Tootfinder

Fermion quasinormal modes on modified RN background
Nikola Herceg, Nikola Konjik, A. Naveena Kumara, Andjelo Samsarov
https://arxiv.org/abs/2507.19343 https://

Fermion quasinormal modes on modified RN background
Noncommutative (NC) geometry may open an alternative route to quantum gravity. We study the influence of the spacetime noncommutativity on the Dirac quasinormal modes in the modified Reissner-Nordström black hole spacetime. The framework for the latter study is provided by a certain effective model of gravity coupled to fermions which in itself encapsulates noncommutative deformation. This model describes a classical Dirac field coupled to a modified Reissner-Nordström geometry where the corr…

Invertible completions of FLI and FRI upper triangular operator matrices
Nikola Sarajlija
https://arxiv.org/abs/2508.20956 https://arxiv.org/pdf/2508.20956…

Invertible completions of FLI and FRI upper triangular operator matrices
If $A\in\mathcal{B}(\mathcal{H})$ and $B\in\mathcal{B}(\mathcal{K})$ are given operators, denote by $M_C$ an operator matrix of the form $$M_C=\begin{pmatrix} A & C\\ 0 & B \end{pmatrix}\in\mathcal{B}(\mathcal{H}\oplus\mathcal{K})$$ acting on a direct sum of infinite dimensional separable Hilbert spaces $\mathcal{H}$ and $\mathcal{K}$, and $C\in\mathcal{B}(\mathcal{K},\mathcal{H})$ is unknown. In this article we solve the completion problem of $M_C$ to Fredholm left and Fredholm right inverti…

Affective Polarization across European Parliaments
Bojan Evkoski, Igor Mozeti\v{c}, Nikola Ljube\v{s}i\'c, Petra Kralj Novak
https://arxiv.org/abs/2508.18916 https://…

Affective Polarization across European Parliaments
Affective polarization, characterized by increased negativity and hostility towards opposing groups, has become a prominent feature of political discourse worldwide. Our study examines the presence of this type of polarization in a selection of European parliaments in a fully automated manner. Utilizing a comprehensive corpus of parliamentary speeches from the parliaments of six European countries, we employ natural language processing techniques to estimate parliamentarian sentiment. By compar…

LARP: Learner-Agnostic Robust Data Prefiltering
Kristian Minchev, Dimitar Iliev Dimitrov, Nikola Konstantinov
https://arxiv.org/abs/2506.20573 https://

LARP: Learner-Agnostic Robust Data Prefiltering
The widespread availability of large public datasets is a key factor behind the recent successes of statistical inference and machine learning methods. However, these datasets often contain some low-quality or contaminated data, to which many learning procedures are sensitive. Therefore, the question of whether and how public datasets should be prefiltered to facilitate accurate downstream learning arises. On a technical level this requires the construction of principled data prefiltering metho…

Crosslisted article(s) found for cs.DM. https://arxiv.org/list/cs.DM/new
[1/1]:
- Generalizing Brooks' theorem via Partial Coloring is Hard Classically and Locally
Jan Bok, Avinandan Das, Anna Gujgiczer, Nikola Jedli\v{c}kov\'a

A Learning-based Domain Decomposition Method
Rui Wu, Nikola Kovachki, Burigede Liu
https://arxiv.org/abs/2507.17328 https://arxiv.org…

A Learning-based Domain Decomposition Method
Recent developments in mechanical, aerospace, and structural engineering have driven a growing need for efficient ways to model and analyse structures at much larger and more complex scales than before. While established numerical methods like the Finite Element Method remain reliable, they often struggle with computational cost and scalability when dealing with large and geometrically intricate problems. In recent years, neural network-based methods have shown promise because of their ability …

Generalizing Brooks' theorem via Partial Coloring is Hard Classically and Locally
Jan Bok, Avinandan Das, Anna Gujgiczer, Nikola Jedli\v{c}kov\'a
https://arxiv.org/abs/2508.16308

