April 2024 arXiv papers — page 24

Yi Jiang, Sen Lu, Abhronil Sengupta

Spiking Neural Networks (SNNs), recognized as the third generation of neural networks, are known for their bio-plausibility and energy efficiency, especially when implemented on neuromorphic hardware. However, the majority of existing studies on SNNs have concentrated on deterministic neurons with rate coding, a method that incurs substantial computational o

Arun N. Sivakumar, Mateus V. Gasparino, Michael McGuire, Vitor A. H. Higuti

We present a vision-based navigation system for under-canopy agricultural robots using semantic keypoints. Autonomous under-canopy navigation is challenging due to the tight spacing between the crop rows ($\sim 0.75$ m), degradation in RTK-GPS accuracy due to multipath error, and noise in LiDAR measurements from the excessive clutter. Our system, CropFollow+

Jiawang Nie, Linghao Zhang

This paper studies the polynomial optimization problem whose feasible set is a union of several basic closed semialgebraic sets. We propose a unified hierarchy of Moment-SOS relaxations to solve it globally. Under some assumptions, we prove the asymptotic or finite convergence of the unified hierarchy. Special properties for the univariate case are discussed

Adis Delanovic, Carmen Chiu, John F. Kolen, Marvin Gülhan

Airlift operations require the timely distribution of various cargo, much of which is time sensitive and valuable. These operations, however, have to contend with sudden disruptions from weather and malfunctions, requiring immediate rescheduling. The Airlift Challenge competition seeks possible solutions via a simulator that provides a simplified abstraction

J. Borowicz, P. Pietrukowicz, J. Skowron, I. Soszyński

In this work, we search the OGLE-IV outer Galactic bulge fields for short-period variable objects. The investigation focuses on unexplored timescales roughly below one hour in an area containing about 700 million stellar sources down to approximately I=20 mag. We concentrate mainly on Blue Large-Amplitude Pulsators (BLAPs), which represent a recently discove

Victor S. Portella, Nick Harvey

We prove lower bounds on the number of samples needed to privately estimate the covariance matrix of a Gaussian distribution. Our bounds match existing upper bounds in the widest known setting of parameters. Our analysis relies on the Stein-Haff identity, an extension of the classical Stein's identity used in previous fingerprinting lemma arguments.

Weihong Qi

This study reevaluates the traditional understanding of the "political resource curse" by examining the unique impact of energy transition metals, specifically cobalt, on local-level conflicts in Africa. Contrary to previous studies that primarily focus on high-value minerals and their political outcomes resulted from substantial economic revenues, this stud

Thai Thanh Nguyen, Vinh Anh Pham

We show the asymptotic relationship between the limit of the normalized length function of a multi-$p-$family of ideals and that of its shifted family under linear growth conditions in a local domain of characteristic $p$. Examples of multi-$p-$families of ideals including products of Frobenius powers of different ideals. We apply our results to obtain a gen

Jared Coleman, Danny Krizanc, Evangelos Kranakis, Oscar Morales-Ponce

We introduce and study a new cooperative delivery problem inspired by drone-assisted package delivery. We consider a scenario where a drone, en route to deliver a package to a destination (a point on the plane), unexpectedly loses communication with its central command station. The command station cannot know whether the drone's system has wholly malfunction

E. Santamaría, J. A. Toalá, T. Liimets, M. A. Guerrero

We present an analysis of high-dispersion spectroscopic observations of the symbiotic system R Aquarii (R Aqr) obtained with the Manchester Echelle Spectrograph (MES) at the 2.1 m telescope of the San Pedro M\'artir Observatory (Mexico). An interpretation of these data is presented by means of the shape software to disclose the morpho-kinematics of the nebul

Yue Kang, Cho-Jui Hsieh, Thomas C. M. Lee

In stochastic low-rank matrix bandit, the expected reward of an arm is equal to the inner product between its feature matrix and some unknown $d_1$ by $d_2$ low-rank parameter matrix $\Theta^*$ with rank $r \ll d_1\wedge d_2$. While all prior studies assume the payoffs are mixed with sub-Gaussian noises, in this work we loosen this strict assumption and cons

Zohreh Ravanpak

In this paper, we introduce the concept of (weak) NL bialgebras. These structures consist of a Lie bialgebra $(\g,[\cdot,\cdot],\delta)$ equipped with a Nijenhuis structure on the Lie algebra $(\g,[\cdot,\cdot])$, satisfying specific compatibility conditions. This construction is analogous to Poisson-Nijenhuis structures studied in the context of integrable

