May 2023 arXiv papers — page 167

Helena La, Abel Brokkelkamp, Stijn van der Lippe, Jaco ter Hoeve

Among the many potential applications of topological insulator materials, their broad potential for the development of novel tunable plasmonics at THz and mid-infrared frequencies for quantum computing, terahertz detectors, and spintronic devices is particularly attractive. The required understanding of the intricate relationship between nanoscale crystal st

Andrew J. Larkoski, Jesse Thaler

By quantifying the distance between two collider events, one can triangulate a metric space and reframe collider data analysis as computational geometry. One popular geometric approach is to first represent events as an energy flow on an idealized celestial sphere and then define the metric in terms of optimal transport in two dimensions. In this paper, we a

Joshua V. Shields, Prasiddha Arunachalam, Wolfgang Kerzendorf, John P. Hughes

The community agrees that Type Ia supernovae arise from Carbon/Oxygen white dwarfs undergoing thermonuclear runaway. However, the full progenitor system and the process that prompts the white dwarf to explode remain unknown. Most current models suggest that the white dwarf explodes because of interaction with a binary companion which may survive the process

Jae Hyeok Chang, Reza Ebadi, Xuheng Luo, Erwin H. Tanin

Recent studies reveal that more than a dozen of white dwarfs displaying near-perfect blackbody spectra in the optical range have been lurking in the Sloan Digital Sky Survey catalog. We point out that, in a way analogous to the Cosmic Microwave Background, these stars serve as excellent testbeds for new physics. Specifically, we show how their observed lack

Jonathan Steinberg, H. Chau Nguyen, Matthias Kleinmann

The activation of Bell nonlocality is a protocol that enables the violation of a Bell inequality from a system that initially did not allow for any such violation because the state of the system was Bell-local. This activation of hidden Bell nonlocality has been demonstrated in experiments; however, while the certification of Bell nonlocality is conceptional

Yixuan Li

Local supersymmetry enhancement (LSE) is a formalism intended to identify information needed to describe microstates of supersymmetric black holes that are realised as brane systems. After illustrating the relationship between LSE and black-hole microstates with the F1-P system, we review two possible strategies to apply the LSE mechanism to get microstates

Toni Bertólez-Martínez, Carlos A. Argüelles, Ivan Esteban, Jacobo Lopez-Pavon

Recently, the ANITA collaboration announced the detection of new, unsettling upgoing Ultra-High-Energy (UHE) events. Understanding their origin is pressing to ensure success of the incoming UHE neutrino program. In this work, we study their internal consistency and the implications of the lack of similar events in IceCube. We introduce a generic, simple para

Alejandro Pozas-Kerstjens, Antoine Girardin, Tamás Kriváchy, Armin Tavakoli

We investigate network nonlocality in the triangle scenario when all three parties have no input and binary outputs. Through an explicit example, we prove that this minimal scenario supports nonlocal correlations compatible with no-signaling and independence of the three sources, but not with realisations based on independent quantum or classical sources. Th

Marco Astorino, Giovanni Boldi

We present a general procedure, based on the Ehlers transformation of the Ernst equations, to add the gravitomagnetic mass to the whole Plebanski-Demianski family of solutions. We can efficiently generate a large class of accelerating black holes, such as Reissner-Nordstrom or Kerr-Newman, endowed with the NUT parameter. The full rotating version carries a c

Bo Li, Yuanhan Zhang, Liangyu Chen, Jinghao Wang

Recent advances in Large Multimodal Models (LMMs) have unveiled great potential as visual assistants. However, most existing works focus on responding to individual instructions or using previous dialogues for contextual understanding. There is little discussion on employing both images and text as in-context examples to enhance the instruction following cap

Pranav Kukreti, Raffaella Morganti, Clive Tadhunter, Francesco Santoro

Feedback from AGN is known to affect the host galaxy's evolution. In radio AGN, one manifestation of feedback is seen in gas outflows. However, it is still not well understood whether the effect of feedback evolves with the radio AGN life cycle. In this study, we investigate this link using the radio spectral shape as a proxy for the evolutionary stage of th

Yunze Man, Liang-Yan Gui, Yu-Xiong Wang

Closing the domain gap between training and deployment and incorporating multiple sensor modalities are two challenging yet critical topics for self-driving. Existing work only focuses on single one of the above topics, overlooking the simultaneous domain and modality shift which pervasively exists in real-world scenarios. A model trained with multi-sensor d

