data:
- - Lhash: '1553674325109728329'
    abs_disc: 253125
    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: '[[3,[1]],[5,[1]]]'
    bad_primes:
    - 3
    - 5
    class: 50625.a
    cond: 50625
    disc_sign: 1
    end_alg: Q
    eqn: '[[-1,0,0,0,0,1],[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
    id: 12759
    igusa_clebsch_inv: '[''0'',''0'',''0'',''324'']'
    igusa_inv: '[''0'',''0'',''0'',''0'',''253125'']'
    is_gl2_type: false
    is_simple_base: true
    is_simple_geom: true
    label: 50625.a.253125.1
    leading_coeff:
      __RealLiteral__: 0
      data: '1.96199322672080862605992473433946946214820104636342'
      prec: 173
    locally_solvable: true
    modell_images:
    - 2.36.1
    - 3.6480.5
    mw_rank: 1
    mw_rank_proved: true
    non_solvable_places: []
    num_rat_pts: 3
    num_rat_wpts: 1
    real_geom_end_alg: C x C
    real_period:
      __RealLiteral__: 0
      data: '5.1751222199913060677920247404'
      prec: 100
    regulator:
      __RealLiteral__: 0
      data: '0.189560086054'
      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: 2
    torsion_order: 1
    torsion_subgroup: '[]'
    two_selmer_rank: 1
    two_torsion_field:
    - 5.1.162000.1
    - - 13
      - -1
      - 4
      - 4
      - -1
      - 1
    - - 5
      - 3
    - false
- - 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
    id: 23010
    is_simple_base: true
    is_simple_geom: true
    label: 50625.a.253125.1
    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
- - id: 12758
    label: 50625.a.253125.1
    mw_gens:
    - - - - 1
          - 1
        - - 0
          - 1
        - - 1
          - 1
      - - - 0
          - 1
        - - 1
          - 1
        - - 0
          - 1
        - - 0
          - 1
    mw_gens_v: true
    mw_heights:
    - __RealLiteral__: 0
      data: '0.18956008605378451053614960347031'
      prec: 113
    mw_invs:
    - 0
    num_rat_pts: 3
    rat_pts:
    - - 1
      - -1
      - 1
    - - 1
      - 0
      - 0
    - - 1
      - 0
      - 1
    rat_pts_v: true
- - conductor: 50625
    id: 13246
    lmfdb_label: 50625.a.253125.1
    modell_image: 2.36.1
    prime: 2