Daniel V. Cotton, Jeremy Bailey, Jean Perkins, Derek L. Buzasi

We write to report the discovery that Deneb is a large amplitude polarization variable. Over a ~400 d time span from August 2022 Deneb's polarization was typically around 3900 parts-per-million (ppm) in the SDSS g'-band. Yet, it varied by several hundred ppm in an irregular way on a timescale of weeks. The largest polarization change, amounting to 2500 ppm,

Elisa Continelli, Cristina Pignotti

In this paper, we study well-posedness and exponential stability for semilinear second order evolution equations with memory and time-varying delay feedback. The time delay function is assumed to be continuous and bounded. Under a suitable assumption on the delay feedback, we are able to prove that solutions corresponding to small initial data are globally d

Stephan Schmidt, Daniel N. Wilke, Konstantinos C. Gryllias

In vibration-based condition monitoring, optimal filter design improves fault detection by enhancing weak fault signatures within vibration signals. This process involves optimising a derived objective function from a defined objective. The objectives are often based on proxy health indicators to determine the filter's parameters. However, these indicators c

Luis Mendo

Two sequential estimators are proposed for the odds p/(1-p) and log odds log(p/(1-p)) respectively, using independent Bernoulli random variables with parameter p as inputs. The estimators are unbiased, and guarantee that the variance of the estimation error divided by the true value of the odds, or the variance of the estimation error of the log odds, are le

Areej Alsaafin, Peyman Nejat, Abubakr Shafique, Jibran Khan

Digital pathology and the integration of artificial intelligence (AI) models have revolutionized histopathology, opening new opportunities. With the increasing availability of Whole Slide Images (WSIs), there's a growing demand for efficient retrieval, processing, and analysis of relevant images from vast biomedical archives. However, processing WSIs present

Refat Ismail, Ashish Kakkar, Anatoly Dymarsky

Quantum error-correcting codes (QECCs) is at the heart of fault-tolerant quantum computing. As the size of quantum platforms is expected to grow, one of the open questions is to design new optimal codes of ever-increasing size. A related challenge is to ``certify'' the quality of a given code by evaluating its minimum distance, a quantity characterizing code

Mayesha Sharmim Tisha, Md. Kamrujjaman, Muhammad Mohebujjaman, Taufiquar Khan

We propose a time-dependent Advection Reaction Diffusion (ARD) $N$-species competition model to investigate the Stocking and Harvesting (SH) effect on population dynamics. For ongoing analysis, we explore the outcomes of a competition between two competing species in a heterogeneous environment under no-flux boundary conditions, meaning no individual can cro

Saydul Akbar Murad, Nick Rahimi

The conversion of brain activity into text using electroencephalography (EEG) has gained significant traction in recent years. Many researchers are working to develop new models to decode EEG signals into text form. Although this area has shown promising developments, it still faces numerous challenges that necessitate further improvement. It's important to

Julia Gonski, Aseem Gupta, Haoyi Jia, Hyunjoon Kim

Embedded field programmable gate array (eFPGA) technology allows the implementation of reconfigurable logic within the design of an application-specific integrated circuit (ASIC). This approach offers the low power and efficiency of an ASIC along with the ease of FPGA configuration, particularly beneficial for the use case of machine learning in the data pip

Juan Melo

This paper investigates the distribution of public school expenditures across U.S. school districts using a bayesian maximum entropy model. Covering the period 2000-2016, I explore how inter-jurisdictional competition and household choice influence spending patterns within the public education sector, providing a novel empirical treatment of the Tiebout hypo

Francis Ogoke, Peter Myung-Won Pak, Alexander Myers, Guadalupe Quirarte

Insufficient overlap between the melt pools produced during Laser Powder Bed Fusion (L-PBF) can lead to lack-of-fusion defects and deteriorated mechanical and fatigue performance. In-situ monitoring of the melt pool subsurface morphology requires specialized equipment that may not be readily accessible or scalable. Therefore, we introduce a machine learning

Ananya Bhattacharjee, Zichen Gong, Bingcheng Wang, Timothy James Luckcock

Regular practice of gratitude has the potential to enhance psychological wellbeing and foster stronger social connections among young adults. However, there is a lack of research investigating user needs and expectations regarding gratitude-promoting applications. To address this gap, we employed a user-centered design approach to develop a mobile applicatio

Thomas Billington, Ansh Gwash, Aadi Kothari, Lucas Izquierdo

In the rapidly advancing landscape of connected and automated vehicles (CAV), the integration of Vehicle-to-Everything (V2X) communication in traditional fusion systems presents a promising avenue for enhancing vehicle perception. Addressing current limitations with vehicle sensing, this paper proposes a novel Vehicle-to-Vehicle (V2V) enabled track managemen

