Tootfinder

Ohio lawmakers to introduce bill banning abortion, criminalizing the procedure (Mary Kekatos/ABC News)
https://abcnews.go.com/Health/ohio-lawmakers-introduce-bill-banning-abortion-criminalizing-procedure/story?id=122922580
http://www.memeorandum.com/250617/p160#a250617p160

Inverse Physics-informed neural networks procedure for detecting noise in open quantum systems
Gubio G. de Lima, Iann Cunha, Leonardo Kleber Castelano
https://arxiv.org/abs/2507.12552

Inverse Physics-informed neural networks procedure for detecting noise in open quantum systems
Accurate characterization of quantum systems is essential for the development of quantum technologies, particularly in the noisy intermediate-scale quantum (NISQ) era. While traditional methods for Hamiltonian learning and noise characterization often require extensive measurements and scale poorly with system size, machine learning approaches offer promising alternatives. In this work, we extend the inverse physics-informed neural network (referred to as PINNverse) framework to open quantum sy…

Today in chatbot uselessness: I was looking for a sentence I knew existed in my bank's website, explaining the procedure for one very specific action. The bank refuses to receive email and does not have a search function; both have been replaced by a chatbot. The bot insisted I must have misspelled my question, and kept directing me to a completely irrelevant page.
Luckily, back in 2014 I saved a PDF file which contained the answer. Once I looked it up, ctrl-f solved my problem in …

The ALM-Framework in the Theory of Multivariate Operator Means
Dante Hoshina, Shuhei Wada
https://arxiv.org/abs/2506.13098 https://ar…

The ALM-Framework in the Theory of Multivariate Operator Means
In this paper, we generalize the ALM-procedure introduced by Ando, Li, and Mathias for extending operator geometric means to multiple variables. We prove that the generalized procedure preserves all the properties required by the axioms of operator means, along with several additional desirable properties. Moreover, we examine the self-adjointness of the canonical geometric mean constructed through this procedure.

Estimating Intractable Posterior Distributions through Gaussian Process regression and Metropolis-adjusted Langevin procedure
Guillaume Perrin, Romain Jorge Do Marco, Christian Soize, Christine Funfschilling
https://arxiv.org/abs/2506.13336

Estimating Intractable Posterior Distributions through Gaussian Process regression and Metropolis-adjusted Langevin procedure
Numerical simulations are crucial for modeling complex systems, but calibrating them becomes challenging when data are noisy or incomplete and likelihood evaluations are computationally expensive. Bayesian calibration offers an interesting way to handle uncertainty, yet computing the posterior distribution remains a major challenge under such conditions. To address this, we propose a sequential surrogate-based approach that incrementally improves the approximation of the log-likelihood using Ga…

from my link log —
Dynamic witnesses for static type errors in OCaml, or, ill-typed programs usually go wrong.
https://arxiv.org/abs/1606.07557
saved 2025-05-31

Dynamic Witnesses for Static Type Errors (or, Ill-Typed Programs Usually Go Wrong)
Static type errors are a common stumbling block for newcomers to typed functional languages. We present a dynamic approach to explaining type errors by generating counterexample witness inputs that illustrate how an ill-typed program goes wrong. First, given an ill-typed function, we symbolically execute the body to synthesize witness values that make the program go wrong. We prove that our procedure synthesizes general witnesses in that if a witness is found, then for all inhabited input types…

A Decision Procedure for Probabilistic Kleene Algebra with Angelic Nondeterminism
Shawn Ong, Dexter Kozen
https://arxiv.org/abs/2507.10980 https://

A Decision Procedure for Probabilistic Kleene Algebra with Angelic Nondeterminism
We give a decision procedure and proof of correctness for the equational theory of probabilistic Kleene algebra with angelic nondeterminism introduced in Ong, Ma, and Kozen (2025).

@… There was an instance where they more or less did.
My in-laws showed up super early one morning, my wife had had a long and crappy night (Induced pregnancy, so we were in the hospital for almost a week).
The nurses told them that she was having a procedure done and they couldn’t see her until 10, giving her the freedom not to deal with them startin…

Production Function Estimation without Invertibility: Imperfectly Competitive Environments and Demand Shocks
Ulrich Doraszelski, Lixiong Li
https://arxiv.org/abs/2506.13520

Production Function Estimation without Invertibility: Imperfectly Competitive Environments and Demand Shocks
We advance the proxy variable approach to production function estimation. We show that the invertibility assumption at its heart is testable. We characterize what goes wrong if invertibility fails and what can still be done. We show that rethinking how the estimation procedure is implemented either eliminates or mitigates the bias that arises if invertibility fails. Furthermore, we show how a modification of the procedure ensures Neyman orthogonality, enhancing efficiency and robustness by rend…

A Non-Wellfounded and Labelled Sequent Calculus for Bimodal Provability Logic
Justus Becker
https://arxiv.org/abs/2506.14307 https://…

A Non-Wellfounded and Labelled Sequent Calculus for Bimodal Provability Logic
We present a labelled and non-wellfounded calculus for the bimodal provability logic CS. The system is obtained by modelling the Kripke-like semantics of this logic. As in arXiv:2309.00532, we enforce the second-order property of converse wellfoundedness by using techniques from cyclic proof theory. We will prove soundness and completeness of this system with respect to the semantics and provide a primitive decision procedure together with a way to extract countermodels.

Dependent Randomized Rounding for Budget Constrained Experimental Design
Khurram Yamin, Edward Kennedy, Bryan Wilder
https://arxiv.org/abs/2506.12677 https…

Dependent Randomized Rounding for Budget Constrained Experimental Design
Policymakers in resource-constrained settings require experimental designs that satisfy strict budget limits while ensuring precise estimation of treatment effects. We propose a framework that applies a dependent randomized rounding procedure to convert assignment probabilities into binary treatment decisions. Our proposed solution preserves the marginal treatment probabilities while inducing negative correlations among assignments, leading to improved estimator precision through variance reduc…

Preference-restricted parking functions
Jasper Bown, Peter Kagey, Alan Kappler, Michael E. Orrison, Jayden Thadani
https://arxiv.org/abs/2507.11701 https:/…

Preference-restricted parking functions
A parking function is a function $π:[n]\to [n]$ whose $i$th-smallest output is at most $i,$ corresponding to a parking procedure for $n$ cars on a one-way street. We refine this concept by introducing preference-restricted parking functions, which are parking functions with codomain restricted to some $S\subseteq[n]$. Particular choices of $S$ yield new combinatorial interpretations of previous results about variant parking procedures, and new results too. In particular we consider prime parki…

ReLCP: Scalable Complementarity-Based Collision Resolution for Smooth Rigid Bodies
Bryce Palmer, Hasan Metin Aktulga, Tong Gao
https://arxiv.org/abs/2506.14097

ReLCP: Scalable Complementarity-Based Collision Resolution for Smooth Rigid Bodies
We present a complementarity-based collision resolution algorithm for smooth, non-spherical, rigid bodies. Unlike discrete surface representation approaches, which approximate surfaces using discrete elements (e.g., tessellations or sub-spheres) with constraints between nearby faces, edges, nodes, or sub-objects, our algorithm solves a recursively generated linear complementarity problem (ReLCP) to adaptively identify potential collision locations during the collision resolution procedure. Desp…

Chargers' Jim Harbaugh provides positive health update after offseason heart procedure, hip replacement

https://www.cbssports.com/nfl/news/charg…

Back of the hand is where they draw blood or give you anesthetic in the hospital. If you're on some meds or the person doing the procedure isn't good at it, you'll bruise easily...
Trump’s strange bruised hand makes reappearance before president’s visit to Pittsburgh | The Independent
https://www.independent.co.uk/news/world/americas/us-politics/trump-hand-bruise-makeup-b2790030.html

The Algebraic Structure Underlying Pole-Skipping Points
Zhenkang Lu, Cheng Ran, Shao-feng Wu
https://arxiv.org/abs/2507.13306 https://