Evgeni Dimitrov, Christian Serio

We consider the Dyson Ferrari--Spohn diffusion $\mathcal{X}^N = (\mathcal{X}^N_1,\dots,\mathcal{X}^N_N)$, consisting of $N$ non-intersecting Ferrari--Spohn diffusions $\mathcal{X}^N_1 > \cdots > \mathcal{X}^N_N > 0$ on $\mathbb{R}$. This object was introduced by Ioffe, Velenik, and Wachtel (2018) as a scaling limit for line ensembles of $N$ non-intersecting

Spencer Dowdall, Howard Masur

This paper concerns the lattice counting problem for the mapping class group of a surface $S$ acting on Teichm\"uller space with the Teichm\"uller metric. In that problem the goal is to count the number of mapping classes that send a given point $x$ into the ball of radius $R$ centered about another point $y$. For the action of the entire group, Athreya, Buf

Xiuwei Xu, Zhihao Sun, Ziwei Wang, Hongmin Liu

In this paper, we propose an efficient feature pruning strategy for 3D small object detection. Conventional 3D object detection methods struggle on small objects due to the weak geometric information from a small number of points. Although increasing the spatial resolution of feature representations can improve the detection performance on small objects, the

Oluwatosin Ogundare, Subuola Sofolahan

This study investigates the potential of an ambulatory device that incorporates Large Language Models (LLMs) in cadence with other specialized ML models to assess anemia severity in sickle cell patients in real time. The device would rely on sensor data that measures angiogenic material levels to assess anemia severity, providing real-time information to pat

Xiao Ling, Tim Menzies

Testing complex simulation models can be expensive and time consuming. Current state-of-the-art methods that explore this problem are fully-supervised; i.e. they require that all examples are labeled. On the other hand, the GenClu system (introduced in this paper) takes a semi-supervised approach; i.e. (a) only a small subset of information is actually label

Ekta Prashnani, Koki Nagano, Shalini De Mello, David Luebke

Modern avatar generators allow anyone to synthesize photorealistic real-time talking avatars, ushering in a new era of avatar-based human communication, such as with immersive AR/VR interactions or videoconferencing with limited bandwidths. Their safe adoption, however, requires a mechanism to verify if the rendered avatar is trustworthy: does it use the app

John J. Cherian, Emmanuel J. Candès

Before deploying a black-box model in high-stakes problems, it is important to evaluate the model's performance on sensitive subpopulations. For example, in a recidivism prediction task, we may wish to identify demographic groups for which our prediction model has unacceptably high false positive rates or certify that no such groups exist. In this paper, we

Yujiang Wang, Anshul Thakur, Mingzhi Dong, Pingchuan Ma

The prevalence of artificial intelligence (AI) has envisioned an era of healthcare democratisation that promises every stakeholder a new and better way of life. However, the advancement of clinical AI research is significantly hurdled by the dearth of data democratisation in healthcare. To truly democratise data for AI studies, challenges are two-fold: 1. th

Anshul Thakur, Tingting Zhu, Vinayak Abrol, Jacob Armstrong

The lack of data democratization and information leakage from trained models hinder the development and acceptance of robust deep learning-based healthcare solutions. This paper argues that irreversible data encoding can provide an effective solution to achieve data democratization without violating the privacy constraints imposed on healthcare data and clin

Victor Lherm, Renaud Deguen

Drop impact experiments allow the modelling of a wide variety of natural processes, from raindrop impacts to planetary impact craters. In particular, interpreting the consequences of planetary impacts requires an accurate description of the flow associated with the cratering process. In our experiments, we release a liquid drop above a deep liquid pool to in

Bérengère Podvin, Laurent Soucasse, François Yvon

We apply a probabilistic clustering method, Latent Dirichlet Allocation (LDA), to characterize the largescale dynamics of Rayleigh-B\'enard convection. The method, introduced in Frihat et al. 2021, is applied to a collection of snapshots in the vertical mid-planes of a cubic cell for Rayleigh numbers in the range [106, 108]. For the convective heat flux, tem

Michaela Brunner, Hye Hyun Lee, Alexander Hepp, Johanna Baehr

Reverse engineering (RE) of finite state machines (FSMs) is a serious threat when protecting designs against RE attacks. While most recent protection techniques rely on the security of a secret key, this work presents a new approach: hardware FSM honeypots. These honeypots lead the RE tools to a wrong but, for the tools, very attractive FSM, while making the

Daniel Ladwig, Bianca Lamm, Janis Keuper

In this paper, we describe a first publicly available fine-grained product recognition dataset based on leaflet images. Using advertisement leaflets, collected over several years from different European retailers, we provide a total of 41.6k manually annotated product images in 832 classes. Further, we investigate three different approaches for this fine-gra

