Tootfinder

Weil es wieder so schön passt: #Stuttgart21 heißt nicht so, weil es 2021 hätte fertig sein sollen. Es heißt so, weil es für's 21. Jahrhundert gedacht ist.
So steht es zumindest in Wikipedia, die Originalquellen sind leider offline.

Stuttgart 21 – Wikipedia

6/ Normalerweise umarmen sich zum Ende eines Hungerstreiks alle und freuen sich. So war es jedenfalls 2021 bei der #LetzteGeneration.
Vielleicht gab es ja die Umarmungen zur vorigen Pressekonferenz, die ich verpasst habe, als die Pause verkündet wurde.
(Übrigens tauchte der Prinz auch dieses Mal zum Ende des Hungerstreiks auf.)

2021 retro-link! https://techcommunity.microsoft.com/t5/azure-database-for-postgresql/speeding-up-recovery-and-vacuum-in-postgres-14/ba-p/2234071 - Speeding up crash recovery and VACUUM in Postgr…

Las Vegas Raiders defensive end Maxx Crosby compares Christian Wilkins to 2021 teammate https://atozsports.com/las-vegas/raiders-maxx-crosby-compares-christian-wilkins-to-2021-teammate/

Banal Deception Human-AI Ecosystems: A Study of People's Perceptions of LLM-generated Deceptive Behaviour
Xiao Zhan, Yifan Xu, Noura Abdi, Joe Collenette, Ruba Abu-Salma, Stefan Sarkadi
https://arxiv.org/abs/2406.08386

Banal Deception Human-AI Ecosystems: A Study of People's Perceptions of LLM-generated Deceptive Behaviour
Large language models (LLMs) can provide users with false, inaccurate, or misleading information, and we consider the output of this type of information as what Natale (2021) calls `banal' deceptive behaviour. Here, we investigate peoples' perceptions of ChatGPT-generated deceptive behaviour and how this affects peoples' own behaviour and trust. To do this, we use a mixed-methods approach comprising of (i) an online survey with 220 participants and (ii) semi-structured interviews with 12 partic…

Predictability Limit of the 2021 Pacific Northwest Heatwave from Deep-Learning Sensitivity Analysis
P. Trent Vonich, Gregory J. Hakim
https://arxiv.org/abs/2406.05019

Predictability Limit of the 2021 Pacific Northwest Heatwave from Deep-Learning Sensitivity Analysis
The traditional method for estimating weather forecast sensitivity to initial conditions uses adjoint models, which are limited to short lead times due to linearization around a control forecast. The advent of deep-learning frameworks enables a new approach using backpropagation and gradient descent to iteratively optimize initial conditions to minimize forecast errors. We apply this approach to forecasts of the June 2021 Pacific Northwest heatwave using the GraphCast model, yielding over 90% r…

Measurement of the integrated luminosity of the data collected at 3.773 GeV by BESIII from 2021 to 2024
BESIII Collaboration, et al.
https://arxiv.org/abs/2406.05827

Measurement of the integrated luminosity of the data collected at 3.773 GeV by BESIII from 2021 to 2024
We present a measurement of the integrated luminosity of $e^+e^-$ collision data collected with the BESIII detector at the BEPCII collider at a center-of-mass energy of $E_{\rm cm} = 3.773$~GeV. The integrated luminosities of the data sets taken from December 2021 to June 2022, from November 2022 to June 2023, and from October 2023 to February 2024 are determined to be $4.995 \pm 0.019$~fb$^{-1}$, $8.157 \pm 0.031$~fb$^{-1}$, and $4.191 \pm 0.016$~fb$^{-1}$, respectively, by analyzing large ang…

GR-Athena : magnetohydrodynamical evolution with dynamical space-time
Boris Daszuta, William Cook
https://arxiv.org/abs/2406.05126 https://

GR-Athena++: magnetohydrodynamical evolution with dynamical space-time
We present a self-contained overview of GR-Athena++, a general-relativistic magnetohydrodynamics (GRMHD) code, that incorporates treatment of dynamical space-time, based on the recent work of (Daszuta+, 2021)[49] and (Cook+, 2023)[45]. General aspects of the Athena++ framework we build upon, such as oct-tree based, adaptive mesh refinement (AMR) and constrained transport, together with our modifications, incorporating the Z4c formulation of numerical relativity, judiciously coupled, enables G…

Weather conditions at Timau National Observatory from ERA5
R. Priyatikanto, A. G. Admiranto, T. Djamaluddin, A. Rachman, D. D. Wijaya
https://arxiv.org/abs/2406.11027

Weather conditions at Timau National Observatory from ERA5
A new observatory site should be investigated for its local climate conditions to see its potential and limitations. In this respect, we examine several meteorological parameters at the site of Timau National Observatory, Indonesia using the ERA5 dataset from 2002 to 2021. Based on this dataset, we conclude that the surface temperature at Timau is around 18.9 C with a relatively small temperature variation (1.5 C) over the day. This temperature stability is expected to give advantages to the ob…

On Conjecture of Binomial Edge Ideals of Linear Type
Marie Amalore Nambi, Neeraj Kumar
https://arxiv.org/abs/2406.05960 https://arxiv…

On Conjecture of Binomial Edge Ideals of Linear Type
An ideal $I$ of a commutative ring $R$ is said to be of {\emph{linear type}} when its Rees algebra and symmetric algebra exhibit isomorphism. In this paper, we investigate the conjecture put forth by Jayanthan, Kumar, and Sarkar (2021) that if $G$ is a tree or a unicyclic graph, then the binomial edge ideal of $G$ is of linear type. Our investigation validates this conjecture for trees. However, our study reveals that not all unicyclic graphs adhere to this conjecture. Furthermore, we provide a…

The renormalized classical spin liquid on the ruby lattice
Zhenjiu Wang, Lode Pollet
https://arxiv.org/abs/2406.07110 https://arxiv.o…

The renormalized classical spin liquid on the ruby lattice
The recent experimental detection of the onset of a dynamically prepared, gapped $Z_2$ quantum spin liquid on the ruby lattice brought the physics of frustrated magnetism and lattice gauge theory to Rydberg tweezer arrays (Semeghini et al, Science 374, 1242 (2021)). The thermodynamic properties of such models remain inadequately addressed, yet knowledge thereof is indispensable if one wants to prepare large, robust, and long-lived quantum spin liquids. Using large scale quantum Monte Carlo simu…