Wei Ouyang, Jane Ye, Binbin Zhang

In this paper we derive new second-order optimality conditions for a very general set-constrained optimization problem where the underlying set may be nononvex. We consider local optimality in specific directions (i.e., optimal in a directional neighborhood) in pursuit of developing these new optimality conditions. First-order necessary conditions for local

Florian Fischer, Aleksi Ikkala, Markus Klar, Arthur Fleig

Automated biomechanical testing has great potential for the development of VR applications, as initial insights into user behaviour can be gained in silico early in the design process. In particular, it allows prediction of user movements and ergonomic variables, such as fatigue, prior to conducting user studies. However, there is a fundamental disconnect be

Muhammad Adam Dombrowski, Gregory Dresden

We find the area between $\cos^p x$ and $\cos^p nx$ as $n$ heads to infinity, and we establish a connection between these limiting values and the exponential generating function for $\arcsin x/(1-x)$ at sequence number A296726 on the OEIS.

Clint Harris, Jonathan T. Eckhardt, Brent Goldfarb

When subjects who respond to requests for data, such as in surveys or post-treatment follow-up, are unrepresentative of the population of interest, inferences drawn from the data can be misleading. We show that if subjects' accumulated requests and responses over time are recorded and organized as panel data, requests can be used as instruments in standa

Giulia Murgia, Sofia Fatigoni

We implement an algorithm based on the weighted stacking of astronomical images that can combine different observations of the same region of the sky removing the interfering signals. We develop a C++ code that takes as input a set of spectral cubes and computes the local weights of the intensity for each pixel of every channel. The weights are calculated as

Joel Wolfrath, Abhishek Chandra

MinMax sampling is a technique for downsampling a real-valued vector which minimizes the maximum variance over all vector components. This approach is useful for reducing the amount of data that must be sent over a constrained network link (e.g. in the wide-area). MinMax can provide unbiased estimates of the vector elements, along with unbiased estimates of

Ronglong Fang, Yuesheng Xu, Mingsong Yan

We study inexact fixed-point proximity algorithms for solving a class of sparse regularization problems involving the $\ell_0$ norm. Specifically, the $\ell_0$ model has an objective function that is the sum of a convex fidelity term and a Moreau envelope of the $\ell_0$ norm regularization term. Such an $\ell_0$ model is non-convex. Existing exact algorithm

Ahmed M. Abuzuraiq, Philippe Pasquier

In this paper, we map out the landscape of options available to visual artists for creating personal artworks, including crafting, adapting and navigating deep generative models. Following that, we argue for revisiting model crafting, defined as the design and manipulation of generative models for creative goals, and motivate studying and designing for model

Sergio A. Serrano, Jose Martinez-Carranza, L. Enrique Sucar

Reinforcement Learning (RL) provides a framework in which agents can be trained, via trial and error, to solve complex decision-making problems. Learning with little supervision causes RL methods to require large amounts of data, rendering them too expensive for many applications (e.g., robotics). By reusing knowledge from a different task, knowledge transfe

Homa Esfahanizadeh, Vipindev Adat Vasudevan, Benjamin D. Kim, Shruti Siva

Network slicing has emerged as an integral concept in 5G, aiming to partition the physical network infrastructure into isolated slices, customized for specific applications. We theoretically formulate the key performance metrics of an application, in terms of goodput and delivery delay, at a cost of network resources in terms of bandwidth. We explore an un-c

Yi Shen, Hao Liu, Xinxin Liu, Wenjing Zhou

The reduced cost and computational and calibration requirements of monocular cameras make them ideal positioning sensors for mobile robots, albeit at the expense of any meaningful depth measurement. Solutions proposed by some scholars to this localization problem involve fusing pose estimates from convolutional neural networks (CNNs) with pose estimates from

Haohong Lin, Radu Corcodel, Ding Zhao

Furniture assembly remains an unsolved problem in robotic manipulation due to its long task horizon and nongeneralizable operations plan. This paper presents the Tactile Ensemble Skill Transfer (TEST) framework, a pioneering offline reinforcement learning (RL) approach that incorporates tactile feedback in the control loop. TEST's core design is to learn a s

Saud Alghumayjan, Jiajun Han, Ningkun Zheng, Ming Yi

This paper presents an integrated model for bidding energy storage in day-ahead and real-time markets to maximize profits. We show that in integrated two-stage bidding, the real-time bids are independent of day-ahead settlements, while the day-ahead bids should be based on predicted real-time prices. We utilize a transformer-based model for real-time price p

Holger Dette, Lukas Koletzko, Frank Bretz

This paper addresses the problem of deciding whether the dose response relationships between subgroups and the full population in a multi-regional trial are similar to each other. Similarity is measured in terms of the maximal deviation between the dose response curves. We consider a parametric framework and develop two powerful bootstrap tests for the simil