Generalizing Brooks' theorem via Partial Coloring is Hard Classically and Locally
We investigate the classical and distributed complexity of \emph{$k$-partial $c$-coloring} where $c=k$, a natural generalization of Brooks' theorem where each vertex should be colored from the palette $\{1,\ldots,c\} = \{1,\ldots,k\}$ such that it must have at least $\min\{k, °(v)\}$ neighbors colored differently. Das, Fraigniaud, and Ros{é}n~[OPODIS 2023] showed that the problem of $k$-partial $(k+1)$-coloring admits efficient centralized and distributed algorithms and posed an open problem …

Physical Embodiment Enables Information Processing Beyond Explicit Sensing in Active Matter
Diptabrata Paul, Nikola Milosevic, Nico Scherf, Frank Cichos
https://arxiv.org/abs/2508.17921

Physical Embodiment Enables Information Processing Beyond Explicit Sensing in Active Matter
Living microorganisms have evolved dedicated sensory machinery to detect environmental perturbations, processing these signals through biochemical networks to guide behavior. Replicating such capabilities in synthetic active matter remains a fundamental challenge. Here, we demonstrate that synthetic active particles can adapt to hidden hydrodynamic perturbations through physical embodiment alone, without explicit sensing mechanisms. Using reinforcement learning to control self-thermophoretic pa…

Crosslisted article(s) found for cs.CC. https://arxiv.org/list/cs.CC/new
[1/1]:
- Generalizing Brooks' theorem via Partial Coloring is Hard Classically and Locally
Jan Bok, Avinandan Das, Anna Gujgiczer, Nikola Jedli\v{c}kov\'a

The Third Hankel determinant for inverse coefficients of bounded turning functions
Mohsan Raza, Nikola Tuneski
https://arxiv.org/abs/2506.16212 https://

The Third Hankel determinant for inverse coefficients of bounded turning functions
In this paper, we obtain sharp bounds for the third Hankel determinants of the coefficients of the inverse of bounded turning functions. Thus answering a negatively to a conjecture recently posed regarding these functions. Additionally, we offer a positive response for the Hankel determinant related to a class of bounded turning functions.

Replaced article(s) found for math.FA. https://arxiv.org/list/math.FA/new
[1/1]:
- Completion problem of upper triangular $3\times3$ operator matrices on arbitrary Banach spaces
Nikola Sarajlija, Dragan S. Djordjevi\'c

Differential Privacy in Kernelized Contextual Bandits via Random Projections
Nikola Pavlovic, Sudeep Salgia, Qing Zhao
https://arxiv.org/abs/2507.13639 htt…

Differential Privacy in Kernelized Contextual Bandits via Random Projections
We consider the problem of contextual kernel bandits with stochastic contexts, where the underlying reward function belongs to a known Reproducing Kernel Hilbert Space. We study this problem under an additional constraint of Differential Privacy, where the agent needs to ensure that the sequence of query points is differentially private with respect to both the sequence of contexts and rewards. We propose a novel algorithm that achieves the state-of-the-art cumulative regret of $\widetilde{\mat…

On the Limits of Selective AI Prediction: A Case Study in Clinical Decision Making
Sarah Jabbour, David Fouhey, Nikola Banovic, Stephanie D. Shepard, Ella Kazerooni, Michael W. Sjoding, Jenna Wiens
https://arxiv.org/abs/2508.07617

On the Limits of Selective AI Prediction: A Case Study in Clinical Decision Making
AI has the potential to augment human decision making. However, even high-performing models can produce inaccurate predictions when deployed. These inaccuracies, combined with automation bias, where humans overrely on AI predictions, can result in worse decisions. Selective prediction, in which potentially unreliable model predictions are hidden from users, has been proposed as a solution. This approach assumes that when AI abstains and informs the user so, humans make decisions as they would w…

Fine-structure Line Atlas for Multi-wavelength Extragalactic Study (FLAMES) III: [C II] as Tracer, Crisis of SFR, [O III]/[C II] at High-z, New Answers and New Questions
Bo Peng, Gordon Stacey, Amit Vishwas, Catie Ball, Cody Lamarche, Christopher Rooney, Thomas Nikola, Carl Ferkinhoff
https://arxiv.org/abs/2507.12896