  - conductor: 50625
    id: 13247
    lmfdb_label: 50625.a.253125.1
    modell_image: 3.6480.5
    prime: 3
- - cluster_label: c5_1~5
    id: 107954
    label: 50625.a.253125.1
    p: 3
    tamagawa_number: 1
  - cluster_label: c5_1~4
    id: 107955
    label: 50625.a.253125.1
    p: 5
    tamagawa_number: 2
- - id: 12759
    label: 50625.a.253125.1
    plot: 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wEQAC4hvPnzdq94mIT%2BD744NLjWQYPdnfr3n03x7MAiGwEQAC4iONIu3a5U7olJVJZmfc1PXu6HT6OZwEQbQiAACDp2DH3eJaiImn/fu94mzZSVpYb%2Bnr18qdOAGgIBEAAVvryS2nVKrfLt2mTd7x5c2nkSHfjxpAhUny8P7UCQEMjAAKwQm2ttHmzG/hWrjRn9NV1551uh2/0aKlVK39qBYDGRgAEELP27nU3bixZIp044R3v2tXt8GVlSbfc4kuZANDkrA6AwWBQwWBQoVDI71IANIDTp806vnDo27XLO56SIo0b53b5%2BvbleBYAdopzHMfxuwi/lZeXKxAIqKysTKmpqX6XA%2BA6VVebI1nC07rr1nmvWYuPl%2B66y711Y9gws7YPAGxndQcQQHS5nmvW%2BvZ1p3XHjZP4Ox0AXIoACCCiHTrkTule7Zq18CM93Z86ASCaEAABRJTwNWvh0Ld9u3c8Odns0M3JMYGPa9YAoP4IgAB8FQqZa9bC07qXu2ZtyBB3WnfkSK5ZA4CbRQAE0KQcR9q92w18S5ea3bt19ejhbtzgmjUAaHgEQACN7uRJcw5fOPTt3esdb9PGBL1w6OOaNQBoXARAAA2uqso9nqWwUNqwwXT%2Bwpo3l0aMcAPfV7/KNWsA0JQIgABumuNIO3a4Hb5lyy49niUjww18Y8dKrVv7UioAQARAADfoiy/cwFdUZI5rqatTJ/fGjexsc%2B0aACAyEAABXJdz56SVK91p3S1bvONJSdKYMW6Xj%2BNZACByEQABXJbjSNu2mbBXVCStWGFCYF0DB5rz%2BCZOlEaNMiEQABD5CIAALjhyxDute/GtG126mLAXPoQ5Lc2fOgEAN8fqABgMBhUMBhUKhfwuBfDFuXPSqlWmy3e5ad2WLc2GjXCXLyODaV0AiAVxjlP3cAY7lZeXKxAIqKysTKncHI8YFt6tW1goLV5srly7eFp30CAT%2BHJyuHUDAGKV1R1AwAbHj5t7dcNdvs8/946Hp3Vzc820bseO/tQJAGg6BEAgxtTUSGvWuF2%2B9eu9hzCHd%2Bvm5pouX//%2BTOsCgG0IgEAM2LPHhL3Fi6WSEqm83DuemWkCX26uNHo0u3UBwHYEQCAKVVaa2zbCoa%2B01Dvevr07rZuTY6Z5AQAIIwACUcBxpO3bpUWLzGPlSqm62h2Pjzd36%2BbmSpMmSYMHS82a%2BVcvACCyEQCBCHX6tNm8EQ59F2/e6N7dhL3cXGnCBCkQ8KdOAED0IQACEaK2Vtq0yYS9ggKzkaPuEZVJSdK4cW7o69OHzRsAgBtDAAR8dOKE2a1bUGDW8n3xhXe8b18T%2BCZNMjt3k5P9qRMAEFsIgEATqq2VNm40ga%2BgQFq71jwX1rq1lJVlAt/kyWaaFwCAhkYABBrZqVOmy5efb6Z3L%2B7yZWaasDd5srl5o0ULf%2BoEANiDAAg0MMeRtm2TFi40oe%2BDD7xr%2BVJSzI0bkyebTl96un%2B1AgDsRAAEGkBlpdmxm59vHgcPesczMkzgmzJFGjWKLh8AwF9WB8BgMKhgMKhQ3fYMcJ327JEWLDCdvmXLpKoqdyw52RzNkpdnQh9r%2BQAAkSTOcereEmqn8vJyBQIBlZWVKTU11e9yEKHOn5dWrzahb8ECaedO73iPHtLUqSbwjRvHjl0AQOSyugMIXMvp02bjxnvvmR9PnnTH4uPNpo2pU82jb1/O5QMARAcCIHCR3btN4