May 2024 arXiv papers — page 81

Wonwoo Kang, Heehyun Park

Curvature serves as a potent and descriptive invariant, with its efficacy validated both theoretically and practically within graph theory. We employ a definition of generalized Ricci curvature proposed by Ollivier, which Lin and Yau later adapted to graph theory, known as Ollivier-Ricci curvature (ORC). ORC measures curvature using the Wasserstein distance,

H. F. Arellano, G. Blanchon

Based on a momentum-space in-medium folding model, we disclose the universal separability of the optical potential, revealing its radial and nonlocality features at beam energies in the range 40 - 400 MeV and target mass numbers in the range $40\le A\le 208$. From this microscopic study we find that the nonlocality form factor is inherently complex and of hy

Ruiqi Li, Maowei Jiang, Kai Wang, Kaiduo Feng

Time Series Forecasting plays a crucial role in various fields such as industrial equipment maintenance, meteorology, energy consumption, traffic flow and financial investment. However, despite their considerable advantages over traditional statistical approaches, current deep learning-based predictive models often exhibit a significant deviation between the

Darshana Wickramaratne, Mackenzie Siford, Md Shafiqul Islam Mollik, John L. Lyons

We use photo-electron paramagnetic resonance (EPR) measurements and first-principles calculations to identify and explain the properties of carbon in AlN. We present clear evidence for carbon substitution on the nitrogen site (C$_{\rm N}$). We also clarify the origin of a widely observed EPR spectra in AlN that, although often attributed to a deep donor defe

Kamrul Hasan Rahi

To solve real-world expensive constrained multi-objective optimization problems (ECMOPs), surrogate/approximation models are commonly incorporated in evolutionary algorithms to pre-select promising candidate solutions for evaluation. However, the performance of existing approaches are highly dependent on the relative position of unconstrained and constrained

Ling Wang

In this paper, we investigate the interior H\"older regularity of solutions to the linearized Monge-Amp\`ere equation. In particular, we focus on the cases with singular right-hand side, which arise from the study of the semigeostrophic equation and singular Abreu equations. In the two-dimensional case, we give a new proof of the Caffarelli-Guti\'errez H\"ol

Markus K. Brunnermeier, Sergio Correia, Stephan Luck, Emil Verner

This paper studies how a large increase in the price level is transmitted to the real economy through firm balance sheets. Using newly digitized macro- and micro-level data from the German inflation of 1919-1923, we show that inflation led to a large reduction in real debt burdens and bankruptcies. Firms with higher nominal liabilities at the onset of inflat

Carolyn Talcott

Messaging protocols for resource limited systems such as distributed IoT systems are often vulnerable to attacks due to security choices made to conserve resources such as time, memory, or bandwidth. For example, use of secure layers such as DTLS are resource expensive and can sometimes cause service disruption. Protocol dialects are intended as a light weig

Hideki Yanaoka, Wataru Sakamoto

This study performed a numerical analysis of the deformation and breakup of a liquid ligament with various disturbances on the interface in shear flow. The shear flow generates a three-dimensional flow and vortices around the liquid ligament. These vortices promote the movement of the liquid inside the liquid ligament. When the velocity difference of shear f

Hojin Chu, Suh-Ryung Kim

In this paper, we introduce the notion of two-way $(t,\lambda)$-liking digraphs as a way to extend the results for generalized friendship graphs. A two-way $(t,\lambda)$-liking digraph is a digraph in which every $t$ vertices have exactly $\lambda$ common out-neighbors and $\lambda$ common in-neighbors. We first show that if $\lambda \ge 2$, then a two-way $

Co Van Dinh, Son T. Luu

The problem of detecting spam reviews (opinions) has received significant attention in recent years, especially with the rapid development of e-commerce. Spam reviews are often classified based on comment content, but in some cases, it is insufficient for models to accurately determine the review label. In this work, we introduce the ViSpamReviews v2 dataset

Hajung Kim, Chanhwi Kim, Hoonick Lee, Kyochul Jang

Transforming natural language questions into SQL queries is crucial for precise data retrieval from electronic health record (EHR) databases. A significant challenge in this process is detecting and rejecting unanswerable questions that request information beyond the database's scope or exceed the system's capabilities. In this paper, we introduce a novel te

Ian Flynn, Eric Ramos, Benjamin Young

Some of the most classically relevant Hyperplane arrangements are the Braid Arrangements $B_n$ and their associated compliment spaces $\mathcal{F}_n$. In their recent work, Tsilevich, Vershik, and Yuzvinsky construct what they refer to as the intrinsic hyperplane arrangement within any irreducible representation of the symmetric group that generalize the cla