The Algebraic Structure Underlying Pole-Skipping Points
The holographic Green's function becomes ambiguous, taking the indeterminate form `$0/0$', at an infinite set of special frequencies and momenta known as ``pole-skipping points''. In this work, we propose that these pole-skipping points can be used to reconstruct both the interior and exterior geometry of a static, planar-symmetric black hole in the bulk. The entire reconstruction procedure is fully analytical and only involves solving a system of linear equations. We demonstrate its effectiven…

Convergence Rate of Generalized Nash Equilibrium Learning in Strongly Monotone Games with Linear Constraints
Tatiana Tatarenko, Maryam Kamgarpour
https://arxiv.org/abs/2507.12112 …

Convergence Rate of Generalized Nash Equilibrium Learning in Strongly Monotone Games with Linear Constraints
We consider payoff-based learning of a generalized Nash equilibrium (GNE) in multi-agent systems. Our focus is on games with jointly convex constraints of a linear structure and strongly monotone pseudo-gradients. We present a convergent procedure based on a partial regularization technique and establish the convergence rate of its iterates under one- and two-point payoff-based feedback. To the best of our knowledge, this work is the first one characterizing the convergence speed of iterates to…

Reset Controller Analysis and Design for Unstable Linear Plants using Scaled Relative Graphs
Julius P. J. Krebbekx, Roland T\'oth, Amritam Das
https://arxiv.org/abs/2506.13518

Reset Controller Analysis and Design for Unstable Linear Plants using Scaled Relative Graphs
In technical communique, we develop a graphical design procedure for reset controllers for unstable LTI plants based on recent developments on Scaled Relative Graph analysis, yielding an $L_2$-gain performance bound. The stabilizing controller consists of a second order reset element in parallel with a proportional gain. The proposed method goes beyond existing approaches that are limited to stable systems only, providing a well-applicable approach to design problems in practice where the plant…

Dark matter detection using optically trapped Rydberg atom tweezer arrays
So Chigusa, Taiyo Kasamaki, Toshi Kusano, Takeo Moroi, Kazunori Nakayama, Naoya Ozawa, Yoshiro Takahashi, Atsuhiro Umemoto, Amar Vutha
https://arxiv.org/abs/2507.12860

Dark matter detection using optically trapped Rydberg atom tweezer arrays
A new scheme for detecting wave-like dark matter (DM) using Rydberg atoms is proposed. Recent advances in trapping and manipulating Rydberg atoms make it possible to use Rydberg atoms trapped in optical tweezer arrays for DM detection. We present a simple and innovative experimental procedure that searches for excitations of trapped Rydberg atoms due to DM-induced electric field. A scan over DM mass is enabled with the use of the Zeeman and diamagnetic shifts of energy levels under an applied e…

Dynamics of Vortex Clusters on a Torus
Aswathy K R, Udaya Maurya, Surya Teja Gavva, Rickmoy Samanta
https://arxiv.org/abs/2506.13158 https://

Dynamics of Vortex Clusters on a Torus
We investigate the collective dynamics of multivortex assemblies in a two dimensional (2D) toroidal fluid film of distinct curvature and topology. The incompressible and inviscid nature of the fluid allows a Hamiltonian description of the vortices, along with a self-force of geometric origin, arising from the standard Kirchhoff-Routh regularization procedure. The Hamiltonian dynamics is constructed in terms of $q$-digamma functions $Ψ_q(z)$, closely related to the Schottky-Klein prime function…

Phase-field modelling of cohesive fracture. Part II: Reconstruction of the cohesive law
Roberto Alessi, Francesco Colasanto, Matteo Focardi
https://arxiv.org/abs/2507.12172

Phase-field modelling of cohesive fracture. Part II: Reconstruction of the cohesive law
This is the second paper of a three-part work the main aim of which is to provide a unified consistent framework for the phase-field modelling of cohesive fracture. Building on the theoretical foundations of the first paper, where {$Γ$-convergence} results have been derived, this second paper presents a systematic procedure for constructing phase-field models that reproduce prescribed cohesive laws. By either selecting the degradation function and determining the damage potential or vice versa…

(Exhaustive) Symbolic Regression and model selection by minimum description length
Harry Desmond
https://arxiv.org/abs/2507.13033 https://

(Exhaustive) Symbolic Regression and model selection by minimum description length
Symbolic regression is the machine learning method for learning functions from data. After a brief overview of the symbolic regression landscape, I will describe the two main challenges that traditional algorithms face: they have an unknown (and likely significant) probability of failing to find any given good function, and they suffer from ambiguity and poorly-justified assumptions in their function-selection procedure. To address these I propose an exhaustive search and model selection by the…

Correcting impedance measurements for background parasitics to characterize circuit components in cryogenic environments
Riley J. Carpenter, Jadyn Anczarski, Ivar Rydstrom, Aviv Simchony, Zoe J. Smith, Noah A. Kurinsky, Betty A. Young
https://arxiv.org/abs/2506.12268

Correcting impedance measurements for background parasitics to characterize circuit components in cryogenic environments
Predictable circuit response is a critical prerequisite for accurate electronic measurements. We describe a powerful, yet straightforward, experimental method and analysis model that utilizes an affordable LCR meter in conjunction with an in situ parasitic impedance background correction procedure to measure the temperature-dependent impedance (magnitude and phase) of individual passive circuit elements mounted in a cryostat. We show how the model unambiguously identified a 20x drop in capacita…

A House Monotonic and Droop Proportional Ranked Candidate Voting Method
Ross Hyman
https://arxiv.org/abs/2506.12318 https://arxiv.org…

A House Monotonic and Droop Proportional Ranked Candidate Voting Method
A Ranked candidate voting methods based on Phragmen's procedure is described that can be used to produce a top-down proportional candidate list. The method complies with the Droop proportionality criterion satisfied by Single Transferable Vote. It also complies with house monotonicity and independence of irrelevant ballots, properties that are the ranked-candidate analogs of the divisor methods properties of always avoiding the Alabama and New State paradoxes. The highest ranked candidate in th…

Adaptive estimation in regression models for weakly dependent data and explanatory variable with known density
Karine Bertin, Lisandro Fermin, Miguel Padrino
https://arxiv.org/abs/2507.11725

Adaptive estimation in regression models for weakly dependent data and explanatory variable with known density
This article is dedicated to the estimation of the regression function when the explanatory variable is a weakly dependent process whose correlation coefficient exhibits exponential decay and has a known bounded density function. The accuracy of the estimation is measured using pointwise risk. A data-driven procedure is proposed using kernel estimation with bandwidth selected via the Goldenshluger-Lepski approach. We demonstrate that the resulting estimator satisfies an oracle-type inequality a…

An improved argument principle root-search method for modes of slab waveguides, optical fibers, and spheres
S. Rao, P. Y. Chen, T. Grossinger, Y. Sivan
https://arxiv.org/abs/2507.11752

An improved argument principle root-search method for modes of slab waveguides, optical fibers, and spheres
We update our root-search method for transcendental equations. Our method is globally convergent and is guaranteed to locate all complex roots within a specified search domain, since it is based on Cauchy's residue theorem. We extend the implementation to treat the dispersion relations of slab waveguides and the resonances of a sphere, in addition to step-index fibers. We also implement other improvements, such as to the contour selection procedure and using non-dimensional search variables, to…

Large effects from quantum reference frames
Martin Bojowald, Luis Martinez
https://arxiv.org/abs/2506.14721 https://arxiv.org/pdf/250…

Large effects from quantum reference frames
Reference frames are used to parameterize measurements of physical effects, but since their practical realization uses material objects, they may affect observations performed in a combined quantum state of the measured system together with the frame. Here, a procedure is used that makes it possible to describe non-monotonic reference scales in a quantum treatment, revealing large quantum effects in the measured system whenever a reference frame encounters a turning point. Subtle quantum correl…

