Embedded newform data - 3024.2.df.e.1601.3

Formats: - HTML - YAML - JSON - 2025-09-08T02:08:59.985770

• mf_newforms •

  Column	Type
  Nk2	integer
  analytic_conductor	double precision
  analytic_rank	smallint
  analytic_rank_proved	boolean
  artin_degree	integer
  artin_field	numeric[]
  artin_field_label	text
  artin_image	text
  atkin_lehner_eigenvals	integer[]
  atkin_lehner_string	text
  char_conductor	integer
  char_degree	integer
  char_is_minimal	boolean
  char_is_real	boolean
  char_orbit_index	smallint
  char_orbit_label	text
  char_order	integer
  char_parity	smallint
  char_values	jsonb
  cm_discs	integer[]
  conrey_index	integer
  dim	integer
  embedded_related_objects	text[]
  field_disc	numeric
  field_disc_factorization	numeric[]
  field_poly	numeric[]
  field_poly_is_cyclotomic	boolean
  field_poly_is_real_cyclotomic	boolean
  field_poly_root_of_unity	integer
  fricke_eigenval	smallint
  has_non_self_twist	smallint
  hecke_cutters	jsonb
  hecke_orbit	integer
  hecke_orbit_code	bigint
  hecke_ring_generator_nbound	integer
  hecke_ring_index	numeric
  hecke_ring_index_factorization	numeric[]
  hecke_ring_index_proved	boolean
  inner_twist_count	integer
  inner_twists	integer[]
  is_cm	boolean
  is_largest	boolean
  is_maximal	boolean
  is_polredabs	boolean
  is_rm	boolean
  is_self_dual	boolean
  is_self_twist	boolean
  is_twist_minimal	boolean
  label	text
  level	integer
  level_is_powerful	boolean
  level_is_prime	boolean
  level_is_prime_power	boolean
  level_is_prime_square	boolean
  level_is_square	boolean
  level_is_squarefree	boolean
  level_primes	integer[]
  level_radical	integer
  minimal_twist	text
  nf_label	text
  prim_orbit_index	smallint
  projective_field	numeric[]
  projective_field_label	text
  projective_image	text
  projective_image_type	text
  qexp_display	text
  related_objects	text[]
  relative_dim	integer
  rm_discs	integer[]
  sato_tate_group	text
  self_twist_discs	integer[]
  self_twist_type	smallint
  space_label	text
  trace_display	numeric[]
  trace_hash	bigint
  trace_moments	numeric[]
  trace_zratio	numeric
  traces	numeric[]
  weight	smallint
  weight_parity	smallint

