Tootfinder

KoopMotion: Learning Almost Divergence Free Koopman Flow Fields for Motion Planning
Alice Kate Li, Thales C Silva, Victoria Edwards, Vijay Kumar, M. Ani Hsieh
https://arxiv.org/abs/2509.09074

KoopMotion: Learning Almost Divergence Free Koopman Flow Fields for Motion Planning
In this work, we propose a novel flow field-based motion planning method that drives a robot from any initial state to a desired reference trajectory such that it converges to the trajectory's end point. Despite demonstrated efficacy in using Koopman operator theory for modeling dynamical systems, Koopman does not inherently enforce convergence to desired trajectories nor to specified goals -- a requirement when learning from demonstrations (LfD). We present KoopMotion which represents motion f…

Block encoding the 3D heterogeneous Poisson equation with application to fracture flow
Austin Pechan, John Golden, Daniel O'Malley
https://arxiv.org/abs/2508.07125 https://

Block encoding the 3D heterogeneous Poisson equation with application to fracture flow
Quantum linear system (QLS) algorithms offer the potential to solve large-scale linear systems exponentially faster than classical methods. However, applying QLS algorithms to real-world problems remains challenging due to issues such as state preparation, data loading, and efficient information extraction. In this work, we study the feasibility of applying QLS algorithms to solve discretized three-dimensional heterogeneous Poisson equations, with specific examples relating to groundwater flow …

Well-posedness of stationary 2D and 3D convective Brinkman-Forchheimer extended Darcy Hemivariational inequalities
Manil T. Mohan
https://arxiv.org/abs/2509.09335 https://

Well-posedness of stationary 2D and 3D convective Brinkman-Forchheimer extended Darcy Hemivariational inequalities
This study addresses the well-posedness of a hemivariational inequality derived from the convective Brinkman-Forchheimer extended Darcy (CBFeD) model in both two and three dimensions. The CBFeD model describes the behavior of incompressible viscous fluid flow through a porous medium, incorporating the effects of convection, damping, and nonlinear resistance. The mathematical framework captures steady-state flow conditions under a no-slip boundary assumption, with a non-monotone boundary conditi…

Study on the equation-of-state with light clusters and hypernuclei
Elena Bratkovskaya, J\"org Aichelin
https://arxiv.org/abs/2509.09061 https://arxiv.…

Study on the equation-of-state with light clusters and hypernuclei
Heavy-ion collision experiments offer a unique opportunity to explore the early stages of the Universe by creating matter under extreme conditions of high temperature and baryon density. The properties of such matter are governed by the equation-of-state (EoS), which remains a central focus of investigation from both experimental and theoretical perspectives. Flow harmonics are among the most sensitive observables for probing the EoS, as they strongly reflect the underlying interactions and deg…

Identifying efficient routes to laminarization: an optimization approach
Jake Buzhardt, Michael D. Graham
https://arxiv.org/abs/2508.08519 https://arxiv.or…

Identifying efficient routes to laminarization: an optimization approach
The inherently nonlinear and chaotic nature of turbulent flows poses a major challenge for designing control strategies to maintain or induce low-drag laminar states. In this work, we study the concept of the minimal seed for relaminarization - the smallest perturbation of a turbulent state that triggers a direct transition to laminar flow without a chaotic transient. We formulate the identification of this optimal perturbation as a fully nonlinear optimization problem and develop a numerical f…

Gemma O‘Brien kicking off day two of #smashingconf Freiburg with an inspiring talk about her beautiful and powerful lettering and art work – and a super interesting interview about flow state. 👏

Optimizing information flow in Gene Regulatory Networks: a geometric perspective
Miguel \'Angel Garc\'ia-Ariza, Alessandro Bravetti, Pablo Padilla, J Roberto Romero-Arias
https://arxiv.org/abs/2509.08167

Optimizing information flow in Gene Regulatory Networks: a geometric perspective
The dynamics of gene regulatory networks is governed by the interaction between deterministic biochemical reactions and molecular noise. To understand how gene regulatory networks process information during cell state transitions, we study stochastic dynamics derived from a Boolean network model via its representation on the parameter space of Gaussian distributions, equipped with the Fisher information metric. This reformulation reveals that the trajectories of optimal information transfer are…

Disorder-induced stress-flow misalignment in soft glassy materials revealed using multi-directional shear
Fr\'ed\'eric Blanc, Guillaume Ovarlez, Adam Trigui, Kirsten Martens, Romain Mari
https://arxiv.org/abs/2508.05379

Disorder-induced stress-flow misalignment in soft glassy materials revealed using multi-directional shear
Controlling the mechanical response of soft glassy materials, such as emulsions, foams, and colloidal suspensions, is key for many industrial processes. While their steady-state flow behavior is reasonably well understood, their response to complex flow histories, as encountered in operations like pumping or mixing, remains poorly known. Using a custom multi-axis shear apparatus that enables arbitrary changes in flow direction, we investigate how shear history influences the mechanical behavior…

Admission Control for Inelastic Traffic on a Link Shared by Deadline-Driven Elastic Traffic
Patrick Kreidl
https://arxiv.org/abs/2509.08135 https://arxiv.o…

Admission Control for Inelastic Traffic on a Link Shared by Deadline-Driven Elastic Traffic
Consider a (logical) link between two distributed data centers with available bandwidth designated for both deadline-driven elastic traffic, such as for scheduled synchronization services, and profitable inelastic traffic, such as for real-time streaming services. Admission control in this setting is cast as a stochastic shortest path problem, with state space derived from (discretization of) the elastic flow's size/deadline and action space corresponding to alternative subsets of admitted inel…

Flux-flow in multiband FeSe$_x$Te$_{1-x}$ explored by microwave magnetotransport
A. Magalotti, A. Alimenti, V. Braccini, P. Manfrinetti, E. Silva, K. Torokhtii, N. Pompeo
https://arxiv.org/abs/2509.04912

Flux-flow in multiband FeSe$_x$Te$_{1-x}$ explored by microwave magnetotransport
We measure the flux-flow resistivity in FeSe$_x$Te$_{1-x}$ epitaxial films using a microwave, dual-frequency technique. The flux-flow resistivity allows to open a window on the microscopic electronic state of quasiparticles. We obtain that the field-dependence of flux-flow is typical for multiband superconductors. Once this is assessed, we are able to extract the temperature dependence of the orbital upper critical field and of the normalised vortex core quasiparticle scattering time. Our data …

Motion of Elastic Thin Films by Evaporation-Condensation in the Dewetting Regime
M. S. Indulekha
https://arxiv.org/abs/2508.07562 https://arxiv.org/pdf/250…

Motion of Elastic Thin Films by Evaporation-Condensation in the Dewetting Regime
In this work, we show the short-time existence of solutions of the evolution equations that represent the solid state dewetting of thin films through evaporation-condensation as a two dimensional sharp interface variational model. The evolution law is established as the $L^2$ gradient flow of surface energies in the presence of epitaxial strain. The main novelty is the presence of moving contact lines when the film formation is governed by the evaporation-condensation method.

