Tootfinder

On the adsorption of oxygen to high entropy alloy surfaces up to 2ML coverage using Density Functional Theory and Monte Carlo calculations
Tyler D. Dole\v{z}al, Adib J. Samin
https://arxiv.org/abs/2507.20084

On the adsorption of oxygen to high entropy alloy surfaces up to 2ML coverage using Density Functional Theory and Monte Carlo calculations
To enhance our understanding of oxidation in high-entropy alloys, the early stages of oxidation on the surface of Al10Nb15Ta5Ti30Zr40 were studied using density functional theory and thermodynamic modeling. Surface slabs were generated from bulk configurations sampled from equilibrium using a multicell Monte Carlo method for phase prediction. The bulk structure was found to be a single BCC phase in good agreement with experimental observations. The oxygen adsorbed with a strong preference for s…

A Simple and Robust Weak Galerkin Method for the Brinkman Equations on Non-Convex Polytopal Meshes
Chunmei Wang, Shangyou Zhang
https://arxiv.org/abs/2507.18896 https://

A Simple and Robust Weak Galerkin Method for the Brinkman Equations on Non-Convex Polytopal Meshes
This paper presents a novel Stabilizer-Free weak Galerkin (WG) finite element method for solving the Brinkman equations without the need for conventional stabilization techniques. The Brinkman model, which mathematically blends features of both the Stokes and Darcy equations, describes fluid flow in multi-physics environments, particularly in heterogeneous porous media characterized by spatially varying permeability. In such settings, flow behavior may be governed predominantly by Darcy dynamic…

First-order methods for stochastic and finite-sum convex optimization with deterministic constraints
Zhaosong Lu, Yifeng Xiao
https://arxiv.org/abs/2506.20630

First-order methods for stochastic and finite-sum convex optimization with deterministic constraints
In this paper, we study a class of stochastic and finite-sum convex optimization problems with deterministic constraints. Existing methods typically aim to find an $ε$-$expectedly\ feasible\ stochastic\ optimal$ solution, in which the expected constraint violation and expected optimality gap are both within a prescribed tolerance $ε$. However, in many practical applications, constraints must be nearly satisfied with certainty, rendering such solutions potentially unsuitable due to the risk of…

A look at seven UX issues in the Fediverse web experience, including complex onboarding, the lack of a dedicated DM UI wrapper, and fragmented user discovery (Tim Chambers)
https://www.timothychambers.net/2025/06/18/113327.html

The Seven Deadly UX Sins of the Fediverse Web Experience (To Fix)
So, confession time: I was recently helping a new client get set up on the Fediverse—guiding them through their first steps into our glorious decentralized galaxy. And seeing it all again through fresh eyes? Reader, it was brutal. So much of what should be table stakes for any social media UX in the year of our Lord 2025 still is missing or deeply broken still. I know progress has been made and a good fight, fought.

Electrically driven first-order phase transition of a 2D ionic crystal at the electrode/electrolyte interface
Federica Angiolari, Alessandro Coretti, Mathieu Salanne, Sara Bonella
https://arxiv.org/abs/2507.19087

Electrically driven first-order phase transition of a 2D ionic crystal at the electrode/electrolyte interface
Liquid electrolytes adsorbed at the surface of metallic electrodes display a multitude of structures that can largely differ from the parent bulk system, both in terms of composition and local organization. In particular, the existence of disorder-order or order-order transitions has been increasingly reported in experimental and simulation studies, and the electrode potential identified as the corresponding driving force. The microscopic mechanisms and the stages of the process are, however, p…

Fast and Fewrious: Stochastic binary perturbations from fast compact objects
Badal Bhalla, Benjamin V. Lehmann, Kuver Sinha, Tao Xu
https://arxiv.org/abs/2507.16894

Fast and Fewrious: Stochastic binary perturbations from fast compact objects
Massive compact objects soften binaries. This process has been used for decades to constrain the population of such objects, particularly as a component of dark matter (DM). The effects of light compact objects, such as those in the unconstrained asteroid-mass range, have generally been neglected. In principle, low-energy perturbers can harden binaries instead of softening them, but the standard lore is that this effect vanishes when the perturber velocities are large compared to the binary's o…

Implications of modern mass-loss rates for massive stars
JD Merritt, Simon Stevenson, Andreas Sander, Ilya Mandel, Jeff Riley, Ben Farr, L. A. C. van Son, Tom Wagg, Serena Vinciguerra, Holden Jose
https://arxiv.org/abs/2507.17052

Implications of modern mass-loss rates for massive stars
Massive stars lose a significant fraction of their mass through stellar winds at various stages of their lives, including on the main sequence, during the red supergiant phase, and as evolved helium-rich Wolf--Rayet stars. In stellar population synthesis, uncertainty in the mass-loss rates in these evolutionary stages limits our understanding of the formation of black holes and merging compact binaries. In the last decade, the theoretical predictions, simulation, and direct observation of wind …

One Step Beyond: Feedthrough & Placement-Aware Rectilinear Floorplanner
Zhexuan Xu, Jie Wang, Siyuan Xu, Zijie Geng, Mingxuan Yuan, Feng Wu
https://arxiv.org/abs/2507.14914

One Step Beyond: Feedthrough & Placement-Aware Rectilinear Floorplanner
Floorplanning determines the shapes and locations of modules on a chip canvas and plays a critical role in optimizing the chip's Power, Performance, and Area (PPA) metrics. However, existing floorplanning approaches often fail to integrate with subsequent physical design stages, leading to suboptimal in-module component placement and excessive inter-module feedthrough. To tackle this challenge, we propose Flora, a three-stage feedthrough and placement aware rectilinear floorplanner. In the firs…

Boosting Accelerated Proximal Gradient Method with Adaptive Sampling for Stochastic Composite Optimization
Dongxuan Zhu, Weihuan Huang, Caihua Chen
https://arxiv.org/abs/2507.18277

Boosting Accelerated Proximal Gradient Method with Adaptive Sampling for Stochastic Composite Optimization
We develop an adaptive Nesterov accelerated proximal gradient (adaNAPG) algorithm for stochastic composite optimization problems, boosting the Nesterov accelerated proximal gradient (NAPG) algorithm through the integration of an adaptive sampling strategy for gradient estimation. We provide a complexity analysis demonstrating that the new algorithm, adaNAPG, achieves both the optimal iteration complexity and the optimal sample complexity as outlined in the existing literature. Additionally, we …

Last-Iterate Complexity of SGD for Convex and Smooth Stochastic Problems
Guillaume Garrigos, Daniel Cortild, Lucas Ketels, Juan Peypouquet
https://arxiv.org/abs/2507.14122

Last-Iterate Complexity of SGD for Convex and Smooth Stochastic Problems
Most results on Stochastic Gradient Descent (SGD) in the convex and smooth setting are presented under the form of bounds on the ergodic function value gap. It is an open question whether bounds can be derived directly on the last iterate of SGD in this context. Recent advances suggest that it should be possible. For instance, it can be achieved by making the additional, yet unverifiable, assumption that the variance of the stochastic gradients is uniformly bounded. In this paper, we show that …