Muhammad Bilal Shaikh, Syed Mohammed Shamsul Islam, Douglas Chai, Naveed Akhtar

Due to its widespread applications, human action recognition is one of the most widely studied research problems in Computer Vision. Recent studies have shown that addressing it using multimodal data leads to superior performance as compared to relying on a single data modality. During the adoption of deep learning for visual modelling in the last decade, ac

Cangqing Wang, Mingxiu Sui, Dan Sun, Zecheng Zhang

This research delves deeply into Meta Reinforcement Learning (Meta RL) through a exploration focusing on defining generalization limits and ensuring convergence. By employing a approach this article introduces an innovative theoretical framework to meticulously assess the effectiveness and performance of Meta RL algorithms. We present an explanation of gener

Yanrong Li, Tengxiang Zhang, Xin Zeng, Yuntao Wang

Recent advancements in augmented reality (AR) have enabled the use of various sensors on smart glasses for applications like facial reconstruction, which is vital to improve AR experiences for virtual social activities. However, the size and power constraints of smart glasses demand a miniature and low-power sensing solution. AUGlasses achieves unobtrusive l

Ryoya Yamasaki, Toshiyuki Tanaka

Threshold methods are popular for ordinal regression problems, which are classification problems for data with a natural ordinal relation. They learn a one-dimensional transformation (1DT) of observations of the explanatory variable, and then assign label predictions to the observations by thresholding their 1DT values. In this paper, we study the influence

Su-Jen Kan

In the tangent bundle of $(M,g)$, it is well-known that the Monge-Amp\`ere equation $(\partial\bar\partial \sqrt\rho)^n=0$ has the asymptotic expansion $ \rho(x+iy)=\sum_{ij} g_{ij} (x) y_{i} y_{j} + O(y^4)$ near $M$. Those 4th order terms are made explicit in this article: $$\rho(x+iy)=\sum_{i}y_{i}^2-\frac 13\sum_{pqij} R_{i p j q}(0)x_p x_q y_{i}y_{j}+O(5

Elise de Doncker, Tadashi Ishikawa, Kiyoshi Kato, Fukuko Yuasa

Four 3-loop two-point functions are studied analytically and numerically using a simplified sector decomposition method. The coefficients of the ultraviolet divergent part are determined analytically, and those of the finite part are computed numerically. The energy dependence of the integrals is shown explicitly, and a discussion of its behavior is presente

David Pogorzelski, Peter Arlinghaus, Wenyan Zhang

In this paper, we introduce a novel method designed to enhance label efficiency in satellite imagery analysis by integrating semi-supervised learning (SSL) with active learning strategies. Our approach utilizes contrastive learning together with uncertainty estimations via Monte Carlo Dropout (MC Dropout), with a particular focus on Sentinel-2 imagery analyz

Chunyi Zhang, Junfeng Wang, Qing-Hua Tan, Yu Gao

Based on the newly acquired dense gas observations from the JCMT MALATANG survey and X-ray data from Chandra, we explore the correlation between hot gas and HCN $J=4 \rightarrow 3$, HCO$^+\ J=4 \rightarrow 3$ emission for the first time at sub-kiloparsec scale of five nearby star-forming galaxies, namely M82, M83, IC 342, NGC 253, and NGC 6946. We find that

J. H. Guo

The hydrodynamic escape driven by external or internal energy sources sculpts the population of low mass close-in planets. However, distinguishing between the driving mechanisms responsible for the hydrodynamic escape of hydrogen-rich atmospheres is a complex task due to the involvement of many physical factors. My simulations show that the hydrodynamic esca

Yu-Bin Liu, Wen-Yi Zhang, Tian-Cheng Yi, Liangsheng Li

In this study, we explore the quantum critical phenomena in generalized Aubry-Andr\'{e} models, with a particular focus on the scaling behavior at various filling states. Our approach involves using quantum fidelity susceptibility to precisely identify the mobility edges in these systems. Through a finite-size scaling analysis of the fidelity susceptibility,

Wen-Yi Zhang, Qing-Min Hu, Jie Ren, Liangsheng Li

We investigate topological gauge-theory terms and quantum criticality in a spin-1 Kitaev chain with general single-ion anisotropies (SIAs). The ground-state phase diagram, including the Kitaev spin liquid (KSL) and gapless dimer phases, is determined by the infinite time evolving block decimation (iTEBD) method. A quantum phase transition between the KSL and

