Embedded newform data - 1860.1.df.b.179.1

Formats: - HTML - YAML - JSON - 2025-11-07T12:56:53.542515

• 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': 1860, 'analytic_conductor': 0.9282609234973844, 'analytic_rank': 0, 'analytic_rank_proved': True, 'char_conductor': 1860, 'char_degree': 8, 'char_is_minimal': True, 'char_is_real': False, 'char_orbit_index': 84, 'char_orbit_label': 'df', 'char_order': 30, 'char_parity': -1, 'char_values': [1860, 30, [931, 1241, 1117, 1801], [15, 15, 15, 13]], 'cm_discs': [-15], 'conrey_index': 179, 'dim': 8, 'field_disc': 1265625, 'field_disc_factorization': [[3, 4], [5, 6]], 'field_poly': [1, -1, 0, 1, -1, 1, 0, -1, 1], 'field_poly_is_cyclotomic': True, 'field_poly_is_real_cyclotomic': False, 'field_poly_root_of_unity': 15, 'has_non_self_twist': 1, 'hecke_cutters': [[17, [81, -81, 54, -27, 9, -9, 6, -3, 1]], [19, [1, -1, -1, 8, 9, 6, 6, 2, 1]]], 'hecke_orbit': 2, 'hecke_orbit_code': 4509303360718660, 'hecke_ring_generator_nbound': 2, 'hecke_ring_index': 1, 'hecke_ring_index_factorization': [], 'hecke_ring_index_proved': True, 'inner_twist_count': 4, 'inner_twists': [[1, 1, 1, 1, 1, 1, 1], [1, 1, 15, 4, -1, 2, -15], [1, 1, 124, 16, 1, 30, 0], [1, 1, 1860, 84, -1, 30, 0]], 'is_cm': True, 'is_largest': False, 'is_maximal': False, 'is_polredabs': True, 'is_rm': False, 'is_self_dual': False, 'is_self_twist': True, 'is_twist_minimal': True, 'label': '1860.1.df.b', 'level': 1860, '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, 5, 31], 'level_radical': 930, 'minimal_twist': '1860.1.df.a', 'nf_label': '8.0.1265625.1', 'prim_orbit_index': 84, 'projective_field': [-11113956788751, 0, 4923274482063, 0, -1244334806167, 0, -527344407272, 0, -275803726152, 0, -150092678021, 0, -58062940015, 0, -13239880830, 0, -1816854045, 0, -152696235, 0, -6919479, 0, 16027, 0, 25172, 0, 1767, 0, 62, 0, 1], 'projective_image': 'D30', 'projective_image_type': 'Dn', 'qexp_display': 'q-\\zeta_{30}^{4}q^{2}+\\zeta_{30}^{14}q^{3}+\\zeta_{30}^{8}q^{4}+\\cdots', 'related_objects': [], 'relative_dim': 1, 'rm_discs': [], 'self_twist_discs': [-15], 'self_twist_type': 1, 'space_label': '1860.1.df', 'trace_display': [-1, 1, -4, 0], 'trace_hash': 858703548399635945, 'trace_moments': [{'__RealLiteral__': 0, 'data': '-0.080', 'prec': 20}, {'__RealLiteral__': 0, 'data': '7.663', 'prec': 17}, {'__RealLiteral__': 0, 'data': '-6.862', 'prec': 20}, {'__RealLiteral__': 0, 'data': '426.660', 'prec': 24}, {'__RealLiteral__': 0, 'data': '-823.212', 'prec': 27}, {'__RealLiteral__': 0, 'data': '36618.169', 'prec': 30}], 'trace_zratio': {'__RealLiteral__': 0, 'data': '0.602', 'prec': 17}, 'traces': [8, -1, 1, 1, -4, 2, 0, 2, 1, -1, 0, 1, 0, 0, -2, 1, 3, -1, -2, -2, 0, 0, -6, -1, -4, 0, -2, 0, 0, -1, -2, 4, 0, 0, 0, -2, 0, 0, 0, -1, 0, 0, 0, 0, 1, -3, 0, 8, -1, 2, -3, 0, 0, -1, 0, 0, -3, 0, 0, 1, 0, 4, 0, -2, 0, 0, 0, -3, 3, 0, 0, 4, 0, 0, 1, 2, 0, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 2, 0, -2, -4, -2, -5, -1, 0, 1, 0, 1, 0, -3, 0, 0, 0, 0, 5, -4, -6, 0, 0, 0, -1, 7, 3, 0, 0, 0, 0, 2, 1, 7, 0, 1, 8, 0, 0, -1, 0, 0, 0, 0, 0, 0, 1, 12, -3, -4, 2, 0, -7, 0, 0, 1, 0, 0, 2, 0, 0, -1, 4, -3, 0, 0, 1, 0, 0, 2, 0, -8, 0, -8, 0, 0, 0, -1, -1, 0, -1, 3, 5, 0, 2, 0, 0, 0, 0, 0, 0, 1, 0, 0, 2, -4, 0, 2, 0, -2, 0, 3, 0, 1, 0, 0, 0, 2, -7, 0, 1, -1, 0, 0, 0, 0, 0, 0, -2, 0, 0, 0, 0, -10, 0, -10, 0, 2, 0, 2, 0, 0, 0, 0, 0, 0, -2, 1, -3, 0, 5, -3, 0, 0, 3, 0, -3, 0, 1, 0, 0, -4, -3, 2, -4, -3, -1, 0, 0, 2, -2, -1, 0, 0, 0, 0, 3, 1, 1, 0, 0, 0, 0, 0, -3, 0, 0, 0, 0, 0, 0, -1, 2, 0, 0, 2, 0, -2, 0, 6, 1, 0, 0, 5, 0, 0, 3, 0, 0, 2, -2, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, -2, 0, -3, 0, 0, 3, -12, 0, 0, 0, 4, 0, 0, 0, 0, 0, -9, 6, -5, 0, 1, -5, 0, 12, 1, 0, 0, -2, 0, 0, 0, 6, -2, 0, -2, 0, 0, 0, -2, 2, 3, 0, 3, 0, 0, -6, 3, -1, 0, 3, 0, 0, 0, -3, 0, 0, 0, 0, 0, 0, 4, -7, 0, 1, 0, 0, 0, 0, -2, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, -7, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, -6, 1, 0, 3, -2, 0, 0, -1, 0, -2, 0, 0, 0, 0, -2, 0, 0, 3, 3, 0, -5, 0, 0, 2, 1, 0, 9, 0, 0, 0, 1, 0, 7, 0, -3, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, -2, -1, 0, 0, 0, -1, 0, -3, 0, 0, 0, 0, 0, 0, -1, 0, -8, 3, 12, 0, 3, 0, 0, -12, 4, 0, 0, 0, 0, 8, -1, 10, 0, 0, 7, 0, 0, 0, -6, 7, 0, 5, 0, 0, -1, 0, -5, 0, 1, 0, -1, 0, 0, 0, -2, 0, 0, 0, 0, 0, 1, 0, -1, -3, 1, -1, 0, 0, 0, 0, 0, -1, 0, 0, 0, 0, 2, 3, -1, 0, 0, 0, 0, 6, 0, 0, 0, 0, 0, 0, 1, 3, 0, 4, 0, 0, 0, 0, 0, -10, 0, 0, 0, 0, 8, 6, 1, 0, 3, 3, 0, 0, 5, 3, 0, 0, 2, 0, 0, 0, -6, 0, -1, 0, 0, 0, 0, -3, -3, -1, 0, 0, 0, 0, -5, -3, 0, 0, 0, 3, 1, 0, -8, 0, 0, 0, 0, 0, 0, 0, 2, -3, -1, 3, 0, 0, 0, -3, 0, 0, 0, -2, 0, 0, -1, 3, 0, 0, -2, -2, 0, 0, -7, 0, -2, 0, 3, 0, 0, 0, 0, -3, 0, -2, -2, 4, 0, 0, 0, -4, 0, 0, 0, 0, 0, -6, -1, 0, 2, 0, 0, 0, 0, 0, -1, 0, 0, 0, 0, 0, 3, 2, -1, 0, 0, 0, 0, -2, -4, 0, 0, 0, 0, 0, 0, -1, -1, 0, -6, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0, 1, -1, 0, -4, 0, 0, 0, 0, 0, 3, 3, 0, 0, 0, 0, 2, 7, 6, 0, -2, -1, 0, 0, 9, 1, 0, 0, 0, 0, 0, 5, 0, 0, 0, -5, 0, 3, 0, 4, 0, 0, 0, 0, 0, 0, -2, 0, 2, -7, 10, 0, -1, 0, 0, -2, 0, 0, 3, 0, 0, -1, -3, 0, 0, -4, 0, 0, 0, -4, -1, 0, 0, 1, 0, 0, 2, -7, -3, 0, 0, -2, 0, 0, -10, 0, 0, 0, 0, 0, 0, -3, 9, 0, 1, 1, 0, -2, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 4, 0, 0, 0, 0, -1, -1, 0, 0, 0, 0, 0, -2, -7, 0, 12, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 0, 0, -1, 0, 0, 3, 0, 0, 0, 0, 0, -2, 0, 0, 0, 0, 6, 4, 0, 2, 0, 0, 0, 3, 2, 0, -2, 0, 0, 0, 2, -1, 0, -5, 2, -3, 0, -5, 0, -3, 0, 0, 0, 0, 2, 0, -3, 0, -1, 0, 0, 0, 4, -1, 2, 0, -16, 0, 0, 0, 0, 6, 0, -5, 0, 0, 0, 0, 1, 0, 0, -2, 0, 0, 0, -3, 0, 0, 0, 0, 0, 0, -3, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, -4, 0, 0, 0, 0, 0, -2, 0, 0, 5, -5, 0, 0, -3, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, -1, 0, 1, 0, 0, 0, 0, 0, 0, 0, -5, 0, 0, 0, 0, 0, 0, 6, -2, 0, -3, 1, 0, 0, 0, 0, 0, 0, 0, 0, -2, -2, 0, 0, 3, 0, 0, 0, -1, 6, 0, 0, -2, 0, 0, 0, -2, -3, 0, 0, -1, -2, 0, -1, 0, 2, 0, 0, 0, 0, 0, 2, -1, -2, 0, 1, -9, 0, 4, 0, 2, 0, 1, 0, 0, 0, -10, 0, 0, -2, 0, 0, 0, 7, 1, 0, 0, 4, 0, 0, 12, 0, 0, 0, -4, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, -2, 0, 3, 3, -5, 0, -1, 0, 0, 0, 0, 0, 6, 0, 0, 0, 2, -1, 0, 0, 0, 0, 0, 2, 3, 5, 0, 0, 0, 0, 0, 0, 0, 