Js/31y5dv68O9aunVnLN3Wq2cDRpo1/dQIAcKMIgLBeKCR9%2BKEJfPPnSzt2eMf79ZOmTzfr%2BUaMkBL4UwMAiHL8rwxW%2BvJLackSad480%2B2rezZfQoK5dWPaNPPo1cu/OgEAaAwEQFjj5EmzeePdd816vrNn3bHUVLN5Y/p0M8XL1C4AIJYRABHTDh40Xb533pGWL/ceyJyeLt1zj3mMGcPZfAAAexAAEXNKS6W33zaPdeu8Y3fcIc2YYULf4MHs2gUA2IkAiKgXvnrtrbfMY/t2dywuTrr7bulrXzPBj/V8AABIzfwuoCHNmTNHPXv2VFJSkoYMGaKVK1f6XRJuxObN0re%2BJXXsaB4PPyxt3ep5ieNIGzdKP/2p1KePNGCA9PzzJvwlJEg5OdJLL0mHDkmrVkk//jHhDwCAsJi5CeRvf/ubHn74Yc2ZM0cjR47U7373O/3hD3/Qjh071K1bt6t%2BLzeBRJDFi838bN171SQpKUnO/Pe0qX22/vu/pTfflD77zB1OTJRyc6V77zU7d9u2bdqyAQCIJjETAO%2B66y4NHjxYv/3tby88169fP82YMUOzZ8%2B%2B6vcSACNEKCT17CkdOHDZ4QMJPdT9/G45/2hcJyebHbv332/O6EtJacpiAQCIXjGxBrC6ulobNmzQk08%2B6Xk%2BJydHq1evvuT1VVVVqqrTYSovL7%2Bhn9dxHFVUVNzQ9%2BIyiouvGP4kKXB%2Br7Kbv6fkyeP1ta%2BZjl%2BrVmbMcaQb/BgBAJZKSUlRnKW7AWMiAB4/flyhUEidOnXyPN%2BpUycdOXLkktfPnj1bzz333E3/vBUVFQoEAjf9PqiHmhnSP27sAADgZtg88xcTATDs4hTvOM5lk/1TTz2lH/3oRxe%2BLi8vV3p6er1/vpSUFJWVlV1xfOjQoVp38TkkNyHS3%2B9G3vP0aXMw89/%2BJjnvv68CTbn6NyxeLA0f3mT1%2BfGekf5%2B4T8vBw4caLD/cEb6rznSf99Ew2fSGO8Z6e8XDZ%2BLbZ/zxZ9JisVrh2IiAHbo0EHx8fGXdPu%2B%2BOKLS7qCkpSYmKjExMSb/nnj4uKu%2Boc6Pj6%2BQf9mEenvd73vWVMjFRRIr71mrmGrrg6PTNbJ5H7q8eXOy39jZqbZ3tvI9fn9npH%2BfmGpqakN9r6R/muOht83UmR/Jo3xnpH%2BfmGR/LnY%2BDlLDfuZRKuYOAamRYsWGjJkiIqKijzPFxUV6e677/apKmnmzJlWvd/V3tNxpE2bpH/9V6lLF7PR9623TPjr31%2BaPVvat0/q8f4bUvv2l75Bhw7S6683Wn2R9J6R/n6NIdJ/zdHw%2B6ahRcOvOdLfrzFEw685GmpEDO0CDh8D89JLL2nEiBF6%2BeWX9fvf/17bt29X9%2B7dr/q97AJuPMeOSW%2B8Ib3yivcov06dpH/6J3PE34ABF93IceiQ9NJLCi1cqPUbN2rgT36ixH/9V6lz5yavH5fiz0vk4TOJTHwukYfPxBUTU8CS9OCDD%2BrEiRN6/vnndfjwYWVmZio/P/%2Ba4Q8NLxQyG3r/8Aezvq%2BmxjyfmGg6f488YmZyE670u69LF%2Bn553X%2B6adVMHu2Bj71lPlmRITExEQ9%2B%2ByzDbKMAg2DzyQy8blEHj4TV8x0AG8GfyNoGIcOSX/8o3ns2%2Bc%2BP2SI9Oij0je/yQHNAABEgpjpAMIftbXSkiXSb39rjmYJhczzbdqY6d3vfc9M8QIAgMhBAMQNKSuTXn1VmjNHKi11nx81Svrnf5buu8/c1AEAACIPARD1Uloq/frXJvxVVprnUlLMur5/%2BRezoxcAAEQ2AiCuyXGk5culF1%2BUFixwn8/IkJ54QvrWt6TWrf2rDwAA1E9MnAOIxhEKSW%2B%2BKQ0bJo0fb8JfXJw0dapUVCR99JHp%2BjV0%2BFuxYoWmTZumLl26KC4uTvPmzWvYnwBXVN9/94cPH9ZDDz2kPn36qFmzZvrhD3/YRJXapb6fy9tvv62JEyeqY8eOSk1N1YgRI7R48eImqtYO9f1MVq1apZEjR6p9%2B/ZKTk5W37599ctf/rKJqrXHzfz/4/3331dCQoIGDhzYiBVGDgIgLlFTY87t69dPeuABaf16KSnJhL2dO83tHdnZF53d14AqKys1YMAA/eY3v2mcnwBXVN9/91VVVerYsaOefvppDWC3T6Op7%2BeyYsUKTZw4Ufn5%2BdqwYYPGjx%2BvadOmadOmTY1cqT3q%2B5m0atVKjz/%2BuFasWKGdO3fqmWee0TPPPKOXX365kSu1y43%2B/6OsrEzf/va3lZWV1UiVRR6OgRHHwIRVV0t/%2BpP085%2B7x7i0bSs9/riZ6u3YselriouL0zvvvKMZM2Y0/U9uufr%2Bux83bpwGDhyo//qv/2rkyux2o38m%2BvfvrwcffFA/%2B9nPGqkye93oZ/L1r39drVq10p///OdGqsxu9flcvvGNb%2Bj2229XfHy85s2bp82bNzdBhf6yugMYDAaVkZGhoUOH%2Bl2Kr0Ihs6mjTx%2Bzg3ffPnNTxwsvSPv3S88/70/4A9AwamtrVVFRoXbt2vldCv5h06ZNWr16tcaOHet3KdZ75ZVXtHv3bj377LN%2Bl9KkrN4EMnPmTM2cOfNCB9A2jmPW9T35pLRjh3muUyfz9Q9%2BwDEuQKx48cUXVVlZqQceeMDvUqx366236tixYzp//rxmzZql73//%2B36XZLVPP/1UTz75pFauXKmEK15PFZvs%2BtXigs2bpf/1v6Rly8zX7dqZ4DdzptSypa%2BlAWhAc%2BfO1axZs/Tuu%2B8qLS3N73Kst3LlSp05c0Zr1qzRk08%2Bqdtuu03f/OY3/S7LSqFQSA899JCee%2B459e7d2%2B9ymhwB0DInT0pPPy397nemA5iUJP3wh9JPfmJu7wAQO/72t7/pe9/7nt58801lZ2f7XQ4k9ezZU5J0xx136OjRo5o1axYB0CcVFRVav369Nm3apMcff1ySWS7hOI4SEhJUWFioCRMm%2BFxl4yEAWsJxpNdfl370I%2Bn4cfPcgw9K//EfUrdu/tYGoOHNnTtXjz76qObOnau8vDy/y8FlOI6jqqoqv8uwVmpqqrZt2%2BZ5bs6cOSopKdHf//73C2E9VhEALXDwoPTYY9KiRebr/v2lYFCK1LXHZ86c0a5duy58vWfPHm3evFnt2rVTN9Jqo7rWv/unnnpKn3/%2BuV577bULrwnvljtz5oyOHTumzZs3q0WLFsrIyGjy%2BmNVfT%2BXuXPn6tvf/rZ%2B9atfafjw4Tpy5IgkKTk52cr1zo2hvp9JMBhUt27d1LdvX0nmXMBf/OIXeuKJJ3ypP1bV53Np1qyZMjMzPd%2BflpampKSkS56PSQ6csrIyR5JTVlbmdykNbu5cx2nTxnEkx0lMdJyf/9xxqqv9rurqli5d6ki65PHII4/4XVrMu9a/%2B0ceecQZO3as53su9/ru3bs3ee2xrL6fy9ixY/kz1Mjq%2B5n8%2Bte/dvr37%2B%2B0bNnSSU1NdQYNGuTMmTPHCYVC/vwCYtSN/DesrmeffdYZMGBA0xTrM84BVGyeA/jll%2Bbsvj/%2B0Xw9bJg54%2B8ff/kEAAAWs/ocwFh14IA0apQJf3Fx0v/5P9KqVYQ/AABgsAYwxmzaJOXlSYcPSx06SHPnmmvbAAAAwgiAMWTVKmnKFKmiQsrMNIc8d%2B/ud1UAACDSMAUcI9askSZNMuFv7FgTBgl/AADgcugAxoBdu6SpU6XKSikrS5o/n9s8AADAldEBjHJnz0pf%2B5p04oT01a9K775L%2BAMAAFdndQAMBoPKyMjQ0KFD/S7lhv30p9JHH0mdOpnw16qV3xUBAIBIxzmAit5zALdskQYNMte8FRSYNYAAAADXYnUHMNo9%2B6wJfw88QPgDAADXjw6gorMDePCg1K2bCYA7dkj9%2BvldEQAAiBZ0AKPUvHkm/I0aRfgDAAD1QwCMUqtXmx%2BZ%2BgUAAPVFAIxSu3ebHzMy/K0DAABEHwJglPryS/Nj69b%2B1gEAAKIPATBKhfeqnDzpbx0AACD6EACjVN%2B%2B5sfNm/2tAwAARB8CYJQaM8b8%2BN57ZjcwAADA9SIARqnp06WkJGn7dmnFCr%2BrAQAA0YQAGKXatJG%2B8x3zzz/9qVRb62s5AAAgihAAo9gzz0itWpkzAV96ye9qAABAtLA6AAaDQWVkZGjo0KF%2Bl3JDunaV/t//M//84