July 2023 arXiv papers — page 147

Deepak Raina, Dimitrios Ntentia, SH Chandrashekhara, Richard Voyles

Ultrasound imaging is a commonly used modality for several diagnostic and therapeutic procedures. However, the diagnosis by ultrasound relies heavily on the quality of images assessed manually by sonographers, which diminishes the objectivity of the diagnosis and makes it operator-dependent. The supervised learning-based methods for automated quality assessm

Benjamin Y. L. Tan, Beng Yee Gan, Daniel Leykam, Dimitris G. Angelakis

We show how the localization landscape, originally introduced to bound low energy eigenstates of disordered wave media and many-body quantum systems, can form the basis for hardware-efficient quantum algorithms for solving binary optimization problems. Many binary optimization problems can be cast as finding low-energy eigenstates of Ising Hamiltonians. Firs

Feiyang Kang, Hoang Anh Just, Anit Kumar Sahu, Ruoxi Jia

Traditionally, data selection has been studied in settings where all samples from prospective sources are fully revealed to a machine learning developer. However, in practical data exchange scenarios, data providers often reveal only a limited subset of samples before an acquisition decision is made. Recently, there have been efforts to fit scaling laws that

Osman Emre Dai, Daniel Cullina, Negar Kiyavash

Database alignment is a variant of the graph alignment problem: Given a pair of anonymized databases containing separate yet correlated features for a set of users, the problem is to identify the correspondence between the features and align the anonymized user sets based on correlation alone. This closely relates to planted matching, where given a bigraph w

Zheyi Ding, Gang Li, Adolfo Santa Fe Dueñas, Robert W. Ebert

We examine the East-West asymmetry of the peak intensity in energetic storm particle (ESP) events using the improved Particle Acceleration and Transport in the Heliosphere (iPATH) model. We find that injection efficiency peaks east of the nose of coronal mass ejection shock where the shock exhibits a quasi-parallel geometry. We show that the peak intensity a

Liangbin Xie, Xintao Wang, Xiangyu Chen, Gen Li

Image super-resolution (SR) with generative adversarial networks (GAN) has achieved great success in restoring realistic details. However, it is notorious that GAN-based SR models will inevitably produce unpleasant and undesirable artifacts, especially in practical scenarios. Previous works typically suppress artifacts with an extra loss penalty in the train

Qingyuan Jiang

This paper establishes semiorthogonal decompositions for derived Grassmannians of perfect complexes with Tor-amplitude in $[0,1]$. This result verifies the author's Quot formula conjecture [J21a] and generalizes and strengthens Toda's result in [Tod23]. We give applications of this result to various classical situations such as blowups of determinantal ideal

Shun Zhang

This article examines the impact of China's delayed retirement announcement on households' savings behavior using data from China Family Panel Studies (CFPS). The article finds that treated households, on average, experience an 8% increase in savings rates as a result of the policy announcement. This estimation is both significant and robust. Different types

Carsten Hartmann, Lorenz Richter

The recent advances in machine learning in various fields of applications can be largely attributed to the rise of deep learning (DL) methods and architectures. Despite being a key technology behind autonomous cars, image processing, speech recognition, etc., a notorious problem remains the lack of theoretical understanding of DL and related interpretability

Francesco Caravenna, Francesca Cottini, Maurizia Rossi

We study the 2d directed polymer in random environment in a novel *quasi-critical regime*, which interpolates between the much studied sub-critical and critical regimes. We prove Edwards-Wilkinson fluctuations throughout the quasi-critical regime, showing that the diffusively rescaled partition functions are asymptotically Gaussian. We deduce a corresponding

Long Bai, Tong Chen, Yanan Wu, An Wang

Wireless capsule endoscopy (WCE) is a painless and non-invasive diagnostic tool for gastrointestinal (GI) diseases. However, due to GI anatomical constraints and hardware manufacturing limitations, WCE vision signals may suffer from insufficient illumination, leading to a complicated screening and examination procedure. Deep learning-based low-light image en