0, -10, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, -1, 0, -3, 4, 9, 0, 5, 0, 3, -2, 2, 0, 0, 0, 0, 0, 3, 0, 3, 0, 0, 0, 0, 3, -6, 0, 0, 0, 0, 0, 0, 0, -2, 0, -7, 0, -2, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, -3, -3, 0, -2, 0, 0, 0, 0, 3, 0, -5, 0, 0, -3, 0, -2, 0, 0, -10, 0, 0, 0, 3, 6, 0, -1, 0, 0, 0, 4, 0, 0, 3, 0, 0, 0, -10, 0, -9, 0, 0, 0, 0, 0, -9, 6, 6, 1, 3, 8, 0, 5, 0, 0, 0, -3, 0, 0, 1, 1, -3, 0, 0, 0, 0, 0, 5, -1, 0, 0, 0, 0, 0, -4, 0, 0, 0, 0, 0, 0, 0, 6, 0, -1, 0, 0, 0, 0, -4, 3, 6, 0, 5, 0, 0, 0, 3, 0, 2, 0, -3, 0, 0, 0, 9, 0, -7, 4, 0, 0, 0, -1, 0, -1, 0, 2, 0, 0, 1, 0, 0, 0, -1, -1, 9, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, -2, 3, 0, 5, 0, 1, 0, 0, 0, -10, 0, 0, 0, 0, 3, 0, 0, -2, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 3, 6, 0, 6, 0, -2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, -12, 3, 0, 0, -4, 0, 0, 0, -6, 0, 0, 0, 0, 0, -2, 1, -1, 3, 0, 0, 0, 6, 0, 0, 0, 0, 0, 0, 0, 6, 0, 0, 0, 0, 0, 0, -3, 0, 0, 0, 0, 0, 0, 2, 0, -4, 0, 0, -1, -1, 0, 0, -2, -3, 0, 3, 0, 0, 0, 2, -9, 5, 4, 5, 0, 0, -3, 5, 0, 0, -3, 0, 0, -2, 5, 7, 0, -2, 0, 0, 0, 9, 0, -9, 0, 0, 0, 0, 1, 1, 0, 2, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, -7, 0, 3, 0, 0, 0, 0, 0, -3, 0, 0, 0, -1, 0, 0, 0, -3, 0, 0, -3, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, -1, 0, 0, 0, -6, -2, 3, 0, -5, 0, 0, 0, -2, 0, 0, 0, 0, 0, -1, 0, 0, 0, 0, 0, -7, -2, 0, 0, 0, 0, 1, 0, -6, 0, 0, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0, 0, 3, 2, -2, 2, 0, 0, 0, -1, -3, 0, 0, 2, 0, 0, 1, -3, 0, 2, -3, 0, 0, 0, 0, -5, -3, 0, 0, 0, 0, 0, 0, 0, 0, 4, -3, 2, 0, 0, 0, -3, 0, 0, 0, 0, 12, -1, -2, 0, 0, 0, 4, 0, -3, -3, 0, 0, 9, 0, 0, 0, 0, 0, 0, 0, -8, 0, 0, -5, 0, 0, 0, -3, 0, 0, 0, 0, 0, 0, 6, 0, 0, 0, -2, 0, 0, 0, 0, 0, 0, 0, -3, -5, -2, -3, 6, -3, 0, 5, 0, 3, 0, -2, 0, 0, -5, 0, -1, 0, -7, 0, 0, 0, -6, 0, 1, 0, 0, 0, 0, -5, 0, 2, 0, -2, 0, 0, 0, -8, 0, -3, 0, 0, 0, 0, 1, -1, -5, 6, 0, 0, 3, 0, 0, -5, 0, 0, 0, 0, 0, 4, 2, 1, 0, 0, 0, 0, 0, -5, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, -1, -9, -3, 0, -3, 0, 1, 0, 0, 0, 0, 0, -3, 1, -1, 3, 1, -2, 0, 0, -1, 0, 0, 0, 0, 0, 0, 1, 1, 0, -2, 0, 0, 0, -5, -5, 1, 0, 0, 0, 0, -1, 0, 5, 0, -3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -3, 0, 0, -4, -2, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 3, 1, 0, -2, 0, -6, 0, 0, 2, 2, 2, 0, 0, 0, 0, 0, 1, 0, 0, -2, 6, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, -10, 0, 9, -4, 0, -1, 0, 0, 4, 0, 0, 7, 0, 0, 0, 0, 5, -3, 0, 0, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0, 4, 3, 0, -2, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, -8, -7, 0, -3, 0, 8, 0, 0, -1, 0, 0, 0, 3, 0, 0, 1, 3, 8, 0, 0, 0, 0, 0, -3, 0, 0, 0, 0, 0, 0, -3, 0, 0, 0, 0, 0, -3, 0, 7, 0, -2, 0, 0, 0, 0, 0, 0, 3, 0, 1, 0, 2, 0, -6, 0, 0, 0, 1, 0, 0, 1, 2, 2, -2, -3, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, -2, 0, -7, 0, 5, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -5, 0, 2, -3, 0, -6, 0, 0, 10, 5, 0, -1, 0, 0, 0, 3, 0, -5, 8, 0, 0, 0, 5, 0, 1, 0, 0, 0, 0, -1, 0, -1, 0, 0, 0, 0, 0, -7, 0, 0, 0, 0, 0, 0, 0, 8, 0, 3, 0, 0, 9, 0, 0, -1, 0, 0, 0, 0, 0, 0, -2, 3, 0, 1, 0, 0, 0, 0, -4, 1, 0, -3, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 6, 0, 1, 0, 0, 0, 0, 0, 0, 1, 2, 8, 0, 9, 0, 0, 0, 2, 0, -3, 0, 0, 0, 2, 2, 0, -4, 1], 'weight': 1, '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

  
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-0.11666666666666667, -0.3333333333333333, -0.1, -0.3, -0.016666666666666666, -0.36666666666666664, -0.03333333333333333, -0.016666666666666666, -0.06666666666666667, -0.13333333333333333, -0.3333333333333333, -0.3333333333333333, -0.21666666666666667, -0.06666666666666667, -0.11666666666666667, -0.18333333333333332, -0.3333333333333333, -0.43333333333333335, -0.3333333333333333, -0.21666666666666667, -0.4, -0.4666666666666667, 0.03333333333333333, -0.15, -0.2, -0.31666666666666665, -0.26666666666666666, -0.4666666666666667, 0.0, -0.13333333333333333, -0.03333333333333333, -0.3333333333333333, -0.48333333333333334, -0.26666666666666666, 0.16666666666666666, -0.2, 0.13333333333333333, -0.11666666666666667, -0.48333333333333334, -0.36666666666666664, -0.2, -0.13333333333333333, -0.13333333333333333, -0.2833333333333333, 0.03333333333333333, -0.45, -0.23333333333333334, -0.1, -0.43333333333333335, -0.05, -0.2, 0.13333333333333333, 0.4, -0.3333333333333333, -0.06666666666666667, -0.11666666666666667, -0.2, -0.23333333333333334, -0.15, -0.13333333333333333, -0.4, -0.25, -0.43333333333333335, -0.016666666666666666, -0.3, 0.23333333333333334, -0.3333333333333333, -0.21666666666666667, 0.26666666666666666, 0.4, -0.26666666666666666, -0.16666666666666666, -0.3, -0.43333333333333335, -0.1, -0.3, -0.15, -0.4666666666666667, -0.3333333333333333, -0.4166666666666667, -0.4, -0.43333333333333335, -0.31666666666666665, -0.4, -0.05, -0.3333333333333333, -0.4, -0.03333333333333333, 0.3, -0.18333333333333332, 0.0, -0.18333333333333332, -0.4666666666666667, -0.35, -0.08333333333333333, -0.4, -0.36666666666666664, -0.2833333333333333, -0.4, -0.06666666666666667, -0.4, -0.1, 0.0, -0.06666666666666667, -0.26666666666666666, -0.13333333333333333, -0.03333333333333333, -0.4, -0.38333333333333336, -0.3, -0.23333333333333334, -0.3, -0.36666666666666664, -0.13333333333333333, -0.4166666666666667, -0.25, -0.25, -0.3333333333333333, -0.23333333333333334, -0.23333333333333334, -0.08333333333333333, -0.03333333333333333, 0.43333333333333335, -0.4666666666666667, -0.13333333333333333, -0.43333333333333335, -0.23333333333333334, -0.2833333333333333, 0.23333333333333334, 0.03333333333333333, 0.03333333333333333, -0.36666666666666664, -0.4666666666666667, -0.08333333333333333, -0.35, 0.43333333333333335, -0.43333333333333335, -0.18333333333333332, -0.16666666666666666, -0.06666666666666667, -0.13333333333333333, -0.2, -0.26666666666666666, -0.4, -0.06666666666666667, -0.4666666666666667, -0.43333333333333335, -0.4, -0.3333333333333333, -0.31666666666666665, -0.23333333333333334, -0.4666666666666667, -0.3333333333333333, -0.16666666666666666, -0.2, -0.26666666666666666, -0.4666666666666667, -0.43333333333333335, -0.3333333333333333, -0.18333333333333332, 0.4, -0.2, 