  
  {'Nk2': 12096, 'analytic_conductor': 24.14676157123519, 'analytic_rank': 0, 'analytic_rank_proved': True, 'char_conductor': 63, 'char_degree': 2, 'char_is_minimal': False, 'char_is_real': False, 'char_orbit_index': 84, 'char_orbit_label': 'df', 'char_order': 6, 'char_parity': 1, 'char_values': [3024, 6, [1135, 757, 785, 2593], [6, 6, 5, 1]], 'cm_discs': [], 'conrey_index': 17, 'dim': 48, 'has_non_self_twist': 1, 'hecke_cutters': [[5, [-6476, 220260, -2383875, 11529738, -25983819, 19294080, 23713832, -47326098, 6433746, 33359910, -15323967, -11791020, 8008817, 2387970, -2188401, -287724, 357756, 20280, -36005, -768, 2175, 12, -72, 0, 1]]], 'hecke_orbit': 5, 'hecke_orbit_code': 18020102259608528, 'inner_twist_count': 2, 'inner_twists': [[1, 1, 1, 1, 1, 1, 1], [1, 1, 63, 19, 1, 6, 0]], 'is_cm': False, 'is_largest': True, 'is_maximal': False, 'is_rm': False, 'is_self_dual': False, 'is_self_twist': False, 'is_twist_minimal': False, 'label': '3024.2.df.e', 'level': 3024, 'level_is_powerful': False, 'level_is_prime': False, 'level_is_prime_power': False, 'level_is_prime_square': False, 'level_is_square': False, 'level_is_squarefree': False, 'level_primes': [2, 3, 7], 'level_radical': 42, 'minimal_twist': '504.2.bs.a', 'prim_orbit_index': 19, 'related_objects': [], 'relative_dim': 24, 'rm_discs': [], 'sato_tate_group': '1.2.3.c6', 'self_twist_discs': [], 'self_twist_type': 0, 'space_label': '3024.2.df', 'trace_display': [0, 0, 0, 0], 'traces': [48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 48, 0, 0, 0, -18, 0, -18, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 0, 6, 0, 0, 0, 18, 0, -12, 0, 0, 0, 12, 0, 0, 0, 0, 0, 0, 0, 18, 0, 0, 0, 36, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 12, 0, -6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 18, 0, -6, 0, 0, 0, -54, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -48, 0, 0, 0, 0, 0, 78, 0, 0, 0, 0, 0, -36, 0, -48, 0, 0, 0, -72, 0, -12, 0, 0, 0, -60, 0, -6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 18, 0, 0, 0, 0, 0, -24, 0, 0, 0, -48, 0, 36, 0, 0, 0, 48, 0, 0, 0, 0, 0, 90, 0, 12, 0, 0, 0, 72, 0, 6, 0, 0, 0, -36, 0, 0, 0, 0, 0, -24, 0, 0, 0, 0, 0, 36, 0, -12, 0, 0, 0, 0, 0, 0, 0, 0, 0, 60, 0, 30, 0, 0, 0, 42, 0, 0, 0, 0, 0, 60, 0, -6, 0, 0, 0, -24, 0, 18, 0, 0, 0, 108, 0, 0, 0, 0, 0, 0, 0, 18, 0, 0, 0, 144, 0, 0, 0, 0, 0, -96, 0, 108, 0, 0, 0, -36, 0, 0, 0, 0, 0, -144, 0, 60, 0, 0, 0, 0, 0, 0, 0, 0, 0, -36, 0, 0, 0, 0, 0, 0, 0, -12, 0, 0, 0, -156, 0, 18, 0, 0, 0, 150, 0, -36, 0, 0, 0, 84, 0, -12, 0, 0, 0, 60, 0, 18, 0, 0, 0, 36, 0, 0, 0, 0, 0, 0, 0, -36, 0, 0, 0, 30, 0, 36, 0, 0, 0, 0, 0, 0, 0, 0, 0, -90, 0, -36, 0, 0, 0, 180, 0, 18, 0, 0, 0, 54, 0, 114, 0, 0, 0, 42, 0, -54, 0, 0, 0, 120, 0, 0, 0, 0, 0, -60, 0, 12, 0, 0, 0, 216, 0, 0, 0, 0, 0, -144, 0, -48, 0, 0, 0, -276, 0, -48, 0, 0, 0, -168, 0, -60, 0, 0, 0, 0, 0, 0, 0, 0, 0, -126, 0, -54, 0, 0, 0, 0, 0, 60, 0, 0, 0, -240, 0, -144, 0, 0, 0, 114, 0, 54, 0, 0, 0, 60, 0, 36, 0, 0, 0, 54, 0, 6, 0, 0, 0, 204, 0, 0, 0, 0, 0, -54, 0, 0, 0, 0, 0, -72, 0, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, -126, 0, -6, 0, 0, 0, 138, 0, -18, 0, 0, 0, 78, 0, -114, 0, 0, 0, -60, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 84, 0, -54, 0, 0, 0, 120, 0, 0, 0, 0, 0, -138, 0, -108, 0, 0, 0, -336, 0, 36, 0, 0, 0, -216, 0, -18, 0, 0, 0, 0, 0, 0, 0, 0, 0, -48, 0, 54, 0, 0, 0, 0, 0, -108, 0, 0, 0, -234, 0, 162, 0, 0, 0, 222, 0, -18, 0, 0, 0, 108, 0, -42, 0, 0, 0, 72, 0, -30, 0, 0, 0, 90, 0, 0, 0, 0, 0, -162, 0, 0, 0, 0, 0, -48, 0, -36, 0, 0, 0, 0, 0, -54, 0, 0, 0, -198, 0, 30, 0, 0, 0, 54, 0, 12, 0, 0, 0, 156, 0, 12, 0, 0, 0, -246, 0, 18, 0, 0, 0, 180, 0, 0, 0, 0, 0, 18, 0, 36, 0, 0, 0, 306, 0, 0, 0, 0, 0, -102, 0, 216, 0, 0, 0, -396, 0, -144, 0, 0, 0, -324, 0, 90, 0, 0, 0, 0, 0, -126, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -60, 0, 0, 0, -216, 0, 108, 0, 0, 0, 312, 0, -12, 0, 0, 0, 276, 0, -24, 0, 0, 0, 42, 0, 54, 0, 0, 0, -210, 0, 0, 0, 0, 0, -96, 0, -126, 0, 0, 0, 180, 0, 36, 0, 0, 0, 0, 0, 36, 0, 0, 0, 108, 0, -42, 0, 0, 0, 180, 0, -12, 0, 0, 0, 96, 0, 72, 0, 0, 0, -144, 0, 54, 0, 0, 0, 252, 0, 0, 0, 0, 0, -84, 0, -30, 0, 0, 0, 276, 0, 0, 0, 0, 0, -264, 0, -132, 0, 0, 0, -168, 0, 24, 0, 0, 0, -96, 0, -120, 0, 0, 0, 0, 0, 72, 0, 0, 0, -108, 0, -252, 0, 0, 0, 0, 0, 120, 0, 0, 0, -372, 0, -162, 0, 0, 0, 306, 0, 66, 0, 0, 0, 120, 0, -36, 