Sergei Stishov

The thermodynamic properties of the Boltzmann hard sphere system is discussed. It was found that zero point energy decreases with temperature so slowly that it turned out to be an almost a constant addition to the classical value. In result the heat capacity of the system differs little from the classical value of 1.5 k everywhere except for the narrow regio

John A. Snoap, Dimitrie C. Popescu, Chad M. Spooner

The paper considers the problem of deep-learning-based classification of digitally modulated signals using I/Q data and studies the generalization ability of a trained neural network (NN) to correctly classify digitally modulated signals it has been trained to recognize when the training and testing datasets are distinct. Specifically, we consider both a res

Aidan O'Gara

Are current language models capable of deception and lie detection? We study this question by introducing a text-based game called $\textit{Hoodwinked}$, inspired by Mafia and Among Us. Players are locked in a house and must find a key to escape, but one player is tasked with killing the others. Each time a murder is committed, the surviving players have a n

Gorka Zamora-López, Matthieu Gilson

Built upon the shoulders of graph theory, the field of complex networks has become a central tool for studying real systems across various fields of research. Represented as graphs, different systems can be studied using the same analysis methods, which allows for their comparison. Here, we challenge the wide-spread idea that graph theory is a universal anal

Oluwami Dosunmu-Ogunbi, Aayushi Shrivastava, Grant Gibson, Jessy W Grizzle

A new control paradigm using angular momentum and foot placement as state variables in the linear inverted pendulum model has expanded the realm of possibilities for the control of bipedal robots. This new paradigm, known as the ALIP model, has shown effectiveness in cases where a robot's center of mass height can be assumed to be constant or near constant a

Timon Böhler, David Richter, Mira Mezini

Automatic Differentiation (AD) has become a dominant technique in ML. AD frameworks have first been implemented for imperative languages using tapes. Meanwhile, functional implementations of AD have been developed, often based on dual numbers, which are close to the formal specification of differentiation and hence easier to prove correct. But these papers h

Alifia Puspaningrum, Muhammad Anis Al Hilmi, Darsih, Muhamad Mustamiin

In Software Development Life Cycle (SDLC), security vulnerabilities are one of the points introduced during the construction stage. Failure to detect software defects earlier after releasing the product to the market causes higher repair costs for the company. So, it decreases the company's reputation, violates user privacy, and causes an unrepairable issue

Dennis Tilipman, Maria Kazachenko, Benoit Tremblay, Ivan Milic

Poynting flux is the flux of magnetic energy, which is responsible for chromospheric and coronal heating in the solar atmosphere. It is defined as a cross product of electric and magnetic fields, and in ideal MHD conditions it can be expressed in terms of magnetic field and plasma velocity. Poynting flux has been computed for active regions and plages, but e

Jacek Brodzki, Ran Levi, Henri Riihimäki

Let $k$ be a field and let $C$ be a small category. A $k$-linear representation of $C$, or a $kC$-module, is a functor from $C$ to the category of finite dimensional vector spaces over $k$. When the category $C$ is more general than a linear order, then its representation type is generally infinite and in most cases wild. Hence the task of understanding such

Max Hort, Anastasiia Grishina, Leon Moonen

Large language models trained on source code can support a variety of software development tasks, such as code recommendation and program repair. Large amounts of data for training such models benefit the models' performance. However, the size of the data and models results in long training times and high energy consumption. While publishing source code allo

Deepak Raina, SH Chandrashekhara, Richard Voyles, Juan Wachs

Ultrasound is a vital imaging modality utilized for a variety of diagnostic and interventional procedures. However, an expert sonographer is required to make accurate maneuvers of the probe over the human body while making sense of the ultrasound images for diagnostic purposes. This procedure requires a substantial amount of training and up to a few years of

M. K. Keshari, Soumi Tikader

Let $A$ be a regular ring of dimension $d$ essentially of finite type over an infinite field $k$ of characteristic $\neq 2$. Let $P$ be a projective $A$-module of rank $n$ with $2n\geq d+3$. Let $I$ be an ideal of $A[T]$ of height $n$ and $\phi:P[T]\twoheadrightarrow I/I^2$ be a surjection. If $\phi\otimes A(T)$ has a surjective lift $\theta :P[T]\otimes A(T

