Tootfinder

Enhanced Ideal Objective Vector Estimation for Evolutionary Multi-Objective Optimization
Ruihao Zheng, Zhenkun Wang, Yin Wu, Maoguo Gong
https://arxiv.org/abs/2505.21903

Enhanced Ideal Objective Vector Estimation for Evolutionary Multi-Objective Optimization
The ideal objective vector, which comprises the optimal values of the $m$ objective functions in an $m$-objective optimization problem, is an important concept in evolutionary multi-objective optimization. Accurate estimation of this vector has consistently been a crucial task, as it is frequently used to guide the search process and normalize the objective space. Prevailing estimation methods all involve utilizing the best value concerning each objective function achieved by the individuals in…

So look, if you talk to me about the job threat from the things we currently call “AI,” well…
…if where you’re going with that is “The concentration of wealth is an existential crisis! Establish UBI! 99% marginal tax rate! Capital gains tax! Wealth tax! Abolish billionaires!” then yes, I’m •all• ears. My pitchfork is already sharpened.
But if where you’re going is “Get in on it now while you still can! Buy the AI vendors’ products! Drink radium for that youthful glow!” then…kthanksbye. I am not going to be a vector for your marketing propaganda, no matter how agitated you are.
/end

Enhanced Ideal Objective Vector Estimation for Evolutionary Multi-Objective Optimization
Ruihao Zheng, Zhenkun Wang, Yin Wu, Maoguo Gong
https://arxiv.org/abs/2505.21903

Enhanced Ideal Objective Vector Estimation for Evolutionary Multi-Objective Optimization
The ideal objective vector, which comprises the optimal values of the $m$ objective functions in an $m$-objective optimization problem, is an important concept in evolutionary multi-objective optimization. Accurate estimation of this vector has consistently been a crucial task, as it is frequently used to guide the search process and normalize the objective space. Prevailing estimation methods all involve utilizing the best value concerning each objective function achieved by the individuals in…

Last week, we continued our #ISE2025 lecture on distributional semantics with the introduction of neural language models (NLMs) and compared them to traditional statistical n-gram models.
Benefits of NLMs:
- Capturing Long-Range Dependencies
- Computational and Statistical Tractability
- Improved Generalisation
- Higher Accuracy
@…

Mixture of Encoders is a vector-native alternative that models both structured and unstructured data in a unified embedding space. Join Filip Makraduli as he introduces the method, demonstrates how it powers natural language search and real-time recommendations, and shares open-source tools and benchmarks for replacing complex hybrid stacks.
Learn more:

Vector-valued Graph Signal Processing
Antonio Caputo
https://arxiv.org/abs/2505.22325 https://arxiv.org/pdf/2505.22325

Vector-valued Graph Signal Processing
Classical graph signal processing (GSP) introduces methodologies for analyzing real or complex signals defined on graph domains, moving beyond classical uniform sampling techniques, such as the graph discrete Fourier transform (GDFT), employed as a pivotal tool for transforming graph signals into their spectral representation, enabling effective signal processing techniques such as filtering and denoising. In this paper, we propose a possible generalization of the set of signals and we study so…

Filter-Centric Vector Indexing: Geometric Transformation for Efficient Filtered Vector Search
Alireza Heidari, Wei Zhang
https://arxiv.org/abs/2506.15987 h…

Filter-Centric Vector Indexing: Geometric Transformation for Efficient Filtered Vector Search
The explosive growth of vector search applications demands efficient handling of combined vector similarity and attribute filtering; a challenge where current approaches force an unsatisfying choice between performance and accuracy. We introduce Filter-Centric Vector Indexing (FCVI), a novel framework that transforms this fundamental trade-off by directly encoding filter conditions into the vector space through a mathematically principled transformation $ψ(v, f, α)$. Unlike specialized soluti…

"It's this brutal fragility of vector stacks — which are used by most modern computer languages — which makes software people so wary of fully exploiting the beauty and power of recursion, and I really think that's a shame"
#Lisp

Huch, Quer (BR) nutzt in einem Beitrag nicht GoogleMaps, sondern Maptiler (OpenStreetMap) (#openstreetmap

So look, if you talk to me about the job threat from the things we currently call “AI,” well…
…if where you’re going with that is “The concentration of wealth is an existential crisis! Establish UBI! 99% marginal tax rate! Capital gains tax! Wealth tax! Abolish billionaires!” then yes, I’m •all• ears. My pitchfork is already sharpened.
But if where you’re going is “Get in on it now while you still can! Buy the AI vendors’ products! Drink radium for that youthful glow!” then…kthanksbye. I am not going to be a vector for your marketing propaganda, no matter how agitated you are.
/end

This https://arxiv.org/abs/2503.10126 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

An LiGME Regularizer of Designated Isolated Minimizers -- An Application to Discrete-Valued Signal Estimation
For a regularized least squares estimation of discrete-valued signals, we propose a Linearly involved Generalized Moreau Enhanced (LiGME) regularizer, as a nonconvex regularizer, of designated isolated minimizers. The proposed regularizer is designed as a Generalized Moreau Enhancement (GME) of the so-called sum-of-absolute-values (SOAV) convex regularizer. Every candidate vector in the discrete-valued set is aimed to be assigned to an isolated local minimizer of the proposed regularizer while …

Efficient Precision-Scalable Hardware for Microscaling (MX) Processing in Robotics Learning
Stef Cuyckens, Xiaoling Yi, Nitish Satya Murthy, Chao Fang, Marian Verhelst
https://arxiv.org/abs/2505.22404

Efficient Precision-Scalable Hardware for Microscaling (MX) Processing in Robotics Learning
Autonomous robots require efficient on-device learning to adapt to new environments without cloud dependency. For this edge training, Microscaling (MX) data types offer a promising solution by combining integer and floating-point representations with shared exponents, reducing energy consumption while maintaining accuracy. However, the state-of-the-art continuous learning processor, namely Dacapo, faces limitations with its MXINT-only support and inefficient vector-based grouping during backpro…

More about solutions of quadratic equations
Wolf-Dieter Richter
https://arxiv.org/abs/2506.20429 https://arxiv.org/pdf/2506.20429

More about solutions of quadratic equations
For polynomials of degree two which have no zeros, the method of accompanying variables is developed and zeros of associated vector polynomials are determined. Our flexible method uses a wide variety of possible vector-valued vector squaring methods and can be adopted to a wide variety of application situations. Known solutions are made much more precise by replacing the imaginary component and supplemented by introducing a whole class of new vector solutions. Circular, generalized circular and…

This https://arxiv.org/abs/2406.11369 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCG_…

Approximation Algorithms for Smallest Intersecting Balls
We study a general smallest intersecting ball problem and its soft-margin variant in high-dimensional Euclidean spaces for input objects that are compact and convex. These two problems link and unify a series of fundamental problems in computational geometry and machine learning, including smallest enclosing ball, polytope distance, intersection radius, $\ell_1$-loss support vector machine, $\ell_1$-loss support vector data description, and so on. Leveraging our novel framework for solving zero…

Vo-Ve: An Explainable Voice-Vector for Speaker Identity Evaluation
Jaejun Lee, Kyogu Lee
https://arxiv.org/abs/2506.19446 https://arx…

Vo-Ve: An Explainable Voice-Vector for Speaker Identity Evaluation
In this paper, we propose Vo-Ve, a novel voice-vector embedding that captures speaker identity. Unlike conventional speaker embeddings, Vo-Ve is explainable, as it contains the probabilities of explicit voice attribute classes. Through extensive analysis, we demonstrate that Vo-Ve not only evaluates speaker similarity competitively with conventional techniques but also provides an interpretable explanation in terms of voice attributes. We strongly believe that Vo-Ve can enhance evaluation schem…

This https://arxiv.org/abs/2504.19731 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Tian's theorem for Grassmannian embeddings and degeneracy sets of random sections
Let $(X,ω)$ be a compact Kähler manifold, $(L,h^L)$ be a positive line bundle, and $(E,h^E)$ be a Hermitian holomorphic vector bundle of rank $r$ on $X$. We prove that the pullback by the Kodaira embedding associated to $L^p\otimes E$ of the $k$-th Chern class of the dual of the universal bundle over the Grassmannian converges as $p\to\infty$ to the $k$-th power of the Chern form $c_1(L,h^L)$, for $0\leq k\leq r$. If $c_1(L,h^L)=ω$ we also determine the second term in the semiclassical expan…

Multidimensional vector-valued Laplace transform and applications
Marko Kostic
https://arxiv.org/abs/2506.18909 https://arxiv.org/pdf…

Multidimensional vector-valued Laplace transform and applications
In this paper, we introduce and analyze multidimensional vector-valued Laplace transform of functions with values in sequentially complete locally convex spaces. A great number of our results seem to be new even for the functions with values in Banach spaces. We provide several new applications of multidimensional vector-valued Laplace transform to the abstract Volterra integro-differential inclusions with multiple variables, as well.