R. K. Kremer, A. Bussmann-Holder, H. Keller

K. Alex M\"uller started his scientific career in 1958 when he was about thirty-one years old. After his wife passed away and being in his nineties, his interest in physics gradually faded. In those years shortly before he passed away, on January 9, 2023, he was no longer interested in superconductivity or ferroelectricity, he had become essentially devoted

Ben Chen, Ke Guan, Danping He, Pengxiang Xie

The terahertz (THz) band (0.1-10 THz) is widely considered to be a candidate band for the sixth-generation mobile communication technology (6G). However, due to its short wavelength (less than 1 mm), scattering becomes a particularly significant propagation mechanism. In previous studies, we proposed a scattering model to characterize the scattering in THz b

Fernando G. Gardim, André V. Giannini, Frédérique Grassi, Kevin P. Pala

Ultrarelativistic isobar collisions have been proposed as a useful tool to investigate nuclear structure. These systems are not created in equilibrium, rather undergo a pre-thermalization stage. In this stage, some of the initial structure information may be lost and additional effects introduced. The objective of this paper is to study this possibility in t

Daniele Guerci, Yuncheng Mao, Christophe Mora

We study trilayer graphene arranged in a staircase stacking configuration with equal consecutive twist angle. On top of the moir\'e cristalline pattern, a supermoir\'e long-wavelength modulation emerges that we treat adiabatically. For each valley, we find that the two central bands are topological with Chern numbers $C=\pm 1$ forming a Chern mosaic at the s

Yunxin Li, Baotian Hu, Xinyu Chen, Lin Ma

Training a Multimodal Large Language Model (MLLM) from scratch, like GPT-4, is resource-intensive. Regarding Large Language Models (LLMs) as the core processor for multimodal information, our paper introduces LMEye, a human-like eye with a play-and-plug interactive perception network, designed to enable dynamic interaction between LLMs and external vision in

Ankur Agrawal, Akash V. Dixit, Tanay Roy, Srivatsan Chakram

The manipulation of quantum states of light has resulted in significant advancements in both dark matter searches and gravitational wave detectors [1-4]. Current dark matter searches operating in the microwave frequency range use nearly quantum-limited amplifiers [3, 5, 6]. Future high frequency searches will use photon counting techniques [1] to evade the s

Aishat Aloba, Sarah Morrison-Smith, Aaliyah Richlen, Kimberly Suarez

As users shift from interacting actively with devices with screens to interacting seamlessly with smart environments, novel models of user authentication will be needed to maintain the security and privacy of user data. To understand users' attitudes toward new models of authentication (e.g., voice recognition), we surveyed 117 Amazon Turk workers and 43 com

Md Mesbah Uddin

Developing a new class of coating materials is necessary to meet the increasing demands of energy and defense-related technologies, aerospace engineering, and harsh environmental conditions. Functional-based coatings, such as ceramic-metal nanolaminates, have gained popularity due to their ability to be customized according to specific requirements. To desig

S. S. Agaev, K. Azizi, B. Barsbay, H. Sundu

The fully charmed hadronic scalar molecules $\mathcal{M}_1=\eta_c \eta_c$ and $\mathcal{M}_2=\chi_{c0}\chi_{c0}$ are studied in the context of the QCD sum rule method. The masses $m$, $\widetilde{m}$ and current couplings $f$, $ \widetilde{f}$ of these states are calculated using the two-point sum rule approach. The obtained results $m=(6264 \pm 50)~\mathrm{

Jiacheng Liu, Wenya Wang, Dianzhuo Wang, Noah A. Smith

Despite the much discussed capabilities of today's language models, they are still prone to silly and unexpected commonsense failures. We consider a retrospective verification approach that reflects on the correctness of LM outputs, and introduce Vera, a general-purpose model that estimates the plausibility of declarative statements based on commonsense know

Benoît Ferté, Xiangyu Cao

We propose a solvable model of Quantum Darwinism to encoding transitions -- abrupt changes in how quantum information spreads in a many-body system under unitary dynamics. We consider a random Clifford circuit on an expanding tree, whose input qubit is entangled with a reference. The model has a Quantum Darwinism phase, where one classical bit of information

Chetan Gupta, Rustam Latypov, Yannic Maus, Shreyas Pai

We present a deterministic algorithm for solving a wide range of dynamic programming problems in trees in $O(\log D)$ rounds in the massively parallel computation model (MPC), with $O(n^\delta)$ words of local memory per machine, for any given constant $0 < \delta < 1$. Here $D$ is the diameter of the tree and $n$ is the number of nodes--we emphasize that ou

