April 2024 arXiv papers — page 33

Richard Nickl, Grigorios A. Pavliotis, Kolyan Ray

We consider nonparametric statistical inference on a periodic interaction potential $W$ from noisy discrete space-time measurements of solutions $\rho=\rho_W$ of the nonlinear McKean-Vlasov equation, describing the probability density of the mean field limit of an interacting particle system. We show how Gaussian process priors assigned to $W$ give rise to p

Gang Li, Ding-Yi Luo, Xiang Zhao

We revisit the contribution to the strong CP parameter $\bar \theta$ from leptonic CP violation at one-loop level in the minimal left-right symmetric model in the case of generalized parity as the left-right symmetry. The Hermitian neutrino Dirac mass matrix $M_D$ can be calculated using the light and heavy neutrino masses and mixings. We propose a parametri

Nitin Kumar, Manisha

Cancelable Biometric is a challenging research field in which security of an original biometric image is ensured by transforming the original biometric into another irreversible domain. Several approaches have been suggested in literature for generating cancelable biometric templates. In this paper, two novel and simple cancelable biometric template generati

Jiajia Huang, Luyang Wang, Dao-Xin Yao

Klein tunneling is an old topic in relativistic quantum physics, and has been observed recently in graphene where massless particles reside. Here, we propose a new heterostructure platform for Klein tunneling to occur, which consists of a Weyl-semimetal-based normal state/superconductor (NS) junction. By developing a Blonder-Tinkham-Klapwijk-like theory, we

Nancy Mead, Carol Woody, Scott Hissam

Caveat emptor, or let the buyer beware, is commonly attributed to open source software (OSS)-the onus is on the OSS consumer to ensure that it is fit for use in the consumer's context. OSS has been compared to an open market bazaar where consumers are free to browse all the source code and take a copy. In this paper, we observe challenges for the OSS consume

Virgile Guemard

We propose a notion of lift for quantum CSS codes, inspired by the geometrical construction of Freedman and Hastings. It is based on the existence of a canonical complex associated to any CSS code, that we introduce under the name of Tanner cone-complex, and over which we generate covering spaces. As a first application, we describe the classification of lif

J. M. Aldaz, H. Render

We show that for all homogeneous polynomials $ f_{m}$ of degree $m$, in $d$ variables, and each $j = 1, \dots , d$, we have \begin{equation*} \left\langle x_{j}^{2}f_{m},f_{m}\right\rangle _{L^{2}\left( \mathbb{S}% ^{d-1}\right) } \geq \frac{\pi ^{2}}{4\left( m+ 2 d + 1 \right)^{2}} \left \langle f_{m},f_{m}\right\rangle _{L^{2}\left( \mathbb{S}^{d-1}\right)

Enguerrand Prebet, André Platzer

This paper introduces a uniform substitution calculus for differential refinement logic dRL. The logic dRL extends the differential dynamic logic dL such that one can simultaneously reason about properties of and relations between hybrid systems. Refinements are useful e.g. for simplifying proofs by relating a concrete hybrid system to an abstract one from w

Florent Hivert, Jeanne Scott

It is well known that the Young lattice is the Bratelli diagram of the symmetric groups expressing how irreducible representations restrict from $S_N$ to $S_{N-1}$. In 1988, Stanley discovered a similar lattice called the Young-Fibonacci lattice which was realized as the Bratelli diagram of a family of algebras by Okada in 1994. In this paper, we realize the

J. Orell-Miquel, F. Murgas, E. Pallé, M. Mallorquín

During the first Gyr of their life, exoplanet atmospheres suffer from different atmospheric escape phenomena that can strongly affect the shape and morphology of the exoplanet itself. These processes can be studied with Ly$\alpha$, H$\alpha$ and/or He I triplet observations. We present high-resolution spectroscopy observations from CARMENES and GIARPS checki

Qiujiang Jin, Ruichen Jiang, Aryan Mokhtari

In this paper, we present the first explicit and non-asymptotic global convergence rates of the BFGS method when implemented with an inexact line search scheme satisfying the Armijo-Wolfe conditions. We show that BFGS achieves a global linear convergence rate of $(1 - \frac{1}{\kappa})^t$ for $\mu$-strongly convex functions with $L$-Lipschitz gradients, wher

Willow Ahrens, Teodoro Fields Collin, Radha Patel, Kyle Deeds

From FORTRAN to NumPy, tensors have revolutionized how we express computation. However, tensors in these, and almost all prominent systems, can only handle dense rectilinear integer grids. Real world tensors often contain underlying structure, such as sparsity, runs of repeated values, or symmetry. Support for structured data is fragmented and incomplete. Ex

