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S. Deodhar

Publications and source records attributed to S. Deodhar.

2 recordsLinked to original sources

Spectral synthesis with the complexity parameter

We show that spectral synthesis thresholds are governed by a quantitative spectral complexity parameter, the Fourier Ratio, in addition to the geometric size of the Fourier support. In the Euclidean setting, we prove that if a compactly supported measure has finite $\alpha$-dimensional packing measure and the associated Fourier ratio decays with asymptotic exponent $\kappa$, then the classical synthesis threshold improves from $\frac{2d}{\alpha}$ to $\frac{2(d-2\kappa)}{\alpha-2\kappa}$. We then establish an analogous result on compact Riemannian manifolds without boundary. In that setting the relevant object is a localized spectral Fourier ratio defined using Laplace--Beltrami spectral projectors. The resulting synthesis threshold is again determined by the decay exponent of this complexity parameter. These results place Euclidean and manifold spectral synthesis into a common framework in which geometric size and spectral complexity jointly govern uniqueness

math.CA

On spectral synthesis in ${\mathbb Z}_N^d$

A classical result due to Agranovsky and Narayanan (\cite{AN04}) says that if the support of the Fourier transform of $f: {\mathbb R}^n \to {\mathbb C}$ is carried by a smooth measure on a $d$-dimensional manifold $M$, and $f \in L^p({\mathbb R}^d)$ for $p \leq \frac{2n}{d}$, then $f$ is identically equal to $0$. In this paper, we investigate an analogous problem for functions $f: {\mathbb Z}_N^d \to {\mathbb C}$. Bourgain's celebrated result on $\Lambda_p$ sets (\cite{Bou89}), random constructions (\cite{Bab89}), and connections with the theory of exact signal recovery (\cite{DS89}, \cite{MS73}, \cite{IKLM24}, \cite{IM24}) play an important role.

math.CA