Tootfinder

A Comparison of Low and high-Order Methods for the Simulation of Supersonic Jet Flows
D. F. Abreu, C. Junqueira-Junior, E. T. V. Dauricio, J. L. F. Azevedo
https://arxiv.org/abs/2509.17725

A Comparison of Low and high-Order Methods for the Simulation of Supersonic Jet Flows
The present work compares results for different numerical methods in search of alternatives to improve the quality of large-eddy simulations for the problem of supersonic turbulent jet flows. Previous work has analyzed supersonic jet flows using a second-order, finite difference solver based on structured meshes, and the results indicated a shorter potential core of the jet and different levels of velocity fluctuations. In the present work, the results of previous simulations are compared to ne…

Long-wave instability of periodic shear flows for the 2D Navier-Stokes equations
Maria Colombo, Michele Dolce, Riccardo Montalto, Paolo Ventura
https://arxiv.org/abs/2509.18070 …

Long-wave instability of periodic shear flows for the 2D Navier-Stokes equations
In 1959, Kolmogorov proposed to study the instability of the shear flow $(\sin(y),0)$ in the vanishing viscosity regime in tori $\mathbb{T}_α\times \mathbb{T}$. This question was later resolved by Meshalkin and Sinai. We extend the problem to general shear flows $(U(y),0)$ and show that every $U(y)$ exhibits long-wave instability whenever $\|\partial_y^{-1} U\|_{L^2} > ν$ and $α\ll ν$, with $ν$ being the kinematic viscosity. This instability mechanism confirms previous findings b…

Hessian-guided Perturbed Wasserstein Gradient Flows for Escaping Saddle Points
Naoya Yamamoto, Juno Kim, Taiji Suzuki
https://arxiv.org/abs/2509.16974 https://

Hessian-guided Perturbed Wasserstein Gradient Flows for Escaping Saddle Points
Wasserstein gradient flow (WGF) is a common method to perform optimization over the space of probability measures. While WGF is guaranteed to converge to a first-order stationary point, for nonconvex functionals the converged solution does not necessarily satisfy the second-order optimality condition; i.e., it could converge to a saddle point. In this work, we propose a new algorithm for probability measure optimization, perturbed Wasserstein gradient flow (PWGF), that achieves second-order opt…

"New conservation area protects 53% of carbon in northern Peruvian Amazon"
#Amazon #Conservation #Environment

New conservation area protects 53% of carbon in northern Peruvian Amazon
A new regional conservation area has been created in Loreto, the largest region in Peru’s Amazon. The Medio Putumayo Algodón Regional Conservation Area is the fourth protected natural area in the Putumayo region, an area connected by the Putumayo River, which flows into Colombia. The Ministry of the Environment established the area on June 6 […]

Waves drive the rise and fall of 2D flows in rotating turbulence
S\'ebastien Gom\'e, Anna Frishman
https://arxiv.org/abs/2509.18323 https://arxiv.o…

🌐 Network and console error diagnosis - analyze network requests for #CORS issues and inspect console logs to understand feature failures
🎯 User behavior simulation - navigate pages, fill forms, click buttons to reproduce bugs and test complex user flows while inspecting runtime environment
🎨 Live styling and layout debugging - connect to live pages, inspect

Pseudo-Anosov Flows: A Plane Approach
Thomas Barthelm\'e, Kathryn Mann
https://arxiv.org/abs/2509.15375 https://arxiv.org/pdf/2509.15375

Pseudo-Anosov Flows: A Plane Approach
In this text we (re)-tell the theory of pseudo-Anosov flows on 3-manifolds with the orbit space as the central character; via a streamlined framework called {\em Anosov-like group actions}. This brings a simplified and unified perspective, and allows for the import of tools from 1- and 2-dimensional topological dynamics. In so doing, we are able to give a relatively efficient presentation (or re-presentation) of foundational results in the field which appeared over several decades and many pape…

Variable-preconditioned transformed primal-dual method for generalized Wasserstein Gradient Flows
Jin Zeng, Dawei Zhan, Ruchi Guo, Chaozhen Wei
https://arxiv.org/abs/2509.15385 …

Variable-preconditioned transformed primal-dual method for generalized Wasserstein Gradient Flows
We propose a Variable-Preconditioned Transformed Primal-Dual (VPTPD) method for solving generalized Wasserstein gradient flows via a structure-preserving JKO scheme. This is a nontrivial extension of the TPD method [Chen et al. (2023) arXiv:2312.12355] incorporating proximal splitting techniques to address the challenges arising from the nonsmoothness of the objective function. Our key contributions include: (i) a semi-implicit-explicit iteration that combines proximal steps for the nonsmooth p…

Real-Time Planning and Control with a Vortex Particle Model for Fixed-Wing UAVs in Unsteady Flows
Ashwin Gupta, Kevin Wolfe, Gino Perrotta, Joseph Moore
https://arxiv.org/abs/2509.16079

Real-Time Planning and Control with a Vortex Particle Model for Fixed-Wing UAVs in Unsteady Flows
Unsteady aerodynamic effects can have a profound impact on aerial vehicle flight performance, especially during agile maneuvers and in complex aerodynamic environments. In this paper, we present a real-time planning and control approach capable of reasoning about unsteady aerodynamics. Our approach relies on a lightweight vortex particle model, parallelized to allow GPU acceleration, and a sampling-based policy optimization strategy capable of leveraging the vortex particle model for predictive…

Non-isentropic cavity flow for the multi-d compressible Euler system
Helge Kristian Jenssen, Charis Tsikkou
https://arxiv.org/abs/2509.16435 https://arxiv.…

Non-isentropic cavity flow for the multi-d compressible Euler system
We rigorously construct non-isentropic and self-similar multi-d Euler flows in which a central cavity (vacuum region) collapses. While isentropic flows of this type have been analyzed earlier by Hunter \cite{hun_60} and others, the non-isentropic setting introduces additional complications, in particular with respect to the behavior along the fluid-vacuum interface. The flows we construct satisfy the physical boundary conditions: the interface is a material surface along which the pressure vani…

ChannelFlow-Tools: A Standardized Dataset Creation Pipeline for 3D Obstructed Channel Flows
Shubham Kavane, Kajol Kulkarni, Harald Koestler
https://arxiv.org/abs/2509.15236 http…

ChannelFlow-Tools: A Standardized Dataset Creation Pipeline for 3D Obstructed Channel Flows
We present ChannelFlow-Tools, a configuration-driven framework that standardizes the end-to-end path from programmatic CAD solid generation to ML-ready inputs and targets for 3D obstructed channel flows. The toolchain integrates geometry synthesis with feasibility checks, signed distance field (SDF) voxelization, automated solver orchestration on HPC (waLBerla LBM), and Cartesian resampling to co-registered multi-resolution tensors. A single Hydra/OmegaConf configuration governs all stages, ena…

Soret and Dufour effects in hot and dense QCD matter
Kamaljeet Singh, Kangkan Goswami, Raghunath Sahoo
https://arxiv.org/abs/2509.18946 https://arxiv.org/p…

Soret and Dufour effects in hot and dense QCD matter
The gradients act as invisible engines of transport, converting microscopic imbalances into macroscopic flows, and thus providing deep insights into the dynamics of physical systems. Thermal gradients do not merely drive the flow of heat, but they also set the microscopic constituents of the system into motion. In such scenarios, the constituents of the system not only transport energy but also diffuse collectively under the influence of these gradients. For the very first time, we present a fi…