Souradeep Pal, K Rajesh Nayak

We investigate the measurement correlation between the effective spin and the effective tidal deformability in gravitational wave signals from binary neutron star mergers. To efficiently measure the effective tidal deformability parameter, we exploit the fact that the tidal effects in a binary system are prominent when the components are closer during the la

C. Ryan-Anderson, N. C. Brown, C. H. Baldwin, J. M. Dreiling

Quantum state teleportation is commonly used in designs for large-scale fault-tolerant quantum computers. Using Quantinuum's H2 trapped-ion quantum processor, we implement the first demonstration of a fault-tolerant state teleportation circuit for a quantum error correction code - in particular, the planar topological [[7,1,3]] color code, or Steane code. Th

Yihan Zhou, Yiwen Lu, Zishuo Li, Jiaqi Yan

Data-Enabled Predictive Control (DeePC) bypasses the need for system identification by directly leveraging raw data to formulate optimal control policies. However, the size of the optimization problem in DeePC grows linearly with respect to the data size, which prohibits its application to resource-constrained systems due to high computational costs. In this

Julia Gastinger, Christian Meilicke, Federico Errica, Timo Sztyler

Temporal Knowledge Graph (TKG) Forecasting aims at predicting links in Knowledge Graphs for future timesteps based on a history of Knowledge Graphs. To this day, standardized evaluation protocols and rigorous comparison across TKG models are available, but the importance of simple baselines is often neglected in the evaluation, which prevents researchers fro

Chandra Chekuri, Rhea Jain

We consider two-cost network design models in which edges of the input graph have an associated cost and length. We build upon recent advances in hop-constrained oblivious routing to obtain two sets of results. We address multicommodity buy-at-bulk network design in the nonuniform setting. Existing poly-logarithmic approximations are based on the junction tr

Pablo Soberón

We show how, using linear-algebraic tools developed to prove Tverberg's theorem in combinatorial geometry, we can design new models of multi-class support vector machines (SVMs). These supervised learning protocols require fewer conditions to classify sets of points, and can be computed using existing binary SVM algorithms in higher-dimensional spaces, inclu

Boris Klemz, Marie Diana Sieper

The problem Level Planarity asks for a crossing-free drawing of a graph in the plane such that vertices are placed at prescribed y-coordinates (called levels) and such that every edge is realized as a y-monotone curve. In the variant Constrained Level Planarity, each level y is equipped with a partial order <_y on its vertices and in the desired drawing the

Susanna F. de Rezende, Aaron Potechin, Kilian Risse

We prove that Sherali-Adams with polynomially bounded coefficients requires proofs of size $n^{\Omega(d)}$ to rule out the existence of an $n^{\Theta(1)}$-clique in Erd\H{o}s-R\'{e}nyi random graphs whose maximum clique is of size $d\leq 2\log n$. This lower bound is tight up to the multiplicative constant in the exponent. We obtain this result by introducin

Min Kyu Shin, Su-Jeong Park, Seung-Keol Ryu, Heeyeon Kim

This paper presents a novel learning approach for Dubins Traveling Salesman Problems(DTSP) with Neighborhood (DTSPN) to quickly produce a tour of a non-holonomic vehicle passing through neighborhoods of given task points. The method involves two learning phases: initially, a model-free reinforcement learning approach leverages privileged information to disti

Carsten Gundlach

We investigate the well-posedness of the characteristic initial-boundary value problem for the Einstein equations in Bondi-like coordinates (including Bondi, double-null and affine). We propose a definition of strong hyperbolicity of a system of partial differential equations of any order, and show that the Einstein equations in Bondi-like coordinates in the

Christos G. Tsagas

Bulk peculiar flows are commonplace in the universe, with many surveys reporting their presence on scales spanning between few hundred and several hundred Mpc. However, the sizes and the speeds of some of these bulk flows are well in excess of those theoretically anticipated, which has made them a potentially serious problem for the $\Lambda$CDM model. Havin

Arina Varlamova, Valery Belotsky, Grigory Novikov, Anton Konushin

Detection of malignant lesions on mammography images is extremely important for early breast cancer diagnosis. In clinical practice, images are acquired from two different angles, and radiologists can fully utilize information from both views, simultaneously locating the same lesion. However, for automatic detection approaches such information fusion remains

Mazda Moayeri, Michael Rabbat, Mark Ibrahim, Diane Bouchacourt

Vision-language models enable open-world classification of objects without the need for any retraining. While this zero-shot paradigm marks a significant advance, even today's best models exhibit skewed performance when objects are dissimilar from their typical depiction. Real world objects such as pears appear in a variety of forms -- from diced to whole, o

