Tootfinder

Apple should be given ten years in the pen for having killed #iTunes
#Music is a POS!

This https://arxiv.org/abs/2410.08562 has been replaced.
initial toot: https://mastoxiv.page/@a…

Rethinking Gradient-Based Methods: Multi-Property Materials Design Beyond Differentiable Targets
Gradient-based methods offer a simple, efficient strategy for materials design by directly optimizing candidates using gradients from pretrained property predictors. However, their use in crystal structure optimization is hindered by two key challenges: handling non-differentiable constraints, such as charge neutrality and structural fidelity, and susceptibility to poor local minima. We revisit and extend the gradient-based methods to address these issues. We propose Simultaneous Multi-property…

Study of the Turbulent/Non-turbulent Interface of Zero-Pressure-Gradient Turbulent Boundary Layer Using the Uniform Momentum Zone Concept
Bihai Sun, Callum Atkinson, Julio Soria
https://arxiv.org/abs/2505.23589

Study of the Turbulent/Non-turbulent Interface of Zero-Pressure-Gradient Turbulent Boundary Layer Using the Uniform Momentum Zone Concept
This paper investigates the turbulent--non-turbulent interface (TNTI) in a zero-pressure-gradient turbulent boundary layer (ZPG-TBL) using a novel, threshold-free method based on the uniform momentum zone (UMZ) concept. Requiring only planar streamwise velocity data, the method is directly applicable to experimental PIV and ensures consistent TNTI detection across simulations and experiments. Its performance is demonstrated using DNS data at $Re_τ= 1,000 - 2,000$. The TNTI height scales with t…

This https://arxiv.org/abs/2505.08408 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

A three-term Polak-Ribière-Polyak conjugate gradient method for vector optimization
A three-term Polak-Ribière-Polyak conjugate gradient method is first proposed in this paper for solving vector optimization problems. This method can autonomously generate descent directions independent of line search procedures, while retaining the conjugate property. The global convergence of the proposed scheme is established by the generalized Wolfe line search procedure without self-adjusting strategies, regular restarts and convexity assumptions. Finally, numerical experiments illustrati…

This https://arxiv.org/abs/2212.06092 has been replaced.
link: https://scholar.google.com/scholar?q=a

A gradient flow for the Porous Medium Equations with Dirichlet boundary conditions
We consider the gradient flow structure of the porous medium equations with non-negative constant Dirichlet boundary conditions. We construct weak solutions to the equations via the minimizing movement scheme by considering an entropy functional with respect to $Wb_2$ distance, which is a modified Wasserstein distance introduced by Figalli and Gigli [J. Math. Pures Appl. 94, (2010), pp. 107-130]. Furthermore, the constructed solutions are characterized as curves of maximal slope in a suitable s…

Modeling extreme events and intermittency in turbulent diffusion with a mean gradient
Mustafa A Mohamad, Di Qi
https://arxiv.org/abs/2505.21688 https://

Modeling extreme events and intermittency in turbulent diffusion with a mean gradient
We study the statistical properties of passive tracer transport in turbulent flows with a mean gradient, emphasizing tracer intermittency and extreme events. An analytically tractable model is developed, coupling zonal and shear velocity components with both linear and nonlinear stochastic dynamics. Formulating the model in Fourier space, a simple explicit solution for the tracer invariant statistics is derived. Through this model we identify the resonance condition responsible for non-Gaussian…

This https://arxiv.org/abs/2403.13627 has been replaced.
initial toot: https://mastoxiv.page/@a…

A Straightforward Gradient-Based Approach for High-Tc Superconductor Design: Leveraging Domain Knowledge via Adaptive Constraints
Materials design aims to discover novel compounds with desired properties. However, prevailing strategies face critical trade-offs. Conventional element-substitution approaches readily and adaptively incorporate various domain knowledge but remain confined to a narrow search space. In contrast, deep generative models efficiently explore vast compositional landscapes, yet they struggle to flexibly integrate domain knowledge. To address these trade-offs, we propose a gradient-based material desig…

This https://arxiv.org/abs/2505.22398 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Numerical Optimization Strategies for the Variational Hamiltonian Ansatz in Noisy Quantum Environments
We conduct a benchmark of eight optimization algorithms for variational quantum chemistry using the tVHA, evaluating performance on $H_2$, $H_4$, and $LiH$ (in both full and active spaces) under noiseless and sampling noise conditions. Sampling noise fundamentally alters optimizer behavior, with gradient-based methods performing best in ideal conditions, while population-based algorithms, such as CMA-ES, show greater resilience under noise. Hartree-Fock initialization reduces the number of func…

