Tootfinder

Multipartite Markov Gaps and Entanglement Wedge Multiway Cuts
Norihiro Iizuka, Akihiro Miyata, Mitsuhiro Nishida
https://arxiv.org/abs/2507.15262 https://

Multipartite Markov Gaps and Entanglement Wedge Multiway Cuts
The Markov gap, defined as the difference between reflected entropy and mutual information, serves as a diagnostic for quantum recoverability and multipartite entanglement. In holographic settings, it admits a geometric interpretation as the deviation between entanglement wedge cross-sections and RT surfaces. Motivated by this holographic perspective, we propose a generalization of the Markov gap to multipartite systems by using a reflected multi-entropy. The resulting Multipartite Markov gap c…

Canonical Representations of Markovian Structural Causal Models: A Framework for Counterfactual Reasoning
Lucas de Lara (IECL)
https://arxiv.org/abs/2507.16370

Canonical Representations of Markovian Structural Causal Models: A Framework for Counterfactual Reasoning
Counterfactual reasoning aims at answering contrary-to-fact questions like ''Would have Alice recovered had she taken aspirin?'' and corresponds to the most fine-grained layer of causation. Critically, while many counterfactual statements cannot be falsified -- even by randomized experiments -- they underpin fundamental concepts like individual-wise fairness. Therefore, providing models to formalize and implement counterfactual beliefs remains a fundamental scientific problem. In the Markovian …

Solving Zero-Sum Convex Markov Games
Fivos Kalogiannis, Emmanouil-Vasileios Vlatakis-Gkaragkounis, Ian Gemp, Georgios Piliouras
https://arxiv.org/abs/2506.16120

Solving Zero-Sum Convex Markov Games
We contribute the first provable guarantees of global convergence to Nash equilibria (NE) in two-player zero-sum convex Markov games (cMGs) by using independent policy gradient methods. Convex Markov games, recently defined by Gemp et al. (2024), extend Markov decision processes to multi-agent settings with preferences that are convex over occupancy measures, offering a broad framework for modeling generic strategic interactions. However, even the fundamental min-max case of cMGs presents signi…

“Ursula von [Bomb?] der Leyen… Mrs. Kallas… you are financing genocide… stop bending the knee to Trump and Netanyahu who are taking us to World War III. If you want war, go yourselves.”
– Irene Montero, Spanish MEP
https://www.reddit.com/r/news_of_world/s/omrCjJgOuB

Die ePetition 178586 an den Bundestag aus dem Bereich Kontrolle von Kriegswaffen und sonstigen Rüstungsgütern mit dem Titel
Keine Lieferung von Taurus-Marschflugkörpern an die Ukraine
kann bis zum Montag 04. August 2025 01:00 UTC mitgezeichnet werden und lautet
Mit der Petition wird gefordert, keine Taurus-Marschflu…

Die ePetition 178586 an den Bundestag aus dem Bereich Kontrolle von Kriegswaffen und sonstigen Rüstungsgütern mit dem Titel
Keine Lieferung von Taurus-Marschflugkörpern an die Ukraine
kann bis zum Montag 04. August 2025 01:00 UTC mitgezeichnet werden und lautet
Mit der Petition wird gefordert, keine Taurus-Marschflu…

Searching for a Hidden Markov Anomaly over Multiple Processes
Levli Citron, Kobi Cohen, Qing Zhao
https://arxiv.org/abs/2506.17108 https://

Searching for a Hidden Markov Anomaly over Multiple Processes
We address the problem of detecting an anomalous process among a large number of processes. At each time t, normal processes are in state zero (normal state), while the abnormal process may be in either state zero (normal state) or state one (abnormal state), with the states being hidden. The transition between states for the abnormal process is governed by a Markov chain over time. At each time step, observations can be drawn from a selected subset of processes. Each probed process generates a…

On Algorithmic Robustness of Corrupted Markov Chains
Jason Gaitonde, Elchanan Mossel
https://arxiv.org/abs/2507.15176 https://arxiv.o…

On Algorithmic Robustness of Corrupted Markov Chains
We study the algorithmic robustness of general finite Markov chains in terms of their stationary distributions to general, adversarial corruptions of the transition matrix. We show that for Markov chains admitting a spectral gap, variants of the \emph{PageRank} chain are robust in the sense that, given an \emph{arbitrary} corruption of the edges emanating from an $ε$-measure of the nodes, the PageRank distribution of the corrupted chain will be $\mathsf{poly}(\varepsilon)$ close in total varia…

Investigation of D-Wave quantum annealing for training Restricted Boltzmann Machines and mitigating catastrophic forgetting
Abdelmoula El-Yazizi, Yaroslav Koshka
https://arxiv.org/abs/2508.15697

Investigation of D-Wave quantum annealing for training Restricted Boltzmann Machines and mitigating catastrophic forgetting
Modest statistical differences between the sampling performances of the D-Wave quantum annealer (QA) and the classical Markov Chain Monte Carlo (MCMC), when applied to Restricted Boltzmann Machines (RBMs), are explored to explain, and possibly address, the absence of significant and consistent improvements in RBM trainability when the D-Wave sampling was used in previous investigations. A novel hybrid sampling approach, combining the classical and the QA contributions, is investigated as a prom…

Finite-Time Ruin for the Compound Markov Binomial Risk Model
Zbigniew Palmowski, Lewis Ramsden, Apostolos D. Papaioannou
https://arxiv.org/abs/2507.16448 h…

Finite-Time Ruin for the Compound Markov Binomial Risk Model
In this paper, we study finite-time ruin probabilities for the compound Markov binomial risk model - a discrete-time model where claim sizes are modulated by a finite-state ergodic Markov chain. In the classic (non-modulated) case, the risk process has interchangeable increments and consequently, its finite-time ruin probability can be obtained in terms of Takács' famous Ballot Theorem results. Unfortunately, due to the dependency of our process on the state(s) of the modulating chain these do…