Kimet Jusufi, Ahmed Farag Ali, Abdelrahman Yasser, Nader Inan

Some time ago, it has been suggested that gravitons can acquire mass in the process of spontaneous symmetry breaking of diffeomorphisms through the condensation of scalar fields [Chamseddine and Mukhanov, JHEP, 2010]. Taking this possibility into account, in the present paper, first we show how the graviton mass intricately reshapes the gravitational potenti

Sean Cotner

Recently, in order to formulate a categorical version of the local Langlands correspondence, several authors have constructed moduli spaces of $\mathbf{Z}[1/p]$-valued L-parameters for $p$-adic groups. The connected components of these spaces over various $\mathbf{Z}[1/p]$-algebras $R$ are conjecturally related to blocks in categories of $R$-representations

Ricardo Fariello, Marcus A. M. de Aguiar

The study of higher order interactions in the dynamics of Kuramoto oscillators has been a topic of intense recent research. Arguments based on dimensional reduction using the Ott-Antonsen ansatz show that such interactions usually facilitate synchronization, giving rise to bi-stability and hysteresis. Here we show that three body interactions shift the criti

Alexandra Fonseca Montenegro, Marzieh Baan, Maryam Ghazisaeidi, Tyler J. Grassman

Scanning electron microscopy (SEM) based electron channeling contrast imaging (ECCI) is used to observe and quantify misfit dislocation (MD) networks formed at the heteroepitaxial interface between ZnS and GaP grown by molecular beam epitaxy (MBE). Below a critical thickness of 15-20 nm, no MDs are observed. However, crystallographic features with strong dip

Marina Tchomakova, Stefan Ivanov, Simeon Zamkovoy

We introduce the notion of paraquaternionic contact structures (pqc structures), which turns out to be a generalization of the para 3-Sasakian geometry. We derive a distinguished linear connection preserving the pqc structure. Its torsion tensor is expressed explicitly in terms of the structure tensors and the structure equations of a pqc manifold are presen

Samuel Mallick, Azita Dabiri, Bart De Schutter

This paper presents a novel approach for distributed model predictive control (MPC) for piecewise affine (PWA) systems. Existing approaches rely on solving mixed-integer optimization problems, requiring significant computation power or time. We propose a distributed MPC scheme that requires solving only convex optimization problems. The key contribution is a

Henning Krause

Matlis duality for modules over commutative rings gives rise to the notion of Matlis reflexivity. It is shown that Matlis reflexive modules form a Krull-Schmidt category. For noetherian rings the absence of infinite direct sums is a characteristic feature of Matlis reflexivity. This leads to a discussion of objects that are extensions of artinian by noetheri

Mostafa Elhoushi, Akshat Shrivastava, Diana Liskovich, Basil Hosmer

We present LayerSkip, an end-to-end solution to speed-up inference of large language models (LLMs). First, during training we apply layer dropout, with low dropout rates for earlier layers and higher dropout rates for later layers, and an early exit loss where all transformer layers share the same exit. Second, during inference, we show that this training re

Yang Liu, Jolynn Pek, Alberto Maydeu-Olivares

We adopt and expand McDonald's (2011) regression framework for measurement precision, integrating two key perspectives: (a) reliability of observed scores and (b) optimal prediction of latent scores. Reliability arises from a measurement decomposition of an observed score into its true score and measurement error. In contrast, proportional reduction in mean

Abbas Khan, Muhammad Asad, Martin Benning, Caroline Roney

We propose a novel multi-stage trans-dimensional architecture for multi-view cardiac image segmentation. Our method exploits the relationship between long-axis (2D) and short-axis (3D) magnetic resonance (MR) images to perform a sequential 3D-to-2D-to-3D segmentation, segmenting the long-axis and short-axis images. In the first stage, 3D segmentation is perf

You-Wei Benson Chen

In this paper we prove that for non-negative measurable functions $f$, \begin{align*} I_\alpha f \in BMO(\mathbb{R}^n) \text{ if and only if } I_\alpha f \in BMO^\beta(\mathbb{R}^n) \text{ for } \beta \in (n-\alpha,n]. \end{align*} Here $I_\alpha$ denotes the Riesz potential of order $\alpha$ and $BMO^\beta$ represents the space of functions of bounded $\bet

Krishnamurthy Dvijotham, H. Brendan McMahan, Krishna Pillutla, Thomas Steinke

In the task of differentially private (DP) continual counting, we receive a stream of increments and our goal is to output an approximate running total of these increments, without revealing too much about any specific increment. Despite its simplicity, differentially private continual counting has attracted significant attention both in theory and in practi