0.03333333333333333, -0.23333333333333334, -0.016666666666666666, -0.1, -0.13333333333333333, -0.13333333333333333, -0.4666666666666667, -0.2, -0.1, -0.2, -0.11666666666666667, -0.13333333333333333, -0.23333333333333334, -0.26666666666666666, -0.48333333333333334, -0.2, -0.4666666666666667, -0.45, -0.13333333333333333, -0.3333333333333333, -0.06666666666666667, -0.36666666666666664, -0.4, -0.4666666666666667, -0.3, -0.06666666666666667, -0.18333333333333332, -0.26666666666666666, -0.11666666666666667, -0.4666666666666667, 0.06666666666666667, -0.05, -0.4666666666666667, -0.26666666666666666, -0.4666666666666667, -0.31666666666666665, -0.016666666666666666, -0.35, 0.03333333333333333, 0.16666666666666666, -0.16666666666666666, -0.03333333333333333, -0.06666666666666667, -0.4, 0.2], 'char_orbit_index': 84, 'conrey_index': 179, 'dual_conrey_index': 239, 'dual_embedding_index': 1, 'dual_embedding_m': 2, 'embedding_index': 1, 'embedding_m': 1, 'embedding_root_imag': -0.20791169081775934, 'embedding_root_real': -0.9781476007338057, 'hecke_orbit': 2, 'hecke_orbit_code': 4509303360718660, 'label': '1860.1.df.b.179.1', 'level': 1860, 'weight': 1}
• 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': 1860, 'a4_dim': 0, 'a5_dim': 0, 'analytic_conductor': 0.9282609234973844, 'char_conductor': 1860, 'char_degree': 8, 'char_is_real': False, 'char_orbit_index': 84, 'char_orbit_label': 'df', 'char_order': 30, 'char_parity': -1, 'char_values': [1860, 30, [931, 1241, 1117, 1801], [15, 15, 15, 13]], 'conrey_index': 179, 'cusp_dim': 32, 'dihedral_dim': 32, 'dim': 32, 'eis_dim': 64, 'eis_new_dim': 64, 'hecke_orbit_code': 5703733348164, 'hecke_orbit_dims': [8, 8, 8, 8], 'label': '1860.1.df', 'level': 1860, '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, 5, 31], 'level_radical': 930, 'mf_dim': 96, 'mf_new_dim': 96, 'num_forms': 4, 'prim_orbit_index': 84, 'relative_dim': 4, 's4_dim': 0, 'sturm_bound': 384, 'trace_bound': 3, 'trace_display': [0, 0, 0, 0], 'traces': [32, 0, 0, 4, 0, 6, 0, 0, 4, 2, 0, 0, 0, 0, 0, 4, 0, 0, 0, 0, 0, 0, 0, 0, -16, 0, 0, 0, 0, 0, 0, 0, 0, 6, 0, -2, 0, 0, 0, -4, 0, 0, 0, 0, 0, -10, 0, 0, -4, 0, 0, 0, 0, -10, 0, 0, 0, 0, 0, 10, 0, 0, 0, -8, 0, 0, 0, 0, 12, 0, 0, 0, 0, 0, 0, 4, 0, 0, 0, 0, 4, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, -8, 0, -6, 0, 0, 0, -2, 0, 0, 0, 0, 0, 20, 0, 0, -24, 0, 0, 0, 0, 14, 0, 0, 0, 0, 0, 0, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 18, 0, 0, 0, 0, -28, 0, 0, 18, 0, 0, 0, 0, 0, -6, 0, 0, 0, 0, 0, 0, 0, 0, 0, -8, 0, 0, 0, 0, 0, -6, 0, 0, -4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -20, 0, 2, 0, 0, 0, -8, 0, 0, 0, 0, 0, 12, 0, 0, 0, 0, 0, 0, 0, -6, 0, 0, 0, 0, 0, 0, 0, 0, 0, -20, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -8, 18, 0, 0, 20, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -10, -12, 0, 0, -10, 0, 0, 0, 0, -8, -4, 0, 0, 0, 0, 0, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -6, 0, -16, 0, 0, 0, 0, 0, 0, 0, 0, 12, 0, 0, 0, -8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 0, -30, 0, 0, 0, 4, 0, 0, 0, 0, 0, -24, 0, 0, 0, 0, -20, 0, 0, -2, 0, 0, 0, 0, 0, 0, 0, 0, 0, -6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -6, 0, 0, 12, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, -28, 0, 0, 0, 0, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 10, 0, 0, 0, 0, 0, 0, 0, -4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 0, 0, 0, 0, 0, -2, 0, 0, 0, 0, 0, 0, 0, 0, 12, 0, 0, 0, 0, 12, 0, 0, 0, 0, 0, 0, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -8, 0, 0, 0, 0, -4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 24, 0, 2, 0, 0, 0, 12, 0, 0, 0, 0, 32, -4, 0, 0, 0, 0, 0, 0, 0, -8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 18, 0, -6, 0, 0, 0, -2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -4, 0, 0, 0, 0, 0, 0, 0, 0, 24, 0, 0, 0, -8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 16, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 14, 24, 0, 0, 6, 0, 0, 0, 0, 12, 0, 0, 0, 0, 0, 0, -10, 0, 0, 0, 0, 0, 0, 0, -6, -4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, -8, 0, 0, 12, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 12, 0, 0, 0, 0, 0, 0, 0, 0, -4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 16, 0, 0, 0, -16, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 18, 0, 0, 0, 0, 0, 0, 0, -2, 0, 0, 0, 0, 0, 0, -4, 0, 0, -10, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 12, 12, 0, 0, 0, 0, 8, 0, 0, 0, 14, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -6, 0, 0, -20, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 20, 0, -6, 0, 0, -8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -12, 14, 0, 0, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 12, 0, 0, 0, 0, -4, 10, 0, 0, 0, 0, 0, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 0, 0, 0, 0, 0, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 8, 0, 0, 0, 0, 0, 0, 8, 0, 0, -10, 0, -6, 0, 0, 0, -6, 0, 0, 0, 0, 0, -10, 0, 0, 0, 0, 0, 0, 0, 0, 8, 0, 0, 0, 0, 0, 0, 0, 0, -12, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 0, 0, 0, 4, 0, -14, 0, 0, 0, 0, 0, 0, 0, 0, 0, -10, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 10, 0, 0, 0, 0, 0, -16, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 10, 0, 0, 0, 0, 0, 0, -8, 0, 0, 6, 0, 0, 0, 0, 24, 0, 0, 0, 0, 0, 0, -10, 0, 0, 0, 0, -8, 0, 0, 0, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -16, 0, 0, 0, 8], 'weight': 1, '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: 39975362
    {'conductor': 1, 'degree': 1, 'order': 1, 'parity': 1, 'source_conrey_index': 179, 'source_dim': 8, 'source_embedding_index': 1, 'source_hecke_orbit_code': 4509303360718660, 'source_is_minimal': True, 'source_label': '1860.1.df.b.179.1', 'source_level': 1860, 'target_conrey_index': 179, 'target_dim': 8, 'target_embedding_index': 1, 'target_hecke_orbit_code': 4509303360718660, 'target_is_minimal': True, 'target_label': '1860.1.df.b.179.1', 'target_level': 1860, 'twist_class_label': '1860.1.df.a.179.1', 'twist_class_level': 1860, 'twisting_char_label': '1.1', 'twisting_conrey_index': 1, 'weight': 1}
  • id: 39975363
