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Turkisasetus sai murskaavan vastaanoton   | Animalia-media
Suurin osa lausujista yhtyi Animalian näkemykseen ja kritisoi turkisasetuksen sisältöä. Moni vaati turkistarhauksen kieltämistä Suomessa. 

Klimakipppunkte: Tropische Korallenriffe kaum mehr zu retten
https://www.zeit.de/wissen/umwelt/2025-10/klima-kipppunkte-korallen-meeresspiegel-bericht
"Forschende beobachten ein erstes Kippen des globalen Klimasystems: Betroffen…

Continuous-Time Quantum Markov Chains And Discretizations Of p-Adic Schr\"odinger Equations: Comparisons And Simulations
W. A. Z\'u\~niga-Galindo, L. F. Chac\'on-Cort\'es
https://arxiv.org/abs/2508.06712

Continuous-Time Quantum Markov Chains And Discretizations Of p-Adic Schrödinger Equations: Comparisons And Simulations
The continuous-time quantum walks (CTQWs) are a fundamental tool in the development of quantum algorithms. Recently, it was shown that discretizations of p-adic Schrödinger equations give rise to continuous-time quantum Markov chains (CTQMCs); this type of Markov chain includes the CTQWs constructed using adjacency matrices of graphs as a particular case. In this paper, we study a large class of p-adic Schrödinger equations and the associated CTQMCs by comparing them with p-adic heat equation…

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What One Cannot, Two Can: Two-Layer Transformers Provably Represent Induction Heads on Any-Order Markov Chains
Chanakya Ekbote, Marco Bondaschi, Nived Rajaraman, Jason D. Lee, Michael Gastpar, Ashok Vardhan Makkuva, Paul Pu Liang
https://arxiv.org/abs/2508.07208

What One Cannot, Two Can: Two-Layer Transformers Provably Represent Induction Heads on Any-Order Markov Chains
In-context learning (ICL) is a hallmark capability of transformers, through which trained models learn to adapt to new tasks by leveraging information from the input context. Prior work has shown that ICL emerges in transformers due to the presence of special circuits called induction heads. Given the equivalence between induction heads and conditional k-grams, a recent line of work modeling sequential inputs as Markov processes has revealed the fundamental impact of model depth on its ICL capa…

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Morcheeba:
🎵 The Sea
#Morcheeba
https://duodomusica.bandcamp.com/track/the-sea-morcheeba-cover
https://open.spotify.com/track/0xjkgYSzHjBZNvyUaC9cXX

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Morcheeba:
🎵 Far We Come
#NowPlaying #Morcheeba
https://morcheeba.bandcamp.com/track/far-we-come
https://open.spotify.com/track/10nJLMsyHVSLOEtSjpimuP

Semi-Markov random walk on complex networks
Lasko Basnarkov
https://arxiv.org/abs/2508.06961 https://arxiv.org/pdf/2508.06961

Semi-Markov random walk on complex networks
We present a semi-Markov model of random walk on complex networks in discrete and continuous-time scenario. In the general setting of the semi-Markov chains, the duration of stay at given node - the sojourn time - is random, and the probability to transition to a neighbor depends on the sojourn time. Analytical formulae for the average sojourn time and the node occupation probability of infinite walk are presented and verified with Monte Carlo simulations for two examples. We propose an applica…

Turnpike properties for zero-sum stochastic linear quadratic differential games of Markovian regime switching system
Xun Li, Fan Wu, Xin Zhang
https://arxiv.org/abs/2509.09358 h…

Turnpike properties for zero-sum stochastic linear quadratic differential games of Markovian regime switching system
This paper investigates the long-time behavior of zero-sum stochastic linear-quadratic (SLQ) differential games within Markov regime-switching diffusion systems and establishes the turnpike property of the optimal triple. By verifying the convergence of the associated coupled differential Riccati equations (CDREs) along with their convergence rate, we show that, for a sufficiently large time horizon, the equilibrium strategy in the finite-horizon problem can be closely approximated by that of t…

Asymptotic Behavior of Random Time-Inhomogeneous Markovian Quantum Dynamics
Lubashan Pathirana, Jeffrey Schenker
https://arxiv.org/abs/2509.08924 https://a…

Asymptotic Behavior of Random Time-Inhomogeneous Markovian Quantum Dynamics
We study the asymptotic behavior of continuous-time, time-inhomogeneous Markovian quantum dynamics in a stationary random environment. Under mild faithfulness and eventually positivity-improving assumptions, the normalized evolution converges almost surely to a stationary family of full-rank states, and the normalized propagators converge almost surely to a rank-one family determined by these states. Beyond a disorder-dependent threshold, these convergences occur at exponential rates that may d…