Katja Gosar, Vesna Pirc Jevšenak, Tadej Mežnaršič, Samo Beguš

We observe dark-state polariton collapses and revivals in a quantum memory based on electromagnetically induced transparency on a cloud of cold cesium atoms in a magnetic field. Using $\sigma^+$ polarized signal and control beams in the direction of the magnetic field, we suppress the dark-state polariton collapses by polarizing the atoms towards one of the

Rémi Nahon, Van-Tam Nguyen, Enzo Tartaglione

Despite significant research efforts, deep neural networks are still vulnerable to biases: this raises concerns about their fairness and limits their generalization. In this paper, we propose a bias-agnostic approach to mitigate the impact of bias in deep neural networks. Unlike traditional debiasing approaches, we rely on a metric to quantify ``bias alignme

Boris Pittel

We study the distribution of the number of leaves of the subtree chosen uniformly at random among all the subtrees of the critical branching process tree at extinction.

Arijit Ray, Filip Radenovic, Abhimanyu Dubey, Bryan A. Plummer

Compositional reasoning is a hallmark of human visual intelligence. Yet, despite the size of large vision-language models, they struggle to represent simple compositions by combining objects with their attributes. To measure this lack of compositional capability, we design Cola, a text-to-image retrieval benchmark to Compose Objects Localized with Attributes

Zeqi Tan, Shen Huang, Zixia Jia, Jiong Cai

The MultiCoNER \RNum{2} shared task aims to tackle multilingual named entity recognition (NER) in fine-grained and noisy scenarios, and it inherits the semantic ambiguity and low-context setting of the MultiCoNER \RNum{1} task. To cope with these problems, the previous top systems in the MultiCoNER \RNum{1} either incorporate the knowledge bases or gazetteer

Vincenzo Minissale, Salvatore Plumari, Yifeng Sun, Vincenzo Greco

We study the production of charmed and multi-charmed hadrons in ultra-relativistic Heavy Ion Collisions coupling the transport approach for charm dynamics in the medium to an hybrid hadronization model of coalescence plus fragmentation. In this paper, we mainly discuss the particle yields for single charmed and multi-charmed baryons focusing mainly on the pr

Xiyue Zhang, Benjie Wang, Marta Kwiatkowska

Neural network verification mainly focuses on local robustness properties, which can be checked by bounding the image (set of outputs) of a given input set. However, often it is important to know whether a given property holds globally for the input domain, and if not then for what proportion of the input the property is true. To analyze such properties requ

Daniel Rudolf, Philip Schär

Polar slice sampling, a Markov chain construction for approximate sampling, performs, under suitable assumptions on the target and initial distribution, provably independent of the state space dimension. We extend the aforementioned result of Roberts & Rosenthal (2002) by developing a theory which identifies conditions, in terms of a generalized level set fu

Mahsa Noroozi, Flavio Gallistl, Majid Noroozi

Multipath QUIC is a transport protocol that allows for the use of multiple network interfaces for a single connection. It thereby offers, on the one hand, the possibility to gather a higher throughput, while, on the other hand, multiple paths can also be used to transmit data redundantly. Selective redundancy combines these two applications and thereby offer

Dessislava Kochloukova, Pavel Zalesskii

Let $\mathcal{C}$ be a class of finite groups closed for subgroups, quotients groups and extensions. Let $\Gamma$ be a finite simplicial graph and $G = G_{\Gamma}$ be the corresponding pro-$\mathcal C$ RAAG. We show that if $N$ is a non-trivial finitely generated, normal, full pro-$\mathcal C$ subgroup of $G$ then $G/ N$ is finite-by-abelian. In the pro-$p$

C. Silva, R. Cabrita, V. N. Solovov, P. Brás

We present a novel method, based on the Saunderson corrections, to predict the reflectance between a liquid interface and a dielectric diffuser. In this method, the diffuse properties of the dielectric are characterized using a single parameter, the multiple-scattering albedo, which is the same irrespective of being in contact with air or liquid. We tested t

Liu Tao, Nina Brown, Paul Fulda

Odd-indexed higher-order Hermite-Gauss (HG) modes are compatible with 4-quadrant segmented mirrors due to their intensity nulls along the principal axes, which guarantees minimum beam intensity illuminating the bond lines between the segments thus leading to low power loss. However, a misplaced HG beam can cause extra power loss due to the bright intensity s

Kovila P. L. Coopamootoo, Magdalene Ng

There are indications in literature that women do not engage with security and privacy (SP) technologies, meant to keep them safe online, in the same way as men do. To better understand this gender gap, we conduct an online survey with N=604 U.K. participants, to elicit SP advice source preference and usage of SP methods and technologies. We find evidence of

