Tootfinder

Weltbekannte Kathedrale in Kiew bei Angriffen leicht beschädigt
Bei russischen Angriffen auf die ukrainische Hauptstadt Kiew ist die weltbekannte Sophienkathedrale offenbar in Mitleidenschaft gezogen worden. Die Kathedrale wurde während der Angriffe in der Nacht leicht beschädigt, wie ein AFP-Journalist in Kiew berichtete. Nach Angaben des ukrainischen Präsident Wolodymyr Selenskyj bröckelte ein Tei…
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Bar-driven dispersal of Galactic substructure
Adam M. Dillamore, Jason L. Sanders
https://arxiv.org/abs/2506.09117 https://arxiv.org/…

Bar-driven dispersal of Galactic substructure
Galactic archaeologists often assume that integrals of motion (IoMs) such as $L_z$ and $E$ are conserved, so substructure remains frozen in IoM space over many Gyr. However, this is not true in the Milky Way due in part to its rotating bar. In this study we quantify the effects of the bar on the dynamics of substructure. We employ three different theoretical models: an analytical toy model; a set of test particle simulations with steady and slowing bars; and a cosmological zoom-in simulation of…

Stark Tuning and Charge State Control in Individual Telecom C-Band Quantum Dots
N. J. Martin, A. J. Brash, A. Tomlinson, E. M. Sala, E. O. Mills, C. L. Phillips, R. Dost, L. Hallacy, P. Millington-Hotze, D. Hallett, K. A. O'Flaherty, J. Heffernan, M. S. Skolnick, A. M Fox, L. R. Wilson
https://arxiv.org/abs/2506.07951…

Stark Tuning and Charge State Control in Individual Telecom C-Band Quantum Dots
Telecom-wavelength quantum dots (QDs) are emerging as a promising solution for generating deterministic single-photons compatible with existing fiber-optic infrastructure. Emission in the low-loss C-band minimizes transmission losses, making them ideal for long-distance quantum communication. In this work, we present the first demonstration of both Stark tuning and charge state control of individual InAs/InP QDs operating within the telecom C-band. These QDs are grown by droplet epitaxy and emb…

The National Guard is here in Westwood. Fully armed & barricading the area around Wilshire & Veteran in Los Angeles.
#LosAngeles #Protests #NationalGuard

Normalized Radon Cumulative Distribution Transforms for Invariance and Robustness in Optimal Transport Based Image Classification
Matthias Beckmann, Robert Beinert, Jonas Bresch
https://arxiv.org/abs/2506.08761

Normalized Radon Cumulative Distribution Transforms for Invariance and Robustness in Optimal Transport Based Image Classification
The Radon cumulative distribution transform (R-CDT), is an easy-to-compute feature extractor that facilitates image classification tasks especially in the small data regime. It is closely related to the sliced Wasserstein distance and provably guaranties the linear separability of image classes that emerge from translations or scalings. In many real-world applications, like the recognition of watermarks in filigranology, however, the data is subject to general affine transformations originating…

STARFlow: Scaling Latent Normalizing Flows for High-resolution Image Synthesis
Jiatao Gu, Tianrong Chen, David Berthelot, Huangjie Zheng, Yuyang Wang, Ruixiang Zhang, Laurent Dinh, Miguel Angel Bautista, Josh Susskind, Shuangfei Zhai
https://arxiv.org/abs/2506.06276

STARFlow: Scaling Latent Normalizing Flows for High-resolution Image Synthesis
We present STARFlow, a scalable generative model based on normalizing flows that achieves strong performance in high-resolution image synthesis. The core of STARFlow is Transformer Autoregressive Flow (TARFlow), which combines the expressive power of normalizing flows with the structured modeling capabilities of Autoregressive Transformers. We first establish the theoretical universality of TARFlow for modeling continuous distributions. Building on this foundation, we introduce several key arch…

Solving excited states for long-range interacting trapped ions with neural networks
Yixuan Ma, Chang Liu, Weikang Li, Shun-Yao Zhang, L. -M. Duan, Yukai Wu, Dong-Ling Deng
https://arxiv.org/abs/2506.08594

Solving excited states for long-range interacting trapped ions with neural networks
The computation of excited states in strongly interacting quantum many-body systems is of fundamental importance. Yet, it is notoriously challenging due to the exponential scaling of the Hilbert space dimension with the system size. Here, we introduce a neural network-based algorithm that can simultaneously output multiple low-lying excited states of a quantum many-body spin system in an accurate and efficient fashion. This algorithm, dubbed the neural quantum excited-state (NQES) algorithm, re…

teaching a transformer net to approximate ray-tracing
input is a sequence of triangle data (limited to 4k triangles), and a sequence of 8x8 radiance pixels representing the camera (limited to 512x512 resolution)
output is a sequence of 8x8 pixels of the rendered scene. training was ~10 days. generation is ~100ms (NVIDIA A100)
the results are pretty good. scaling will be a challenge (since transformers are quadratic in sequence length)

"Dans la voix, la langue résiste Š la littérature. Par cette manière de retourner la table du sens, la voix déploie tout ce qu’elle ne peut pas et l’offre négativement Š qui sait l’entendre. Avec l’incertitude de l’onde sonore qui se fracasse."
🔗 https://abrupt.cc/charles-pennequin/ra