Diego Martinez-Baselga, Oscar de Groot, Luzia Knoedler, Luis Riazuelo

Navigating mobile robots in social environments remains a challenging task due to the intricacies of human-robot interactions. Most of the motion planners designed for crowded and dynamic environments focus on choosing the best velocity to reach the goal while avoiding collisions, but do not explicitly consider the high-level navigation behavior (avoiding th

Chen-Chang Zeng, Zhen Cai, Guang-Heng Wang, Gaoyong Sun

We study the critical behaviors of the ground and first excited states in the one-dimensional nonreciprocal Aubry-Andr{\'e}-Harper model using both the self-normal and biorthogonal fidelity susceptibilities. We demonstrate that fidelity susceptibility serves as a probe for the phase transition in the nonreciprocal AAH model. For ground states, characterized

Stefan Ivanov, Marina Tchomakova, Simeon Zamkovoy

A tensor invariant is defined on a paraquaternionic contact manifold in terms of the curvature and torsion of the canonical paraquaternionic connection involving derivatives up to third order of the contact form. This tensor, called paraquaternionic contact conformal curvature, is similar to the Weyl conformal curvature in Riemannian geometry, the Chern-Mose

Irfan Mohammad Al Hasib

Informative gradients are often lost in large batch updates. We propose a robust mechanism to reinforce the sparse components within a random batch of data points. A finite queue of online gradients is used to determine their expected instantaneous statistics. We propose a function to measure the scarcity of incoming gradients using these statistics and esta

Yan Li, Jia-Jun Wu, T. -S. H. Lee, R. D. Young

The investigation of hadron interactions within lattice QCD has been facilitated by the well-known quantisation condition, linking scattering phase shifts to finite-volume energies. Additionally, the ability to utilise systems at finite total boosts has been pivotal in smoothly charting the energy-dependent behaviour of these phase shifts. The existing imple

Yu Chen, Michael Kapralov, Mikhail Makarov, Davide Mazzali

In this paper we study the problem of finding $(\epsilon, \phi)$-expander decompositions of a graph in the streaming model, in particular for dynamic streams of edge insertions and deletions. The goal is to partition the vertex set so that every component induces a $\phi$-expander, while the number of inter-cluster edges is only an $\epsilon$ fraction of the

N. Lejeune, E. Fourneau, A. Barrera, O. Morris

Transformation optics applied to low frequency magnetic systems has been recently implemented to design magnetic field concentrators and cloaks with superior performance. Although this achievement has been amply demonstrated theoretically and experimentally in bulk 3D macrostructures, the performance of these devices at low dimensions remains an open questio

Andrei V. Ermolaev, Christophe Finot, Goery Genty, John M. Dudley

Identifying the underlying processes that locally dominate physical interactions is the key to understanding nonlinear dynamics. Machine-learning techniques have recently been shown to be highly promising in automating the search for dominant physics, adding important insights that complement analytical methods and empirical intuition. Here we apply a fully

Charlotte Vermeylen, Marc Van Barel

A new generalized cyclic symmetric structure in the factor matrices of polyadic decompositions of matrix multiplication tensors for non-square matrix multiplication is proposed to reduce the number of variables in the optimization problem and in this way improve the convergence. The structure is implemented in an existing numerical optimization algorithm. Ex

Giorgio Piatti, Zhijing Jin, Max Kleiman-Weiner, Bernhard Schölkopf

As AI systems pervade human life, ensuring that large language models (LLMs) make safe decisions remains a significant challenge. We introduce the Governance of the Commons Simulation (GovSim), a generative simulation platform designed to study strategic interactions and cooperative decision-making in LLMs. In GovSim, a society of AI agents must collectively

Ahmed Hajr, Bingcheng Qing, Ke Wang, Gerwin Koolstra

The Kerr-cat qubit is a bosonic qubit in which multi-photon Schrodinger cat states are stabilized by applying a two-photon drive to an oscillator with a Kerr nonlinearity. The suppressed bit-flip rate with increasing cat size makes this qubit a promising candidate to implement quantum error correction codes tailored for noise-biased qubits. However, achievin

Andres Campero

This report enlists 13 functional conditions cashed out in computational terms that have been argued to be constituent of conscious valenced experience. These are extracted from existing empirical and theoretical literature on, among others, animal sentience, medical disorders, anaesthetics, philosophy, evolution, neuroscience, and artificial intelligence.