J. M. Zúñiga, C. A. Caretta, H. Andernach

We applied a Density-Based Clustering algorithm on samples of galaxies and galaxy systems belonging to 53 rich superclusters from the \textit{Main SuperCluster Catalogue} (MSCC) to identify the presence of ``central regions'', or \emph{cores}, in these large-scale structures. \emph{Cores} are defined here as large gravitationally bound galaxy structures, com

Bo Gao, Shao-Peng Tang, Hai-Tian Wang, Jingzhi Yan

In this work, we study the implications of GW230529 on gravity theories and the charge of black holes. The GW230529, which was initially released in O4a, is most likely neutron star-black hole (NSBH) mergers. We reanalyze the data from the GW230529 event to obtain bounds on the Einstein-dilation-Gauss-Bonnet (EdGB) gravity parameter $\sqrt{\alpha_{\rm EdGB}}

Mengkun Chen, Yen-Tung Liu, Fadeel Sher Khan, Matthew C. Fox

Virtual staining streamlines traditional staining procedures by digitally generating stained images from unstained or differently stained images. While conventional staining methods involve time-consuming chemical processes, virtual staining offers an efficient and low infrastructure alternative. Leveraging microscopy-based techniques, such as confocal micro

Tobias Micklitz, Alexander Altland

Light scattering in random media is usually considered within the framework of the three-dimensional Anderson universality class, with modifications for the vector nature of electromagnetic waves. We propose that the linear dispersiveness of light introduces topological aspects into the picture. The dynamics of electromagnetic waves follow the same different

Fredrik Brange, Neill Lambert, Franco Nori, Christian Flindt

The Dicke model describes an ensemble of two-level atoms that are coupled to a confined light mode of an optical cavity. Above a critical coupling, the cavity becomes macroscopically occupied, and the system enters the superradiant phase. This phase transition can be observed by detecting the photons that are emitted from the cavity; however, it only becomes

Ya-jin Zhou

The coherent photons induced by relativistic heavy ions are highly linearly polarized, in close analogy to the linear polarization of gluons in a large nucleus. We proposed to measure the photon polarization through azimuthal asymmetries in dilepton production in ultra-peripheral collisions. Our prediction for the asymmetries were soon confirmed by the STAR

Weiting Tan, Jingyu Zhang, Lingfeng Shen, Daniel Khashabi

Non-autoregressive Transformers (NATs) are recently applied in direct speech-to-speech translation systems, which convert speech across different languages without intermediate text data. Although NATs generate high-quality outputs and offer faster inference than autoregressive models, they tend to produce incoherent and repetitive results due to complex dat

Abel C. H. Chen

With the maturation of quantum computing technology, many cryptographic methods are gradually facing threats from quantum computing. Although the Grover algorithm can accelerate search speeds, current research indicates that the Advanced Encryption Standard (AES) method can still enhance security by increasing the length of the secret key. However, the AES m

Tae-Won Kim, Byung-Soo Choi

By comparing constructions of block encoding given by [1-4], we propose a way to extract dequantizability from advancements in dequantization techniques that have been led by Tang, as in [5]. Then we apply this notion to the sparse-access input model that is known to be BQP-complete in general, thereby conceived to be un-dequantizable. Our goal is to break d

Xi Chen, Mattia Samory, Scott Hale, David Jurgens

Understanding the writing frame of news articles is vital for addressing social issues, and thus has attracted notable attention in the fields of communication studies. Yet, assessing such news article frames remains a challenge due to the absence of a concrete and unified standard dataset that considers the comprehensive nuances within news content. To addr

Nisarg Patel, Dennis Shasha, Thomas Wies

We present and verify template algorithms for lock-free concurrent search structures that cover a broad range of existing implementations based on lists and skiplists. Our linearizability proofs are fully mechanized in the concurrent separation logic Iris. The proofs are modular and cover the broader design space of the underlying algorithms by parameterizin

Dino Osmanovic, Elisa Franco

Understanding how to produce forces using biomolecular building blocks is essential for the development of adaptive synthetic cells and living materials. Here we ask whether a dynamic polymer system can generate deformation forces in soft compartments by pure self-assembly, motivated by the fact that biological polymer networks like the cytoskeleton can exer

Alexander Katsevich

We consider a wide class of generalized Radon transforms $\mathcal R$, which act in $\mathbb{R}^n$ for any $n\ge 2$ and integrate over submanifolds of any codimension $N$, $1\le N\le n-1$. Also, we allow for a fairly general reconstruction operator $\mathcal A$. The main requirement is that $\mathcal A$ be a Fourier integral operator with a phase function, w

Messi H. J. Lee, Jacob M. Montgomery, Calvin K. Lai

Vision Language Models (VLMs), exemplified by GPT-4V, adeptly integrate text and vision modalities. This integration enhances Large Language Models' ability to mimic human perception, allowing them to process image inputs. Despite VLMs' advanced capabilities, however, there is a concern that VLMs inherit biases of both modalities in ways that make biases mor

Haosen Ge, Hamsa Bastani, Osbert Bastani

Conformal prediction has emerged as an effective strategy for uncertainty quantification by modifying a model to output sets of labels instead of a single label. These prediction sets come with the guarantee that they contain the true label with high probability. However, conformal prediction typically requires a large calibration dataset of i.i.d. examples.