Numerical asymptotics of near-axis expansions of quasisymmetric magnetohydrostatic equilibria with anisotropic pressure
Lanke Fu, Eduardo Rodriguez, Rory Conlin, Amitava Bhattacharjee
https://arxiv.org/abs/2505.20475

Numerical asymptotics of near-axis expansions of quasisymmetric magnetohydrostatic equilibria with anisotropic pressure
Quasisymmetry (QS) is a property of special magnetic configurations, where the magnetic field strength, but not necessarily the full vector field, has a direction of symmetry. QS leads to reduced neoclassical transport and thus can be a desirable property in stellarator design. The Garren-Boozer (GB) conundrum has been interpreted to mean that globally quasisymmetric magnetohydrostatic (MHS) equilibria, other than axisymmetric solutions, with isotropic pressure do not exist. When expanded as po…

Maximal Matching Matters: Preventing Representation Collapse for Robust Cross-Modal Retrieval
Hani Alomari, Anushka Sivakumar, Andrew Zhang, Chris Thomas
https://arxiv.org/abs/2506.21538

Maximal Matching Matters: Preventing Representation Collapse for Robust Cross-Modal Retrieval
Cross-modal image-text retrieval is challenging because of the diverse possible associations between content from different modalities. Traditional methods learn a single-vector embedding to represent semantics of each sample, but struggle to capture nuanced and diverse relationships that can exist across modalities. Set-based approaches, which represent each sample with multiple embeddings, offer a promising alternative, as they can capture richer and more diverse relationships. In this paper,…

Modern applications require search capabilities that go beyond basic text matching. They must be fast, accurate, personalised and context-aware. At this year's Berlin Buzzwords, Saurabh Singh will demonstrate how OpenSearch’s latest AI/ML enhancements and engine improvements enable organisations to build intelligent, scalable search experiences that meet these evolving needs.
Learn more:

From Search to Insight: Leveraging OpenSearch for Scalable, AI-Driven Search Experiences
Observability, log analytics, GenAI systems, and RAG pipelines must query massive volumes of semantic embeddings to retrieve relevant content instantly. Today’s search systems often fall short in handling high-dimensional vector data and similarity search. OpenSearch 3.0 brings significant architectural improvements to address these challenges. Integrating Apache Lucene 10 and JVM 21, the platform delivers 20% faster queries than its 2.x predecessor and 10× the throughput of 1.x versions. Ne…

Probing the Higgs boson CP properties in vector-boson fusion production in the $H\rightarrow\tau^ \tau^-$ channel with the ATLAS detector
ATLAS Collaboration
https://arxiv.org/abs/2506.19395

Probing the Higgs boson CP properties in vector-boson fusion production in the $H\rightarrowτ^+τ^-$ channel with the ATLAS detector
The CP properties of the Higgs boson are studied in the vector-boson fusion production mode. The analysis exploits the decay mode of the Higgs boson into two $τ$-leptons using 140 fb$^{-1}$ of proton-proton collision data at $\sqrt{s}=13$ TeV collected by the ATLAS experiment at the Large Hadron Collider. Results are obtained using the Optimal Observable method. CP-violating interactions between the Higgs boson and electroweak gauge bosons are considered in the effective field theory framework…

PDE methods for extracting normal vector fields and distance functions of shapes
Takahiro Hasebe, Jun Masamune, Hiroshi Teramoto, Takayuki Yamada
https://arxiv.org/abs/2506.19323 …

PDE methods for extracting normal vector fields and distance functions of shapes
Partial differential equations can be used for extracting geometric features of shapes. This article summarizes recent methods to extract the normal vector field from an elliptic equation proposed by Yamada and from the heat equation, and also a method to extract the (signed) distance function from an elliptic equation that generalizes Varadhan's in 1967.

Borrowing on Belief? Consumer Confidence and U.S. Credit -- A VECM Study
Samiha Tariq, Weikang Zhang
https://arxiv.org/abs/2505.21832 https://

Borrowing on Belief? Consumer Confidence and U.S. Credit -- A VECM Study
This study explores the interdependent relationship between consumer credit and consumer confidence in the United States using monthly data from January 1978 to August 2024. Utilizing a Vector Error Correction Model (VECM), the analysis focuses on the interplay between household borrowing behaviour and consumer sentiment while controlling for macroeconomic factors such as interest rates, inflation, unemployment, and money supply. The results reveal a stable long-run equilibrium: heightened cons…

Linear codes arising from the point-hyperplane geometry-Part I: the Segre embedding
Ilaria Cardinali, Luca Giuzzi
https://arxiv.org/abs/2506.21309 https://…

Linear codes arising from the point-hyperplane geometry-Part I: the Segre embedding
Let $V$ be a vector space over the finite field $\mathbb{F}_q$ with $q$ elements and $Λ$ be the image of the Segre geometry $\mathrm{PG}(V)\otimes\mathrm{PG}(V^*)$ in $\mathrm{PG}(V\otimes V^*)$. Consider the subvariety $Λ_{1}$ of $Λ$ represented by the pure tensors $x\otimes ξ$ with $x\in V$ and $ξ\in V^*$ such that $ξ(x)=0$. Regarding $Λ_1$ as a projective system of $\mathrm{PG}(V\otimes V^*)$, we study the linear code $\mathcal{C}(Λ_1)$ arising from it. The code $\mathcal{C}(Λ_1)$ i…

jina-embeddings-v4: Universal Embeddings for Multimodal Multilingual Retrieval
Michael G\"unther, Saba Sturua, Mohammad Kalim Akram, Isabelle Mohr, Andrei Ungureanu, Sedigheh Eslami, Scott Martens, Bo Wang, Nan Wang, Han Xiao
https://arxiv.org/abs/2506.18902

jina-embeddings-v4: Universal Embeddings for Multimodal Multilingual Retrieval
We introduce jina-embeddings-v4, a 3.8 billion parameter multimodal embedding model that unifies text and image representations through a novel architecture supporting both single-vector and multi-vector embeddings in the late interaction style. The model incorporates task-specific Low-Rank Adaptation (LoRA) adapters to optimize performance across diverse retrieval scenarios, including query-based information retrieval, cross-modal semantic similarity, and programming code search. Comprehensive…

Linearithmic Clean-up for Vector-Symbolic Key-Value Memory with Kroneker Rotation Products
Ruipeng Liu, Qinru Qiu, Simon Khan, Garrett E. Katz
https://arxiv.org/abs/2506.15793

Linearithmic Clean-up for Vector-Symbolic Key-Value Memory with Kroneker Rotation Products
A computational bottleneck in current Vector-Symbolic Architectures (VSAs) is the ``clean-up'' step, which decodes the noisy vectors retrieved from the architecture. Clean-up typically compares noisy vectors against a ``codebook'' of prototype vectors, incurring computational complexity that is quadratic or similar. We present a new codebook representation that supports efficient clean-up, based on Kroneker products of rotation-like matrices. The resulting clean-up time complexity is linearithm…