Marin Bougeret, Bart M. P. Jansen, Ignasi Sau

For a fixed graph $H$, the $H$-SUBGRAPH HITTING problem consists in deleting the minimum number of vertices from an input graph to obtain a graph without any occurrence of $H$ as a subgraph. This problem can be seen as a generalization of VERTEX COVER, which corresponds to the case $H = K_2$. We initiate a study of $H$-SUBGRAPH HITTING from the point of view

Pep Mulet, Juan Ruiz-Alvarez, Chi-Wang Shu, Dionisio F. Yáñez

The weighted essentially non-oscillatory {technique} using a stencil of $2r$ points (WENO-$2r$) is an interpolatory method that consists in obtaining a higher approximation order from the non-linear combination of interpolants of $r+1$ nodes. The result is an interpolant of order $2r$ at the smooth parts and order $r+1$ when an isolated discontinuity falls a

Alexander Yu. Vlasov

It is shown that ternary qubit trees with the same number of nodes can be transformed by the naturally defined sequence of Clifford gates into each other or into standard representation as 1D chain corresponding to Jordan-Wigner transform.

Lydia Uhler, Verena Jordan, Jürgen Buder, Markus Huff

Generative artificial intelligences, particularly large language models (LLMs), play an increasingly prominent role in human decision-making contexts, necessitating transparency about their capabilities. While prior studies have shown addition biases in humans (Adams et al., 2021) and OpenAI's GPT-3 (Winter et al., 2023), this study extends the research by c

R. Krivonos, I. Mereminskiy, S. Sazonov

We have carried out a deep survey of the M81 field in the 25-60 keV energy band based on long-term (2003-2023) INTEGRAL observations. A record sensitivity of 0.16 mCrab at a detection significance of 4 sigma has been achieved in the central part of the field owing to the long accumulated exposure (19.2 Ms). The total area of the survey is 1004 deg^2 at a sen

Fenglin Liu, Zheng Li, Hongjian Zhou, Qingyu Yin

The adoption of large language models (LLMs) to assist clinicians has attracted remarkable attention. Existing works mainly adopt the close-ended question-answering (QA) task with answer options for evaluation. However, many clinical decisions involve answering open-ended questions without pre-set options. To better understand LLMs in the clinic, we construc

Vincenzo Cirigliano, Srimoyee Sen, Yukari Yamauchi

We study neutrino flavor evolution in the quantum many-body approach using the full neutrino-neutrino Hamiltonian, including the usually neglected terms that mediate non-forward scattering processes. Working in the occupation number representation with plane waves as single-particle states, we explore the time evolution of simple initial states with up to $N

Radovan Haluska, Martin Schmid

While Poker, as a family of games, has been studied extensively in the last decades, collectible card games have seen relatively little attention. Only recently have we seen an agent that can compete with professional human players in Hearthstone, one of the most popular collectible card games. Although artificial agents must be able to work with imperfect i

Sai Krishna Revanth Vuruma, Dezhi Wu, Saborny Sen Gupta, Lucas Aust

The widespread adoption of social media platforms globally not only enhances users' connectivity and communication but also emerges as a vital channel for the dissemination of health-related information, thereby establishing social media data as an invaluable organic data resource for public health research. The surge in popularity of vaping or e-cigarette u

Bowen Xue, Giuseppe Claudio Guarnera, Shuang Zhao, Zahra Montazeri

We introduce Reflectance Diffusion, a new neural text-to-texture model capable of generating high-fidelity SVBRDF maps from textual descriptions. Our method leverages a tandem neural approach, consisting of two modules, to accurately model the distribution of spatially varying reflectance as described by text prompts. Initially, we employ a pre-trained stabl

James C. Davis, Purvish Jajal, Wenxin Jiang, Taylor R. Schorlemmer

Deep neural networks (DNNs) achieve state-of-the-art performance in many areas, including computer vision, system configuration, and question-answering. However, DNNs are expensive to develop, both in intellectual effort (e.g., devising new architectures) and computational costs (e.g., training). Reusing DNNs is a promising direction to amortize costs within

Alvaro Alonso Domenech, Jonathan Heiss, Stefan Tai

Zk-SNARKs help scale blockchains with Verifiable Off-chain Computations (VOC). zk-SNARK DSL toolkits are key when designing arithmetic circuits but fall short of automating the subsequent proof-generation step in an automated manner. We emphasize the need for portability, interoperability, and manageability in VOC-based solutions and introduce a Proving Serv

Peizhuang Cong, Aomufei Yuan, Shimao Chen, Yuxuan Tian

MoE facilitates the development of large models by making the computational complexity of the model no longer scale linearly with increasing parameters. The learning sparse gating network selects a set of experts for each token to be processed; however, this may lead to differences in the number of tokens processed by each expert over several successive iter

Allen Nie, Yash Chandak, Miroslav Suzara, Ali Malik

Large language models (LLMs) are quickly being adopted in a wide range of learning experiences, especially via ubiquitous and broadly accessible chat interfaces like ChatGPT and Copilot. This type of interface is readily available to students and teachers around the world, yet relatively little research has been done to assess the impact of such generic tool