Mohammed Talha Alam, Raza Imam, Mohsen Guizani, Fakhri Karray

The intersection of Astronomy and AI encounters significant challenges related to issues such as noisy backgrounds, lower resolution (LR), and the intricate process of filtering and archiving images from advanced telescopes like the James Webb. Given the dispersion of raw images in feature space, we have proposed a \textit{two-stage augmentation framework} e

Shaolin Ji, Chenyao Yu, Linlin Zhu

This paper investigates the nonparametric estimation of the functional coefficients of the FBSDEs with random terminal time, including the local constant and local linear estimators. We provide complete two-dimensional asymptotics in both the time span and the sampling interval, allowing for the precise characterization of their distribution. Moreover, the e

Z. M. McIntyre, W. A. Coish

We present measurement schemes that do not rely on photon-number resolving detectors, but that are nevertheless optimal for estimating a differential phase shift in interferometry with either an entangled coherent state or a qubit-which-path state (where the path taken by a coherent-state wavepacket is entangled with the state of a qubit). The homodyning sch

Osman Tursun, Sinan Kalkan, Simon Denman, Sridha Sridharan

Heatmaps have been instrumental in helping understand deep network decisions, and are a common approach for Explainable AI (XAI). While significant progress has been made in enhancing the informativeness and accessibility of heatmaps, heatmap analysis is typically very subjective and limited to domain experts. As such, developing automatic, scalable, and num

Maxwell Gold, Jianlong Lin, Eric Chitambar, Elizabeth A. Goldschmidt

Quantum emitter-based schemes for the generation of photonic graph states offer a promising, resource efficient methodology for realizing distributed quantum computation and communication protocols on near-term hardware. We present a heralded scheme for making photonic graph states that is compatible with the typically poor photon collection from state-of-th

Harry Gingold, Jocelyn Quaintance

This article produces wave equations and constructs traveling wave solutions that are intimately related to Newton's equations of celestial mechanics. The traveling wave solutions are expressed in ``closed form'' in terms of elementary functions. They are specialized to the 2-body and the relative 2-body problem. The traveling wave solutions disclose the sha

Tingtao Zhou, Dorian Bruch, Zhen-Gang Wang

Image charge effect is a fundamental problem in electrostatics. However, a proper treatment at the continuum level for many-ion systems, such as electrolyte solutions or ionic liquids, remains an open theoretical question. Here, we demonstrate and systematically compare the image charge effects under metal and dielectric boundary conditions (BCs), based on a

S. J. Liu, D. Wu, B. Liu, Y. -K. M. Peng

Compared to the D-T reaction, the neutron-free proton-boron (p-$^{11}$B) fusion has garnered increasing attention in recent years. However, significant Bremsstrahlung losses pose a formidable challenge in p-$^{11}$B plasmas in achieving $Q>1$ in thermal equilibrium. The primary aim of this study is to corroborate Todd H. Rider's seminal work in the 1997 Phys

Sam Young

An accurate calculation of their abundance is crucial for numerous aspects of cosmology related to primordial black holes (PBHs). For example, placing constraints on the primordial power spectrum from constraints on the abundance of PBHs (or vice-versa), calculating the mass function observable today, or predicting the merger rate of (primordial) black holes

Alexey Glutsyuk

Let $K\subset\mathbb R^n_q$, $T\subset\mathbb R^n_p$ be two bounded strictly convex bodies (open subsets) with $C^6$-smooth boundaries. We consider the product $\overline K\times\overline T\subset\mathbb R^{2n}_{q,p}$ equipped with the standard symplectic form $\omega=\sum_{j=1}^ndq_j\wedge dp_j$. The $(K,T)$-billiard orbits are continuous curves in the boun

Smail Benzaki, Youssef Rami

In this paper, we first prove the existence of relative free models of morphisms (resp. relative commutative models) in the category of $DGA(R)$ (resp. $CDGA(R)$), where $R$ is a principal ideal domain containing $\frac{1}{2}$. Next, we restrict to the category of $(r,\rho(R))$-H-mild algebras and we introduce, following Carrasquel's characterization, $secat

