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g2c_curves • Show schema
{'Lhash': '1811255940982796660', 'abs_disc': 274625, 'analytic_rank': 0, 'analytic_rank_proved': True, 'analytic_sha': 1, 'aut_grp_id': '[2,1]', 'aut_grp_label': '2.1', 'aut_grp_tex': 'C_2', 'bad_lfactors': '[[5,[1,2,1]],[13,[1,-2,1]]]', 'bad_primes': [5, 13], 'class': '4225.a', 'cond': 4225, 'disc_sign': -1, 'end_alg': 'RM', 'eqn': '[[1,3,10,6,4,1],[1,0,0,1]]', 'g2_inv': "['148628987203643/274625','2391820186409/274625','1805778919/10985']", 'geom_aut_grp_id': '[2,1]', 'geom_aut_grp_label': '2.1', 'geom_aut_grp_tex': 'C_2', 'geom_end_alg': 'RM', 'globally_solvable': 1, 'has_square_sha': True, 'hasse_weil_proved': True, 'igusa_clebsch_inv': "['2732','286321','209098567','35152000']", 'igusa_inv': "['683','7507','96775','2435569','274625']", 'is_gl2_type': True, 'is_simple_base': True, 'is_simple_geom': True, 'label': '4225.a.274625.1', 'leading_coeff': {'__RealLiteral__': 0, 'data': '0.9122508780379557949829381684019972441583519995065058745', 'prec': 190}, 'locally_solvable': True, 'modell_images': ['2.90.1', '3.1920.1'], 'mw_rank': 0, 'mw_rank_proved': True, 'non_solvable_places': [], 'num_rat_pts': 2, 'num_rat_wpts': 0, 'real_geom_end_alg': 'R x R', 'real_period': {'__RealLiteral__': 0, 'data': '8.2102579023416021548464435156', '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': 4, 'torsion_order': 6, 'torsion_subgroup': '[6]', 'two_selmer_rank': 1, 'two_torsion_field': ['4.0.1040.1', [5, -2, -3, 0, 1], [4, 3], False]} -
g2c_endomorphisms • Show schema
{'factorsQQ_base': [['2.2.12.1', [-3, 0, 1], -1]], 'factorsQQ_geom': [['2.2.12.1', [-3, 0, 1], -1]], 'factorsRR_base': ['RR', 'RR'], 'factorsRR_geom': ['RR', 'RR'], 'fod_coeffs': [0, 1], 'fod_label': '1.1.1.1', 'is_simple_base': True, 'is_simple_geom': True, 'label': '4225.a.274625.1', 'lattice': [[['1.1.1.1', [0, 1], [0]], [['2.2.12.1', [-3, 0, 1], -1]], ['RR', 'RR'], [1, -1], 'G_{3,3}']], 'ring_base': [1, -1], 'ring_geom': [1, -1], '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': '4225.a.274625.1', 'mw_gens': [[[[1, 2], [1, 1], [1, 1]], [[-1, 2], [-2, 