Independent vector analysis -- an introduction for statisticians
Miro Arvila, Klaus Nordhausen, Mika Sipil\"a, Sara Taskinen
https://arxiv.org/abs/2506.16175

Independent vector analysis -- an introduction for statisticians
Blind source separation (BSS), particularly independent component analysis (ICA), has been widely used in various fields of science such as biomedical signal processing to recover latent source signals from the observed mixture. While ICA is typically applied to individual datasets, many real-world applications share underlying sources across datasets. Independent vector analysis (IVA) extends ICA to jointly analyze multiple datasets by exploiting statistical dependencies across them. While var…

Exact vacuum solution with Hopf structure in general relativity
Junpei Harada
https://arxiv.org/abs/2506.20878 https://arxiv.org/pdf/…

Exact vacuum solution with Hopf structure in general relativity
An exact solution to the vacuum Einstein equations is presented, whose structure is based on the Hopf fibration. The solution employs a geodesic null vector field that defines a twisting congruence and appears in the metric in Kerr-Schild form. This solution is of Petrov type D and involves two parameters. Remarkably, the resulting spacetime is regular, with no curvature singularities. Both the Kretschmann scalar and the Chern-Pontryagin scalar are nonzero and remain finite throughout the space…

NLO QCD effects on angular observables in $e^-p \to e^-(\nu_e)Hj$ in presence of non-standard $HVV$ couplings
Biswajit Das, Pramod Sharma, Ambresh Shivaji
https://arxiv.org/abs/2506.21472

NLO QCD effects on angular observables in $e^-p \to e^-(ν_e)Hj$ in presence of non-standard $HVV$ couplings
The single Higgs production in neutral-current (NC) and charged-current (CC) processes at an electron-proton ($ep$) collider is a useful channel to probe new physics effects in the Higgs coupling to vector boson ($HVV$). In this context, observables sensitive to non-standard couplings previously studied at leading order require improved theoretical precision through the inclusion of radiative corrections. In this work, we present a fully differential Higgs plus one jet production at next-to-lea…

Resilience Through Escalation: A Graph-Based PACE Architecture for Satellite Threat Response
Anouar Boumeftah, Sarah McKenzie-Picot, Peter Klimas, Gunes Karabulut Kurt
https://arxiv.org/abs/2506.20882

Resilience Through Escalation: A Graph-Based PACE Architecture for Satellite Threat Response
Satellite systems increasingly face operational risks from jamming, cyberattacks, and electromagnetic disruptions. Traditional redundancy strategies often fail against dynamic, multi-vector threats. This paper introduces a resilience-by-design framework grounded in the PACE (Primary, Alternate, Contingency, Emergency) methodology, originally developed for tactical communications in military operations, adapting it to satellite systems through a layered state-transition model informed by threat …

Dynamic Race Detection With O(1) Samples
Mosaad Al Thokair, Minjian Zhang, Umang Mathur, Mahesh Viswanathan
https://arxiv.org/abs/2506.20127 https://

Dynamic Race Detection With O(1) Samples
Happens before-based dynamic analysis is the go-to technique for detecting data races in large scale software projects due to the absence of false positive reports. However, such analyses are expensive since they employ expensive vector clock updates at each event, rendering them usable only for in-house testing. In this paper, we present a sampling-based, randomized race detector that processes only constantly many events of the input trace even in the worst case. This is the first sub-linear …

Special vector fields on Riemannian manifolds of constant negative sectional curvature and conservation laws
Keti Tenenblat, Alice Barbora Tumpach
https://arxiv.org/abs/2506.14960

Special vector fields on Riemannian manifolds of constant negative sectional curvature and conservation laws
We show that any $n$-dimensional Riemannian manifold with constant negative sectional curvature admits local orthonormal vector fields such that one of them $v_1$ is tangent to geodesics and the other $n-1$ vector fields are tangent to horocycles. We prove that the $1$-form dual to $v_1$ is a closed form. We show how the closed form can be used to obtain conservation laws for PDEs whose generic solutions define metrics on open subsets with constant negative sectional curvature. These results ex…

Cuntz--Pimsner algebras of partial automorphisms twisted by vector bundles II: Nuclear dimension
Aaron Kettner
https://arxiv.org/abs/2506.16630 https://

Cuntz--Pimsner algebras of partial automorphisms twisted by vector bundles II: Nuclear dimension
We show that Cuntz--Pimsner algebras associated to partial automorphisms twisted by vector bundles are classifiable in the sense of the Elliott program whenever the action is minimal and the base space is compact, infinite and has finite covering dimension. We also investigate the tracial state space of our algebras, and show that traces are in bijection to certain conformal measures. This generalizes results about partial crossed products by Geffen and complements results about the $C^*$-algeb…

Two-dimensional greedy randomized Kaczmarz methods for solving large-scale linear systems
Tao Li, Meng-Long Xiao, Xin-Fang Zhang
https://arxiv.org/abs/2506.20940

Two-dimensional greedy randomized Kaczmarz methods for solving large-scale linear systems
In this paper, we consider a novel two-dimensional randomized Kaczmarz method and its improved version with simple random sampling, which chooses two active rows with probability proportional to the square of their cross-product-like constant, for solving large-scale linear systems. From the greedy selection strategy with grasping two larger entries of the residual vector at each iteration, we then devise a two-dimensional greedy randomized Kaczmarz method. To improve the above methods further,…

Replaced article(s) found for stat.ML. https://arxiv.org/list/stat.ML/new
[1/2]:
- Efficient uniform approximation using Random Vector Functional Link networks
Palina Salanevich, Olov Schavemaker

Communication-Efficient Publication of Sparse Vectors under Differential Privacy
Quentin Hillebrand, Vorapong Suppakitpaisarn, Tetsuo Shibuya
https://arxiv.org/abs/2506.20234

Communication-Efficient Publication of Sparse Vectors under Differential Privacy
In this work, we propose a differentially private algorithm for publishing matrices aggregated from sparse vectors. These matrices include social network adjacency matrices, user-item interaction matrices in recommendation systems, and single nucleotide polymorphisms (SNPs) in DNA data. Traditionally, differential privacy in vector collection relies on randomized response, but this approach incurs high communication costs. Specifically, for a matrix with $N$ users, $n$ columns, and $m$ nonzero …

Canard cycles of non-linearly regularized piecewise smooth vector fields
Peter De Maesschalck, Renato Huzak, Otavio Henrique Perez
https://arxiv.org/abs/2506.18099

Canard cycles of non-linearly regularized piecewise smooth vector fields
The main purpose of this paper is to study limit cycles in non-linear regularizations of planar piecewise smooth systems with fold points (or more degenerate tangency points) and crossing regions. We deal with a slow fast Hopf point after non-linear regularization and blow-up. We give a simple criterion for upper bounds and the existence of limit cycles of canard type, expressed in terms of zeros of the slow divergence integral. Using the criterion we can construct a quadratic regularization of…

Hodge-Riemann polynomials
Qing Lu, Weizhe Zheng
https://arxiv.org/abs/2506.16992 https://arxiv.org/pdf/2506.16992

Hodge-Riemann polynomials
We show that Schur classes of ample vector bundles on smooth projective varieties satisfy Hodge--Riemann relations on $H^{p,q}$ under the assumption that $H^{p-2,q-2}$ vanishes. More generally, we study Hodge--Riemann polynomials, which are partially symmetric polynomials that produce cohomology classes satisfying the Hodge--Riemann property when evaluated at Chern roots of ample vector bundles. In the case of line bundles and in bidegree $(1,1)$, these are precisely the nonzero dually Lorentzi…

On sharp stable recovery from clipped and folded measurements
Pedro Abdalla, Daniel Freeman, Jo\~ao P. G. Ramos, Mitchell A. Taylor
https://arxiv.org/abs/2506.20054

