Tootfinder

🇺🇦 #NowPlaying on KEXP's #VarietyMix
Melody’s Echo Chamber:
🎵 Eyes Closed
#MelodysEchoChamber
https://melodysechochamber.bandcamp.com/track/eyes-closed
https://open.spotify.com/track/7dTZ0dEnpFed6ohli3g5NE

Dynamical Quantum Multigraphs
Kassahun H. Betre, Nathan Lewis
https://arxiv.org/abs/2509.08296 https://arxiv.org/pdf/2509.08296

Dynamical Quantum Multigraphs
Motivated by applications in background-independent quantum gravity, we discuss the quantization of labeled and unlabeled finite multigraphs with a maximum edge count. We provide a unified way to represent quantum multigraphs with labeled or unlabeled vertices, which enables the study of quantum multigraphs as dynamical microscopic degrees of freedom and not just as representations of relations among quantum states of particles. The quantum multigraphs represent a quantum mechanical treatment o…

Integrating Quantum Computing with Multiconfiguration Pair-Density Functional Theory for Biological Electron Transfer
Yibo Chen, Zirui Sheng, Weitang Li, Yong Zhang, Xun Xu, Jun-Han Huang, Yuxiang Li
https://arxiv.org/abs/2508.07359

Integrating Quantum Computing with Multiconfiguration Pair-Density Functional Theory for Biological Electron Transfer
Accurate calculation of strongly correlated electronic systems requires proper treatment of both static and dynamic correlations, which remains challenging for conventional methods. To address this, we present VQE-PDFT, a quantum-classical hybrid framework that integrates variational quantum eigensolver with multiconfiguration pair-density functional theory (MC-PDFT). This framework strategically employs quantum circuits for multiconfigurational wavefunction representation while utilizing densi…

Unstructured to structured: geometric multigrid on complex geometries via domain remapping
Nicolas Nytko, Scott MacLachlan, J. David Moulton, Luke N. Olson, Andrew Reisner, Matthew West
https://arxiv.org/abs/2509.08109

Unstructured to structured: geometric multigrid on complex geometries via domain remapping
For domains that are easily represented by structured meshes, robust geometric multigrid solvers can quickly provide the numerical solution to many discretized elliptic PDEs. However, for complicated domains with unstructured meshes, constructing suitable hierarchies of meshes becomes challenging. We propose a framework for mapping computations from such complex domains to regular computational domains via diffeomorphisms, enabling the use of robust geometric-style multigrid. This mapping facil…

Sain potut kaivettua ylös. Aika pienehköjä osa, vois laittaa ne multasäkkiin sisälle, mutta näillä mennään. Sain kaikki kaivettua ylös, mutta meni pimeässä kaivamiseksi lopussa kun tuo aurinko laskee niin aikaisin nyt.. ja tietty omputkin vei taas aikaa kun raahasin 3 laatikkoa lisää.. puuh. 😅
Ilmeisesti ompuille on ollut kysyntää jotka jätin tontin eteen. Ahkerasti ihmiset ovat hakeneet ainakin. 👍 Helpottaa omaa työtä.. 😄
Keräsin samasta penkistä myös viimeiset pavutkin.

Computational modelling of Parkinson's disease: A multiscale approach with deep brain stimulation and stochastic noise
Aaron Herrera, Hina Shaheen
https://arxiv.org/abs/2509.08179

Computational modelling of Parkinson's disease: A multiscale approach with deep brain stimulation and stochastic noise
Multiscale modelling presents a multifaceted perspective into understanding the mechanisms of the brain and how neurodegenerative disorders like Parkinson's disease (PD) manifest and evolve over time. In this study, we propose a novel co-simulation multiscale approach that unifies both micro- and macroscales to more rigorously capture brain dynamics. The presented design considers the electrodiffusive activity across the brain and in the network defined by the cortex, basal ganglia, and thalamu…

Multispectral CT Denoising via Simulation-Trained Deep Learning: Experimental Results at the ESRF BM18
Peter G\"anz, Steffen Kie{\ss}, Guangpu Yang, Jajnabalkya Guhathakurta, Tanja Pienkny, Charls Clark, Paul Tafforeau, Andreas Balles, Astrid H\"olzing, Simon Zabler, Sven Simon
https://arxiv.org/abs/2509.08528

Multispectral CT Denoising via Simulation-Trained Deep Learning: Experimental Results at the ESRF BM18
Multispectral computed tomography (CT) enables advanced material characterization by acquiring energy-resolved projection data. However, since the incoming X-ray flux is be distributed across multiple narrow energy bins, the photon count per bin is greatly reduced compared to standard energy-integrated imaging. This inevitably introduces substantial noise, which can either prolong acquisition times and make scan durations infeasible or degrade image quality with strong noise artifacts. To addre…

Tree-OPO: Off-policy Monte Carlo Tree-Guided Advantage Optimization for Multistep Reasoning
Bingning Huang, Tu Nguyen, Matthieu Zimmer
https://arxiv.org/abs/2509.09284 https://

Tree-OPO: Off-policy Monte Carlo Tree-Guided Advantage Optimization for Multistep Reasoning
Recent advances in reasoning with large language models (LLMs) have shown the effectiveness of Monte Carlo Tree Search (MCTS) for generating high-quality intermediate trajectories, particularly in math and symbolic domains. Inspired by this, we explore how MCTS-derived trajectories, traditionally used for training value or reward models, can be repurposed to improve policy optimization in preference-based reinforcement learning (RL). Specifically, we focus on Group Relative Policy Optimization …

Channel Estimation and Analog Precoding for Pixel-based Fluid-Antenna-Assisted Multiuser MIMO-OFDM Systems
Huayan Guo, Jichen Zhang, Junhui Rao, Ross Murch, Vincent K. N. Lau
https://arxiv.org/abs/2509.09373

Channel Estimation and Analog Precoding for Pixel-based Fluid-Antenna-Assisted Multiuser MIMO-OFDM Systems
Pixel-based fluid antennas provide enhanced multiplexing gains and quicker radiation pattern switching than traditional designs. However, this innovation introduces challenges for channel estimation and analog precoding due to the state-non-separable channel response problem. This paper explores a multiuser MIMO-OFDM system utilizing pixel-based fluid antennas, informed by measurements from a real-world prototype. We present a sparse channel recovery framework for uplink channel sounding, emplo…

Optimal convergence rates in multiscale elliptic homogenization
Weisheng Niu, Yao Xu, Jinping Zhuge
https://arxiv.org/abs/2509.09410 https://arxiv.org/pdf/…

Optimal convergence rates in multiscale elliptic homogenization
This paper is devoted to the quantitative homogenization of multiscale elliptic operator $-\nabla\cdot A_\varepsilon \nabla$, where $A_\varepsilon(x) = A(x/\varepsilon_1, x/\varepsilon_2,\cdots, x/\varepsilon_n)$, $\varepsilon = (\varepsilon_1, \varepsilon_2,\cdots, \varepsilon_n) \in (0,1]^n$ and $\varepsilon_i > \varepsilon_{i+1}$. We assume that $A(y_1,y_2,\cdots, y_n)$ is 1-periodic in each $y_i \in \mathbb{R}^d$ and real analytic. Classically, the method of reiterated homogenization has be…