Summing Real Time Feynman Paths of Lattice Polaron with Matrix Product States
Qi Gao, Yuan Wan
https://arxiv.org/abs/2507.07648 https://

Summing Real Time Feynman Paths of Lattice Polaron with Matrix Product States
We study numerically the real time dynamics of lattice polarons by combining the Feynman path integral and the matrix product state (MPS) approach. By constructing and solving a flow equation, we show that the integrand, viewed as a multivariable function of polaron world line parameters, can be compressed as a low bond dimension MPS, thereby allowing for efficient evaluation of various dynamical observables. We establish the effectiveness of our method by benchmarking the calculated polaron sp…

Spherical Accretion on a Schwarzschild-MOG Black Hole
Ayyesha K. Ahmed, M Z A Moughal
https://arxiv.org/abs/2509.05783 https://arxiv.org/pdf/2509.05783

Spherical Accretion on a Schwarzschild-MOG Black Hole
In this paper we have examined spherical accretion onto Schwarzschild MOG Black Holes within the framework of Modified Gravity. Using isothermal test fluids, we analyze the behavior of the flow near the critical (sonic) point for various values of the equation of state parameter $k$. Depending on the fluid type, the flow exhibits either subsonic or supersonic behavior, with ultra-stiff and ultra-relativistic fluids allowing both regimes, while radiation and sub-relativistic fluids show more res…

Upon arrival in Australia and some other countries passengers are sprayed with stuff to either disinfect them or kill insects.
And on California highways, upon entering the state, there are agricultural inspection stations to try to block bad bugs and stuff from getting into the state. (There is reason to believe that this system was established as a pretense in order to reduce the flow of "Okies" during the Dust Bowl era.)
Well, now that the anti-vax disease has struc…

An MLIR-based Compilation Framework for Control Flow Management on CGRAs
Yuxuan Wang, Cristian Tirelli, Giovanni Ansaloni, Laura Pozzi, David Atienza
https://arxiv.org/abs/2508.02167

An MLIR-based Compilation Framework for Control Flow Management on CGRAs
Coarse Grained Reconfigurable Arrays (CGRAs) present both high flexibility and efficiency, making them well-suited for the acceleration of intensive workloads. Nevertheless, a key barrier towards their widespread adoption is posed by CGRA compilation, which must cope with a multi-dimensional space spanning both the spatial and the temporal domains. Indeed, state-of-the-art compilers are limited in scope as they mostly deal with the data flow of applications, while having little or no support fo…

Attraction of the core and the cohesion flow
Dylan Laplace Mermoud
https://arxiv.org/abs/2507.02918 https://arxiv.org/pdf/2507.02918

Attraction of the core and the cohesion flow
We adopt a continuous-time dynamical system approach to study the evolution of the state of a game driven by the willingness to reduce the total dissatisfaction of the coalitions about their payment. Inspired by the work of Grabisch and Sudhölter about core stability, we define a vector field on the set of preimputations from which is defined, for any preimputation, a cohesion curve describing the evolution of the state. We prove that for each preimputation, there exists a unique cohesion curv…

OGF: An Online Gradient Flow Method for Optimizing the Statistical Steady-State Time Averages of Unsteady Turbulent Flows
Tom Hickling, Jonathan F. MacArt, Justin Sirignano, Den Waidmann
https://arxiv.org/abs/2507.05149

OGF: An Online Gradient Flow Method for Optimizing the Statistical Steady-State Time Averages of Unsteady Turbulent Flows
Turbulent flows are chaotic and unsteady, but their statistical distribution converges to a statistical steady state. Engineering quantities of interest typically take the form of time-average statistics such as $ \frac{1}{t} \int_0^t f ( u(x,τ; θ) ) dτ\overset{t \rightarrow \infty}{\rightarrow} F(x; θ)$, where $u(x,t; θ)$ are solutions of the Navier--Stokes equations with parameters $θ$. Optimizing over $F(x; θ)$ has many engineering applications including geometric optimization, flow c…

Distribution estimation via Flow Matching with Lipschitz guarantees
Lea Kunkel
https://arxiv.org/abs/2509.02337 https://arxiv.org/pdf/2509.02337

Distribution estimation via Flow Matching with Lipschitz guarantees
Flow Matching, a promising approach in generative modeling, has recently gained popularity. Relying on ordinary differential equations, it offers a simple and flexible alternative to diffusion models, which are currently the state-of-the-art. Despite its empirical success, the mathematical understanding of its statistical power so far is very limited. This is largely due to the sensitivity of theoretical bounds to the Lipschitz constant of the vector field which drives the ODE. In this work, we…

Align Your Flow: Scaling Continuous-Time Flow Map Distillation
Amirmojtaba Sabour, Sanja Fidler, Karsten Kreis
https://arxiv.org/abs/2506.14603 https://

Align Your Flow: Scaling Continuous-Time Flow Map Distillation
Diffusion- and flow-based models have emerged as state-of-the-art generative modeling approaches, but they require many sampling steps. Consistency models can distill these models into efficient one-step generators; however, unlike flow- and diffusion-based methods, their performance inevitably degrades when increasing the number of steps, which we show both analytically and empirically. Flow maps generalize these approaches by connecting any two noise levels in a single step and remain effecti…

So tired of this bullshit...
Ya’know what ALL OF THOSE THINGS require? More D's in Congress. Whinging about people working towards that immediate goal is obnoxious and harmful.
https://pdx.social/@portlandy/114971733036422173

Stability-Constrained AC Optimal Power Flow -- A Gaussian Process-Based Approach
Vincenzo Di Vito, Kaarthik Sundar, Ferdinando Fioretto, Deepjyoti Deka
https://arxiv.org/abs/2507.23094

Stability-Constrained AC Optimal Power Flow -- A Gaussian Process-Based Approach
The Alternating Current Optimal Power Flow (ACOPF) problem is a core task in power system operations, aimed at determining cost-effective generation dispatch while satisfying physical and operational constraints. However, conventional ACOPF formulations rely on steady-state models and neglect the dynamic behavior of generators, which can lead to operating points that are economically optimal but dynamically unstable. This paper proposes a novel, data-driven approach to incorporate generator dyn…

Newton-Flow Particle Filters based on Generalized Cram\'er Distance
Uwe D. Hanebeck
https://arxiv.org/abs/2509.00182 https://arxiv.org/pdf/2509.00182…

Newton-Flow Particle Filters based on Generalized Cramér Distance
We propose a recursive particle filter for high-dimensional problems that inherently never degenerates. The state estimate is represented by deterministic low-discrepancy particle sets. We focus on the measurement update step, where a likelihood function is used for representing the measurement and its uncertainty. This likelihood is progressively introduced into the filtering procedure by homotopy continuation over an artificial time. A generalized Cramér distance between particle sets is der…

Prediction of acoustic field in 1-D uniform duct with varying mean flow and temperature using neural networks
D. Veerababu, Prasanta K. Ghosh
https://arxiv.org/abs/2507.22370 ht…