The relative index in coarse index theory and submanifold obstructions to uniform positive scalar curvature
Alexander Engel, Christopher Wulff
https://arxiv.org/abs/2506.14301

The relative index in coarse index theory and submanifold obstructions to uniform positive scalar curvature
We provide a coarse version of the relative index of Gromov and Lawson and thoroughly establish all of its basic properties. As an application, we discuss a general procedure to construct wrong way maps on the $K$-theory of the Roe algebra mapping the coarse index class of the Dirac operator of a manifold to the one of a suitably embedded submanifold of arbitrary codimension, thereby establishing an abstract machinery to find obstructions to uniform positive scalar curvature coming from these s…

Wow. Yes. From a California district court:
“At this early stage of the proceedings, the Court must determine whether the President followed the congressionally mandated procedure for his actions. He did not. His actions were illegal—both exceeding the scope of his statutory authority and violating the Tenth Amendment to the United States Constitution. He must therefore return control of the California National Guard to the Governor of the State of California forthwith.” https://journa.host/@chrisgeidner/114673375048335011

Bootstrap prediction intervals for the age distribution of life-table death counts
Han Lin Shang
https://arxiv.org/abs/2507.11946 https://

Bootstrap prediction intervals for the age distribution of life-table death counts
We introduce a nonparametric bootstrap procedure based on a dynamic factor model to construct pointwise prediction intervals for period life-table death counts. The age distribution of death counts is an example of constrained data, which are nonnegative and have a constrained integral. A centered log-ratio transformation is used to remove the constraints. With a time series of unconstrained data, we introduce our bootstrap method to construct prediction intervals, thereby quantifying forecast …

The phenomenological renormalization group in neuronal models near criticality
Kaio F. R. Nascimento, Daniel M. Castro, Gustavo G. Cambrainha, Mauro Copelli
https://arxiv.org/abs/2506.14053

The phenomenological renormalization group in neuronal models near criticality
The phenomenological renormalization group (PRG) has been applied to the study of scaleinvariant phenomena in neuronal data, providing evidence for critical phenomena in the brain. However, it remains unclear how reliably these observed signatures indicate genuine critical behavior, as it is not well established how close to criticality a system must be for them to emerge. Here, we rely on neuronal models with known critical points to investigate under which conditions the PRG procedure yields …

On the Complexity of the Skolem Problem at Low Orders
Piotr Bacik, Jo\"el Ouaknine, James Worrell
https://arxiv.org/abs/2507.11234 https://

On the Complexity of the Skolem Problem at Low Orders
The Skolem Problem asks to determine whether a given linear recurrence sequence (LRS) $\langle u_n \rangle_{n=0}^\infty$ over the integers has a zero term, that is, whether there exists $n$ such that $u_n = 0$. Decidability of the problem is open in general, with the most notable positive result being a decision procedure for LRS of order at most 4. In this paper we consider a bounded version of the Skolem Problem, in which the input consists of an LRS $\langle u_n \rangle_{n=0}^\infty$ and a…

Learning the Analytic Geometry of Transformations to Achieve Efficient Computation
Pei-Chun Su, Ronald R. Coifman
https://arxiv.org/abs/2506.11990 https://…

Learning the Analytic Geometry of Transformations to Achieve Efficient Computation
We propose a novel framework for fast integral operations by uncovering hidden geometries in the row and column structures of the underlying operators. This is accomplished through an iterative procedure that constructs adaptive hierarchical partition trees, revealing latent multiscale organization and exposing local low-rank structures within the data. Guided by this geometry, we employ two complementary techniques: (1) the \emph{butterfly algorithm}, which exploits the learned hierarchical lo…

Least total curvature solutions to steady Euler system and monotone solutions to semilinear equations in a strip
Changfeng Gui, David Ruiz, Chunjing Xie, Huan Xu
https://arxiv.org/abs/2507.11837

Least total curvature solutions to steady Euler system and monotone solutions to semilinear equations in a strip
This paper focuses on establishing the existence of a class of steady solutions, termed least total curvature solutions, to the incompressible Euler system in a strip. The solutions obtained in this paper complement the least total curvature solutions already known. Our approach employs a minimization procedure to identify a monotone heteroclinic solution for a conveniently chosen semilinear elliptic PDE. This method also enables us to construct positive and monotone (and consequently stable) s…

Gradient Boosting for Spatial Regression Models with Autoregressive Disturbances
Michael Balzer
https://arxiv.org/abs/2506.13682 https://

Gradient Boosting for Spatial Regression Models with Autoregressive Disturbances
Researchers in urban and regional studies increasingly deal with spatial data that reflects geographic location and spatial relationships. As a framework for dealing with the unique nature of spatial data, various spatial regression models have been introduced. In this article, a novel model-based gradient boosting algorithm for spatial regression models with autoregressive disturbances is proposed. Due to the modular nature, the approach provides an alternative estimation procedure which is fe…

Structure of Galois rings and the Gelfand-Kirillov Conjecture
Vyacheslav Futorny, Jonas T. Hartwig, Erich C. Jauch, Jo\~ao Schwarz
https://arxiv.org/abs/2507.10782

Structure of Galois rings and the Gelfand-Kirillov Conjecture
The theory of Galois rings and orders, introduced by Futorny and Ovsienko, has many interesting applications to the structure and representation theory of algebras. This paper focuses on ring theoretical properties of Galois rings. The main technique is based on the fact that our algebras are embedded in a nice way into fixed rings of skew group (or monoid) rings, and via a simple localization procedure many facts about our rings can be deduced from properties of the associated skew group rings…

Interpolation and Quantifiers in Ortholattices
Simon Guilloud, Sankalp Gambhir, Viktor Kun\v{c}ak
https://arxiv.org/abs/2507.11141 https://

Interpolation and Quantifiers in Ortholattices
We study quantifiers and interpolation properties in \emph{orthologic}, a non-distributive weakening of classical logic that is sound for formula validity with respect to classical logic, yet has a quadratic-time decision procedure. We present a sequent-based proof system for quantified orthologic, which we prove sound and complete for the class of all complete ortholattices. We show that orthologic does not admit quantifier elimination in general. Despite that, we show that interpolants always…

Inference for microbe--metabolite association networks using a latent graph model
Jing Ma
https://arxiv.org/abs/2506.12275 https://ar…

Inference for microbe--metabolite association networks using a latent graph model
Correlation networks are commonly used to infer associations between microbes and metabolites. The resulting p-values are then corrected for multiple comparisons using existing methods such as the Benjamini and Hochberg procedure to control the false discovery rate (FDR). However, most existing methods for FDR control assume the p-values are weakly dependent. Consequently, they can have low power in recovering microbe-metabolite association networks that exhibit important topological features, …

On exterior-algebraic quaternions with application to Maxwell equations
Ivano Colombaro
https://arxiv.org/abs/2506.13927 https://arxi…

On exterior-algebraic quaternions with application to Maxwell equations
Within the framework of exterior algebra, the concept of time-like quaternions has been previously established. This paper advances beyond the existing structure by elucidating the procedure for constructing time-like quaternions with the feature of complex scalar terms. We delineate on the crucial role of these extended definition of quaternions in formulating Maxwell equations, having properly defined a pure quaternion containing the components of the classical electric and magnetic fields. T…

Robust Multi-Manifold Clustering via Simplex Paths
Haoyu Chen, Anna Little, Akin Narayan
https://arxiv.org/abs/2507.10710 https://arx…

Robust Multi-Manifold Clustering via Simplex Paths
This article introduces a novel, geometric approach for multi-manifold clustering (MMC), i.e. for clustering a collection of potentially intersecting, d-dimensional manifolds into the individual manifold components. We first compute a locality graph on d-simplices, using the dihedral angle in between adjacent simplices as the graph weights, and then compute infinity path distances in this simplex graph. This procedure gives a metric on simplices which we refer to as the largest angle path dista…

