Latest papers
Learning the natural parameters $z \in \mathbb{R}^n$ of discrete distributions $\mu_z$ from independent samples constrained to a subset $S \subseteq \{0,1\}^n$ is a foundational challenge in high-dimensional statistics. Existing methods for…
Let $\Omega \Subset \mathbb{R}^{n}$ be a strictly convex bounded domain. Suppose $\mathbf{A} : \mathbb{R}^{Nn} \longrightarrow \mathbb{R}^{Nn}$, $\mathbf{B}: \mathbb{R}^{Nn} \longrightarrow \mathbb{R}^{N}$, $\mathbf{C}: \mathbb{R}^{N}…
I provide and introductory overview of the field of nuclear structure, with a focus on physical concepts. I describe some basic nuclear structure observables, followed by a qualitative description of nuclear forces. I then outline some…
We investigate finite-horizon, zero-sum controller-stopper games in which the stopper observes the state process and implements a feedback stopping rule. Building on a nonlinear Snell envelope representation for a related game established…
This paper considers the general problem of the design of boundary controllers for distributed parameter systems. The control objectives are the asymptotic stability of the closed-loop system, as well as the disturbance attenuation of…
We establish dispersive decay estimates for two-dimensional Dirac equations with bounded and unbounded domain walls, together with estimates for the analogous one-dimensional problem. These are paradigmatic models of bulk-edge…
Clustering of large deviations events in a stationary stochastic process depends critically on the interplay between the tail behavior of the marginal distribution and the strength of temporal dependence. In the class of doubly infinite…
In this work, we study Casimir wormhole solutions and investigate satisfaction of energy conditions in the framework of Einstein-Gauss-Bonnet (EGB) gravity. We firstly find traversable wormhole solutions supported by a general form for the…
Akbari, Elphick, Kumar, Pragada and Tang [Discrete Math. 349 (2026) 114953] conjectured that for every connected graph G, the line graph of G has at most one more positive than negative adjacency eigenvalue; equivalently, the signature of a…
Classical delay, chorus, and reverb effects model multiple pro- pagation paths using discrete delays or statistical distributions. This work proposes a model inspired by gravitational lensing, where an audio signal is treated as a wave…
This paper develops a two-stage hurdle model for predicting power outage occurrence and severity at the census-tract level. The proposed framework is then used to assess the sensitivity of power outage to socioeconomic, demographic, and…
Radon emanation from detector materials is a critical background for next-generation rare event searches, in particular those using noble liquid targets. While highly sensitive screening facilities mitigate this risk prior to detector…
Optical scattering has conventionally been regarded as an impediment in imaging research due to the degradation of image quality during reconstruction. Nevertheless, this study explores two cases in which optical scattering may serve a…
Finding Nash equilibria in the pure coordination game is trivial when every player interacts with every other player evenly. However, when players have a relational structure, the question becomes harder to answer. Here, we show that Nash…
Variational ans\"atze are a cornerstone of quantum many-body physics, providing compact approximations to complex ground states using finite resources. Recent quantum-technology advances have introduced a new class based on layered…
We show how finite-difference time-domain (FDTD) simulations can be extended to model ultrafast nonlinear microscopy, enabling the prediction of spatially-resolved pump--probe signals in arbitrary electromagnetic environments. Focusing on…
We construct Vaidya-type solutions of quasitopological gravity coupled to nonlinear electrodynamics in arbitrary spacetime dimensions. Starting from the corresponding static spherically symmetric charged solutions, we obtain their dynamical…
In this paper, we focus on a scheme in which three high-quality-factor mechanical modes of a hexagonal boron nitride (hBN) membrane monolayer are coupled to a common optically addressable spin defect present in the membrane via magnetic…
In this work, we investigate the application of Machine Learning (ML) algorithms to the identification and quantitative characterization of quantum entanglement in polarization-entangled photon pairs. The analysis is based on simulated…
Cat qubits can exhibit strong noise bias due to their exponentially enhanced bit-flip times and only polynomially reduced phase-flip times with increasing photon number, which makes them attractive candidates for hardware-efficient quantum…