-
g2c_curves • Show schema
{'Lhash': '1179899777022999227', 'abs_disc': 458752, 'analytic_rank': 0, 'analytic_rank_proved': True, 'analytic_sha': 2, 'aut_grp_id': '[4,2]', 'aut_grp_label': '4.2', 'aut_grp_tex': 'C_2^2', 'bad_lfactors': '[[2,[1]],[7,[1,1,7,7]]]', 'bad_primes': [2, 7], 'class': '3584.c', 'cond': 3584, 'disc_sign': 1, 'end_alg': 'Q x Q', 'eqn': '[[-4,-12,-21,-22,-13,-4,1],[0,0,0,1]]', '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': 0, 'has_square_sha': False, 'hasse_weil_proved': True, 'igusa_clebsch_inv': "['828','16635','5308452','56']", 'igusa_inv': "['3312','279616','-54648832','-64795509760','458752']", 'is_gl2_type': True, 'is_simple_base': False, 'is_simple_geom': False, 'label': '3584.c.458752.1', 'leading_coeff': {'__RealLiteral__': 0, 'data': '0.8688785795393727751338729339821103719580913693941874576', 'prec': 190}, 'locally_solvable': False, 'modell_images': ['2.45.1', '3.2160.9'], 'mw_rank': 0, 'mw_rank_proved': True, 'non_solvable_places': [2], 'num_rat_pts': 0, 'num_rat_wpts': 0, 'real_geom_end_alg': 'C x R', 'real_period': {'__RealLiteral__': 0, 'data': '3.4755143181574911005354917359', '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': 2, 'torsion_order': 4, 'torsion_subgroup': '[4]', 'two_selmer_rank': 2, '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': '3584.c.458752.1', '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': [[[528], [-12096]], [[505], [11341]]], 'spl_facs_condnorms': [32, 112], 'spl_facs_labels': ['32.a2', '112.c4'], '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': '3584.c.458752.1', 'mw_gens': [[[[1, 1], [1, 1], [1, 1]], [[0, 1], [0, 1], [0, 1], [0, 1]]]], 'mw_gens_v': True, 'mw_heights': [], 'mw_invs': [4], 'num_rat_pts': 0, 'rat_pts': [], 'rat_pts_v': True} - g2c_galrep • Show schema
- g2c_tamagawa • Show schema
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g2c_plots • Show schema