This https://arxiv.org/abs/2505.08408 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

A three-term Polak-Ribière-Polyak conjugate gradient method for vector optimization
A three-term Polak-Ribière-Polyak conjugate gradient method is first proposed in this paper for solving vector optimization problems. This method can autonomously generate descent directions independent of line search procedures, while retaining the conjugate property. The global convergence of the proposed scheme is established by the generalized Wolfe line search procedure without self-adjusting strategies, regular restarts and convexity assumptions. Finally, numerical experiments illustrati…

Aggregation of vortex structures in 2D: the blob-wave system and its role in zonal flows
Franco Flandoli, Matteo Palmieri, Milo Viviani
https://arxiv.org/abs/2505.22700

Aggregation of vortex structures in 2D: the blob-wave system and its role in zonal flows
We give a rigorous mathematical result, supported by accurate numerical simulations, of the aggregation of a concentrated vortex blob with an underlying non constant vorticity field: the blob moves in the direction of the gradient of the field. It is a unique example of Lagrangian explanation of aggregation of vortex structures of the same sign in 2D inviscid fluids. A conceptual model of zonal flow maintenance and modulation based on this idea is then developed, which produces shapes in accord…

This https://arxiv.org/abs/2409.17022 has been replaced.
initial toot: https://mastoxiv.page/@a…

Improper flexoelectricity in hexagonal rare-earth ferrites
Flexoelectricity is a universal effect that generates electric polarization due to broken inversion symmetry caused by local strain gradient. The large strain gradient at nanoscale makes flexo-electric effects, especially in nanoscopic ferroelectric materials, promising in sensors, actuator, energy harvesting, and memory applications. In this work, we studied flexoelectricity in hexagonal ferrites h-YbFeO3, an improper ferroelectric expected to have weak piezoelectricity and low sensitivity to …

This https://arxiv.org/abs/2411.05696 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

A gradient flow perspective on McKean-Vlasov equations in econophysics
We prove that the Gini coefficient of economic inequality is a Lyapunov functional for a class of nonlinear, nonlocal integro-differential equations arising at the intersection of mathematics, economics, and statistical physics. Next, a novel Riemannian geometry is imposed on a subset of probability densities such that the evolutionary dynamics are formally driven by the Gini coefficient functional as a gradient flow. Thus in the same way that classical 2-Wasserstein theory connects heat flow a…

This https://arxiv.org/abs/2410.03874 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

A differentiable N-body code for transit timing and dynamical modelling -- II. Photodynamics
Exoplanet transits contain substantial information about the architecture of a system. By fitting transit light curves we can extract dynamical parameters and place constraints on the properties of the planets and their host star. Having a well-defined probabilistic model plays a crucial role in making robust measurements of these parameters, and the ability to differentiate the model provides access to more robust inference tools. Gradient-based inference methods can allow for more rapid and a…

Theory of chiral-phonon-activated spin Seebeck effect
Naoki Nishimura, Takumi Funato, Mamoru Matsuo, Takeo Kato
https://arxiv.org/abs/2505.23083 https://…

Theory of chiral-phonon-activated spin Seebeck effect
We theoretically explore the generation of spin current driven by a temperature gradient in a junction between a chiral insulator and a normal metal. Based on the gyromagnetic effect caused by microscopic rotation due to phonons, we derive a formula for a spin current when a finite temperature difference is imposed at two ends of the sample. We clarify how the spin current depends on the sample geometry, the thermal conductivity, the heat conductance at the interface, and the average temperatur…

Emergent universal long-range structure in random-organizing systems
Satyam Anand, Guanming Zhang, Stefano Martiniani
https://arxiv.org/abs/2505.22933 http…

Emergent universal long-range structure in random-organizing systems
Self-organization through noisy interactions is ubiquitous across physics, mathematics, and machine learning, yet how long-range structure emerges from local noisy dynamics remains poorly understood. Here, we investigate three paradigmatic random-organizing particle systems drawn from distinct domains: models from soft matter physics (random organization, biased random organization) and machine learning (stochastic gradient descent), each characterized by distinct sources of noise. We discover …

This https://arxiv.org/abs/2406.19061 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Entrywise dynamics and universality of general first order methods
General first order methods (GFOMs), including various gradient descent and AMP algorithms, constitute a broad class of iterative algorithms in modern statistical learning problems. Some GFOMs also serve as constructive proof devices, iteratively characterizing the empirical distributions of statistical estimators in the large system limits for any fixed number of iterations. This paper develops a non-asymptotic, entrywise characterization for a general class of GFOMs. Our characterizations c…