Xiaohong Liu, Xiongkuo Min, Guangtao Zhai, Chunyi Li

This paper reports on the NTIRE 2024 Quality Assessment of AI-Generated Content Challenge, which will be held in conjunction with the New Trends in Image Restoration and Enhancement Workshop (NTIRE) at CVPR 2024. This challenge is to address a major challenge in the field of image and video processing, namely, Image Quality Assessment (IQA) and Video Quality

Hanyin Wang, Chufan Gao, Bolun Liu, Qiping Xu

Proprietary Large Language Models (LLMs) such as GPT-4 and Gemini have demonstrated promising capabilities in clinical text summarization tasks. However, due to patient data privacy concerns and computational costs, many healthcare providers prefer using small, locally-hosted models over external generic LLMs. This study presents a comprehensive domain- and

Jian Ren, F. S. Liu, Nan Li, Qifan Cui

The measurements of morphological indicators of galaxies are often influenced by a series of observational effects. In this study, we utilize a sample of over 800 TNG50 simulated galaxies with log($M_*$/M$_\odot$)$>9$ at $0.5<z<3$ to investigate the differences in non-parametric morphological indicators ($C$, $S$, $Gini$, $M_{\rm 20}$, $A_{\rm O}$, and $D_{\

Huiyu Zhai, Mo Chen, Xingxing Yang, Gusheng Kang

The NIR-to-RGB spectral domain translation is a formidable task due to the inherent spectral mapping ambiguities within NIR inputs and RGB outputs. Thus, existing methods fail to reconcile the tension between maintaining texture detail fidelity and achieving diverse color variations. In this paper, we propose a Multi-scale HSV Color Feature Embedding Network

Stefan Meggendorfer, Guido Kanschat, Johannes Kraus

This paper addresses the construction and analysis of a class of domain decomposition methods for the iterative solution of the quasi-static Biot problem in three-field formulation. The considered discrete model arises from time discretization by the implicit Euler method and space discretization by a family of strongly mass-conserving methods exploiting $H^

Tianheng Wei, Yanzhao Liu, Wei Ren, Zhen Liang

In unconventional high-temperature (high-Tc) superconductors, the pair density wave state, an exotic superconducting order showing spatially periodic order parameter modulations with the period of several unit cells and translational symmetry breaking, has attracted broad attention. However, the superconducting pair density modulation within a single unit ce

V. H. Mikaelian

An exhaustive version of the thesis to a talk presented at the Groups \& Algebras in Bicocca Conference (GABY), University of Milano-Bicocca (Milan, Italy), June 17 to June 21, 2024.

Oisín Flynn-Connolly

This is the first in a sequence of articles exploring the relationship between commutative algebras and $E_\infty$-algebras in characteristic $p$ and mixed characteristic. In this paper we lay the groundwork by defining a new class of cohomology operations over $\mathbb F_p$ called cotriple products, generalising Massey products. We compute the secondary coh

Dicong Liang, Siyuan Chen, Chao Zhang, Lijing Shao

With the strong evidence for a gravitational wave (GW) background in the nanohertz frequency band from pulsar timing arrays, the detection of continuous GWs from individual supermassive black hole binaries is already at the dawn. Utilizing continuous GWs to test theories of gravity, especially to test the polarizations of GWs is becoming more and more realis

Sandro Franceschi

We study a space-time Brownian motion with drift B(t)=(t_0+t,y_0+W(t)+t) killed at the moving boundary of the cone {(t,x):0<x<t}. This article determines the parabolic Martin boundary and all harmonic functions associated with this process. To that end, the asymptotics of Green's functions are determined along all directions. We also find the exit probabilit

Han Wang, Xinning Chai, Yiwen Wang, Yuhong Zhang

Colorizing grayscale images offers an engaging visual experience. Existing automatic colorization methods often fail to generate satisfactory results due to incorrect semantic colors and unsaturated colors. In this work, we propose an automatic colorization pipeline to overcome these challenges. We leverage the extraordinary generative ability of the diffusi

Alice C. Quillen, Sean Doran

We measure ejecta mass as a function of azimuthal and impact angle for 104 m/s oblique impacts into sand. We find that the ejecta mass distribution is strongly sensitive to azimuthal angle with as high as 8 times more mass in ejecta on the downrange side compared to the uprange side. Crater radii, measured from the impact point, are measured at different imp