Whistling of turbulent cavity flows: Self-consistent predictions with the linearized compressible Navier-Stokes equations
Nikolaos Bozikis, Dilara \"Ozev, Nicolas Noiray
https://arxiv.org/abs/2509.17986

Whistling of turbulent cavity flows: Self-consistent predictions with the linearized compressible Navier-Stokes equations
A self-consistent saturation model for the prediction of aeroacoustic limit cycles emerging in turbulent low-Mach cavity flows (Re=O(10^5), M\simeq 0.2) is proposed. It predicts the nonlinear interactions between the acoustic modes of a deep rectangular cavity and the hydrodynamic instabilities of the turbulent shear-layer that forms over its opening due to the presence of a grazing flow. The model is based on the triple decomposition of the flow variables and the compressible Navier-Stokes equ…

Bacteria collective motion is scale-free
Benjamin Perez-Estay, Vincent Martinez, Carine Douarche, Jana Schwarz-Linek, Jochen Arlt, Pierre-Henri Delville, Gail McConnell, Wilson C. K. Poon, Anke Lindner, Eric Clement
https://arxiv.org/abs/2509.15918

Bacteria collective motion is scale-free
Suspensions of swimming bacteria interact hydrodynamically over long ranges, organizing themselves into collective states that drive large-scale chaotic flows, often referred to as "bacterial turbulence". Despite extensive experimental and theoretical work, it remains unclear whether an intrinsic length scale underlies the observed patterns. To shed light on the mechanism driving active turbulence, we investigate the emergence of large-scale flows in E. coli suspensions confined within cylindri…

Replaced article(s) found for physics.plasm-ph. https://arxiv.org/list/physics.plasm-ph/new
[1/1]:
- Vibrational-Electron Heating in Plasma Flows: A Thermodynamically Consistent Model
Felipe Martin Rodriguez Fuentes, Bernard Parent

Reconstruction of three-dimensional turbulent flows from sparse and noisy planar measurements: A weight-sharing neural network approach
Yaxin Mo, Luca Magri
https://arxiv.org/abs/2509.18687

Reconstruction of three-dimensional turbulent flows from sparse and noisy planar measurements: A weight-sharing neural network approach
This paper proposes a method for reconstructing three-dimensional turbulent flows from sparse measurements without the need for ground truth data during training. A weight-sharing network is developed to infer the full flow fields from measurements of velocity sampled at three planes and boundary pressure at one additional plane, inspired by experimental configurations. The weight-sharing network shares identical parameters along homogeneous directions, which results in efficient data utilizati…

On Uniformly Scaling Flows: A Density-Aligned Approach to Deep One-Class Classification
Faried Abu Zaid, Tim Katzke, Emmanuel M\"uller, Daniel Neider
https://arxiv.org/abs/2510.09452

On Uniformly Scaling Flows: A Density-Aligned Approach to Deep One-Class Classification
Unsupervised anomaly detection is often framed around two widely studied paradigms. Deep one-class classification, exemplified by Deep SVDD, learns compact latent representations of normality, while density estimators realized by normalizing flows directly model the likelihood of nominal data. In this work, we show that uniformly scaling flows (USFs), normalizing flows with a constant Jacobian determinant, precisely connect these approaches. Specifically, we prove how training a USF via maximum…

Paris Marx visits Mél’s podcast.🍿
When asked how he would advise a government on/vs #AI, Paris expects fundamental confusion, as a state wants to use the current capital flows. Reminds me of how AI creeps into #university.

Crosslisted article(s) found for physics.geo-ph. https://arxiv.org/list/physics.geo-ph/new
[1/1]:
- Waves drive the rise and fall of 2D flows in rotating turbulence
S\'ebastien Gom\'e, Anna Frishman

A Comparison of LES Inlet Boundary Conditions for Supersonic Jet Flows
Diego F. Abreu, Carlos Junqueira-Junior, Eron T. V. Dauricio, Jo\~ao Luiz F. Azevedo
https://arxiv.org/abs/2509.17732

A Comparison of LES Inlet Boundary Conditions for Supersonic Jet Flows
The present work evaluates the effects of three inflow boundary conditions on large-eddy simulations of supersonic jet flows. The three inlet flow configurations considered are an inviscid profile, a stationary turbulent profile extracted from a RANS calculation, and a time-dependent tripped turbulent profile. The study applies the nodal discontinuous Galerkin spatial discretization to perform the supersonic jet flow simulations. Initially, a mesh and polynomial resolution study is performed to…

On-device Internet of Sounds Sonification with Wavetable Synthesis Techniques for Soil Moisture Monitoring in Water Scarcity Contexts
Stephen Roddy
https://arxiv.org/abs/2509.19097

China is allowing Nexperia to export chips again, according to officials from several auto companies; shares in Wingtech, Nexperia's Chinese parent, surged 10% (Bloomberg)
https://www.bloomberg.com/news/articles/2025-11-07…

Nexperia Spat Eases as Chip Flows Open Door to Dutch Reversal
China is allowing Dutch chipmaker Nexperia to export again, setting the stage for the Netherlands to suspend its powers over the Chinese-owned company.

An $\epsilon$-Regularity Theorem for Non-collapsed Ricci Flow
Harry Fluck, Max Hallgren
https://arxiv.org/abs/2509.14154 https://arxiv.org/pdf/2509.14154…

An $ε$-Regularity Theorem for Non-collapsed Ricci Flow
In this article we prove an $ε$-regularity theorem for non-collapsed Ricci flows, and use this to prove new estimates for singularity models of Fano Kähler-Ricci flows. In the course of our proof, we find a criterion for uniform convergence of solutions to the heat equation along a sequence of $\mathbb{F}$-converging Ricci flows, and apply this to new parabolic regularizations of some natural geometric quantities.

Crosslisted article(s) found for math.GT. https://arxiv.org/list/math.GT/new
[1/1]:
- Pseudo-Anosov Flows: A Plane Approach
Thomas Barthelm\'e, Kathryn Mann

Knotting Minimal Sets
Alex Clark, John Hunton
https://arxiv.org/abs/2509.17133 https://arxiv.org/pdf/2509.17133

Knotting Minimal Sets
We consider the ways minimal sets of flows in $S^3$ may be embedded. We prove that given any $C^2$ flow on $S^3$ with positive entropy, there is an uncountable collection of topologically distinct minimal sets $\mathcal{M}$ such that for each $M\in \mathcal{M}$ there are infinitely many embedded copies of $M$ in the flow, each copy with a distinct knot type, thus extending work of Franks and Williams for periodic orbits.

Modeling nonstationary spatial processes with normalizing flows
Pratik Nag, Andrew Zammit-Mangion, Ying Sun
https://arxiv.org/abs/2509.12884 https://arxiv.…

Modeling nonstationary spatial processes with normalizing flows
Nonstationary spatial processes can often be represented as stationary processes on a warped spatial domain. Selecting an appropriate spatial warping function for a given application is often difficult and, as a result of this, warping methods have largely been limited to two-dimensional spatial domains. In this paper, we introduce a novel approach to modeling nonstationary, anisotropic spatial processes using neural autoregressive flows (NAFs), a class of invertible mappings capable of generat…

16WW Electricity Profiles - 16WW grid import and export and other electricity hour-of-day flows. #stats #loadProfile - https://www.