J. A. Toalá, O. González-Martín, M. Karovska, R. Montez

We present the analysis of archival XMM-Newton and Chandra observations of CH Cyg, one of the most studied symbiotic stars (SySts). The combination of the high-resolution XMM-Newton RGS and Chandra HETG X-ray spectra allowed us to obtain reliable estimates of the chemical abundances and to corroborate the presence of multi-temperature X-ray-emitting gas. Spe

Yichi Zhang, Rushi Jiao

Due to the flexibility of prompting, foundation models have become the dominant force in the domains of natural language processing and image generation. With the recent introduction of the Segment Anything Model (SAM), the prompt-driven paradigm has entered the realm of image segmentation, bringing with a range of previously unexplored capabilities. However

Toby Driscoll, Yuji Nakatsukasa, Lloyd N. Trefethen

AAA rational approximation has normally been carried out on a discrete set, typically hundreds or thousands of points in a real interval or complex domain. Here we introduce a continuum AAA algorithm that discretizes a domain adaptively as it goes. This enables fast computation of high-accuracy rational approximations on domains such as the unit interval, th

Shuaiqi Zhang, Zhen-Qing Chen

In this paper, we study optimal stochastic control problems for stochastic systems driven by non-Markov sub-diffusion $B_{L_t}$, which have the mixed features of deterministic and stochastic controls. Here $B_t$ is the standard Brownian motion on $R$, and $L_t:= \inf\{r>0: S_r>t\}, \quad t\geq 0,$ is the inverse of a subordinator $S_t$ with drift $\kappa >0$

Sanjib Kumar Agarwalla, Mauricio Bustamante, Sudipta Das, Ashish Narang

The discovery of new, flavor-dependent neutrino interactions would provide compelling evidence of physics beyond the Standard Model. We focus on interactions generated by the anomaly-free, gauged, abelian lepton-number symmetries, specifically $L_e-L_\mu$, $L_e-L_\tau$, and $L_\mu-L_\tau$, that introduce a new matter potential sourced by electrons and neutro

Tiago C Dias, Chloé Fromentin, Luís L Alves, Antonio Tejero-del-Caz

This work presents a reaction mechanism for oxygen plasmas, i.e. a set of reactions and corresponding rate coefficients that are validated against benchmark experiments. The kinetic scheme is validated in a DC glow discharge for gas pressures of 0.2-10 Torr and currents of 10-40 mA, using the 0D LisbOn KInetics (LoKI) simulation tool and available experiment

Kris Mackewicz, Craig Hogan

We analyze the classical linear gravitational effect of idealized pion-like dynamical systems, consisting of light quarks connected by attractive gluonic material with a stress-energy $p=-\rho c^2$ in one or more dimensions. In one orbit of a system of total mass $M$, quarks of mass $m<<M$ expand apart initially with $v/c\sim 1$, slow due to the gluonic attr

Björn Sbierski, Marcus Bintz, Shubhayu Chatterjee, Michael Schuler

Motivated by a recent experiment on a square-lattice Rydberg atom array realizing a long-range dipolar XY model [Chen et al., Nature (2023)], we numerically study the model's equilibrium properties. We obtain the phase diagram, critical properties, entropies, variance of the magnetization, and site-resolved correlation functions. We consider both ferromagnet

Kanaya Malakar, Rafael I. Rubenstein, Dapeng Bi, Bulbul Chakraborty

The organization of cells within tissues plays a vital role in various biological processes, including development and morphogenesis. As a result, understanding how cells self-organize in tissues has been an active area of research. In our study, we explore a mechanistic model of cellular organization that represents cells as force dipoles that interact with

Shi-Dong Liang, Matthew J. Lake

In recent years, many new developments in theoretical physics, and in practical applications rely on different techniques of noncommutative algebras. In this review, we introduce the basic concepts and techniques of noncommutative physics in a range of areas, including classical physics, condensed matter systems, statistical mechanics, and quantum mechanics,

Allison W. Teixeira, Mykola Tasinkevych, Cristóvão S. Dias

Motivated by recent experimental results that reveal rich collective dynamics of thousands-to-millions of active liquid crystal skyrmions we have developed a coarse grained particle-based model of the dynamics of skyrmions in dilute regime. The basic physical mechanism of the skyrmion motion is related to the non-reciprocal rotational dynamics of the liquid

Chaoming Song

Recently, there has been renewed interest in a crossing-symmetric dispersion relation from the 1970s due to its implications for both regular quantum field theory and conformal field theory. However, this dispersion relation introduces nonlocal spurious singularities and requires additional locality constraints for their removal, a process that presents cons