Fine-structure Line Atlas for Multi-wavelength Extragalactic Study (FLAMES) III: [C II] as Tracer, Crisis of SFR, [O III]/[C II] at High-z, New Answers and New Questions
In the final paper of this series, we discuss new perspectives and challenges in the study of interstellar medium (ISM), leveraging comprehensive catalogs and physical insights presented in our previous papers. We focus on key questions of far-infrared (FIR) fine-structure lines (FSLs): their origins, diagnostic value, and implications of correlations. Our analysis reveals a strong dependence on elemental abundance, so that FSL/H$α$ traces metallicity, [N II]/[C II] traces N/O, and $\sim$80% o…

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…

Bisections of mass assignments by parallel hyperplanes
Nikola Sadovek, Pablo Sober\'on
https://arxiv.org/abs/2507.06924 https://a…

Bisections of mass assignments by parallel hyperplanes
In this paper, we prove a result on the bisection of mass assignments by parallel hyperplanes on Euclidean vector bundles. Our methods consist of the development of a novel lifting method to define the configuration space--test map scheme, which transforms the problem to a Borsuk--Ulam-type question on equivariant fiber bundles, along with a new computation of the parametrized Fadell--Husseini index. As the primary application, we show that any $d+k+m-1$ mass assignments to linear $d$-spaces in…

FLIP: Flowability-Informed Powder Weighing
Nikola Radulov (Department of Computer Science University of Liverpool UK), Alex Wright (Department of Computer Science University of Liverpool UK), Thomas little (Department of Computer Science University of Liverpool UK), Andrew I. Cooper (Department of Chemistry university of Liverpool UK), Gabriella Pizzuto (Department of Computer Science University of Liverpool UK, Department of Chemistry university of Liverpool UK)

FLIP: Flowability-Informed Powder Weighing
Autonomous manipulation of powders remains a significant challenge for robotic automation in scientific laboratories. The inherent variability and complex physical interactions of powders in flow, coupled with variability in laboratory conditions necessitates adaptive automation. This work introduces FLIP, a flowability-informed powder weighing framework designed to enhance robotic policy learning for granular material handling. Our key contribution lies in using material flowability, quantifie…

🇺🇦 #NowPlaying on BBCRadio3's #ThroughTheNight
Maria Herz, Nadja Saminskaja, Ronny Spiegel, Yuta Takase, Daphne Unseld, Fedor Saminski, Nikola Major & Christian Madlener:
🎵 Concerto for Harpsichord or Fortepiano, String Orchestra and Flute, op. 15
#MariaHerz #YutaTakase

SoK: Data Minimization in Machine Learning
Robin Staab, Nikola Jovanovi\'c, Kimberly Mai, Prakhar Ganesh, Martin Vechev, Ferdinando Fioretto, Matthew Jagielski
https://arxiv.org/abs/2508.10836

SoK: Data Minimization in Machine Learning
Data minimization (DM) describes the principle of collecting only the data strictly necessary for a given task. It is a foundational principle across major data protection regulations like GDPR and CPRA. Violations of this principle have substantial real-world consequences, with regulatory actions resulting in fines reaching hundreds of millions of dollars. Notably, the relevance of data minimization is particularly pronounced in machine learning (ML) applications, which typically rely on large…

Will Agents Replace Us? Perceptions of Autonomous Multi-Agent AI
Nikola Balic
https://arxiv.org/abs/2506.02055 https://arxiv.org/pdf/…

Will Agents Replace Us? Perceptions of Autonomous Multi-Agent AI
Autonomous multi-agent AI systems are poised to transform various industries, particularly software development and knowledge work. Understanding current perceptions among professionals is crucial for anticipating adoption challenges, ethical considerations, and future workforce development. This study analyzes responses from 130 participants to a survey on the capabilities, impact, and governance of AI agents. We explore expected timelines for AI replacing programmers, identify perceived barri…

The Predictive Brain: Neural Correlates of Word Expectancy Align with Large Language Model Prediction Probabilities
Nikola K\"olbl, Konstantin Tziridis, Andreas Maier, Thomas Kinfe, Ricardo Chavarriaga, Achim Schilling, Patrick Krauss
https://arxiv.org/abs/2506.08511

The Predictive Brain: Neural Correlates of Word Expectancy Align with Large Language Model Prediction Probabilities
Predictive coding theory suggests that the brain continuously anticipates upcoming words to optimize language processing, but the neural mechanisms remain unclear, particularly in naturalistic speech. Here, we simultaneously recorded EEG and MEG data from 29 participants while they listened to an audio book and assigned predictability scores to nouns using the BERT language model. Our results show that higher predictability is associated with reduced neural responses during word recognition, as…