16WW Electricity Profiles
16WW grid import and export and other electricity hour-of-day flows. #stats #loadProfile

On thermal holographic RG flows
Elena C\'aceres, Hare Krishna
https://arxiv.org/abs/2510.09955 https://arxiv.org/pdf/2510.09955

On thermal holographic RG flows
Holographic Renormalization Group (RG) flows, described by Einstein gravity coupled to matter fields, have been thoroughly explored in the context of vacuum states. In this work, we shift the focus to thermal states. Using the Hamilton-Jacobi formalism for the coupled system, we derive the Ward identity associated with broken dilatation symmetry in thermal correlators and obtain the modified Callan-Symanzik equation for the dual thermal CFT. We then employ the Hamiltonian approach to analyze th…

Modeling skiers flows via Wardrope equilibrium in closed capacitated networks
Demyan Yarmoshik, Igor Ignashin, Ekaterina Sikacheva, Alexander Gasnikov
https://arxiv.org/abs/2509.13392

Modeling skiers flows via Wardrope equilibrium in closed capacitated networks
We propose an equilibrium model of ski resorts where users are assigned to cycles in a closed network. As queues form on lifts with limited capacity, we derive an efficient way to find waiting times via convex optimization. The equilibrium problem is formulated as a variational inequality, and numerical experiments show that it can be solved using standard algorithms.

Whil I'm editing photos from our vacation I quickly share this from last year for #WaterfallWednesday .
Enjoy!
#photography #nature

Dynamics of quantized vortices under quasi-periodic boundary conditions
Fabio Magistrelli, Marco Antonelli
https://arxiv.org/abs/2509.15298 https://arxiv.o…

Dynamics of quantized vortices under quasi-periodic boundary conditions
The Gross-Pitaevskii equation is widely used for vortex dynamics, but finite domains with hard walls or confining potentials distort bulk behavior through vortex-image effects or induced flows. Periodic boundaries reduce wall artifacts yet cannot realize finite net vorticity because of topological obstruction, so bulk simulations with non-zero circulation are typically unavailable. Hence, we impose quasi-periodic boundary conditions that keep the superfluid's density periodic while enforcing ph…

Appreciate the WSJ essay from Lauren Powell Jobs on Philanthropy/Giving https://www.wsj.com/us-news/laurene-powell-jobs-beware-of-philanthropists-who-want-control-in-exc…

Super-resolution reconstruction of turbulent flows from a single Lagrangian trajectory
Hua-Lin Wu, Ao Xu, Heng-Dong Xi
https://arxiv.org/abs/2509.17109 https://

Super-resolution reconstruction of turbulent flows from a single Lagrangian trajectory
We studied the reconstruction of turbulent flow fields from trajectory data recorded by actively migrating Lagrangian agents. We propose a deep learning model, Track-to-Flow (T2F), which employs a Vision Transformer as an encoder to capture the spatiotemporal features of a single agent trajectory, and a convolutional neural network as the decoder to reconstruct the flow field. To enhance the physical consistency of the T2F model, we further incorporate a physics-informed loss function inspired …

On the Feasibility of Inter-Flow Service Degradation Detection
Balint Bicski, Adrian Pekar
https://arxiv.org/abs/2509.11140 https://arxiv.org/pdf/2509.1114…

On the Feasibility of Inter-Flow Service Degradation Detection
Hardware acceleration in modern networks creates monitoring blind spots by offloading flows to a non-observable state, hindering real-time service degradation (SD) detection. To address this, we propose and formalize a novel inter-flow correlation framework, built on the hypothesis that observable flows can act as environmental sensors for concurrent, non-observable flows. We conduct a comprehensive statistical analysis of this inter-flow landscape, revealing a fundamental trade-off: while the …

Simulation-based Inference of Massive Black Hole Binaries using Sequential Neural Likelihood
Iv\'an Mart\'in V\'ilchez, Carlos F. Sopuerta
https://arxiv.org/abs/2509.13842

Simulation-based Inference of Massive Black Hole Binaries using Sequential Neural Likelihood
We propose a machine learning-based approach for parameter estimation of Massive Black Hole Binaries (MBHBs), leveraging normalizing flows to approximate the likelihood function. By training these flows on simulated data, we can generate posterior samples via Markov Chain Monte Carlo with a relatively reduced computational cost. Our method enables iterative refinement of smaller models targeting specific MBHB events, with significantly fewer waveform template evaluations. However, dimensionalit…

Adapting Noise to Data: Generative Flows from 1D Processes
Jannis Chemseddine, Gregor Kornhardt, Richard Duong, Gabriele Steidl
https://arxiv.org/abs/2510.12636 https://

Adapting Noise to Data: Generative Flows from 1D Processes
We introduce a general framework for constructing generative models using one-dimensional noising processes. Beyond diffusion processes, we outline examples that demonstrate the flexibility of our approach. Motivated by this, we propose a novel framework in which the 1D processes themselves are learnable, achieved by parameterizing the noise distribution through quantile functions that adapt to the data. Our construction integrates seamlessly with standard objectives, including Flow Matching an…

Singular jump processes as generalized gradient flows
Jasper Hoeksema, Riccarda Rossi, Oliver Tse
https://arxiv.org/abs/2509.19138 https://arxiv.org/pdf/25…

FLOWING: Implicit Neural Flows for Structure-Preserving Morphing
Arthur Bizzi, Matias Grynberg, Vitor Matias, Daniel Perazzo, Jo\~ao Paulo Lima, Luiz Velho, Nuno Gon\c{c}alves, Jo\~ao Pereira, Guilherme Schardong, Tiago Novello
https://arxiv.org/abs/2510.09537

FLOWING: Implicit Neural Flows for Structure-Preserving Morphing
Morphing is a long-standing problem in vision and computer graphics, requiring a time-dependent warping for feature alignment and a blending for smooth interpolation. Recently, multilayer perceptrons (MLPs) have been explored as implicit neural representations (INRs) for modeling such deformations, due to their meshlessness and differentiability; however, extracting coherent and accurate morphings from standard MLPs typically relies on costly regularizations, which often lead to unstable traini…

There is a fascinating map on the website of the French transmission system operator RTE showing transmission network flows. I think it's updated hourly, so the movement is just an animation. Still cool!
https://analysesetdonnees.rte-france.com/reseaux/carteflux

Compression, Impact and Hot Rebound Flows from Coronal Rain Downflows
Jamal Wachira, Patrick Antolin
https://arxiv.org/abs/2509.11627 https://arxiv.org/pdf…

Compression, Impact and Hot Rebound Flows from Coronal Rain Downflows
Understanding the processes associated with coronal rain due to the thermal non-equilibrium (TNE) and thermal instability (TI) scenario can help us understand coronal heating. We aim to study the properties of a quiescent coronal rain event and its effect on the solar atmosphere. We utilise space-based data from the \textit{High-Resolution Imager in Extreme Ultraviolet} of Solar Orbiter, the \textit{Atmospheric Imaging Assembly} of the Solar Dynamics Observatory, and the Slit-Jaw Imager (SJI) f…

Compact representation of transonic airfoil buffet flows with observable-augmented machine learning
Kai Fukami, Yuta Iwatani, Soju Maejima, Hiroyuki Asada, Soshi Kawai
https://arxiv.org/abs/2509.17306 …

Compact representation of transonic airfoil buffet flows with observable-augmented machine learning
Transonic buffet presents time-dependent aerodynamic characteristics associated with shock, turbulent boundary layer, and their interactions. Despite strong nonlinearities and a large degree of freedom, there exists a dominant dynamic pattern of a buffet cycle, suggesting the low dimensionality of transonic buffet phenomena. This study seeks a low-dimensional representation of transonic airfoil buffet at a high Reynolds number with machine learning. Wall-modeled large-eddy simulations of flow o…

Cash-flows in the #AIBubble, in one neat diagram. Carole Cadwalladr has one question, "when will it pop". No answer yet, but the question is delicious. https://open.substack.com/pub/broligar