This https://arxiv.org/abs/2412.19529 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Nonconvex Stochastic Optimization under Heavy-Tailed Noises: Optimal Convergence without Gradient Clipping
Recently, the study of heavy-tailed noises in first-order nonconvex stochastic optimization has gotten a lot of attention since it was recognized as a more realistic condition as suggested by many empirical observations. Specifically, the stochastic noise (the difference between the stochastic and true gradient) is considered to have only a finite $\mathfrak{p}$-th moment where $\mathfrak{p}\in\left(1,2\right]$ instead of assuming it always satisfies the classical finite variance assumption. To…

Precise Gradient Discontinuities in Neural Fields for Subspace Physics
Mengfei Liu, Yue Chang, Zhecheng Wang, Peter Yichen Chen, Eitan Grinspun
https://arxiv.org/abs/2505.20421

Precise Gradient Discontinuities in Neural Fields for Subspace Physics
Discontinuities in spatial derivatives appear in a wide range of physical systems, from creased thin sheets to materials with sharp stiffness transitions. Accurately modeling these features is essential for simulation but remains challenging for traditional mesh-based methods, which require discontinuity-aligned remeshing -- entangling geometry with simulation and hindering generalization across shape families. Neural fields offer an appealing alternative by encoding basis functions as smooth…

Response to comment on Mutualism weaken the latitudinal diversity gradient among oceanic islands
Camille Delavaux, Thomas Crowther, James Bever, Evan Gora
https://arxiv.org/abs/2505.21006

Response to comment on Mutualism weaken the latitudinal diversity gradient among oceanic islands
In our original paper (Delavaux et al. 2024; https://www.nature.com/articles/s41586-024-07110-y), we find that the latitudinal diversity gradient (LDG) in plant species richness is reduced on oceanic islands worldwide. Moreover, we find that plants that associate with mutualists, including pollinators, AM fungi, and N-fixing bacteria, disproportionately contribute to this reduction. To make this assertion, we fit models of continental diversity to absolute latitude and compared mainland diversi…

This https://arxiv.org/abs/2412.19529 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Nonconvex Stochastic Optimization under Heavy-Tailed Noises: Optimal Convergence without Gradient Clipping
Recently, the study of heavy-tailed noises in first-order nonconvex stochastic optimization has gotten a lot of attention since it was recognized as a more realistic condition as suggested by many empirical observations. Specifically, the stochastic noise (the difference between the stochastic and true gradient) is considered to have only a finite $\mathfrak{p}$-th moment where $\mathfrak{p}\in\left(1,2\right]$ instead of assuming it always satisfies the classical finite variance assumption. To…

Competing Mechanisms at Vibrated Interfaces of Density-Stratified Fluids
Tianyi Chu, Benjamin Wilfong, Timothy Koehler, Ryan M. McMullen, Spencer H. Bryngelson
https://arxiv.org/abs/2505.23578

Competing Mechanisms at Vibrated Interfaces of Density-Stratified Fluids
Fluid--fluid interfacial instability and subsequent fluid mixing are ubiquitous in nature and engineering. Two hydrodynamic instabilities have long been thought to govern the interface behavior: the pressure gradient-driven long-wavelength Rayleigh--Taylor (RT) instability and resonance-induced short-wavelength Faraday instability. However, neither instability alone can explain the dynamics when both mechanisms act concurrently. Instead, we identify a previously unseen multi-modal instability e…

Geometry effects on zonal flow dynamics and turbulent transport in optimized stellarators
Haotian Chen, Xishuo Wei, Hongxuan Zhu, Zhihong Lin
https://arxiv.org/abs/2505.21886

Geometry effects on zonal flow dynamics and turbulent transport in optimized stellarators
Global gyrokinetic simulations find a strong suppression of ion temperature gradient (ITG) turbulence by zonal flows in stellarators optimized for neoclassical transport. The reduction of the ITG transport by the zonal flows in quasi-helicalsymmetric (QH) and quasi-isodynamic (QI) stellarators are much larger than a quasi-axisymmetric (QA) stellarator or a tokamak, thanks to higher linear residual levels and lower nonlinear frequencies of the zonal flows in the QH and QI. The transport level an…

This https://arxiv.org/abs/2504.11021 has been replaced.
initial toot: https://mastoxiv.page/@arXi…