In-situ SHG microscopy investigation of the domain-wall-conductivity enhancement procedure in lithium niobate
Iuliia Kiseleva, Boris Koppitz, Elke Beyreuther, Matthias Roeper, Samuel D. Seddon, Lukas M. Eng
https://arxiv.org/abs/2507.07466

In-situ SHG microscopy investigation of the domain-wall-conductivity enhancement procedure in lithium niobate
Conductive domain walls (CDWs) in the uniaxial ferroelectric lithium niobate (LiNbO$_3$, LN) have attracted a lot of interest as potential elements in 2D nanoelectronics, due to their orders-of-magnitude larger electronic AC and DC conductivities as compared to the host material. On the way towards generating standardized CDWs into z-cut bulk LN crystals with controllable geometry and electrical properties, we have encountered setbacks recently: Although the first preparation step, i.e., the es…

Physics-Informed Transfer Learning for Data-Driven Sound Source Reconstruction in Near-Field Acoustic Holography
Xinmeng Luan, Mirco Pezzoli, Fabio Antonacci, Augusto Sarti
https://arxiv.org/abs/2507.11070

Physics-Informed Transfer Learning for Data-Driven Sound Source Reconstruction in Near-Field Acoustic Holography
We propose a transfer learning framework for sound source reconstruction in Near-field Acoustic Holography (NAH), which adapts a well-trained data-driven model from one type of sound source to another using a physics-informed procedure. The framework comprises two stages: (1) supervised pre-training of a complex-valued convolutional neural network (CV-CNN) on a large dataset, and (2) purely physics-informed fine-tuning on a single data sample based on the Kirchhoff-Helmholtz integral. This meth…

3D forest semantic segmentation using multispectral LiDAR and 3D deep learning
Narges Takhtkeshha, Lauris Bocaux, Lassi Ruoppa, Fabio Remondino, Gottfried Mandlburger, Antero Kukko, Juha Hyypp\"a
https://arxiv.org/abs/2507.08025

3D forest semantic segmentation using multispectral LiDAR and 3D deep learning
Conservation and decision-making regarding forest resources necessitate regular forest inventory. Light detection and ranging (LiDAR) in laser scanning systems has gained significant attention over the past two decades as a remote and non-destructive solution to streamline the labor-intensive and time-consuming procedure of forest inventory. Advanced multispectral (MS) LiDAR systems simultaneously acquire three-dimensional (3D) spatial and spectral information across multiple wavelengths of the…

Worst-Case Complexity of High-Order Algorithms for Pareto-Front Reconstruction
Andrea Cristofari, Marianna De Santis, Stefano Lucidi, Giampaolo Liuzzi
https://arxiv.org/abs/2506.11929

Worst-Case Complexity of High-Order Algorithms for Pareto-Front Reconstruction
In this paper, we are concerned with a worst-case complexity analysis of a-posteriori algorithms for unconstrained multiobjective optimization. Specifically, we propose an algorithmic framework that generates sets of points by means of $p$th-order models regularized with a power $p+1$ of the norm of the step. Through a tailored search procedure, several trial points are generated at each iteration and they can be added to the current set if a decrease is obtained for at least one objective func…

It's always a bit annoying to use journal abbreviations in the bibliography when the journal requires it.
Does anyone know whether this procedure works reliably in #Zotero:
https://www.zotero.org/support/kb/journal_abbreviations

Constraints on Kinetic Mixing of Dark Photons from Dilepton Spectra
A. W. Romero Jorge, E. Bratkovskaya, T. Song, L. Sagunski
https://arxiv.org/abs/2507.11163

Constraints on Kinetic Mixing of Dark Photons from Dilepton Spectra
Dark photons, the hypothetical gauge bosons associated with an additional $U(1)^{\prime}$ symmetry, can couple to Standard Model particles through a small kinetic mixing parameter $\varepsilon$ with the ordinary photon. This mechanism provides a portal between the dark sector and visible matter. In this study, we present a procedure to derive theoretical upper bounds on the kinetic mixing parameter $\varepsilon^2(M_U)$ by analyzing dilepton spectra from heavy-ion collisions across a broad energ…

Network Cross-Validation for Nested Models by Edge-Sampling: Selection Consistency
Bokai Yang
https://arxiv.org/abs/2506.14244 https://

Network Cross-Validation for Nested Models by Edge-Sampling: Selection Consistency
In the network literature, a wide range of statistical models have been proposed to exploit structural patterns in the data. Therefore, model selection between different models is a fundamental problem. Cross-validation is a powerful candidate to solve this problem, and Li et al. have already proposed an edge-sampling procedure to choose the number of communities in the block model framework. In this paper, we propose a penalized edge-sampling cross-validation framework for nested network model…

Oh give me your pity!
I'm on a committee, We attend and amend
Which means that from morning And contend and defend
to night, Without a conclusion in sight.
We confer and concur,
We defer and demur, We revise the agenda
And reiterate all of our thoughts. With frequent addenda
And consider a load of reports.
We compose and propose,
We suppose and oppose, But though various notions
And the points of procedure are fun; Are br…

Resa: Transparent Reasoning Models via SAEs
Shangshang Wang, Julian Asilis, \"Omer Faruk Akg\"ul, Enes Burak Bilgin, Ollie Liu, Deqing Fu, Willie Neiswanger
https://arxiv.org/abs/2506.09967

Resa: Transparent Reasoning Models via SAEs
How cost-effectively can we elicit strong reasoning in language models by leveraging their underlying representations? We answer this question with Resa, a family of 1.5B reasoning models trained via a novel and efficient sparse autoencoder tuning (SAE-Tuning) procedure. This method first trains an SAE to capture reasoning abilities from a source model, and then uses the trained SAE to guide a standard supervised fine-tuning process to elicit such abilities in a target model, all using verified…

Entropy-conservative numerical fluxes for compressible Euler equations with thermally perfect gas models
Alessandro Aiello, Carlo De Michele, Gennaro Coppola
https://arxiv.org/abs/2507.08115

Entropy-conservative numerical fluxes for compressible Euler equations with thermally perfect gas models
This study proposes a novel spatial discretization procedure for the compressible Euler equations that guarantees entropy conservation at a discrete level for thermally perfect gases. The procedure is based on a locally conservative formulation, and extends the entropy-conserving schemes to the more realistic case of thermally perfect gases, while still guaranteeing preservation of both linear invariants and kinetic energy. The proposed methodology, which can also be extended to multicomponent …

A new discretization of the Euler equation via the finite operator theory
Miguel A. Rodr\'iguez, Piergiulio Tempesta
https://arxiv.org/abs/2507.05040 h…

A new discretization of the Euler equation via the finite operator theory
We propose a novel discretization procedure for the classical Euler equation based on the theory of Galois differential algebras and the finite operator calculus developed by G.C. Rota and collaborators. This procedure allows us to define algorithmically a new discrete model that inherits from the continuous Euler equation a class of exact solutions.