Jan Verschelde, Kylash Viswanathan

A polynomial homotopy is a family of polynomial systems in one parameter, which defines solution paths starting from known solutions and ending at solutions of a system that has to be solved. We consider paths leading to isolated singular solutions, to which the Taylor series converges logarithmically. Whether or not extrapolation algorithms manage to accele

Giles Blaney, Jodee Frias, Fatemeh Tavakoli, Angelo Sassaroli

Significance: Pulsatile blood Oxygen Saturation (SpO2 ) via pulse oximetry is a valuable clinical metric for assessing oxygen delivery. Individual anatomical features, including skin tone, may affect current optical pulse oximetry methods. Aim: Develop an optical pulse oximetry method based on Dual-Ratio (DR) measurements to suppress individual anatomical fe

Dan Olteanu

We overview recent progress on the longstanding problem of incremental view maintenance (IVM), with a focus on the fine-grained complexity and optimality of IVM for classes of conjunctive queries. This theoretical progress guided the development of IVM engines that reported practical benefits in academic papers and industrial settings. When taken in isolatio

Dermot McCarthy, Mohit Tripathi

We examine hypergeometric functions in the finite field, p-adic and classical settings. In each setting, we prove a formula which splits the hypergeometric function into a sum of lower order functions whose arguments differ by roots of unity. We provide multiple applications of these results, including new reduction and summation formulas for finite field hy

Vadym Kliuchnikov, Sebastian Schönnenbeck

We give a simple description of rectangular matrices that can be implemented by a post-selected stabilizer circuit. Given a matrix with entries in dyadic cyclotomic number fields $\mathbb{Q}(\exp(i\frac{2\pi}{2^m}))$, we show that it can be implemented by a post-selected stabilizer circuit if it has entries in $\mathbb{Z}[\exp(i\frac{2\pi}{2^m})]$ when expre

Noah Berthusen, Dhruv Devulapalli, Eddie Schoute, Andrew M. Childs

Geometric locality is an important theoretical and practical factor for quantum low-density parity-check (qLDPC) codes which affects code performance and ease of physical realization. For device architectures restricted to 2D local gates, naively implementing the high-rate codes suitable for low-overhead fault-tolerant quantum computing incurs prohibitive ov

Xinyu Fan, Ding Xu, Jianhua Zhang, Hao Hu

Order and disorder constitute two fundamental and opposite themes in condensed matter physics and materials science. Crystals are considered the epitome of order, characterised by long-range translational order. The discovery of quasicrystals, which exhibit rotational symmetries forbidden in crystals and lack periodicity, led to a paradigm shift in solid-sta

Xingli Fang, Jung-Eun Kim

Membership inference attacks (MIAs) are currently considered one of the main privacy attack strategies, and their defense mechanisms have also been extensively explored. However, there is still a gap between the existing defense approaches and ideal models in performance and deployment costs. In particular, we observed that the privacy vulnerability of the m

Hariharan Arunachalam, Marc Hanheide, Sariah Mghames

Automating the segregation process is a need for every sector experiencing a high volume of materials handling, repetitive and exhaustive operations, in addition to risky exposures. Learning automated pick-and-place operations can be efficiently done by introducing collaborative autonomous systems (e.g. manipulators) in the workplace and among human operator

Ian Huang, Guandao Yang, Leonidas Guibas

Graphics design is important for various applications, including movie production and game design. To create a high-quality scene, designers usually need to spend hours in software like Blender, in which they might need to interleave and repeat operations, such as connecting material nodes, hundreds of times. Moreover, slightly different design goals may req

Zhicheng Bao, Chen Dong, Xiaodong Xu

In this paper, we propose a novel semantic digital analog converter (sDAC) for the compatibility of semantic communications and digital communications. Most of the current semantic communication systems are based on the analog modulations, ignoring their incorporation with digital communication systems, which are more common in practice. In fact, quantizatio

Alejandro Luque-Cerpa, Miguel A. Gutiérrez-Naranjo

In Evolutionary Game Theory (EGT), a population reaches a Nash equilibrium when none of the agents can improve its objective by solely changing its strategy on its own. Roughly speaking, this equilibrium is a protection against betrayal. Generalized Nash Equilibrium (GNE) is a more complex version of this idea with important implications in real-life problem

Vikhyat Agrawal, Sunil Vasu Kalmady, Venkataseetharam Manoj Malipeddi, Manisimha Varma Manthena

This research paper explores ways to apply Federated Learning (FL) and Differential Privacy (DP) techniques to population-scale Electrocardiogram (ECG) data. The study learns a multi-label ECG classification model using FL and DP based on 1,565,849 ECG tracings from 7 hospitals in Alberta, Canada. The FL approach allowed collaborative model training without

Brian B. Moser, Ahmed Anwar, Federico Raue, Stanislav Frolov

Traditional blind image SR methods need to model real-world degradations precisely. Consequently, current research struggles with this dilemma by assuming idealized degradations, which leads to limited applicability to actual user data. Moreover, the ideal scenario - training models on data from the targeted user base - presents significant privacy concerns.