0, 0, 0, 216, 0, -18, 0, 0, 0, 150, 0, 0, 0, 0, 0, 0, 0, 108, 0, 0, 0, 66, 0, 0, 0, 0, 0, 0, 0, 36, 0, 0, 0, 84, 0, -48, 0, 0, 0, 282, 0, -12, 0, 0, 0, 246, 0, -114, 0, 0, 0, 0, 0, -72, 0, 0, 0, 144, 0, 0, 0, 0, 0, -132, 0, -6, 0, 0, 0, 366, 0, 0, 0, 0, 0, -492, 0, -120, 0, 0, 0, -324, 0, -48, 0, 0, 0, -120, 0, -54, 0, 0, 0, 0, 0, -18, 0, 0, 0, -216, 0, 216, 0, 0, 0, 0, 0, -120, 0, 0, 0, -480, 0, 126, 0, 0, 0, 312, 0, 18, 0, 0, 0, 78, 0, -6, 0, 0, 0, 228, 0, -90, 0, 0, 0, 384, 0, 0, 0, 0, 0, -66, 0, 0, 0, 0, 0, 12, 0, -42, 0, 0, 0, 0, 0, -72, 0, 0, 0, -174, 0, 108, 0, 0, 0, 252, 0, 6, 0, 0, 0, 228, 0, -24, 0, 0, 0, 6, 0, 144, 0, 0, 0, -108, 0, 0, 0, 0, 0, -258, 0, 0, 0, 0, 0, 390, 0, 0, 0, 0, 0, -210, 0, 228, 0, 0, 0, -684, 0, -72, 0, 0, 0, -372, 0, 192, 0, 0, 0, 0, 0, -18, 0, 0, 0, -84, 0, 0, 0, 0, 0, 0, 0, 36, 0, 0, 0, -426, 0, 0, 0, 0, 0, 336, 0, -84, 0, 0, 0, 258, 0, -54, 0, 0, 0, 126, 0, 126, 0, 0, 0, 288, 0, 0, 0, 0, 0, -180, 0, -180, 0, 0, 0, 186, 0, 24, 0, 0, 0, 0, 0, -54, 0, 0, 0, 156, 0, -36, 0, 0, 0, 132, 0, 18, 0, 0, 0, 132, 0, 126, 0, 0, 0, -336, 0, -90, 0, 0, 0, 180, 0, 0, 0, 0, 0, -144, 0, -12, 0, 0, 0, 354, 0, 0, 0, 0, 0, -36, 0, -144, 0, 0, 0, -396, 0, 144, 0, 0, 0, -588, 0, -174, 0, 0, 0, 0, 0, 162, 0, 0, 0, 102, 0, -198, 0, 0, 0, 0, 0, 132, 0, 0, 0, -342, 0, -234, 0, 0, 0, 210, 0, 96, 0, 0, 0, 414, 0, 42, 0, 0, 0, 240, 0, -180, 0, 0, 0, -108, 0, 0, 0, 0, 0, -132, 0, 324, 0, 0, 0, 228, 0, -6, 0, 0, 0, 0, 0, 162, 0, 0, 0, 120, 0, -48, 0, 0, 0, 210, 0, -42, 0, 0, 0, 120, 0, -198, 0, 0, 0, -174, 0, -162, 0, 0, 0, 708, 0, 0, 0, 0, 0, -66, 0, 18, 0, 0, 0, 474, 0, 0, 0, 0, 0, -264, 0, -144, 0, 0, 0, -264, 0, 84, 0, 0, 0, -708, 0, -6, 0, 0, 0, 0, 0, -18, 0, 0, 0, -36, 0, 378, 0, 0, 0, 0, 0, -72, 0, 0, 0, -366, 0, 0, 0, 0, 0, 294, 0, -30, 0, 0, 0, 318, 0, 54, 0, 0, 0, 312, 0, -90, 0, 0, 0, 18, 0, 0, 0, 0, 0, 102, 0, 36, 0, 0, 0, 204, 0, -42, 0, 0, 0, 0, 0, -126, 0, 0, 0, -102, 0, 228, 0, 0, 0, 306, 0, -6, 0, 0, 0, 78, 0, -24, 0, 0, 0, 180, 0, 108, 0, 0, 0, 84, 0, 0, 0, 0, 0, -156, 0, 6, 0, 0, 0, 414, 0, 0, 0, 0, 0, -588, 0, 360, 0, 0, 0, -696, 0, 108, 0, 0, 0, -228, 0, 258, 0, 0, 0, 0, 0, 198, 0, 0, 0, -348, 0, 0, 0, 0, 0, 0, 0, 48, 0, 0, 0, -540, 0, 108, 0, 0, 0, 348, 0, -216, 0, 0, 0, 72, 0, -48, 0, 0, 0, 204, 0, 108, 0, 0, 0, 600, 0, 0, 0, 0, 0, -162, 0, -126, 0, 0, 0, 36, 0, 48, 0, 0, 0, 0, 0, 90, 0, 0, 0, -216, 0, -138, 0, 0, 0, 108, 0, 72, 0, 0, 0, 426, 0, 246, 0, 0, 0, -216, 0, -144, 0, 0, 0, -132, 0, 0, 0, 0, 0, 18, 0, 84, 0, 0, 0, 540, 0, 0, 0, 0, 0, -516, 0, -96, 0, 0, 0, -888, 0, -24, 0, 0, 0, -564, 0, -120, 0, 0, 0, 0, 0, 36, 0, 0, 0, -144, 0, -72, 0, 0, 0, 0, 0, 84, 0, 0, 0, -450, 0, -432, 0, 0, 0, 456, 0, 138, 0, 0, 0, 198, 0, 222, 0, 0, 0, 150, 0, -48, 0, 0, 0, -60, 0, 0, 0, 0, 0, -330, 0, 234, 0, 0, 0, 120, 0, -6, 0, 0, 0, 0, 0, 180, 0, 0, 0, -186, 0, -36, 0, 0, 0, 132, 0, -90, 0, 0, 0, 282, 0, -198, 0, 0, 0, -480, 0, -108, 0, 0, 0, 372, 0, 0, 0, 0, 0, 162, 0, -78, 0, 0, 0, 540, 0, 0, 0, 0, 0, 90, 0, -240, 0, 0, 0, -624, 0, 276, 0, 0, 0, -756, 0, -54, 0, 0, 0, 0, 0, -144, 0, 0, 0, 126, 0, 288, 0, 0, 0, 0, 0, -36, 0, 0, 0, -456, 0, 144, 0, 0, 0, 498, 0, -48, 0, 0, 0, 360, 0, -54, 0, 0, 0, 240, 0, 132, 0, 0, 0, -114, 0, 0, 0, 0, 0, -84, 0, 126, 0, 0, 0, 198, 0, -114, 0, 0, 0, 0, 0, -144, 0, 0, 0, 294, 0, 180, 0, 0, 0, 408, 0, 66, 0, 0, 0, 78, 0, 36, 0, 0, 0, -96, 0, 90, 0, 0, 0, 756, 0, 0, 0, 0, 0, -174, 0, 48, 0, 0, 0, 756, 0, 0, 0, 0, 0, -294, 0, 432, 0, 0, 0, -264, 0, -72, 0, 0, 0, -288, 0, 258, 0, 0, 0, 0, 0, 18, 0, 0, 0, -120, 0, 0, 0, 0, 0, 0, 0, -108, 0, 0, 0, -576, 0, 432, 0, 0, 0, 222, 0, -162, 0, 0, 0, 336, 0, 60, 0, 0, 0, 252, 0, 138, 0, 0, 0, 240, 0, 0, 0, 0, 0, 60, 0, -270, 0, 0, 0, -168, 0, -6, 0, 0, 0, 0, 0, 108, 0, 0, 0, 84, 0, -210, 0, 0, 0, 504, 0, -6, 0, 0, 0, 318, 0, 144, 0, 0, 0, 444, 0, 270, 0, 0, 0, 408, 0, 0, 0, 0, 0, -390, 0, 36, 0, 0, 0, 468, 0, 0, 0, 0, 0, -798, 0, -192, 0, 0, 0, -324, 0, -96, 0, 0, 0, -216, 0, -156, 0, 0, 0, 0, 0, -144, 0, 0, 0, -300, 0, -432, 0, 0, 0, 0, 0, 60, 0, 0, 0, -516, 0, -216, 0, 0, 0, 732, 0, 168, 0, 0, 0, 174, 0, 60, 0, 0, 0, 306, 0, 162, 0, 0, 0, 384, 0, 0, 0, 0, 0, 6, 0, 108, 0, 0, 0, -126, 0, 72, 0, 0, 0, 0, 0, 90, 0, 0, 0, -510, 0, -126, 0, 0, 0, 324, 0, -60, 0, 0, 0, 330, 0, 6, 0, 0, 0, -258, 0, 0, 0, 0, 0, -444, 0, 0, 0, 0, 0, -414, 0, 12, 0], 'weight': 2, 'weight_parity': 1}
• mf_hecke_cc •

