Tootfinder

Unterzeichnet das hier Mal bitte! Es gibt Bestrebungen, dass Leute mit Solaranlagen Netzentgelte bezahlen sollen. Das wäre der Tod der dezentralen Stromproduktion.
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Finger weg von der Photovoltaik!
Was genau plant die Bundesnetzagentur? Die Bundesnetzagentur stellt in einem offiziellen Diskussionspapier sechs Modelle zur Debatte, wie private Einspeiser künftig Netzentgelte zahlen sollen – also eine Art Gebühr für jede eingespeiste Kilowattstunde oder bereitgestellte Leistung. Auch Bestandsanlagen sind hier betroffen! Viele dieser Modelle sind nicht nur unsozial und unplanbar – sie sind auch energiewirtschaftlich kontraproduktiv. Denn: Sie bieten wenig Anreiz, PV-Anlagen und Speich…

This https://arxiv.org/abs/2503.24207 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Definability of mad families of vector spaces and two local Ramsey theories
Let $E$ be a vector space over a countable field of dimension $\aleph_0$. Two infinite-dimensional subspaces $V,W \subseteq E$ are almost disjoint if $V \cap W$ is finite-dimensional. This paper provides some improvements on results about the definability of maximal almost disjoint families (mad families) of subspaces in [17]. We show that a full mad family of block subspaces exists assuming either $\frak{p} = \max\{\frak{b},\frak{s}\}$ or a positive answer to a problem in [17], improving Smyth…

This https://arxiv.org/abs/2503.15375 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Well-Posedness of Contact Discontinuity Solutions and Vanishing Pressure Limit for the Aw-Rascle Traffic Flow Model
This paper investigates the well-posedness of contact discontinuity solutions and the vanishing pressure limit for the Aw-Rascle traffic flow model with general pressure functions. The well-posedness problem is formulated as a free boundary problem, where initial discontinuities propagate along linearly degenerate characteristics. To address vacuum degeneracy, a condition at density jump points is introduced, ensuring a uniform lower bound for density. The Lagrangian coordinate transformation i…

Evolutionary model for energy trading in community microgrids using Hawk-Dove strategies
Viorica Rozina Chifu, Tudor Cioara, Cristina Bianca Pop, Ionut Anghel
https://arxiv.org/abs/2506.06325

Evolutionary model for energy trading in community microgrids using Hawk-Dove strategies
This paper proposes a decentralized model of energy cooperation between microgrids, in which decisions are made locally, at the level of the microgrid community. Each microgrid is modeled as an autonomous agent that adopts a Hawk or Dove strategy, depending on the level of energy stored in the battery and its role in the energy trading process. The interactions between selling and buying microgrids are modeled through an evolutionary algorithm. An individual in the algorithm population is repre…

New Limits on Distributed Quantum Advantage: Dequantizing Linear Programs
Alkida Balliu, Corinna Coupette, Antonio Cruciani, Francesco d'Amore, Massimo Equi, Henrik Lievonen, Augusto Modanese, Dennis Olivetti, Jukka Suomela
https://arxiv.org/abs/2506.07574

New Limits on Distributed Quantum Advantage: Dequantizing Linear Programs
In this work, we give two results that put new limits on distributed quantum advantage in the context of the LOCAL model of distributed computing. First, we show that there is no distributed quantum advantage for any linear program. Put otherwise, if there is a quantum-LOCAL algorithm $\mathcal{A}$ that finds an $α$-approximation of some linear optimization problem $Π$ in $T$ communication rounds, we can construct a classical, deterministic LOCAL algorithm $\mathcal{A}'$ that finds an $α$-ap…

Gradient Similarity Surgery in Multi-Task Deep Learning
Thomas Borsani, Andrea Rosani, Giuseppe Nicosia, Giuseppe Di Fatta
https://arxiv.org/abs/2506.06130

Gradient Similarity Surgery in Multi-Task Deep Learning
The multi-task learning ($MTL$) paradigm aims to simultaneously learn multiple tasks within a single model capturing higher-level, more general hidden patterns that are shared by the tasks. In deep learning, a significant challenge in the backpropagation training process is the design of advanced optimisers to improve the convergence speed and stability of the gradient descent learning rule. In particular, in multi-task deep learning ($MTDL$) the multitude of tasks may generate potentially conf…

Revealing the Dominance of the Orbital Hall Effect over Spin in Transition Metal Heterostructures
J. L. Costa, E. Santos, J. B. S. Mendes, A. Azevedo
https://arxiv.org/abs/2506.08425

Revealing the Dominance of the Orbital Hall Effect over Spin in Transition Metal Heterostructures
We study inverse spin and orbital Hall effects in 19 transition metals using spin-pumping driven by ferromagnetic resonance. Spin-to-charge conversion was measured in YIG/X(5), while orbital-to-charge conversion was probed in YIG/Pt(2)/X(5) heterostructures. Here, X represents the different transition metals. Surprisingly, the orbital contribution overwhelmingly dominates over the spin response, clarifying the challenge of disentangling these effects. Our results largely agree with first-princi…

This https://arxiv.org/abs/2312.03941 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Minimising Numbers of Losses and Abandonments in Small Call Centres Under a Transient Regime
We consider the problem of allocating customers to agents in small call centres so that transient performance indicators in terms of expected numbers of losses and abandonments are optimised. To gain insight into the general structure of optimal policies, we start by (i) using backward induction based upon Bellman's equation for a finite-horizon discrete-time model, and (ii) deriving stationary policies for an infinite-horizon continuous-time model with discounting. We then compare the performa…

This https://arxiv.org/abs/2505.17282 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLG_…

Attention with Trained Embeddings Provably Selects Important Tokens
Token embeddings play a crucial role in language modeling but, despite this practical relevance, their theoretical understanding remains limited. Our paper addresses the gap by characterizing the structure of embeddings obtained via gradient descent. Specifically, we consider a one-layer softmax attention model with a linear head for binary classification, i.e., $\texttt{Softmax}( p^\top E_X^\top ) E_X v = \frac{ \sum_{i=1}^T \exp(p^\top E_{x_i}) E_{x_i}^\top v}{\sum_{j=1}^T \exp(p^\top E_{x_{j…

A Strongly Non-Saturated Aronszajn Tree Without Weak Kurepa Trees
John Krueger
https://arxiv.org/abs/2506.06878 https://arxiv.org/pdf…

A Strongly Non-Saturated Aronszajn Tree Without Weak Kurepa Trees
For an inaccessible cardinal $κ$, there exists a forcing poset which is Y-proper and $κ$-c.c., collapses $κ$ to become $ω_2$, and adds an Aronszajn tree together with a family of $ω_2$-many strongly almost disjoint subtrees of it. The quotients of this forcing in intermediate extensions are indestructibly Y-proper on a stationary set with respect to any Y-proper forcing extension. As a consequence of this forcing, we prove from an inaccessible cardinal that the existence of a strongly non-…