Yury Makarychev, Max Ovsiankin, Erasmo Tani

We present polylogarithmic approximation algorithms for variants of the Shortest Path, Group Steiner Tree, and Group ATSP problems with vector costs. In these problems, each edge e has a non-negative vector cost $c_e \in \mathbb{R}^{\ell}_{\ge 0}$. For a feasible solution - a path, subtree, or tour (respectively) - we find the total vector cost of all the ed

Osher Lerner, Zachary Tam, Michael Equi

Precise object manipulation and placement is a common problem for household robots, surgery robots, and robots working on in-situ construction. Prior work using computer vision, depth sensors, and reinforcement learning lacks the ability to reactively recover from planning errors, execution errors, or sensor noise. This work introduces a method that uses for

Cheng Ding, Zhicheng Guo, Zhaoliang Chen, Randall J Lee

Foundation models, especially those using transformers as backbones, have gained significant popularity, particularly in language and language-vision tasks. However, large foundation models are typically trained on high-quality data, which poses a significant challenge, given the prevalence of poor-quality real-world data. This challenge is more pronounced f

J. Aalbers, D. S. Akerib, A. K. Al Musalhi, F. Alder

The first science run of the LUX-ZEPLIN (LZ) experiment, a dual-phase xenon time project chamber operating in the Sanford Underground Research Facility in South Dakota, USA, has reported leading limits on spin-independent WIMP-nucleon interactions and interactions described from a non-relativistic effective field theory (NREFT). Using the same 5.5~t fiducial

R. Bacewicz, C. Jastrzębski, K. Zberecki, A. S. Wadge

We present a Raman study of ZrAs_{2} single crystals, a nodal line semimetal with symmetry-enforced Dirac-like band crossings. We identified the symmetry of phonon modes by polarized light measurements and comparison with calculated phonon frequencies. Significant dependence of peak intensities on the excitation wavelength was observed, indicating quantum in

A. Martinez Torres, Brenda B. Malabarba, K. P. Khemchandani

We summarize the results we obtained for the partial decay widths of $\phi(2170)$ into two-body final states formed by a $\bar K$ and a Kaonic resonance, like $K(1460)$, $K_1(1270)$, as well as to final states constituted by a $\phi$ and an $\eta/\eta^\prime$ mesons. The results obtained are compared with the values extracted from experimental data on the co

Juan Pablo Alperin, Jason Portenoy, Kyle Demes, Vincent Larivière

Scopus and the Web of Science have been the foundation for research in the science of science even though these traditional databases systematically underrepresent certain disciplines and world regions. In response, new inclusive databases, notably OpenAlex, have emerged. While many studies have begun using OpenAlex as a data source, few critically assess it

Qinglin Zhu, Runcong Zhao, Bin Liang, Jinhua Du

We introduce WellPlay, a reasoning dataset for multi-agent conversational inference in Murder Mystery Games (MMGs). WellPlay comprises 1,482 inferential questions across 12 games, spanning objectives, reasoning, and relationship understanding, and establishes a systematic benchmark for evaluating agent reasoning abilities in complex social settings. Building

H. Wells

A virtual element discretisation of an Arbitrary Lagrangian-Eulerian method for two-dimensional convection-diffusion equations is proposed employing an isoparametric Virtual Element Method to achieve higher-order convergence rates on curved edged polygonal meshes. The proposed method is validated with numerical experiments in which optimal $H^1$ and $L^2$ co

Dennis V. Perepelitsa

A major complication in the search for jet quenching in proton- or deuteron-nucleus collision systems is the presence of physical effects which influence the experimental determination of collision centrality in the presence of a hard process. For example, in the proton color fluctuation picture, protons with a large Bjorken-$x$ ($x \gtrsim 0.1$) parton inte

Lucas Dyke, Hans-Reinhard Müller

Radiation pressure exerted by solar photon output is salient to the motion of primary neutral hydrogen atoms streaming into the inner heliosphere directly from the Local Interstellar Medium (LISM). The action of a time-dependent radiation pressure force, when coupled with the usual gravitational force, changes the characteristic velocities, and therefore ene