Méric L. Augat, Robert T. W. Martin, Eli Shamovich

A realization is a triple, $(A,b,c)$, consisting of a $d-$tuple, $A= (A =_1, \cdots, A_d )$, $d\in \mathbb{N}$, of bounded linear operators on a separable, complex Hilbert space, $\mathcal{H}$, and vectors $b,c \in \mathcal{H}$. Any such realization defines a (uniformly) analytic non-commutative (NC) function in an open neighbourhood of the origin, $0:= (0,

B. Hamil, B. C. Lütfüoğlu, F. Ahmed, Z. Yousaf

In this paper, we introduce a metric ansatz designed to describe spherically symmetric quantum-corrected black hole (BH) space-time within an AdS space background, incorporating both an ordinary and a phantom global monopole. Our study focus into the thermodynamic properties of this BH, where we compute key parameters such as the Hawking temperature and spec

Yifan Chen, Ran Ding, Yuxin Liu, Yosuke Mizuno

The Event Horizon Telescope (EHT) has significantly advanced our ability to study black holes, achieving unprecedented spatial resolution and revealing horizon-scale structures. Notably, these observations feature a distinctive dark shadow--primarily arising from faint jet emissions--surrounded by a bright photon ring. Anticipated upgrades of the EHT promise

Diego Martinez-Baselga, Luis Riazuelo, Luis Montano

Autonomous navigation in dynamic environments is a complex but essential task for autonomous robots, with recent deep reinforcement learning approaches showing promising results. However, the complexity of the real world makes it infeasible to train agents in every possible scenario configuration. Moreover, existing methods typically overlook factors such as

Xiangdong Zhang, Jinbo Hu, Da-Wu Xiao, Nan Zhao

In magnetic resonance experiments, it is widely recognized that a nonuniform magnetic field can lead to an increase in the resonance line width, as well as a reduction in sensitivity and spectral resolution. However, a nonuniform magnetic field can also cause shifts in resonance frequency, which has received far less attention. In this work, we investigate t

Matthew Squires, Xiaohui Tao, Soman Elangovan, Raj Gururajan

Repetitive Transcranial Magnetic Stimulation (rTMS) is a well-supported, evidence-based treatment for depression. However, patterns of response to this treatment are inconsistent. Emerging evidence suggests that artificial intelligence can predict rTMS treatment outcomes for most patients using fMRI connectivity features. While these models can reliably pred

Hongxia Xie, Chu-Jun Peng, Yu-Wen Tseng, Hung-Jen Chen

Visual Instruction Tuning represents a novel learning paradigm involving the fine-tuning of pre-trained language models using task-specific instructions. This paradigm shows promising zero-shot results in various natural language processing tasks but is still unexplored in vision emotion understanding. In this work, we focus on enhancing the model's proficie

Jixuan Li, Yang Gao, Di Li, Kinwah Wu

A firm establishment of the presence or the lack of periodicity in repeating Fast Radio Bursts (FRBs) is crucial for determining their origins. Here we compile 1145 radio bursts of FRB 20121102A with fluence larger than 0.15 Jy ms from observations using the Five-hundredmeter Aperture Spherical radio Telescope, Arecibo Observatory, Green Bank Telescope, Effe

Travis J. Thieme, Shih-Ping Lai, Yueh-Ning Lee, Sheng-Jun Lin

Protostars are born in magnetized environments. As a consequence, the formation of protostellar disks can be suppressed by the magnetic field efficiently removing angular momentum of the infalling material. Non-ideal MHD effects are proposed to as one way to allow protostellar disks to form. Thus, it is important to understand their contributions in observat

Ana María Zamora-Vinaroz, Pablo de Vera, Isabel Abril, Rafael Garcia-Molina

We have determined the depth-dose curve, the penetration range, and the water equivalent ratio (WER), for proton beams of clinical energies in cortical bone, by means of a detailed and accurate simulation that combines molecular dynamics and Monte Carlo techniques. The fundamental input quantities (stopping power and energy loss straggling) for the simulatio

José L. Cereceda

For integer $k \geq 1$, let $S_k(n)$ denote the sum of the $k$th powers of the first $n$ positive integers. In this paper, we derive a new formula expressing $2^{2k}$ times $S_{2k}(n)$ as a sum of $k$ terms involving the numbers in the $k$th row of the integer sequence A304330, which is closely related to the central factorial numbers with even indices of th

Junfeng Ni, Yixin Chen, Bohan Jing, Nan Jiang

We address the issue of physical implausibility in multi-view neural reconstruction. While implicit representations have gained popularity in multi-view 3D reconstruction, previous work struggles to yield physically plausible results, limiting their utility in domains requiring rigorous physical accuracy. This lack of plausibility stems from the absence of p

