Tootfinder

Portfolio construction using a sampling-based variational quantum scheme
Gabriele Agliardi, Dimitris Alevras, Vaibhaw Kumar, Roberto Lo Nardo, Gabriele Compostella, Sumit Kumar, Manuel Proissl, Bimal Mehta
https://arxiv.org/abs/2508.13557

Portfolio construction using a sampling-based variational quantum scheme
The efficient and effective construction of portfolios that adhere to real-world constraints is a challenging optimization task in finance. We investigate a concrete representation of the problem with a focus on design proposals of an Exchange Traded Fund. We evaluate the sampling-based CVaR Variational Quantum Algorithm (VQA), combined with a local-search post-processing, for solving problem instances that beyond a certain size become classically hard. We also propose a problem formulation tha…

The Cost Advantage of Virtual Machine Migrations: Empirical Insights into Amazon's EC2 Marketspace
Benedikt Pittl, Werner Mach, Erich Schikuta
https://arxiv.org/abs/2508.14883

The Cost Advantage of Virtual Machine Migrations: Empirical Insights into Amazon's EC2 Marketspace
In recent years, cloud providers have introduced novel approaches for trading virtual machines. For example, Virtustream introduced so-called muVMs to charge cloud computing resources while other providers such as Google, Microsoft, or Amazon re-invented their marketspaces. Today, the market leader Amazon runs six marketspaces for trading virtual machines. Consumers can purchase bundles of virtual machines, which are called cloud-portfolios, from multiple marketspaces and providers. An industry…

Apple seems to be working on adding CUDA support to open-source ML framework MLX, which may mean that code developed using MLX would work with CUDA (Malcolm Owen/AppleInsider)
https://appleinsider.com/articles/25/0

Apple Silicon machine learning code may become more easily portable to Nvidia hardware
A project is trying to cut the cost of making machine learning applications for Nvidia hardware, by developing on an Apple Silicon Mac and exporting it to CUDA.

Skellam Processes via Multiparameter Poisson Process
Pradeep Vishwakarma
https://arxiv.org/abs/2509.12729 https://arxiv.org/pdf/2509.12729

Skellam Processes via Multiparameter Poisson Process
We introduce a mltiparameter version of Skellam point process via multiparameter Poisson processes. Its distributional properties are studied in detail. Its compound representation is derived for a particular case. Also, its Riemann integral over a rectangle in $\mathbb{R}^M_+$, $M\ge1$ is introduced and a closed expression for its characteristic function is obtained. Later, we introduce a different version of multiparameter Skellam process, and derive a weak convergence result for it. Moreover…

Marc Uwe Kling jetzt mit einen eigenen Peertube Kanal zum Folgen https://digitalcourage.video/c/marc_uwe_kling/videos
So langsam bewegt sich auch dieses Projekt 😄

From Chaos to Automation: Enabling the Use of Unstructured Data for Robotic Process Automation
Kelly Kurowski, Xixi Lu, Hajo A. Reijers
https://arxiv.org/abs/2507.11364

From Chaos to Automation: Enabling the Use of Unstructured Data for Robotic Process Automation
The growing volume of unstructured data within organizations poses significant challenges for data analysis and process automation. Unstructured data, which lacks a predefined format, encompasses various forms such as emails, reports, and scans. It is estimated to constitute approximately 80% of enterprise data. Despite the valuable insights it can offer, extracting meaningful information from unstructured data is more complex compared to structured data. Robotic Process Automation (RPA) has ga…

Consistent Modeling of Non-equilibrium Dust Sublimation and the Interactions with Dust Evolution in the Inner Regions of Protoplanetary Disks
Sheng Xu, Lile Wang, Luis C. Ho, Renyue Cen, Shenzhen Xu
https://arxiv.org/abs/2509.11036

Consistent Modeling of Non-equilibrium Dust Sublimation and the Interactions with Dust Evolution in the Inner Regions of Protoplanetary Disks
The inner regions of protoplanetary disks are host to the sublimation of dust grains, a process traditionally modeled using equilibrium thermodynamics. We demonstrate through ab-initio density functional theory (DFT) and kinetic Monte Carlo (KMC) simulations that silicate dust sublimation is inherently a non-equilibrium kinetic process. The binding energies and vibrational frequencies governing desorption, calculated for MgSiO3 and other compositions, reveal that sublimation timescales far exce…

Reinforcement Learning for Autonomous Point-to-Point UAV Navigation
Salim Oyinlola, Nitesh Subedi, Soumik Sarkar
https://arxiv.org/abs/2509.13943 https://a…

Reinforcement Learning for Autonomous Point-to-Point UAV Navigation
Unmanned Aerial Vehicles (UAVs) are increasingly used in automated inspection, delivery, and navigation tasks that require reliable autonomy. This project develops a reinforcement learning (RL) approach to enable a single UAV to autonomously navigate between predefined points without manual intervention. The drone learns navigation policies through trial-and-error interaction, using a custom reward function that encourages goal-reaching efficiency while penalizing collisions and unsafe behavior…

Reconfigurable miniaturized computational spectrometer enabled by photoelastic effect
Linjun Zhai, Baolei Liu, Muchen Zhu, Yao Wang, Chaohao Chen, Zhaohua Yang, Lan Fu, Fan Wang
https://arxiv.org/abs/2508.12077

Reconfigurable miniaturized computational spectrometer enabled by photoelastic effect
Miniatured computational spectrometers, distinguished by their compact size and lightweight, have shown great promise for on-chip and portable applications in the fields of healthcare, environmental monitoring, food safety, and industrial process monitoring. However, the common miniaturization strategies predominantly rely on advanced micro-nano fabrication and complex material engineering, limiting their scalability and affordability. Here, we present a broadband miniaturized computational spe…

BIM Informed Visual SLAM for Construction Monitoring
Asier Bikandi, Miguel Fernandez-Cortizas, Muhammad Shaheer, Ali Tourani, Holger Voos, Jose Luis Sanchez-Lopez
https://arxiv.org/abs/2509.13972

BIM Informed Visual SLAM for Construction Monitoring
Simultaneous Localization and Mapping (SLAM) is a key tool for monitoring construction sites, where aligning the evolving as-built state with the as-planned design enables early error detection and reduces costly rework. LiDAR-based SLAM achieves high geometric precision, but its sensors are typically large and power-demanding, limiting their use on portable platforms. Visual SLAM offers a practical alternative with lightweight cameras already embedded in most mobile devices. however, visually …