Prediction of acoustic field in 1-D uniform duct with varying mean flow and temperature using neural networks
Neural networks constrained by the physical laws emerged as an alternate numerical tool. In this paper, the governing equation that represents the propagation of sound inside a one-dimensional duct carrying a heterogeneous medium is derived. The problem is converted into an unconstrained optimization problem and solved using neural networks. Both the acoustic state variables: acoustic pressure and particle velocity are predicted and validated with the traditional Runge-Kutta solver. The effect …

Monte-Carlo radiation hydrodynamic simulations of line-driven disc winds: relaxing the isothermal approximation
Amin Mosallanezhad, Christian Knigge, Nicolas Scepi, James H. Matthews, Knox S. Long, Stuart A. Sim, Austen Wallis
https://arxiv.org/abs/2507.05085

Monte-Carlo radiation hydrodynamic simulations of line-driven disc winds: relaxing the isothermal approximation
Disc winds play a crucial role in many accreting astrophysical systems across all scales. In accreting white dwarfs (AWDs) and active galactic nuclei (AGN), radiation pressure on spectral lines is a promising wind-driving mechanism. However, the efficiency of line driving is extremely sensitive to the ionization state of the flow, making it difficult to construct a reliable physical picture of these winds. Recently, we presented the first radiation-hydrodynamic (RHD) simulations for AWDs that i…

Coexistence and Extinction in Flow-Kick Systems: An invasion growth rate approach
Sebastian J. Schreiber
https://arxiv.org/abs/2507.02157 https://

Coexistence and Extinction in Flow-Kick Systems: An invasion growth rate approach
Populations experience a complex interplay of continuous and discrete processes: continuous growth and interactions are punctuated by discrete reproduction events, dispersal, and external disturbances. These dynamics can be modeled by impulsive or flow-kick systems, where continuous flows alternate with instantaneous discrete changes. To study species persistence in these systems, an invasion growth rate theory is developed for flow-kick models with state-dependent timing of kicks and auxiliary…

Machine-learning based particle-flow algorithm in CMS
Farouk Mokhtar
https://arxiv.org/abs/2508.20541 https://arxiv.org/pdf/2508.20541

Machine-learning based particle-flow algorithm in CMS
The particle-flow (PF) algorithm provides a global event description by reconstructing final-state particles and is central to event reconstruction in CMS. Recently, end-to-end machine learning (ML) approaches have been proposed to directly optimize physical quantities of interest and to leverage heterogeneous computing architectures. One such approach, machine-learned particle flow (MLPF), uses a transformer model to infer particles directly from tracks and clusters in a single pass. We presen…

A level-set based finite difference method for the ground state Bose-Einstein condensates in smooth bounded domains
Hwi Lee, Yingjie Liu
https://arxiv.org/abs/2509.00668 https:/…

A level-set based finite difference method for the ground state Bose-Einstein condensates in smooth bounded domains
We present a level-set based finite difference method to calculate the ground states of Bose Einstein condensates in domains with curved boundaries. Our method draws on the variational and level set approaches, benefiting from both of their long-standing success. More specifically, we use the normalized gradient flow, where the spatial discretization is based on the simple Cartesian grid with fictitious values in the outer vicinity of the domains. We develop a PDE-based extension technique that…

Stochastic systems with Bose-Hubbard interactions: Effects of bias on particles on a 1D lattice and random comb
Swastik Majumder, Mustansir Barma
https://arxiv.org/abs/2508.03344

Stochastic systems with Bose-Hubbard interactions: Effects of bias on particles on a 1D lattice and random comb
Driven non-equilibrium lattice models have wide-ranging applications in contexts such as mass transport, traffic flow, and transport in biological systems. In this work, we investigate the steady-state properties of a one-dimensional lattice system that allows multiple particle occupancy on each site. The particles undergo stochastic nearest-neighbor jumps influenced by both a directional bias and on-site repulsive interactions. With periodic boundary conditions, we observe a non-monotonic depe…

Two-dimensional Carreau law for a quasi-newtonian fluid flow through a thin domain with a slightly rough boundary
Mar\'ia Anguiano, Francisco J. Su\'arez-Grau
https://arxiv.org/abs/2508.04785

Two-dimensional Carreau law for a quasi-newtonian fluid flow through a thin domain with a slightly rough boundary
This study investigates the asymptotic behavior of the steady-state quasi-Newtonian Stokesflow with viscosity given by the Carreau law within a thin domain, focusing on the effects of a slightly rough boundary of the domain. Employing asymptotic techniques with respect to the domain's thickness, we rigorously derive the effective nonlinear two-dimensional Reynolds model describing the fluid flow. The mathematical analysis is based on deriving the sharp a priori estimates and proving the compact…

Efficient many-jet event generation with Flow Matching
Enrico Bothmann, Timo Jan{\ss}en, Max Knobbe, Bernhard Schmitzer, Fabian Sinz
https://arxiv.org/abs/2506.18987

Efficient many-jet event generation with Flow Matching
We apply for the first time the Flow Matching method to the problem of phase-space sampling for event generation in high-energy collider physics. By training the model to remap the random numbers used to generate the momenta and helicities of the scattering matrix elements as implemented in the portable partonic event generator Pepper, we find substantial efficiency improvements in the studied processes. We focus our study on the highest final-state multiplicities in Drell--Yan and top--antitop…

Machine Learning Assisted Parameter-Space Searches for Lensed Gravitational Waves
Giulia Campailla, Marco Raveri, Wayne Hu, Jose Mar\'ia Ezquiaga
https://arxiv.org/abs/2509.06901

Machine Learning Assisted Parameter-Space Searches for Lensed Gravitational Waves
When a gravitational wave encounters a massive object along the line of sight, repeated copies of the original signal may be produced due to gravitational lensing. In this paper, we develop a series of new machine-learning based statistical methods to identify promising strong lensing candidates in gravitational wave catalogs. We employ state-of-the-art normalizing flow generative models to perform statistical calculations on the posterior distributions of gravitational wave events that would o…

Flow-dependent tagging of $^{214}$Pb decays in the LZ dark matter detector
J. Aalbers, D. S. Akerib, A. K. Al Musalhi, F. Alder, C. S. Amarasinghe, A. Ames, T. J. Anderson, N. Angelides, H. M. Ara\'ujo, J. E. Armstrong, M. Arthurs, A. Baker, S. Balashov, J. Bang, J. W. Bargemann, E. E. Barillier, K. Beattie, T. Benson, A. Bhatti, T. P. Biesiadzinski, H. J. Birch, E. Bishop, G. M. Blockinger, B. Boxer, C. A. J. Brew, P. Br\'as, S. Burdin, M. C. Carmona-Benitez, M. Carter, A. Cha…