    {'conductor': 3, 'degree': 1, 'order': 2, 'parity': -1, 'source_conrey_index': 179, 'source_dim': 8, 'source_embedding_index': 1, 'source_hecke_orbit_code': 4509303360718660, 'source_is_minimal': True, 'source_label': '1860.1.df.b.179.1', 'source_level': 1860, 'target_conrey_index': 179, 'target_dim': 8, 'target_embedding_index': 1, 'target_hecke_orbit_code': 9012902988089156, 'target_is_minimal': True, 'target_label': '1860.1.df.c.179.1', 'target_level': 1860, 'twist_class_label': '1860.1.df.a.179.1', 'twist_class_level': 1860, 'twisting_char_label': '3.2', 'twisting_conrey_index': 2, 'weight': 1}
  • id: 39975364
    {'conductor': 4, 'degree': 1, 'order': 2, 'parity': -1, 'source_conrey_index': 179, 'source_dim': 8, 'source_embedding_index': 1, 'source_hecke_orbit_code': 4509303360718660, 'source_is_minimal': True, 'source_label': '1860.1.df.b.179.1', 'source_level': 1860, 'target_conrey_index': 179, 'target_dim': 8, 'target_embedding_index': 1, 'target_hecke_orbit_code': 5703733348164, 'target_is_minimal': True, 'target_label': '1860.1.df.a.179.1', 'target_level': 1860, 'twist_class_label': '1860.1.df.a.179.1', 'twist_class_level': 1860, 'twisting_char_label': '4.3', 'twisting_conrey_index': 3, 'weight': 1}
  • id: 39975365
    {'conductor': 5, 'degree': 1, 'order': 2, 'parity': 1, 'source_conrey_index': 179, 'source_dim': 8, 'source_embedding_index': 1, 'source_hecke_orbit_code': 4509303360718660, 'source_is_minimal': True, 'source_label': '1860.1.df.b.179.1', 'source_level': 1860, 'target_conrey_index': 179, 'target_dim': 8, 'target_embedding_index': 1, 'target_hecke_orbit_code': 9012902988089156, 'target_is_minimal': True, 'target_label': '1860.1.df.c.179.1', 'target_level': 1860, 'twist_class_label': '1860.1.df.a.179.1', 'twist_class_level': 1860, 'twisting_char_label': '5.4', 'twisting_conrey_index': 4, 'weight': 1}
  • id: 39975366
    {'conductor': 12, 'degree': 1, 'order': 2, 'parity': 1, 'source_conrey_index': 179, 'source_dim': 8, 'source_embedding_index': 1, 'source_hecke_orbit_code': 4509303360718660, 'source_is_minimal': True, 'source_label': '1860.1.df.b.179.1', 'source_level': 1860, 'target_conrey_index': 179, 'target_dim': 8, 'target_embedding_index': 1, 'target_hecke_orbit_code': 13516502615459652, 'target_is_minimal': True, 'target_label': '1860.1.df.d.179.1', 'target_level': 1860, 'twist_class_label': '1860.1.df.a.179.1', 'twist_class_level': 1860, 'twisting_char_label': '12.11', 'twisting_conrey_index': 11, 'weight': 1}
  • id: 39975367
    {'conductor': 15, 'degree': 1, 'order': 2, 'parity': -1, 'source_conrey_index': 179, 'source_dim': 8, 'source_embedding_index': 1, 'source_hecke_orbit_code': 4509303360718660, 'source_is_minimal': True, 'source_label': '1860.1.df.b.179.1', 'source_level': 1860, 'target_conrey_index': 179, 'target_dim': 8, 'target_embedding_index': 1, 'target_hecke_orbit_code': 4509303360718660, 'target_is_minimal': True, 'target_label': '1860.1.df.b.179.1', 'target_level': 1860, 'twist_class_label': '1860.1.df.a.179.1', 'twist_class_level': 1860, 'twisting_char_label': '15.14', 'twisting_conrey_index': 14, 'weight': 1}
  • id: 39975368
    {'conductor': 20, 'degree': 1, 'order': 2, 'parity': -1, 'source_conrey_index': 179, 'source_dim': 8, 'source_embedding_index': 1, 'source_hecke_orbit_code': 4509303360718660, 'source_is_minimal': True, 'source_label': '1860.1.df.b.179.1', 'source_level': 1860, 'target_conrey_index': 179, 'target_dim': 8, 'target_embedding_index': 1, 'target_hecke_orbit_code': 13516502615459652, 'target_is_minimal': True, 'target_label': '1860.1.df.d.179.1', 'target_level': 1860, 'twist_class_label': '1860.1.df.a.179.1', 'twist_class_level': 1860, 'twisting_char_label': '20.19', 'twisting_conrey_index': 19, 'weight': 1}
  • id: 39975369
    {'conductor': 31, 'degree': 8, 'order': 30, 'parity': -1, 'source_conrey_index': 179, 'source_dim': 8, 'source_embedding_index': 1, 'source_hecke_orbit_code': 4509303360718660, 'source_is_minimal': True, 'source_label': '1860.1.df.b.179.1', 'source_level': 1860, 'target_conrey_index': 239, 'target_dim': 8, 'target_embedding_index': 1, 'target_hecke_orbit_code': 5703733348164, 'target_is_minimal': True, 'target_label': '1860.1.df.a.239.1', 'target_level': 1860, 'twist_class_label': '1860.1.df.a.179.1', 'twist_class_level': 1860, 'twisting_char_label': '31.22', 'twisting_conrey_index': 22, 'weight': 1}
  • id: 39975370
    {'conductor': 60, 'degree': 1, 'order': 2, 'parity': 1, 'source_conrey_index': 179, 'source_dim': 8, 'source_embedding_index': 1, 'source_hecke_orbit_code': 4509303360718660, 'source_is_minimal': True, 'source_label': '1860.1.df.b.179.1', 'source_level': 1860, 'target_conrey_index': 179, 'target_dim': 8, 'target_embedding_index': 1, 'target_hecke_orbit_code': 5703733348164, 'target_is_minimal': True, 'target_label': '1860.1.df.a.179.1', 'target_level': 1860, 'twist_class_label': '1860.1.df.a.179.1', 'twist_class_level': 1860, 'twisting_char_label': '60.59', 'twisting_conrey_index': 59, 'weight': 1}
  • id: 39975371
    {'conductor': 93, 'degree': 8, 'order': 30, 'parity': 1, 'source_conrey_index': 179, 'source_dim': 8, 'source_embedding_index': 1, 'source_hecke_orbit_code': 4509303360718660, 'source_is_minimal': True, 'source_label': '1860.1.df.b.179.1', 'source_level': 1860, 'target_conrey_index': 239, 'target_dim': 8, 'target_embedding_index': 1, 'target_hecke_orbit_code': 13516502615459652, 'target_is_minimal': True, 'target_label': '1860.1.df.d.239.1', 'target_level': 1860, 'twist_class_label': '1860.1.df.a.179.1', 'twist_class_level': 1860, 'twisting_char_label': '93.53', 'twisting_conrey_index': 53, 'weight': 1}
  • id: 39975372
    {'conductor': 124, 'degree': 8, 'order': 30, 'parity': 1, 'source_conrey_index': 179, 'source_dim': 8, 'source_embedding_index': 1, 'source_hecke_orbit_code': 4509303360718660, 'source_is_minimal': True, 'source_label': '1860.1.df.b.179.1', 'source_level': 1860, 'target_conrey_index': 239, 'target_dim': 8, 'target_embedding_index': 1, 'target_hecke_orbit_code': 4509303360718660, 'target_is_minimal': True, 'target_label': '1860.1.df.b.239.1', 'target_level': 1860, 'twist_class_label': '1860.1.df.a.179.1', 'twist_class_level': 1860, 'twisting_char_label': '124.115', 'twisting_conrey_index': 115, 'weight': 1}
  • id: 39975373