  Column	Type
  an_normalized	double precision[]
  angles	double precision[]
  char_orbit_index	smallint
  conrey_index	integer
  dual_conrey_index	integer
  dual_embedding_index	integer
  dual_embedding_m	integer
  embedding_index	integer
  embedding_m	integer
  embedding_root_imag	double precision
  embedding_root_real	double precision
  hecke_orbit	integer
  hecke_orbit_code	bigint
  label	text
  level	integer
  weight	smallint

  
  {'an_normalized': [[1.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [-1.58045757771506, 0.0], [0.0, 0.0], [-0.49166724789000665, 0.8707831632227777], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, -0.5482299097810442], [0.0, 0.0], [0.771808737567078, -0.44560398239725774], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.7116817668158537, 1.2326689789454448], [0.0, 0.0], [0.4798071373799915, 0.2770167799254418], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.8025124743650741], [0.0, 0.0], [1.4978461549569548, 0.0], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [-1.075380743995112, -0.620871362026918], [0.0, 0.0], [0.7578609224820066, 0.43755120760328464], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.7770592276420698, -1.376235848862129], [0.0, 0.0], [-0.14884438048268384, 0.2578060294171218], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [-0.7857918212217513, -1.3610313585281533], [0.0, 0.0], [0.36025098124757415, -0.6239730029973413], [0.0, 0.0], [0.0, 0.0], [0.0, 0.0], [0.5777356928315845, 1.000667573330311], [0.0, 0.0], 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-0.06009004930594848, -0.12726328648432586, 0.03663078569473062, 0.02572998628567293, 0.1222977221401115, -0.2987143730010403, -0.23766485039379565, -0.07808768162469684, -0.43273866298626845, -0.10155055057654513, -0.47254765500499263, -0.011430753816575448, -0.3433178324144434, -0.3288867611618438, -0.30897842249235696, -0.18546060896794708, 0.1512883362850391, -0.12226063887455561, -0.16102715037728305, -0.33917475959347476, 0.1031830215334986, -0.13223683765535962, -0.43312150150776024, -0.09167754304622641, -0.49477221418369, -0.12734128718692528, -0.4794212834604743, -0.3680398351827972, -0.2975589296853121, 0.18807849593776632, -0.48562643507442704, -0.18506424346924275, -0.46688453755653775, -0.23760891066325, 0.08039437173088121], 'char_orbit_index': 84, 'conrey_index': 1601, 'dual_conrey_index': 17, 'dual_embedding_index': 3, 'dual_embedding_m': 3, 'embedding_index': 3, 'embedding_m': 27, 'hecke_orbit': 5, 'hecke_orbit_code': 18020102259608528, 'label': '3024.2.df.e.1601.3', 'level': 3024, 'weight': 2}
• mf_newspaces •