Flow-dependent tagging of $^{214}$Pb decays in the LZ dark matter detector
The LUX-ZEPLIN (LZ) experiment is searching for dark matter interactions in a liquid xenon time projection chamber (LXe-TPC). This article demonstrates how control of the flow state in the LXe-TPC enables the identification of pairs of sequential alpha-decays, which are used to map fluid flow and ion drift in the liquid target. The resulting transport model is used to tag $^{214}$Pb beta-decays, a leading background to dark matter signals in LZ. Temporally evolving volume selections, at a cost …

Quantifying Flow State Dynamics: A Prefrontal Cortex EEG-Based Model Validation Study. Unveiling the Prefrontal Cortex's Role in Flow State Experience: An Empirical EEG Analysis
Gianluca Rosso, Raffaella Ricci, Lorenzo Pia, Giovanni Rebaudo, Michele Guindani, Alberto Marocchino, Giorgio De Pieri, Andrea Filippo Rosso
https://

Quantifying Flow State Dynamics: A Prefrontal Cortex EEG-Based Model Validation Study. Unveiling the Prefrontal Cortex's Role in Flow State Experience: An Empirical EEG Analysis
This article aims to explore the optimization of mental performance through the analysis of metrics associated with the psychological state known as flow. Several clinical studies have shown a correlation between the mental state of flow (characterized by deep and relaxed concentration and high psychophysical efficiency) and brain activity measured through electroencephalography (EEG). This study confirms such a correlation, focusing in particular on the sports field, where the flow state tends…

I think the Vibecoding reddit has accidentally stumbled on the best description of vibecoding:
It's "roleplay for guys [it is always guys] who want to feel like hackers without doing the hard part".
(Source: https://www.reddit.com/r/vibecoding/com…

Nonlinear analysis of causality for heat flow in heavy-ion collisions: constraints from equation of state
Victor Roy
https://arxiv.org/abs/2508.03265 https://

Nonlinear analysis of causality for heat flow in heavy-ion collisions: constraints from equation of state
We explore the causal parameter space of the Mueller-Israel-Stewart second-order theory for heat-conducting fluids in nonlinear regimes for one-dimensional fluid flow. We show that this parameter space is highly constrained and particularly sensitive to the equation of state and second-order transport coefficients. Through numerical analysis of the characteristic equations, we identify regions of strong hyperbolicity, weak hyperbolicity, and non-hyperbolicity, mapping the boundaries of causalit…

Envisioning the Distance Ladder in the Era of the Habitable Worlds Observatory
Gagandeep Anand, Meredith Durbin, Rachael Beaton, Joseph Jensen, Adam Riess
https://arxiv.org/abs/2507.02056

Envisioning the Distance Ladder in the Era of the Habitable Worlds Observatory
The current state-of-the-art cosmic distance ladder requires three rungs--geometric distances, primary indicators, and Type Ia Supernovae--to achieve a 1% measurement of the Hubble constant $H_0$. The Habitable Worlds Observatory will have the sensitivity and resolution to reduce this to a two-step measurement, eliminating the third rung entirely and reaching into the Hubble flow with stellar distance indicators such as Cepheid variables and the tip of the red giant branch alone. We discuss the…

Analytical Framework for Evaluating Traffic Capacity Impacts of Electric Vehicles' Regenerative Braking Dynamics
Yuhang Wang, Md. Zidan Shahriar, Hao Zhou
https://arxiv.org/abs/2508.01938

Analytical Framework for Evaluating Traffic Capacity Impacts of Electric Vehicles' Regenerative Braking Dynamics
Regenerative braking (RB) significantly influences electric vehicle (EV) car-following (CF) dynamics, yet traditional traffic-flow models rarely capture these effects. We introduce a comprehensive empirical dataset comprising 197.5 hours of driving data from 25 drivers across eight EV models to systematically investigate regen-induced CF behaviors. Two primary CF patterns emerge: (i) steady-state scenarios where EVs use regenerative braking and subsequently re-accelerate to equilibrium speeds w…

is AI real life
is it just fantasy
caught up in the hype
no escape from reality
#ai #llm #vibecoding

Velocity optimization of self-equilibrated obstacles in a two-dimensional viscous flow
Gilles A. Francfort, Alessandro Giacomini, Scott Weady
https://arxiv.org/abs/2508.05481 ht…

Velocity optimization of self-equilibrated obstacles in a two-dimensional viscous flow
An obstacle is immersed in an externally driven 2D Stokes or Navier-Stokes fluid. We study the self-equilibration conditions for that obstacle under steady state assumptions on the flow. We then seek to optimize the translational and/or angular velocity of the obstacle by varying its shape. To allow general variations, we must consider a very large class of obstacles for which the notion of trace is meaningless. This forces us to revisit the notion of self-equilibration for both Stokes and Navi…

A novel parallelizable convergence accelerating method: Pointwise Frequency Damping
Zikun Liu, Xukun Wang, Yilang Liu, Weiwei Zhang
https://arxiv.org/abs/2507.04873

A novel parallelizable convergence accelerating method: Pointwise Frequency Damping
This paper proposes a novel class of data-driven acceleration methods for steady-state flow field solvers. The core innovation lies in predicting and assigning the asymptotic limit value for each parameter during iterations based on its own historical data, rather than processing and assigning the entire flow field at once. This approach fundamentally guarantees identical results between serial and parallel computations. Subsequently, a formula for representing the asymptotic limit based on his…

To encourage a mental flow state, I listen to 'zone music'. Whenever I have to concentrate, I turn this music on.
The songs below are also a Pomodoro 25min so it's break time when the song ends.
✅ INFO: Maintaining focus w/ “Music to Code By”
https://kurtsh.com/2015/05/05/i…

INFO: Maintaining focus w/ “Music to Code By”
Totally off topic, but it relates to a few posts I made 5-10 years ago.  INFOMANIA. ALIVE & WELL. One of my interests is the study of “Infomania”, a syndrome described by Hewlett Packard R…

Dynamical symmetry breaking in Georgi-Glashow chiral-gauge theories
Hao-Lin Li, \'Alvaro Pastor-Guti\'errez, Shahram Vatani, Ling-Xiao Xu
https://arxiv.org/abs/2507.21208

Dynamical symmetry breaking in Georgi-Glashow chiral-gauge theories
We investigate dynamical symmetry breaking in a class of chiral gauge theories containing the Georgi-Glashow model. These theories feature a gauge sector and two fermion species that transform in the two-index antisymmetric and antifundamental representations with different multiplicities. Using the effective action formalism and the functional renormalization group, we derive the flow of four-fermion interactions that encode their resonant structure and information about bound-state formation.…

Inserting Planar-Measured Qubits into MBQC Patterns while Preserving Flow
Miriam Backens (Universit\'e de Lorraine, CNRS, Inria, LORIA, F-54000 Nancy, France), Thomas Perez (Inria, Palaiseau, France, LIX, CNRS, Ecole Polytechnique, Institut Polytechnique de Paris, Palaiseau, France, CPHT, CNRS, Ecole Polytechnique, Institut Polytechnique de Paris, Palaiseau, France)