Kuni H Iwasa

Avian prestin is sensitive to membrane thickness as much as mammalian prestin, which undergoes conformational transitions in membrane area and thereby drives length changes of the cylindrical cell body of outer hair cells. The membrane thickness dependence of mammalian prestin stems from changes in hydrophobic profile in conformational states, accompanied by

I. Arregui, D. Y. Kolotkov, V. M. Nakariakov

We compute the evidence in favour of two models, one based on field-aligned thermal conduction alone and another that includes thermal misbalance as well, in explaining the damping of slow magneto-acoustic waves in hot coronal loops. Our analysis is based on the computation of the marginal likelihood and the Bayes factor for the two damping models. We quanti

Dominik Fay, Sebastian Mair, Jens Sjölund

For scalable machine learning on large data sets, subsampling a representative subset is a common approach for efficient model training. This is often achieved through importance sampling, whereby informative data points are sampled more frequently. In this paper, we examine the privacy properties of importance sampling, focusing on an individualized privacy

Bojan Nikolić, Danijel Obrić

In this article we examine T-dualization in double space formalism of type II superstring theory in pure spinor formulation. Background fields that we consider will all be constant except Ramond-Ramond field which will infinitesimally depend only on bosonic coordinates $x^\mu$. In double space T-dual transformations are represented as permutations between st

Akide Liu

Memory is identified as a crucial human faculty that allows for the retention of visual and linguistic information within the hippocampus and neurons in the brain, which can subsequently be retrieved to address real-world challenges that arise through a lifetime of learning. The resolution of complex AI tasks through the application of acquired knowledge rep

Jiaxin Huang, Sarah Meng Li, Lia Yeh, Aleks Kissinger

In this work, we present a generic approach to transform CSS codes by building upon their equivalence to phase-free ZX diagrams. Using the ZX calculus, we demonstrate diagrammatic transformations between encoding maps associated with different codes. As a motivating example, we give explicit transformations between the Steane code and the quantum Reed-Muller

Zonglin Li, Nadav Yesha

For a real-valued sequence $(x_n)_{n=1}^\infty$, denote by $S_N(\ell)$ the number of its first $N$ fractional parts lying in a random interval of size $\ell:=L/N$, where $L=o(N)$ as $N\to\infty$. We study the variance of $S_N(\ell)$ (the number variance) for sequences of the form $x_n=\alpha a_n$, where $(a_n)_{n=1}^\infty$ is a sequence of distinct integers

Prateek Yadav, Qing Sun, Hantian Ding, Xiaopeng Li

Large-scale code generation models such as Codex and CodeT5 have achieved impressive performance. However, libraries are upgraded or deprecated very frequently and re-training large-scale language models is computationally expensive. Therefore, Continual Learning (CL) is an important aspect that remains underexplored in the code domain. In this paper, we int

David Camarena, Valerio Marra

This study aims to elucidate the tension in the Hubble constant ($H_0$), a key metric in cosmology representing the universe's expansion rate. Conflicting results from independent measurements such as the Planck satellite mission and the SH0ES collaboration have sparked interest in exploring alternative cosmological models. We extend the analysis by SH0ES to

Peter Frolkovič, Nikola Gajdošová

We present compact semi-implicit finite difference schemes on structured grids for numerical solutions of the advection by an external velocity and by a speed in normal direction that are applicable in level set methods. The most involved numerical scheme is third order accurate for the linear advection with a space dependent velocity and unconditionally sta

Atul Agrawal, Phaedon-Stelios Koutsourelakis

We propose a data-driven, closure model for Reynolds-averaged Navier-Stokes (RANS) simulations that incorporates aleatoric, model uncertainty. The proposed closure consists of two parts. A parametric one, which utilizes previously proposed, neural-network-based tensor basis functions dependent on the rate of strain and rotation tensor invariants. This is com