    {'conductor': 155, 'degree': 8, 'order': 30, 'parity': -1, 'source_conrey_index': 179, 'source_dim': 8, 'source_embedding_index': 1, 'source_hecke_orbit_code': 4509303360718660, 'source_is_minimal': True, 'source_label': '1860.1.df.b.179.1', 'source_level': 1860, 'target_conrey_index': 239, 'target_dim': 8, 'target_embedding_index': 1, 'target_hecke_orbit_code': 13516502615459652, 'target_is_minimal': True, 'target_label': '1860.1.df.d.239.1', 'target_level': 1860, 'twist_class_label': '1860.1.df.a.179.1', 'twist_class_level': 1860, 'twisting_char_label': '155.84', 'twisting_conrey_index': 84, 'weight': 1}
  • id: 39975374
    {'conductor': 372, 'degree': 8, 'order': 30, 'parity': -1, 'source_conrey_index': 179, 'source_dim': 8, 'source_embedding_index': 1, 'source_hecke_orbit_code': 4509303360718660, 'source_is_minimal': True, 'source_label': '1860.1.df.b.179.1', 'source_level': 1860, 'target_conrey_index': 239, 'target_dim': 8, 'target_embedding_index': 1, 'target_hecke_orbit_code': 9012902988089156, 'target_is_minimal': True, 'target_label': '1860.1.df.c.239.1', 'target_level': 1860, 'twist_class_label': '1860.1.df.a.179.1', 'twist_class_level': 1860, 'twisting_char_label': '372.239', 'twisting_conrey_index': 239, 'weight': 1}
  • id: 39975375
    {'conductor': 465, 'degree': 8, 'order': 30, 'parity': 1, 'source_conrey_index': 179, 'source_dim': 8, 'source_embedding_index': 1, 'source_hecke_orbit_code': 4509303360718660, 'source_is_minimal': True, 'source_label': '1860.1.df.b.179.1', 'source_level': 1860, 'target_conrey_index': 239, 'target_dim': 8, 'target_embedding_index': 1, 'target_hecke_orbit_code': 5703733348164, 'target_is_minimal': True, 'target_label': '1860.1.df.a.239.1', 'target_level': 1860, 'twist_class_label': '1860.1.df.a.179.1', 'twist_class_level': 1860, 'twisting_char_label': '465.239', 'twisting_conrey_index': 239, 'weight': 1}
  • id: 39975376
    {'conductor': 620, 'degree': 8, 'order': 30, 'parity': 1, 'source_conrey_index': 179, 'source_dim': 8, 'source_embedding_index': 1, 'source_hecke_orbit_code': 4509303360718660, 'source_is_minimal': True, 'source_label': '1860.1.df.b.179.1', 'source_level': 1860, 'target_conrey_index': 239, 'target_dim': 8, 'target_embedding_index': 1, 'target_hecke_orbit_code': 9012902988089156, 'target_is_minimal': True, 'target_label': '1860.1.df.c.239.1', 'target_level': 1860, 'twist_class_label': '1860.1.df.a.179.1', 'twist_class_level': 1860, 'twisting_char_label': '620.239', 'twisting_conrey_index': 239, 'weight': 1}
  • id: 39975377
    {'conductor': 1860, 'degree': 8, 'order': 30, 'parity': -1, 'source_conrey_index': 179, 'source_dim': 8, 'source_embedding_index': 1, 'source_hecke_orbit_code': 4509303360718660, 'source_is_minimal': True, 'source_label': '1860.1.df.b.179.1', 'source_level': 1860, 'target_conrey_index': 239, 'target_dim': 8, 'target_embedding_index': 1, 'target_hecke_orbit_code': 4509303360718660, 'target_is_minimal': True, 'target_label': '1860.1.df.b.239.1', 'target_level': 1860, 'twist_class_label': '1860.1.df.a.179.1', 'twist_class_level': 1860, 'twisting_char_label': '1860.239', 'twisting_conrey_index': 239, 'weight': 1}
• mf_hecke_charpolys •

  Column	Type
  charpoly_factorization	jsonb
  hecke_orbit_code	bigint
  p	integer

  
  
  • id: 2249975
    {'charpoly_factorization': [[[1, 1, 0, -1, -1, -1, 0, 1, 1], 1]], 'hecke_orbit_code': 4509303360718660, 'p': 2}
  • id: 2249976
    {'charpoly_factorization': [[[1, -1, 0, 1, -1, 1, 0, -1, 1], 1]], 'hecke_orbit_code': 4509303360718660, 'p': 3}
  • id: 2249977
    {'charpoly_factorization': [[[1, 1, 1], 4]], 'hecke_orbit_code': 4509303360718660, 'p': 5}
  • id: 2249978
    {'charpoly_factorization': [[[0, 1], 8]], 'hecke_orbit_code': 4509303360718660, 'p': 7}
  • id: 2249979
    {'charpoly_factorization': [[[0, 1], 8]], 'hecke_orbit_code': 4509303360718660, 'p': 11}
  • id: 2249980
    {'charpoly_factorization': [[[0, 1], 8]], 'hecke_orbit_code': 4509303360718660, 'p': 13}
  • id: 2249981
    {'charpoly_factorization': [[[81, -81, 54, -27, 9, -9, 6, -3, 1], 1]], 'hecke_orbit_code': 4509303360718660, 'p': 17}
  • id: 2249982
    {'charpoly_factorization': [[[1, -1, -1, 8, 9, 6, 6, 2, 1], 1]], 'hecke_orbit_code': 4509303360718660, 'p': 19}
  • id: 2249983
    {'charpoly_factorization': [[[1, 2, 4, 3, 1], 2]], 'hecke_orbit_code': 4509303360718660, 'p': 23}
  • id: 2249984
    {'charpoly_factorization': [[[0, 1], 8]], 'hecke_orbit_code': 4509303360718660, 'p': 29}
  • id: 2249985
    {'charpoly_factorization': [[[1, 1, 1, 1, 1], 2]], 'hecke_orbit_code': 4509303360718660, 'p': 31}
  • id: 2249986
    {'charpoly_factorization': [[[0, 1], 8]], 'hecke_orbit_code': 4509303360718660, 'p': 37}
  • id: 2249987
    {'charpoly_factorization': [[[0, 1], 8]], 'hecke_orbit_code': 4509303360718660, 'p': 41}
  • id: 2249988
    {'charpoly_factorization': [[[0, 1], 8]], 'hecke_orbit_code': 4509303360718660, 'p': 43}
  • id: 2249989
    {'charpoly_factorization': [[[1, 5, 13, 15, 4, -5, -3, 0, 1], 1]], 'hecke_orbit_code': 4509303360718660, 'p': 47}
  • id: 2249990
    {'charpoly_factorization': [[[25, -25, 25, 0, -5, 10, 0, 0, 1], 1]], 'hecke_orbit_code': 4509303360718660, 'p': 53}
  • id: 2249991
    {'charpoly_factorization': [[[0, 1], 8]], 'hecke_orbit_code': 4509303360718660, 'p': 59}
  • id: 2249992
    {'charpoly_factorization': [[[1, 0, 8, 0, 14, 0, 7, 0, 1], 1]], 'hecke_orbit_code': 4509303360718660, 'p': 61}
  • id: 2249993
    {'charpoly_factorization': [[[0, 1], 8]], 'hecke_orbit_code': 4509303360718660, 'p': 67}
  • id: 2249994
    {'charpoly_factorization': [[[0, 1], 8]], 'hecke_orbit_code': 4509303360718660, 'p': 71}
  • id: 2249995
    {'charpoly_factorization': [[[0, 1], 8]], 'hecke_orbit_code': 4509303360718660, 'p': 73}
  • id: 2249996
    {'charpoly_factorization': [[[1, -6, 20, 11, -6, -4, 0, -1, 1], 1]], 'hecke_orbit_code': 4509303360718660, 'p': 79}
  • id: 2249997
    {'charpoly_factorization': [[[1, 9, 20, -4, 9, -4, 0, -1, 1], 1]], 'hecke_orbit_code': 4509303360718660, 'p': 83}
  • id: 2249998
    {'charpoly_factorization': [[[0, 1], 8]], 'hecke_orbit_code': 4509303360718660, 'p': 89}
  • id: 2249999
    {'charpoly_factorization': [[[0, 1], 8]], 'hecke_orbit_code': 4509303360718660, 'p': 97}
• 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': 2, 'label': '1860.1.df.b', 'level': 1860, 'portrait': 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', 'weight': 1}
• mf_hecke_traces •

  Column	Type
  hecke_orbit_code	bigint
  n	integer
  trace_an	numeric

  
  
