27dzBYzN98stW5tX40AALgFAdChnBYASzt92gwRv/22%2BVpU5H3Wv780frwZKm7e3L4aAQAIZQRAh0lPT1d6erqKi4v1ww8/ODIAlnb0qDmDeMYMacUK01MoSWFh5jSSG26Qxo2T4uJsLRMAgJBCAHQoJ/cAXsj%2B/dL775sh4s8/994PC5OSkkyv4HXXSfHx9tUIAEAoIAA6VCgGwNJyckzP4AcfmLmDpfXpI117rbnYYxAAAP8RAB0q1ANgabt3S7NmSR99JGVmeoeJJalTJ2nsWHPySGIiW8sAAFAeBECHclMALO3AAenTT00gXLZMOnPG%2BywuTho1Sho92hxJV6uWfXUCAFCdEQAdyq0BsLTcXLPR9CefSPPnm/OJPWrXloYONYFw5EgWkQAAUBoB0KEIgL4KCswq4k8/lT77TNqzx/d5r17SNddII0ZIvXszVAwAcDcCoEMRAC/MsqTsbGnOHBMG16/3fd6kiTR8uLnS0qQGDeypEwAAuxAAHYoAWH4HDpih4nnzpEWLfIeKw8PN5tPDh0tXXy317EnvIAAg9BEAHYoAWDGFhdLq1d5AuGmT7/MmTUyv4FVXScOGSU2b2lMnAABViQDoUATAwNi1S1qwwFxLl/r2DkpSjx4mDKalmc2oo6LsqRMAgEAiADoUATDwCgulNWukhQvNlZXl%2B7x2bWnAANMzOGyY1LWrOaUEAACnIQA6TKidBVydHTwoLV5swuDixWYuYWnNmpmtZjxXixb21AkAgL8IgA5FD2BwWZb07bcmCC5ZImVkSKdO%2Bb7TsaM0ZIi5Bg5kdTEAoPoiADoUAdBep0%2Bb4eIlS8z15Ze%2BR9SFh0sJCSYMDh4sJSebIWQAAKoDAqBDEQCrl6NHzUbUS5aYxSRbtvg%2Br1HDbDczaJAJhH37sqAEAGAfAqBDEQCrt717zVnFy5aZQLh7t%2B/zWrXMquJBg8xwcWKiCYkAAAQDAdChCIDOYVnS9u3eQLh8uVlgUlqdOmaYeOBAc/XqRSAEAFQdAqBDEQCdy7LMBtTLl5srI0M6fNj3ndKBMDXVnF9MIAQABAqHXlWSZVmaPHmymjdvrlq1amngwIHauHHjL37P5MmTFRYW5nM1a9YsSBXDbmFhUpcu0oMPSh99ZHoDv/5aev55aexYs3r4xAmz/cyjj0pXXinVr282o37ySSkzUyoosLsVAAAni7S7AKd75pln9Ne//lXTp0/X5ZdfrieeeELDhg3Tli1bFBMTc8Hv69Kli5YsWXL2c0RERDDKRTUUHi5dcYW5HnpIKikxW86sWGF6B1euND2EixebS5Kio82iktRUszl1376sMgYAlB9DwJVgWZaaN2%2BuiRMn6ve//70kqaCgQE2bNtXTTz%2Bt%2B%2B6777zfN3nyZH3yySfKzs6u8D%2BbIWD3KCmRNm40YdBz/fyz7zs1apiFJJ5AeOWVEr8tAAAXwhBwJezYsUMHDhxQWlra2XtRUVFKTU3VmjVrfvF7t27dqubNm6tt27YaP368fvzxx198v6CgQHl5eT4X3CE8XOrWzQwZf/CB9NNPZg7hK69I48dLzZtLRUVmX8KpU6Xhw80wcu/e0m9/K338sXTokN2tAABUJ/QAVsKaNWuUlJSkvXv3qnnz5mfv33vvvdq1a5cWLlx43u%2BbP3%2B%2BTp48qcsvv1w//fSTnnjiCX3//ffauHGjLrnkkvN%2Bz%2BTJkzVlypQy9%2BkBhGVJP/5ohoo91/n%2Be6JjR9M7mJJirtatg18rAKB6IAD64Z133vEZ1p07d64GDhyoffv2KS4u7uz9e%2B65R7t379aCBQvK9XNPnDihdu3a6Xe/%2B50mTZp03ncKCgpUUGrmf15enuLj4wmAOK89e6RVq8y1cqUZQj5XfLw3ECYnS506md5GAEDoYxGIH0aPHq2%2Bffue/ewJZAcOHPAJgAcPHlTTpk3L/XPr1Kmjbt26aevWrRd8JyoqSlEcHYFyatlSuvlmc