Johannes Wirtz, Stéphane Guindon

The introduction of the spatial Lambda-Fleming-Viot model (LV) in population genetics was mainly driven by the pioneering work of Alison Etheridge, in collaboration with Nick Barton and Amandine V\'eber about ten years ago (1,2). The LV model provides a sound mathematical framework for describing the evolution of a population of related individuals along a s

Yalda Foroutan, Alon Harell, Anderson de Andrade, Ivan V. Bajić

A basic premise in scalable human-machine coding is that the base layer is intended for automated machine analysis and is therefore more compressible than the same content would be for human viewing. Use cases for such coding include video surveillance and traffic monitoring, where the majority of the content will never be seen by humans. Therefore, base lay

Md Washik Al Azad, Hasniuj Zahan, Sifat Ut Taki, Spyridon Mastorakis

Tor is the most popular anonymous communication overlay network which hides clients' identities from servers by passing packets through multiple relays. To provide anonymity to both clients and servers, Tor onion services were introduced by increasing the number of relays between a client and a server. Because of the limited bandwidth of Tor relays, large nu

Miles Bakenhus, Sonja Petrović

The set of nonnegative integer lattice points in a polytope, also known as the fiber of a linear map, makes an appearance in several applications including optimization and statistics. We address the problem of sampling from this set using three ingredients: an easy-to-compute lattice basis of the constraint matrix, a biased sampling algorithm with a Bayesia

Stefano Ferraro, Pietro Mazzaglia, Tim Verbelen, Bart Dhoedt

Understanding the world in terms of objects and the possible interplays with them is an important cognition ability, especially in robotics manipulation, where many tasks require robot-object interactions. However, learning such a structured world model, which specifically captures entities and relationships, remains a challenging and underexplored problem.

Oana Vesa, Jason Jackiewicz, Kevin Reardon

Atmospheric gravity waves (AGWs) are low-frequency, buoyancy-driven waves that are generated by turbulent convection and propagate obliquely throughout the solar atmosphere. Their proposed energy contribution to the lower solar atmosphere and sensitivity to atmospheric parameters (e.g. magnetic fields and radiative damping) highlight their diagnostic potenti

Roberto Abril Valenzuela, Paul Z. Hanakata, Mark J. Bowick

We study the finite-temperature dynamics of thin elastic sheets in a single-clamped cantilever configuration. This system is known to exhibit a tilt transition at which the preferred mean plane of the sheet shifts from horizontal to a plane above or below the horizontal. The resultant thermally roughened two-state (up/down) system possesses rich dynamics on

Stephan Sinzig, Christoph P. Schmidt, Wolfgang A. Wall

A novel approach is presented to efficiently include transport effects in thin active material coating layers of all-solid-state batteries using a dimensionally reduced formulation embedded into a three-dimensionally resolved coupled electrochemo-mechanical continuum model. In the literature, the effect of coating layers is so far captured by additional zero

Matthew Mizell, James Oxley

Targets are matroids that arise from a nested sequence of flats in a projective geometry. This class of matroids was introduced by Nelson and Nomoto, who found the forbidden induced restrictions for binary targets. This paper generalizes their result to targets arising from projective geometries over $GF(q)$. We also consider targets arising from nested sequ

Jarrod Burgh, Emerson Melo

We develop a model of wishful thinking that incorporates the costs and benefits of biased beliefs. We establish the connection between distorted beliefs and risk, revealing how wishful thinking can be understood in terms of risk measures. Our model accommodates extreme beliefs, allowing wishful-thinking decision-makers to assign zero probability to undesirab

Chong Mou, Xintao Wang, Jiechong Song, Ying Shan

Despite the ability of existing large-scale text-to-image (T2I) models to generate high-quality images from detailed textual descriptions, they often lack the ability to precisely edit the generated or real images. In this paper, we propose a novel image editing method, DragonDiffusion, enabling Drag-style manipulation on Diffusion models. Specifically, we c