{'label': '3584.c.458752.1', 'plot': 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CDgI%2Bn7k8u3mztGWL2bZuNWv57t37yz8bESFdcYWZZPGb30jR0QX6y1/u0ZIl/1Tz5hFq0MDZzZkr0%2B7du/2XYBo1amR1OY7DLGxr8f1bK5Df/7ffmsD3zTemv%2Bvzz5tRQIdeKQ1ZRINK5vVKX38tbdx4avvmG7OG4vnUr2/W623a1Gynr8BRv37ZP5SFhS4VF7fQDTeEsf5iJXP/9wt388Vbwu1266mnnuL7twjfv7UC9f3Pmyfde6/p5hATI739tvT73weoSAQVRgArwbx5pjt6dra5V%2B9cqlQx4a5FC7OVrr171VXmvjsEP0ZAANjVyZPS6NHSP/5hHt9wg/TWWyYEIjQxAlgJvv1Weu%2B9U4/j4qRWraSWLaXERLPFx4fuEmkAgOCVlyf17y8tX24ejxxp%2Bv1x%2B1Bo4z9vJejZ00ydv/Za6ZprWCcRABAc1q419/vt3m3adL3%2ButS3r9VVoTJwCRgIEC4BA7CT6dOlIUPMOu7x8dL8%2BeYWJDgDyzaHiBMnTuiJJ55Qy5YtFRERodjYWA0YMEB7f20aMWBzY8eOVVJSkiIjIxUVFaU%2Bffro22%2B/tbosRxo7dqxcLpeGDx9udSmOsWfPHt19992qV6%2BeatSooWuvvVbr16//xZ8pKpIeekgaNMgc9%2BljRgIJf85CAAwRx48f14YNG/TnP/9ZGzZs0LvvvqvvvvtOKSkpVpcW8jIyMpSQkKCkpCSrS3Gkzz77TEOHDlVWVpaWLl2qkydPqlu3bjp27JjVpTnKunXrNHXqVLVq1crqUhzj0KFD6tixo6pVq6aPPvpImzdv1gsvvKDatWuf92f275duvll69VXTQeJvfzMTFblo4TxcAg5h69atU9u2bbVz5041btzY6nJCHpeAg8OBAwcUFRWlzz77TDfccIPV5TjC0aNHdf311%2BuVV17R3/72N1177bV68cUXrS4r5D355JP64osvtGLFigs6f8MG6dZbzf1%2BtWqZJs89e1ZwkQhajACGMK/XK5fL9Yv/GgRCjdfrlSTVZbZVpRk6dKh69uypLl26WF2KoyxYsEBt2rTR7bffrqioKF133XWaNm3aOc996y2pY0cT/uLjzSVfwp%2BzEQBDVEFBgZ588kmlpqYyGgXH8Pl8GjFihH73u98psaIWLEUZc%2BfO1YYNGzR27FirS3GcH3/8UZMnT1azZs308ccf68EHH9SwYcM0a9Ys/zk%2Bn/T006bNS0GBdMst0po1JgTC2QiANpWZmamaNWv6t9MvAZw4cUL9%2B/dXSUmJXnnlFQurBCrXww8/rK%2B//lpvvvmm1aU4Qk5Ojh599FHNmTNHl9HItNKVlJTo%2Buuv15gxY3Tddddp8ODBSk9P1%2BTJkyVJP/8s3Xmn9Ne/mvNHjpQ%2B%2BEDyeCwsGkGDPoA2lZKSonbt2vkfN2zYUJIJf/369dP27dv1ySefMPoHx3jkkUe0YMECff7556zFXEnWr1%2BvvLw8tW7d2v9ccXGxPv/8c02aNEmFhYWqWrWqhRWGtgYNGighIaHMcy1atNC8efN04ICZ3btqlWnoPGWKdN99FhWKoEQAtKnIyEhFRkaWea40/G3btk3Lly9XvXr1LKoOqDw%2Bn0%2BPPPKI5s%2Bfr08//VRXXHGF1SU5RufOnbVx48Yyz917771q3ry5nnjiCcJfBevYseNZLY%2B%2B%2B%2B47RUV1UIcO0vffS7VrS%2B%2B%2BK910k0VFImgRAEPEyZMn1bdvX23YsEELFy5UcXGxcnNzJZmb4atXr25xhUDFGDp0qN544w29//77ioyM9P%2B%2B93g8Cg8Pt7i60BYZGXnWvZYRERGqV68e92BWgscee0wdOnTQmDFj1K9fP61du1aTJ38pt3up8vOlJk2kDz%2Bkvx/OjTYwIWLHjh3nHflYvny5brzxxsotyIFoA2MNl8t1zudff/11DRw4sHKLgW688UbawFSihQsXatSoUdq2bZuiou5SXt6rKiyspuuvlxYtkmJirK4QwYoACAQIARCAVebNMxM%2BTpyQunQxl33PuEsIKINZwAAA2NicOVK/fib83X67tHAh4Q%2B/jgAIAIBNzZghDRgglZRI994rvfmm5HZbXRXsgAAIlBNrAQOwwqxZprWLzyc99JD02msSE69xobgHEAgQ7gEEUFneeces7lFSIg0ZIk2aJJ1nPhRwTowAAgBgI0uXSnfdZcLfoEHSxImEP1w8AiAAADbx1VfSn/5kJnz06ye9%2BqpUhb/JcQn4bQMAgA3s2SP16iUdPSrdfLO5B5B7/nCpCIAAAAS5ggLpj3%2BU9u6VEhJMnz9m%2B6I8CIAAAAS5hx%2BW1q2T6taVPvhA8nisrgh2RwAEACCIzZkjTZ9uJnrMnStdeaXVFSEUEAABAAhSO3aYNi%2BS9NRTUteulpaDEEIABAAgCPl8ptHzkSNSx47S//6v1RUhlBAAAQAIQjNmSMuXS%2BHh0syZzPhFYBEAgXJiKTgAgXb4sPTEE%2Bb4r3%2BVfvtba%2BtB6GEpOCBAWAoOQKA8%2BaT03HNS8%2BbS119L1apZXRFCDSOAAAAEkdxc6eWXzfHzzxP%2BUDEIgAAABJEJE6Sff5batzcrfwAVgQAIAECQOHZMmjLFHI8ebXr/ARWBAAgAQJCYO1fyeqWmTaWePa2uBqGMAAgAQJCYOdPsBw2SqvA3NCoQv70AAAgC%2B/ZJK1aY47vusrYWhD4CIAAAQWDRIrNv21Zq1MjaWhD6CIAAAASBZcvM/pZbrK0DzkAABAAgCKxcafY33mhpGXAIAiBQTiwFB6C89u%2BX9uwxbV/atLG6GjgBS8EBAcJScAAu1SefSJ07m/Yv27ZZXQ2cgBFAAAAs9sMPZn/VVdbWAecgAAIAYLGcHLOPi7O2DjgHARAAAIsdOGD2UVHW1gHnIAACAGCxI0fM3uOxtg44BwEQAACLFRSY/WWXWVsHnIMACNt799131b17d9WvX18ul0vZ2dlnnVNYWKhHHnlE9evXV0REhFJSUrR79%2B4y5%2BzatUu9e/dWRESE6tevr2HDhqmoqKiyPgYAyOWyugI4BQEQtnfs2DF17NhRzz777HnPGT58uObPn6%2B5c%2Bdq5cqVOnr0qHr16qXi4mJJUnFxsXr27Kljx45p5cqVmjt3rubNm6eRI0dW1scA4GDVq5s9/%2BZEZQmzugCgvNLS0iRJO3bsOOfrXq9X06dP1%2BzZs9WlSxdJ0pw5cxQXF6dly5ape/fuWrJkiTZv3qycnBzFxsZKkl544QUNHDhQf//73%2BnrB6BCRUSY/dGj1tYB52AEECFv/fr1OnHihLp16%2BZ/LjY2VomJiVq1apUkafXq1UpMTPSHP0nq3r27CgsLtX79%2BkqvGYCz1Klj9gcPWlsHnIMRQIS83NxcVa9eXXVK/w/7X9HR0crNzfWfEx0dXeb1OnXqqHr16v5zzlRYWKjCwkL/4/z8/ABXDsApStu/nOd/N0DAMQIIW8nMzFTNmjX924oVKy75vXw%2Bn1yn3XHtOsfd12eec7qxY8fK4/H4tzg6uAK4RI0amf0Zc9OACkMAhK2kpKQoOzvbv7W5gFXTY2JiVFRUpEOHDpV5Pi8vzz/qFxMTc9ZI36FDh3TixImzRgZLjRo1Sl6v17/llLbyB4CLdMUVZv/jj9bWAecgAMJWIiMj1bRpU/8WHh7%2Bqz/TunVrVatWTUuXLvU/t2/fPm3atEkdOnSQJCUnJ2vTpk3at2%2Bf/5wlS5bI7XardevW53xft9utWrVqldkA4FI0a2b2e/YwEQSVg3sAYXsHDx7Url27tHfvXknSt99%2BK8mM6sXExMjj8ej%2B%2B%2B/XyJEjVa9ePdWtW1ePP/64WrZs6Z8V3K1bNyUkJCgtLU3/%2BMc/dPDgQT3%2B%2BONKT08n2AGocHXrStHR0v790ubNUtu2VleEUMcIIGxvwYIFuu6669SzZ09JUv/%2B/XXdddfp1Vdf9Z8zYcIE9enTR/369VPHjh1Vo0YNffDBB6pataokqWrVqlq0aJEuu%2BwydezYUf369VOfPn00btw4Sz4TAOdp1crsz9HLHgg4l8/n81ldBBAK8vPz5fF45PV6GTUEcNGefFJ67jkpPV2aOtXqahDqGAEEACAIlF72XbPG2jrgDARAAACCQHKy2W/cKB0%2BbG0tCH0EQAAAgkCDBlLTppLPJ33xhdXVINQRAAEACBI33