x9LGzb4Ww8AAIgO3AWs6LwLOKy21qwHXLhQ6tLFdAO7d/e7KgAAEMms7gDGgmbNpDfekPr3lw4dkrKzpQMH/K4KAABEMgJgDAgEpEWLpJ49pV27pNGjpU8%2B8bsqAAAQqQiAMeLWW6Vly6Tbb5f27ZNGjJBKSvyuCgAARCICYAzp1k1atUoaPlw6dUrKyZFeeIGDogEAgBcBMMakpZnO38MPS6GQ9G//Jk2dKh096ndlAAAgUhAAY1BysvSnP0m//a2UmCjl50t33CG99ZbflQEAgEhAAIxRcXHSv/yLtG6dCX/Hjkn33Sfde6/0%2Bed%2BVwcAAPxEAIxxd9xhQuDTT0sJCdLbb0v9%2Bkn/%2BZ9STY3f1QEAAD8QAC2QmCj93/8rrV8v3XWXVFFhbg65806poIBNIgA8o3UuAAAYP0lEQVQA2IYAaJEBA8xNIb//vdShg/Txx9KUKWa38MaNflcHAACaCgHQMs2aSd//vvTpp6YL2KKFVFwsDRkiPfigCYUAACC2EQAt1aaN9ItfmMD30EPmuf/%2Bb3Ol3MMPc5MIAACxzOoAGAwGlZGRoaFDh/pdim969jR3CW/ZIt1zj1RbK73%2Butko8o1vSFu3%2Bl0hAABoaHGOwxaA8vJyBQIBlZWVKTU11e9yfLVhg/T889L8%2Be5zU6aYA6XHjDHHywAAgOhmdQcQlxoyRHr3XWnzZumBB8yawfx8adw4s4P4r3/l%2BBgAAKIdHUDRAbyaXbukF1%2BUXn1VOnfOPHfrrdLjj5vNJO3b%2B1oeAAC4AQRAEQCvx7Fj0pw5UjBo/lmSkpLMBpLHH5cGDfK3PgAAcP0IgCIA1se5c2Ya%2BFe/MtPEYcOHS//jf0j332/uIgYAAJGLACgC4I1wHOn9901H8K233HWBbdtK3/629Nhj5kgZAAAQeQiAIgDerKNHpT/%2BUXr5ZWnfPvf5u%2B%2BWvvc9s5mkdWv/6gMAAF4EQBEAG0ooJBUWmiD43nvma8mEv/vvlx59VBo5kqNkAADwGwFQBMDGcPiw9NprpjP46afu8716SY88Ym4b6dHjGm8S/q1JYgQAoEFF/TmAb7/9tnJzc9WhQwfFxcVpc92dCfBN587ST35irpRbuVL67ndNJ3D3bulnPzM3kIwdK/3hD9Lp0xd984oV5vTp5s3NIy9PWrXKl18HAACxKOo7gH/%2B85%2B1Z88edenSRY899pg2bdqkgQMH1us96AA2jcpKs2HktdekkhK3wZeYKE2bJv3TP0l5595S82896M4fhyUkSG%2B%2BKc2Y0fSFAwAQY6I%2BAIbt3btXPXv2JABGiQMHpL/8Rfrzn6Xt281zCarRwbh0dXKOXv6bunQxu0wSEpquUAAAYlDUTwHfiKqqKpWXl3seaFrp6WaKeNs2aeNG6cc/lh5qt/jK4U%2BSDh2SioubrkgAAGKUlQFw9uzZCgQCFx7p6el%2Bl2StuDhzi8gvfiG98h/Hrvn6z9YeU2z0rAEA8E9UBcA33nhDrVu3vvBYuXLlDb3PU089pbKysguPAwcONHCluBHN%2Bve75msemNVPvXpJ//Zv0vr1IgwCAHADomoNYEVFhY4edacIu3btquR/3DvGGsAYMXiwtGnTZYd2t/2q7qxap7Nn3ed69JDuvVe67z5p2DCpWVT9lQYAAH9E1f8uU1JSdNttt114JHPpbOyZO1fq2vXS59PT1WvtX/TFF2Yz8P33Sy1bSnv3Si%2B%2BKI0YIXXvLv3P/yktX37pJmIAAOCKqg7g5Zw8eVL79%2B/XoUOHlJeXp7/%2B9a/q06ePbrnlFt1yyy3X9R50ACPM6dPSq69KixaZRYKTJknf%2BY4UCHhedvasVFAg/f3v0sKFUkWFO9axo3TPPdLXvy5NmGCOmgEAAEbUB8BXX31V3/3udy95/tlnn9WsWbOu6z0IgNHv3DlzDd1bb5lr6E6dcsdSUqSpU80RgpMnm68BALBZ1AfAhkAAjC01NWYa%2BK23pHffNdfShbVoIWVlmTA4fbp0nU1iAABiCgFQBMBYVlsrrV0rzZsnvfOO917iuDjprrvMVPE990h9%2B3LtMADADgRAEQBt4TjSzp0mDM6bJ61b5x2/7TbTFZw%2BXRo5kgtHAACxiwAoAqCtDh2S5