  • id: 25864477
    {'hecke_orbit_code': 4509303360718660, 'n': 1, 'trace_an': 8}
  • id: 25864478
    {'hecke_orbit_code': 4509303360718660, 'n': 2, 'trace_an': -1}
  • id: 25864479
    {'hecke_orbit_code': 4509303360718660, 'n': 3, 'trace_an': 1}
  • id: 25864480
    {'hecke_orbit_code': 4509303360718660, 'n': 4, 'trace_an': 1}
  • id: 25864481
    {'hecke_orbit_code': 4509303360718660, 'n': 5, 'trace_an': -4}
  • id: 25864482
    {'hecke_orbit_code': 4509303360718660, 'n': 6, 'trace_an': 2}
  • id: 25864483
    {'hecke_orbit_code': 4509303360718660, 'n': 7, 'trace_an': 0}
  • id: 25864484
    {'hecke_orbit_code': 4509303360718660, 'n': 8, 'trace_an': 2}
  • id: 25864485
    {'hecke_orbit_code': 4509303360718660, 'n': 9, 'trace_an': 1}
  • id: 25864486
    {'hecke_orbit_code': 4509303360718660, 'n': 10, 'trace_an': -1}
  • id: 25864487
    {'hecke_orbit_code': 4509303360718660, 'n': 11, 'trace_an': 0}
  • id: 25864488
    {'hecke_orbit_code': 4509303360718660, 'n': 12, 'trace_an': 1}
  • id: 25864489
    {'hecke_orbit_code': 4509303360718660, 'n': 13, 'trace_an': 0}
  • id: 25864490
    {'hecke_orbit_code': 4509303360718660, 'n': 14, 'trace_an': 0}
  • id: 25864491
    {'hecke_orbit_code': 4509303360718660, 'n': 15, 'trace_an': -2}
  • id: 25864492
    {'hecke_orbit_code': 4509303360718660, 'n': 16, 'trace_an': 1}
  • id: 25864493
    {'hecke_orbit_code': 4509303360718660, 'n': 17, 'trace_an': 3}
  • id: 25864494
    {'hecke_orbit_code': 4509303360718660, 'n': 18, 'trace_an': -1}
  • id: 25864495
    {'hecke_orbit_code': 4509303360718660, 'n': 19, 'trace_an': -2}
  • id: 25864496
    {'hecke_orbit_code': 4509303360718660, 'n': 20, 'trace_an': -2}
  • id: 25864497
    {'hecke_orbit_code': 4509303360718660, 'n': 21, 'trace_an': 0}
  • id: 25864498
    {'hecke_orbit_code': 4509303360718660, 'n': 22, 'trace_an': 0}
  • id: 25864499
    {'hecke_orbit_code': 4509303360718660, 'n': 23, 'trace_an': -6}
  • id: 25864500
    {'hecke_orbit_code': 4509303360718660, 'n': 24, 'trace_an': -1}
  • id: 25864501
    {'hecke_orbit_code': 4509303360718660, 'n': 25, 'trace_an': -4}
  • id: 25864502
    {'hecke_orbit_code': 4509303360718660, 'n': 26, 'trace_an': 0}
  • id: 25864503
    {'hecke_orbit_code': 4509303360718660, 'n': 27, 'trace_an': -2}
  • id: 25864504
    {'hecke_orbit_code': 4509303360718660, 'n': 28, 'trace_an': 0}
  • id: 25864505
    {'hecke_orbit_code': 4509303360718660, 'n': 29, 'trace_an': 0}
  • id: 25864506
    {'hecke_orbit_code': 4509303360718660, 'n': 30, 'trace_an': -1}
  • id: 25864507
    {'hecke_orbit_code': 4509303360718660, 'n': 31, 'trace_an': -2}
  • id: 25864508
    {'hecke_orbit_code': 4509303360718660, 'n': 32, 'trace_an': 4}
  • id: 25864509
    {'hecke_orbit_code': 4509303360718660, 'n': 33, 'trace_an': 0}
  • id: 25864510
    {'hecke_orbit_code': 4509303360718660, 'n': 34, 'trace_an': 0}
  • id: 25864511
    {'hecke_orbit_code': 4509303360718660, 'n': 35, 'trace_an': 0}
  • id: 25864512
    {'hecke_orbit_code': 4509303360718660, 'n': 36, 'trace_an': -2}
  • id: 25864513
    {'hecke_orbit_code': 4509303360718660, 'n': 37, 'trace_an': 0}
  • id: 25864514
    {'hecke_orbit_code': 4509303360718660, 'n': 38, 'trace_an': 0}
  • id: 25864515
    {'hecke_orbit_code': 4509303360718660, 'n': 39, 'trace_an': 0}
  • id: 25864516
    {'hecke_orbit_code': 4509303360718660, 'n': 40, 'trace_an': -1}
  • id: 25864517
    {'hecke_orbit_code': 4509303360718660, 'n': 41, 'trace_an': 0}
  • id: 25864518
    {'hecke_orbit_code': 4509303360718660, 'n': 42, 'trace_an': 0}
  • id: 25864519
    {'hecke_orbit_code': 4509303360718660, 'n': 43, 'trace_an': 0}
  • id: 25864520
    {'hecke_orbit_code': 4509303360718660, 'n': 44, 'trace_an': 0}
  • id: 25864521
    {'hecke_orbit_code': 4509303360718660, 'n': 45, 'trace_an': 1}
  • id: 25864522
    {'hecke_orbit_code': 4509303360718660, 'n': 46, 'trace_an': -3}
  • id: 25864523
    {'hecke_orbit_code': 4509303360718660, 'n': 47, 'trace_an': 0}
  • id: 25864524
    {'hecke_orbit_code': 4509303360718660, 'n': 48, 'trace_an': 8}
  • id: 25864525
    {'hecke_orbit_code': 4509303360718660, 'n': 49, 'trace_an': -1}
  • id: 25864526
    {'hecke_orbit_code': 4509303360718660, 'n': 50, 'trace_an': 2}
  • id: 25864527
    {'hecke_orbit_code': 4509303360718660, 'n': 51, 'trace_an': -3}
  • id: 25864528
    {'hecke_orbit_code': 4509303360718660, 'n': 52, 'trace_an': 0}
  • id: 25864529
    {'hecke_orbit_code': 4509303360718660, 'n': 53, 'trace_an': 0}
  • id: 25864530
    {'hecke_orbit_code': 4509303360718660, 'n': 54, 'trace_an': -1}
  • id: 25864531
    {'hecke_orbit_code': 4509303360718660, 'n': 55, 'trace_an': 0}
  • id: 25864532
    {'hecke_orbit_code': 4509303360718660, 'n': 56, 'trace_an': 0}
  • id: 25864533
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  • id: 25864534
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  • id: 25864535
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  • id: 25864536
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  • id: 25864537
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  • id: 25864538
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  • id: 25864539
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  • id: 25864540
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  • id: 25864541
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  • id: 25864542
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  • id: 25864543
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  • id: 25864544
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  • id: 25864545
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  • id: 25864546
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  • id: 25864547
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  • id: 25864548
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  • id: 25864549
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  • id: 25864550
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  • id: 25864551
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  • id: 25864552
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  • id: 25864553
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  • id: 25864554
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  • id: 25864555
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  • id: 25864556
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  • id: 25864557
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  • id: 25864558
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  • id: 25864559
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  • id: 25864560
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  • id: 25864561
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  • id: 25864562
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  • id: 25864563
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  • id: 25864564
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  • id: 25864565
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  • id: 25864566
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  • id: 25864567
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  • id: 25864568
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  • id: 25864569
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  • id: 25864570
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  • id: 25864571
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  • id: 25864572
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  • id: 25864573
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  • id: 25864574
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  • id: 25864575
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  • id: 25864576
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  • id: 25864577
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  • id: 25864578
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  • id: 25864579
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  • id: 25864580
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  • id: 25864581
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  • id: 25864582
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  • id: 25864583
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  • id: 25864584
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  • id: 25864585
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  • id: 25864586
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  • id: 25864587
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  • id: 25864588
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  • id: 25864589
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  • id: 25864590
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  • id: 25864591
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  • id: 25864592
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  • id: 25864593
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  • id: 25864594
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  • id: 25864595
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  • id: 25864596
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  • id: 25864597
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  • id: 25864598
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  • id: 25864599
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  • id: 25864600
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  • id: 25864601
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  • id: 25864602
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  • id: 25864603
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  • id: 25864604
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  • id: 25864605
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  • id: 25864606
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  • id: 25864607
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  • id: 25864608
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  • id: 25864609
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  • id: 25864610
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  • id: 25864611
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  • id: 25864612
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  • id: 25864613
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  • id: 25864614
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  • id: 25864615
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  • id: 25864616
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  • id: 25864617
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  • id: 25864618
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  • id: 25864619
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  • id: 25864620
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  • id: 25864621
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  • id: 25864622
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  • id: 25864623
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  • id: 25864624
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  • id: 25864625
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  • id: 25864626
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  • id: 25864627
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  • id: 25864628
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  • id: 25864629
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  • id: 25864630
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  • id: 25864631
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  • id: 25864632
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  • id: 25864633
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  • id: 25864634
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  • id: 25864635
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  • id: 25864636
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  • id: 25864637
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  • id: 25864638
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  • id: 25864639
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  • id: 25864640
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  • id: 25864641
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  • id: 25864642
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  • id: 25864643
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  • id: 25864644
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  • id: 25864645