On sharp stable recovery from clipped and folded measurements
We investigate the stability of vector recovery from random linear measurements which have been either clipped or folded. This is motivated by applications where measurement devices detect inputs outside of their effective range. As examples of our main results, we prove sharp lower bounds on the recovery constant for both the declipping and unfolding problems whenever samples are taken according to a uniform distribution on the sphere. Moreover, we show such estimates under (almost) the best…

Vector Representations of Vessel Trees
James Batten, Michiel Schaap, Matthew Sinclair, Ying Bai, Ben Glocker
https://arxiv.org/abs/2506.11163 https://

Vector Representations of Vessel Trees
We introduce a novel framework for learning vector representations of tree-structured geometric data focusing on 3D vascular networks. Our approach employs two sequentially trained Transformer-based autoencoders. In the first stage, the Vessel Autoencoder captures continuous geometric details of individual vessel segments by learning embeddings from sampled points along each curve. In the second stage, the Vessel Tree Autoencoder encodes the topology of the vascular network as a single vector r…

Simple smooth modules over the Lie algebras of polynomial vector fields
Zhiqiang Li, Cunguang Cheng, Shiyuan Liu, Rencai Lu, Kaiming Zhao, Yueqiang Zhao
https://arxiv.org/abs/2506.18262

Simple smooth modules over the Lie algebras of polynomial vector fields
Let $\mathfrak{g}:={\rm Der}(\mathbb{C}[t_1, t_2,\cdots, t_n])$ and $\mathcal{L}:={\rm Der}(\mathbb{C}[[t_1, t_2,\cdots, t_n]])$ be the Witt Lie algebras. Clearly, $\mathfrak{g}$ is a proper subalegbra of $\mathcal{L}$. Surprisingly, we prove that simple smooth modules over $\mathfrak{g}$ are exactly the simple modules over $\mathcal{L}$ studied by Rodakov (no need to take completion). Then we find an easy and elementary way to classify all simple smooth modules over $\mathfrak{g}$. When the …

Replaced article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[1/4]:
- A Robust Twin Parametric Margin Support Vector Machine for Multiclass Classification
Renato De Leone, Francesca Maggioni, Andrea Spinelli

Legendre-Gauss-Lobatto Collocation Method for Optimal Control via Polynomial Approximations of Differential Equation Vector Fields
Gabriela Abadia-Doyle, William W. Hager, Anil V. Rao
https://arxiv.org/abs/2506.13938

Legendre-Gauss-Lobatto Collocation Method for Optimal Control via Polynomial Approximations of Differential Equation Vector Fields
A new method is described for solving optimal control problems using direct collocation at Legendre-Gauss-Lobatto points. The approach of this paper employs a polynomial approximation of the right-hand side vector field of the differential equations and leads to the following important outcomes. First, the first-order optimality conditions of the LGL integral form are derived, which lead to a full-rank transformed adjoint system and novel costate estimate. Next, a derivative-like form of the LG…

Deterministic Switching of the N\'{e}el Vector by Asymmetric Spin Torque
Shui-Sen Zhang, Zi-An Wang, Bo Li, Wen-Jian Lu, Mingliang Tian, Yu-Ping Sun, Haifeng Du, Ding-Fu Shao
https://arxiv.org/abs/2506.10786

Deterministic Switching of the Néel Vector by Asymmetric Spin Torque
Néel vector, the order parameter of collinear antiferromagnets, serves as a state variable in associated antiferromagnetic (AFM) spintronic devices to encode information. A deterministic switching of Néel vector is crucial for the write-in operation, which, however, remains a challenging problem in AFM spintronics. Here we demonstrate, based on analytical derivation and macro-spin simulations, that Néel vector switching can be generally achieved via a current-induced spin torque, provided th…

This https://arxiv.org/abs/2405.10282 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

GKLS Vector Field Dynamics for Gaussian States
We construct the vector field associated to the GKLS generator for systems described by Gaussian states. This vector field is defined on the dual space of the algebra of operators, restricted to operators quadratic in position and momentum. It is shown that the GKLS dynamics accepts a decomposition principle, that is, this vector field can be decomposed in three parts, a conservative Hamiltonian component, a gradient-like, and a Choi-Kraus or jump vector field. The two last terms are considered…

Lack-of-fit reduction in the path-integral formalism
Katerina Mlada, Michal Pavelka, Vaclav Klika
https://arxiv.org/abs/2506.20242 https://

Lack-of-fit reduction in the path-integral formalism
We present a reformulation of the lack-of-fit reduction in non-equilibrium thermodynamics using the path-integral formalism. The reformulation is based on the Onsager-Machlup variational principle, and it allows us to minimize the action while keeping only thermodynamically relevant solutions. The reduced evolution consists of a Hamiltonian vector field and a gradient flow. The reformulation is illustrated on the Kac-Zwanzig model, where we show how irreversibility emerges from purely Hamiltoni…

Introduction to the Cohomology of the Flag Variety
Sara C. Billey, Yibo Gao, Brendan Pawlowski
https://arxiv.org/abs/2506.21064 https://

Introduction to the Cohomology of the Flag Variety
One hundred years ago, Hilbert gave a list of important open problems in mathematics. His 15th problem asked for the development of a rigorous calculus explaining Schubert's enumerative results for intersecting varieties defined by rank conditions on vector spaces. Today by way of many contributions in algebraic topology, geometry, and combinatorics, we consider this solved. Yet, deep questions remain about the subtleties of actually carrying out the process. In this chapter, we hope to summari…

A curvilinear framework for vector light fields
Leonardo S. Gonzalez-Aceves, Gabriela Flores-Cova, Blas M. Rodr\'iguez-Lara, Raul I. Hernandez-Aranda, Alfonso Jaimes-Najera, Carmelo Rosales-Guzman, Benjamin Perez-Garcia
https://arxiv.org/abs/2506.11407

A curvilinear framework for vector light fields
Vector beams are often regarded as non-separable superpositions of spatial and polarization degrees of freedom that satisfy the wave equation. This interpretation ties their polarization structure to their spatial shape. Here, we introduce a generalized method to construct vector beams whose structure is entirely encoded in the polarization degree of freedom. Using conformal maps, we construct orthonormal polarization bases from the geometry of the coordinates and encode them experimentally via…

Supervised Similarity for Firm Linkages
Ryan Samson, Adrian Banner, Luca Candelori, Sebastien Cottrell, Tiziana Di Matteo, Paul Duchnowski, Vahagn Kirakosyan, Jose Marques, Kharen Musaelian, Stefano Pasquali, Ryan Stever, Dario Villani
https://arxiv.org/abs/2506.19856

Supervised Similarity for Firm Linkages
We introduce a novel proxy for firm linkages, Characteristic Vector Linkages (CVLs). We use this concept to estimate firm linkages, first through Euclidean similarity, and then by applying Quantum Cognition Machine Learning (QCML) to similarity learning. We demonstrate that both methods can be used to construct profitable momentum spillover trading strategies, but QCML similarity outperforms the simpler Euclidean similarity.