s8308QlJVJ1tTvWtq00ZYq5o3jSpEv2nwAAENUIgCIAwuwgXrzYBMKFC6WTJ92xhARpzBgTBqdONZ1CAACiGQFQBEB4nT8vffCBCYMLFkgff%2Bwd79vXBMG8PDNV3Ly5P3UCAHCjCIAiAOLqdu1yO4MrVpiAGBYISLm5JgxOnmzOHwQAINIRAEUAxPUrKzNTxQsWmEOojx93x%2BLipOHDzdrBvDxp4EB2FQMAIpPVATAYDCoYDCoUCqm0tJQAiHoJhaQPPzRhcOFCacsW73jnzqYrOGWKlJ3NRhIAQOSwOgCG0QFEQzh40HQFFy6Uioulykp3LCFBGjXKhMHJk6X%2B/ekOAgD8QwAUARANr6rKrBdcuNCEwtJS73h6utsdnDCB6%2BkAAE2LACgCIBrf7t1Sfr55LFtm7i4Oa97cdAcnT6Y7CABoGgRAEQDRtM6eNXcV5%2Beb7uDu3d7xW281h09PmsTaQQBA4yAAigAIf336qQmCBQWXdgfj46URI0xncNIks7O4WTPfSgUAxAgCoAiAiBxffmm6g4sWXX7tYFqaOXcwJ8c80tL8qRMAEN0IgCIAInLt2WPC4KJF5r7iM2fcsbg4afBgEwhzc02nkFtJAADXgwAoAiCiQ3W1tHq1GwgvPncwJUXKynIDYc%2Be/tQJAIh8BEARABGdDh%2BWCgvNzSRFRd5bSSTp9tvNNHFurjR%2BvNS6tT91AgAiDwFQBEBEv9paaeNG0xksLDSdwlDIHW/eXLr7bnf94KBBbCYBAJsRAEUAROwpK5OWLjXdwcWLzVrCujp0kCZOdDeTdOniT50AAH8QAEUARGxzHGnXLtMZLCy8dDOJJGVmumFw9GipZUt/agUANA0CoAiAsEtNjfTBB24gXL/ehMSwxEQTAnNyTJfwzjuZLgaAWGN1AAwGgwoGgwqFQiotLSUAwkonTkjFxW4gPHjQO96pk7mRJBwIO3f2p04AQMOxOgCG0QEEDMeRPvnErBssLDQ3k5w9631NeLp44kRpzBimiwEgGhEARQAEriR89mC4O7hxo3e6uEULadQod0MJV9UBQHQgAIoACFyv48fNJpLCQnP24P793vEOHcxh1BMnmke3bv7UCQC4OgKgCIDAjQhPFxcVmcfSpZfuLu7Tx3QGs7OlceMk/ngBQGQgAIoACDSEmhppzRo3EH74oTmgOiwhQRo%2B3ITBiROlYcPMcwCApkcAFAEQaAynT5vp4nAg3L3bO56aKk2YYMJgdra5ui4uzp9aAcA2BEARAIGmsGePGwaXLJFOnfKOd%2Bvmrh3MyjLrCQEAjYMAKAIg0NRCIbOjOBwIV682O47rGjTI3V08cqSUlORPrQAQiwiAIgACfquslFasMAdSFxVJ27Z5x5OSzO0k4QOpuZ0EAG4OAVAEQCDSHDlipokLC00oPHTIO96xo3vcTHY2x80AQH0RAEUABCKZ40g7d7rTxcuWmY5hXb17u2Fw/HgpEPClVACIGgRAEQCBaFJdLa1d6wbCdevMmsKw%2BHhzxEz4uJm77jI3lgAAXARAEQCBaFZWZg6hLioy08Wlpd7x1q2lsWPdHcb9%2BnHcDABYHQCDwaCCwaBCoZBKS0sJgEAM2L/fe9zM8ePe8S5dTHcw/Ojc2Z86AcBPVgfAMDqAQGyqrZW2bHF3F69cKZ07531NZqY7XTxmjOkYAkCsIwCKAAjY4tw56f333Q7hpk1mk0lY8%2BbSiBHudPGQIVxXByA2EQBFAARsdfy4ua4u3CHcu9c7Hgh4r6u77TbWDwKIDQRAEQABmE7g7t1uGCwpMfcZ19W9uztdzHV1AKIZAVAEQACXCoWkDRvc3cXvvy/V1HhfM2iQuZkkO1saNYrr6gBEDwKgCIAArq3udXWFhdJHH3nHw9fVhdcPcl0dgEhGABQBEED9HTniThdf7bq68JQx19UBiCQEQBEAAdyci6%2BrW75cOnPG%2B5rwdXUTJ5rr6vhPDQA/EQBFAATQsOpeV1dcLH344aXX1d11l%2BkO5uSYq%2BuaN/evXgD2IQCKAAigcZ0%2Bba6rC68f3LXLO56SYrqC4Q5h794cNwOgcREARQAE0LT27nXXDy5ZIp044R1PT3fDYFaWWU8IAA2JACgCIAD/1NaaG0nC6wdXrTJTyHUNGuQGQo6bAdAQCIAiAAKIHGfPmjuLw4Fw61bveFKSubO47nEzTBcDqC%2BrA2AwGFQwGFQoFFJpaSkBEEDEudZxM2lp7maSiROlLl38qRNAdLE6AIbRAQQQDRxH2rHDhMHCQnPczNmz3tdkZLhhcOxYqVUrf2oFENkIgCIAAohOVVXSBx%2B4gXDDBhMSw5o3N2sGJ040oXDQIG4nAWAQAEUABBAbTpyQSkpMGCwqkvbt8463b292FYc7hNxOAtiLACgCIIDY4zjmvMFwGCwpkSoqvK/p08eEwZwcadw4qXVrX0oF4AMCoAiAAGJfTY17O0lhobmdpLbWHW/eXBoxwg2EgwebG0sAxCYCoAiAAOxz6pS5naSw0Dz27PGOt2vnThfn5DBdDMQaAqAIgACwe7cbBktKpPJy73jfvm4YHDuW6WIg2hEARQAEgLrOnzfTxeH1g2vXXjpdPHKkGwjZXQxEHwKgCIAAcDWnT7u7iy83Xdyhg3sYdW4uh1ED0SCqA2BNTY2eeeYZ5efn67PPPlMgEFB2drb%2B/d//XV3q8V8gAiAAXB/HuXS6%2BOLdxZmZbndwzBgpOdmfWgFcWVQHwLKyMt1333167LHHNGDAAJ06dUo//OEPdf78ea1fv/6634cACAA3pqZGWrPGhMHFi6X1672HUScmmhAY7g5mZnJ3MRAJojoAXs66des0bNgw7du3T92uc9saARAAGsaJE9KSJSYMFhZKBw96xzt3dsNgdrbUsaM/dQK2i7kAWFxcrJycHJ0%2BffqKYa6qqkpVVVUXvi4vL1d6ejoBEAAakONIO3e63cHly6Uvv3TH4%2BLMeYO5ueYxYoTZYAKg8cVUADx37pxGjRqlvn376vXXX7/i62bNmqXnnnvukucJgADQeM6dk1atcgPh1q3e8ZQUafx4EwYnTZK%2B8hV/6gRsEFUB8I033tAPfvCDC18XFBRo9OjRksyGkPvvv1/79%2B/XsmXLrhrk6AACgP8OH3bDYFGRdPy4d7xXL7c7OGECZw8CDSmqAmBFRYWOHj164euuXbsqOTlZNTU1euCBB/TZZ5%2BppKRE7du3r9f7sgYQAPxVWytt2uSuHXz/fXMeYVj47MFwIBwwgLMHgZsRVQHwcsLh79NPP9XSpUvV8QZWFBMAASCyVFSYI2YWLzaPzz7zjnfq5G4myclhMwlQX1EdAM%2BfP697771XGzdu1IIFC9SpU6cLY%2B3atVOLFi2u630IgAAQ2XbtcsNgSYlUWekdHzLErBvMzZWGD2czCXAtUR0A9%2B7dq549e152bOnSpRo3btx1vQ8BEACiR3W1mSJevFhatEjassU7npoqZWW5gbB7d3/qBCJZVAfAhkIABIDodeSI2x0sLDRnEdbVt68Jg5MmcTMJEEYAFAEQAGJFKCRt3Gg6g4sWmVtKamvd8aQkadw4NxD27s3NJLATAVAEQACIVadOmZtJFi0yHcKLbybp0cNME0%2BebI6aSUnxpUygyREARQAEABs4jrR9u7t2cMUKs54wLCFBGjXK7Q7eeSfdQcQuAqAIgABgo8pKaelSd7p4927veJcubhjMzpbatvWnTqAxEABFAAQAmKNmCgpMGFy61HtvcbNm5q7iSZPMdPGgQRxEjehGABQBEADgde6ctHKlCYMFBdLOnd7xtDS3O5iTI9XzAirAdwRAEQABAFe3b58bBpcskc6cccfi4qRhw0xncMoUcyg13UFEOqsDYDAYVDAYVCgUUmlpKQEQAHBN4YOoCwrM46OPvOMdOrg7i3NzzddApLE6AIbRAQQA3KiDB93uYHGxVF7ujtEdRKQiAIoACABoGDU10urVbndw61bveMeO3u4gawfhFwKgCIAAgMbx%2BeduGCwqkioq3LFmzaS77nK7g%2BwsRlMiAIoACABofDU13rWD27Z5xzt1MruKp0wxO4vbtPGnTtiBACgCIACg6R08KOXnu2sH6%2B4sjo835w7m5ZlAeMcd3EqChkUAFAEQAOCv6mpp1SoTCPPzLz13sGtXM1WclydlZXFnMW4eAVAEQABAZNm71w2DJSXeW0maN5fGjHG7g7170x1E/REARQAEAESuc%2BekZcvcQHjxncVf%2BYoJgnl50rhxUlKSH1Ui2hAARQAEAESP0lITBBculFasMNPHYS1bShMmuN