Shifted Lagrangian thickenings of shifted Poisson derived schemes
Nikola Tomi\'c
https://arxiv.org/abs/2506.23348 https://arxiv.o…

Shifted Lagrangian thickenings of shifted Poisson derived schemes
We prove that the space of shifted Poisson structures on a derived scheme $X$ locally of finite presentation is equivalent to the space of shifted Lagrangian thickenings out $X$, solving a conjecture in shifted Poisson geometry. As a corollary, we show that for $M$ a compact oriented $d$-dimensional manifold and an $n$-shifted Poisson structure on $X$, the mapping stack $\mathrm{Map}(M,X)$ has an $(n-d)$-shifted Poisson structure. It extends a known theorem for shifted symplectic structures to …

DV365: Extremely Long User History Modeling at Instagram
Wenhan Lyu, Devashish Tyagi, Yihang Yang, Ziwei Li, Ajay Somani, Karthikeyan Shanmugasundaram, Nikola Andrejevic, Ferdi Adeputra, Curtis Zeng, Arun K. Singh, Maxime Ransan, Sagar Jain
https://arxiv.org/abs/2506.00450

DV365: Extremely Long User History Modeling at Instagram
Long user history is highly valuable signal for recommendation systems, but effectively incorporating it often comes with high cost in terms of data center power consumption and GPU. In this work, we chose offline embedding over end-to-end sequence length optimization methods to enable extremely long user sequence modeling as a cost-effective solution, and propose a new user embedding learning strategy, multi-slicing and summarization, that generates highly generalizable user representation of …

Replaced article(s) found for math.CO. https://arxiv.org/list/math.CO/new
[1/1]:
- Complex analogues of the Tverberg--Vre\'cica conjecture and central transversal theorems
Nikola Sadovek, Pablo Sober\'on

The effect of local magnetic fields in quiet regions of stellar atmospheres simulated with MANCHA
Andrea Perdomo Garc\'ia, Nikola Vitas, Elena Khomenko, Manuel Collados
https://arxiv.org/abs/2507.00636

The effect of local magnetic fields in quiet regions of stellar atmospheres simulated with MANCHA
Our aim is to characterize the effects of the local magnetic fields in quiet regions of stellar atmospheres. We compute magneto-hydrodynamic and purely hydrodynamic simulations of G2V, K0V and M2V star. The magnetic simulations are started from the hydrodynamical ones, adding the Biermann battery term in the induction equation to produce a magnetic seed, that is enhanced by the action of the small-scale dynamo. Once the magnetic field is saturated, we compare the simulations with and without ma…

Rademacher learning rates for iterated random functions
Nikola Sandri\'c
https://arxiv.org/abs/2506.13946 https://arxiv.org/pdf/2…

Rademacher learning rates for iterated random functions
Most existing literature on supervised machine learning assumes that the training dataset is drawn from an i.i.d. sample. However, many real-world problems exhibit temporal dependence and strong correlations between the marginal distributions of the data-generating process, suggesting that the i.i.d. assumption is often unrealistic. In such cases, models naturally include time-series processes with mixing properties, as well as irreducible and aperiodic ergodic Markov chains. Moreover, the lear…

Overcoming Data Scarcity in Scanning Tunnelling Microscopy Image Segmentation
Nikola L. Kolev, Max Trouton, Filippo Federici Canova, Geoff Thornton, David Z. Gao, Neil J. Curson, Taylor J. Z. Stock
https://arxiv.org/abs/2506.01678

Overcoming Data Scarcity in Scanning Tunnelling Microscopy Image Segmentation
Scanning tunnelling microscopy (STM) is a powerful technique for imaging surfaces with atomic resolution, providing insight into physical and chemical processes at the level of single atoms and molecules. A regular task of STM image analysis is the identification and labelling of features of interest against a uniform background. Performing this manually is a labour-intensive task, requiring significant human effort. To reduce this burden, we propose an automated approach to the segmentation of…