This https://arxiv.org/abs/2504.19332 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Reeb orbits frequently intersecting a symplectic surface
Consider a symplectic surface in a three-dimensional contact manifold with boundary on Reeb orbits (periodic orbits of the Reeb vector field). We assume that the rotation numbers of the boundary Reeb orbits satisfy a certain inequality, and we also make a technical assumption that the Reeb vector field has a particular ``nice'' form near the boundary of the surface. We then show that there exist Reeb orbits which intersect the interior of the surface, with a lower bound on the frequency of thes…

Infinity Search: Approximate Vector Search with Projections on q-Metric Spaces
Antonio Pariente, Ignacio Hounie, Santiago Segarra, Alejandro Ribeiro
https://arxiv.org/abs/2506.06557

Infinity Search: Approximate Vector Search with Projections on q-Metric Spaces
Despite the ubiquity of vector search applications, prevailing search algorithms overlook the metric structure of vector embeddings, treating it as a constraint rather than exploiting its underlying properties. In this paper, we demonstrate that in $q$-metric spaces, metric trees can leverage a stronger version of the triangle inequality to reduce comparisons for exact search. Notably, as $q$ approaches infinity, the search complexity becomes logarithmic. Therefore, we propose a novel projectio…

Gravitational Wave Generation and Detection in Gravitational Quantum Field Theory
Yuan-Kun Gao, Da Huang, Yue-Liang Wu
https://arxiv.org/abs/2506.21225 htt…

Gravitational Wave Generation and Detection in Gravitational Quantum Field Theory
We investigate the production and detection of gravitational waves (GWs) within the framework of Gravitational Quantum Field Theory (GQFT). In this theory, GWs exhibit five propagating modes: one scalar, two vector, and two tensor modes. Unlike General Relativity, the gravitational field equations in GQFT involve both symmetric and antisymmetric tensors, governed by their respective energy-momentum tensors, both of which can act as sources for GW radiation. By solving the linearized gravitation…

A new, updated, streamlined, and generally improved version of The Vector Grounding Problem paper, joint work by @… and me on the meaningfulness or else of LLM outputs and internal representations is now available on ArXiv.

The Vector Grounding Problem
The remarkable performance of large language models (LLMs) on complex linguistic tasks has sparked debate about their capabilities. Unlike humans, these models learn language solely from textual data without directly interacting with the world. Yet they generate seemingly meaningful text on diverse topics. This achievement has renewed interest in the classical `Symbol Grounding Problem' -- the question of whether the internal representations and outputs of symbolic AI systems can possess intrin…

DECA: A Near-Core LLM Decompression Accelerator Supporting Out-of-Order Invocation
Gerasimos Gerogiannis (Intel Corporation,University of Illinois at Urbana-Champaign), Stijn Eyerman (Intel Corporation), Evangelos Georganas (Intel Labs), Wim Heirman (Intel Corporation), Josep Torrellas (University of Illinois at Urbana-Champaign)
https://

DECA: A Near-Core LLM Decompression Accelerator Supporting Out-of-Order Invocation
To alleviate the memory bandwidth bottleneck in Large Language Model (LLM) inference workloads, weight matrices are stored in memory in quantized and sparsified formats. Hence, before tiles of these matrices can be processed by in-core generalized matrix multiplication (GeMM) hardware engines, they need to be dequantized and de-sparsified. This is currently performed in software with vector operations. Unfortunately, this approach delivers only modest performance. Moreover, it is hard to unders…

Is Sparse Matrix Reordering Effective for Sparse Matrix-Vector Multiplication?
Omid Asudeh, Sina Mahdipour Saravani, Gerald Sabin, Fabrice Rastello, P Sadayappan
https://arxiv.org/abs/2506.10356

Is Sparse Matrix Reordering Effective for Sparse Matrix-Vector Multiplication?
This work evaluates the impact of sparse matrix reordering on the performance of sparse matrix-vector multiplication across different multicore CPU platforms. Reordering can significantly enhance performance by optimizing the non-zero element patterns to reduce total data movement and improve the load-balancing. We examine how these gains vary over different CPUs for different reordering strategies, focusing on both sequential and parallel execution. We address multiple aspects, including appro…

This https://arxiv.org/abs/2410.09939 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCG_…

Efficient computations of discrete cubical homology
We present a fast algorithm for computing discrete cubical homology of graphs over finite fields with an appropriate characteristic. This algorithm improves on several computational steps compared to constructions in the existing literature, with the key insights including: a faster way to generate all singular cubes, reducing the dimensions of vector spaces in the chain complex by taking a quotient over automorphisms of the cube, and preprocessing graphs using the axiomatic treatment of discre…

Next stop in our NLP timeline is 2013, the introduction of low dimensional dense word vectors - so-called "word embeddings" - based on distributed semantics, as e.g. word2vec by Mikolov et al. from Google, which enabled representation learning on text.
T. Mikolov et al. (2013). Efficient Estimation of Word Representations in Vector Space.
…

Efficient Estimation of Word Representations in Vector Space
We propose two novel model architectures for computing continuous vector representations of words from very large data sets. The quality of these representations is measured in a word similarity task, and the results are compared to the previously best performing techniques based on different types of neural networks. We observe large improvements in accuracy at much lower computational cost, i.e. it takes less than a day to learn high quality word vectors from a 1.6 billion words data set. Fur…

Spectrum of the Laplacian in waveguide shaped surfaces
Diana C. S. Bello
https://arxiv.org/abs/2506.18875 https://arxiv.org/pdf/2506.…

Spectrum of the Laplacian in waveguide shaped surfaces
Let $-Δ_{\cal S}$ be the Laplace operator in ${\cal S} \subset \mathbb{R}^3$ on a waveguide shaped surfaces, i.e., ${\cal S}$ is built by translating a closed curve in a constant direction along an unbounded spatial curve. Under the condition that the tangent vector of the reference curve admits a finite limit at infinity, we find the essential spectrum of $-Δ_{\cal S}$ and discuss conditions under which discrete eigenvalues emerge. Furthermore, we analyze the Laplacian in the case of a broke…

Robust Anomaly Detection in Network Traffic: Evaluating Machine Learning Models on CICIDS2017
Zhaoyang Xu, Yunbo Liu
https://arxiv.org/abs/2506.19877 https…

Robust Anomaly Detection in Network Traffic: Evaluating Machine Learning Models on CICIDS2017
Identifying suitable machine learning paradigms for intrusion detection remains critical for building effective and generalizable security solutions. In this study, we present a controlled comparison of four representative models - Multi-Layer Perceptron (MLP), 1D Convolutional Neural Network (CNN), One-Class Support Vector Machine (OCSVM) and Local Outlier Factor (LOF) - on the CICIDS2017 dataset under two scenarios: detecting known attack types and generalizing to previously unseen threats. O…

Fair Allocation with Money: What is Your Objective?
Noga Klein Elmalem, Rica Gonen, Erel Segal-Halevi
https://arxiv.org/abs/2506.18794 https://

Fair Allocation with Money: What is Your Objective?
When allocating indivisible items, there are various ways to use monetary transfers for eliminating envy. Particularly, one can apply a balanced vector of transfer payments, or charge each agent a positive amount, or -- contrarily -- give each agent a positive amount as a ``subsidy''. In each model, one can aim to minimize the amount of payments used; this aim translates into different optimization objectives in each setting. This note compares the various models, and the relations between uppe…

Measuring Fractal Dimension using Discrete Global Grid Systems
Pramit Ghosh
https://arxiv.org/abs/2506.18175 https://arxiv.org/pdf/25…

Measuring Fractal Dimension using Discrete Global Grid Systems
This study builds a bridge between two well-studied but distant topics: fractal dimension and Discrete Global Grid System (DGGS). DGGSs are used as covering sets for geospatial vector data to calculate the Minkowski-Bouligand dimension. Using the method on synthetic data yields results within 1% of their theoretical fractal dimensions. A case study on opaque cloud fields obtained from satellite images gives fractal dimension in agreement with that available in the literature. The proposed metho…

Partial Inverse Spectral Problems for Sturm-Liouville Operators with Frozen Arguments on a Star-Shaped Graph
Chung-Tsun Shieh, Tzong-Mo Tsai, Meng-Nien Wu
https://arxiv.org/abs/2506.20569

Partial Inverse Spectral Problems for Sturm-Liouville Operators with Frozen Arguments on a Star-Shaped Graph
This paper is devoted to the study of a partial inverse spectral problem for Sturm-Liouville operators with frozen arguments on a star-shaped graph. The potentials are assumed to be known a priori on all edges except one, and the objective is to reconstruct the unknown potential on the remaining edge using a subset of the spectral data. A constructive algorithm for solving this problem is presented, which relies on the Riesz basis property of a system of vector functions.