Mahdi Jamebozorg, Mohsen Hami, Sajjad Deh Deh Jani

Optimal management of traffic light timing is one of the most effective factors in reducing urban traffic. In most old systems, fixed timing was used along with human factors to control traffic, which is not very efficient in terms of time and cost. Nowadays, methods in the field of traffic management are based on the use of artificial intelligence. In this

Yijie Jin, Shu Liu, Hao Wu, Xiaojing Ye

We develop a fast and scalable numerical approach to solve Wasserstein gradient flows (WGFs), particularly suitable for high-dimensional cases. Our approach is to use general reduced-order models, like deep neural networks, to parameterize the push-forward maps such that they can push a simple reference density to the one solving the given WGF. The new dynam

Yuki Ishida, Atsuki Kuramoto, Dingchuan Zheng

In this paper, we study an asymptotic distribution of sets of primes satisfying certain "linking conditions" in arithmetic topology, namely, conditions given by the Legendre and Rédei symbols among sets of primes. As our Main Theorem, we prove an asymptotic density formula for Borromean primes among all primes. For the proof, we use the effective Che

Arka Ghosh, Sławomir Lasota

We study existence and computability of finite bases for ideals of polynomials over infinitely many variables. In our setting, variables come from a countable logical structure A, and embeddings from A to A act on polynomials by renaming variables. First, we give a sufficient and necessary condition for A to guarantee the following generalisation of Hilbert&

Elias Bernreuther, Nicoline Hemme, Felix Kahlhoefer, Suchita Kulkarni

Stable dark matter particles may arise as pseudo-Goldstone bosons from the confinement of dark quarks interacting via a non-Abelian gauge force. Their relic abundance is determined not by annihilations into visible particles but by dark pion number-changing processes within the dark sector, such as $3 π_D \to 2 π_D$. However, if the dark vector mesons $ρ_D$

Xinyuanmeng Yao, Xiao Ma

Successive cancellation list (SCL) decoding enables polar codes and their generalizations to deliver satisfactory performance in finite-length scenarios but it comes with high latency and complexity. To reduce latency, a partitioned SCL (PSCL) decoding algorithm, implemented over a PSCL decoding tree, can be utilized. In this work, we aim to lower down the c

Sepehr Sharifi, Andrea Stocco, Lionel C. Briand

In learning-enabled autonomous systems, safety monitoring of learned components is crucial to ensure their outputs do not lead to system safety violations, given the operational context of the system. However, developing a safety monitor for practical deployment in real-world applications is challenging. This is due to limited access to internal workings and

Vedansh Arya, Agnid Banerjee, Nicola Garofalo

We establish a new sharp estimate of the order of vanishing of solutions to parabolic equations with variable coefficients. For real-analytic leading coefficients, we prove a localised estimate of the nodal set, at a given time-level, that generalises the celebrated one of Donnelly and Fefferman. We also establish Landis type results for global solutions.

Jorge Alberto Robles Hernández, J. Rogelio Pérez-Buendía

This article, written in Spanish, provides a comprehensive review of the Fargues-Fontaine curve, a cornerstone in $p$-adic Hodge theory, and its pivotal role in classifying $p$-adic Galois representations. We synthesize key developments surrounding this curve, emphasizing its connection between advanced concepts in arithmetic geometry and the practical theor

Issam Khayr, Sajna Hameed, Jakov Budić, Xing He

Dislocation engineering has the potential to open new avenues toward the exploration and modification of the properties of quantum materials. Strontium titanate (SrTiO3, STO) and potassium tantalate (KTaO3, KTO) are incipient ferroelectrics that show metallization and superconductivity at extremely low charge carrier concentrations, and have been the subject

Nathaniel Kingsbury-Neuschotz

Let $R$ be a finite ring (with unit, not necessarily commutative) and define the paraboloid $P = \{(x_1, \dots, x_d)\in R^d|x_d = x_1^2 + \dots + x_{d-1}^2\}.$ Suppose that for a sequence of finite rings of size tending to infinity, the Fourier transform of $P$ satisfies a square-root law of the form $|\hat{P}(\chi)|\leq C|R|^{-d}|P|^\frac{1}{2}$ for some fi

Jaliya L. Wijayaraja, Janaka L. Wijekoon, Malitha Wijesundara, L. J. Mendis Wickramasinghe

The long-distance detection of the presence of elephants is pivotal to addressing the human-elephant conflict. IoT-based solutions utilizing seismic signals originating from the movement of elephants are a novel approach to solving this problem. This study introduces an instrumentation system comprising a specially designed geophone-sensor interface for non-

