Tootfinder

Unter anderem weil am Freitag laut MeteoSchweiz der erste Schnee in Zürich fallen soll, habe ich mein #BromptonElectricGLine heute Abend (naja, eher Spätnachmittag, war aber schon nach Sonnenuntergang) zum #Velofix gebracht zum

Geometric phase in dissipative quantum batteries
Camila Cristiano, Ludmila Viotti, Paula I. Villar
https://arxiv.org/abs/2509.11313 https://arxiv.org/pdf/2…

Geometric phase in dissipative quantum batteries
We study the geometric phase accumulated during non-adiabatic charging of different driven open quantum systems serving as quantum battery models. We provide a full numerical analysis of dy- namics under different type of noises typically reported in superconducting circuits implementations. We complement the study with analytic results derived in the limiting case of no noise (i.e. isolated systems). We compute the non-unitary geometric phase acquired by the quantum batteries during the transi…

Melanie #Amann stellt Poschardts autoritäres Weltbild nicht einfach bloß. Sie seziert messerscharf die verdorben anti-liberale Agenda des Acelspringerverlags, dessen Leithammelgesicht der Professionalität der Spiegeljournalistin in keiner Weise, weder in der Vorbereitung, noch in der Rhetorik, noch in der Glaubwürdigkeit gewachsen ist.
Dieser Ausschnitt ist nur ein Beispiel für die journalisti…

Hitze trifft alle – aber nicht alle Länder reagieren gleich. Der Kommentar hält Deutschland vor, Klimaanlagen aus moralischem Reflex abzulehnen, obwohl sie technisch dasselbe Prinzip nutzen wie die hierzulande gefeierte Wärmepumpe, nur mit umgekehrter Prozessrichtung. Gerade in unseren Breiten arbeiten Kälteanlagen oft dann, wenn Photovoltaik reichlich Strom liefert – das senkt die CO₂-Last. 🧊
Zum Kommentar:

🇺🇦 #NowPlaying on BBCRadio3's #ThroughTheNight
Ludmil Angelov & Fryderyk Chopin:
🎵 Variations in E major on a German National Air (op.posth)
#LudmilAngelov #FryderykChopin

Freigelegte Inschrift an der Müllerstraße

Kinetic description of one-dimensional stochastic dynamics with small inertia
Denis S. Goldobin, Lyudmila S. Klimenko, Irina V. Tyulkina, Vasily A. Kostin, Lev A. Smirnov
https://arxiv.org/abs/2510.08502

Kinetic description of one-dimensional stochastic dynamics with small inertia
We study single-variable approaches for describing stochastic dynamics with small inertia. The basic models we deal with describe passive Brownian particles and phase elements (phase oscillators, rotators, superconducting Josephson junctions) with an effective inertia in the case of a linear dissipation term and active Brownian particles in the case of a nonlinear dissipation. Elimination of a fast variable (velocity) reduces the characterization of the system state to a single variable and is …

Replaced article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[1/5]:
- Reservoir kernels and Volterra series
Lukas Gonon, Lyudmila Grigoryeva, Juan-Pablo Ortega

Probing the Origin of Water in Planets within Habitable Zones by HWO
Yasuhiro Hasegawa, Courtney Dressing, Ludmila Carone
https://arxiv.org/abs/2510.07349 https://

Probing the Origin of Water in Planets within Habitable Zones by HWO
How do habitable environments arise and evolve within the context of their planetary systems? This is one fundamental question, and it can be addressed partly by identifying how planets in habitable zones obtain water. Historically, astronomers considered that water was delivered to the Earth via dynamical shake-up by Jupiter, which took place during the formation and post-formation eras (e.g., $\lesssim 100$ Myr). This hypothesis has recently been challenged by a more dynamic view of planet fo…

Fine-Grained Urban Traffic Forecasting on Metropolis-Scale Road Networks
Fedor Velikonivtsev, Oleg Platonov, Gleb Bazhenov, Liudmila Prokhorenkova
https://arxiv.org/abs/2510.02278

Fine-Grained Urban Traffic Forecasting on Metropolis-Scale Road Networks
Traffic forecasting on road networks is a complex task of significant practical importance that has recently attracted considerable attention from the machine learning community, with spatiotemporal graph neural networks (GNNs) becoming the most popular approach. The proper evaluation of traffic forecasting methods requires realistic datasets, but current publicly available benchmarks have significant drawbacks, including the absence of information about road connectivity for road graph constru…