  Column	Type
  ALdims	integer[]
  ALdims_eis_new	integer[]
  ALdims_eis_old	integer[]
  ALdims_old	integer[]
  Nk2	integer
  a4_dim	integer
  a5_dim	integer
  analytic_conductor	double precision
  char_conductor	integer
  char_degree	integer
  char_is_real	boolean
  char_orbit_index	smallint
  char_orbit_label	text
  char_order	integer
  char_parity	smallint
  char_values	jsonb
  conrey_index	integer
  cusp_dim	integer
  dihedral_dim	integer
  dim	integer
  eis_dim	integer
  eis_new_dim	integer
  hecke_cutter_primes	integer[]
  hecke_orbit_code	bigint
  hecke_orbit_dims	integer[]
  label	text
  level	integer
  level_is_powerful	boolean
  level_is_prime	boolean
  level_is_prime_power	boolean
  level_is_prime_square	boolean
  level_is_square	boolean
  level_is_squarefree	boolean
  level_primes	integer[]
  level_radical	integer
  mf_dim	integer
  mf_new_dim	integer
  num_forms	smallint
  plus_dim	integer
  prim_orbit_index	smallint
  relative_dim	integer
  s4_dim	integer
  sturm_bound	integer
  trace_bound	integer
  trace_display	numeric[]
  traces	numeric[]
  weight	smallint
  weight_parity	smallint

  
  {'Nk2': 12096, 'analytic_conductor': 24.14676157123519, 'char_conductor': 63, 'char_degree': 2, 'char_is_real': False, 'char_orbit_index': 84, 'char_orbit_label': 'df', 'char_order': 6, 'char_parity': 1, 'char_values': [3024, 6, [1135, 757, 785, 2593], [6, 6, 5, 1]], 'conrey_index': 17, 'cusp_dim': 1080, 'dim': 92, 'eis_dim': 144, 'eis_new_dim': 8, 'hecke_cutter_primes': [5], 'hecke_orbit_code': 5703750126544, 'hecke_orbit_dims': [2, 10, 16, 16, 48], 'label': '3024.2.df', 'level': 3024, 'level_is_powerful': False, 'level_is_prime': False, 'level_is_prime_power': False, 'level_is_prime_square': False, 'level_is_square': False, 'level_is_squarefree': False, 'level_primes': [2, 3, 7], 'level_radical': 42, 'mf_dim': 1224, 'mf_new_dim': 100, 'num_forms': 5, 'prim_orbit_index': 19, 'relative_dim': 46, 'sturm_bound': 1152, 'trace_bound': 7, 'trace_display': [0, 0, 6, 1], 'traces': [92, 0, 0, 0, 6, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 0, 0, 0, 0, 0, 74, 0, 0, 0, -6, 0, -15, 0, 0, 0, -15, 0, -2, 0, 0, 0, 0, 0, 8, 0, 0, 0, -3, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, -3, 0, -3, 0, 0, 0, 27, 0, -1, 0, 0, 0, 0, 0, -6, 0, 0, 0, 27, 0, -1, 0, 0, 0, -30, 0, 3, 0, 0, 0, -12, 0, 12, 0, 0, 0, -87, 0, 0, 0, 0, 0, 6, 0, 0, 0, 0, 0, 0, 0, -2, 0, 0, 0, 42, 0, 0, 0, 0, 0, 18, 0, -54, 0, 0, 0, 30, 0, 20, 0, 0, 0, -6, 0, -15, 0, 0, 0, 0, 0, 0, 0, 0, 0, 33, 0, -21, 0, 0, 0, 0, 0, 2, 0, 0, 0, 54, 0, -3, 0, 0, 0, -21, 0, 2, 0, 0, 0, 90, 0, 20, 0, 0, 0, 51, 0, 34, 0, 0, 0, -96, 0, 0, 0, 0, 0, 3, 0, 3, 0, 0, 0, 27, 0, 1, 0, 0, 0, 0, 0, 6, 0, 0, 0, 63, 0, 3, 0, 0, 0, -33, 0, 2, 0, 0, 0, -15, 0, -9, 0, 0, 0, 42, 0, 0, 0, 0, 0, 102, 0, 0, 0, 0, 0, 24, 0, 12, 0, 0, 0, 66, 0, 0, 0, 0, 0, 3, 0, 60, 0, 0, 0, 168, 0, 14, 0, 0, 0, -90, 0, 29, 0, 0, 0, 0, 0, -15, 0, 0, 0, 0, 0, 6, 0, 0, 0, 0, 0, -2, 0, 0, 0, 6, 0, 21, 0, 0, 0, 66, 0, -16, 0, 0, 0, 24, 0, 12, 0, 0, 0, -3, 0, 1, 0, 0, 0, 18, 0, 0, 0, 0, 0, 63, 0, -3, 0, 0, 0, 51, 0, 13, 0, 0, 0, 0, 0, -45, 0, 0, 0, -93, 0, -37, 0, 0, 0, 144, 0, 10, 0, 0, 0, 0, 0, 88, 0, 0, 0, 183, 0, -36, 0, 0, 0, 6, 0, 0, 0, 0, 0, -84, 0, 8, 0, 0, 0, 93, 0, 0, 0, 0, 0, -114, 0, -2, 0, 0, 0, -72, 0, -64, 0, 0, 0, -6, 0, -27, 0, 0, 0, 0, 0, -51, 0, 0, 0, -126, 0, -6, 0, 0, 0, 0, 0, 54, 0, 0, 0, -117, 0, -3, 0, 0, 0, -81, 0, 33, 0, 0, 0, -102, 0, -2, 0, 0, 0, -33, 0, 81, 0, 0, 0, 228, 0, 0, 0, 0, 0, 3, 0, -87, 0, 0, 0, -147, 0, -9, 0, 0, 0, 0, 0, -27, 0, 0, 0, -219, 0, 13, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, -35, 0, 0, 0, -45, 0, 87, 0, 0, 0, -222, 0, 0, 0, 0, 0, 135, 0, -28, 0, 0, 0, -126, 0, 0, 0, 0, 0, -78, 0, -82, 0, 0, 0, -252, 0, -42, 0, 0, 0, -138, 0, -18, 0, 0, 0, 0, 0, 66, 0, 0, 0, 0, 0, -84, 0, 0, 0, 0, 0, -54, 0, 0, 0, -42, 0, 165, 0, 0, 0, 51, 0, -14, 0, 0, 0, -45, 0, -52, 0, 0, 0, -60, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, -165, 0, -33, 0, 0, 0, -69, 0, 11, 0, 0, 0, 0, 0, -42, 0, 0, 0, -189, 0, -71, 0, 0, 0, -156, 0, -21, 0, 0, 0, 96, 0, 15, 0, 0, 0, -285, 0, -36, 0, 0, 0, -60, 0, 0, 0, 0, 0, 129, 0, 22, 0, 0, 0, 66, 0, 0, 0, 0, 0, 177, 0, 32, 0, 0, 0, -168, 0, -196, 0, 0, 0, -144, 0, -3, 0, 0, 0, 0, 0, -126, 0, 0, 0, 126, 0, -6, 0, 0, 0, 0, 0, 42, 0, 0, 0, 72, 0, -3, 0, 0, 0, 108, 0, 73, 0, 0, 0, 180, 0, -26, 0, 0, 0, -129, 0, 39, 0, 0, 0, -426, 0, 0, 0, 0, 0, 42, 0, -123, 0, 0, 0, 93, 0, 18, 0, 0, 0, 0, 0, -12, 0, 0, 0, 267, 0, -11, 0, 0, 0, 60, 0, -87, 0, 0, 0, -60, 0, -33, 0, 0, 0, -39, 0, 126, 0, 0, 0, 348, 0, 0, 0, 0, 0, -138, 0, -40, 0, 0, 0, 36, 0, 0, 0, 0, 0, -93, 0, -106, 0, 0, 0, 342, 0, 40, 0, 0, 0, 246, 0, -46, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -105, 0, 0, 0, 0, 0, 116, 0, 0, 0, -42, 0, -51, 0, 0, 0, 78, 0, -3, 0, 0, 0, -120, 0, -87, 0, 0, 0, 87, 0, 57, 0, 0, 0, 96, 0, 0, 0, 0, 0, 177, 0, -60, 0, 0, 0, 3, 0, -19, 0, 0, 0, 0, 0, -6, 0, 0, 0, 159, 0, 9, 0, 0, 0, 180, 0, -12, 0, 0, 0, 174, 0, -72, 0, 0, 0, 423, 0, 0, 0, 0, 0, 6, 0, 0, 0, 0, 0, -102, 0, -24, 0, 0, 0, -66, 0, 0, 0, 0, 0, -459, 0, -50, 0, 0, 0, 96, 0, -64, 0, 0, 0, 222, 0, -20, 0, 0, 0, 0, 0, 15, 0, 0, 0, -303, 0, 66, 0, 0, 0, 0, 0, -58, 0, 0, 0, -114, 0, 63, 0, 0, 0, 105, 0, 44, 0, 0, 0, -174, 0, 37, 0, 0, 0, 123, 0, -156, 0, 0, 0, 483, 0, 0, 0, 0, 0, 3, 0, -135, 0, 0, 0, -69, 0, -12, 0, 0, 0, 0, 0, 6, 0, 0, 0, -285, 0, 11, 0, 0, 0, 96, 0, -46, 0, 0, 0, 144, 0, -42, 0, 0, 0, 123, 0, -33, 0, 0, 0, -510, 0, 0, 0, 0, 0, -237, 0, -34, 0, 0, 0, -75, 0, 0, 0, 0, 0], 'weight': 2, 'weight_parity': 1}
• mf_twists_cc •

