Tootfinder

Dynamics of the Kac Ring Model with switching scatterers
Leonid A. Bunimovich, Emilio N. M. Cirillo, Matteo Colangeli, Lamberto Rondoni
https://arxiv.org/abs/2510.04104 https://…

Dynamics of the Kac Ring Model with switching scatterers
We introduce a generalized version of the Kac ring model in which particles are of two types, black and white. Black particles modify the environment through which all particles move, thereby inducing indirect and potentially long-range interactions among them. Unlike the inert scatterers of Kac's original model, the scatterers in our setting possess internal states that change upon interaction with black particles and can be interpreted as energy levels of the environment. This makes the model…

Quantum chaos and semiclassical behavior in mushroom billiards I: Spectral statistics
Matic Orel, \v{C}rt Lozej, Marko Robnik, Hua Yan
https://arxiv.org/abs/2507.13823

Quantum chaos and semiclassical behavior in mushroom billiards I: Spectral statistics
We study the aspects of quantum chaos in mushroom billiards introduced by Bunimovich. This family of billiards classically has the property of mixed phase space with precisely one entirely regular and one fully chaotic (ergodic) component, whose size depends on the width w of the stem, and has two limiting geometries, namely the circle (as the integrable system) and stadium (as the fully chaotic system). Therefore, this one-parameter system is ideal to study the semiclassical behavior of the qu…

Quantum enhanced ensemble GANs for anomaly detection in continuous biomanufacturing
Rajiv Kailasanathan, William R. Clements, Mohammad Reza Boskabadi, Shawn M. Gibford, Emmanouil Papadakis, Christopher J. Savoie, Seyed Soheil Mansouri
https://arxiv.org/abs/2508.21438

Quantum enhanced ensemble GANs for anomaly detection in continuous biomanufacturing
The development of continuous biomanufacturing processes requires robust and early anomaly detection, since even minor deviations can compromise yield and stability, leading to disruptions in scheduling, reduced weekly production, and diminished economic performance. These processes are inherently complex and exhibit non-linear dynamics with intricate relationships between process variables, thus making advanced methods for anomaly detection essential for efficient operation. In this work, we p…

RAPTOR-GEN: RApid PosTeriOR GENerator for Bayesian Learning in Biomanufacturing
Wandi Xu, Wei Xie
https://arxiv.org/abs/2509.20753 https://arxiv.org/pdf/25…

RAPTOR-GEN: RApid PosTeriOR GENerator for Bayesian Learning in Biomanufacturing
Biopharmaceutical manufacturing is vital to public health but lacks the agility for rapid, on-demand production of biotherapeutics due to the complexity and variability of bioprocesses. To overcome this, we introduce RApid PosTeriOR GENerator (RAPTOR-GEN), a mechanism-informed Bayesian learning framework designed to accelerate intelligent digital twin development from sparse and heterogeneous experimental data. This framework is built on a multi-scale probabilistic knowledge graph (pKG), formul…

BiNoMaP: Learning Category-Level Bimanual Non-Prehensile Manipulation Primitives
Huayi Zhou, Kui Jia
https://arxiv.org/abs/2509.21256 https://arxiv.org/pdf…

BiNoMaP: Learning Category-Level Bimanual Non-Prehensile Manipulation Primitives
Non-prehensile manipulation, encompassing ungraspable actions such as pushing, poking, and pivoting, represents a critical yet underexplored domain in robotics due to its contact-rich and analytically intractable nature. In this work, we revisit this problem from two novel perspectives. First, we move beyond the usual single-arm setup and the strong assumption of favorable external dexterity such as walls, ramps, or edges. Instead, we advocate a generalizable dual-arm configuration and establis…