Oracle-Based Multistep Strategy for Solving Polynomial Systems Over Finite Fields and Algebraic Cryptanalysis of the Aradi Cipher
La Scala Roberto, Sharwan Kumar Tiwari
https://arxiv.org/abs/2506.09950

Oracle-Based Multistep Strategy for Solving Polynomial Systems Over Finite Fields and Algebraic Cryptanalysis of the Aradi Cipher
The multistep solving strategy consists in a divide-and-conquer approach: when a multivariate polynomial system is computationally infeasible to solve directly, one variable is assigned over the elements of the base finite field, and the procedure is recursively applied to the resulting simplified systems. In a previous work by the same authors (among others), this approach proved effective in the algebraic cryptanalysis of the Trivium cipher. In this paper, we present a new implementation of t…

Propose or Vote: A simple Democratic Procedure
Hans Gersbach
https://arxiv.org/abs/2506.05998 https://arxiv.org/pdf/2506.05998…

Propose or Vote: A simple Democratic Procedure
This paper introduces a simple democratic procedure. In a first stage, all members of a polity decide whether to apply for proposal-making or later vote on proposals made in the second stage. This procedure is called Propose or Vote (PoV). With appropriate default points and majority voting over two randomly selected proposals, the PoV procedure can implement the Condorcet winner with only one round of voting if a Condorcet winner exists. We explore ways to establish uniqueness, alternative vot…

Collaborative Human-Robot Surgery for Mandibular Angle Split Osteotomy: Optical Tracking based Approach
Zhe Han, Huanyu Tian, Tom Vercauteren, Da Liu, Changsheng Li, Xingguang Duan
https://arxiv.org/abs/2507.07794

Collaborative Human-Robot Surgery for Mandibular Angle Split Osteotomy: Optical Tracking based Approach
Mandibular Angle Split Osteotomy (MASO) is a significant procedure in oral and maxillofacial surgery. Despite advances in technique and instrumentation, its success still relies heavily on the surgeon's experience. In this work, a human-robot collaborative system is proposed to perform MASO according to a preoperative plan and under guidance of a surgeon. A task decomposition methodology is used to divide the collaborative surgical procedure into three subtasks: (1) positional control and (2) o…

Testing the ubiquitous presence of very high energy emission in gamma-ray bursts with the MAGIC telescopes
S. Abe, J. Abhir, A. Abhishek, V. A. Acciari, A. Aguasca-Cabot, I. Agudo, T. Aniello, S. Ansoldi, L. A. Antonelli, A. Arbet Engels, C. Arcaro, T. T. H. Arnesen, K. Asano, A. Babic, C. Bakshi, U. Barres de Almeida, J. A. Barrio, L. Barrios-Jimenez, I. Batkovic, J. Baxter, J. Becerra Gonzalez, W. Bednarek, E. Bernardini, J. Bernete, A. Berti, J. Besenrieder, C. Bigongiari, A. Biland…

Testing the ubiquitous presence of very high energy emission in gamma-ray bursts with the MAGIC telescopes
Gamma-ray bursts (GRBs) are the most powerful transient objects in the Universe, and they are a primary target for the MAGIC Collaboration. Recognizing the challenges of observing these elusive objects with Imaging Atmospheric Cherenkov Telescopes (IACTs), we implemented a dedicated observational strategy that included an automated procedure for rapid re-pointing to transient sources. Since 2013, this automated procedure has enabled MAGIC to observe GRBs at a rate of approximately ten per year,…

Indian Charity Organizes Limb Giveaway for 75 Afghan Amputees, Fitting Them with Free Prosthetic Feet https://www.goodnewsnetwork.org/indian-charity-organizes-limb-giveaway-for-75-afghan-amput…

Indian Charity Organizes Limb Giveaway for 75 Afghan Amputees, Fitting Them with Free Prosthetic Feet in Kabul
In Kabul, BMVSS also organized training for local hospital staff in the procedure for measuring, creating, and fitting a prosthetic.

Equilibrium-preserving Laplacian renormalization group
Sudo Yi, Seong-Gyu Yang, K. -I. Goh, D. -S. Lee
https://arxiv.org/abs/2507.04977 https://

Equilibrium-preserving Laplacian renormalization group
Diffusion over networks has recently been used to define spatiotemporal scales and extend Kadanoff block spins of Euclidean space to supernodes of networks in the Laplacian renormalization group (LRG). Yet, its ad hoc coarse-graining procedure remains underdeveloped and unvalidated, limiting its broader applicability. Here we rigorously formulate an LRG preserving the equilibrium state, offering a principled coarse-graining procedure. We construct the renormalized Laplacian matrix preserving do…

SakugaFlow: A Stagewise Illustration Framework Emulating the Human Drawing Process and Providing Interactive Tutoring for Novice Drawing Skills
Kazuki Kawamura, Jun Rekimoto
https://arxiv.org/abs/2506.08443

SakugaFlow: A Stagewise Illustration Framework Emulating the Human Drawing Process and Providing Interactive Tutoring for Novice Drawing Skills
While current AI illustration tools can generate high-quality images from text prompts, they rarely reveal the step-by-step procedure that human artists follow. We present SakugaFlow, a four-stage pipeline that pairs diffusion-based image generation with a large-language-model tutor. At each stage, novices receive real-time feedback on anatomy, perspective, and composition, revise any step non-linearly, and branch alternative versions. By exposing intermediate outputs and embedding pedagogical …

Symplectification of Rank 2 Distributions, Normal Cartan Connections, and Cartan Prolongations
Nicklas Day, Boris Doubrov, Igor Zelenko
https://arxiv.org/abs/2506.09232

Symplectification of Rank 2 Distributions, Normal Cartan Connections, and Cartan Prolongations
We study the Doubrov--Zelenko symplectification procedure for rank~2 distributions of maximal class -- originally motivated by optimal control theory -- through the lens of Tanaka--Morimoto theory for normal Cartan connections. In this way, for ambient manifolds of dimension $n \geq 5$, we prove the existence of the normal Cartan connection associated with the symplectified distribution. Furthermore, we show that this symplectification can be interpreted as the $(n-4)$th iterated Cartan prolong…

@… I have a new #git repository on my laptop of a project I started today. What's the procedure for pushing it up to my #forgejo instance?

X-Shooting ULLYSES: Massive stars at low metallicity. XIII. Putting the bi-stability jump to the test in the LMC
T. Alkousa (Astrophysics Research Cluster, School of Mathematical and Physical Sciences, University of Sheffield), P. A. Crowther (Astrophysics Research Cluster, School of Mathematical and Physical Sciences, University of Sheffield), J. M. Bestenlehner (Astrophysics Research Cluster, School of Mathematical and Physical Sciences, University of Sheffield, School of Chemical, M…

X-Shooting ULLYSES: Massive stars at low metallicity. XIII. Putting the bi-stability jump to the test in the LMC
We aim to investigate the theoretical bi-stability jump, which predicts an increase in mass-loss rates below 21 kK. We further aim to constrain the photospheric and wind parameters of a sample of 16 LMC late-O and B supergiants. We utilise the 1D, non-LTE radiative transfer model CMFGEN in a grid-based approach and subsequent fine-tuned spectroscopic fitting procedure to determine the stellar and wind parameters of each star. We apply this method to ultra-violet data from the ULLYSES programme …

Adaptation of Multi-modal Representation Models for Multi-task Surgical Computer Vision
Soham Walimbe, Britty Baby, Vinkle Srivastav, Nicolas Padoy
https://arxiv.org/abs/2507.05020

Adaptation of Multi-modal Representation Models for Multi-task Surgical Computer Vision
Surgical AI often involves multiple tasks within a single procedure, like phase recognition or assessing the Critical View of Safety in laparoscopic cholecystectomy. Traditional models, built for one task at a time, lack flexibility, requiring a separate model for each. To address this, we introduce MML-SurgAdapt, a unified multi-task framework with Vision-Language Models (VLMs), specifically CLIP, to handle diverse surgical tasks through natural language supervision. A key challenge in multi-t…

Before states banned abortion,
one of the gravest outcomes of early miscarriage could easily be avoided:
👉Doctors could offer a dilation and curettage procedure, which quickly empties the uterus and allows it to close,
protecting against a life-threatening hemorrhage.
⚠️But because the procedures, known as D&Cs, are also used to end pregnancies, they have gotten tangled up in state legislation that restricts abortion.
🆘Reports now abound of doctors hesitat…

A “Striking” Trend: After Texas Banned Abortion, More Women Nearly Bled to Death During Miscarriage
A new ProPublica data analysis adds to the mounting evidence that abortion bans have made the common experience of first-trimester miscarriage far more dangerous.