1], [0, 1], [0, 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': '4225.a.274625.1', 'plot': 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SQGgHg3cuRI5efnKzMzU61bt9aFF16ohQsX%2Bl0W4hQBEPj/WreW/vxn2zfwiitsqPi112x%2B4A03SD/84HeFAFC7qVOnavjw4friiy80efJkVVRUaPDgwSotLfW7NMQhtoEBavHNN9Jdd0mTJtn9tDTrIRwxQmrZ0t/aAGB/Nm7cqNatW2vq1Kk69dRTD%2Bg9bAPjDnoAgVr07m1Hy02bJvXrZ1vHPP641KmTzRksKfG7QgCoXVFRkSSpRYsWtb4mFAqpuLi4RoMb6AEEDoDnWRi85x7rGZSsF3DECGn4cKlJE3/rA4DqPM/TBRdcoK1bt2r69Om1vu7%2B%2B%2B/XAw888KPH6QFMfgRA4CBUVUlvvCH97/9KixbZY1lZdsrIL39pR84BgN%2BGDx%2Bud955R59%2B%2BqnatWtX6%2BtCoZBCodDu%2B8XFxcrJySEAOoAACNRBRYX04os2FLx8uT3Wrp10773SNddIjRv7Wh4Ah918882aMGGCpk2bpk6dOh3Ue5kD6A7mAAJ10LChBb2FC6VnnpGys6XVq221cPfu0t//LpWX%2B10lAJd4nqebbrpJ48aN08cff3zQ4Q9uIQACh6BxYwt9S5ZITz1lw8HLl0v//d921Nw//mG9hQBQ34YPH66XXnpJL7/8sjIzM7Vu3TqtW7dOO3bs8Ls0xCGGgIEoKiuzHsHHHpM2bLDHunSxoeGrrrKeQwCoD4FAYK%2BPv/DCC/r5z39%2BQJ/BELA7CIBAPSgtlf7yF9s2ZuNGe6xz50gQbNTI3/oAYG8IgO5gCBioB02bSr/9rbRsmfToo1KrVtLSpdK119ocwb/9Tdq1y%2B8qAQCuIgAC9ahpU%2BmOO2xe4OOP23Fzy5ZJ110nde1qvYQ7d/pdJQDANQRAIAaaNpX%2B538s/D35pC0WWbnSNpHu3Fn64x9t2BgAgFggAAIx1KSJ9Otf23Dw00/b3oFr10q33y517Cg98oj0/09vAoCYKSgoUF5envLz8/0uBTHCIhDAR7t2SWPGSKNGWSiUpGDQegZvu006/HB/6wPgFhaBuIMeQMBHjRvbfMCFC%2B1kkbw86wF85BGpQwfp1lulVav8rhIAkGwIgEAcaNjQtocpLJTefFM67jhpxw7pz3%2B2OYLXXCMtWOB3lQCAZEEABOJIgwbSxRdLM2dKH3wgnX66nSTyj39IPXpIF10kzZjhd5UAgERHAATiUCAgnXmm9PHH0hdfSBdeaI9PmCCdeKI0YID07rsSM3gBAHVBAATi3AknSOPHS/PmST//uZ0iMnWqdO65Uq9e0j//yabSAICDwypgIMGsXi396U/Sc89J27fbY9nZtmDkl7%2B0VcQAUBesAnYHARBIUNu2Sc8%2BKz31lLRunT2WmWkh8JZbpPbt/a0PQOIhALqDAAgkuFBIGjtW%2BsMfbJhYklJSpMsuk37zG1tRDAAHggDoDuYAAgkuNVW69lrbQuadd6QzzpAqK6VXXpH69pVOO80Wj1RW%2Bl0pgHjFSSDuoQcQSEKzZ9uZw6%2B%2BatvISFKXLjY0fM01NlQMAHuiB9AdBEAgia1ZY2cOP/eczRmUpGbNpP/%2Bb%2Bmmm6ROnfytD0B8IQC6gwAIOKC01M4cfuopadEie6xBA%2BmCC2z18Kmn2t6DANxGAHQHARBwSFWV9N57to3M5MmRx3v3lm6%2BWbriCik93b/6APiLAOgOAiDgqHnz7Kzhf/7Tzh2WpJYtbXj4xhulDh38rQ9A7BEA3UEABBy3ZYv0979LBQXSihX2WIMG0pAhNk/wjDMYHgZcQQB0BwEQgCTbJuatt6TRo6WPPoo8npsr/epX0s9%2BxikjQLIjALqDAAjgR%2BbNk/7yF1s4Ej5urmlT6aqrLAz26uVvfQDqBwHQHQRAALUqLrY5gs88EzllRJL69ZNuuEG65BIpLc