  Column	Type
  conductor	integer
  degree	integer
  order	integer
  parity	smallint
  source_conrey_index	integer
  source_dim	integer
  source_embedding_index	integer
  source_hecke_orbit_code	bigint
  source_is_minimal	boolean
  source_label	text
  source_level	integer
  target_conrey_index	integer
  target_dim	integer
  target_embedding_index	integer
  target_hecke_orbit_code	bigint
  target_is_minimal	boolean
  target_label	text
  target_level	integer
  twist_class_label	text
  twist_class_level	integer
  twisting_char_label	text
  twisting_conrey_index	integer
  weight	smallint

  
  
  • id: 44866157
    {'conductor': 1, 'degree': 1, 'order': 1, 'parity': 1, 'source_conrey_index': 1601, 'source_dim': 48, 'source_embedding_index': 3, 'source_hecke_orbit_code': 18020102259608528, 'source_is_minimal': False, 'source_label': '3024.2.df.e.1601.3', 'source_level': 3024, 'target_conrey_index': 1601, 'target_dim': 48, 'target_embedding_index': 3, 'target_hecke_orbit_code': 18020102259608528, 'target_is_minimal': False, 'target_label': '3024.2.df.e.1601.3', 'target_level': 3024, 'twist_class_label': '504.2.bs.a.257.1', 'twist_class_level': 504, 'twisting_char_label': '1.1', 'twisting_conrey_index': 1, 'weight': 2}
  • id: 44866158
    {'conductor': 3, 'degree': 1, 'order': 2, 'parity': -1, 'source_conrey_index': 1601, 'source_dim': 48, 'source_embedding_index': 3, 'source_hecke_orbit_code': 18020102259608528, 'source_is_minimal': False, 'source_label': '3024.2.df.e.1601.3', 'source_level': 3024, 'target_conrey_index': 929, 'target_dim': 48, 'target_embedding_index': 18, 'target_hecke_orbit_code': 18020102259606512, 'target_is_minimal': False, 'target_label': '1008.2.df.e.929.18', 'target_level': 1008, 'twist_class_label': '504.2.bs.a.257.1', 'twist_class_level': 504, 'twisting_char_label': '3.2', 'twisting_conrey_index': 2, 'weight': 2}
  • id: 44866159
    {'conductor': 4, 'degree': 1, 'order': 2, 'parity': -1, 'source_conrey_index': 1601, 'source_dim': 48, 'source_embedding_index': 3, 'source_hecke_orbit_code': 18020102259608528, 'source_is_minimal': False, 'source_label': '3024.2.df.e.1601.3', 'source_level': 3024, 'target_conrey_index': 89, 'target_dim': 48, 'target_embedding_index': 3, 'target_hecke_orbit_code': 5153994311144, 'target_is_minimal': False, 'target_label': '1512.2.cx.a.89.3', 'target_level': 1512, 'twist_class_label': '504.2.bs.a.257.1', 'twist_class_level': 504, 'twisting_char_label': '4.3', 'twisting_conrey_index': 3, 'weight': 2}
  • id: 44866160
    {'conductor': 7, 'degree': 2, 'order': 6, 'parity': -1, 'source_conrey_index': 1601, 'source_dim': 48, 'source_embedding_index': 3, 'source_hecke_orbit_code': 18020102259608528, 'source_is_minimal': False, 'source_label': '3024.2.df.e.1601.3', 'source_level': 3024, 'target_conrey_index': 2033, 'target_dim': 48, 'target_embedding_index': 3, 'target_hecke_orbit_code': 18017971955829712, 'target_is_minimal': False, 'target_label': '3024.2.ca.e.2033.3', 'target_level': 3024, 'twist_class_label': '504.2.bs.a.257.1', 'twist_class_level': 504, 'twisting_char_label': '7.3', 'twisting_conrey_index': 3, 'weight': 2}
  • id: 44866161
    {'conductor': 9, 'degree': 2, 'order': 3, 'parity': 1, 'source_conrey_index': 1601, 'source_dim': 48, 'source_embedding_index': 3, 'source_hecke_orbit_code': 18020102259608528, 'source_is_minimal': False, 'source_label': '3024.2.df.e.1601.3', 'source_level': 3024, 'target_conrey_index': 257, 'target_dim': 48, 'target_embedding_index': 24, 'target_hecke_orbit_code': 18017971955827696, 'target_is_minimal': False, 'target_label': '1008.2.ca.e.257.24', 'target_level': 1008, 'twist_class_label': '504.2.bs.a.257.1', 'twist_class_level': 504, 'twisting_char_label': '9.4', 'twisting_conrey_index': 4, 'weight': 2}
  • id: 44866162
    {'conductor': 9, 'degree': 2, 'order': 6, 'parity': -1, 'source_conrey_index': 1601, 'source_dim': 48, 'source_embedding_index': 3, 'source_hecke_orbit_code': 18020102259608528, 'source_is_minimal': False, 'source_label': '3024.2.df.e.1601.3', 'source_level': 3024, 'target_conrey_index': 2609, 'target_dim': 48, 'target_embedding_index': 3, 'target_hecke_orbit_code': 18017971955829712, 'target_is_minimal': False, 'target_label': '3024.2.ca.e.2609.3', 'target_level': 3024, 'twist_class_label': '504.2.bs.a.257.1', 'twist_class_level': 504, 'twisting_char_label': '9.5', 'twisting_conrey_index': 5, 'weight': 2}
  • id: 44866163
    {'conductor': 12, 'degree': 1, 'order': 2, 'parity': 1, 'source_conrey_index': 1601, 'source_dim': 48, 'source_embedding_index': 3, 'source_hecke_orbit_code': 18020102259608528, 'source_is_minimal': False, 'source_label': '3024.2.df.e.1601.3', 'source_level': 3024, 'target_conrey_index': 425, 'target_dim': 48, 'target_embedding_index': 7, 'target_hecke_orbit_code': 5153994310136, 'target_is_minimal': True, 'target_label': '504.2.cx.a.425.7', 'target_level': 504, 'twist_class_label': '504.2.bs.a.257.1', 'twist_class_level': 504, 'twisting_char_label': '12.11', 'twisting_conrey_index': 11, 'weight': 2}
  • id: 44866164
    {'conductor': 21, 'degree': 2, 'order': 6, 'parity': 1, 'source_conrey_index': 1601, 'source_dim': 48, 'source_embedding_index': 3, 'source_hecke_orbit_code': 18020102259608528, 'source_is_minimal': False, 'source_label': '3024.2.df.e.1601.3', 'source_level': 3024, 'target_conrey_index': 353, 'target_dim': 48, 'target_embedding_index': 24, 'target_hecke_orbit_code': 18017971955827696, 'target_is_minimal': False, 'target_label': '1008.2.ca.e.353.24', 'target_level': 1008, 'twist_class_label': '504.2.bs.a.257.1', 'twist_class_level': 504, 'twisting_char_label': '21.17', 'twisting_conrey_index': 17, 'weight': 2}
  • id: 44866165
    {'conductor': 28, 'degree': 2, 'order': 6, 'parity': 1, 'source_conrey_index': 1601, 'source_dim': 48, 'source_embedding_index': 3, 'source_hecke_orbit_code': 18020102259608528, 'source_is_minimal': False, 'source_label': '3024.2.df.e.1601.3', 'source_level': 3024, 'target_conrey_index': 521, 'target_dim': 48, 'target_embedding_index': 3, 'target_hecke_orbit_code': 3023690532328, 'target_is_minimal': False, 'target_label': '1512.2.bs.a.521.3', 'target_level': 1512, 'twist_class_label': '504.2.bs.a.257.1', 'twist_class_level': 504, 'twisting_char_label': '28.3', 'twisting_conrey_index': 3, 'weight': 2}
  • id: 44866166
    {'conductor': 36, 'degree': 2, 'order': 6, 'parity': 1, 'source_conrey_index': 1601, 'source_dim': 48, 'source_embedding_index': 3, 'source_hecke_orbit_code': 18020102259608528, 'source_is_minimal': False, 'source_label': '3024.2.df.e.1601.3', 'source_level': 3024, 'target_conrey_index': 1097, 'target_dim': 48, 'target_embedding_index': 3, 'target_hecke_orbit_code': 3023690532328, 'target_is_minimal': False, 'target_label': '1512.2.bs.a.1097.3', 'target_level': 1512, 'twist_class_label': '504.2.bs.a.257.1', 'twist_class_level': 504, 'twisting_char_label': '36.23', 'twisting_conrey_index': 23, 'weight': 2}
  • id: 44866167
    {'conductor': 36, 'degree': 2, 'order': 6, 'parity': -1, 'source_conrey_index': 1601, 'source_dim': 48, 'source_embedding_index': 3, 'source_hecke_orbit_code': 18020102259608528, 'source_is_minimal': False, 'source_label': '3024.2.df.e.1601.3', 'source_level': 3024, 'target_conrey_index': 257, 'target_dim': 48, 'target_embedding_index': 1, 'target_hecke_orbit_code': 3023690531320, 'target_is_minimal': True, 'target_label': '504.2.bs.a.257.1', 'target_level': 504, 'twist_class_label': '504.2.bs.a.257.1', 'twist_class_level': 504, 'twisting_char_label': '36.31', 'twisting_conrey_index': 31, 'weight': 2}
  • id: 44866168
    {'conductor': 63, 'degree': 2, 'order': 6, 'parity': -1, 'source_conrey_index': 1601, 'source_dim': 48, 'source_embedding_index': 3, 'source_hecke_orbit_code': 18020102259608528, 'source_is_minimal': False, 'source_label': '3024.2.df.e.1601.3', 'source_level': 3024, 'target_conrey_index': 689, 'target_dim': 48, 'target_embedding_index': 18, 'target_hecke_orbit_code': 18020102259606512, 'target_is_minimal': False, 'target_label': '1008.2.df.e.689.18', 'target_level': 1008, 'twist_class_label': '504.2.bs.a.257.1', 'twist_class_level': 504, 'twisting_char_label': '63.31', 'twisting_conrey_index': 31, 'weight': 2}
  • id: 44866169
    {'conductor': 63, 'degree': 2, 'order': 6, 'parity': 1, 'source_conrey_index': 1601, 'source_dim': 48, 'source_embedding_index': 3, 'source_hecke_orbit_code': 18020102259608528, 'source_is_minimal': False, 'source_label': '3024.2.df.e.1601.3', 'source_level': 3024, 'target_conrey_index': 17, 'target_dim': 48, 'target_embedding_index': 3, 'target_hecke_orbit_code': 18020102259608528, 'target_is_minimal': False, 'target_label': '3024.2.df.e.17.3', 'target_level': 3024, 'twist_class_label': '504.2.bs.a.257.1', 'twist_class_level': 504, 'twisting_char_label': '63.59', 'twisting_conrey_index': 59, 'weight': 2}
  • id: 44866170
    {'conductor': 84, 'degree': 2, 'order': 6, 'parity': -1, 'source_conrey_index': 1601, 'source_dim': 48, 'source_embedding_index': 3, 'source_hecke_orbit_code': 18020102259608528, 'source_is_minimal': False, 'source_label': '3024.2.df.e.1601.3', 'source_level': 3024, 'target_conrey_index': 353, 'target_dim': 48, 'target_embedding_index': 1, 'target_hecke_orbit_code': 3023690531320, 'target_is_minimal': True, 'target_label': '504.2.bs.a.353.1', 'target_level': 504, 'twist_class_label': '504.2.bs.a.257.1', 'twist_class_level': 504, 'twisting_char_label': '84.59', 'twisting_conrey_index': 59, 'weight': 2}
  • id: 44866171
    {'conductor': 252, 'degree': 2, 'order': 6, 'parity': 1, 'source_conrey_index': 1601, 'source_dim': 48, 'source_embedding_index': 3, 'source_hecke_orbit_code': 18020102259608528, 'source_is_minimal': False, 'source_label': '3024.2.df.e.1601.3', 'source_level': 3024, 'target_conrey_index': 185, 'target_dim': 48, 'target_embedding_index': 7, 'target_hecke_orbit_code': 5153994310136, 'target_is_minimal': True, 'target_label': '504.2.cx.a.185.7', 'target_level': 504, 'twist_class_label': '504.2.bs.a.257.1', 'twist_class_level': 504, 'twisting_char_label': '252.31', 'twisting_conrey_index': 31, 'weight': 2}
  • id: 44866172
    {'conductor': 252, 'degree': 2, 'order': 6, 'parity': -1, 'source_conrey_index': 1601, 'source_dim': 48, 'source_embedding_index': 3, 'source_hecke_orbit_code': 18020102259608528, 'source_is_minimal': False, 'source_label': '3024.2.df.e.1601.3', 'source_level': 3024, 'target_conrey_index': 17, 'target_dim': 48, 'target_embedding_index': 3, 'target_hecke_orbit_code': 5153994311144, 'target_is_minimal': False, 'target_label': '1512.2.cx.a.17.3', 'target_level': 1512, 'twist_class_label': '504.2.bs.a.257.1', 'twist_class_level': 504, 'twisting_char_label': '252.59', 'twisting_conrey_index': 59, 'weight': 2}
• hecke_orbit_code 18020102259608528 does not appear in mf_hecke_charpolys
• mf_newform_portraits •

