2014
DOI: 10.1090/s0002-9947-2014-06103-5
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Further refinement of strong multiplicity one for GL(2)

Abstract: Abstract. We obtain a sharp refinement of the strong multiplicity one theorem for the case of unitary non-dihedral cuspidal automorphic representations for GL(2). Given two unitary cuspidal automorphic representations for GL(2) that are not twist-equivalent, we also find sharp lower bounds for the number of places where the Hecke eigenvalues are not equal, for both the general and non-dihedral cases. We then construct examples to demonstrate that these results are sharp.

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Cited by 10 publications
(22 citation statements)
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References 41 publications
(78 reference statements)
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“…(2) If n = 3 and c > 5 7 , then ρ ≃ ρ ′ . When n = 2, if ρ and ρ ′ are automorphic, i.e., satisfy the strong Artin conjecture, then the above result already follows by [Wal14]. When n = 2, the strong Artin conjecture for ρ is known in many cases-for instance, if ρ has solvable image by Langlands [Lan80] and Tunnell [Tun81], or if F = Q and ρ is "odd" via Serre's conjecture by Khare-Wintenberger [KW09].…”
Section: 2mentioning
confidence: 88%
“…(2) If n = 3 and c > 5 7 , then ρ ≃ ρ ′ . When n = 2, if ρ and ρ ′ are automorphic, i.e., satisfy the strong Artin conjecture, then the above result already follows by [Wal14]. When n = 2, the strong Artin conjecture for ρ is known in many cases-for instance, if ρ has solvable image by Langlands [Lan80] and Tunnell [Tun81], or if F = Q and ρ is "odd" via Serre's conjecture by Khare-Wintenberger [KW09].…”
Section: 2mentioning
confidence: 88%
“…Examples. We now delineate the construction of two examples of matching densities already known, the first being an example of Serre that provides matching densities of the form 1 − 1/2k 2 and the second being a matching density of 17/32 from [Wa14a].…”
Section: 2mentioning
confidence: 99%
“…We now briefly outline an example with matching density 17/32 and refer the reader to [Wa14a] for further details. This will differ from the one above in that it does not rely on twisting the first representation with a character in order to obtain the second representation.…”
Section: 2mentioning
confidence: 99%
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