Andrea Burns, Krishna Srinivasan, Joshua Ainslie, Geoff Brown

Webpages have been a rich, scalable resource for vision-language and language only tasks. Yet only pieces of webpages are kept in existing datasets: image-caption pairs, long text articles, or raw HTML, never all in one place. Webpage tasks have resultingly received little attention and structured image-text data left underused. To study multimodal webpage u

Marie-Sophie Hartig, Gudrun Wanner

Tilt-to-length coupling was the limiting noise source in LISA Pathfinder between 20 and 200 mHz before subtraction in post-processing. To prevent the adding of sensing noise to the data by the subtraction process, the success of this strategy depended on a previous direct noise reduction by test mass alignment. The exact dependency of the level of tilt-to-le

Badal Mondal, Julia Westermayr, Ralf Tonner-Zech

Quaternary III-V semiconductors are one of the major promising material classes in optoelectronics. The bandgap and its character, direct or indirect, are the most important fundamental properties determining the performance and characteristics of optoelectronic devices. Experimental approaches screening a large range of possible combinations of III- and V-e

LSD Collaboration, T. Appelquist, R. C. Brower, K. K. Cushman

We analyze newly expanded and refined data from lattice studies of an SU(3) gauge theory with eight Dirac fermions in the fundamental representation. We focus on the light composite states emerging from these studies, consisting of a set of pseudoscalars and a single light scalar. We first consider the view that this theory is just outside the conformal wind

Francesco Pogliano, Ann-Cecilie Larsen

Studies attempting to quantify the sensitivity of the $r$-process abundances to nuclear input have to cope with the fact that the theoretical models they rely on, rarely come with confidence intervals. This problem has been dealt with by either estimating these intervals and propagating them statistically to the final abundances using reaction networks withi

Benjamin Loewe, Tyler N. Shendruk

Run-and-tumble processes successfully model several living systems. While studies have typically focused on particles with isotropic tumbles, recent examples exhibit "tumble-turns", in which particles undergo 90{\deg} tumbles and so possess explicitly anisotropic dynamics. We study the consequences of such tumble-turn anisotropicity at both short and long-ti

Bharat Srikishan, Samantha Kleinberg

Using observational data to learn causal relationships is essential when randomized experiments are not possible, such as in healthcare. Discovering causal relationships in time-series health data is even more challenging when relationships change over the course of a disease, such as medications that are most effective early on or for individuals with sever

Dmitriy Umerenkov, Oleg Cherkashin, Alexander Nesterov, Victor Gombolevskiy

In this paper we present a novel approach to risk assessment for patients hospitalized with pneumonia or COVID-19 based on their admission reports. We applied a Longformer neural network to admission reports and other textual data available shortly after admission to compute risk scores for the patients. We used patient data of multiple European hospitals to

Mercy Ranjit, Gopinath Ganapathy, Ranjit Manuel, Tanuja Ganu

We propose Retrieval Augmented Generation (RAG) as an approach for automated radiology report writing that leverages multimodally aligned embeddings from a contrastively pretrained vision language model for retrieval of relevant candidate radiology text for an input radiology image and a general domain generative model like OpenAI text-davinci-003, gpt-3.5-t

Cristiano Longarini, Philip J. Armitage, Giuseppe Lodato, Daniel J. Price

Young protostellar discs are likely to be both self-gravitating, and to support grain growth to sizes where the particles decoupled from the gas. This combination could lead to short-wavelength fragmentation of the solid component in otherwise non-fragmenting gas discs, forming Earth-mass solid cores during the Class 0/I stages of Young Stellar Object evolut

Liu Tao, Anna C. Green, Paul Fulda

The locking of lasers to optical cavities is ubiquitously required in the field of precision interferometry such as Advanced LIGO to yield optimal sensitivity. Using higher-order Hermite-Gauss (HG) modes for the main interferometer beam has been a topic of recent study, due to their potential for reducing thermal noise of the test masses. It has been shown h

Tommaso Sferruzza

The property of admitting an astheno-K\"ahler metric is not stable under the action of small deformations of the complex structure of a compact complex manifold. In this paper, we prove necessary cohomological conditions for the existence of curves of astheno-K\"ahler metrics along curves of deformations starting from an initial compact complex manifold endo

Mamady Delamou, Ahmad Bazzi, Marwa Chafii, El Mehdi Amhoud

Target detection and recognition is a very challenging task in a wireless environment where a multitude of objects are located, whether to effectively determine their positions or to identify them and predict their moves. In this work, we propose a new method based on a convolutional neural network (CNN) to estimate the range and velocity of moving targets d