Yinan Zhao, Xavier Dumusque, Michael Cretignier, Andrew Collier Cameron

Many novel methods have been proposed to mitigate stellar activity for exoplanet detection as the presence of stellar activity in radial velocity (RV) measurements is the current major limitation. Unlike traditional methods that model stellar activity in the RV domain, more methods are moving in the direction of disentangling stellar activity at the spectral

Geoffrey W. Marcy, Nathaniel K. Tellis

We searched the Milky Way Plane along a 6-deg swath for pulses of monochromatic light as faint as 15th mag (V band) using a wide-field telescope equipped with a prism. Pulses with duration less than 1 second that occur more often than once every 10 minutes would be detected, and pulses arriving less frequently would be detected with proportionally lower prob

Shih-Yu Chang

Mond and Pecaric introduced a method to simplify the determination of complementary inequalities for Jensen's inequality by converting it into a single-variable maximization or minimization problem of continuous functions. This principle has significantly enriched the field of operator inequalities. Our contribution lies in extending the Mond-Pecaric method

Vanya Cohen, Jason Xinyu Liu, Raymond Mooney, Stefanie Tellex

With large language models, robots can understand language more flexibly and more capable than ever before. This survey reviews and situates recent literature into a spectrum with two poles: 1) mapping between language and some manually defined formal representation of meaning, and 2) mapping between language and high-dimensional vector spaces that translate

Achim Basermann, Michael Epping, Benedikt Fauseweh, Michael Felderer

The rapid advancements in quantum computing necessitate a scientific and rigorous approach to the construction of a corresponding software ecosystem, a topic underexplored and primed for systematic investigation. This chapter takes an important step in this direction: It presents scientific considerations essential for building a quantum software ecosystem t

Shervin Salehi Rad, Micheal Muhlbaier, Oleg Fishman, Javad Chevinly

The design and development of power electronics converters pose a multitude of challenges. The evaluation of power electronics converters, particularly when operating at high power levels, presents a significant task, offering designers a deeper understanding of the functionality. Several methodologies have been devised to conduct hardware-in-the-loop (HIL)

Guy Davidson, Graham Todd, Julian Togelius, Todd M. Gureckis

People are remarkably capable of generating their own goals, beginning with child's play and continuing into adulthood. Despite considerable empirical and computational work on goals and goal-oriented behavior, models are still far from capturing the richness of everyday human goals. Here, we bridge this gap by collecting a dataset of human-generated playful

Michael Gechter, Keisuke Hirano, Jean Lee, Mahreen Mahmud

Policy decisions often depend on evidence generated elsewhere. We take a Bayesian decision-theoretic approach to choosing where to experiment to optimize external validity. We frame external validity through a policy lens, developing a prior specification for the joint distribution of site-level treatment effects using a microeconometric structural model and

Tugdual LeBohec

We investigate the effects of the repeated application of Lorentz-boosts to the four momentum of a photon in the transverse direction and observe that this can take us to a reference frame in which the direction of the photon's momentum is apparently reversed. We further extend this to an infinite succession of infinitesimal transverse Lorentz-boosts and sho

Rongfeng Xie, Alex Kamenev

We discuss adiabatic spectra and dynamics of the quantum, i.e. transverse field, Hopfield model with dilute memories (the number of stored patterns $p < log_2 N$, where $N$ is the number of qubits). At some critical transverse field the model undergoes the quantum phase transition from the ordered to the paramagnetic state. The corresponding critical exponen

Domenic P. J. Germano, Alexander E. Zarebski, Sophie Hautphenne, Robert Moss

Multi-scale systems often exhibit a combination of stochastic and deterministic dynamics. In compartmental models, low occupancy compartments tend to exhibit stochastic dynamics while high occupancy compartments tend to follow deterministic dynamics. Representing both dynamics with existing methods is challenging. Failing to account for stochasticity in smal

Peng Liu, Nian Wang, Cong Xu, Ming Zhao

Recommender System (RS) provides personalized recommendation service based on user interest. However, lots of users' interests are sparse due to lacking consumption behaviors, making it challenging to provide accurate recommendations for them, which is widespread in large-scale RSs. In particular, efficiently solving this problem in the ranking stage of RS i

Noor Nakhaei, Chrysostomos Marasinou, Akinyinka Omigbodun, Nina Capiro

Accurate characterization of suspicious microcalcifications is critical to determine whether these calcifications are associated with invasive disease. Our overarching objective is to enable the joint characterization of microcalcifications and surrounding breast tissue using mammography images and digital histopathology images. Towards this goal, we investi