Hana Mizerová, Katarína Tvrdá

Runge-Kutta methods have an irreplaceable position among numerical methods designed to solve ordinary differential equations. Especially, implicit ones are suitable for approximating solutions of stiff initial value problems. We propose a new way of deriving coefficients of implicit Runge-Kutta methods. This approach based on repeated integrals yields both n

Yannik Stradmann, Julian Göltz, Mihai A. Petrovici, Johannes Schemmel

With an increasing presence of science throughout all parts of society, there is a rising expectation for researchers to effectively communicate their work and, equally, for teachers to discuss contemporary findings in their classrooms. While the community can resort to an established set of teaching aids for the fundamental concepts of most natural sciences

Chih-Hong Cheng, Changshun Wu, Xingyu Zhao, Saddek Bensalem

The deployment of generative AI (GenAI) models raises significant fairness concerns, addressed in this paper through novel characterization and enforcement techniques specific to GenAI. Unlike standard AI performing specific tasks, GenAI's broad functionality requires ``conditional fairness'' tailored to the context being generated, such as demographic fairn

Jesse Beisegel, Fabienne Ratajczak, Robert Scheffler

When solving the Hamiltonian path problem it seems natural to be given additional precedence constraints for the order in which the vertices are visited. For example one could decide whether a Hamiltonian path exists for a fixed starting point, or that some vertices are visited before another vertex. We consider the problem of finding a Hamiltonian path that

Aleksandar Ichkov, Aron Schott, Niklas Beckmann, Ljiljana Simić

Agile beam management is key for providing seamless millimeter wave (mm-wave) connectivity given the site-specific spatio-temporal variations of the mm-wave channel. Leveraging non radio frequency (RF) sensor inputs for environment awareness, e.g. via machine learning (ML) techniques, can greatly enhance RF-based beam steering. To overcome the lack of divers

Xuying Zhang, Jixuan Li, Yang Gao, Qian Lei

Radio bursts of magnetically active stars reveal the intensity and activity of the stellar magnetic field. They may also be related to the planets around the stars. We monitored a radio-active star, AD Leonis, 3000 seconds per day for 17 days in November 2020, and 5000 seconds per day for 5 days in July 2023 with the Five-hundred-meter Aperture Spherical rad

Juyong Lee, Taywon Min, Minyong An, Dongyoon Hahm

Mobile device control agents can largely enhance user interactions and productivity by automating daily tasks. However, despite growing interest in developing practical agents, the absence of a commonly adopted benchmark in this area makes it challenging to quantify scientific progress. In this work, we introduce B-MoCA: a novel benchmark with interactive en

Sangryul Kim, Donghee Han, Sehyun Kim

Recently, deep learning-based language models have significantly enhanced text-to-SQL tasks, with promising applications in retrieving patient records within the medical domain. One notable challenge in such applications is discerning unanswerable queries. Through fine-tuning model, we demonstrate the feasibility of converting medical record inquiries into S

João dos Reis Frazão, Vincent van Vliet, Kadir Gümüş, Menno van den Hout

Real-time CV-QKD receiver achieves peak 2.9 Mbit/s secret-key-rates over 12.8 km of fiber, while co-propagating 15 classical channels, separated 1 nm from the quantum signal. Performance degrades at higher launch powers due to crosstalk.

A. Emir Gumrukcuoglu, James Burridge, Kieran O'Regan, Emma Kendrick

Data collected using the galvanostatic intermittent titration technique (GITT) and application of the Sand equation is a ubiquitous method for inferring the solid-state diffusivity in lithium-ion battery active materials. However, the experiment is notoriously time-consuming and the Sand equation relies on assumptions whose applicability can be questionable.

Yiwen Ding

We build a one-to-one correspondence between $3$-dimensional (generic) crystabelline representations of the absolute Galois group of $\mathbb{Q}_p$ and certain locally analytic representations of $\mathrm{GL}_3(\mathbb{Q}_p)$. We show that the correspondence can be realized in subspaces of $p$-adic automorphic representations.

Sebastián Basterrech, Line Clemmensen, Gerardo Rubino

Modeling non-stationary data is a challenging problem in the field of continual learning, and data distribution shifts may result in negative consequences on the performance of a machine learning model. Classic learning tools are often vulnerable to perturbations of the input covariates, and are sensitive to outliers and noise, and some tools are based on ri

Xiu-e Zhang, Xue Wei, Wei-Bo Cui, Jin-Pu Bai

Recently, two-photon fluorescent probes based on anthocyanidins molecules have attracted extensive attention due to their outstanding photophysical properties. However, there are only a few two-photon excited fluorescent probes that really meet the requirements of relatively long emission wavelengths (>600 nm), large two-photon absorption (TPA) cross section