Inserting Planar-Measured Qubits into MBQC Patterns while Preserving Flow
In the one-way model of measurement-based quantum computation (MBQC), computation proceeds via single-qubit measurements on a resource state. Flow conditions ensure that the overall computation is deterministic in a suitable sense, and are required for efficient translation into quantum circuits. Procedures that rewrite MBQC patterns -- e.g. for optimisation, or adapting to hardware constraints -- thus need to preserve the existence of flow. Most previous work has focused on rewrites that reduc…

Flexibility-Conditioned Protein Structure Design with Flow Matching
Vsevolod Viliuga, Leif Seute, Nicolas Wolf, Simon Wagner, Arne Elofsson, Jan St\"uhmer, Frauke Gr\"ater
https://arxiv.org/abs/2508.18211

Flexibility-Conditioned Protein Structure Design with Flow Matching
Recent advances in geometric deep learning and generative modeling have enabled the design of novel proteins with a wide range of desired properties. However, current state-of-the-art approaches are typically restricted to generating proteins with only static target properties, such as motifs and symmetries. In this work, we take a step towards overcoming this limitation by proposing a framework to condition structure generation on flexibility, which is crucial for key functionalities such as c…

Flow Matching-Based Generative Modeling for Efficient and Scalable Data Assimilation
Taos Transue, Bohan Chen, So Takao, Bao Wang
https://arxiv.org/abs/2508.13313 https://

Flow Matching-Based Generative Modeling for Efficient and Scalable Data Assimilation
Data assimilation (DA) is the problem of sequentially estimating the state of a dynamical system from noisy observations. Recent advances in generative modeling have inspired new approaches to DA in high-dimensional nonlinear settings, especially the ensemble score filter (EnSF). However, these come at a significant computational burden due to slow sampling. In this paper, we introduce a new filtering framework based on flow matching (FM) -- called the ensemble flow filter (EnFF) -- to accelera…

Global existence for full compressible Navier-Stokes equations around the Couette flow with a temperature gradient in an infinite channel
Tuowei Chen, Qiangchang Ju
https://arxiv.org/abs/2507.04088

Global existence for full compressible Navier-Stokes equations around the Couette flow with a temperature gradient in an infinite channel
This paper is concerned with the two-dimensional full compressible Navier-Stokes equations between two infinite parallel isothermal walls, where the upper wall is moving with a horizontal velocity, while the lower wall is stationary, and there allows a temperature difference between the two walls. It is shown that if the initial state is close to the Couette flow with a temperature gradient, then the global strong solutions exist, provided that the Reynolds and Mach numbers are low and the temp…

High-order fully well-balanced numerical methods for one-dimensional blood flow with discontinuous properties, friction and gravity
Ernesto Pimentel-Garc\'ia, Lucas O. M\"uller, Carlos Par\'es
https://arxiv.org/abs/2508.20638

High-order fully well-balanced numerical methods for one-dimensional blood flow with discontinuous properties, friction and gravity
We present well-balanced, high-order, semi-discrete numerical schemes for one-dimensional blood flow models with discontinuous mechanical properties and algebraic source terms representing friction and gravity. While discontinuities in model parameters are handled using the Generalized Hydrostatic Reconstruction, the presence of algebraic source terms implies that steady state solutions cannot always be computed analytically. In fact, steady states are defined by an ordinary differential equati…

Metrics for Assessing Changes in Flow-based Networks
Micha{\l} Rzepka, Piotr Cho{\l}da
https://arxiv.org/abs/2508.09573 https://arxiv.org/pdf/2508.09573

Metrics for Assessing Changes in Flow-based Networks
This paper addresses the challenges of evaluating network performance in the presence of fluctuating traffic patterns, with a particular focus on the impact of peak data rates on network resources. We introduce a set of metrics to quantify network load and measure the impact of individual flows on the overall network state. By analyzing link and flow data through percentile values and sample distributions, and introducing the Utilization Score metric, the research provides insights into resourc…

DIJE: Dense Image Jacobian Estimation for Robust Robotic Self-Recognition and Visual Servoing
Yasunori Toshimitsu, Kento Kawaharazuka, Akihiro Miki, Kei Okada, Masayuki Inaba
https://arxiv.org/abs/2507.00446

DIJE: Dense Image Jacobian Estimation for Robust Robotic Self-Recognition and Visual Servoing
For robots to move in the real world, they must first correctly understand the state of its own body and the tools that it holds. In this research, we propose DIJE, an algorithm to estimate the image Jacobian for every pixel. It is based on an optical flow calculation and a simplified Kalman Filter that can be efficiently run on the whole image in real time. It does not rely on markers nor knowledge of the robotic structure. We use the DIJE in a self-recognition process which can robustly disti…

GLOW: A Unified Particle Flow Transformer
Dmitrii Kobylianskii, Samuel Van Stroud, Kwok Yiu Wong, Max Hart, Etienne Dreyer, Eilam Gross, Gabriel Facini, Tim Scanlon
https://arxiv.org/abs/2508.20092

GLOW: A Unified Particle Flow Transformer
We present GLOW, a transformer-based particle flow model that combines incidence matrix supervision from HGPflow with a MaskFormer architecture. Evaluated on CLIC detector simulations, GLOW achieves state-of-the-art performance and, together with prior work, demonstrates that a single unified transformer architecture can effectively address diverse reconstruction tasks in particle physics.

Synchronization driven acoustics: The nonlinear scattering of a self-oscillating meta-atom
Alexander K. Stoychev, Xinxin Guo, Ulrich Kuhl, Nicolas Noiray
https://arxiv.org/abs/2508.14819

Synchronization driven acoustics: The nonlinear scattering of a self-oscillating meta-atom
In this study we demonstrate a self-oscillating acoustic meta-atom functioning as an amplifying transistor, where a steady external flow serves as a control signal to switch between reflective (off-state) and transmissive (on-state) regimes. In the on-state, an acoustic limit cycle synchronizes with incident sound waves. This process governs the energy transfer across the device, with a transmission bandwidth dictated by the synchronization region in parameter space (Arnold tongue). Our experim…

Extraction of ground-state nuclear deformations from ultra-relativistic heavy-ion collisions: Nuclear structure physics context
J. Dobaczewski, A. Gade, K. Godbey, R. V. F. Janssens, W. Nazarewicz
https://arxiv.org/abs/2507.05208

Extraction of ground-state nuclear deformations from ultra-relativistic heavy-ion collisions: Nuclear structure physics context
The collective-flow-assisted nuclear shape-imaging method in ultra-relativistic heavy-ion collisions has recently been used to characterize nuclear collective states. In this paper, we assess the foundations of the shape-imaging technique employed in these studies. We conclude that, on the whole, the discussion regarding low-energy nuclear physics is confusing and the suggested impact on nuclear structure research is overstated. Conversely, efforts to incorporate existing knowledge on nuclear s…

$\textit{BMAD}$-Circumbinary Magnetically Arrested Disks around Stellar or Black Hole Binaries: Hot Accretion Flows, Disk Properties, and Angular Momentum Transfer
Hai-Yang Wang, Elias R. Most, Philip F. Hopkins
https://arxiv.org/abs/2508.16855