Massimo Lanza de Cristoforis

We prove that a condition of boundedness of the maximal function of a singular integral operator, that is known to be sufficient for the continuity of the corresponding integral operator in H\"{o}lder spaces, is actually also necessary in case the action of the integral operator does not decrease the regularity of a function. We do so in the frame of metric

Yufei Li, Zexin Li, Yingfan Gao, Cong Liu

Pre-trained transformers are popular in state-of-the-art dialogue generation (DG) systems. Such language models are, however, vulnerable to various adversarial samples as studied in traditional tasks such as text classification, which inspires our curiosity about their robustness in DG systems. One main challenge of attacking DG models is that perturbations

Amanda Matson, Claude-Michel Brauner, Peter V. Gordon

In this paper, we consider a reaction-diffusion system describing the propagation of flames under the assumption of ignition-temperature kinetics and fractional reaction order. It was shown in [3] that this system admits a traveling front solution. In the present work, we show that this traveling front is unique up to translations. We also study some qualita

Rolf Jagerman, Honglei Zhuang, Zhen Qin, Xuanhui Wang

Query expansion is a widely used technique to improve the recall of search systems. In this paper, we propose an approach to query expansion that leverages the generative abilities of Large Language Models (LLMs). Unlike traditional query expansion approaches such as Pseudo-Relevance Feedback (PRF) that relies on retrieving a good set of pseudo-relevant docu

Yang Liu, Zheru Qiu, Xinru Ji, Andrea Bancora

Erbium-doped fiber lasers exhibit high coherence and low noise as required for applications in fiber optic sensing, gyroscopes, LiDAR, and optical frequency metrology. Endowing Erbium-based gain in photonic integrated circuits can provide a basis for miniaturizing low-noise fiber lasers to chip-scale form factor, and enable large-volume applications. Yet, wh

Lauren Snider, Catherine Yan

Graphical parking functions, or $G$-parking functions, are a generalization of classical parking functions which depend on a connected multigraph $G$ having a distinguished root vertex. Gaydarov and Hopkins characterized the relationship between $G$-parking functions and another vector-dependent generalization of parking functions, the $\boldsymbol{u}$-parki

Antoine Zakardjian, Jérôme Pety, Cinthya N. Herrera, Annie Hughes

We identify giant molecular clouds (GMCs) associated with HII regions for a sample of 19 nearby galaxies using catalogs of GMCs and H regions released by the PHANGS-ALMA and PHANGS-MUSE surveys, using the overlap of the CO and H{\alpha} emission as the key criterion for physical association. We compare the distributions of GMC and HII region properties for p

Charlotte Kristjansen, Konstantin Zarembo

We consider the defect CFT defined by a 't Hooft line embedded in N=4 super Yang-Mills theory. By explicitly quantizing around the given background we exactly reproduce a prediction from S-duality for the correlators between the 't Hooft line and chiral primaries in the bulk and pave the way for higher loop analyses for non-protected operators. Furthermore,

Lorenzo Bonicelli, Matteo Boschini, Emanuele Frascaroli, Angelo Porrello

Humans can learn incrementally, whereas neural networks forget previously acquired information catastrophically. Continual Learning (CL) approaches seek to bridge this gap by facilitating the transfer of knowledge to both previous tasks (backward transfer) and future ones (forward transfer) during training. Recent research has shown that self-supervision can

Enrico Ballini, Alberto Silvio Chiappa, Stefano Micheletti

We present a deep reinforcement learning approach to a classical problem in fluid dynamics, i.e., the reduction of the drag of a bluff body. We cast the problem as a discrete-time control with continuous action space: at each time step, an autonomous agent can set the flow rate of two jets of fluid, positioned at the back of the body. The agent, trained with

Tathagata Ghosh

We develop the deformation theory of instantons on asymptotically conical $Spin(7)$-manifolds where the instanton is asymptotic to a fixed nearly $G_2$-instanton at infinity. By relating the deformation complex with spinors, we identify the space of infinitesimal deformations with the kernel of the twisted negative Dirac operator on the asymptotically conica

Carlo Baldassi, Fabio Maccheroni, Massimo Marinacci, Marco Pirazzini

We develop a full-fledged analysis of an algorithmic decision process that, in a multialternative choice problem, produces computable choice probabilities and expected decision times.