0lmEUlmpjcQfvWV2Zz6nXfMJUkNG5rNqT09hAkJUs2a9rUBAFB1CIB%2BiImJ8VnZa1mWmjVrpsWLF6tnz56SpMLCQmVkZOjpp58u988tKCjQ5s2blZKSEvCaAUm65BJpzBhzSdLx49LatSYQZmZKn38uHTkiffaZuSRzWknfvqZ3MCVF6tePhSUAECoYAq6kp59%2BWlOnTtXrr7%2Bu9u3b66mnntKKFSt8toEZMmSIrr32Wj344IOSpIcfflijRo1Sq1atdPDgQT3xxBPKyMjQt99%2Bq9blnJjFKmAEUlGR6RX0BMLMzLKbU4eHS927m0DouUpNfQUAOAg9gJX0u9/9TqdOndJvfvMbHT16VH379tWiRYt8egq3b9%2BuQ6WWYe7Zs0c333yzDh06pMaNG6tfv35au3ZtucMfEGg1apjevr59pYcfNlvPfP%2B9NwxmZko7dkhZWeZ66SXzfW3b%2BgbCjh2ZRwgATkAPoEPRA4hg27vXNxB%2B/bVZgVyaZx5hcrL52ru3xNRVAKh%2BCIAORQCE3fLyzNxBTyD84gvp1Cnfd6KiTAj09BBeeaUJiQAAexEAHYoAiOrGM49w9WoTCFevNuccn6tzZ28PYXKyGUYOCwt%2BvQDgZgRAhyIAorqzLGnrVm8gzMyUfvih7HtxcaZn0NNL2L27mZMIAKg6BECHIgDCiX7%2B2QRCz/Xll6bnsLTatc2WM0lJ5urfn%2B1nACDQCIAORQBEKDh1Slq/3jtkvGaNdOyY7zvh4dIVV3gDYXKyOcUEAFBxBECHSU9PV3p6uoqLi/XDDz8QABFSSkqkzZu9Q8arV5vtZ84VH%2B87j7BrVykiIvj1AoBTEQAdih5AuMW%2Bfd4h48xMKTtbKi72fadePTNU7Okl7NtXqlPHnnoBwAkIgA5FAIRbHT9utpzxBMK1a6X8fN93IiOlnj199yRs1syeegGgOiIAOhQBEDCKi6VvvvFdbbx3b9n32rXznmuclCR16MD2MwDciwDoUARA4PwsS8rJ8Z1H%2BN13ZU8tadTId/uZXr2kmjXtqRkAgo0A6FAEQKD8jh3zPbVk3Trp9Gnfd6KjpT59fE8tiY21p14AqGoEQIciAAIVV1hoTi0p3Ut46JDvO2FhUrduZsjYEwpbtrSnXgAINAKgQxEAgcCxLGnLFm8gzMyUtm8v%2B16bNt4wmJIiderEPEIAzkQAdCgCIFC1DhzwDYRZWWafwtIuucQsKPH0EvbqxTF2AJyBAOhQBEAguPLzzZYzq1Z5t585dcr3nVq1zDF2KSnm6tdPqlvXnnoB4JcQAB2KAAjYq/Q8Qk8oPHLE952ICLMf4YAB3l7CRo3sqRcASiMAOhQBEKheSkqk7783YdBz5eSUfa9zZ28P4YABnGsMwB4EQIfhLGDAOXJyTBBcudJ83by57Dtt2nh7CAcMkNq3Z2EJgKpHAHQoegAB5zl0yAwVr1xprvMtLGna1ATB1FTztUsXKTzcnnoBhC4CoEMRAAHny883G1RnZJhAuG6dmVtYWoMG3t7B1FSpRw9z1jEAVAYB0KEIgEDoOX3ahMCVK00o/Pxz6cQJ33diYsxiEk8g7N2brWcA%2BI8A6FAEQCD0FRWZlcaeIeNVq6TcXN93atc2x9alpkoDB0qJiVJUlC3lAnAQAqBDEQAB9ykulr75xvQOZmSYQHj4sO870dG%2BgbBPH3MPAEojADoUARBASYm0caN3DmFGhnTwoO87UVHeQDhoEIEQgEEAdCgCIIBzWZbZaiYjQ1qxwnz96Sffd6Kjpf79Te%2BgJxAyZAy4DwHQoQiAAC7GsqQtW0wY9FznBsJatUwP4aBB5kpMZFEJ4AYEQIciAALwl2WZ00oyMqTly00gPHfIuE4ds8rYEwgTEth2BghFBECHIgACqCzLkjZtMkHQEwjPXVRSr56ZPzh4sLm6dmVjaiAUEAAdigAIINBKSqTvvjNhcNky01N47rYzjRqZnkFPIOToOsCZCIAOw1