$\textit{BMAD}$-Circumbinary Magnetically Arrested Disks around Stellar or Black Hole Binaries: Hot Accretion Flows, Disk Properties, and Angular Momentum Transfer
Binary systems surrounded by a circumbinary accretion flow can be subject to strong magnetic fields, potentially altering the character of the accretion flow itself, the evolution of the orbital dynamics, and outflow properties from the system. Here we focus on a regime where magnetic fields become so strong that the outer circumbinary flow becomes magnetically arrested, establishing a (circum)binary magnetically arrested disk ($\textit{BMAD}$) state. Such flows feature quasi-periodic magnetic …

Differences in Neurovascular Coupling in Patients with Major Depressive Disorder: Evidence from Simultaneous Resting-State EEG-fNIRS
Feng Yan, Xiaobin Wang, Yao Zhao, Shuyi Yang, Zhiren Wang
https://arxiv.org/abs/2506.11634

Differences in Neurovascular Coupling in Patients with Major Depressive Disorder: Evidence from Simultaneous Resting-State EEG-fNIRS
Neurovascular coupling (NVC) refers to the process by which local neural activity, through energy consumption, induces changes in regional cerebral blood flow to meet the metabolic demands of neurons. Event-related studies have shown that the hemodynamic response typically lags behind neural activation by 4-6 seconds. However, little is known about how NVC is altered in patients with major depressive disorder (MDD) and throughout the recovery process. In this study, we employed simultaneous res…

Channel flows of deformable nematics
Ioannis Hadjifrangiskou, Sumesh P. Thampi, Julia M. Yeomans
https://arxiv.org/abs/2508.19013 https://arxiv.org/pdf/250…

Channel flows of deformable nematics
We describe channel flows in a continuum model of deformable nematic particles. In a simple shear flow, deformability leads to a nonlinear coupling of strain rate and vorticity, and results in shape oscillations or flow alignment. The final steady state can depend on initial conditions, and we explain this behaviour by considering a phase space representation of the dynamics. In Poiseuille flow, particle deformability and nematic elasticity induce banding, where particles near the walls are ali…

Spiral renormalization group flow and universal entanglement spectrum of the non-Hermitian 5-state Potts model
Vic Vander Linden, Boris De Vos, Kevin Vervoort, Frank Verstraete, Atsushi Ueda
https://arxiv.org/abs/2507.14732

Spiral renormalization group flow and universal entanglement spectrum of the non-Hermitian 5-state Potts model
The quantum $5$-state Potts model is known to possess a perturbative description using complex conformal field theory (CCFT), the analytic continuation of ``theory space" to a complex plane. To study the corresponding complex fixed point on the lattice, the model must be deformed by an additional non-Hermitian term due to its complex coefficient $λ$. Although the variational principle breaks down in this case, we demonstrate that tensor network algorithms are still capable of simulating these …

Origami slope gaps and the Hall distribution
Taylor McAdam, Xiaoxing Yu
https://arxiv.org/abs/2508.16186 https://arxiv.org/pdf/2508.16186

Origami slope gaps and the Hall distribution
In this paper we review the theory of slope gap distributions of translation surfaces and summarize the state-of-the-art for calculating slope gap distributions of Veech surfaces. We then derive the slope gap distribution of a particular 10-tile origami by considering the origami's return times to a Poincaré section under the horocycle flow on the moduli space associated with the origami. We show that the resulting distribution is not a sum of scaled Hall distributions, unlike all previously p…

SplitMeanFlow: Interval Splitting Consistency in Few-Step Generative Modeling
Yi Guo, Wei Wang, Zhihang Yuan, Rong Cao, Kuan Chen, Zhengyang Chen, Yuanyuan Huo, Yang Zhang, Yuping Wang, Shouda Liu, Yuxuan Wang
https://arxiv.org/abs/2507.16884

SplitMeanFlow: Interval Splitting Consistency in Few-Step Generative Modeling
Generative models like Flow Matching have achieved state-of-the-art performance but are often hindered by a computationally expensive iterative sampling process. To address this, recent work has focused on few-step or one-step generation by learning the average velocity field, which directly maps noise to data. MeanFlow, a leading method in this area, learns this field by enforcing a differential identity that connects the average and instantaneous velocities. In this work, we argue that this d…

Wow. Maria's still got it.
▶️ Maria Sharapova Finds Flow State While Eating Spicy Wings | Hot Ones
#tennis

Impact of porous media heterogeneity on convective mixing in a Rayleigh-B\'enard instability
Rima Benhammadi, Juan J. Hidalgo
https://arxiv.org/abs/2508.04342 https://

Impact of porous media heterogeneity on convective mixing in a Rayleigh-Bénard instability
This work studies the effect of the heterogeneity of a porous medium on convective mixing. We consider a system where a Rayleigh-Bénard instability is triggered by a temperature difference between the top and bottom boundaries. Heterogeneity is represented by multi-Gaussian log-normally distributed permeability fields. We explore the effect of the Rayleigh number, the variance and correlation length of the log-permeability field on the fingering patterns, heat flux, mixing state and flow struc…

Optimal Control of ODE Car-Following Models: Applications to Mixed-Autonomy Platoon Control via Coupled Autonomous Vehicles
Arwa Alanqary, Alexandre M. Bayen, Xiaoqian Gong, Anish Gollakota, Alexander Keimer, Ashish Pandian
https://arxiv.org/abs/2508.19417

Optimal Control of ODE Car-Following Models: Applications to Mixed-Autonomy Platoon Control via Coupled Autonomous Vehicles
In this paper, we study the optimal control of a mixed-autonomy platoon driving on a single lane to smooth traffic flow. The platoon consists of autonomous vehicles, whose acceleration is controlled, and human-driven vehicles, whose behavior is described using a microscopic car-following model. We formulate the optimal control problem where the dynamics of the platoon are describing through a system of non-linear ODEs, with explicit constraints on both the state and the control variables. Theor…

Phase Transition in Non-isentropic Compressible Immiscible Two-Phase Flow with van der Waals Equation of State
Yazhou Chen, Yi Peng, Xiaoding Shi, Xiaoping Wang
https://arxiv.org/abs/2506.20955

Phase Transition in Non-isentropic Compressible Immiscible Two-Phase Flow with van der Waals Equation of State
This study establishes the global well-posedness of the compressible non-isentropic Navier-Stokes/Allen-Cahn system governed by the van der Waals equation of state $p(ρ,θ)=- aρ^2+\frac{Rθρ}{1-bρ}$ and degenerate thermal conductivity $κ(θ)=\tildeκθ^β$, where $p$, $ρ$ and $θ$ are the pressure, the density and the temperature of the flow respectively, and $a,b,R,\tildeκ$ are positive constants related to the physical properties of the flow. Navier-Stokes/Allen-Cahn system models immi…