Finite temperature Casimir effect of a Lorentz-violating scalar with higher order derivatives
Andrea Erdas
https://arxiv.org/abs/2506.10284 https://…

Finite temperature Casimir effect of a Lorentz-violating scalar with higher order derivatives
In this work I study the finite temperature Casimir effect caused by a complex and massive scalar field that breaks Lorentz invariance in a CPT-even, aether-like manner. The Lorentz invariance breaking is caused by a constant space-like vector directly coupled to higher order field derivatives. This vector needs to be space-like in order to avoid non-causality problems that will arise with a time-like vector. I investigate the two scenarios of the scalar field satisfying either Dirichlet or mix…

Hadronic decays of possible pseudoscalar $P$-wave $D\bar{D}^\ast/\bar{D}D^\ast$ molecular state
Shi-Dong Liu, Qi Wu, Gang Li
https://arxiv.org/abs/2506.18273

Hadronic decays of possible pseudoscalar $P$-wave $D\bar{D}^\ast/\bar{D}D^\ast$ molecular state
Recently, the new structure $G(3900)$ observed by the BESIII collaboration in the $e^+e^-\to D\bar{D}$ was identified to be the $P$-wave $D\bar{D}^\ast/\bar{D}D^\ast$ vector molecular resonance using a unified meson exchange model. Apart from the vector $P$-wave state, a possible pseudoscalar $P$-wave molecular state of the $D\bar{D}^\ast/\bar{D}D^\ast$ (called $G_0(3900)$ for short) was also predicted, which is likely to be observed in the future experiments. Within the molecular framework, we…

Vector bundles on bielliptic surfaces: Ulrich bundles and degree of irrationality
Edoardo Mason
https://arxiv.org/abs/2506.10696 https://

Vector bundles on bielliptic surfaces: Ulrich bundles and degree of irrationality
This paper deals with two problems about vector bundles on bielliptic surfaces. The first is to give a classification of Ulrich bundles on such surfaces $S$, which depends on the topological type of $S$. In doing so, we study the weak Brill-Noether property for moduli spaces of sheaves with isotropic Mukai vector. Adapting an idea of Moretti, we also interpret the problem of determining the degree of irrationality of bielliptic surfaces in terms of the existence of certain stable vector bundles…

Series representation in tensor products of Banach spaces
Jochen Wengenroth
https://arxiv.org/abs/2506.21344 https://arxiv.org/pdf/25…

Series representation in tensor products of Banach spaces
We show by a ridiculously simple argument that, for any norm on the tensor product of vector spaces, every element of the completion can be represented as a convergent series of elementary tensors.

We're thrilled to announce that Superlinked has joined Berlin Buzzwords as a Gold Partner!
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Conformal Vector Fields on Complex Hyperbolic Space
Hiroyasu Satoh, Hemangi Madhusudan Shah
https://arxiv.org/abs/2506.09710 https://…

Conformal Vector Fields on Complex Hyperbolic Space
In this article, we show that there does not exist any non-trivial conformal vector field on complex hyperbolic space. That is, we show that any conformal vector field on a complex hyperbolic space is indeed a Killing vector field.

HARMONY: A Scalable Distributed Vector Database for High-Throughput Approximate Nearest Neighbor Search
Qian Xu, Feng Zhang, Chengxi Li, Lei Cao, Zheng Chen, Jidong Zhai, Xiaoyong Du
https://arxiv.org/abs/2506.14707

HARMONY: A Scalable Distributed Vector Database for High-Throughput Approximate Nearest Neighbor Search
Approximate Nearest Neighbor Search (ANNS) is essential for various data-intensive applications, including recommendation systems, image retrieval, and machine learning. Scaling ANNS to handle billions of high-dimensional vectors on a single machine presents significant challenges in memory capacity and processing efficiency. To address these challenges, distributed vector databases leverage multiple nodes for the parallel storage and processing of vectors. However, existing solutions often suf…

Replaced article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[9/11]:
- Cramming 1568 Tokens into a Single Vector and Back Again: Exploring the Limits of Embedding Space...
Yuri Kuratov, Mikhail Arkhipov, Aydar Bulatov, Mikhail Burtsev

Unveiling the role of vector potential in the Aharonov-Bohm effect
Masashi Wakamatsu
https://arxiv.org/abs/2506.07018 https://arxiv.o…

Unveiling the role of vector potential in the Aharonov-Bohm effect
The most popular interpretation of the Aharonov-Bohm (AB) effect is that the electromagnetic potential locally affects the complex phase of a charged particle's wave function in the magnetic field free region. However, since the vector potential is a gauge-variant quantity, not a few researchers suspect that it is just a convenient tool for calculating the force field. This motivates them to explain the AB effect without using the vector potential, which inevitably leads to some sort of non-loc…

Low-order finite element complex with application to a fourth-order elliptic singular perturbation problem
Xuewei Cui, Xuehai Huang
https://arxiv.org/abs/2506.20240

Low-order finite element complex with application to a fourth-order elliptic singular perturbation problem
A low-order nonconforming finite element discretization of a smooth de Rham complex starting from the $H^2$ space in three dimensions is proposed, involving an $H^2$-nonconforming finite element space, a new tangentially continuous $H^1$-nonconforming vector-valued finite element space, the lowest-order Raviart-Thomas space, and piecewise constant functions. While nonconforming for the smooth complex, the discretization conforms to the classical de Rham complex. It is applied to develop a decou…

Search for single production of vector-like quarks decaying into $W(\ell\nu)b$ in $pp$ collisions at $\sqrt{s} = 13$ TeV with the ATLAS detector
ATLAS Collaboration
https://arxiv.org/abs/2506.15515

Search for single production of vector-like quarks decaying into $W(\ellν)b$ in $pp$ collisions at $\sqrt{s} = 13$ TeV with the ATLAS detector
A search for single production of a vector-like quark $Q$, which could be either a singlet $T$, with charge $\tfrac23$, or a $Y$ from a $(T,B,Y)$ triplet, with charge $-\tfrac43$, is performed using data from proton-proton collisions at a centre-of-mass energy of 13 TeV. The data correspond to the full integrated luminosity of 140 fb$^{-1}$ recorded with the ATLAS detector during Run 2 of the Large Hadron Collider. The analysis targets $Q \to Wb$ decays where the $W$ boson decays leptonically. …

Lightweight Relevance Grader in RAG
Taehee Jeong
https://arxiv.org/abs/2506.14084 https://arxiv.org/pdf/2506.14084

Lightweight Relevance Grader in RAG
Retrieval-Augmented Generation (RAG) addresses limitations of large language models (LLMs) by leveraging a vector database to provide more accurate and up-to-date information. When a user submits a query, RAG executes a vector search to find relevant documents, which are then used to generate a response. However, ensuring the relevance of retrieved documents with a query would be a big challenge. To address this, a secondary model, known as a relevant grader, can be served to verify its relevan…

The Voronoi Spherical CDF for Lattices and Linear Codes: New Bounds for Quantization and Coding
Or Ordentlich
https://arxiv.org/abs/2506.19791 https://

The Voronoi Spherical CDF for Lattices and Linear Codes: New Bounds for Quantization and Coding
For a lattice/linear code, we define the Voronoi spherical cumulative density function (CDF) as the CDF of the $\ell_2$-norm/Hamming weight of a random vector uniformly distributed over the Voronoi cell. Using the first moment method together with a simple application of Jensen's inequality, we develop lower bounds on the expected Voronoi spherical CDF of a random lattice/linear code. Our bounds are quite close to a trivial ball-based lower bound and immediately translate to improved upper boun…

Segre forms of singular metrics on vector bundles and Lelong numbers
Mats Andersson, Richard L\"ark\"ang
https://arxiv.org/abs/2506.15473 https:/…

Segre forms of singular metrics on vector bundles and Lelong numbers
Let $E\to X$ be a holomorphic vector bundle with a singular Griffiths negative Hermitian metric $h$ with analytic singularities. One can define, given a smooth reference metric $h_0$, a current $s(E,h,h_0)$ that is called the associated Segre form, which defines the expected Bott-Chern class and coincides with the usual Segre form of $h$ where it is smooth. We prove that $s(E,h,h_0)$ is the limit of the Segre forms of a sequence of smooth metrics if the metric is smooth outside the unbounded lo…

Cluster structures in mixed Grassmanianns
Zenan Fu
https://arxiv.org/abs/2506.20038 https://arxiv.org/pdf/2506.20038

Cluster structures in mixed Grassmanianns
Generalizing the results by Fomin-Pylyavskyy and Carde, we construct a family of natural cluster structures in the coordinate ring of a mixed Grassmannian, the configuration space of tuples of several vectors and covectors in a finite-dimensional complex vector space. We describe and explore these cluster structures using the machinery of weaves introduced by Casals and Zaslow.