Karthik Adimurthi, Wontae Kim

In this paper, we study some regularity issues concerning the gradient of weak solutions of $u_t - {\rm div} \mathcal{A}(x,t,\nabla u) = g$, where $\mathcal{A}(x,t,\nabla u)$ is modeled after the $p$-Laplace operator. The main results we are interested in is to obtain optimal conditions on the datum $g$ (independent of time) such that borderline higher integ

Yeqi Gao, Zhao Song, Shenghao Xie

Large language models (LLMs) have brought significant and transformative changes in human society. These models have demonstrated remarkable capabilities in natural language understanding and generation, leading to various advancements and impacts across several domains. We consider the in-context learning under two formulation for attention related regressi

Ryan M. Shifler

Let $\mbox{IG}:=\mbox{IG}(2,2n+1)$ denote the odd symplectic Grassmannian of lines which is a horospherical variety of Picard rank 1. The quantum cohomology ring $\mbox{QH}^*(\mbox{IG})$ has negative structure constants. For $n \geq 3$, we give a positivity condition that implies the quantum cohomology ring $\mbox{QH}^*(\mbox{IG})$ is the only quantum deform

Luigi Freda, Tiago Novo, David Portugal, Rui P. Rocha

This work presents a 3D multi-robot exploration framework for a team of UGVs moving on uneven terrains. The framework was designed by casting the two-level coordination strategy presented in [1] into the context of multi-robot exploration. The resulting distributed exploration technique minimizes and explicitly manages the occurrence of conflicts and interfe

Sayan Bhattacharya, Martín Costa, Nadav Panski, Shay Solomon

Vizing's theorem asserts the existence of a $(\Delta+1)$-edge coloring for any graph $G$, where $\Delta = \Delta(G)$ denotes the maximum degree of $G$. Several polynomial time $(\Delta+1)$-edge coloring algorithms are known, and the state-of-the-art running time (up to polylogarithmic factors) is $\tilde{O}(\min\{m \cdot \sqrt{n}, m \cdot \Delta\})$, by Gabo

Ning Yang, Junrui Wen, Meng Zhang, Ming Tang

Mobile edge computing (MEC) is essential for next-generation mobile network applications that prioritize various performance metrics, including delays and energy consumption. However, conventional single-objective scheduling solutions cannot be directly applied to practical systems in which the preferences of these applications (i.e., the weights of differen

Xin Sheng, Lizhong Zhang, Omer Blaes, Yan-Fei Jiang

We present relativistic, radiation magnetohydrodynamic simulations of supercritical neutron star accretion columns in Cartesian geometry, including temperature-dependent, polarization-averaged Rosseland mean opacities accounting for classical electron scattering in a magnetic field. Just as in our previous pure Thomson scattering simulations, vertical oscill

Enrique Saurez, Harshit Gupta, Henriette Roger, Sukanya Bhowmik

Real-time video analytics typically require video frames to be processed by a query to identify objects or activities of interest while adhering to an end-to-end frame processing latency constraint. Such applications impose a continuous and heavy load on backend compute and network infrastructure because of the need to stream and process all video frames. Vi

Shengding Hu, Ning Ding, Weilin Zhao, Xingtai Lv

The scale of large pre-trained models (PTMs) poses significant challenges in adapting to downstream tasks due to the high optimization overhead and storage costs associated with full-parameter fine-tuning. To address this, many studies explore parameter-efficient tuning methods, also framed as "delta tuning", which updates only a small subset of parameters,

Federico Dell'Anna, Sunny Pradhan, Cristian Degli Esposti Boschi, Elisa Ercolessi

In this paper, we study the ground state Quantum Fisher Information (QFI) in one-dimensional spin-1 models, as witness to Multipartite Entanglement. The models addressed are the Bilinear-Biquadratic model, the most general isotropic SU(2)-invariant spin-1 chain, and the XXZ spin-1 chain, both with nearest-neighbor interactions and open boundary conditions. W