2/%2BgBEFwHQHQRAAPvledLUqdYrOH58ZHPpli1tY%2Bnrr5eOPNLfGgHUXUFBgQoKClRZWalFixYRAB1AAARwUNaulf72N%2Bn556XVqyOPDxxovYJDhkiNG/tXH4C6owfQHQRAAHVSUSG9%2B6707LO2t2D4b5LWra1X8Lrr7Pg5AImDAOgOAiCAQ7Z8ufUK/v3v0rp1kcfPOMOC4EUXSampvpUH4AARAN1BAAQQNeXl0ttv2/Dw%2B%2B9HegVbtpSuvlr6xS%2Bknj39rRFA7QiA7iAAAqgXK1ZI//d/1qrPFTzhBAuCP/2pxO8XIL4QAN1BAARQryorbY7g3/5mvYPhFcRNmkiXXmrzBU89ldNGgHhAAHQHARBAzKxfL734os0VXLAg8niXLtLPf26njbRv71t5gPMIgO4gAAKIOc%2BTPv/chodfey1y2kggYNvJDBsmXXyx9RICiB0CoDsIgAB8VVoq/etf0j/%2BIU2ZEnk8I0O67DLrFezfX2rQwK8KAXcQAN1BAAQQN5Yts6Pnxoyxn8M6drRVxFddJXXr5lt5QNIjALqDAAgg7lRVSZ9%2BakHwjTekkpLIcyecYGHwpz%2BVWrXyr0YgmXAUnHsIgADiWlmZ9O9/2%2BKRDz6wVcWS1LCh9JOfSFdeacfPMV8QOHT0ALqDAAggYaxfL73yioXBWbMij2dk2GkjV1whDRpk4RDAwSMAuoMACCAhzZ8vjR0rvfxyzfmChx9u%2Bwtefrl08sksHgEOBgHQHQRAAAktvKXMyy/bljKbNkWey8mxuYJDh0rHHstm08D%2BEADdwb%2BNASS0QMB6%2BkaPln74QZo0ybaOycyUVq2SnnhC6tvXVg/fc4/07beRM4qBZDNt2jSdf/75atu2rQKBgCZMmOB3SYhTBEAASaNRI1sYMmaMtGGD9OabNhycni4tWSI98ojUu7eUlyf97/9K331HGERyKS0tVe/evTV69Gi/S0GcYwgYQNLbvt3OIX71VTuXOBSKPJebK11yiQXFo49mmBjJIxAIaPz48brwwgsP%2BD0MAbuDHkAASS8jw%2BYBTphgPYMvvmhbxzRubGcSP/SQ9Qx26ybddZf01Vf0DAJIbvQAAnBWcbH01lu22fSePYMdOtjWMhdfbHMMU1L8qxOoiwPpAQyFQgpV%2B4NfXFysnJwcegAdQA8gAGc1a2YbSU%2BYIG3caEPEl1xim0qvWCH96U/SqadKbdtK110nvfOOtHOn31UD0TNy5EgFg8HdLScnx%2B%2BSECP0AALAHnbskN5/Xxo3znoIt22LPJeRIZ19tnTBBdI550jNm/tXJ7Av9ABiXwiAALAP5eXSlCnWS/jvf0tr1kSeS0mxHsIhQ6x17uxbmcCPsAgE%2B0IABIADVFUlff11JAzOnVvz%2Bbw86fzzpfPOk046iXmDiL3t27dryZIlkqQ%2BffroySef1Omnn64WLVqoffv2%2B30/AdAdBEAAqKPvv5cmTrQ2fbpUWRl5rkULGyo%2B91zprLPsPlDfpkyZotNPP/1Hjw8bNkz/%2BMc/9vv%2BRA6Anmf/QOvQwY6ExL4RAAEgCrZutZXEb71lt1u3Rp5r0MB6BM85x0LhMcew3yDiU6IFQM%2BT5syRXn/d2tKl0h//KN12m9%2BVxT8CIABEWUWFnU/8zjvWvvuu5vNZWdYr%2BJOfSGeeKbVs6U%2BdwJ4SIQCGe/refNO2cPr%2B%2B8hz6enSHXdI99/vW3kJgwAIAPVs5Urp3XetffyxVFoaeS4QkPLzpcGDLRSecIIdaQf4IV4DYGWl/aNq3Dhp/Hhp%2BfLIc2lp1rt%2B2WU2/7ZpU9/KTCgEQACIoVBI%2BvRTadIk22pmz97BzEzp9NOtZ3DQIKl7d4aLETvxFAB37rR/ME2YYPNs16%2BPPNekiYW%2BSy6xebYZGf7VmagIgADgozVrLAh%2B8IH04YfS5s01n8/OtiA4cKB0xhl2H6gvfgfAjRutp3ziRPv/RfXe8mDQevguvtimTzRpEvPykgoBEADiRFWVNHu2NHmytf/8p%2BbxdJKdV3zGGdZLOGCA1Lq1L6UiyRQUFKigoECVlZVatGhRzAKg50mFhTZX9u23bZi3eirJzrY9Ni%2B80P68N25c7yU5gwAIAHFqxw4bLv7oI2uzZllIrC4vTzrtNGunniq1aeNPrUgOsegBLCqyP8%2BTJlmrvrm6ZKvkzz/fgt9xxzEFor4QAAEgQWzbJk2dKn3yibVvv/3xa7p2lfr3j7TOnfkFigNXHwGwslL66ivr1X7/fevlq75nZnq6TXE47zyb18dxxLFBAASABLV5szRtmoXCqVOlb76pOXwm2ZYzp5wi9esnnXyy1KcPq4xRu2gEQM%2BTFi2yBRwffmi31c/Tlmwqw9lnWzvtNFvJi9giAAJAkti2zYaMp0%2B325kz7Szj6tLSbNuZE0%2B0zalPPJFhY0TUJQB6nm3APGWKtY8/ln74oeZrgkGbu3rWWbblUadOUS8dB4kACABJascOC4H/%2BY%2B1zz%2BXtmz58etycmz/weOPt3B43HG2HQ3ccyABsKpKmjfP/qExfbr1Qu85jy811f6BMXCgbWl03HFSw4Yx%2BAI4YARAAHCE50kLF1oQ/Pxz6YsvpLlzf7ywJBCQcnOlvn3tF/dxx9nEfPZaS357C4AlJdKXX9qfmc8%2Bs9s9h3QbNbJ/QAwYYCvUTz7Z5vYhfhEAAcBhJSV2rNaMGfZL/ssvpdWrf/y6QMDmbfXpY2Gwd29rWVksMkkmmzcXq1WroP70pyIVFjbTjBn2j4Q9k0LTpjZ9ILzY6MQT2Zcv0RAAAQA1rF9vqza/%2BsrC4axZPx7iCzv8cKlXL%2Bnoo6317Glb09BbGP927LBwN3u2/W88a5Y0Z06xdu0KSiqSFBkCbt/ehnRPPtkWFPXuzZBuoiMAAgD2a8MGCwizZ0tz5tiK48WLfzx8HNahgwXBvDwbTg63li3pMYy1qio7O3fuXNt0ubDQthBauLDmdiymWFJQAwYU6aSTmun4421%2BKAuFkg8BEABQJ2VlNUNFYaGdbVz9zNY9NW9uQ8ldu1o78kipSxfbr7BVK8Lhodi%2BXVqyxLZgWbhQWrBAmj/fbnfs2Pt7WrWyIX1plubPf0mNG3%2BrZcs%2BiouzgFG/CIAAgKjavNlWic6bZwEkHEJWrtz3%2BzIzpY4dbYuQDh0irV07G4I84ggpJSUmXyEulZfbUPyKFdaWLbP2/ffW1q6t/b2NG1sPbHio/uijbRi3bduaodvvs4AROwRAAEBMlJXZsHH1Fg4vtc0xrC4lxRadtG1rQ5Jt2tj9I46w1rq1zUls1Uo67LDECYulpdLGjdbWr4%2B0tWvtuqxZYwtz1q2rfcg9rGVL62Ht1s0CX48e1jp3PrA5ewRAdxAAAQC%2B27GjZq9WuJdr1SprP/ywt/lqtQsELAQ2b27tsMNsM%2BJmzaynMTPTVrI2bWqrV9PTbe%2B6tDTrLWvUyFpKirVAINI8z4JYZaW18nJroZC1HTuslZVZuCspibSiIttCZetWa5s3Szt3Hvj3atzY9m3s2DHSW9qli7Ujj7TveigIgO4gAAIA4l5lpfWKhXvE1q61HrFw27DBetA2bbKQlWgaN7bey9atrTcz3MPZtq2UnW0tJ8eeb9Cg/uogALqDAAgASCrl5XbiyZYtkZ62bdssGBYXR3rjSkutlZVZL9zOnZFevPJyqaIi0stXVRXZCy8QsBAW7h0M9xY2bmw9iGlp1qPYpIn1MGZkWI9js2bWCxkMSi1aWG9dixY2ZJ2RER8LYAiA7mAXHwBAUmnUKDIvEMDe1WNHMgAAAOIRARAAAMAxBEAAAADHEAABAHBcQUGB8vLylJ%2Bf73cpiBFWAQMAAEmsAnYJPYAAAACOIQACAAA4hgAIAADgGAIgAACAYwiAAAAAjiEAAgAAOIYACAAA4BgCIAAAgGMIgAAAOI6TQNzDSSAAAEASJ4G4hB5AAAAAxxAAAQAAHEMABAAAcAwBEAAAwDEEQAAAAMcQAAEAABxDAAQAAHBMQ78LSGSe56mkpMTvMgAAqJNQKKRQKLT7fvh3WnFxsV8lxVRmZqYCgYDfZfiCjaAPQXjDTAAAkHhc3vCaAHgI9uwBzM/P18yZMw/pMw/1M4qLi5WTk6NVq1bV%2BQ91PHyPQ/2MaFyHQ60hXj6DaxGRTNciHv6uiEYd0fiMZLkWflzLPXsA165dq%2BOPP17z5s1TdnZ2zOqI9vsP9DNc7gFkCPgQBAKBGn9ZpKSkHPK/JKLxGZLUrFmzOn9OvHyPaHzGoVyHaNUQL5/BtYhIhmsRD39XRKsOrkV03h%2Btz5AsGHEtkhuLQKJo%2BPDhcfEZ8VBDvHxGPNQQL58RDzXEy2fEQw2H%2BhnxcB0krkV18fAM8TeqAAAaBklEQVQ9uBbR/YxkxhBwkuEgb8N1iOBaRHAtIrgWEVyLiNWrV%2B8eDm/Xrp3f5aAepdx///33%2B10EoislJUUDBgxQw4Zuj/BzHSK4FhFciwiuRQTXwoRCIT3%2B%2BOO666671LRpU7/LQT2iBxAAAEiiN9QlzAEEAABwDAEQAADAMQRAAAAAxxAAAQBwXEFBgfLy8pSfn%2B93KYgRAmACGjdunM466yy1atVKgUBAc%2BbM2e97/vrXv6p///5q3ry5mjdvrkGDBunLL7%2BMQbX%2BqMs1SnSe5%2Bn%2B%2B%2B9X27ZtlZ6ergEDBmju3Ln7fE9FRYXuvfdederUSenp6ercubMefPBBVVVVxajq6KvLdZCkNWvW6KqrrlLLli3VpEkTHXPMMfr6669jUHH9qeu1CBs5cqQCgYBuu%2B22eqwyNupyLUaOHKn8/HxlZmaqdevWuvDCC7Vw4cIYVRxbw4cP17x58w759A0kDgJgAiotLVW/fv00atSoA37PlClTdPnll%2BuTTz7R559/rvbt22vw4MFas2ZNPVbqn7pco0T32GOP6cknn9To0aM1c%2BZMZWVl6cwzz6xxXOGeHn30UT377LMaPXq05s%2Bfr8cee0yPP/64nn766RhWHl11uQ5bt25Vv3791KhRI02aNEnz5s3TH/7wBx122GExrDz66nItwmbOnKnnn39evXr1ikGl9a8u12Lq1KkaPny4vvjiC02ePFkVFRUaPHiwSktLY1g5UE88JKxly5Z5krzZs2cf9HsrKiq8zMxMb8yYMfVQWfw4lGuUSKqqqrysrCxv1KhRux/buXOnFwwGvWeffbbW95177rnetddeW%2BOxiy%2B%2B2Lvqqqvqrdb6VNfrMGLECO%2BUU06JRYkxU9dr4XmeV1JS4nXt2tWbPHmyd9ppp3m33nprfZdbrw7lWlS3YcMGT5I3derU%2BigzLhQVFXmSvKKiIr9LQT2jB9BRZWVlKi8vV4sWLfwuBVGwbNkyrVu3ToMHD979WGpqqk477TR99tlntb7vlFNO0UcffaRFixZJkr755ht9%2BumnOuecc%2Bq95vpQ1%2BswceJE9e3bV5deeqlat26tPn366K9//WssSq43db0Wkg0HnnvuuRo0aFB9lxkTh3ItqisqKpIk/t5EUnB7y3OH3XnnncrOzk6av%2BBdt27dOknSEUccUePxI444QitWrKj1fSNGjFBRUZFyc3OVkpKiyspKPfzww7r88svrtd76UtfrsHTpUj3zzDO6/fbbdffdd%2BvLL7/ULbfcotTUVP3sZz%2Br15rrS12vxauvvqpZs2Yl1Vywul6L6jzP0%2B23365TTjlFPXv2jHqNQKzRAxjnxo4dq4yMjN1t%2BvTph/yZjz32mF555RWNGzdOaWlpUajSX/VxjeLdnt%2B5vLxckhQIBGq8zvO8Hz1W3WuvvaaXXnpJL7/8smbNmqUxY8boiSee0JgxY%2Bq1/miJ1nWoqqrSscceq0ceeUR9%2BvTR9ddfr%2Buuu07PPPNMvdYfTdG4FqtWrdKtt96ql156KaH/bojWn4vqbrrpJn377bd65ZVXol4v4Ad6AOPckCFDdMIJJ%2By%2Bn52dfUif98QTT%2BiRRx7Rhx9%2BmDSTu6N9jRLBnt85FApJsp6ONm3a7H58w4YNP%2Br1qO63v/2t7rzzTg0dOlSSdPTRR2vFihUaOXKkhg0bVk/VR0%2B0rkObNm2Ul5dX47EePXrozTffjHLF9Sca1%2BLrr7/Whg0bdNxxx%2B1%2BrLKyUtOmTdPo0aMVCoWUkpJST98geqL15yLs5ptv1sSJEzVt2jS1a9cu%