An Eulerian Perspective on Straight-Line Sampling
Panos Tsimpos, Youssef Marzouk
https://arxiv.org/abs/2510.11657 https://arxiv.org/pdf/2510.11657

An Eulerian Perspective on Straight-Line Sampling
We study dynamic measure transport for generative modeling: specifically, flows induced by stochastic processes that bridge a specified source and target distribution. The conditional expectation of the process' velocity defines an ODE whose flow map achieves the desired transport. We ask \emph{which processes produce straight-line flows} -- i.e., flows whose pointwise acceleration vanishes and thus are exactly integrable with a first-order method? We provide a concise PDE characterization of s…

CDFlow: Generative Gradient Flows for Configuration Space Distance Fields via Neural ODEs
Mengzhu Li, Yunyu Zhou, He Ying, F. Richard Yu
https://arxiv.org/abs/2509.13771 https:/…

CDFlow: Generative Gradient Flows for Configuration Space Distance Fields via Neural ODEs
Signed Distance Fields (SDFs) are a fundamental representation in robot motion planning. Their configuration-space counterpart, the Configuration Space Distance Field (CDF), directly encodes distances in joint space, offering a unified representation for optimization and control. However, existing CDF formulations face two major challenges in high-degree-of-freedom (DoF) robots: (1) they effectively return only a single nearest collision configuration, neglecting the multi-modal nature of minim…

Using white dwarf lensing to resolve accretion flows
Sophie L. Newman, Matthew J. Middleton, Adam McMaster
https://arxiv.org/abs/2509.10674 https://arxiv.o…

Using white dwarf lensing to resolve accretion flows
Microlensing is one of the most powerful tools for probing the nature of dark halo objects and the sources they lens. As our nearest massive galaxy, M31 provides a rich source population with many potential lenses in its halo crossing our field of view at any one time. In this paper we explore the probability that X-ray sources in M31 will be lensed by white dwarfs in M31's halo. We find an expected lensing rate of 2.6/year within the mean archival Swift XRT field-of-view, and 6.3/year for the …

With Apache NiFi, a multimodal data pipelining tool, you can assemble existing and/or custom Java & Python processors into a variety of flows. At Berlin Buzzwords 2025, Lester Martin discussed how a rich data pipeline can be constructed from Kafka, stored using the Apache Iceberg table format and consumed from Trino.
Watch the full session: https://youtu.be/2yH9PfiXb9Y?si=Xhi_xDMzLQOps8my
Berlin Buzzwords returns on 7-9 June 2026! Get 36% off with our Trust Us Ticket: https://tickets.plainschwarz.com/bbuzz26/c/8Hvk0ZvJA/

“They’ve put up windmills around the world and they’re generating electricity and cash flows, and those assets are worth money regardless of what Donald Trump says.”
What next for troubled Ørsted? - https://on.ft.com/4n8pc5N via @FT

Wavefunction Flows: Efficient Quantum Simulation of Continuous Flow Models
David Layden, Ryan Sweke, Vojt\v{e}ch Havl\'i\v{c}ek, Anirban Chowdhury, Kirill Neklyudov
https://arxiv.org/abs/2510.08462

Wavefunction Flows: Efficient Quantum Simulation of Continuous Flow Models
Flow models are a cornerstone of modern machine learning. They are generative models that progressively transform probability distributions according to learned dynamics. Specifically, they learn a continuous-time Markov process that efficiently maps samples from a simple source distribution into samples from a complex target distribution. We show that these models are naturally related to the Schrödinger equation, for an unusual Hamiltonian on continuous variables. Moreover, we prove that the…

Forward Euler for Wasserstein Gradient Flows: Breakdown and Regularization
Yewei Xu, Qin Li
https://arxiv.org/abs/2509.13260 https://arxiv.org/pdf/2509.132…

Forward Euler for Wasserstein Gradient Flows: Breakdown and Regularization
Wasserstein gradient flows have become a central tool for optimization problems over probability measures. A natural numerical approach is forward-Euler time discretization. We show, however, that even in the simple case where the energy functional is the Kullback-Leibler (KL) divergence against a smooth target density, forward-Euler can fail dramatically: the scheme does not converge to the gradient flow, despite the fact that the first variation $\nabla\frac{δF}{δρ}$ remains formally well …

Towards a unified turbulence model through multi-objective learning
Zhuo-Ran Liu, Hao-Chen Wang, Zhuo-Lin Zhao, Heng Xiao
https://arxiv.org/abs/2509.17189 https://

Towards a unified turbulence model through multi-objective learning
Turbulence is a central challenge in classical physics and a critical barrier to accurate flow prediction in climate, aerospace, and energy systems. Despite the widespread reliance on Reynolds-averaged Navier-Stokes (RANS) solvers in industrial simulations, existing turbulence models lack the generalizability to handle diverse regimes, such as separation, secondary flows, and free-shear flows, without manual tuning or switching. We propose a unified data-driven turbulence modeling framework bas…

Learning Informed Prior Distributions with Normalizing Flows for Bayesian Analysis
Hendrik Roch, Chun Shen
https://arxiv.org/abs/2509.14911 https://arxiv.o…

Learning Informed Prior Distributions with Normalizing Flows for Bayesian Analysis
We investigate the use of normalizing flow (NF) models as flexible priors in Bayesian inference with Markov Chain Monte Carlo (MCMC) sampling. Trained on posteriors from previous analyses, these models can be used as informative priors, capturing non-trivial distributions and correlations, in subsequent inference tasks. We compare different training strategies and loss functions, finding that training based on Kullback-Leibler (KL) divergence and unsupervised learning consistently yield the mos…

The National Weather Service is forecasting a major storm for Santa Barbara County expected to arrive Monday, October 13th. The following conditions are possible countywide:
Hail and lightning
Brief, heavy rainfall
Dangerous flash flooding
Flooding in low-lying areas and strong winds
Shallow debris flows for locations in and beneath recent wildfire burn areas including the Gifford Fire and Lake Fire.
Detailed weather forecasts are available at

Anomaly detection in network flows using unsupervised online machine learning
Alberto Miguel-Diez, Adri\'an Campazas-Vega, \'Angel Manuel Guerrero-Higueras, Claudia \'Alvarez-Aparicio, Vicente Matell\'an-Olivera
https://arxiv.org/abs/2509.01375

Anomaly detection in network flows using unsupervised online machine learning
Nowadays, the volume of network traffic continues to grow, along with the frequency and sophistication of attacks. This scenario highlights the need for solutions capable of continuously adapting, since network behavior is dynamic and changes over time. This work presents an anomaly detection model for network flows using unsupervised machine learning with online learning capabilities. This approach allows the system to dynamically learn the normal behavior of the network and detect deviations …

Nowhere-zero flows on signed supereulerian graphs
Chao Wen, Qiang Sun, Chao Zhang
https://arxiv.org/abs/2510.08192 https://arxiv.org/pdf/2510.08192

Nowhere-zero flows on signed supereulerian graphs
In 1983, Bouchet conjectured that every flow-admissible signed graph admits a nowhere-zero 6-flow. We verify this conjecture for the class of flow-admissible signed graphs possessing a spanning even Eulerian subgraph, which includes as a special case all signed graphs with a balanced Hamiltonian circuit. Furthermore, we show that this result is sharp by citing a known infinite family of signed graphs with a balanced Hamiltonian circuit that do not admit a nowhere-zero 5-flow. Our proof relies o…