  Column	Type
  char_orbit_index	smallint
  hecke_orbit	integer
  label	text
  level	integer
  portrait	text
  weight	smallint

  
  {'char_orbit_index': 84, 'hecke_orbit': 5, 'label': '3024.2.df.e', 'level': 3024, 'portrait': 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', 'weight': 2}
• mf_hecke_traces •

  Column	Type
  hecke_orbit_code	bigint
  n	integer
  trace_an	numeric

  
  
  • id: 41758309
    {'hecke_orbit_code': 18020102259608528, 'n': 1, 'trace_an': 48}
  • id: 41758310
    {'hecke_orbit_code': 18020102259608528, 'n': 2, 'trace_an': 0}
  • id: 41758311
    {'hecke_orbit_code': 18020102259608528, 'n': 3, 'trace_an': 0}
  • id: 41758312
    {'hecke_orbit_code': 18020102259608528, 'n': 4, 'trace_an': 0}
  • id: 41758313
    {'hecke_orbit_code': 18020102259608528, 'n': 5, 'trace_an': 0}
  • id: 41758314
    {'hecke_orbit_code': 18020102259608528, 'n': 6, 'trace_an': 0}
  • id: 41758315
    {'hecke_orbit_code': 18020102259608528, 'n': 7, 'trace_an': 0}
  • id: 41758316
    {'hecke_orbit_code': 18020102259608528, 'n': 8, 'trace_an': 0}
  • id: 41758317
    {'hecke_orbit_code': 18020102259608528, 'n': 9, 'trace_an': 0}
  • id: 41758318
    {'hecke_orbit_code': 18020102259608528, 'n': 10, 'trace_an': 0}
  • id: 41758319
    {'hecke_orbit_code': 18020102259608528, 'n': 11, 'trace_an': 0}
  • id: 41758320
    {'hecke_orbit_code': 18020102259608528, 'n': 12, 'trace_an': 0}
  • id: 41758321
    {'hecke_orbit_code': 18020102259608528, 'n': 13, 'trace_an': 0}
  • id: 41758322
    {'hecke_orbit_code': 18020102259608528, 'n': 14, 'trace_an': 0}
  • id: 41758323
    {'hecke_orbit_code': 18020102259608528, 'n': 15, 'trace_an': 0}
  • id: 41758324
    {'hecke_orbit_code': 18020102259608528, 'n': 16, 'trace_an': 0}
  • id: 41758325
    {'hecke_orbit_code': 18020102259608528, 'n': 17, 'trace_an': 0}
  • id: 41758326
    {'hecke_orbit_code': 18020102259608528, 'n': 18, 'trace_an': 0}
  • id: 41758327
    {'hecke_orbit_code': 18020102259608528, 'n': 19, 'trace_an': 0}
  • id: 41758328
    {'hecke_orbit_code': 18020102259608528, 'n': 20, 'trace_an': 0}
  • id: 41758329
    {'hecke_orbit_code': 18020102259608528, 'n': 21, 'trace_an': 0}
  • id: 41758330
    {'hecke_orbit_code': 18020102259608528, 'n': 22, 'trace_an': 0}
  • id: 41758331
    {'hecke_orbit_code': 18020102259608528, 'n': 23, 'trace_an': 0}
  • id: 41758332
    {'hecke_orbit_code': 18020102259608528, 'n': 24, 'trace_an': 0}
  • id: 41758333
    {'hecke_orbit_code': 18020102259608528, 'n': 25, 'trace_an': 48}
  • id: 41758334
    {'hecke_orbit_code': 18020102259608528, 'n': 26, 'trace_an': 0}
  • id: 41758335
    {'hecke_orbit_code': 18020102259608528, 'n': 27, 'trace_an': 0}
  • id: 41758336
    {'hecke_orbit_code': 18020102259608528, 'n': 28, 'trace_an': 0}
  • id: 41758337
    {'hecke_orbit_code': 18020102259608528, 'n': 29, 'trace_an': -18}
  • id: 41758338
    {'hecke_orbit_code': 18020102259608528, 'n': 30, 'trace_an': 0}
  • id: 41758339
    {'hecke_orbit_code': 18020102259608528, 'n': 31, 'trace_an': -18}
  • id: 41758340
    {'hecke_orbit_code': 18020102259608528, 'n': 32, 'trace_an': 0}
  • id: 41758341
    {'hecke_orbit_code': 18020102259608528, 'n': 33, 'trace_an': 0}
  • id: 41758342
    {'hecke_orbit_code': 18020102259608528, 'n': 34, 'trace_an': 0}
  • id: 41758343
    {'hecke_orbit_code': 18020102259608528, 'n': 35, 'trace_an': 0}
  • id: 41758344
    {'hecke_orbit_code': 18020102259608528, 'n': 36, 'trace_an': 0}
  • id: 41758345
    {'hecke_orbit_code': 18020102259608528, 'n': 37, 'trace_an': 0}
  • id: 41758346
    {'hecke_orbit_code': 18020102259608528, 'n': 38, 'trace_an': 0}
  • id: 41758347
    {'hecke_orbit_code': 18020102259608528, 'n': 39, 'trace_an': 0}
  • id: 41758348
    {'hecke_orbit_code': 18020102259608528, 'n': 40, 'trace_an': 0}
  • id: 41758349
    {'hecke_orbit_code': 18020102259608528, 'n': 41, 'trace_an': 6}
  • id: 41758350
    {'hecke_orbit_code': 18020102259608528, 'n': 42, 'trace_an': 0}
  • id: 41758351
    {'hecke_orbit_code': 18020102259608528, 'n': 43, 'trace_an': 6}
  • id: 41758352
    {'hecke_orbit_code': 18020102259608528, 'n': 44, 'trace_an': 0}
  • id: 41758353
    {'hecke_orbit_code': 18020102259608528, 'n': 45, 'trace_an': 0}
  • id: 41758354
    {'hecke_orbit_code': 18020102259608528, 'n': 46, 'trace_an': 0}
  • id: 41758355
    {'hecke_orbit_code': 18020102259608528, 'n': 47, 'trace_an': 18}
  • id: 41758356
    {'hecke_orbit_code': 18020102259608528, 'n': 48, 'trace_an': 0}
  • id: 41758357
    {'hecke_orbit_code': 18020102259608528, 'n': 49, 'trace_an': -12}
  • id: 41758358
    {'hecke_orbit_code': 18020102259608528, 'n': 50, 'trace_an': 0}
  • id: 41758359
    {'hecke_orbit_code': 18020102259608528, 'n': 51, 'trace_an': 0}
  • id: 41758360
    {'hecke_orbit_code': 18020102259608528, 'n': 52, 'trace_an': 0}
  • id: 41758361
    {'hecke_orbit_code': 18020102259608528, 'n': 53, 'trace_an': 12}
  • id: 41758362
    {'hecke_orbit_code': 18020102259608528, 'n': 54, 'trace_an': 0}
  • id: 41758363
    {'hecke_orbit_code': 18020102259608528, 'n': 55, 'trace_an': 0}
  • id: 41758364
    {'hecke_orbit_code': 18020102259608528, 'n': 56, 'trace_an': 0}
  • id: 41758365
    {'hecke_orbit_code': 18020102259608528, 'n': 57, 'trace_an': 0}
  • id: 41758366
    {'hecke_orbit_code': 18020102259608528, 'n': 58, 'trace_an': 0}
  • id: 41758367
    {'hecke_orbit_code': 18020102259608528, 'n': 59, 'trace_an': 0}
  • id: 41758368
    {'hecke_orbit_code': 18020102259608528, 'n': 60, 'trace_an': 0}
  • id: 41758369
    {'hecke_orbit_code': 18020102259608528, 'n': 61, 'trace_an': 18}
  • id: 41758370
    {'hecke_orbit_code': 18020102259608528, 'n': 62, 'trace_an': 0}
  • id: 41758371
    {'hecke_orbit_code': 18020102259608528, 'n': 63, 'trace_an': 0}
  • id: 41758372
    {'hecke_orbit_code': 18020102259608528, 'n': 64, 'trace_an': 0}
  • id: 41758373
    {'hecke_orbit_code': 18020102259608528, 'n': 65, 'trace_an': 36}
  • id: 41758374
    {'hecke_orbit_code': 18020102259608528, 'n': 66, 'trace_an': 0}
  • id: 41758375
    {'hecke_orbit_code': 18020102259608528, 'n': 67, 'trace_an': 0}
  • id: 41758376
    {'hecke_orbit_code': 18020102259608528, 'n': 68, 'trace_an': 0}
  • id: 41758377
    {'hecke_orbit_code': 18020102259608528, 'n': 69, 'trace_an': 0}
  • id: 41758378
    {'hecke_orbit_code': 18020102259608528, 'n': 70, 'trace_an': 0}
  • id: 41758379
    {'hecke_orbit_code': 18020102259608528, 'n': 71, 'trace_an': 0}
  • id: 41758380
    {'hecke_orbit_code': 18020102259608528, 'n': 72, 'trace_an': 0}
  • id: 41758381
    {'hecke_orbit_code': 18020102259608528, 'n': 73, 'trace_an': 0}
  • id: 41758382
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  • id: 41758383
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  • id: 41758384
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  • id: 41758385
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  • id: 41758386
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  • id: 41758387
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  • id: 41758388
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  • id: 41758389
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  • id: 41758390
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  • id: 41758391
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  • id: 41758392
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  • id: 41758393
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  • id: 41758394
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  • id: 41758395
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  • id: 41758396
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  • id: 41758397
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  • id: 41758398
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  • id: 41758399
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  • id: 41758400
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  • id: 41758401
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  • id: 41758402
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  • id: 41758403
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  • id: 41758404
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  • id: 41758405
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  • id: 41758406
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  • id: 41758407
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  • id: 41758408
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  • id: 41758409
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  • id: 41758410
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  • id: 41758411
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  • id: 41758412
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  • id: 41758413
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  • id: 41758414
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  • id: 41758415
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  • id: 41758416
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  • id: 41758417
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  • id: 41758418
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  • id: 41758419
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  • id: 41758420
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  • id: 41758421
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  • id: 41758422
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  • id: 41758423
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  • id: 41758424
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  • id: 41758425
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  • id: 41758426
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  • id: 41758427
