Tootfinder

Transition to chaos with conical billiards
Lara Braverman, David R. Nelson
https://arxiv.org/abs/2508.02786 https://arxiv.org/pdf/2508.02786

Transition to chaos with conical billiards
We adapt ideas from geometrical optics and classical billiard dynamics to consider particle trajectories with constant velocity on a cone with specular reflections off an elliptical boundary formed by the intersection with a tilted plane, with tilt angle $γ$. We explore the dynamics as a function of $γ$ and the cone deficit angle $χ$ that controls the sharpness of the apex, where a point source of positive Gaussian curvature is concentrated. We find regions of the ($γ, χ$) plane where, dep…

Compressibility and speed of sound in magnetized nuclear matter with broken scale invariance
Pallabi Parui, Nilanjan Chaudhuri, Pradip Roy, Sourav Sarkar
https://arxiv.org/abs/2509.15700

Compressibility and speed of sound in magnetized nuclear matter with broken scale invariance
The thermodynamical properties of magnetized nuclear matter at finite temperature and baryon chemical potential are studied within an effective model incorporating the QCD trace anomaly effect. The presence of magnetic field induces anisotropic structure in the energy momentum tensor due to the broken rotational invariance. The study exhibits a phase transition through the sudden change of the effective nucleon mass in a certain range of baryon chemical potential and temperature. The addition o…

Dynamic effects of electric field in hybrid coupling thermosensitive neuronal network
Ediline L. F. Nguessap (Department of Physics, FFCLRP, Sao Paulo, Brazil), Antonio C. Roque (Department of Physics, FFCLRP, Sao Paulo, Brazil), Fernando F. Ferreira (Department of Physics, FFCLRP, Sao Paulo, Brazil)
https://arxiv.org/abs/2509.14910…

Dynamic effects of electric field in hybrid coupling thermosensitive neuronal network
The dynamic of thermosensitive neuronal networks under the influence of external electric fields is explored, focusing on hybrid coupling models that incorporate both electrical and chemical synapses. Numerical simulations reveal a variety of complex behaviors, including coherent, incoherent, and chimera states, which are influenced by the frequency of the external field and the cell size. Specificaly chemical coupling is shown to enhances the appearance of a typical chimera states called trave…

Deep Learning for Analyzing Chaotic Dynamics in Biological Time Series: Insights from Frog Heart Signals
Carmen Mayora-Cebollero, Flavio H. Fenton, Molly Halprin, Conner Herndon, Mikael J. Toye, Roberto Barrio
https://arxiv.org/abs/2509.13027

Deep Learning for Analyzing Chaotic Dynamics in Biological Time Series: Insights from Frog Heart Signals
The study of experimental data is a relevant task in several physical, chemical and biological applications. In particular, the analysis of chaotic dynamics in cardiac systems is crucial as it can be related to some pathological arrhythmias. When working with short and noisy experimental time series, some standard techniques for chaos detection cannot provide reliable results because of such data characteristics. Moreover, when small datasets are available, Deep Learning techniques cannot be ap…