Switching topological states via uniaxial strain in 2D materials
Joshua J. Sanchez, Raagya Aurora, Daniel Bennett, Daniel T. Larson, Efthimios Kaxiras, Riccardo Comin
https://arxiv.org/abs/2509.03854

Switching topological states via uniaxial strain in 2D materials
In topological materials, dissipationless edge currents are protected against local defect scattering by the bulk inverted band structure and band gap. We propose that large uniaxial strain can effectively switch a 2D Chern insulator to a topologically trivial state. Further, we suggest that the boundary between strained and unstrained regions of a sample can act as a new edge for dissipationless current flow. Using density functional theory (DFT) calculations we demonstrate the strain-tunabili…

Information dynamics, natural computing and Maxwell's demon in two skyrmions system
Yoshishige Suzuki, Hiroki Mori, Soma Miki, Kota Emoto, Ryo Ishikawa, Eiiti Tamura, Hikaru Nomura, Minori Goto
https://arxiv.org/abs/2506.12881

Information dynamics, natural computing and Maxwell's demon in two skyrmions system
The probabilistic information flow and natural computational capability of a system with two magnetic skyrmions at room temperature have been experimentally evaluated. Based on this evaluation, an all-solid-state built-in Maxwell's demon operating at room temperature is also proposed. Probabilistic behavior has gained attention for its potential to enable unconventional computing paradigms. However, information propagation and computation in such systems are more complex than in conventional co…

Steady-state extensional viscosity of wormlike micellar solutions via dissipative particle dynamics simulations
Yusuke Koide, Takato Ishida, Takashi Uneyama, Yuichi Masubuchi
https://arxiv.org/abs/2507.11923

Steady-state extensional viscosity of wormlike micellar solutions via dissipative particle dynamics simulations
We investigate the steady-state extensional viscosity of wormlike micellar solutions using dissipative particle dynamics simulations. As the extension rate increases, the steady-state extensional viscosity initially increases and subsequently decreases after reaching a maximum, as observed in experiments. We reveal that this nonmonotonic behavior arises from the competition between micellar stretching and scission under uniaxial extensional flow. We further propose a relation that connects the …

Persistent spin currents in superconducting altermagnets
Kyle Monkman, Joan Weng, Niclas Heinsdorf, Alberto Nocera, Marcel Franz
https://arxiv.org/abs/2507.22139 https://…

Persistent spin currents in superconducting altermagnets
Superconductors are famously capable of supporting persistent electrical currents, that is, currents that flow without any measurable decay as long as the material is kept in the superconducting state. We introduce here a class of materials -- superconducting altermagnets -- that can both generate and carry persistent {\em spin} currents. This includes spin-polarized electrical supercurrent as well as pure spin supercurrent that facilitates spin transport in the absence of any charge transport.…

Testing hydrodynamic response to initial-state geometry in Pb $d^\uparrow$ collisions
Heikki M\"antysaari, Bj\"orn Schenke, Chun Shen, Wenbin Zhao
https://arxiv.org/abs/2509.00511

Testing hydrodynamic response to initial-state geometry in Pb+$d^\uparrow$ collisions
Deuterons with different polarization states have distinct shapes for their wavefunctions. This offers a unique opportunity to experimentally control the initial-state collision geometry with the polarization of the light-ion targets in relativistic heavy-ion experiments. We study the charged hadron elliptic flow coefficients with respect to the polarization angle of deuterons in Pb + polarized deuteron collisions using a hydrodynamics + hadronic transport model. Hydrodynamic response to initia…

Algorithmic Approaches to Enhance Safety in Autonomous Vehicles: Minimizing Lane Changes and Merging
Seyed Moein Abtahi, Akramul Azim
https://arxiv.org/abs/2506.15026

Algorithmic Approaches to Enhance Safety in Autonomous Vehicles: Minimizing Lane Changes and Merging
The rapid advancements in autonomous vehicle (AV) technology promise enhanced safety and operational efficiency. However, frequent lane changes and merging maneuvers continue to pose significant safety risks and disrupt traffic flow. This paper introduces the Minimizing Lane Change Algorithm (MLCA), a state-machine-based approach designed to reduce unnecessary lane changes, thereby enhancing both traffic safety and efficiency. The MLCA algorithm prioritizes maintaining lane stability unless saf…

Direct numerical simulations of inhalation in a 23-generation lung model
Marco Atzori, Emanuele Gallorini, Ciro Cottini, Andrea Benassi, Maurizio Quadrio
https://arxiv.org/abs/2506.14729

Direct numerical simulations of inhalation in a 23-generation lung model
The air flows in the proximal and distal portions of the human lungs are interconnected: the lower Reynolds number in the deeper generations causes a progressive flow regularization, while mass conservation requires flow rate oscillations to propagate through the airway bifurcations. To explain how these two competing effects shape the flow state in the deeper generations, we have performed the first high-fidelity numerical simulations of the air flow in a lung model including 23 successive bif…

Understanding the correlation between elliptic and triangular flow
Mubarak Alqahtani, Jean-Yves Ollitrault
https://arxiv.org/abs/2507.20315 https://arxiv.o…

Understanding the correlation between elliptic and triangular flow
The relative correlation between the magnitudes of elliptic flow ($v_2$) and triangular flow ($v_3$) has been accurately measured in nucleus-nucleus collisions at the LHC collider. As a function of the centrality of the collision, it changes sign and varies non-monotonically. We show that this is naturally explained by two combined effects. The first effect is a skewness in initial-state fluctuations, which is quantified by the correlation between the geometry-driven elliptic deformation in the…

Deep Variational Free Energy Calculation of Hydrogen Hugoniot
Zihang Li, Hao Xie, Xinyang Dong, Lei Wang
https://arxiv.org/abs/2507.18540 https://arxiv.org…

Deep Variational Free Energy Calculation of Hydrogen Hugoniot
We develop a deep variational free energy framework to compute the equation of state of hydrogen in the warm dense matter region. This method parameterizes the variational density matrix of hydrogen nuclei and electrons at finite temperature using three deep generative models: a normalizing flow model that represents the Boltzmann distribution of the classical nuclei, an autoregressive transformer that models the distribution of electrons in excited states, and a permutational equivariant flow …

A Hidden Pulse: Uncovering a New Timing Signal in Cygnus X-1 with AstroSat
Sandeep K. Rout, Federico Garcia, Mariano Mendez, Abhay Kumar, Santosh Vadawale, David M. Russell, Pei Jin
https://arxiv.org/abs/2507.13884

A Hidden Pulse: Uncovering a New Timing Signal in Cygnus X-1 with AstroSat
The study of fast variability properties in X-ray binaries advances our understanding of the physical processes and geometric properties of the accretion flow around the compact object. In this work, we study the evolution of the timing properties of Cygnus X-1 with AstroSat/LAXPC, during the transition of the source from the hard to soft state in 2017. We use a novel frequency-segmented technique to fit simultaneously the cross spectra and part of the power spectra and coherence function with …