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  • id: 41758428
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  • id: 41758429
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  • id: 41758430
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  • id: 41758431
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  • id: 41758432
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  • id: 41758433
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  • id: 41758434
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  • id: 41758435
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  • id: 41758436
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  • id: 41758437
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  • id: 41758438
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  • id: 41758439
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  • id: 41758440
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  • id: 41758441
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  • id: 41758442
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  • id: 41758443
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  • id: 41758444
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  • id: 41758445
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  • id: 41758446
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  • id: 41758447
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  • id: 41758448
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  • id: 41758449
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  • id: 41758450
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  • id: 41758451
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  • id: 41758452
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  • id: 41758453
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  • id: 41758454
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  • id: 41758455
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  • id: 41758456
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  • id: 41758457
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  • id: 41758458
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  • id: 41758459
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  • id: 41758460
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  • id: 41758461
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  • id: 41758462
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  • id: 41758463
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  • id: 41758464
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  • id: 41758465
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  • id: 41758466
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  • id: 41758467
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  • id: 41758468
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  • id: 41758469
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  • id: 41758470
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  • id: 41758471
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  • id: 41758472
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  • id: 41758473
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  • id: 41758474
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  • id: 41758475
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  • id: 41758476
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  • id: 41758477
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  • id: 41758478
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  • id: 41758479
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  • id: 41758480
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  • id: 41758481
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  • id: 41758482
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  • id: 41758483
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  • id: 41758484
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  • id: 41758485
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  • id: 41758486
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  • id: 41758487
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  • id: 41758488
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  • id: 41758489
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  • id: 41758490
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  • id: 41758491
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  • id: 41758492
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  • id: 41758493
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  • id: 41758494
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  • id: 41758495
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  • id: 41758496
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  • id: 41758497
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  • id: 41758498
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  • id: 41758499
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  • id: 41758500
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  • id: 41758501
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  • id: 41758502
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  • id: 41758503
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  • id: 41758504
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  • id: 41758505
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  • id: 41758506
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  • id: 41758507
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  • id: 41758508
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  • id: 41758509
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  • id: 41758510
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  • id: 41758511
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  • id: 41758512
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  • id: 41758513
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  • id: 41758514
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  • id: 41758515
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  • id: 41758516
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  • id: 41758517
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  • id: 41758518
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  • id: 41758519
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  • id: 41758520
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  • id: 41758521
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  • id: 41758522
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  • id: 41758523
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  • id: 41758524
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  • id: 41758525
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  • id: 41758526
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  • id: 41758527
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  • id: 41758528
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  • id: 41758529
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  • id: 41758530
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  • id: 41758531
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  • id: 41758532
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  • id: 41758533
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  • id: 41758534
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  • id: 41758535
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  • id: 41758536
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  • id: 41758537
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  • id: 41758538
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  • id: 41758539
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  • id: 41758540
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  • id: 41758541
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  • id: 41758542
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  • id: 41758543
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  • id: 41758544
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  • id: 41758545
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  • id: 41758546
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  • id: 41758547
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  • id: 41758548
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  • id: 41758549
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  • id: 41758550
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  • id: 41758551
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  • id: 41758552
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  • id: 41758553
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  • id: 41758554
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  • id: 41758555
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  • id: 41758556
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  • id: 41758557
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  • id: 41758558
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  • id: 41758559
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  • id: 41758560
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  • id: 41758561
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  • id: 41758562
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  • id: 41758563
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  • id: 41758564
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  • id: 41758565
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  • id: 41758566
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