Tootfinder

I'm setting up a new device for someone who wants to try out Linux. What distro would you recommend?
Some information about the user:
- uses MacOS currently
- wants stuff to work (minimal tinkering after setup)
- quick to boot
The device will probs be quite an old device (~3-5 years old, 8gb RAM though) and is mostly to run OBS. I'll check system requirements when I know the device ofc, just wondering what you people think is a good distro for them.

Noise-tolerant tomography of multimode linear optical interferometers with single photons
Yu. A. Biriukov, R. D. Morozov, I. V. Dyakonov, M. V. Rakhlin, A. I. Galimov, G. V. Klimko, S. V. Sorokin, I. V. Sedova, M. M. Kulagina, Yu. M. Zadiranov, A. A. Toropov, A. A. Korneev, S. P. Kulik, S. S. Straupe
https://arxiv.org/abs/2506.2…

Noise-tolerant tomography of multimode linear optical interferometers with single photons
Linear optical networks are fundamental to the advancement of quantum technologies, including quantum computing, communication, and sensing. The accurate characterization of these networks, described by unitary matrices, is crucial to their effective utilization and scalability. In this work, we present the method for reconstructing the transfer matrix of a linear optical interferometer based on the analysis of cross-correlation functions of photon counts between pairs of output modes. Our appr…

Vores nevŸ har lavet skilte til anti-Trump-demoen:
#NoTyrants #DemocratsAbroad

Semi-Tensor-Product Based Convolutional Neural Networks
Daizhan Cheng
https://arxiv.org/abs/2506.10407 https://arxiv.org/pdf/2506.104…

Semi-Tensor-Product Based Convolutional Neural Networks
The semi-tensor product (STP) of vectors is a generalization of conventional inner product of vectors, which allows the factor vectors to of different dimensions. This paper proposes a domain-based convolutional product (CP). Combining domain-based CP with STP of vectors, a new CP is proposed. Since there is no zero or any other padding, it can avoid the junk information caused by padding. Using it, the STP-based convolutional neural network (CNN) is developed. Its application to image and thir…

NeRF-based CBCT Reconstruction needs Normalization and Initialization
Zhuowei Xu, Han Li, Dai Sun, Zhicheng Li, Yujia Li, Qingpeng Kong, Zhiwei Cheng, Nassir Navab, S. Kevin Zhou
https://arxiv.org/abs/2506.19742

NeRF-based CBCT Reconstruction needs Normalization and Initialization
Cone Beam Computed Tomography (CBCT) is widely used in medical imaging. However, the limited number and intensity of X-ray projections make reconstruction an ill-posed problem with severe artifacts. NeRF-based methods have achieved great success in this task. However, they suffer from a local-global training mismatch between their two key components: the hash encoder and the neural network. Specifically, in each training step, only a subset of the hash encoder's parameters is used (local sparse…

Für die breite Verwendung von #KI, speziell im Kontext #Schule, muss sichergestellt sein, dass #LLMs user:innen nicht zu selbstgefährdendem Verhalten animieren.
Das Nonprofit Transluce arbeitet an verschie…

Surfacing Pathological Behaviors in Language Models
We train reinforcement learning (RL) agents to craft realistic natural-language prompts that elicit specified behaviors in frontier open-weight models (Llama 3.1/4, Qwen 2.5, and DeepSeek-V3), using a proposed variational lower bound to guide the search.

Turbulent stretching of dumbbells with hydrodynamic interactions: an analytical study
Jason R. Picardo, Dario Vincenzi
https://arxiv.org/abs/2506.14282 htt…

Turbulent stretching of dumbbells with hydrodynamic interactions: an analytical study
We study the stretching of an elastic dumbbell in a turbulent flow, with the aim of understanding and quantifying the effect of hydrodynamic interactions (HI) between the beads of the dumbbell. Adopting the Batchelor-Kraichnan model for the flow, we derive a Fokker-Planck equation and solve it analytically to obtain the probability distribution of the dumbbell's extension. Using different formulations of the HI tensor, we find that HI preferentially enhances the stretching of stiff dumbbells, i…

Inf-sup stable space-time discretization of the wave equation based on a first-order-in-time variational formulation
Matteo Ferrari, Ilaria Perugia, Enrico Zampa
https://arxiv.org/abs/2506.05886

Inf-sup stable space-time discretization of the wave equation based on a first-order-in-time variational formulation
In this paper, we present a conforming space-time discretization of the wave equation based on a first-order-in-time variational formulation with exponential weights in time. We analyze the method, showing its stability without imposing any restrictions on the mesh size or time step, and proving quasi-optimal convergence for any choice of space-time tensor product discrete spaces that satisfies standard approximation assumptions. Numerical examples are provided to support the theoretical findin…

Statistical microlocal analysis in two-dimensional X-ray CT
Anuj Abhishek, Alexander Katsevich, James W. Webber
https://arxiv.org/abs/2506.05113 https://…

Statistical microlocal analysis in two-dimensional X-ray CT
In many imaging applications it is important to assess how well the edges of the original object, $f$, are resolved in an image, $f^\text{rec}$, reconstructed from the measured data, $g$. In this paper we consider the case of image reconstruction in 2D X-ray Computed Tomography (CT). Let $f$ be a function describing the object being scanned, and $g=Rf + η$ be the Radon transform data in $\mathbb{R}^2$ corrupted by noise, $η$, and sampled with step size $\simε$. Conventional microlocal analys…