Richard Pymar, Nicolás Rivera

We study the mixing time of the symmetric beta-binomial splitting process on finite weighted connected graphs $G=(V,E,\{r_e\}_{e\in E})$ with vertex set $V$, edge set $E$ and positive edge-weights $r_e>0$ for $e\in E$. This is an interacting particle system with a fixed number of particles that updates through vertex-pairwise interactions which redistribute

John Andrew Raine, Matthew Leigh, Knut Zoch, Tobias Golling

In this work we introduce $\nu^2$-Flows, an extension of the $\nu$-Flows method to final states containing multiple neutrinos. The architecture can natively scale for all combinations of object types and multiplicities in the final state for any desired neutrino multiplicities. In $t\bar{t}$ dilepton events, the momenta of both neutrinos and correlations bet

Yu. M. Andreev, D. Banerjee, B. Banto Oberhauser, J. Bernhard

Thermal dark matter models with particle $\chi$ masses below the electroweak scale can provide an explanation for the observed relic dark matter density. This would imply the existence of a new feeble interaction between the dark and ordinary matter. We report on a new search for the sub-GeV $\chi$ production through the interaction mediated by a new vector

Pritam P Shetty, Hemalatha V, Mahalingam Babu, Jayachandra Bingi

Common path interferometers (CPI) are significant due to their compactness and vibration resistance. The usual challenge in CPI would arise due to a very small separation between reference and sample beams, where sending a reference beam through a sample is considered as a limitation. But this limitation also makes it difficult to probe the interaction of be

Henri De Plaen, Pierre-François De Plaen, Johan A. K. Suykens, Marc Proesmans

During training, supervised object detection tries to correctly match the predicted bounding boxes and associated classification scores to the ground truth. This is essential to determine which predictions are to be pushed towards which solutions, or to be discarded. Popular matching strategies include matching to the closest ground truth box (mostly used in

T. -K. Hsiao, P. Cova Fariña, S. D. Oosterhout, D. Jirovec

Quantum systems with engineered Hamiltonians can be used as simulators of many-body physics problems to provide insights beyond the capabilities of classical computers. Semiconductor gate-defined quantum dot arrays have emerged as a versatile platform for quantum simulation of generalized Fermi-Hubbard physics, one of the richest playgrounds in condensed mat

A. A. Kirillov, E. P. Savelova

It is shown that in the presence of virtual wormholes, the vacuum is unstable, which leads to a series of phase transitions in the early Universe. Then the standard Kibble scenario predicts the formation of defects such as domain walls. An unusual feature of virtual wormholes is that they generate defects with negative energy density. Such defects have macro

Einar Aurbakken, Benedicte Sverdrup Ofstad, Håkon Emil Kristiansen, Øyvind Sigmundson Schøyen

Based on the work done by an electromagnetic field on an atomic or molecular electronic system, a general gauge invariant formulation of transient absorption spectroscopy is presented within the semi-classical approximation. Avoiding multipole expansions, a computationally viable expression for the spectral response function is derived from the minimal-coupl

Daniel G. Figueroa, Mauro Pieroni, Angelo Ricciardone, Peera Simakachorn

We discuss the interpretation of the detected signal by Pulsar Timing Array (PTA) observations as a gravitational wave background (GWB) of cosmological origin. We combine NANOGrav 15-years and EPTA-DR2new data sets and confront them against backgrounds from supermassive black hole binaries (SMBHBs), and cosmological signals from inflation, cosmic (super)stri

Zhaoze Wang, Junsong Wang

Hub structure, characterized by a few highly interconnected nodes surrounded by a larger number of nodes with fewer connections, is a prominent topological feature of biological brains, contributing to efficient information transfer and cognitive processing across various species. In this paper, a mathematical model of hub structure is presented. The propose

Wen Ji, Ke Han, Qian Ge

Vehicle-based mobile sensing is an emerging data collection paradigm that leverages vehicle mobilities to scan a city at low costs. Certain urban sensing scenarios require dedicated vehicles for highly targeted monitoring, such as volatile organic compounds (VOCs, a type of air pollutant) sensing, road surface monitoring, and accident site investigation. A h