Dissecting the Segmentation Model of End-to-End Diarization with Vector Clustering
Alexis Plaquet, Naohiro Tawara, Marc Delcroix, Shota Horiguchi, Atsushi Ando, Shoko Araki, Herv\'e Bredin
https://arxiv.org/abs/2506.11605

Dissecting the Segmentation Model of End-to-End Diarization with Vector Clustering
End-to-End Neural Diarization with Vector Clustering is a powerful and practical approach to perform Speaker Diarization. Multiple enhancements have been proposed for the segmentation model of these pipelines, but their synergy had not been thoroughly evaluated. In this work, we provide an in-depth analysis on the impact of major architecture choices on the performance of the pipeline. We investigate different encoders (SincNet, pretrained and finetuned WavLM), different decoders (LSTM, Mamba, …

An extension of the SM with vector-like quarks and hypothetical heavy bosons: model independent parametrisation at NLO order
Chahra Rekaik, Mohamed Sadek Zidi
https://arxiv.org/abs/2506.14663

An extension of the SM with vector-like quarks and hypothetical heavy bosons: model independent parametrisation at NLO order
A model independent parameterization of an extension of the Standard Model including vector-like quarks, new heavy gauge bosons and an extra scalar, involving a minimal number of free parameters, is introduced. Theoretical constraints on the model couplings and hypothetical particle masses are established by making use of perturbative unitarity. The production of heavy charged and neutral gauge bosons which subsequently decay to vector-like quarks at the LHC are investigated at both leading-ord…

Characterizations of Faces of Convex Sets in Infinite-dimensional Vector Spaces
Valentin V. Gorokhovik
https://arxiv.org/abs/2506.08742 https://

Characterizations of Faces of Convex Sets in Infinite-dimensional Vector Spaces
In the paper three different characterizations of faces of convex sets, belonging to infinite-dimensional real vector spaces, are presented. The first one is formulated in the terms of generalized semispaces, the second -- in the terms of compatible complete (total) preorders, and the third -- in the terms of step-affine functions. All three characterization are equivalent each other and extend to infinite-dimensional vector spaces the lexicographical characterization of faces established in fi…

Join Kevin Liang at this year's Berlin Buzzwords, where he will discuss how Apache Solr/Lucene builds dense vector indexes and talk about how he and his team optimised their dense vector setup, sharing the challenges they faced and the best practices they learned along the way.
Learn more: https…

Replaced article(s) found for cs.PL. https://arxiv.org/list/cs.PL/new
[1/1]:
- Zoozve: A Strip-Mining-Free RISC-V Vector Extension with Arbitrary Register Grouping Compilation ...
Siyi Xu, Limin Jiang, Yintao Liu, Yihao Shen, Yi Shi, Shan Cao, Zhiyuan Jiang

Compact Cauchy horizons admit constant surface gravity
Raymond A. Hounnonkpe, Ettore Minguzzi
https://arxiv.org/abs/2506.20004 https://

Compact Cauchy horizons admit constant surface gravity
We prove that in any spacetime dimension and under the dominant energy condition, every totally geodesic connected smooth compact null hypersurface (hence every compact Cauchy horizon) admits a smooth lightlike tangent vector field of constant surface gravity. That is, we solve the open degenerate case by showing that, if there is a complete generator, then there exists a smooth future-directed geodesic lightlike tangent field. The result can be stated as an existence result for a particular co…

Exchange-correlation torques from gauge symmetries
Jacques K. Desmarais, Kamel Bencheikh, Giovanni Vignale, Stefano Pittalis
https://arxiv.org/abs/2506.19458

Exchange-correlation torques from gauge symmetries
The problem of predicting accurate exchange-correlation (xc) spin-torques in non-collinear magnetic systems has dominated the scene of spin-density functional theory (SDFT) in the last two decades. Progress has been hindered by the fact that the spin torque is directly connected to the divergence of the spin current, a quantity that is extraneous to SDFT. Furthermore, SDFT does not apply in the presence of vector potentials and spin-orbit couplings. Here, we propose a solution that exploits the…

Symbolic Reduction for Formal Synthesis of Global Lyapunov Functions
Jun Liu, Maxwell Fitzsimmons
https://arxiv.org/abs/2506.18171 https://

Symbolic Reduction for Formal Synthesis of Global Lyapunov Functions
We investigate the formal synthesis of global polynomial Lyapunov functions for polynomial vector fields. We establish that a sign-definite polynomial must satisfy specific algebraic constraints, which we leverage to develop a set of straightforward symbolic reduction rules. These rules can be recursively applied to symbolically simplify the Lyapunov candidate, enabling more efficient and robust discovery of Lyapunov functions via optimization or satisfiability modulo theories (SMT) solving. In…

Double Higgs Production via Vector Boson Fusion in SMEFT
Athanasios Dedes, Janusz Rosiek, Micha{\l} Ryczkowski
https://arxiv.org/abs/2506.12917 https://

Double Higgs Production via Vector Boson Fusion in SMEFT
While gluon fusion dominates Higgs pair production at the LHC, vector boson fusion (VBF) offers a unique window into Beyond the Standard Model (BSM) physics through its distinctive kinematic features and direct sensitivity to Higgs-vector boson interactions. We perform a comprehensive analysis of double Higgs production via VBF in the Standard Model Effective Field Theory (SMEFT), systematically investigating how dimension-6 and dimension-8 bosonic operators - particularly those involving field…

VecFlow: A High-Performance Vector Data Management System for Filtered-Search on GPUs
Jingyi Xi, Chenghao Mo, Benjamin Karsin, Artem Chirkin, Mingqin Li, Minjia Zhang
https://arxiv.org/abs/2506.00812

VecFlow: A High-Performance Vector Data Management System for Filtered-Search on GPUs
Vector search and database systems have become a keystone component in many AI applications. While many prior research has investigated how to accelerate the performance of generic vector search, emerging AI applications require running more sophisticated vector queries efficiently, such as vector search with attribute filters. Unfortunately, recent filtered-ANNS solutions are primarily designed for CPUs, with few exploration and limited performance of filtered-ANNS that take advantage of the m…

The Hamilton cycle space of random graphs
Dan Hefetz, Michael Krivelevich
https://arxiv.org/abs/2506.19731 https://arxiv.org/pdf/2506…

The Hamilton cycle space of random graphs
The cycle space of a graph $G$, denoted $C(G)$, is a vector space over ${\mathbb F}_2$, spanned by all incidence vectors of edge-sets of cycles of $G$. If $G$ has $n$ vertices, then $C_n(G)$ denotes the subspace of $C(G)$, spanned by the incidence vectors of Hamilton cycles of $G$. A classical result in the theory of random graphs asserts that for $G \sim \mathbb{G}(n,p)$, asymptotically almost surely the necessary condition $δ(G) \geq 2$ is also sufficient to ensure Hamiltonicity. Resolving a…

Fast Flexible LSQR with a Hybrid Variant for Efficient Large-Scale Regularization
Eva Miku\v{s}ov\'a, Iveta Hn\v{e}tynkov\'a
https://arxiv.org/abs/2506.19666