Tunable self-emulsification via viscoelastic control of Marangoni-driven interfacial instabilities
Interfacial instabilities in multicomponent fluidic systems are widespread in nature and in industrial processes, yet controlling their dynamics remains a challenge. Here, we present a strategy to actively tune Marangoni-driven self-emulsification at liquid-liquid interfaces by harnessing fluid viscoelasticity. When a water-alcohol droplet spreads on an oil bath, a radial surface tension gradient induced by selective alcohol evaporation drives an interfacial instability, leading to the spontane…

This https://arxiv.org/abs/2501.01797 has been replaced.
initial toot: https://mastoxiv.page/@arX…

Ohm's law, Joule heat, and Planckian dissipation
Electric current generation and its dissipation are important physical processes. It ranges from the one follows the Ohm's law to superconductivity. Recently, it has been shown that the gradient of the chemical potential force arises from the time-component of the Berry connection from many-electron wave functions, and we consider its importance for the electric current conduction in this work. We first show that it rectifies the odd explanation in Joule heating by electric current in a metalli…

This https://arxiv.org/abs/2504.01195 has been replaced.
initial toot: https://mastoxiv.page/@ar…

Towards Signed Distance Function based Metamaterial Design: Neural Operator Transformer for Forward Prediction and Diffusion Model for Inverse Design
The inverse design of metamaterial architectures presents a significant challenge, particularly for nonlinear mechanical properties involving large deformations, buckling, contact, and plasticity. Traditional methods, such as gradient-based optimization, and recent generative deep-learning approaches often rely on binary pixel-based representations, which introduce jagged edges that hinder finite element (FE) simulations and 3D printing. To overcome these challenges, we propose an inverse desig…

Hybrid Machine Learning and Mathematical Modeling for Tumor Dynamics Prediction: Comparing SPIONs against mNP-FDG
Amit K Chattopadhyay, Aimee Pascaline N Unkundiye, Gillian Pearce
https://arxiv.org/abs/2505.21094

Hybrid Machine Learning and Mathematical Modeling for Tumor Dynamics Prediction: Comparing SPIONs against mNP-FDG
This is a Machine Learning guided study towards zone-specific ray therapy. Combining Machine Learning (Extreme Gradient Boosting) with continuum modeling (exponential and logistic growth), we find that while fluorodeoxyglucose-coated (mNP-FDG) can control cancerous tumor progression within 2 days compared to 18 days by Superparamagnetic Iron Oxide Nanoparticles (SPIONs), for complete termination of the tumor, SPIONS (20 days) are superior compared to mNP-FDG (more than 40 days). We also provide…

Layer potentials for elliptic operators with DMO-type coefficients: big pieces $Tb$ theorem, quantitative rectifiability, and free boundary problems
Andrea Merlo, Mihalis Mourgoglou, Carmelo Puliatti
https://arxiv.org/abs/2505.23478

Layer potentials for elliptic operators with DMO-type coefficients: big pieces $Tb$ theorem, quantitative rectifiability, and free boundary problems
For $n \geq 2$, we consider the operator $L_A = -\mathrm{div }(A(\cdot)\nabla)$, where $A$ is a uniformly elliptic $(n+1)\times(n+1)$ matrix with variable coefficients, a Radon measure $μ$ on $\mathbb{R}^{n+1}$, and the associated gradient of the single layer potential operator $T_μ$. Under a Dini-type assumption on the mean oscillation of the matrix $A$, we establish the following results: 1) A rectifiability criterion for $μ$ in terms of $T_μ$. Under quantitative geometric and analytic …

Turns out that if you model online spaces after real world ones, it works pretty well. Online spaces let you be in many places at once which changes the dynamics, but as an example of something that ports well,
https://www.patternlanguageindex.com/patterns/intimacy-gradient
This pattern works not just for the design of houses but online spaces. Let people get to know a group in less-intimate space before they end up in the more-intimate space. Having a few gradations works really well, and it doesn't have to be a power play or status game.

This https://arxiv.org/abs/2412.13523 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qfi…

Strictly monotone mean-variance preferences with applications to portfolio selection
This paper extends the monotone mean-variance (MMV) preference to a broader class of strictly monotone mean-variance (SMMV) preferences, and demonstrates its applications to portfolio selection problems. For the single-period portfolio problem under the SMMV preference, we derive the gradient condition for the optimal strategy, and investigate its association with the optimal mean-variance (MV) static strategy. A novel contribution of this work is the reduction of the problem to solving a set o…