Anna Gagnebin, Sagnick Mukherjee, Jonathan J. Fortney, Natasha E. Batalha

Recent JWST eclipse spectra of the high-density hot Saturn HD 149026b between 2.35 and 5.08 $\mu$m has allowed for in-depth study of its atmosphere. To understand its atmospheric properties, we have created a grid of 1D radiative-convective-thermochemical equilibrium atmosphere models and spectra with PICASO 3.0. In agreement with previous work, we find that

Frédéric Bouchard, Kate Fenwick, Kent Bonsma-Fisher, Duncan England

We propose a quantum information processing platform that utilizes the ultrafast time-bin encoding of photons. This approach offers a pathway to scalability by leveraging the inherent phase stability of collinear temporal interferometric networks at the femtosecond-to-picosecond timescale. The proposed architecture encodes information in ultrafast temporal b

Grigore Călugăreanu, Horia F. Pop, Adrian Vasiu

A unimodular $2\times 2$ matrix $A$ with entries in a commutative ring $R$ is called weakly determinant liftable if there exists a matrix $B$ congruent to $A$ modulo $R\det(A)$ and $\det(B)=0$; if we can choose $B$ to be unimodular, then $A$ is called determinant liftable. If $A$ is extendable to an invertible $3\times 3$ matrix $A^+$, then $A$ is weakly det

Alessandro Geraldini, Stephan Brunner

Between a plasma and a solid target lies a positively charged sheath of several Debye lengths $\lambda_{\rm D}$ in width, typically much smaller than the characteristic length scale $L$ of the main plasma. This scale separation implies that the asymptotic limit $\epsilon = \lambda_{\rm D} / L \rightarrow 0$ is useful to solve for the plasma-sheath system. In

Daniel G. Figueroa, Toby Opferkuch, Ben A. Stefanek

We study the dynamics of a non-minimally coupled (NMC) scalar spectator field in non-oscillatory inflationary scenarios, where there is a transition from inflation to kination domination (KD). Engineering a realistic finite-duration transition through a CMB-compatible inflaton potential, we calculate the initial tachyonic growth of the NMC field during KD an

Bharat Chandra P, Binukumar G. Nair, Shubham Jankiram Ghatul, Shubhangi Jain

The Spectroscopic Investigation of Nebular Gas (SING) is a near-ultraviolet (NUV) low-resolution spectrograph payload designed to operate in the NUV range, 1400 $\unicode{x212B}$ -- 2700 $\unicode{x212B}$, from a stable space platform. SING telescope has a primary aperture of 298 mm, feeding the light to the long-slit UV spectrograph. SING has a field of vie

Yi-Xuan Lee, Ho-Lin Chen

The Chemical Reaction Network (CRN) is a well-studied model that describes the interaction of molecules in well-mixed solutions. In 2014, Qian and Winfree [22] proposed the abstract surface chemical reaction network model (sCRN), which takes the advantage of spatial separation by placing molecules on a structured surface, limiting the interaction between mol

Olivier C. Pasche, Jonathan Wider, Zhongwei Zhang, Jakob Zscheischler

The forecast accuracy of machine learning (ML) weather prediction models is improving rapidly, leading many to speak of a "second revolution in weather forecasting". With numerous methods being developed and limited physical guarantees offered by ML models, there is a critical need for a comprehensive evaluation of these emerging techniques. While this need

Santtu Keskinen

In class incremental learning, neural networks typically suffer from catastrophic forgetting. We show that an MLP featuring a sparse activation function and an adaptive learning rate optimizer can compete with established regularization techniques in the Split-MNIST task. We highlight the effectiveness of the Adaptive SwisH (ASH) activation function in this

Oliver R. Gittus, Fernando Bresme

The thermal conductivity of water features a maximum (TCM) as a function of temperature at constant pressure. By examining why molecular force fields succeed or fail to reproduce the maximum and interpreting our results using the Bridgman equation, we show that water's TCM is connected with its compressibility minimum. Using Stillinger-Weber potentials for t

Néstor Jara, Emir Molina

We extend the notions of nonautonomous dynamics to arbitrary groups, through groupoid morphisms. This also presents a generalization of classic dynamical systems and group actions. We introduce the structure of cotranslations, as a specific kind of groupoid morphism, and establish a correspondence between cotranslations and skew-products. We give application

J. Pedro de Souza, Howard A. Stone

The Flory-Huggins theory describes the phase separation of solutions containing polymers. Although it finds widespread application from polymer physics to materials science to biology, the concentrations that coexist in separate phases at equilibrium have not been determined analytically, and numerical techniques are required that restrict the theory's ease