nAAIKluNgcV%2BcJhKtWld2YumVLacgQEwaHDJFatLCnVgD%2BIQA6FD2AAIKtqMicVLJsmbR0qTmp5Nyj6zp0MEFwyBDTU9iggT21AvhlBECHIgACsNvJk9Lq1d5AuGGDGUb2CA%2BXevXyBsLkZPYgBKoLAqBDEQABVDdHj5p5g0uXSkuWmBXHpUVHmxA4dKg0bJjUowcLSgC7EAAdigAIoLrbu9cbBpcskfbv931%2BySWmZ9ATCNu0saVMwJUIgA5FAATgJJ5TSjxhcPly6fhx33cuu0xKSzNhcNAgKTbWnloBNyAAOhQBEICTeRaULF5sAuHatWbVsUdEhNSvnwmDaWnmhBI2pAYChwDoUARAAKEkL8/0Ci5eLC1aJG3d6vu8fn0zXJyWZi6Gi4HKIQA6FAEQQCjbtcsEwUWLzDzCo0d9n19%2BuQmCV19tTiqpW9eeOgGnIgA6FAEQgFsUF0tffiktXGgC4bnDxTVrmtXFV19trq5dOZ0EuBgCoEMRAAG4VW6u6RVctMiEwp07fZ83by5ddZUJg8OGsRk1cD4EQIfhKDgA8LIsM19wwQJzrVghnTrlfe5ZTHL11dLw4VLPnuw9CEgEQMeiBxAAyjp9Wlq50hsIN2/2fd6kiTcMpqVJDRvaUydgNwKgQxEAAeDidu0yQXD%2BfDNsXHrvwfBw0zs4YoS5evRg7iDcgwDoUARAAPBPYaGUmWnC4Lx50qZNvs/j4kwQHDnSnE4SE2NPnUAwEAAdigAIAJWTk2PC4Ny5pnfw5Envsxo1pAEDTBgcOdJsOwOEEgKgQxEAASBwPHMH580zgXDbNt/nl10mjRplwmBKitl6BnAyAqBDEQABoOr88IMJgnPnmmBYVOR9FhNjtpkZNcosJmnc2L46gYoiADoUARAAgiMvzxxR5wmEBw96n4WFmYUko0ebQNi5MwtJ4AwEQBvMmjVL//znP7VhwwYdPnxYWVlZ6tGjh18/gwAIAMFXUmJOJfnsM2nOHCk72/d527YmCI4ebeYQ1qhhT53AxRAAbfDWW29px44dat68ue655x4CIAA41O7dplfws8/MQpKCAu%2Bz2FgzRDx6tPlav759dQLnIgDaaOfOnWrbti0BEABCwPHjZqj4s8/KDhVHRkqpqdKYMSYQtm5tX52ARAC0lT8BsKCgQAWl/tMyLy9P8fHxBEAAqIaKi6V166TZs6VPPy17IkmPHiYMjhnDBtSwByciOsTUqVMVGxt79oqPj7e7JADABURESP37S1Onmg2nf/hBeu45s4VMeLiZOzhlipSQYOYNTpxozjE%2Bc8buyuEW9ABWsXfeeUf33Xff2c/z589XSkqKJHoAAcCNDh0yC0g%2B/VRauFA6dcr7rGFDs4jk2mvNWcW1atlXJ0IbAbCK5efn66effjr7uUWLFqr17z/RzAEEAHc7eVJatEj65BMTCg8f9j6rXdssHrn2Wumaa8yiEiBQCIA2IgACADzOnDFnFX/8sQmEOTneZzVqSIMHS%2BPGmXmDTZrYVydCAwHQBkeOHFFOTo727dunkSNHaubMmerQoYOaNWumZs2aletnEAABIHRZlvTVVyYMzprlu4gkPFxKTjZh8NprJaaEoyIIgDaYPn26JkyYUOb%2BY489psmTJ5frZxAAAcA9vv/ehMGPPpI2bPB91revCYPjxkmXXmpPfXAeAqBDEQABwJ127TK9grNmSatXm95Cj549peuvN9fll9tXI6o/AqBDEQABAAcOmJ7BDz%2BUMjLM/oMe3bpJN9xgro4d7asR1RMB0KEIgACA0g4dMotHPvzQHEtXek/Brl29YbBTJ/tqRPVBAHQoAiAA4EKOHDH7DH7wgbRkiVRU5H3Wtat0443m6tDBvhphLwKgQxEAAQDlcfSoNwwuXuwbBq%2B4QrrpJhMGL7vMvhoRfARAhyIAAgD8dfSoGSb2hMHSw8S9ennDYOvW9tWI4CAAOkx6errS09NVXFysH374gQAIAKiQI0fMApL33pOWLfNdQNK/vzcMxsXZVyOqDgHQoegBBAAEys8/mz0G33vPrCb2JIOwMGngQOnmm6XrrpMuucTWMhFABECHIgACAKrCvn1miHjmTGntWu/9yEjp6qtNGBw9Wqpb174aUXkEQIciAAIAqtrOnSYIzpwpff21937t2iYE3nKLdNVVUs2atpWICiIAOhQBEAAQTJs3SzNmSO%2B%2BK23f7r3fsKHZX/CWW8wZxeHh9tWI8iMAOhQBEABgB8uSvvxSeucdM2fwwAHvs1atzBDxbbeZ/QZRfREAHYoACACwW3GxtHy56RX86CMpL8/77IorTBC85RapRQv7asT5EQAdigAIAKhOTp2S5s6V3n5bmjfPu%2BF0WJg0eLAJg%2BPGSTEx9tYJgwDoUARAAEB1deSIWUn89ttSZqb3fq1a0tix0h13SEOHmpXFsAcB0KEIgAAAJ9ixw8wXfOst6YcfvPebNTPDw3fcIXXvbl99bkUAdCgCIADASSxLWr/eBMEZM6TDh73Punc3QfDWW6WmTe2r0U0IgA5FAAQAOFVRkTR/vvTGG9KcOVJhobkfEWE2m77zTmnUKCk62t46QxkB0GE4CxgAEEqOHDHbybzxhvTFF977DRqYLWXuukvq3dssJkHgEAAdih5AAECo%2Bf576c03zTDxnj3e%2B507myB4%2B%2B1m7iAqjwDoUARAAECoKi6Wli41vYKzZkmnT5v7ERHSiBHShAnSyJEcQVcZBECHIgACANwgN9cMEb/%2BurR2rfd%2Bo0amR/Duu6UuXeyrz6kIgA5FAAQAuM3335sg%2BOabvkfQJSaaIHjzzRJ/JZYPAdChCIAAALc6c0ZasED63/%2BVPvvMfJbMRtP/7/9JU6bYW58ThNtdAAAAgD8iI6VrrjHzA/fulZ57TurUyRxHx1Fz5UMPoEPRAwgAgJdlmTmC7dub%2BYH4ZZzCBwAAHC8sTOrf3%2B4qnIMhYAAAAJchAAIAALgMARAAAMBlCIAOk56ers6dOysxMdHuUgAAgEOxCtihWAUMAAAqih5AAAAAlyEAAgAAuAwBEAAAwGUIgAAAAC5DAAQAAHAZAiAAAIDLEAABAABchgAIAADgMgRAAAAAlyEAOgxHwQEAgMriKDiH4ig4AABQUfQAAgAAuAwBEAAAwGUIgAAAAC5DAAQAAHAZAiAAAIDLEAABAABchgBYSbNmzdJVV12lRo0aKSwsTNnZ2Rf9nunTpyssLKzMdfr06SBUDAAA3I4AWEknTpxQUlKS/vu//9uv76tXr57279/vc0VHR1dRlQAAAF6RdhfgdLfffrskaefOnX59X1hYmJo1a1YFFQEAAPwyegBtcvz4cbVu3VotW7bUNddco6ysrF98v6CgQHl5eT4XAABARRAAbdCxY0dNnz5ds2fP1owZMxQdHa2kpCRt3br1gt8zdepUxcbGnr3i4%2BODWDEAAAglnAXsh3feeUf33Xff2c/z589XSkqKJDME3LZtW2VlZalHjx5%2B/dySkhIlJCRowIABevHFF8/7TkFBgQoKCs5%2BzsvLU3x8PGcBAwAAvzEH0A%2BjR49W3759z35u0aJFQH5ueHi4EhMTf7EHMCoqSlFRUQH55wEAAHcjAPohJiZGMTExAf%2B5lmUpOztb3bp1C/jPBgAAOBcBsJKOHDminJwc7du3T5K0ZcsWSVKzZs3OrvK944471KJFC02dOlWSNGXKFPXr10/t27dXXl6eXnzxRWVnZys9Pd2eRgAAAFdhEUglzZ49Wz179tTIkSMlSePHj1fPnj31j3/84%2Bw7OTk52r9//9nPx44d07333qtOnTopLS1Ne/fu1cqVK9WnT5%2Bg1w8AANyHRSAOlZeXp9jYWBaBAAAAv9EDCAAA4DIEQAAAAJdhCNihLMtSfn6%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%3D%3D'}
Genus 2 curve data - 9216.a.36864.1