269 research outputs found
An Explicit CM Type Norm Formula and Effective Nonvanishing of Class Group L-functions for CM Fields
We show that the central value of class group L-functions of CM fields can be
expressed in terms of derivatives of real-analytic Hilbert Eisenstein series at
CM points. Then, following an idea of Iwaniec and Kowalski we obtain a
conditional explicit lower bound of class numbers of CM fields under a weaker
assumption. Some results in the proof lead to an effective nonvanishing result
for class group L-functions of general CM fields, generalizing the only known
ineffective results.Comment: Some typos are corrected. To appear in the Pacific Journal of Mat
Relative Trace Formula, Subconvexity and Quantitative Nonvanishing of Rankin-Selberg -functions for
Let be a fixed unitary cuspidal representation of
We establish a subconvex bound in the -aspect
for any unitary pure isobaric automorphic
representation of Moreover, the bound
improves in the standard -function case
We also prove an explicit lower bound for nonvanishing of central -values
for a suitable finite family of unitary cuspidal
representations of More generally, we address
the spectral side subconvexity in the case of uniform parameter growth, and a
quantitative form of simultaneous nonvanishing of central -values for
(over ) in both level and
eigenvalue aspects.
Among other ingredients, our proofs employ a new relative trace formula in
conjunction with P. Nelson's construction of archimedean test functions in
\cite{Nel21} and volume estimates in \cite{Nel20}.Comment: 79 page
Summing Hecke Eigenvalues over Polynomials
In this paper we estimate sums of the form ∑n≤X|aSymmπ(|f(n)|)|, for symmetric power lifts of automorphic representations π attached to holomorphic forms and polynomials f(x)∈Z[x] of arbitrary degree. We give new upper bounds for these sums under certain natural assumptions on f. Our results are unconditional when deg(f)≤4. Moreover, we study the analogous sum over polynomials in several variables. We obtain an estimate for all cubic polynomials in two variables that define elliptic curves
Non-vanishing of twists of -functions
Let be a unitary cuspidal automorphic representation of
. Let be given. We show that
there exists infinitely many primitive even (resp. odd) Dirichlet characters
with conductor co-prime to such that is
non-vanishing at the central point.
Our result has applications for the construction of -adic -functions
for following Loeffler-Pilloni-Skinner-Zerbes, the Bloch-Kato
conjecture and the Birch-Swinnerton-Dyer conjecture for abelian surfaces
following Loeffler-Zerbes, strong multiplicity one results for paramodular
cuspidal representations of and the
rationality of the central values of
-functions in the remaining non-regular weight case.Comment: 45 page
A Coarse Jacquet-Zagier Trace Formula for GL(n) with Applications
In this thesis we establish a coarse Jacquet-Zagier trace identity fo GL(n). This formula connects adjoint L-functions on GL(n) with Artin L-functions attached to certain induced Galois representations. We prove the absolute convergence when Re(s) > 1, and obtain holomorphic continuation under almost all character twists. Moreover, as an application, we obtain that holomorphy of certain adjoint L-functions for GL(n) implies Dedekind conjecture of degree n. Some nonvanishing results are also proved.</p
Modular development of deep potential for complex solid solutions
The multicomponent oxide solid solution is a versatile platform to tune the
delicate balance between competing spin, charge, orbital, and lattice degrees
of freedom for materials design and discovery. The development of
compositionally complex oxides with superior functional properties has been
largely empirical and serendipitous, in part due to the exceedingly complex
chemistry and structure of solid solutions that span a range of length scales.
The classical molecular dynamics (MD), as a powerful statistical method to
investigate materials properties over large spatial and temporal scales, often
plays a secondary role in computer-aided materials discovery because of the
limited availability and accuracy of classical force fields. Here, we introduce
the strategy of ``modular developing deep potential" (ModDP) that enables a
systematic development and improvement of deep neural network-based model
potential, termed as deep potential, for complex solid solutions with minimum
human intervention. The converged training database associated with an
end-member material is treated as an independent module and is reused to train
the deep potential of solid solutions via a concurrent learning procedure. We
apply ModDP to obtain classical force fields of two technologically important
solid solutions, PbSrTiO and HfZrO. For both
materials systems, a single model potential is capable of predicting various
properties of solid solutions including temperature-driven and
composition-driven phase transitions over a wide range of compositions. In
particular, the deep potential of PbSrTiO reproduces a few
known topological textures such as polar vortex lattice and electric dipole
waves in PbTiO/SrTiO superlattices, paving the way for MD
investigations on the dynamics of topological structures in response to
external stimuli.Comment: 32 pages, 9 figure
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