Sigma model renormalisation group flows, singularities and some remarks on cosmology
Georgios Papadopoulos
https://arxiv.org/abs/2509.13092 https://arxiv.o…

Sigma model renormalisation group flows, singularities and some remarks on cosmology
We investigate the properties of the renormalisation group (RG) flow of two-dimensional sigma models with a generic metric coupling by utilising known results for the Ricci flow. We point out that on many occasions the RG flow develops singularities, due to strong coupling behaviour, before it reaches a UV or an IR fixed point. We illustrate our analysis with several examples. We give particular emphasis to type I singularities, where the length of the curvature of the sigma model target space …

Multi-robot Multi-source Localization in Complex Flows with Physics-Preserving Environment Models
Benjamin Shaffer, Victoria Edwards, Brooks Kinch, Nathaniel Trask, M. Ani Hsieh
https://arxiv.org/abs/2509.14228

Multi-robot Multi-source Localization in Complex Flows with Physics-Preserving Environment Models
Source localization in a complex flow poses a significant challenge for multi-robot teams tasked with localizing the source of chemical leaks or tracking the dispersion of an oil spill. The flow dynamics can be time-varying and chaotic, resulting in sporadic and intermittent sensor readings, and complex environmental geometries further complicate a team's ability to model and predict the dispersion. To accurately account for the physical processes that drive the dispersion dynamics, robots must…

Dynamical generation of macroscale magnetic fields and fast flows in a four-component astrophysical plasma
Usman Shazad, M. Iqbal
https://arxiv.org/abs/2509.11122 https://

Dynamical generation of macroscale magnetic fields and fast flows in a four-component astrophysical plasma
We explore the possibility of the generation or amplification of macroscale magnetic fields and flows in a four-component astrophysical dusty plasma composed of mobile massless electrons and positrons, inertial positive ions and negatively charged static dust particles. The investigation demonstrates that when microscopic turbulent ambient plasma energy is predominantly kinetic, a straight dynamo (DY) mechanism is feasible. Conversely, a unified reverse-dynamo/dynamo (RDY/DY) mechanism is possi…

Stick-Breaking Mixture Normalizing Flows with Component-Wise Tail Adaptation for Variational Inference
Seungsu Han, Juyoung Hwang, Won Chang
https://arxiv.org/abs/2510.07965 htt…

Stick-Breaking Mixture Normalizing Flows with Component-Wise Tail Adaptation for Variational Inference
Normalizing flows with a Gaussian base provide a computationally efficient way to approximate posterior distributions in Bayesian inference, but they often struggle to capture complex posteriors with multimodality and heavy tails. We propose a stick-breaking mixture base with component-wise tail adaptation (StiCTAF) for posterior approximation. The method first learns a flexible mixture base to mitigate the mode-seeking bias of reverse KL divergence through a weighted average of component-wise …

Thin-film flows of granular suspensions on a solid surface
Alice Pelosse, Elisabeth Guazzelli, Matthieu Roch\'e
https://arxiv.org/abs/2510.11127 https://

Thin-film flows of granular suspensions on a solid surface
This review article examines the complex dynamics of thin-film flows of granular suspensions spreading over rigid solid substrates with free air interfaces. Such systems feature an involved coupling of the free-surface dynamics with the flow and microstructure of the suspension. In particular, we develop two canonical thin-film situations: drop spreading and dip-coating. In drop spreading, confinement of the particulate phase near the advancing contact line alters both the spreading rate and th…

A family of three maximally symmetric boost-invariant flows in relativistic hydrodynamics
Sa\v{s}o Grozdanov
https://arxiv.org/abs/2510.10769 https://arxiv…

A family of three maximally symmetric boost-invariant flows in relativistic hydrodynamics
I discuss the constructions of boost-invariant dissipative conformal hydrodynamic flows by elaborating on the geometric procedure by Gubser and Yarom, which starts from a static, maximally symmetric flow on dS$_3\times\mathbb{R}$. Three foliations of dS$_3$ preserve three-dimensional non-Abelian isometry groups, namely, the flat ISO(2)-invariant, the spherical (closed) SO(3)-invariant, and the hyperbolic (open) SO(2,1)-invariant slicings. I show that the fluids that preserve these symmetries, a…

Constraints on Radial Gas Flows in the Milky Way Disk Revealed by Large Stellar Age Catalogs
James W. Johnson
https://arxiv.org/abs/2510.05223 https://arxi…

Constraints on Radial Gas Flows in the Milky Way Disk Revealed by Large Stellar Age Catalogs
Disk galaxies like the Milky Way are expected to experience gas flows carrying matter toward their centers. This paper investigates the role of these radial gas flows in models of Galactic chemical evolution (GCE). We follow five different parameterizations of the Galactocentric radial velocity, $v_{r,g}$, of the interstellar medium (ISM). Relative to the $v_{r,g}=0$ limit, all models predict stellar metallicity to decline less significantly with age in the outer disk and more significantly in …

Data-driven transient growth analysis
Yin Wang, Xuerui Mao
https://arxiv.org/abs/2509.18974 https://arxiv.org/pdf/2509.18974…

Data-driven transient growth analysis
Transient growth analysis has been extensively studied in asymptotically stable flows to identify their short-term amplification of perturbations. Generally, in global transient growth analyses, matrix-free methods are adopted, requiring the construction of adjoint equations, either in the discrete or continuous form. This paper introduces a data-driven algorithm that circumvents the adjoint equations by extracting the optimal initial perturbation and its energy growth over a specified time hor…

iPhone Air hands-on: very thin with rounded edges reminiscent of previous iPhone designs and a camera "plateau" that flows smoothly into the back of the phone (The Verge)
https://www.theverge.com/tech/773244/apple-iphone-air-hands-on-photos-awe-dr…

iPhone Air hands-on
Here’s our hands-on impressions of Apple’s new thin and light iPhone that it announced at its iPhone 17 “Awe dropping” launch event.

Wasserstein convergence rates in the invariance principle for nonuniformly hyperbolic flows
Ian Melbourne, Zhe Wang
https://arxiv.org/abs/2509.07657 https://

Wasserstein convergence rates in the invariance principle for nonuniformly hyperbolic flows
We obtain $q$-Wasserstein convergence rates in the invariance principle for nonuniformly hyperbolic flows, where $q\ge1$ depends on the degree of nonuniformity. Utilizing a martingale-coboundary decomposition for nonuniformly expanding semiflows, we extend techniques from the discrete-time setting to the continuous-time case. Our results apply to uniformly hyperbolic (Axiom A) flows, nonuniformly hyperbolic flows that can be modelled by suspensions over Young towers with exponential tails (such…

On traveling wave solutions of water-wave equations in curved annular domains
Liang Li, Quan Wang
https://arxiv.org/abs/2509.15881 https://arxiv.org/pdf/25…

On traveling wave solutions of water-wave equations in curved annular domains
This paper presents a pioneering investigation into the existence of traveling wave solutions for the two-dimensional Euler equations with constant vorticity in a curved annular domain, where gravity acts radially inward. This configuration is highly relevant to astrophysical and equatorial oceanic flows, such as those found in planetary rings and equatorial currents. Unlike traditional water wave models that assume flat beds and vertical gravity, our study more accurately captures the centripe…

Heyo this is one of the #photos that I shared recently in my blog (or ON my blog? 🤔).
Anyways, this scene showed up during our walk near #ebersberg. This scene was one of the very unexpected ones during our walk. - I am really happy that I saw it while we were walking.
It's currentl…

Uniformly High Order Discontinuous Galerkin Gas Kinetic Scheme for Compressible flows
Mengqing Zhang, Shiyi Li, Dongmi Luo, Jianxian Qiu, Yibing Chen
https://arxiv.org/abs/2510.10656