Effective quality factor of mechanical resonators under complex-frequency excitations
Wenbo Li, Skriptyan Syuhri, Pablo Tarazaga, Raj Kumar Pal
https://arxiv.org/abs/2507.10940

Effective quality factor of mechanical resonators under complex-frequency excitations
We investigate the dynamics of mechanical resonators subject to excitations comprising of an oscillating or harmonic part, whose amplitude decays exponentially in time. We call these complex frequency excitations and show that the resulting response is quasi-steady, i.e. after an appropriate transform, the response of the new variable corresponds to the steady state behavior under a harmonic excitation. A procedure is presented to determine the amplitude-frequency response and effective quality…

Mesoscience-based structural theory for heterogeneous gas-solid flows
Yige Liu, Bidan Zhao, Junwu Wang
https://arxiv.org/abs/2507.11010 https://

Mesoscience-based structural theory for heterogeneous gas-solid flows
Quantification of the spatiotemporal dynamics of heterogeneous gas-solid flows is critical for the design, scale-up and optimization of gas-solid reactors. In this article, by using the core concept of mesoscience (the compromise in competition between dominant mechanisms), a mathematically rigorous procedure is proposed to develop a mesoscience-based structural theory for the dynamics of heterogeneous gas-solid flows via describing the physical states corresponding to the realization of domina…

Hierarchical formula classes with respect to semi-classical prenex normalization
Makoto Fujiwara, Taishi Kurahashi
https://arxiv.org/abs/2506.22348 https:/…

Hierarchical formula classes with respect to semi-classical prenex normalization
In [10], the authors formalized the standard transformation procedure for prenex normalization of first-order formulas and showed that the classes $\mathrm{E}_k$ and $\mathrm{U}_k$ introduced in Akama et al. [1] are exactly the classes induced by $Σ_k$ and $Π_k$ respectively via the transformation procedure. In that sense, the classes $\mathrm{E}_k$ and $\mathrm{U}_k$ correspond to $Σ_k$ and $Π_k$ based on classical logic respectively. On the other hand, some transformations of the prenex n…

P.808 Multilingual Speech Enhancement Testing: Approach and Results of URGENT 2025 Challenge
Marvin Sach, Yihui Fu, Kohei Saijo, Wangyou Zhang, Samuele Cornell, Robin Scheibler, Chenda Li, Anurag Kumar, Wei Wang, Yanmin Qian, Shinji Watanabe, Tim Fingscheidt
https://arxiv.org/abs/2507.11306

P.808 Multilingual Speech Enhancement Testing: Approach and Results of URGENT 2025 Challenge
In speech quality estimation for speech enhancement (SE) systems, subjective listening tests so far are considered as the gold standard. This should be even more true considering the large influx of new generative or hybrid methods into the field, revealing issues of some objective metrics. Efforts such as the Interspeech 2025 URGENT Speech Enhancement Challenge also involving non-English datasets add the aspect of multilinguality to the testing procedure. In this paper, we provide a brief reca…

Exact renormalisation for patch frequencies in inflation systems
Jan Maz\'a\v{c}
https://arxiv.org/abs/2507.07753 https://arxiv.o…

Exact renormalisation for patch frequencies in inflation systems
This note provides an explicit way of calculating the patch frequencies in geometric realisations of primitive substitutions using exact renormalisation relations. Further, we profit from these results to obtain the patch frequencies in the symbolic case as well as in other suspensions (under mild assumptions on the substitution). We illustrate this procedure on the Fibonacci example.

Implementation of Wildberger's Polyseries
Mahdi-Tahar Brahimi
https://arxiv.org/abs/2507.04231 https://arxiv.org/pdf/2507.04231…

Implementation of Wildberger's Polyseries
We study the computational framework of polyseries and poly-numbers introduced by Wildberger and Rubine in [2]. After reviewing Peano arithmetic, computable naturals, and non-standard models, we define the core data and procedure operations on polyseries. We then apply Catalan number expansions to solve quadratic congruences and derive explicit truncated series formulas in a finite field $\mathbb{Z}_p$. Our main result gives a closed form poly series solution in terms of Catalan numbers.

Kernel-based Greedy Approximation of Parametric Elliptic Boundary Value Problems
Bernard Haasdonk, Gabriele Santin, Tizian Wenzel
https://arxiv.org/abs/2507.06731

Kernel-based Greedy Approximation of Parametric Elliptic Boundary Value Problems
We recently introduced a scale of kernel-based greedy schemes for approximating the solutions of elliptic boundary value problems. The procedure is based on a generalized interpolation framework in reproducing kernel Hilbert spaces and was coined PDE-$β$-greedy procedure, where the parameter $β\geq 0$ is used in a greedy selection criterion and steers the degree of function adaptivity. Algebraic convergence rates have been obtained for Sobolev-space kernels and solutions of finite smoothness.…

A Two-step Estimating Approach for Heavy-tailed AR Models with General Non-zero Median Noises
Rui She, Linlin Dai, Shiqing Ling
https://arxiv.org/abs/2506.11509

A Two-step Estimating Approach for Heavy-tailed AR Models with General Non-zero Median Noises
This paper develops a novel two-step estimating procedure for heavy-tailed AR models with non-zero median noises, allowing for time-varying volatility. We first establish the self-weighted quantile regression estimator (SQE) across all quantile levels $τ\in (0,1)$ for the AR parameters $θ_{0}$. We show that the SQE, minus a bias, converges weakly to a Gaussian process uniformly at a rate of $n^{-1/2}$. The bias is zero if and only if $τ$ equals $τ_{0}$, the probability that the noise is l…

MAMBO: High-Resolution Generative Approach for Mammography Images
Milica \v{S}kipina, Nikola Jovi\v{s}i\'c, Nicola Dall'Asen, Vanja \v{S}venda, Anil Osman Tur, Slobodan Ili\'c, Elisa Ricci, Dubravko \'Culibrk
https://arxiv.org/abs/2506.08677

MAMBO: High-Resolution Generative Approach for Mammography Images
Mammography is the gold standard for the detection and diagnosis of breast cancer. This procedure can be significantly enhanced with Artificial Intelligence (AI)-based software, which assists radiologists in identifying abnormalities. However, training AI systems requires large and diverse datasets, which are often difficult to obtain due to privacy and ethical constraints. To address this issue, the paper introduces MAMmography ensemBle mOdel (MAMBO), a novel patch-based diffusion approach des…

Polyadic encryption
Steven Duplij, Qiang Guo
https://arxiv.org/abs/2507.05683 https://arxiv.org/pdf/2507.05683

Polyadic encryption
A novel original procedure of encryption/decryption based on the polyadic algebraic structures and on signal processing methods is proposed. First, we use signals with integer amplitudes to send information. Then we use polyadic techniques to transfer the plaintext into series of special integers. The receiver restores the plaintext using special rules and systems of equations.