Fast Flexible LSQR with a Hybrid Variant for Efficient Large-Scale Regularization
A wide range of applications necessitates solving large-scale ill-posed problems contaminated by noise. Krylov subspace regularization methods are particularly advantageous in this context, as they rely solely on matrix-vector multiplication. Among the most widely used techniques are LSQR and CGLS, both of which can be extended with flexible preconditioning to enforce solution properties such as nonnegativity or sparsity. Flexible LSQR (FLSQR) can also be further combined with direct methods to…

A huge thank you to Qdrant for sponsoring the coffee breaks at Berlin Buzzwords! We're thrilled to have their support in keeping everyone energised and connected throughout the conference.
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Analyzing PDFs like Binaries: Adversarially Robust PDF Malware Analysis via Intermediate Representation and Language Model
Side Liu, Jiang Ming, Guodong Zhou, Xinyi Liu, Jianming Fu, Guojun Peng
https://arxiv.org/abs/2506.17162

Analyzing PDFs like Binaries: Adversarially Robust PDF Malware Analysis via Intermediate Representation and Language Model
Malicious PDF files have emerged as a persistent threat and become a popular attack vector in web-based attacks. While machine learning-based PDF malware classifiers have shown promise, these classifiers are often susceptible to adversarial attacks, undermining their reliability. To address this issue, recent studies have aimed to enhance the robustness of PDF classifiers. Despite these efforts, the feature engineering underlying these studies remains outdated. Consequently, even with the appli…

A criterion for holomorphic Lie algebroid connections
David Alfaya, Indranil Biswas, Pradip Kumar, Anoop Singh
https://arxiv.org/abs/2506.10514 https://

A criterion for holomorphic Lie algebroid connections
Given a holomorphic Lie algebroid $(V, ϕ)$ on a compact connected Riemann surface $X$, we give a necessary and sufficient condition for a holomorphic vector bundle $E$ on $X$ to admit a holomorphic Lie algebroid connection. If $(V, ϕ)$ is nonsplit, then every holomorphic vector bundle on $X$ admits a holomorphic Lie algebroid connection for $(V, ϕ)$. If $(V, ϕ)$ is split, then a holomorphic vector bundle $E$ on $X$ admits a holomorphic Lie algebroid connection if and only if the degree of e…

Bias-field-free operation of nitrogen-vacancy ensembles in diamond for accurate vector magnetometry
Lilian Childress, Vincent Halde, Kayla Johnson, Andrew Lowther, David Roy-Guay, Romain Ruhlmann, Adrian Solyom
https://arxiv.org/abs/2505.24574

Bias-field-free operation of nitrogen-vacancy ensembles in diamond for accurate vector magnetometry
Accurate measurement of vector magnetic fields is critical for applications including navigation, geoscience, and space exploration. Nitrogen-vacancy (NV) center spin ensembles offer a promising solution for high-sensitivity vector magnetometry, as their different orientations in the diamond lattice measure different components of the magnetic field. However, the bias magnetic field typically used to separate signals from each NV orientation introduces inaccuracy from drifts in permanent magnet…

Hybrid high-order approximations of div-curl systems on domains with general topology
J\'er\'emy Dalphin, Jean-Pierre Ducreux, Simon Lemaire, Silvano Pitassi
https://arxiv.org/abs/2506.19616

Hybrid high-order approximations of div-curl systems on domains with general topology
We devise and analyze hybrid polyhedral methods of arbitrary order for the approximation of div-curl systems on three-dimensional domains featuring non-trivial topology. The div-curl systems we are interested in stem from magnetostatics, and can either be first-order (field formulation) or second-order (vector potential formulation). The well-posedness of the resulting discrete problems essentially hinges on recently established, topologically generic, hybrid versions of the (first and second) …

Proposed measurement of longitudinally polarised vector bosons in $WH$ and $ZH$ production at Hadron colliders
Rosa Colyer, Dominik Duda
https://arxiv.org/abs/2506.13002

Proposed measurement of longitudinally polarised vector bosons in $WH$ and $ZH$ production at Hadron colliders
The longitudinal polarisation states of the $W$ and $Z$ bosons arise during electroweak (EW) symmetry breaking as the vector bosons absorb the Higgs boson's massless degrees of freedom. Consequently, these states are intrinsically linked to the EW symmetry breaking mechanism. Measuring the Higgs boson's coupling to them thus offers a unique opportunity to deepen our understanding of EW symmetry breaking and potentially opens a window to physics beyond the Standard Model. This work studies vecto…

Replaced article(s) found for cs.DB. https://arxiv.org/list/cs.DB/new
[1/1]:
- When Large Language Models Meet Vector Databases: A Survey
Zhi Jing, Yongye Su, Yikun Han, Bo Yuan, Haiyun Xu, Chunjiang Liu, Kehai Chen, Min Zhang

Remarks on Higgs bundles twisted by a vector bundle
David Alfaya, Indranil Biswas, Pradip Kumar
https://arxiv.org/abs/2506.06573 https://

Remarks on Higgs bundles twisted by a vector bundle
For any V-twisted Higgs bundle on a compact Riemann surface X, where V is a holomorphic vector bundle of rank two on X, there are two associated Higgs bundles on X, twisted by line bundles, which are constructed using a Hecke transformation on V. We characterize all such pairs of Higgs bundles (twisted by line bundles) given by V-twisted Higgs bundles. Using this characterization, we provide a spectral correspondence for the moduli space, identifying V-twisted Higgs bundles with the direct imag…

Counting edges of different types in a local graph of a Grassmann graph
Ian Seong
https://arxiv.org/abs/2506.18700 https://arxiv.org/…

Counting edges of different types in a local graph of a Grassmann graph
Let $\mathbb{F}_q$ denote a finite field with $q$ elements. Let $n,k$ denote integers with $n>2k\geq 6$. Let $V$ denote a vector space over $\mathbb{F}_{q}$ that has dimension $n$. The vertex set of the Grassmann graph $J_q(n,k)$ consists of the $k$-dimensional subspaces of $V$. Two vertices of $J_q(n,k)$ are adjacent whenever their intersection has dimension $k-1$. Let $\partial$ denote the path-length distance function of $J_q(n,k)$. Pick vertices $x,y$ of $J_q(n,k)$ such that $1<\partial(x,y…

Imaging the charge distributions of flavor-symmetric and -asymmetric mesons
Yin-Zhen Xu, Adnan Bashir, Kh\'epani Raya, Jos\'e Rodr\'iguez-Quintero, Jorge Segovia
https://arxiv.org/abs/2506.17993

Imaging the charge distributions of flavor-symmetric and -asymmetric mesons
We investigate the internal structure of a comprehensive set of pseudoscalar and vector mesons, including both flavor-symmetric and flavor-asymmetric systems, by reconstructing their charge distributions from electromagnetic form factors. To achieve this, we employ a Maximum Entropy Method optimized for charge distributions, utilizing previously published form factor data obtained within the Dyson-Schwingers and Bethe-Salpeter equations framework. Furthermore, we calculate the average distance …

Relativistic corrections to exclusive photoproduction of Quarkonia near-threshold
Sarah K. Blask, Sean Fleming, Thomas Mehen, Jyotirmoy Roy, Iain W. Stewart, Fanyi Zhao
https://arxiv.org/abs/2506.18905

Relativistic corrections to exclusive photoproduction of Quarkonia near-threshold
Non-relativistic QCD (NRQCD) is used to calculate the relativistic correction to the amplitude for exclusive photoproduction of vector Quarkonia in the near-threshold region within the generalized parton distribution (GPD) framework. The relativistic corrections are found to be large for $J/ψ$. Cross-sections for both $J/ψ$ and $Υ$ are calculated with the former being compared to the data. We also demonstrate the presence of endpoint divergences for the relativistic correction away from the …