Uniformly High Order Discontinuous Galerkin Gas Kinetic Scheme for Compressible flows
In this paper, a uniformly high-order discontinuous Galerkin gas kinetic scheme (DG-HGKS) is proposed to solve the Euler equations of compressible flows. The new scheme is an extension of the one-stage compact and efficient high-order GKS (CEHGKS, Li et al. , 2021. J. Comput. Phys. 447, 110661) in the finite volume framework. The main ideas of the new scheme consist of two parts. Firstly, starting from a fully discrete DG formulation, the numerical fluxes and volume integrals are expanded in ti…

Digital Twin-based Cooperative Autonomous Driving in Smart Intersections: A Multi-Agent Reinforcement Learning Approach
Taoyuan Yu, Kui Wang, Zongdian Li, Tao Yu, Kei Sakaguchi, Walid Saad
https://arxiv.org/abs/2509.15099

Digital Twin-based Cooperative Autonomous Driving in Smart Intersections: A Multi-Agent Reinforcement Learning Approach
Unsignalized intersections pose safety and efficiency challenges due to complex traffic flows and blind spots. In this paper, a digital twin (DT)-based cooperative driving system with roadside unit (RSU)-centric architecture is proposed for enhancing safety and efficiency at unsignalized intersections. The system leverages comprehensive bird-eye-view (BEV) perception to eliminate blind spots and employs a hybrid reinforcement learning (RL) framework combining offline pre-training with online fi…

Analysis of the Rarefied Flow at Micro-Step using a DeepONet Surrogate Model with a Physics-Guided Zonal Loss Function
Ehsan Roohi, Amirmehran Mahdavi
https://arxiv.org/abs/2509.17254

Analysis of the Rarefied Flow at Micro-Step using a DeepONet Surrogate Model with a Physics-Guided Zonal Loss Function
The Direct Simulation Monte Carlo (DSMC) method remains the gold standard for simulating rarefied gas flows but is prohibitively expensive for parametric and many-query applications. To address this limitation, we introduce a Deep Operator Network (DeepONet) surrogate framework featuring an innovative, physics-guided zonal loss function. The zonal loss prioritizes physical fidelity in critical flow regions over global error metrics, leading to predictions with greater engineering relevance. It …

Floating-Body Hydrodynamic Neural Networks
Tianshuo Zhang, Wenzhe Zhai, Rui Yann, Jia Gao, He Cao, Xianglei Xing
https://arxiv.org/abs/2509.13783 https://a…

Floating-Body Hydrodynamic Neural Networks
Fluid-structure interaction is common in engineering and natural systems, where floating-body motion is governed by added mass, drag, and background flows. Modeling these dissipative dynamics is difficult: black-box neural models regress state derivatives with limited interpretability and unstable long-horizon predictions. We propose Floating-Body Hydrodynamic Neural Networks (FHNN), a physics-structured framework that predicts interpretable hydrodynamic parameters such as directional added mas…

Observables of boundary RG flows from string field theory
Jaroslav Scheinpflug, Martin Schnabl, Jakub Vo\v{s}mera
https://arxiv.org/abs/2510.07155 https://…

Observables of boundary RG flows from string field theory
We present simple explicit formulae for the change of the $g$-function, boundary state, boundary spectrum and structure constants between the endpoints of short boundary RG flows at next-to-leading order. The formulae are derived using open string field theory and tested on integrable RG flows between conformal boundary states in unitary Virasoro minimal models.

A zero-dimensional global conservation model to determine non-ideal nozzle conditions for gas injections
N. Diepstraten, L. M. T. Somers, J. A. van Oijen
https://arxiv.org/abs/2509.17614

A zero-dimensional global conservation model to determine non-ideal nozzle conditions for gas injections
To reduce computation times of simulations involving gas fueled internal combustion engines (ICEs), a model is developed that determines non-ideal nozzle exit conditions to spare expensive simulations of internal injector flows. The model, to which we will refer as the Global Conservation Model (GCM), computes nozzle exit values based on reservoir conditions, and a discharge and momentum coefficient. These coefficients can be obtained via common flow bench experiments or a validated numerical s…

Symbolic dynamics for non-uniformly hyperbolic flows in high dimension
Yuri Lima, Juan Carlos Mongez, Jo\~ao Paulo Nascimento
https://arxiv.org/abs/2509.09050 https://

Symbolic dynamics for non-uniformly hyperbolic flows in high dimension
We construct symbolic dynamics for flows with positive speed in any dimension: for each $χ>0$, we code a set that has full measure for every invariant probability measure which is $χ$--hyperbolic. In particular, the coded set contains all hyperbolic periodic orbits with Lyapunov exponents outside of $[-χ,χ]$. This extends the recent work of Buzzi, Crovisier, and Lima for three dimensional flows with positive speed. As an application, we code homoclinic classes of measures by suspensions of …

Crosslisted article(s) found for physics.flu-dyn. https://arxiv.org/list/physics.flu-dyn/new
[1/1]:
- Long-wave instability of periodic shear flows for the 2D Navier-Stokes equations
Maria Colombo, Michele Dolce, Riccardo Montalto, Paolo Ventura

TopoSizing: An LLM-aided Framework of Topology-based Understanding and Sizing for AMS Circuits
Ziming Wei, Zichen Kong, Yuan Wang, David Z. Pan, Xiyuan Tang
https://arxiv.org/abs/2509.14169

TopoSizing: An LLM-aided Framework of Topology-based Understanding and Sizing for AMS Circuits
Analog and mixed-signal circuit design remains challenging due to the shortage of high-quality data and the difficulty of embedding domain knowledge into automated flows. Traditional black-box optimization achieves sampling efficiency but lacks circuit understanding, which often causes evaluations to be wasted in low-value regions of the design space. In contrast, learning-based methods embed structural knowledge but are case-specific and costly to retrain. Recent attempts with large language m…

de Sitter versus Anti de Sitter flows and the (super)gravity landscape: Part II
Elias Kiritsis, Sergio Morales-Tejera, Christopher Rosen
https://arxiv.org/abs/2510.12373 https:/…

de Sitter versus Anti de Sitter flows and the (super)gravity landscape: Part II
Generic solutions are studied in Einstein-scalar gravity in an ansatz that can interpolate between de Sitter and Anti-de Sitter regimes. The scalar potential is arbitrary. All solutions are determined by their end-points in the scalar field space. All such end-points are classified. This provides a complete classification and characterization of the full space of regular solutions. It is shown that there are no regular (Centaur) solutions that interpolate between an AdS boundary and a dS interi…

$L^2$ normal velocity implies strong solution for graphical Brakke flows
Kotaro Motegi
https://arxiv.org/abs/2510.11377 https://arxiv.org/pdf/2510.11377

$L^2$ normal velocity implies strong solution for graphical Brakke flows
We prove that if a one-parameter family of varifolds has an $L^2$ normal velocity $v$ in the sense of Brakke, and if the family is represented as the graph of a continuous function $f$ with continuous spatial derivative $\nabla f$, then $f$ has weak derivatives $\partial_t f, \nabla^2 f \in L^2$, and $v$ coincides with the usual normal velocity of the graph. Moreover, by combining this result with parabolic regularity theory, we show that graphical Brakke flows with forcing term in $L^{p,q}$ an…

Structure-Preserving High-Order Methods for the Compressible Euler Equations in Potential Temperature Formulation for Atmospheric Flows
Marco Artiano, Oswald Knoth, Peter Spichtinger, Hendrik Ranocha
https://arxiv.org/abs/2509.10311