M. Janvier, S. Mzerguat, P. R. Young, É. Buchlin

The Solar Orbiter mission completed its first remote-sensing observation windows in the spring of 2022. On 2/4/2022, an M-class flare followed by a filament eruption was seen both by the instruments on board the mission and from several observatories in Earth's orbit. The complexity of the observed features is compared with the predictions given by the stand

Natsumi Ikeno, Akira Ono

The momentum dependence of the nucleon mean-field potential in a wide momentum range can be an important factor to determine the $\Delta$ resonance and pion production in intermediate-energy heavy-ion collisions. In particular, in neutron-rich systems such as ${}^{132}\mathrm{Sn}+{}^{124}\mathrm{Sn}$ collisions, we need to carefully treat the momentum depend

Shengding Hu, Yifan Luo, Huadong Wang, Xingyi Cheng

Pre-trained language models (PLMs) have shown unprecedented potential in various fields, especially as the backbones for question-answering (QA) systems. However, they tend to be easily deceived by tricky questions such as "How many eyes does the sun have?". Such frailties of PLMs often allude to the lack of knowledge within them. In this paper, we find that

Parul Janagal, Samuel J. McSweeney, Manoneeta Chakraborty, N. D. Ramesh Bhat

PSR J0026-1955 was independently discovered by the Murchison Widefield Array (MWA) recently. The pulsar exhibits subpulse drifting, where the radio emission from a pulsar appears to drift in spin phase within the main pulse profile, and nulling, where the emission ceases briefly. The pulsar showcases a curious case of drift rate evolution as it exhibits rapi

Renato Sortino, Thomas Cecconello, Andrea DeMarco, Giuseppe Fiameni

Along with the nearing completion of the Square Kilometre Array (SKA), comes an increasing demand for accurate and reliable automated solutions to extract valuable information from the vast amount of data it will allow acquiring. Automated source finding is a particularly important task in this context, as it enables the detection and classification of astro

John A. Snoap

Physical layer approaches for generating secret encryption keys for wireless systems using channel information have attracted increased interest from researchers in recent years. This paper presents a new approach for calculating log-likelihood ratios (LLRs) for secret key generation that is based on one-bit quantization of channel measurements and the diffe

Stephanie Long, Alexandre Piché, Valentina Zantedeschi, Tibor Schuster

Understanding the causal relationships that underlie a system is a fundamental prerequisite to accurate decision-making. In this work, we explore how expert knowledge can be used to improve the data-driven identification of causal graphs, beyond Markov equivalence classes. In doing so, we consider a setting where we can query an expert about the orientation

Christian Ikenmeyer, Sathyawageeswar Subramanian

We prove that the computation of the Kronecker coefficients of the symmetric group is contained in the complexity class #BQP. This improves a recent result of Bravyi, Chowdhury, Gosset, Havlicek, and Zhu. We use only the quantum computing tools that are used in their paper and additional classical representation theoretic insights. We also prove the analogou

Parker Knight, Rui Duan

Multi-task learning has emerged as a powerful machine learning paradigm for integrating data from multiple sources, leveraging similarities between tasks to improve overall model performance. However, the application of multi-task learning to real-world settings is hindered by data-sharing constraints, especially in healthcare settings. To address this chall

Taras Mel'nyk, Christian Rohde

This article completes the study of the influence of the intensity parameter $\alpha$ in the boundary condition $\varepsilon \partial_{\boldsymbol{\nu}_\varepsilon} u_\varepsilon - u_\varepsilon \, \overrightarrow{V_\varepsilon}\boldsymbol{\cdot}\boldsymbol{\nu}_\varepsilon = \varepsilon^{\alpha} \varphi_\varepsilon $ given on the boundary of a thin three-di

A. L. Harris

In traditional scattering theory, the incident projectile is assumed to have an infinite coherence length. However, over the last decade, experimental and theoretical studies of collisions using heavy ion projectiles have shown that this assumption is not always valid. This has led to a growing number of studies that specifically examined the effects of the