WT2//d/1taB0EcABAAgSHTubPantS0FKgQBECinjIwMJSQkKCkpyepSANhcly5SlSrSpk0sC4eKRRsYIEBoAwMgEDp0kFavll59VRo82OpqEKoYAQQAIIj06mX2H3xgbR0IbQRAAACCSEqK2S9bJh05Ym0tCF0EQAAAgsjVV0vNmkmFhdKHH1pdDUIVARAAgCDickm33WaO33nH2loQugiAAAAEmX79zH7RIi4Do2IQAAEACDLXXmsuAxcUSO%2B/b3U1CEUEQAAAgozLJaWmmuPMTGtrQWgiAAIAEITuusvsly6VcnOtrQWhhwAIAEAQatZMatdOKi6W3njD6moQagiAAAAEqXvuMfuZMyXW7UIgEQCBcmItYAAVpX9/ye2Wvv5a2rDB6moQSlgLGAgQ1gIGUBHuvFOaO1d66CHplVesrgahghFAAACC2P33m/0bb0jHj1tbC0IHARAAgCB2883SFVdIXi8rgyBwCIAAAASxKlVOjQJOnWptLQgdBEAAAILcffdJYWHSqlXSxo1WV4NQQAAEACDINWgg3XqrOX71VWtrQWggAAIAYAMPPWT2s2dLR45YWwvsjwAIAIAN3HyzFB9vwt%2BcOVZXA7sjAAIAYAMu16lRwIwMVgZB%2BRAAAQCwiYEDpYgI6ZtvpE8/tboa2BkBECgnloIDUFk8HiktzRxPmmRtLbA3loIDAoSl4ABUhm%2B%2BkRITTX/AH3%2BUfvMbqyuCHTECCACAjVx9tZkQUlLC2sC4dARAAABs5tFHzX7aNNYHxqUhAAIAYDM9e0pXXikdOmT6AgIXiwAIAIDNVK0qPfKIOX7pJVrC4OIRAAEAsKH77pMiI6UtW6QlS6yuBnZDAAQAwIZq1TIhUJImTLC2FtgPARAAAJsaNsysEPLxx9LmzVZXAzshAAIAYFNXXin16WOOGQXExSAAAgBgYyNGmP3s2dKBA9bWAvsgAAIAYGMdO0pJSVJhIY2hceEIgEA5sRYwACu5XKdGATMypIICa%2BuBPbAWMBAgrAUMwConTkhNm0q7dpnVQQYNsroiBDtGAAEAsLlq1U4tDzd%2BvFknGPglBEAAAELAoEGmN%2BCWLdJHH1ldDYIdARAAgBBQq5aUnm6OX3jB2loQ/AiAAACEiEcfNesEL18ubdhgdTUIZgRAAABCRFyc1L%2B/OR43ztpaENwIgLC1EydO6IknnlDLli0VERGh2NhYDRgwQHv37i1z3qFDh5SWliaPxyOPx6O0tDQdPny4zDkbN25Up06dFB4eroYNG%2BqZZ54Rk%2BQB2M3IkWb/9ttmVjBwLgRA2Nrx48e1YcMG/fnPf9aGDRv07rvv6rvvvlNKSkqZ81JTU5Wdna3Fixdr8eLFys7OVlpamv/1/Px8de3aVbGxsVq3bp0mTpyocePGafz48ZX9kQCgXK67Trr5Zqm4WHrpJaurQbCiDyBCzrp169S2bVvt3LlTjRs31pYtW5SQkKCsrCy1a9dOkpSVlaXk5GRt3bpV8fHxmjx5skaNGqX9%2B/fL7XZLkp599llNnDhRu3fvlsvl%2BtVflz6AAILFRx9Jf/iDVLOmlJMj1a5tdUUINowAIuR4vV65XC7V/u//8VavXi2Px%2BMPf5LUvn17eTwerVq1yn9Op06d/OFPkrp37669e/dqx44d5/x1CgsLlZ%2BfX2YDgGDQo4d09dXS0aPS1KlWV4NgRABESCkoKNCTTz6p1NRU/yhcbm6uoqKizjo3KipKubm5/nOio6PLvF76uPScM40dO9Z/T6HH41FcXFwgPwoAXDKXS3r8cXP80ktSUZG19SD4EABhK5mZmapZs6Z/W7Fihf%2B1EydOqH///iopKdErZ6yIfq5LuD6fr8zzZ55TenfE%2BS7/jho1Sl6v17/l5ORc8ucCgEC7806pQQNp717pzTetrgbBJszqAoCLkZKSUuZSbsOGDSWZ8NevXz9t375dn3zySZl78GJiYrR///6z3uvAgQP%2BUb6YmJizRvry8vIk6ayRwVJut7vMJWMACCZutzRsmDRqlGkJM2CAGRkEJEYAYTORkZFq2rSpfwsPD/eHv23btmnZsmWqV69emZ9JTk6W1%2BvV2rVr/c%2BtWbNGXq9XHTp08J/z%2Beefq%2Bi06yRLlixRbGysmjRpUimfDQACbfBgMxHy4R79AAAXiUlEQVRk0ybp44%2BtrgbBhAAIWzt58qT69u2rL7/8UpmZmSouLlZubq5yc3P9Ya5Fixbq0aOH0tPTlZWVpaysLKWnp6tXr16Kj4%2BXZNrEuN1uDRw4UJs2bdL8%2BfM1ZswYjRgx4oJmAANAMKpTx6wRLNEYGmXRBga2tmPHDl1xxRXnfG358uW68cYbJUkHDx7UsGHDtGDBAknmUvKkSZP8M4Ul0wh66NChWrt2rerUqaMHH3xQf/nLXy44ANIGBkAw2rlT%2Bu1vTV/ADRtMn0CAAAgECAEQQLBKTTUTQVJTpcxMq6tBMOASMAAAIa60Jcxbb7E8HAwCIAAAIe76608tD/fii1ZXg2BAAAQAwAFKRwGnTZMOH7a2FliPAAgAgAP06CElJprl4aZMsboaWI0ACACAA7hc0siR5vjll1kezukIgEA5ZWRkKCEhQUlJSVaXAgC/iOXhUIo2MECA0AYGgB08%2B6xZHi4xUfr6a5aHcypGAAEAcJAHHzy1PNySJVZXA6sQAAEAcJDataX77zfHLA/nXARAAAAcZvhwqWpVadky6d//troaWIEACACAwzRpIvXta44ZBXQmAiAAAA5U2hh67lxp925ra0HlIwACAOBAbdpIN9wgnTxp%2BgLCWQiAAAA4VOko4NSp0pEj1taCykUABADAoXr2lOLjJa9Xmj7d6mpQmQiAAAA4VJUq0mOPmeMXXzSXg%2BEMBECgnFgKDoCdDRgg1a8v7dwpvfuu1dWgsrAUHBAgLAUHwK6eekp65hmpbVspK4vl4ZyAEUAAABxu6FDJ7ZbWrpW%2B%2BMLqalAZCIAAADhcVJR0993mePx4a2tB5SAAAgAAjRhh9u%2B9J/3wg7W1oOIRAAEAgBISpB49JJ9Peuklq6tBRSMAAgAASdLIkWb/z39Khw5ZWwsqFgEQAABIkjp3llq2lI4dk6ZNs7oaVCQCIAAAkGTav5Q2hp44UTpxwtp6UHEIgAAAwC81VYqOlnbvlv71L6urQUUhAAIAAD%2B3WxoyxBxPmGAmhSD0EAABAEAZDz1kguC6ddKqVVZXg4pAAATKibWAAYSayy8/1Rh6wgRra0HFYC1gIEBYCxhAKNm0ycwIrlLFNIZu0sTqihBIjAACAICzJCZKXbtKJSVmRjBCCwEQAACc0/DhZv/aa9KRI9bWgsAiAAIAgHPq0UOKj5fy86XXX7e6GgQSARAAAJxTlSrSo4%2Ba45dfloqLra0HgUMABAAA5zVggFS7tpkI8uGHVleDQCEAAgCA84qIkNLTzfGLL1pbCwKHAAgAAH7Rww%2Bby8GffCJt3Gh1NQgEAiAAAPhFjRtLf/qTOX75ZWtrQWAQAAEAwK8qnQwyZ47000/W1oLyIwAC5cRScACcoGNH6frrpYICaepUq6tBebEUHBAgLAUHINTNnCkNHCg1aiRt3y6FhVldES4VI4AAAOCC3HGHFBUl7d4tzZ9vdTUoDwIgAAC4IJddJg0ebI5fesnaWlA%2BBEAAAHDBHnzQXPr94gvpq6%2BsrgaXigAIAAAuWGys1LevOaYljH0RAAEAwEUZNszs33xTOnDA2lpwaQiAsL2nn35azZs3V0REhOrUqaMuXbpozZo1Zc45dOiQ0tLS5PF45PF4lJaWpsOHD5c5Z%2BPGjerUqZPCw8PVsGFDPfPMM2KSPACcrX17qU0bqbBQeu01q6vBpSAAwvauuuoqTZo0SRs3btTKlSvVpEkTdevWTQdO%2B2dpamqqsrOztXjxYi1evFjZ2dlKS0vzv56fn6%2BuXbsqNjZW69at08SJEzVu3DiNHz/eio8EAEHN5ZIeecQcv/KKdPKktfXg4tEHECGntB/fsmXL1LlzZ23ZskUJCQnKyspSu3btJElZWVlKTk7W1q1bFR8fr8mTJ2vUqFHav3%2B/3G63JOnZZ5/VxIkTtXv3brlcrgv%2BdekDCMAJCgrMEnEHDkj/%2Bpd0221WV4SLwQggQkpRUZGmTp0qj8eja665RpK0evVqeTwef/iTpPbt28vj8WjVqlX%2Bczp16uQPf5LUvXt37d27Vzt27KjUzwAAdnDZZVJ6ujmeONHaWnDxCIAICQsXLlTNmjV12WWXacKECVq6dKnq168vScrNzVVUVNRZPxMVFaXc3Fz/OdHR0WVeL31ces6ZCgsLlZ%2BfX2YDACd56CGpalXps8%2BkjRutrgYXgwAIW8nMzFTNmjX924oVKyRJN910k7Kzs7Vq1Sr16NFD/fr1U15env/nznUJ1%2BfzlXn%2BzHNK74443%2BXfsWPH%2BieVeDwexcXFlfvzAYCdNGok9eljjjMyrK0FF4cACFtJSUlRdna2f2vTpo0kKSIiQk2bNlX79u01ffp0hYWFafr06ZKkmJgY7d%2B//6z3OnDggH%2BULyYm5qyRvtIAeebIYKlRo0bJ6/X6t5ycnIB9TgCwi4cfNvvZs6UzmisgiBEAYSuRkZFq2rSpfwsPDz/neT6fT4WFhZKk5ORkeb1erV271v/6mjVr5PV61aFDB/85n3/%2BuYqKivznLFmyRLGxsWrSpMk5fw23261atWqV2QDAaTp1kq6%2BWjp%2BXJoxw%2BpqcKEIgLC1Y8eOafTo0crKytLOnTu1YcMGDRo0SLt379btt98uSWrRooV69Oih9PR0ZWVlKSsrS%2Bnp6erVq5fi4%2BMlmTYxbrdbAwcO1KZNmzR//nyNGTNGI0aMuKAZwADgVC6XNHSoOX7lFamkxNp6cGEIgLC1qlWrauvWrbrtttt01VVXqVevXjpw4IBWrFihq6%2B%2B2n9eZmamWrZsqW7duqlbt25q1aqVZs%2Be7X/d4/Fo6dKl2r17t9q0aaMhQ4ZoxIgRGjFihBUfCwBsJS1NqlVL2rZNWrbM6mpwIegDCAQIfQABONmwYaYdTEqK9P77VleDX8MIIAAAKLchQ8x%2B4UJp505ra8GvIwACAIBya95c6tzZ3AP46qtWV4NfQwAEAAABUToKOH269N9GDAhSBEAAABAQKSmmOXTp%2BsAIXgRAAAAQEGFh0gMPmONXXrG2FvwyAiBQThkZGUpISFBSUpLVpQCA5QYNMkFw1Srp3/%2B2uhqcD21ggAChDQwAGP36Se%2B8Iw0ezISQYMUIIAAACKjSySBz5kj5%2BdbWgnMjAAIAgIDq1Elq0UI6dsyEQAQfAiAAAAgol0t68EFzPHmyxM1mwYcACAAAAm7AACk8XNq0SfriC6urwZkIgAAAIOBq15buvNMcMxEk%2BBAAAQBAhSi9DPzOO9J//mNtLSiLAAgAACpEUpLUurVUVCTNmGF1NTgdARAAAFSY0lHAKVOkkhJra8EpBEAAAFBh%2BveXIiOl77%2BXli%2B3uhqUIgAC5cRScABwfjVrSnffbY6nTLG2FpzCUnBAgLAUHACc29dfS9dcY9YIzsmRYmKsrgiMAAIAgArVqpXUvr108iSTQYIFARAAAFS4Bx4w%2B2nTmAwSDAiAAACgwt1xh%2BTxSD/%2BKC1bZnU1IAACAIAKV6PGqckgU6daWwsIgAAAoJKUXgZ%2B/31p/35ra3E6AiAAAKgUp08Gef11q6txNgIgAACoNOnpZv/aa0wGsRIBEAAAVJo77jArg/zwg/Tpp1ZX41wEQAAAUGkiIqS77jLH06ZZW4uTEQABAEClKr0M/O670k8/WVuLUxEAgXJiLWAAuDjXX2%2B2oiJp1iyrq3Em1gIGAoS1gAHgwk2eLA0ZIiUkSJs2SS6X1RU5CyOAAACg0qWmSuHh0ubNUlaW1dU4DwEQAABUOo9H6tfPHDMZpPIRAAEAgCUGDTL7t96SjhyxthanIQACAABLdOwoxcdLx49Lc%2BdaXY2zEAABAIAlXC7p/vvN8WuvWVuL0xAAAQCAZQYMkMLCpLVrzWxgVA4CIAAAsEx0tNS7tzn%2B5z%2BtrcVJCIAAAMBSpZeBZ82SCgutrcUpCIAAAMBS3btLsbFmWbgPPrC6GmcgAALlxFJwAFA%2BYWHSPfeY4%2BnTra3FKVgKDggQloIDgEv3/fdSs2ZSlSrSzp1So0ZWVxTaGAEEAACWa9pUuuEGqaREmjnT6mpCHwEQAAAEhfvuM/vXX5e4PlmxCIAAACAo9O0r1awp/fCDtGKF1dWENgIgAAAIChER0h13mGN6AlYsAiAAAAga995r9v/6l3TkiLW1hDICIELK4MGD5XK59OKLL5Z5/tChQ0pLS5PH45HH41FaWpoOHz5c5pyNGzeqU6dOCg8PV8OGDfXMM8%2BISfIAULk6dJCuuko6dkx65x2rqwldBECEjPfee09r1qxRbGzsWa%2BlpqYqOztbixcv1uLFi5Wdna20tDT/6/n5%2BeratatiY2O1bt06TZw4UePGjdP48eMr8yMAgOO5XNLAgeb49dctLSWkEQAREvbs2aOHH35YmZmZqlatWpnXtmzZosWLF%2Bu1115TcnKykpOTNW3aNC1cuFDffvutJCkzM1MFBQWaMWOGEhMT9ac//UmjR4/W%2BPHjGQUEgEo2YIDpB7hypekPiMAjAML2SkpKlJaWpv/5n//R1Vdffdbrq1evlsfjUbt27fzPtW/fXh6PR6tWrfKf06lTJ7ndbv853bt31969e7Vjx44K/wwAgFMaNpS6dTPHM2ZYWkrIIgDC9p577jmFhYVp2LBh53w9NzdXUVFRZz0fFRWl3Nxc/znR0dFlXi99XHrOmQoLC5Wfn19mAwAERull4FmzTHNoBBYBELaSmZmpmjVr%2BrfPPvtML730kmbMmCGXy3XenzvXaz6fr8zzZ55Teun3fO87duxY/6QSj8ejuLi4S/lIAIBzuPVWqXZtKSdHWr7c6mpCDwEQtpKSkqLs7Gz/tmrVKuXl5alx48YKCwtTWFiYdu7cqZEjR6pJkyaSpJiYGO3fv/%2Bs9zpw4IB/lC8mJuaskb68vDxJOmtksNSoUaPk9Xr9W05OTgA/KQA422WXSf37m2MmgwRemNUFABcjMjJSkZGR/scPPPCAevfuXeac7t27Ky0tTff%2Bt5lUcnKyvF6v1q5dq7Zt20qS1qxZI6/Xqw4dOvjPGT16tIqKilS9enVJ0pIlSxQbG%2BsPkmdyu91l7hkEAATWwIHSq69K774r5edLtWpZXVHoYAQQtlavXj0lJiaW2apVq6aYmBjFx8dLklq0aKEePXooPT1dWVlZysrKUnp6unr16uU/JzU1VW63WwMHDtSmTZs0f/58jRkzRiNGjPjFS8sAgIrTtq3UvLn088/0BAw0AiAcITMzUy1btlS3bt3UrVs3tWrVSrNnz/a/7vF4tHTpUu3evVtt2rTRkCFDNGLECI0YMcLCqgHA2Vwu6Z57zPHMmdbWEmpcPpqcAQGRn58vj8cjr9erWlynAICA2LNHiouTfD7phx%2BkK6%2B0uqLQwAggAAAIWg0bSl26mONZs6ytJZQQAAEAQFArvQw8a5YZCUT5EQABAEBQ%2B%2BMfpZo1pe3bzfJwKD8CIAAACGo1akh9%2B5pjLgMHBgEQAAAEvdLLwG%2B/bdrCoHwIgEA5ZWRkKCEhQUlJSVaXAgAh64YbpMaNTUPoBQusrsb%2BaAMDBAhtYACgYv3v/0p//7vUs6e0cKHV1dgbI4AAAMAW0tLMfvFi6RxLvOMiEAABAIAtxMdLSUlScbH05ptWV2NvBEAAAGAbAwaY/Zw51tZhdwRAAABgG/37S2Fh0vr10ubNVldjXwRAAABgG/XrS7fcYo4ZBbx0BEAAAGArd99t9pmZUkmJtbXYFQEQAADYSu/eUq1a0q5d0ooVVldjTwRAAABgK%2BHh0u23m%2BPZs62txa4IgAAAwHZKLwP/619SQYG1tdgRARAAANjODTdIjRpJXq%2B0aJHV1dgPARAoJ9YCBoDKV6WKlJpqjpkNfPFYCxgIENYCBoDKtXGj1KqVVL26lJsr1aljdUX2wQggAACwpZYtTQAsKjL3AuLCEQABAIBt3XWX2WdmWluH3RAAAQCAbd15p9l/9pmUk2NtLXZCAAQAALYVF2dmBEvSm29aW4udEAABAICtcRn44hEAAQCArfXtK1WrJn39tfTNN1ZXYw8EQAAAYGt160q33GKO33jD2lrsggAIAABsr7Qp9BtvSHQ4/nUEQAAAYHu9e0s1a0o7dkhZWVZXE/zCrC4AsLuMjAxlZGSouLjY6lIAwLFq1JBGjjT7K6%2B0uprgx1JwQICwFBwAwC64BAwAAOAwBEAAAACHIQACAAA4DAEQAADAYQiAAAAADkMABAAAcBgCIAAAgMMQAAEAAByGAAgAAOAwBEAAAACHIQAC5ZSRkaGEhAQlJSVZXQoAABeEtYCBAGEtYACAXTACCAAA4DAEQAAAAIchAAIAADgMARAAAMBhCIAAAAAOQwCE7Q0cOFAul6vM1r59%2BzLnFBYW6pFHHlH9%2BvUVERGhlJQU7d69u8w5u3btUu/evRUREaH69etr2LBhKioqqsyPAgBApSAAIiT06NFD%2B/bt828ffvhhmdeHDx%2Bu%2BfPna%2B7cuVq5cqWOHj2qXr16qbi4WJJUXFysnj176tixY1q5cqXmzp2refPmaeTIkVZ8HAAAKlSY1QUAgeB2uxUTE3PO17xer6ZPn67Zs2erS5cukqQ5c%2BYoLi5Oy5YtU/fu3bVkyRJt3rxZOTk5io2NlSS98MILGjhwoP7%2B97/T1w8AEFIYAURI%2BPTTTxUVFaWrrrpK6enpysvL87%2B2fv16nThxQt26dfM/Fxsbq8TERK1atUqStHr1aiUmJvrDnyR1795dhYWFWr9%2B/Tl/zcLCQuXn55fZAACwAwIgbO%2BWW25RZmamPvnkE73wwgtat26dbr75ZhUWFkqScnNzVb16ddWpU6fMz0VHRys3N9d/TnR0dJnX69Spo%2BrVq/vPOdPYsWPl8Xj8W1xcXAV8OgAAAo8ACFvJzMxUzZo1/duKFSt0xx13qGfPnkpMTFTv3r310Ucf6bvvvtOiRYt%2B8b18Pp9cLpf/8enH5zvndKNGjZLX6/VvOTk55ftwAABUEu4BhK2kpKSoXbt2/scNGzY865wGDRroN7/5jbZt2yZJiomJUVFRkQ4dOlRmFDAvL08dOnTwn7NmzZoy73Po0CGdOHHirJHBUm63W263u9yfCQCAysYIIGwlMjJSTZs29W/h4eFnnfPTTz8pJydHDRo0kCS1bt1a1apV09KlS/3n7Nu3T5s2bfIHwOTkZG3atEn79u3zn7NkyRK53W61bt26gj8VAACVy%2BXz%2BXxWFwFcqqNHj%2Brpp5/WbbfdpgYNGmjHjh0aPXq0du3apS1btigyMlKS9NBDD2nhwoWaMWOG6tatq8cff1w//fST1q9fr6pVq6q4uFjXXnutoqOj9Y9//EMHDx7UwIED1adPH02cOPGCasnPz5fH45HX62XWMAAgqHEJGLZWtWpVbdy4UbNmzdLhw4fVoEED3XTTTXrrrbf84U%2BSJkyYoLCwMPXr108///yzOnfurBkzZqhq1ar%2B91m0aJGGDBmijh07Kjw8XKmpqRo3bpxVHw0AgArDCCAQIIwAAgDsgnsAAQAAHIYACAAA4DAEQAAAAIchAAIAADgMARAAAMBhCIBAOWVkZCghIUFJSUlWlwIAwAWhDQwQILSBAQDYBSOAAAAADsMIIBAgPp9PR44cUWRkpFwul9XlAABwXgRAAAAAh%2BESMAAAgMMQAAEAAByGAAgAAOAwBEAAAACHIQACAAA4DAEQAADAYQiAAAAADkMABAAAcBgCIAAAgMMQAAEAAByGAAgAAOAwBEAAAACHIQACAAA4DAEQAADAYQiAAAAADkMABAAAcBgCIAAAgMMQAAEAAByGAAgAAOAwBEAAAACHIQACAAA4DAEQAADAYQiAAAAADkMABAAAcBgCIAAAgMMQAAEAAByGAAgAAOAwBEAAAACHIQACAAA4DAEQAADAYQiAAAAADkMABAAAcBgCIAAAgMMQAAEAAByGAAgAAOAwBEAAAACHIQACAAA4DAEQAADAYQiAAAAADkMABAAAcBgCIAAAgMMQAAEAAByGAAgAAOAwBEAAAACHIQACAAA4DAEQAADAYQiAAAAADkMABAAAcBgCIAAAgMMQAAEAABzm/wN5EM1duT3nNgAAAABJRU5ErkJggg%3D%3D'}
Genus 2 curve data - 3584.c.458752.1