Augusto B. Corrêa, Jendrik Seipp

One key decision for heuristic search algorithms is how to balance exploration and exploitation. In classical planning, novelty search has come out as the most successful approach in this respect. The idea is to favor states that contain previously unseen facts when searching for a plan. This is done by maintaining a record of the tuples of facts observed in

Dmitry D. Ofengeim, Peter S. Shternin, Tsvi Piran

Numerous models of neutron star (NS) equation of state (EoS) exist based on different superdense-matter physics approaches. Nevertheless, some NS properties show universal (EoS-independent) relations. Here, we propose a novel class of such universalities. Despite different physics inputs, a wide class of realistic nucleonic, hyperonic, and hybrid EoS models

Siddhant Das

In the framework of the de Broglie-Bohm pilot-wave theory, or Bohmian mechanics, we examine two pedagogical problems that illustrate the bound and unbound motion of spin-1/2 particles: First, a single spin-1/2 particle trapped in the ground state of a spherical box is studied in both the relativistic and nonrelativistic versions of the theory; second, the fr

Boyang Sun, Yu Yao, Guang-Yuan Hao, Yumou Qiu

Testing conditional independence has many applications, such as in Bayesian network learning and causal discovery. Different test methods have been proposed. However, existing methods generally can not work when only discretized observations are available. Specifically, consider $X_1$, $\tilde{X}_2$ and $X_3$ are observed variables, where $\tilde{X}_2$ is a

Masakazu Muto, Tatsuya Yoshino, Shinji Tamano

The present study proposes a novel and simple rheo-optical technique to investigate the relation between the rheology of complex fluids and their internal structural deformation under uniaxial extensional flow. The macroscale results of viscoelasticity from rheological measurements and microscale results of birefringence from optical measurements are combine

Yichuan Li, Kaize Ding, Jianling Wang, Kyumin Lee

With the capabilities of understanding and executing natural language instructions, Large language models (LLMs) can potentially act as a powerful tool for textual data augmentation. However, the quality of augmented data depends heavily on the augmentation instructions provided, and the effectiveness can fluctuate across different downstream tasks. While ma

Vasu Sharma, Karthik Padthe, Newsha Ardalani, Kushal Tirumala

In recent times training Language Models (LMs) have relied on computationally heavy training over massive datasets which makes this training process extremely laborious. In this paper we propose a novel method for numerically evaluating text quality in large unlabelled NLP datasets in a model agnostic manner to assign the text instances a "quality score". By

Vitali Telezki, Stefan Klumpp

Active particles with a (magnetic) dipole moment are of interest for steering self-propelled motion, but also result in novel collective effects due to their dipole-dipole interaction. Here systems of active dipolar particles are studied with Brownian dynamics simulations to systematically characterize the different patterns they form, specifically in the pr

Jo Verwohlt, Charlotte A. Mason, Julian B. Muñoz, Francis-Yan Cyr-Racine

The formation redshift and abundance of the first stars and galaxies is highly sensitive to the build up of low mass dark matter halos as well as astrophysical feedback effects which modulate star formation in these low mass halos. The 21-cm signal at cosmic dawn will depend strongly on the formation of these first luminous sources and thus can be used to co

Noah Braeger, Vivek Chakrabhavi, Jonathan J. Heckman, Max Hübner

We determine generalized symmetries for 4D theories engineered via type II strings on non-supersymmetric orbifold backgrounds $\mathbb{R}^{3,1} \times \mathbb{R}^6 / \Gamma$. Probe branes detect generalized symmetries via the adjacency matrix for fermionic degrees of freedom in an associated quiver gauge theory. In situations where the tachyons are sequester

Mohammed M. Al Ezzi, Liangtao Peng, Zhengyu Liu, Jonah Huang Zi Chao

For twisted bilayer graphene close to magic angle, we show that the effects of lattice relaxation and the Hartree interaction both become simultaneously important. Including both effects in a continuum theory reveals a Lifshitz transition to a Fermi surface topology that supports both a ``heavy fermion" pocket and an ultraflat band ($\approx 8~{\rm meV}$) th

Claire L. Greenwell, Lizelke Klindt, George B. Lansbury, David J. Rosario

We present a catalog of hard X-ray serendipitous sources detected in the first 80 months of observations by the Nuclear Spectroscopic Telescope Array (NuSTAR). The NuSTAR serendipitous survey 80-month (NSS80) catalog has an unprecedented $\sim$ 62 Ms of effective exposure time over 894 unique fields (a factor of three increase over the 40-month catalog), wit

Minyuan Jiang, Benjamin D. Pecjak, Gilad Perez, Somasundaram Sankaranarayanan

We consider an effective theory for a shift-symmetric, quadratically-coupled, ultralight spin-0 field. The leading CP-conserving interactions with Standard Model fields in the effective theory arise at dimension 8. We discuss the renormalization group evolution and positivity bounds on these operators, as well as their possible UV origins. Assuming that the