Bayesian analysis of properties of nuclear matter with the FOPI experimental data
Guojun Wei, Manzi Nan, Pengcheng Li, Yongjia Wang, Qingfeng Li, Gaochan Yong, Fuhu Liu
https://arxiv.org/abs/2509.03406

Bayesian analysis of properties of nuclear matter with the FOPI experimental data
Based on the ultra-relativistic quantum molecular dynamics (UrQMD) transport model, combined with experimental data of directed flow, elliptic flow, and nuclear stopping power measured by FOPI in $\rm ^{197}Au+^{197}Au$ collisions at beam energies ($E_{lab}$) of 0.25 and 0.4 GeV/nucleon, the incompressibility of the nuclear equation of state $K_0$, the nucleon effective mass $m^*$, and the in-medium correction factor ($F$, with respect to free-space values) on the nucleon-nucleon elastic cross …

Vertex corrections to nonlinear photoinduced currents in 2D superconductors
A. V. Parafilo, V. M. Kovalev, I. G. Savenko
https://arxiv.org/abs/2506.17714 h…

Vertex corrections to nonlinear photoinduced currents in 2D superconductors
The emergence of a rectified steady-state supercurrent as a response to the photoexcited current of the quasiparticles constitutes the concept of a superconducting photodiode. This phenomenon occurs in a two-dimensional thin superconducting film with a built-in DC supercurrent that is exposed to a circularly polarized external electromagnetic field. The flow of a Cooper-pair condensate, resulting as a second-order photo-response in a direction transverse to the initially built-in supercurrent, …

Quantum-assisted tracer dispersion in turbulent shear flow
Julia Ingelmann, Fabian Schindler, J\"org Schumacher
https://arxiv.org/abs/2506.14586 https…

Quantum-assisted tracer dispersion in turbulent shear flow
We present a quantum-assisted generative algorithm for synthetic tracks of Lagrangian tracer particles in a turbulent shear flow. The parallelism and sampling properties of quantum algorithms are used to build and optimize a parametric quantum circuit, which generates a quantum state that corresponds to the joint probability density function of the classical turbulent velocity components, p(u_1^{\prime}, u_2^{\prime}, u_3^{\prime}). Velocity samples are drawn by one-shot measurements on the qua…

Make Your AUV Adaptive: An Environment-Aware Reinforcement Learning Framework For Underwater Tasks
Yimian Ding, Jingzehua Xu, Guanwen Xie, Shuai Zhang, Yi Li
https://arxiv.org/abs/2506.15082

Make Your AUV Adaptive: An Environment-Aware Reinforcement Learning Framework For Underwater Tasks
This study presents a novel environment-aware reinforcement learning (RL) framework designed to augment the operational capabilities of autonomous underwater vehicles (AUVs) in underwater environments. Departing from traditional RL architectures, the proposed framework integrates an environment-aware network module that dynamically captures flow field data, effectively embedding this critical environmental information into the state space. This integration facilitates real-time environmental ad…

On the temperature of an active nematic
Jay Armas, Akash Jain, Ruben Lier
https://arxiv.org/abs/2506.20602 https://arxiv.org/pdf/2506…

On the temperature of an active nematic
We employ a novel hydrodynamic framework for active matter coupled to an environment to study the local temperature of an active nematic, assuming proximity to thermal equilibrium. We show that, due to the mechanosensitivity of fuel consumption, linearized temperature correlations in a homogeneous active nematic steady state remain unaffected by activity. However, we demonstrate that local shearing and twisting cause a confined active nematic undergoing a spontaneous flow transition to develop …

Monotone Multispecies Flows
Lauren Conger, Franca Hoffmann, Eric Mazumdar, Lillian J. Ratliff
https://arxiv.org/abs/2506.22947 https://

Monotone Multispecies Flows
We present a novel notion of $λ$-monotonicity for an $n$-species system of partial differential equations governed by mass-preserving flow dynamics, extending monotonicity in Banach spaces to the Wasserstein-2 metric space. We show that monotonicity implies the existence of and convergence to a unique steady state, convergence of the velocity fields and second moments, and contraction in the Wasserstein-2 metric, at rates dependent on $λ$. In the special setting of Wasserstein-2 gradient desc…

Versatile SPH Open Boundary Conditions for Multiphase Flows in Extreme Condition
Zi-Yang Zhan, Zhen Chen
https://arxiv.org/abs/2506.14500 https://

Versatile SPH Open Boundary Conditions for Multiphase Flows in Extreme Condition
Although the Smoothed Particle Hydrodynamics (SPH) method has been demonstrated as a promising numerical solver for multiphase flow problems due to its Lagrangian nature, its application to complex channel flow may encounter additional issues such as the open boundary condition and numerical instability in the extreme flow state. The present work aims to establish a general SPH algorithm for accurate and stable simulation of complex multiphase flows in configurations with open boundaries. The g…

The Anisotropy of Thermal Activation Energy of 2H-NbS$_2$
Yang Wang, Pengjian Tan, Mingxi Chi, Boxi Wei, Anchun Ji, Jian Wang, He Wang
https://arxiv.org/abs/2507.14540

The Anisotropy of Thermal Activation Energy of 2H-NbS$_2$
We investigate the anisotropic flux dynamics in 2H-NbS$_2$ single crystals through temperature-dependent resistance measurements under in-plane ($H \parallel ab$ plane) and out-of-plane ($H \perp ab$ plane) magnetic fields. Analysis of thermally activated flux flow (TAFF) resistance in the superconducting mixed state reveals stark contrasts in thermal activation energy ($U_0$) scaling and field dependence. For $H \perp ab$, $U_0(0.1 \mathrm{T}) = (1228.76 \pm 53.64)$ K follows the Arrhenius rel…

Integral fractional viscoelastic models in SPH: LAOS simulations versus experimental data
Luca Santelli, Adolfo V\'azquez-Quesada, Aizzati Burgoa, Aitor Arriaga, Ritardo Hernandez, Marco Ellero
https://arxiv.org/abs/2507.14149

Integral fractional viscoelastic models in SPH: LAOS simulations versus experimental data
The rheological behaviour of a polymer was investigated by performing numerical simulations in complex flow and comparing them to experiments. For our simulations, we employed a Smoothed Particle Hydrodynamics scheme, utilizing an integral fractional model based on the K-BKZ framework. The results are compared with experiments performed on melt-state isotactic polypropylene under medium and large amplitude oscillatory shear. The numerical results are in good agreement with the experimental da…

Quick starch guide: A perspective on shear thickening in dense non-Brownian suspensions
C\'ecile Clavaud, Abhinendra Singh
https://arxiv.org/abs/2506.11951

Quick starch guide: A perspective on shear thickening in dense non-Brownian suspensions
In this article, we provide a brief perspective on recent developments in the study of shear thickening in dense suspensions. We give a rapid overview of the state of the art and discuss current models aiming to describe this particular rheology. Although most of the experiments and simulation studies are conducted in "ideal" flows, where the sample is confined without an open boundary condition, we have decided to highlight more realistic flow conditions. We further provide an overview on how …