Structure-Preserving High-Order Methods for the Compressible Euler Equations in Potential Temperature Formulation for Atmospheric Flows
We develop structure-preserving numerical methods for the compressible Euler equations, employing potential temperature as a prognostic variable.We construct three numerical fluxes designed to ensure the conservation of entropy and total energy within the discontinuous Galerkin framework on general curvilinear meshes.Furthermore, we introduce a generalization for the kinetic energy preservation property and total energy conservation in the presence of a gravitational potential term. To this end…

Extreme vertical drafts as drivers of Lagrangian dispersion in stably stratified turbulent flows
Christian Reartes, Pablo D. Mininni, Raffaele Marino
https://arxiv.org/abs/2509.12962

Extreme vertical drafts as drivers of Lagrangian dispersion in stably stratified turbulent flows
The dispersion of Lagrangian particle pairs is a fundamental process in turbulence, with implications for mixing, transport, and the statistical properties of particles in geophysical and environmental flows. While classical theories describe pair dispersion through scaling laws related to energy cascades, extreme events in turbulent flows can significantly alter these dynamics. This is especially important in stratified flows, where intermittency manifests itself also as strong updrafts and do…

Conjugacies of geodesic flows in affine cylinders and tori
Xavier Buff (IMT), Guillaume Tahar (BIMSA)
https://arxiv.org/abs/2509.06391 https://arxiv.org/pd…

Conjugacies of geodesic flows in affine cylinders and tori
Affine cylinders (genus zero surfaces with two singularities) and affine tori (genus one surfaces without singularities) are among the simplest examples of surfaces endowed with a complex affine structure. Their geodesic flows are particularly tractable. In this article, we provide explicit necessary and sufficient conditions under which the geodesic flows on such surfaces are conjugate, in the topological and in the holomorphic category.

Integrability in Three-Dimensional Gravity: Eigenfunction-Forced KdV Flows
Hamed Adami, Anousheh Latifi
https://arxiv.org/abs/2510.10519 https://arxiv.org/…

Integrability in Three-Dimensional Gravity: Eigenfunction-Forced KdV Flows
We uncover a direct connection between three-dimensional gravity with chiral boundary conditions and a class of forced integrable systems. Starting from the Chern-Simons formulation, we derive consistent boundary conditions on a non-compact spatial slice, leading to boundary dynamics described by the potential modified KdV hierarchy. The dynamics reduce to a forced KdV equation, where the forcing term is determined self-consistently by the eigenfunctions of the associated Schrödinger operator.…

Transport Based Mean Flows for Generative Modeling
Elaheh Akbari, Ping He, Ahmadreza Moradipari, Yikun Bai, Soheil Kolouri
https://arxiv.org/abs/2509.22592 https://

Transport Based Mean Flows for Generative Modeling
Flow-matching generative models have emerged as a powerful paradigm for continuous data generation, achieving state-of-the-art results across domains such as images, 3D shapes, and point clouds. Despite their success, these models suffer from slow inference due to the requirement of numerous sequential sampling steps. Recent work has sought to accelerate inference by reducing the number of sampling steps. In particular, Mean Flows offer a one-step generation approach that delivers substantial s…

On Kanai's conjecture for frame flows over negatively curved manifolds
Louis-Brahim Beaufort
https://arxiv.org/abs/2509.09500 https://arxiv.org/pdf/250…

On Kanai's conjecture for frame flows over negatively curved manifolds
Let $M$ be a closed, negatively curved Riemannian manifold of dimension $n \neq 4, 8$ with strictly $1/4$-pinched sectional curvature. We prove, that if the frame flow is ergodic and the sum of its unstable and stable bundles together with its flow direction is $\mathcal{C}^2$, then $M$ is homothetic to a real hyperbolic manifold. This extends to higher dimensions a previous result of Kanai in dimension 3. The proof generalises to isometric extensions of geodesic flows to a principal bundle $P$…

Two-dimensional steady supersonic ramp flows of Bethe-Zel'dovich-Thompson fluids
Geng Lai
https://arxiv.org/abs/2509.08212 https://arxiv.org/pdf/2509.0…

Two-dimensional steady supersonic ramp flows of Bethe-Zel'dovich-Thompson fluids
Two-dimensional steady supersonic ramp flows are important and well-studied flow patterns in aerodynamics. Vimercati, Kluwick and Guardone [J. Fluid Mech., 885 (2018) 445--468] constructed various self-similar composite wave solutions to the supersonic flow of Bethe-Zel'dovich-Thompson (BZT) fluids past compressible and rarefactive ramps. We study the stabilities of the self-similar fan-shock-fan and shock-fan-shock composite waves constructed by Vimercati et al. in that paper. %In order to stu…

kh2d-solver: A Python Library for Idealized Two-Dimensional Incompressible Kelvin-Helmholtz Instability
Sandy H. S. Herho, Nurjanna J. Trilaksono, Faiz R. Fajary, Gandhi Napitupulu, Iwan P. Anwar, Faruq Khadami, Dasapta E. Irawan
https://arxiv.org/abs/2509.16080

kh2d-solver: A Python Library for Idealized Two-Dimensional Incompressible Kelvin-Helmholtz Instability
We present an open-source Python library for simulating two-dimensional incompressible Kelvin-Helmholtz instabilities in stratified shear flows. The solver employs a fractional-step projection method with spectral Poisson solution via Fast Sine Transform, achieving second-order spatial accuracy. Implementation leverages NumPy, SciPy, and Numba JIT compilation for efficient computation. Four canonical test cases explore Reynolds numbers 1000--5000 and Richardson numbers 0.1--0.3: classical shear…

Anisotropic critical points from holography
Dimitrios Giataganas, Umut G\"ursoy, Claire Moran, Juan F. Pedraza, David Rodr\'iguez Fern\'andez
https://arxiv.org/abs/2509.15021

Anisotropic critical points from holography
We present a comprehensive analysis of generic 5-dimensional Einstein-Maxwell-Dilaton-Axion (EMDA) holographic theories with exponential couplings. We find and classify exact, analytic, anisotropic solutions, both zero-temperature vacua and finite-temperature black brane backgrounds, with anisotropy sourced by scalar axions, magnetic fields, and charge densities, that can be interpreted as IR fixed points of renormalisation-group flows from UV-conformal fixed points. The resulting backgrounds f…

Gradient Flows of Interfacial Energies: Curvature Agents and Incompressibility
Keith Promislow, Truong Vu, Brian Wetton
https://arxiv.org/abs/2509.07380 https://

Gradient Flows of Interfacial Energies: Curvature Agents and Incompressibility
We present a framework for the gradient flow of sharp-interface surface energies that couple to embedded curvature active agents. We use a penalty method to develop families of locally incompressible gradient flows that couple interface stretching or compression to local flux of interfacial mass. We establish the convergence of the penalty method to an incompressible flow both formally for a broad family of surface energies and rigorously for a more narrow class of surface energies. We present …

Two irrationally elliptic closed orbits of Reeb flows on the boundary of star-shaped domain in $\mathbb{R}^{2n}$
Xiaorui Li, Hui Liu, Wei Wang
https://arxiv.org/abs/2510.06597 h…

Two irrationally elliptic closed orbits of Reeb flows on the boundary of star-shaped domain in $\mathbb{R}^{2n}$
There are two long-standing conjectures in Hamiltonian dynamics concerning Reeb flows on the boundaries of star-shaped domains in $\mathbb{R}^{2n}$ ($n \geq 2$). One conjecture states that such a Reeb flow possesses either $n$ or infinitely many prime closed orbits; the other states that all the closed Reeb orbits are irrationally elliptic when the domain is convex and the flow possesses finitely many prime closed orbits. In this paper, we prove that for dynamically convex Reeb flow on the boun…