Sergey Alekseev, Sayed Ali Akbar Ghorashi, Rafael M. Fernandes, Jennifer Cano

Motivated by recent experiments reporting unconventional collective modes in the charge density-wave (CDW) state of rare-earth tritellurides $R$Te$_3$, we derive from a multi-orbital microscopic model on the square net a CDW Ginzburg-Landau theory that allows for non-trivial orbital order. Our analysis reveals unconventional CDWs where order parameters with

L. Bisigello, C. Gruppioni, A. Bolatto, L. Ciesla

The most active phases of star formation and black hole accretion are strongly affected by dust extinction, making far-infrared (far-IR) observations the best way to disentangle and study the co-evolution of galaxies and super massive black holes. The plethora of fine structure lines and emission features from dust, ionised and neutral atomic and warm molecu

Kathleen Hart, Ruairidh Sutcliffe, Gil Refael, Arun Paramekanti

Motivated by advances in pump-probe experiments and light-driven phenomena, we theoretically study the impact of pumped and driven phonons in Mott insulators which host multipole moments, thus going beyond conventional dipolar magnetism. As a case study, we examine pseudospin-1/2 Mott insulators hosting quadrupolar and octupolar moments, and investigate the

Marco Matteini, Miha Nemevšek, Yutaro Shoji, Lorenzo Ubaldi

We consider a single real scalar field in flat spacetime with a polynomial potential up to $\phi^4$, that has a local minimum, the false vacuum, and a deeper global minimum, the true vacuum. When the vacua are almost degenerate we are in the thin wall regime, while as their difference in potential energy increases, we approach the thick wall regime. We give

Angelina Sherman, Ke Fang, Rafael Alves Batista, Rogerio Menezes de Almeida

Ultra-high-energy cosmic rays, accelerated hadrons that can exceed energies of $10^{20}$ eV, are the highest-energy particles ever observed. While the sources producing UHECRs are still unknown, the Pierre Auger Observatory has detected a large-scale dipole anisotropy in the arrival directions of cosmic rays above 8 EeV. In this work, we explore whether reso

Oliver Zier, Rahul Kannan, Aaron Smith, Mark Vogelsberger

Radiative transfer (RT) is a crucial ingredient for self-consistent modelling of numerous astrophysical phenomena across cosmic history. However, on-the-fly integration into radiation-hydrodynamics (RHD) simulations is computationally demanding, particularly due to the stringent time-stepping conditions and increased dimensionality inherent in multi-frequenc

Jasleen Matharu, Erica J. Nelson, Gabriel Brammer, Pascal A. Oesch

We present the first results on the spatial distribution of star formation in 454 star-forming galaxies at $4.8<z<6.5$ using H-Alpha emission-line maps and F444W imaging tracing the stellar continuum from JWST FRESCO NIRCam Slitless Spectroscopy. Star-forming galaxies with stellar masses $6.8\leq$log($M_{*}/\mathrm{M}_{\odot}$)$<11.1$ have positive H-Alpha e

Maxime Dupont, Bhuvanesh Sundar, Bram Evert, David E. Bernal Neira

Achieving high-quality solutions faster than classical solvers on computationally hard problems is a challenge for quantum optimization to deliver utility. Using a superconducting quantum computer, we experimentally investigate the performance of a hybrid quantum-classical algorithm inspired by semidefinite programming approaches for solving the maximum-cut

Elizabeth J. Dresselhaus, Alexander Avdoshkin, Zhetao Jia, Matteo Secli

Emerging experimental platforms use amorphousness, a constrained form of disorder, to tailor meta-material properties. We study localization under this type of disorder in a family of 2D models generalizing recent experiments on photonic systems. Models in this family reside on amorphous analogs of kagom\'{e} lattices with fixed coordination number, vary by

Eric B. Roon, Robert Sims

We consider models of open quantum spin systems with irreversible dynamics and show that general quasi-locality results for long-range models, e.g. as proven for the Heisenberg dynamics associated to quantum systems in [27], naturally extend to this setting. Given these bounds, we provide two applications. First, we use these results to obtain estimates on a

Jessica L. Ross, Arman Sabbaghi, Run Zhuang, Daniele Bertolini

Clinical trials are critical in advancing medical treatments but often suffer from immense time and financial burden. Advances in statistical methodologies and artificial intelligence (AI) present opportunities to address these inefficiencies. Here we introduce Prognostic Covariate-Adjusted Mixed Models for Repeated Measures (PROCOVA-MMRM) as an advantageous