Perturbative K\"ahler Moduli Inflation
Mishaal Hai, Ahmed Rakin Kamal, Noshin Ferdous Shamma, Md Shaikot Jahan Shuvo
https://arxiv.org/abs/2506.08083 …

Perturbative Kähler Moduli Inflation
In this work, we present two classes of inflationary models in the framework of type IIB string theory. The inflatons correspond to blow-up Kähler modulus arising from compactifying type IIB on a Calabi-Yau. Using perturbative corrections, we first highlight a procedure for stabilising more than one Kähler modulus. For the case of two Kähler moduli, we explicitly construct two class of inflationary potentials within the Kähler cone which satisfy both EFT and cosmological constraints. The fi…

Effective criteria for entanglement witnesses in small dimensions
{\L}ukasz Grzelka, {\L}ukasz Skowronek, Karol \.Zyczkowski
https://arxiv.org/abs/2506.09298

Effective criteria for entanglement witnesses in small dimensions
We present an effective set of necessary and sufficient criteria for block-positivity of matrices of order $4$ over $\mathbb{C}$. The approach is based on Sturm sequences and quartic polynomial positivity conditions presented in recent literature. The procedure allows us to test whether a given $4\times 4$ complex matrix corresponds to an entanglement witness, and it is exact when the matrix coefficients belong to the rationals, extended by $\mathrm{i}$. The method can be generalized to $\mathc…

Minimal Order Recovery through Rank-adaptive Identification
Fr\'ed\'eric Zheng, Yassir Jedra, Alexandre Prouti\`ere
https://arxiv.org/abs/2506.08720

Minimal Order Recovery through Rank-adaptive Identification
This paper addresses the problem of identifying linear systems from noisy input-output trajectories. We introduce Thresholded Ho-Kalman, an algorithm that leverages a rank-adaptive procedure to estimate a Hankel-like matrix associated with the system. This approach optimally balances the trade-off between accurately inferring key singular values and minimizing approximation errors for the rest. We establish finite-sample Frobenius norm error bounds for the estimated Hankel matrix. Our algorithm…

A potential-theoretic approach to optimal stopping in a spectrally L\'evy Model
Masahiko Egami, Tomohiro Koike
https://arxiv.org/abs/2506.10538 https:/…

A potential-theoretic approach to optimal stopping in a spectrally Lévy Model
We present a systematic solution method for optimal stopping problem of one-dimensional spectrally negative Lévy processes. Our main tools are based on potential theory, particularly the Riesz decomposition and the maximum principle. This novel approach allows us to handle a broad class of reward functions. That is, we solve the problem in a general setup without relying on specific form of the reward function or on the fluctuation identities. We provide a step-by-step solution procedure, whic…

This https://arxiv.org/abs/2501.14478 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

Alignment and optical verification of DESHIMA 2.0 at ASTE
We developed, characterized, and verified an alignment procedure for the DESHIMA 2.0 instrument, an ultra wide-band spectrometer operating between 200--400 GHz, at the ASTE telescope. To this end, we mounted the warm optics, consisting of a modified Dragonian dual reflector system, on a motor controlled hexapod. Crucial in the alignment procedure is our sky chopper, which allows fast beam switching. It has a small entrance and exit aperture coupling to (cold) sky, which creates a measurable sig…

Inference on the value of linear programs
Leonard Goff, Eric Mbakop
https://arxiv.org/abs/2506.06776 https://arxiv.org/pdf/2506.06776…

Inference on the value of linear programs
This paper studies inference on the value of linear programs (LPs) when both the objective function and constraints are possibly unknown and must be estimated from data. We show that many inference problems in partially identified models can be reformulated in this way. Building on Shapiro (1991) and Fang and Santos (2019), we develop a pointwise valid inference procedure for the value of LPs. We modify this pointwise inference procedure to construct one-sided inference procedures that are unif…

Classification of Extremal Dependence in Financial Markets via Bootstrap Inference
Qian Hui, Sidney I. Resnick, Tiandong Wang
https://arxiv.org/abs/2506.04656

Classification of Extremal Dependence in Financial Markets via Bootstrap Inference
Accurately identifying the extremal dependence structure in multivariate heavy-tailed data is a fundamental yet challenging task, particularly in financial applications. Following a recently proposed bootstrap-based testing procedure, we apply the methodology to absolute log returns of U.S. S&P 500 and Chinese A-share stocks over a time period well before the U.S. election in 2024. The procedure reveals more isolated clustering of dependent assets in the U.S. economy compared with China which e…

Double neutral-current corrections to NLO electroweak leptonic cross sections
Stefano Frixione, Fabio Maltoni, Davide Pagani, Marco Zaro
https://arxiv.org/abs/2506.10732

Double neutral-current corrections to NLO electroweak leptonic cross sections
We present a method for improving next-to-leading order electroweak (EW) predictions for lepton-scattering processes by consistently including double neutral-current corrections arising from vector-boson-fusion topologies, which are formally of higher order. By combining, in a process-independent manner, exact fixed-order results, collinear resummation of QED radiation, and a subtraction procedure, we obtain results which are gauge invariant and valid in the entire phase space, retain any depen…

Asymptotic Normality of Infinite Centered Random Forests -Application to Imbalanced Classification
Moria Mayala (LPSM), Erwan Scornet (LPSM), Charles Tillier (LMV), Olivier Wintenberger (LPSM)
https://arxiv.org/abs/2506.08548

Asymptotic Normality of Infinite Centered Random Forests -Application to Imbalanced Classification
Many classification tasks involve imbalanced data, in which a class is largely underrepresented. Several techniques consists in creating a rebalanced dataset on which a classifier is trained. In this paper, we study theoretically such a procedure, when the classifier is a Centered Random Forests (CRF). We establish a Central Limit Theorem (CLT) on the infinite CRF with explicit rates and exact constant. We then prove that the CRF trained on the rebalanced dataset exhibits a bias, which can be r…

Cauchy Data for 1D singular Schr\"odinger operators
Luc Hillairet, Jeremy L. Marzuola
https://arxiv.org/abs/2507.05772 https://a…

Cauchy Data for 1D singular Schrödinger operators
We study semiclassical 1D Schrödinger operators with a power-like singularity at $0$. We show that WKB expansions can be extended on any interval of the form [h^{1-},b]. Using a different approximation near 0 and a matching procedure we obtain an asymptotic expansion for the Cauchy Data at 0 of such WKB solutions that involves non-integer powers of h.

Coarse-graining dynamics to maximize irreversibility
Qiwei Yu, Matthew P. Leighton, Christopher W. Lynn
https://arxiv.org/abs/2506.01909 https://

Coarse-graining dynamics to maximize irreversibility
In many far-from-equilibrium biological systems, energy injected by irreversible processes at microscopic scales propagates to larger scales to fulfill important biological functions. But given dissipative dynamics at the microscale, how much irreversibility can persist at the macroscale? Here, we propose a model-free coarse-graining procedure that merges microscopic states to minimize the amount of lost irreversibility. Beginning with dynamical measurements, this procedure produces coarse-grai…

On ADEG-polyhedra in hyperbolic spaces
Naomi Bredon
https://arxiv.org/abs/2507.05153 https://arxiv.org/pdf/2507.05153

On ADEG-polyhedra in hyperbolic spaces
In this paper, we establish that the non-zero dihedral angles of hyperbolic Coxeter polyhedra of large dimensions are not arbitrarily small. Namely, for dimensions $n\geq 32$, they are of the form $\fracπ{m}$ with $m\leq 6$. Moreover, this property holds in all dimensions $n\geq 7$ for Coxeter polyhedra with mutually intersecting facets. Then, we develop a constructive procedure tailored to Coxeter polyhedra with prescribed dihedral angles, from which we derive the complete classification of A…

AURA-CVC: Autonomous Ultrasound-guided Robotic Assistance for Central Venous Catheterization
Deepak Raina, Lidia Al-Zogbi, Brian Teixeira, Vivek Singh, Ankur Kapoor, Thorsten Fleiter, Muyinatu A. Lediju Bell, Vinciya Pandian, Axel Krieger
https://arxiv.org/abs/2507.05979

AURA-CVC: Autonomous Ultrasound-guided Robotic Assistance for Central Venous Catheterization
Purpose: Central venous catheterization (CVC) is a critical medical procedure for vascular access, hemodynamic monitoring, and life-saving interventions. Its success remains challenging due to the need for continuous ultrasound-guided visualization of a target vessel and approaching needle, which is further complicated by anatomical variability and operator dependency. Errors in needle placement can lead to life-threatening complications. While robotic systems offer a potential solution, achiev…

This https://arxiv.org/abs/2311.16593 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Empowering COVID-19 Detection: Optimizing Performance Through Fine-Tuned EfficientNet Deep Learning Architecture
The worldwide COVID-19 pandemic has profoundly influenced the health and everyday experiences of individuals across the planet. It is a highly contagious respiratory disease requiring early and accurate detection to curb its rapid transmission. Initial testing methods primarily revolved around identifying the genetic composition of the coronavirus, exhibiting a relatively low detection rate and requiring a time-intensive procedure. To address this challenge, experts have suggested using radiolo…