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  • id: 25864646
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  • id: 25864647
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  • id: 25864648
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  • id: 25864649
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  • id: 25864650
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  • id: 25864651
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  • id: 25864652
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  • id: 25864653
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  • id: 25864654
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  • id: 25864655
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  • id: 25864656
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  • id: 25864657
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  • id: 25864658
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  • id: 25864659
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  • id: 25864660
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  • id: 25864661
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  • id: 25864662
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  • id: 25864663
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  • id: 25864664
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  • id: 25864665
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  • id: 25864666
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  • id: 25864667
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  • id: 25864668
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  • id: 25864669
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  • id: 25864670
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  • id: 25864671
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  • id: 25864672
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  • id: 25864673
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  • id: 25864674
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  • id: 25864675
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  • id: 25864676
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  • id: 25864677
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  • id: 25864678
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  • id: 25864679
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  • id: 25864680
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  • id: 25864681
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  • id: 25864682
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  • id: 25864683
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  • id: 25864684
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  • id: 25864685
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  • id: 25864686
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  • id: 25864687
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  • id: 25864688
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  • id: 25864689
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  • id: 25864690
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  • id: 25864691
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  • id: 25864692
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  • id: 25864693
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  • id: 25864694
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  • id: 25864695
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  • id: 25864696
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  • id: 25864697
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  • id: 25864698
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  • id: 25864699
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  • id: 25864700
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  • id: 25864701
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  • id: 25864702
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  • id: 25864703
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  • id: 25864704
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  • id: 25864705
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  • id: 25864706
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  • id: 25864707
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  • id: 25864708
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  • id: 25864709
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  • id: 25864710
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  • id: 25864711
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  • id: 25864712
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  • id: 25864713
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  • id: 25864714
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  • id: 25864715
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  • id: 25864716
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  • id: 25864717
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  • id: 25864718
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  • id: 25864719
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  • id: 25864720
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  • id: 25864721
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  • id: 25864722
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  • id: 25864723
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  • id: 25864724
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  • id: 25864725
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  • id: 25864726
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  • id: 25864727
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  • id: 25864728
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  • id: 25864729
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  • id: 25864730
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  • id: 25864731
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  • id: 25864732
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  • id: 25864733
    {'hecke_orbit_code': 4509303360718660, 'n': 991, 'trace_an': 2}
  • id: 25864734
    {'hecke_orbit_code': 4509303360718660, 'n': 997, 'trace_an': 0}