Mitchell G. Irmer, Emily E. Brodsky, Abram H. Clark

We use numerical simulations to demonstrate a local rheology for sheared, vibrated granular flows. We consider a granular assembly that is subjected to simple shear and harmonic vibration at the boundary. This configuration allows us to isolate the effects of vibration, as parameterized by granular temperature. We find that friction is reduced due to local v

Jayroop Ramesh, Nicola K Dinsdale, the INTERGROWTH-21st Consortium, Pak-Hei Yeung

Accurately localizing two-dimensional (2D) ultrasound (US) fetal brain images in the 3D brain, using minimal computational resources, is an important task for automated US analysis of fetal growth and development. We propose an uncertainty-aware deep learning model for automated 3D plane localization in 2D fetal brain images. Specifically, a multi-head netwo

Khemraj Shukla, Jasmine Ratchford, Luis Bravo, Vivek Oommen

Neural networks are universal approximators that traditionally have been used to learn a map between function inputs and outputs. However, recent research has demonstrated that deep neural networks can be used to approximate operators, learning function-to-function mappings. Creating surrogate models to supplement computationally expensive hypersonic aerothe

Sirou Chen, Sakiko Yahata, Shuichiro Shimizu, Zhengdong Yang

Emotion plays a crucial role in human conversation. This paper underscores the significance of considering emotion in speech translation. We present the MELD-ST dataset for the emotion-aware speech translation task, comprising English-to-Japanese and English-to-German language pairs. Each language pair includes about 10,000 utterances annotated with emotion

B. Clavier, D. Zarzoso, D. del-Castillo-Negrete, E. Frenod

Generative artificial intelligence methods are employed for the first time to construct a surrogate model for plasma turbulence that enables long time transport simulations. The proposed GAIT (Generative Artificial Intelligence Turbulence) model is based on the coupling of a convolutional variational auto-encoder, that encodes precomputed turbulence data int

Sam Whitman McGrath, Jacob Russin

The multiple realizability thesis holds that psychological states may be implemented in a diversity of physical systems. The deep learning revolution seems to be bringing this possibility to life, offering the most plausible examples of man-made realizations of sophisticated cognitive functions to date. This paper explores the implications of deep learning m

Dean Crnkovic, Maarten De Boeck, Francesco Pavese, Andrea Svob

Divisible design graphs were introduced in 2011 by Haemers, Kharaghani and Meulenberg. In this paper, we introduce the notion of $q$-analogs of divisible design graphs and show that all $q$-analogs of divisible design graphs come from spreads, and are actually $q$-analogs of strongly regular graphs. Deza graphs were introduced by Erickson, Fernando, Haemers

Obadage Rochana Rumalshan, Pramuka Weerasinghe, Mohamed Shaheer, Prabhath Gunathilake

The extreme popularity over the years for railway transportation urges the necessity to maintain efficient railway management systems around the globe. Even though, at present, there exist a large collection of Computer Aided Designed Railway Technical Maps (RTMs) but available only in the portable document format (PDF). Using Deep Learning and Optical Chara

Chi Ian Jess Ip, Qiang Gao, Khanhy Du Nguyen, Chenhui Yan

Ultrathin topological insulator membranes are building blocks of exotic quantum matter. However, traditional epitaxy of these materials does not facilitate stacking in arbitrary orders, while mechanical exfoliation from bulk crystals is also challenging due to the non-negligible interlayer coupling therein. Here we liberate millimeter-scale films of topologi

Xinhao Yang, Zhen Han, Xiaodong Lu, Yuan Zhang

With rapid urbanisation and the accompanying increase in traffic density, traffic noise has become a major concern in urban planning. However, traditional grid noise mapping methods have limitations in terms of time consumption, software costs, and a lack of parameter integration interfaces. These limitations hinder their ability to meet the need for iterati

Hadi Pouransari, Chun-Liang Li, Jen-Hao Rick Chang, Pavan Kumar Anasosalu Vasu

Large language models (LLMs) are commonly trained on datasets consisting of fixed-length token sequences. These datasets are created by randomly concatenating documents of various lengths and then chunking them into sequences of a predetermined target length (concat-and-chunk). Recent attention implementations mask cross-document attention, reducing the effe

Aishabibi Dukenbayeva

In this note, we show a global existence and blow-up of the positive solutions to the initial-boundary value problem of the nonlinear porous medium equation related to Baouendi-Grushin operator. Our approach is based on the concavity argument and the Poincar\'e inequality for Baouendi-Grushin vector fields from [35], inspired by the recent works [28] and [29