2BgUDPiAAxrnMzExlZmZG5bMef/xxPfTQQ3r//ffVt2/fqHxmPIjmNUoUe35nz/OUlZWlyZMnq0%2BfPpKkXbt2aerUqXr00Udr/ZyysjI1aFBzICAlJSVhtoGJ1nXo16/fj7b3WLRokTp06FA/hdeDaFyLgQMHqrCwsMZj11xzjXJzczVixIiECH9S9P5ceJ6nm2%2B%2BWePHj9eUKVPUqVOneq8diBm/Vp%2Bg7jZv3uzNnj3be%2BeddzxJ3quvvurNnj3bW7t27e7XXH311d6dd965%2B/6jjz7qNW7c2PvXv/7lrV27dncrKSnx4yvUuwO5Rslm1KhRXjAY9MaNG%2BcVFhZ6l19%2BudemTRuvuLh492vOOOMM7%2Bmnn959f9iwYV52drb39ttve8uWLfPGjRvntWrVyrvjjjv8%2BApRUZfr8OWXX3oNGzb0Hn74YW/x4sXe2LFjvSZNmngvvfSSH18haupyLfaUDKuAPa9u1%2BLGG2/0gsGgN2XKlBp/b5aVlfnxFWKCVcDuIAAmoBdeeMGT9KN233337X7Naaed5g0bNmz3/Q4dOuz3PcnkQK5RsqmqqvLuu%2B8%2BLysry0tNTfVOPfVUr7CwsMZrOnToUOMaFBcXe7feeqvXvn17Ly0tzevcubN3zz33eKFQKMbVR09droPned5bb73l9ezZ00tNTfVyc3O9559/PoZV14%2B6XovqkiUA1uVa7O3vEEneCy%2B8ENviY2D06NFejx49vG7duhEAHRHwPM%2BLWXcjAACIW8XFxQoGgyoqKlKzZs38Lgf1iFXAAAAAjiEAAgAAOIYACAAA4BgCIAAAgGMIgAAAAI4hAAIAADiGAAgAAOAYAiAAAIBjCIAAAACOIQACAOC4goIC5eXlKT8/3%2B9SECMcBQcAACRxFJxL6AEEAABwDAEQAADAMQRAAAAAxxAAAQAAHEMABAAAcAwBEAAAwDEEQAAAAMcQAAEAABxDAAQAwHGcBOIeTgIBAACSOAnEJfQAAgAAOIYACAAA4BgCIAAAgGMIgAAAJIFx48bprLPOUqtWrRQIBDRnzhy/S0IcIwACAJAESktL1a9fP40aNcrvUpAAGvpdAAAAOHRXX321JGn58uX%2BFoKEQA8gAACAY%2BgBBADAUaFQSKFQaPf94uJiH6tBLNEDCABAghk7dqwyMjJ2t%2BnTp9fpc0aOHKlgMLi75eTkRLlSxCtOAgEAIMGUlJRo/fr1u%2B9nZ2crPT1dks0B7NSpk2bPnq1jjjlmn5%2Bztx7AnJwcTgJxAEPAAAAkmMzMTGVmZh7y56Smpio1NTUKFSHREAABAEgCW7Zs0cqVK/XDDz9IkhYuXChJysrKUlZWlp%2BlIQ4xBxAAgCQwceJE9enTR%2Beee64kaejQoerTp4%2BeffZZnytDPGIOIAAAkGRzAIPBIHMAHUAPIAAAgGMIgAAAAI4hAAIAADiGAAgAAOAYAiAAAI4rKChQXl6e8vPz/S4FMcIqYAAAIIlVwC6hBxAAAMAxBEAAAADHEAABAAAcQwAEAABwDAEQAADAMQRAAAAAxxAAAQAAHEMABAAAcAwBEAAAx3ESiHs4CQQAAEjiJBCX0AMIAADgmIZ%2BFwAAgB%2BqqqTycmsVFdYqK%2B3x6mNjgYDUoIG1hg2llBSpcWOpUSP7GUhEBEAAQEKoqJC2bpW2bLG2dau0bZu1oiJrJSVScbG0fXuklZVZ27FD2rnTWihkn3eoUlKk1FQpPV1KS5OaNpWaNLHbjAwpM1Nq1kwKBqXDDpOaN7fWooXUsqXUqpV0%2BOH2ukDg0OsBDhQBEADgC8%2Bz0LZuXaStX29twwZp40a73bTJ2rZtsakr3OMXCFiNnme9gntTWRkJmIciNVVq3Vo64ggpK0tq00Zq21bKzpbatbPWvr0FSSAaCIAAgKirrJTWrpVWrZJWr460NWukH36ItB07Dv6zg8FIT1rz5tazFgxGetoyM633LdyaNIm0tDRrqak2jBseym3Y0FqDfcyMr6qy71VRYcPGu3ZZT2IoZL2KO3ZEwmC497G42Holwz2V27ZZz%2BXmzdY2bbLXh0J2rVat2vd3b9ZM6tBB6tRJ6thR6tzZ2pFH2m1q6sFfT7iJVcAAgIO2c6e0cqW0fLm0YkXkduVKu12zxsLSgQgGrdcrK8t6wFq3rtlatYq05s0tqCWTsjLr6dywwXo/166NBOQ1ayLhecuWfX9OIGDhsGtXKTc30vLy7LoeyBAzq4DdQQAEAPyI51kgWbJEWrpU%2Bv57u122zG5/%2BGH/n5GSEhnCzMmx2%2BxsG9oMD29mZVnPHPavtDQSupcvj/xv8f339r/T9u21v7dFC%2Bmoo6SePaWjj5Z69bLbPTMeAdAdBEAAcJTnWW/TokUWIBYvttslSyxUlJbu%2B/1Nm9owZIcO1sI/t29vLSuLVbKxEg7sixdLCxdKCxbY7fz5FhJrm8PYubN0zDHSscda69q1WF27EgBdQAAEgCS3bZuFgYULLeyFQ8LixftevBAIWJDr0iUy16xTJ2udO9uQLCtX49%2BOHRYI586VvvtO%2BvZba2vW7O3VxZKCOv/8Ip18cjMdf7yUn2/zKpFcCIAAkAQqK23u3YIFkRbuCdqwofb3NWhgge7II23uWPi2Sxfr0WNRQfLavFmaM0eaPdva119LCxdaAJSKJFkPYIMGNnx80knSySdbO/JIwn%2BiIwACQALZudN67ubNs%2BG9%2BfMt5C1aZM/Vpk0bqXt3qVu3mq1TJ1sJC0jSmjXFatcuqAcfLFJhYTPNmGHzDvfUurV0yilS//7SqadKvXsz3J9oCIAAEIfKyiLDdvPnW%2BCbN8/m5tU2nys19ccrQMOhj%2BlcOBB7WwSydq30xRfSZ59Z%2B%2Bor2wKnumbNLAwOGCCdfrrNKyQQxjcCIAD4qKwsEvDmzo3cLltW8ziy6oJB29ojN1fq0SPSOnbkly4OzYGsAg6FLAROn27t009tv8Pqmje3MDhokLWuXRkyjjcEQACIgVDI5uSFJ%2BKHb5curT3otWxpQW/P1qYNv0xRP%2BqyDUxlpc0lnDLF2rRpPw6E7dtLgwdbGzTIAiL8RQAEgCiqrLRh2u%2B%2Bq9kWLap9Y%2BSWLSN7tOXl2c95eTbPCoilaOwDWFFhC0o%2B%2Bkj68EPpP/%2BpOWTcoIF04onSOedYO%2BYY/kHjBwIgANSB59npDIWFkZBXWGjDuaHQ3t8TDFrIO%2BqoSOA76igLevwCRDyoj42gS0utV/CDD6T337f/j1TXpo107rnSeedZ72DTplH5z2I/CIAAsB9btkSCXvXAV1S099enp1sP3tFHR0Jez5528gVBD/EsFieBrFwpvfee9O671kNYfcPx1FRp4EBpyBBrbdrUSwkQARAAdtuxwxZhhINeOOzVduxZw4a2wjZ8vFbPntY6dWIxBhJTrI%2BCC4WkqVOlt9%2B2tmxZzedPPFG68ELp4ottIQmihwAIwDmVlXbcWfVevcLCfW%2Bx0qFDJOSFb7t3Z6NkJIeCggIVFBSosrJSixYt8uUoOM%2BzxVETJ1qbMaPm8z17Sv/1X9Ill1ivOr3ph4YACCBpeZ713lUPeeF5erVtmtyqVSTkVR/CZR89uCDWPYD78sMP0r//LY0fL33yiS0uCcvNtSD4058SBuuKAAggKWzdar0He87V27p1769v0iQyT696z94RR/DLBO6KpwBY3dat1iv4r3/ZYpLqq4p79JCGDrUw2L27fzUmGgIggIQS3ji5%2BmKM776r7WB7m4vXtWvNoNezp9S5M/P0gD3FawCsrrjYwuDrr9uq4uph8NhjpVtukYYN86%2B%2BRNHQ7wIAYG/Ky23vvD330/v%2B%2B9o3Tm7fPhLwwmEvN1dKS4tt7QDqT7Nm0lVXWSsqkiZMkF59VZo8WZo1y/6OwP7RAwjAV%2BGNk/c8IWPhwppzfqoLz9OrHvaOOsr22QNQd4nQA1ibTZukN96QzjxTOvJIv6uJfwRAADFRWSktXx4JeeEzb/e1cXJmZs1Nk8ONeXpATeXl5br33nv17rvvaunSpQoGgxo0aJBGjRqltm3bHvDnJHIAxMFhCBhAVFVW2l5e8%2BZFQt7cudKCBbbP3t6kp9tE7uqbJvfsKeXkEPSAA1FWVqZZs2bpd7/7nXr37q2tW7fqtttu05AhQ/TVV1/5XR7iED2AAOqkosKGbsNBb/78SNCrbYuV1FQLeuFevXDr1MnOBwUQPTNnztTxxx%2BvFStWqH379gf0HnoA3UEPIIB92rHDFmPMnx9p8%2BbZY%2BXle39POOjl5VkLBz1W3gKxU1RUpEAgoMMOO6zW14RCIYWqzcEoLi6ORWmIAwRAAJLsvNv5860Hb8GCSNhbtqz2VbdNmljQqx728vIIeoDfdu7cqTvvvFNXXHHFPnvyRo4cqQceeCCGlSFeMAQMOCS8EGPhwkjQC7eNG2t/X/PmkaAXDns9eti2KwzdArE3duxYXX/99bvvT5o0Sf3795dkC0IuvfRSrVy5UlOmTNlnANxbD2BOTg5DwA4gAAJJaOtWC3mLFlm4W7jQ2uLFNTdN3VO7dpGQl5sb%2Bbl1axZjAPGkpKRE69ev330/Oztb6enpKi8v12WXXaalS5fq448/VsuWLQ/qc5kD6A6GgIEEtXOntGSJhbzqbeFC2w%2BrNqmpdjJGbm7N1r27lJERu/oB1F1mZqYyMzNrPBYOf4sXL9Ynn3xy0OEPbiEAAnFs1y6bg7d4caQtWmS3q1bVPjdPkrKzLdR162a34ZDXvj3z84BkU1FRoUsuuUSzZs3S22%2B/rcrKSq1bt06S1KJFCzVu3NjnChFvGAIGfLZzp7R0qW2psmRJpC1eLK1YIVVV1f7eYNACXteuNcNe16705gEuWb58uTp16rTX5z755BMNGDDggD6HIWB30AMIxMDWrZGQt2dbvXrfPXlNm9qxRl27Rlo49B1%2BOHPzAEgdO3YU/Tk4GARAIAp27ZJWrrTh2qVLI7fh0Ldt277fn5lpIW/P1rWrlJVFyAMARBcBEDgAFRXSDz9YsFu%2B3IZmw0Fv%2BXLrxdvXUK1k59d26bL3Rk8eACCWCICApFDIFlWsXGnhbvly%2B3n58kjAq6jY92ekp0sdO9omyJ062W311rRp/X8PAAAOBAEQSc/zpA0bIgGv%2Bu2KFfbz/18st0%2BNGtkK2o4drXXqZC38M0O1ABJVQUGBCgoKVFlZ6XcpiBFWASOhVVZauFu9Wlqzxm7DbdWqyM/72vw4LD3dAl6HDpHWsWPktk0btk8BkNxYBewOegARlzxPKiqyeXdr19rtmjWR2/DPa9fuf2hWsp65rCwLeDk5dhtuOTkW8lq1ogcPAOAGAiBiqqLCzpxdv96GXdeujbQ97%2B/YcWCf2aCBhbt27Wzz43btLNRVv83OtiFcAABAAEQUlJXZMOyGDRbuNmywgBe%2Brd42bdr3nnd7Cgaltm0twLVtG2nZ2ZGwd8QRUkP%2BJAMAcMD4tYkaysulLVukzZstrG3aVPPnTZss5FVvZWUH999o0MC2PcnKstamjbXqP4dbkyb18z0BAHAZATAJVVVJJSV2%2BsS2bda2brVgt3VrpG3ZEgl74duSkrr9Nxs3llq3rtmOOGLvrVUrFlMAAOAnAmAcqaqStm%2B3EBa%2BLSmRiosjt%2BFWVBS53bbNbsM/Fxcf3DDrngIBqXlzqWVLC2vh21atrOcufFu9ZWaygAIAgERBAIyBSZOkceOk0tK9t%2B3brR3sUOr%2BpKZakDvsMLut3lq0sBYOei1a2G3LlvZ6eugAAEheBMAY%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%2B/y0Ecauh3AQAAIDrefvttDR06VGVlZWrTpo0mT56sVq1a1fr6UCikUCi0%2B35xcXEsykQcoAcQAIAEM3bsWGVkZOxu06dPlySdfvrpmjNnjj777DP95Cc/0WWXXaYNGzbU%2BjkjR45UMBjc3XJycmL1FeAz5gACAJBgSkpKtH79%2Bt33s7OzlZ6e/qPXde3aVddee63uuuuuvX7O3noAc3JymAPoAIaAAQBIMJmZmcrMzNzv6zzPqxHw9pSamqrU1NRoloYEQQAEACDBlZaW6uGHH9aQIUPUpk0bbd68WX/5y1%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%3D'}
Genus 2 curve data - 4225.a.274625.1