This https://arxiv.org/abs/2305.02313 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hept…

From 5d Flat Connections to 4d Fluxes (the Art of Slicing the Cone)
We compute the Coulomb branch partition function of the 4d $\mathcal{N}=2$ vector multiplet on closed simply-connected quasi-toric manifolds $B$. This includes a large class of theories, localising to either instantons or anti-instantons at the torus fixed points (including Donaldson-Witten and Pestun-like theories as examples). The main difficulty is to obtain flux contributions from the localisation procedure. We achieve this by taking a detour via the 5d $\mathcal{N}=1$ vector multiplet on c…

Exploring Noncommutative Polynomial Equation Methods for Discrete-Time Quaternionic Control
Michael Sebek
https://arxiv.org/abs/2506.08034 https://

Exploring Noncommutative Polynomial Equation Methods for Discrete-Time Quaternionic Control
We present new polynomial-based methods for discrete-time quaternionic systems, highlighting how noncommutative multiplication modifies classical control approaches. Defining quaternionic polynomials via a backward-shift operator, we examine left and right fraction representations of transfer functions, showing that right zeros correspond to similarity classes of quaternionic matrix right eigenvalues. We then propose a feedback design procedure that generalizes pole placement to quaternions - a…

Non-uniform time-stepping in k-space pseudospectral time domain models of acoustic propagation
Matthew J. King, B. E. Treeby, B. T. Cox
https://arxiv.org/abs/2507.07635

Non-uniform time-stepping in k-space pseudospectral time domain models of acoustic propagation
Non-uniform time stepping in acoustic propagation models can be used to preserve accuracy or reduce computational cost for an acoustic simulation with a wave front propagating through a domain with both heterogeneous and homogenous regions, such as for a simulation of breast ultrasound tomography. The k-space correction already exist within the literature to remove numerical dispersion caused by the time stepping procedure in pseudo-spectral time domain models, but requires a uniform time step.…

A weighted quantum ensemble of homogeneous quantum classifiers
Emiliano Tolotti, Enrico Blanzieri, Davide Pastorello
https://arxiv.org/abs/2506.07810 https…

A weighted quantum ensemble of homogeneous quantum classifiers
Ensemble methods in machine learning aim to improve prediction accuracy by combining multiple models. This is achieved by ensuring diversity among predictors to capture different data aspects. Homogeneous ensembles use identical models, achieving diversity through different data subsets, and weighted-average ensembles assign higher influence to more accurate models through a weight learning procedure. We propose a method to achieve a weighted homogeneous quantum ensemble using quantum classifie…

This https://arxiv.org/abs/2503.00555 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

Safety Tax: Safety Alignment Makes Your Large Reasoning Models Less Reasonable
Safety alignment is an important procedure before the official deployment of a Large Language Model (LLM). While safety alignment has been extensively studied for LLM, there is still a large research gap for Large Reasoning Models (LRMs) that equip with improved reasoning capability. We in this paper systematically examine a simplified pipeline for producing safety aligned LRMs. With our evaluation of various LRMs, we deliver two main findings: i) Safety alignment can be done upon the LRM to re…

This https://arxiv.org/abs/2306.01952 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Online Control with Adversarial Disturbance for Continuous-time Linear Systems
We study online control for continuous-time linear systems with finite sampling rates, where the objective is to design an online procedure that learns under non-stochastic noise and performs comparably to a fixed optimal linear controller. We present a novel two-level online algorithm, by integrating a higher-level learning strategy and a lower-level feedback control strategy. This method offers a practical and robust solution for online control, which achieves sublinear regret. Our work provi…

Higher-Order Newton-Cartan Gravity
Biel Cardona, Luca Romano
https://arxiv.org/abs/2507.05489 https://arxiv.org/pdf/2507.05489…

Higher-Order Newton-Cartan Gravity
We study the non-relativistic Newton-Cartan limit of higher-order gravity theories in arbitrary dimensions. We first study it at the level of the action by introducing an additional 1-form gauge field and coupling it appropriately to the gravity sector. We extend this procedure to any theory whose Lagrangian is a function of the Ricci scalar, quadratic Ricci tensor and quadratic Riemann tensor. We also study the limit of the equations of motion for two models, Einstein-Gauss-Bonnet gravity and …

Uncovering Neuroimaging Biomarkers of Brain Tumor Surgery with AI-Driven Methods
Carmen Jimenez-Mesa, Yizhou Wan, Guilio Sansone, Francisco J. Martinez-Murcia, Javier Ramirez, Pietro Lio, Juan M. Gorriz, Stephen J. Price, John Suckling, Michail Mamalakis
https://arxiv.org/abs/2507.04881 …

Uncovering Neuroimaging Biomarkers of Brain Tumor Surgery with AI-Driven Methods
Brain tumor resection is a complex procedure with significant implications for patient survival and quality of life. Predictions of patient outcomes provide clinicians and patients the opportunity to select the most suitable onco-functional balance. In this study, global features derived from structural magnetic resonance imaging in a clinical dataset of 49 pre- and post-surgery patients identified potential biomarkers associated with survival outcomes. We propose a framework that integrates Ex…

This https://arxiv.org/abs/2407.09207 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hepp…

Quantification of the low-$p_{\rm T}$ pion excess in heavy-ion collisions at the LHC and top RHIC energy
While the abundances of the final state hadrons in relativistic heavy-ion collisions are rather well described by the thermal particle production, the shape of the transverse momentum, $p_{\rm T}$, distribution below $p_{\rm T}\approx500$ MeV$/c$, is still poorly understood. We propose a procedure to quantify the model-to-data differences using Bayesian inference techniques, which allows for consistent treatment of the experimental uncertainties and tests the completeness of the available hydro…

Guidelines for LASSO and derivatives use under different dependence and scale structures
Laura Freijeiro-Gonz\'alez, Manuel Febrero-Bande, Wenceslao Gonz\'alez-Manteiga
https://arxiv.org/abs/2506.08582

Guidelines for LASSO and derivatives use under different dependence and scale structures
In a multivariate linear regression model with $p>1$ covariates, implementation of penalization techniques often implies a preliminary univariate standardization step. Although this prevents scale effects on the covariates selection procedure, possible dependence structures can be disrupted, leading to wrong results. This is particularly challenging in high-dimensional settings where $p \geq n$. In this paper, we analyze the standardization effect on the LASSO for different dependence-scales co…

Electroweak splitting functions in the Standard Model and beyond
Stefan Dittmaier, Max Reyer
https://arxiv.org/abs/2507.06568 https://

Electroweak splitting functions in the Standard Model and beyond
We derive quasi-collinear factorization formulas in generic spontaneously broken gauge theories with scalars, fermions, and vector bosons. Specifically, we obtain polarized leading-order splitting functions for all possible final-state and initial-state 1->2 processes in the considered gauge theory. The main complication lies in the presence of mass-singular terms in longitudinal polarization vectors, prohibiting the direct application of the usual factorization procedure known from Quantum Ele…

Conformal Link Prediction with False Discovery Rate Control
Wenqin Du, Wanteng Ma, Dong Xia, Yuan Zhang, Wen Zhou
https://arxiv.org/abs/2507.07025 https://…

Conformal Link Prediction with False Discovery Rate Control
We propose a new method for predicting multiple missing links in partially observed networks while controlling the false discovery rate (FDR), a largely unresolved challenge in network analysis. The main difficulty lies in handling complex dependencies and unknown, heterogeneous missing patterns. We introduce conformal link prediction ({\tt clp}), a distribution-free procedure grounded in the exchangeability structure of weighted graphon models. Our approach constructs conformal p-values via a …