3Bbt38qxORjQAoAiAAIDqdOWOuplu40ITCzz/3jmdmmjCYl2c2lSQk%2BFMnIg8BUARAAED0cxxz8PTCheaxZo1UW%2BuOt21rDp/OyzPHzXBFnd0IgCIAAgBiz4kT0uLFJgwuWiSdPOmOxcVJw4ebMDh1qnTnnWwksQ0BUARAAEBsC4WktWtNGFyw4NIr6m691awZnDrVrCFs1cqfOtF0rA6AwWBQwWBQoVBIpaWlBEAAgBUOHHA3kixZIp09644lJkrjx5swmJcn9ejhW5loRFYHwDA6gAAAW4WPmVmwwATCvXu94/37mzA4daqZNmYjSWwgAIoACACAZDaS7NjhhsHVq830cVi7dmYDybRpZkNJ27b%2B1YqbQwAUARAAgMs5dcpsIFmwwNxZfOqUOxYfL40a5XYH%2B/RhI0k0IQCKAAgAwLWcPy998IEJgwsWmE5hXb16uWFwzBipRQt/6sT1IQCKAAgAQH3t2eOGwWXLvDeSpKSYKeJp06TJk6WOHX0rE1dAABQBEACAm3HmjFRUJL33ntldfPSoOxYXZ24hmTbNdAf792eqOBIQAEUABACgodTWSuvXmzC4YIG0ebN3vEcPEwanTZPGjmWq2C8EQBEAAQBoLAcOuFPFS5ZIVVXuWN2p4ilTuJ6uKREARQAEAKApVFZKxcVud7DuVHGzZtLdd5tp4unTpb59mSpuTARAEQABAGhqdaeK33tP2rLFO96rl%2BkMTp9ujptp3tyfOmMVAVAEQAAA/LZ/v%2BkKzp8vLV3q3VXcpo2ZIp42zRxE3aaNf3XGCgKgCIAAAESSigqpsNB0BhculI4fd8cSEsw5g9Onm0fPnv7VGc0IgCIAAgAQqUIhac0aEwbnz5d27vSOZ2a6YXDoULOWENdmdQAMBoMKBoMKhUIqLS0lAAIAEOF27TJBcP58adUq713Ft9wi/e//Lf34x/7VFy2sDoBhdAABAIg%2BJ0%2Bag6fnzzd3FldUSC%2B8YEIgro4AKAIgAADRrrraXEnXv7/Utavf1US%2BBL8LAAAAuFktWkg5OX5XET1YKgkAAGAZAiAAAIBlCIAAAACWIQACAABYhgAIAABgGQIgAACAZQiAAAAAliEAAgAAWIYACAAAYBkCIAAAgGWsDoDBYFAZGRkaOnSo36UAAAA0mTjHcRy/i/BbeXm5AoGAysrKlJqa6nc5AAAAjcrqDiAAAICNCIAAAACWIQACAABYhgAIAABgGQIgAACAZQiAAAAAliEAAgAAWIYACAAAYJmoD4CzZs1S37591apVK7Vt21bZ2dlau3at32UBAABErKgPgL1799ZvfvMbbdu2TatWrVKPHj2Uk5OjY8eO%2BV0aAABARIq5q%2BDC17oVFxcrKyurXt/DVXAAAMAGCX4X0JCqq6v18ssvKxAIaMCAAVd8XVVVlaqqqi58XV5e3hTlAQAARISonwKWpAULFqh169ZKSkrSL3/5SxUVFalDhw5XfP3s2bMVCAQuPNLT05uwWgAAAH9F1RTwG2%2B8oR/84AcXvi4oKNDo0aNVWVmpw4cP6/jx4/r973%2BvkpISrV27VmlpaZd9n8t1ANPT05kCBgAAVoiqAFhRUaGjR49e%2BLpr165KTk6%2B5HW33367Hn30UT311FPX9b6sAQQAADaJqjWAKSkpSklJuebrHMfxdPgAAADgiqoAeLHKykr9/Oc/1/Tp09W5c2edOHFCc%2BbM0cGDB3X//ff7XR4AAEBEiuoAGB8fr48//lh/%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%2BtXeq2bjS/TAAAAAElFTkSuQmCC
label_cols:
- label
- label
- label
- lmfdb_label
- label
- label
labels:
- 50625.a.253125.1
- 50625.a.253125.1
- 50625.a.253125.1
- 50625.a.253125.1
- 50625.a.253125.1
- 50625.a.253125.1
tables:
- g2c_curves
- g2c_endomorphisms
- g2c_ratpts
- g2c_galrep
- g2c_tamagawa
- g2c_plots
timestamp: '2024-04-25T09:19:44.215294'