Zero-disparity Distribution Synthesis: Fast Exact Calculation of Chi-Squared Statistic Distribution for Discrete Uniform Histograms
Nikola Bani\'c, Neven Elezovi\'c
https://arxiv.org/abs/2506.23416

Zero-disparity Distribution Synthesis: Fast Exact Calculation of Chi-Squared Statistic Distribution for Discrete Uniform Histograms
Pearson's chi-squared test is widely used to assess the uniformity of discrete histograms, typically relying on a continuous chi-squared distribution to approximate the test statistic, since computing the exact distribution is computationally too costly. While effective in many cases, this approximation allegedly fails when expected bin counts are low or tail probabilities are needed. Here, Zero-disparity Distribution Synthesis is presented, a fast dynamic programming approach for computing the…

Diver-Robot Communication Dataset for Underwater Hand Gesture Recognition
Igor Kvasi\'c, Derek Orbaugh Antillon, {\DH}ula Na{\dj}, Christopher Walker, Iain Anderson, Nikola Mi\v{s}kovi\'c
https://arxiv.org/abs/2506.08974

Diver-Robot Communication Dataset for Underwater Hand Gesture Recognition
In this paper, we present a dataset of diving gesture images used for human-robot interaction underwater. By offering this open access dataset, the paper aims at investigating the potential of using visual detection of diving gestures from an autonomous underwater vehicle (AUV) as a form of communication with a human diver. In addition to the image recording, the same dataset was recorded using a smart gesture recognition glove. The glove uses elastomer sensors and on-board processing to determ…

Fine-structure Line Atlas for Multi-wavelength Extragalactic Study (FLAMES) I: Comprehensive Low and High Redshift Catalogs and Empirical Relations for Probing Gas Conditions
Bo Peng, Cody Lamarche, Catie Ball, Amit Vishwas, Gordon Stacey, Christopher Rooney, Thomas Nikola, Carl Ferkinhoff
https://arxiv.org/abs/2507.10702…

Fine-structure Line Atlas for Multi-wavelength Extragalactic Study (FLAMES) I: Comprehensive Low and High Redshift Catalogs and Empirical Relations for Probing Gas Conditions
Far-infrared (FIR) and mid-infrared (MIR) fine-structure lines (FSLs) are widely used for studying galaxies nearby and faraway. However, interpreting these lines is complicated by factors including sample and data bias, mismatch between resolved calibrations and unresolved observations, limitations in generalizing from case studies, and unresolved issues like the origin of [C II] emission and the so-called ``deficit.''In this series of papers, we assemble and analyze the most comprehensive atla…

Computational complexity of covering regular trees
Jan Bok, Ji\v{r}\'i Fiala, Nikola Jedli\v{c}kov\'a, Jan Kratochv\'il
https://arxiv.org/abs/2507.00564

Computational complexity of covering regular trees
A graph covering projection, also referred to as a locally bijective homomorphism, is a mapping between the vertices and edges of two graphs that preserves incidences and is a local bijection. This concept originates in topological graph theory but has also found applications in combinatorics and theoretical computer science. In this paper we consider undirected graphs in the most general setting -- graphs may contain multiple edges, loops, and semi-edges. This is in line with recent trends in …

A State of the Art on Recent Progress and Emerging Challenges on Energy Transfer Between Vibrating Modes Under an External Mechanical Force With Time-Varying Frequency From 2020 to 2025
Jose Manoel Balthazar, Jorge Luis Palacios Felix, Mauricio A. Ribeiro, Angelo Marcelo Tusset, Jeferson Jose de Lima, Vinicius Piccirillo, Julijana Simonovic, Nikola D. Nevsic, Marcos Varanis, Clivaldo de Oliveira, Raphaela C. Machado, Gabriella O M Oliveira

A State of the Art on Recent Progress and Emerging Challenges on Energy Transfer Between Vibrating Modes Under an External Mechanical Force With Time-Varying Frequency From 2020 to 2025
In this paper, we discuss an example of current importance with a future perspective in engineering, in which excitation sources always have limited power, limited inertia, and their frequencies vary according to the instantaneous state of the vibrating system. Practical examples of non-ideal systems are considered. The most common phenomenon for this kind of system is discussed. The period considered is from 2020 to 2025. The specific properties of various models are also discussed. Directions…