Updated baseline design for HALHF: the hybrid, asymmetric, linear Higgs factory
C. A. Lindstr{\o}m, E. Adli, J. B. B. Chen, P. Drobniak, E. E. H{\o}rlyk, D. Kalvik, K. N. Sjobak, T. Barklow, S. Gessner, M. Hogan, M. Berggren, A. Laudrain, B. List, J. List, V. Maslov, K. P\~oder, M. Th\'evenet, N. Walker, J. Wood, S. Boogert, P. N. Burrows, V. Cilento, R. D'Arcy, B. Foster, S. Farrington, X. Lu, G. Moortgat-Pick, A. Seryi

Updated baseline design for HALHF: the hybrid, asymmetric, linear Higgs factory
Particle physicists aim to construct a electron-positron Higgs factory as the next major particle collider. However, the high associated costs motivate the development of more affordable collider designs. Plasma-wakefield acceleration is a promising technology to this end. HALHF is a proposal for a Higgs factory that utilizes beam-driven plasma-wakefield acceleration to accelerate electrons to high energy with high gradient, while using radio-frequency acceleration to accelerate positrons to a …

News That Matters
https://velvetshark.com/ai-company-logos-that-look-like-buttholes

Why do AI company logos look like buttholes?
A humorous exploration of the uncanny resemblance between AI company logos and human anatomy. Discover why circular, gradient-based designs dominate the AI industry, and what this design convergence tells us about branding in tech.

This https://arxiv.org/abs/2505.09551 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qfi…

Fast Learning in Quantitative Finance with Extreme Learning Machine
This paper demonstrates that a broad class of problems in quantitative finance, including those previously addressed using deep neural networks, can be efficiently solved using single-layer neural networks without iterative gradient-based training, namely extreme learning machine (ELM). ELM utilizes a single-layer network with randomly initialized hidden nodes and analytically computed output weights obtained via convex optimization, enabling rapid training and inference. Both supervised and un…

This https://arxiv.org/abs/2203.06002 has been replaced.
link: https://scholar.google.com/scholar?q=a

Experiments on the Violation of Electromagnetic Gauge Symmetry by Yang-Mills Gravity Using Josephson Effects in Superconductors
Yang-Mills gravity is a quantum theory of gravity with translational gauge symmetry that is based on a flat space-time. The universal coupling of all quantum fields to quantum Yang-Mills gravity is based on the replacement of $\partial_μ$ by the translational gauge covariant derivative $(\partial_μ+gϕ_μ^ν\partial_ν)$ in the Lagrangians of non-gravitational fields. Near the surface of the Earth, Yang-Mills gravity causes the phase gradient $\partial_k θ$ to be altered by a factor of $h_1\…

This https://arxiv.org/abs/2412.18751 has been replaced.
initial toot: https://mastoxiv.page/@arXi…

Two apparently different interfacial stress formulations constructed from the diffuse interface free energy model
To express the capillary stress in the diffuse interface method, there are two different formulations in the literature: one formulation is proportional to the density and the other is to the density gradient. In the present study, we theoretically show that only the latter represents the capillary stress in one-component fluids and the former represents the stress related to the osmotic pressure.

Adjoint chromoelectric correlators for heavy quarkonium diffusion
Julian Mayer-Steudte
https://arxiv.org/abs/2505.20549 https://arxiv…

Adjoint chromoelectric correlators for heavy quarkonium diffusion
We here measure, for the first time, adjoint chromoelectric correlators at finite temperatures that encode the diffusion of quarkonium in the medium. Understanding the dynamics of quarkonium in the QGP plays an essential role in understanding quarkonium suppression and the QGP in general. We perform SU(3) gauge theory calculations and use gradient flow to improve the signal-to-noise ratio and chromoelectric field discretizations. The continuum limit and the zero-flow-time extrapolation are perf…

This https://arxiv.org/abs/2410.09795 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qbi…

WGFormer: An SE(3)-Transformer Driven by Wasserstein Gradient Flows for Molecular Ground-State Conformation Prediction
Predicting molecular ground-state conformation (i.e., energy-minimized conformation) is crucial for many chemical applications such as molecular docking and property prediction. Classic energy-based simulation is time-consuming when solving this problem, while existing learning-based methods have advantages in computational efficiency but sacrifice accuracy and interpretability. In this work, we propose a novel and effective method to bridge the energy-based simulation and the learning-based st…

Two years ago at #CSUN I learned about what became my favorite browser extension, BeeLine Reader. I've been a subscriber ever since.
It's easy to set up on desktop, but has been some struggle to get working on Android. But this week I discovered it works with Microsoft's Edge Canary mobile browser, which has experimental support for extensions. Instructions are here:

https://velvetshark.com/ai-company-logos-that-look-like-buttholes