Radu Tanase, René Algesheimer, Manuel S. Mariani

Addressing global challenges often involves stimulating the large-scale adoption of new products or behaviors. Research traditions that focus on individual decision making suggest that achieving this objective requires identifying the drivers of individual discrete adoption choices. On the other hand, computational approaches rooted in complexity science foc

Sunil K. Chebolu, Ján Mináč, Cihan Okay, Andrew Schultz

The famous Bloch--Kato conjecture implies that for a field $F$ containing a primitive $p$th root of unity, the cohomology ring of the absolute Galois group $G_F$ of $F$ with $\mathbb{F}_p$ coefficients is generated by degree one elements. We investigate other groups with this property and characterize all such groups that are finite. Restricting to the case

Aishabibi Dukenbayeva

In this note, we study a global existence and blow-up of the positive solutions to the initial-boundary value problem of the nonlinear pseudo-parabolic equation for the Baouendi-Grushin operator. The approach is based on the concavity argument and the Poincar\'e inequality related to the Baouendi-Grushin operator from [24], inspired by the recent work [21].

Tyler McMaken

Black holes modeled by the Kerr metric are not semiclassically self-consistent at or below the inner horizon. The renormalized stress-energy tensor (RSET) of a scalar quantum field in the Unruh state has been found to diverge at the Kerr inner horizon [arXiv:2203.08502], causing the geometry to backreact in a non-trivial way. In an effort to understand this

Matthias Chung, Emma Hart, Julianne Chung, Bas Peters

We consider the solution of nonlinear inverse problems where the forward problem is a discretization of a partial differential equation. Such problems are notoriously difficult to solve in practice and require minimizing a combination of a data-fit term and a regularization term. The main computational bottleneck of typical algorithms is the direct estimatio

Ayesha Siddika Nipu, K M Sajjadul Islam, Praveen Madiraju

Artificial Intelligence (AI) chatbots leveraging Large Language Models (LLMs) are gaining traction in healthcare for their potential to automate patient interactions and aid clinical decision-making. This study examines the reliability of AI chatbots, specifically GPT 4.0, Claude 3 Opus, and Gemini Ultra 1.0, in predicting diseases from patient complaints in

Antonio Quintero-Rincón, Jorge Prendes, Valeria Muro, Carlos D'Giano

Pattern classification in electroencephalography (EEG) signals is an important problem in biomedical engineering since it enables the detection of brain activity, particularly the early detection of epileptic seizures. In this paper, we propose a k-nearest neighbors classification for epileptic EEG signals based on a t-location-scale statistical representati

Maciej Kilian, Varun Jampani, Luke Zettlemoyer

Nearly every recent image synthesis approach, including diffusion, masked-token prediction, and next-token prediction, uses a Transformer network architecture. Despite this common backbone, there has been no direct, compute controlled comparison of how these approaches affect performance and efficiency. We analyze the scalability of each approach through the

Peter Bajcsy, Maxime Bros

This work addresses the problem of planting and defending cryptographic-based backdoors in artificial intelligence (AI) models. The motivation comes from our lack of understanding and the implications of using cryptographic techniques for planting undetectable backdoors under theoretical assumptions in the large AI model systems deployed in practice. Our app

Chenghao Yang, Zi Yang, Nan Hua

Long-context modeling presents a significant challenge for transformer-based large language models (LLMs) due to the quadratic complexity of the self-attention mechanism and issues with length extrapolation caused by pretraining exclusively on short inputs. Existing methods address computational complexity through techniques such as text chunking, the kernel

John A. Schneeloch, Adam A. Aczel, Feng Ye, Despina Louca

In the study of van der Waals-layered magnetic materials, the properties of CrCl$_3$ continue to attract attention. This compound is reported to undergo antiferromagnetic (AFM) ordering below $\sim$14 K, with a ferromagneticlike region proposed to exist between 14 and 17 K. Ideally, the crystal structure is rhombohedral (R) below $\sim$235 K, separated from

Owen Melia, Olivia Tsang, Vasileios Charisopoulos, Yuehaw Khoo

Interpreting scattered acoustic and electromagnetic wave patterns is a computational task that enables remote imaging in a number of important applications, including medical imaging, geophysical exploration, sonar and radar detection, and nondestructive testing of materials. However, accurately and stably recovering an inhomogeneous medium from far-field sc

Kumar Miskin, Yi Cao, Madaline Marland, Jay Rwaka

Self-regulation of free charge carriers in perovskites via Schottky defect formation has been posited as the origin of the well-known defect tolerance of metal halide perovskite materials that are promising candidates for photovoltaic applications, like solar cells. Understanding the mechanisms of self-regulation, here for a representative of more commercial