Multiscale super-resolution reconstruction of fluid flows with deep neural networks
Gengchao Yang, Renyu Luo, Qinghe Yao, Peiji Wang, Jinxiu Zhang
https://arxiv.org/abs/2509.14721

Multiscale super-resolution reconstruction of fluid flows with deep neural networks
We present a novel multiscale super-resolution framework (SRLBM) that applies deep learning directly to the mesoscopic density distribution functions of the lattice Boltzmann method for high-fidelity flow reconstruction. Two neural network architectures, a standard convolutional neural network (CNN) and a deeper residual dense network (RDN), are trained to upscale distribution functions from coarse grids by factors of 2, 4 and 8, and then recover velocity, pressure, and vorticity from a single …

Massless S-matrix Bootstraps and RG Flows
Changrim Ahn
https://arxiv.org/abs/2509.20740 https://arxiv.org/pdf/2509.20740

Massless S-matrix Bootstraps and RG Flows
We find complete solutions of S-matrix bootstrap equations for the scatterings of massless particles in (1+1) dimensions with A_n symmetries. We show that only three types (minimal, diagonal, and saturated cases) of these S-matrices can generate RG flows that lead to UV-complete theories, and other RG flows predicted in [11] are inconsistent with the bootstrap equations. Using these S-matrices, we derived the TBA equations and corresponding Y-systems that generate the RG flows between the IR an…

Capillary $L_p$ Minkowski Flows
Jinrong Hu, Yingxiang Hu, Mohammad N. Ivaki
https://arxiv.org/abs/2509.06110 https://arxiv.org/pdf/2509.06110

Capillary $L_p$ Minkowski Flows
We study the long-time existence and asymptotic behavior of a class of anisotropic capillary Gauss curvature flows. As an application, we provide a flow approach to the existence of smooth solutions to the capillary even $L_p$ Minkowski problem in the Euclidean half-space for all $p \in (-n-1, \infty)$ and capillary $L_p$ Minkowski problem for $p > n+1$.

Understanding the effect of wall elasticity in turbulent channel flows
M. Koseki, M. S. Aswathy, M. E. Rosti
https://arxiv.org/abs/2509.11142 https://arxiv…

Understanding the effect of wall elasticity in turbulent channel flows
This study compares turbulent channel flows over elastic walls with those over rough walls, to explore the role of the dynamic change of shape of the wall on turbulence. The comparison is made meaningful by generating rough walls from instantaneous configurations of the elastic cases. The aim of this comparison is to individually understand the role of fluid-structure interaction effects and the role of wall shape/undulations in determining the overall physics of flow near elastic walls. With a…

Model of deep zonal flows in giant planets
Laura K. Currie, Chris A. Jones
https://arxiv.org/abs/2510.12236 https://arxiv.org/pdf/2510.12236

Model of deep zonal flows in giant planets
A mechanism by which the surface zonal flows of giant planets can be gradually attenuated with depth is explored. The zonal flow is driven by an imposed forcing in a thin layer near the surface. A meridional circulation is set up, analogous to the Ferrel-like cells observed in Jupiter's atmosphere. Acting on a stably stratified thin surface layer, the meridional flow induces a horizontal temperature anomaly which leads to a gradual reduction of the zonal winds with depth, governed by the therma…

A model for transport of soluble surfactants in two-phase flows
Suhas S. Jain
https://arxiv.org/abs/2510.10857 https://arxiv.org/pdf/2510.10857

A model for transport of soluble surfactants in two-phase flows
In this work, we propose a novel transport model for soluble surfactants in two-phase flows. In a two-phase flow, the soluble surfactants can adsorb/desorb from/into the bulk of any of the phases to the interface and can modify the interface properties. This results in sharp gradients in the surfactant concentration on the interface and also between the two phases in the bulk when there is selective adsorption/desorption, presenting a serious challenge for the numerical simulations. To overco…

Lagrangian Stability Analysis Technique for Fluid Flows
Vilas J. Shinde
https://arxiv.org/abs/2509.10316 https://arxiv.org/pdf/2509.10316

Lagrangian Stability Analysis Technique for Fluid Flows
Flow transition from a stable to unstable states and eventually to turbulence is a classical fluid mechanics phenomenon with a strong practical relevance. Conventional hydrodynamic stability deals with perturbation dynamics on a steady baseflow, typically in Eulerian reference frame. Common modal techniques, e.g., linear stability theory, involve linearization of governing flow equations and flow/geometrical simplifications, which can be tedious and restrictive. This paper presents a perturbati…

Effect of Stokes number on erosion on Pelton buckets for sediment-laden flows
Aron Dagur Beck, Elena Vagnoni
https://arxiv.org/abs/2510.08036 https://arxiv…

Effect of Stokes number on erosion on Pelton buckets for sediment-laden flows
With increased glacial melting and the need to maintain sediment continuity for ecosystem health, sediment-laden flows through hydropower plants are becoming increasingly problematic, particularly due to erosion on runner blades and buckets. A widely used mitigation strategy is the use of filters to protect Pelton turbines. However, these filters lead to rapid sediment accumulation in reservoirs, which must be drained frequently to maintain storage capacity. The high cost of such drainage opera…

Active Control of Turbulent Airfoil Flows Using Adjoint-based Deep Learning
Xuemin Liu, Tom Hickling, Jonathan F. MacArt
https://arxiv.org/abs/2510.07106 https://

Active Control of Turbulent Airfoil Flows Using Adjoint-based Deep Learning
We train active neural-network flow controllers using a deep learning PDE augmentation method to optimize lift-to-drag ratios in turbulent airfoil flows at Reynolds number $5\times10^4$ and Mach number 0.4. Direct numerical simulation and large eddy simulation are employed to model compressible, unconfined flow over two- and three-dimensional semi-infinite NACA 0012 airfoils at angles of attack $α= 5^\circ$, $10^\circ$, and $15^\circ$. Control actions, implemented through a blowing/suction jet…

Experimental study of turbulent mixing in a T-shaped mixer
Huixin Li, Mohammad Mehdi Zamani Asl, Bastian B\"auerlein, Kerstin Avila, Duo Xu, Marc Avila
https://arxiv.org/abs/2509.10264

Experimental study of turbulent mixing in a T-shaped mixer
One of the most widespread canonical devices for fluid mixing is the T-shaped mixer, in which two opposing miscible liquid streams meet at a junction and then mix along a main channel. Laminar steady and time-periodic flows in T-shaped mixers have been thoroughly studied, but turbulent flows have received much less scrutiny despite their prevalence in applications. We here introduce a novel experimental setup with a hydraulic diameter of four centimetres that enables the optical study of turbul…

Stability of vortex lattices in rotating flows
Juli\'an Amette Estrada, Alexandros Alexakis, Marc E. Brachet, Pablo D. Mininni
https://arxiv.org/abs/2510.06374 https://

Stability of vortex lattices in rotating flows
Vortex lattices -- highly ordered arrays of vortices -- are known to arise in quantum systems such as type II superconductors and Bose-Einstein condensates. More recently, similar arrangements have been reported in classical rotating fluids. However, the mechanisms governing their formation, stability, and eventual breakdown remain poorly understood. We explore the dynamical stability of vortex lattices in three-dimensional rotating flows. To that end we construct controlled initial conditions …