Andrew Kloosterman, Peter Troyan

We investigate whether preferences for objects received via a matching mechanism are influenced by how highly agents rank them in their reported rank order list. We hypothesize that all else equal, agents receive greater utility for the same object when they rank it higher. The addition of rankings-dependent utility implies that it may not be a dominant stra

Luca Benatti, Mattia Fogagnolo

We review some recent results about the relations among isoperimetric sets, Penrose inequalities and related concepts in the analysis of $3$-manifolds of nonnegative scalar curvature. We also show that if the isoperimetric sets of big volume have connected boundaries, the equivalence among suitable notions of mass hold.

Somin Wadhwa, Jay DeYoung, Benjamin Nye, Silvio Amir

Results from Randomized Controlled Trials (RCTs) establish the comparative effectiveness of interventions, and are in turn critical inputs for evidence-based care. However, results from RCTs are presented in (often unstructured) natural language articles describing the design, execution, and outcomes of trials; clinicians must manually extract findings perta

Bastian Hacker, Kevin Günthner, Conrad Rößler, Christoph Marquardt

We report on a novel phase-locking technique for fiber-based Mach-Zehnder interferometers based on discrete single-photon detections, and demonstrate this in a setup. Our interferometer decodes relative-phase-encoded optical pulse pairs for quantum key distribution applications and requires no locking laser in addition to the weak received signal. Our new si

Sanket Kachole, Yusra Alkendi, Fariborz Baghaei Naeini, Dimitrios Makris

In the context of robotic grasping, object segmentation encounters several difficulties when faced with dynamic conditions such as real-time operation, occlusion, low lighting, motion blur, and object size variability. In response to these challenges, we propose the Graph Mixer Neural Network that includes a novel collaborative contextual mixing layer, appli

Anakha Anson, Dipanjana Mondal, Varsha Biswas, Kusuma Urs MB

In this paper, we show the direct correlation between suppression of polaronic oxygen vacancy defect (Vo) density and gas sensor response of 1 at% Mo doped $V_2O_5$ (MVONW) nanowires. Doping 1 at% $Mo^{5+}$ leads to substitution at the $V^{5+}$ site in $V_2O_5$ nanowires (VONW) and thereby reduction in Vo defects. This in turn affects the charge carrier hopp

Hamid Tebyanian, Mujtaba Zahidy, Ronny Müller, Søren Forchhammer

Random number generators (RNG) based on quantum mechanics are captivating due to their security and unpredictability compared to conventional generators, such as pseudo-random number generators and hardware-random number generators. This work analyzes evolutions in the extractable amount of randomness with increasing the Hilbert space dimension, state prepar

Manh Hong Duong, Hung D. Nguyen

We consider a system of interacting particles governed by the generalized Langevin equation (GLE) in the presence of external confining potentials, singular repulsive forces, as well as memory kernels. Using a Mori-Zwanzig approach, we represent the system by a class of Markovian dynamics. Under a general set of conditions on the nonlinearities, we study the

Jose Ramos-Méndez, Catherine Park, Manju Sharma

Purpose: The aim of this work was, a) to assess two treatment planning strategies for accounting CT-artifacts introduced by temporary tissue-expanders(TTEs); b) to evaluate the dosimetric impact of two commercially available and one novel TTE. MethodsThe CT artifacts were managed using two strategies. 1) Identifying the metal in the RayStation treatment plan

Ferdinand Ihringer

A minimum storage regenerating (MSR) subspace family of $\mathbb{F}_q^{2m}$ is a set $\mathcal{S}$ of $m$-spaces in $\mathbb{F}_q^{2m}$ such that for any $m$-space $S$ in $\mathcal{S}$ there exists an element in $\mathrm{PGL}(2m, q)$ which maps $S$ to a complement and fixes $\mathcal{S} \setminus \{ S \}$ pointwise. We show that an MSR subspace family of $2$

Adelchi Azzalini

Consider a regression or some regression-type model for a certain response variable where the linear predictor includes an ordered factor among the explanatory variables. The inclusion of a factor of this type can take place is a few different ways, discussed in the pertaining literature. The present contribution proposes a different way of tackling this pro

Paula Onuchic, João Ramos

We consider a team-production environment where all participants are motivated by career concerns, and where a team's joint productive outcome may have different reputational implications for different team members. In this context, we characterize equilibrium disclosure of team-outcomes when team-disclosure choices aggregate individual decisions through som

Keisuke Okumura

This study extends the recently-developed LaCAM algorithm for multi-agent pathfinding (MAPF). LaCAM is a sub-optimal search-based algorithm that uses lazy successor generation to dramatically reduce the planning effort. We present two enhancements. First, we propose its anytime version, called LaCAM*, which eventually converges to optima, provided that solut