Manuel Concha, Luc Lapointe

Bisymmetric Macdonald polynomials can be obtained through a process of antisymmetrization and $t$-symmetrization of non-symmetric Macdonald polynomials. Using the double affine Hecke algebra, we show that the evaluation of the bisymmetric Macdonald polynomials satisfies a symmetry property generalizing that satisfied by the usual Macdonald polynomials. We th

Zahra Molaee, Ahmad Shirzad

We present a new Lagrangian approach for the dynamical structure of the generalized Proca theory (GP). This approach includes the A-Z constraint structure of the model in the Lagrangian formalism and ends up with an accurate count of the number of degrees of freedom. We also give the complete Hamiltonian constraint structure of the model.

Brian A. Bittner, Jason Reid, Kevin C. Wolfe

To achieve high-dexterity motion planning on floating-base systems, the base dynamics induced by arm motions must be treated carefully. In general, it is a significant challenge to establish a fixed-base frame during tasking due to forces and torques on the base that arise directly from arm motions (e.g. arm drag in low Reynolds environments and arm momentum

Jing Song, L. R. Dai, E. Oset

We study the molecular probability of the $X(3872)$ in the $D^0 \bar D^{*0}$ and $D^+ D^{*-}$ channels in several scenarios. One of them assumes that the state is purely due to a genuine nonmolecular component. However, it gets unavoidably dressed by the meson components to the point that in the limit of zero binding of the $D^0 \bar D^{*0}$ component become

Radu Iosif, Florian Zuleger

In this paper we study a Separation Logic of Relations (SLR) and compare its expressiveness to (Monadic)Second Order Logic (M)SO. SLR is based on the well-known Symbolic Heap fragment of Separation Logic, whose formulae are composed of points-to assertions, inductively defined predicates, with the separating conjunction as the only logical connective. SLR ge

Alessandro Ingrosso, Emanuele Panizon

The cost of information processing in physical systems calls for a trade-off between performance and energetic expenditure. Here we formulate and study a computation-dissipation bottleneck in mesoscopic systems used as input-output devices. Using both real datasets and synthetic tasks, we show how non-equilibrium leads to enhanced performance. Our framework

Nicolas Garcia Trillos, Melanie Weber

Let $M$ denote a low-dimensional manifold embedded in Euclidean space and let ${X}= \{ x_1, \dots, x_n \}$ be a collection of points uniformly sampled from it. We study the relationship between the curvature of a random geometric graph built from ${X}$ and the curvature of the manifold $M$ via continuum limits of Ollivier's discrete Ricci curvature. We prove

Ioanna-Yvonni Tsaknaki, Fabrizio Lillo, Piero Mazzarisi

Financial order flow exhibits a remarkable level of persistence, wherein buy (sell) trades are often followed by subsequent buy (sell) trades over extended periods. This persistence can be attributed to the division and gradual execution of large orders. Consequently, distinct order flow regimes might emerge, which can be identified through suitable time ser

Aurélien Grabsch, Pierre Rizkallah, Olivier Bénichou

The symmetric simple exclusion process (SEP) is a paradigmatic model of diffusion in a single-file geometry, in which the particles cannot cross. In this model, the study of currents have attracted a lot of attention. In particular, the distribution of the integrated current through the origin, and more recently, of the integrated current through a moving re

Cong X. Kang, Aleksander Kelenc, Eunjeong Yi

Let $G$ be a graph with vertex set $V$. A set $S \subseteq V$ is a \emph{strong resolving set} of $G$ if, for distinct $x,y\in V$, there exists $z\in S$ such that either $x$ lies on a $y-z$ geodesic or $y$ lies on an $x-z$ geodesic in $G$. In this paper, we study maker-breaker strong resolving game (MBSRG) played on a graph by two players, Maker and Breaker,

Dong-Xu Sun, Pei-Pei Zhang, Yi-Qing Guo, Wei Liu

The observations of the energy spectra of cosmic-ray have revealed complicated structures. Especially, spectral hardenings in the boron-to-carbon and boron-to-oxygen ratios above $\sim 200$ GV has been revealed by AMS-02 and DAMPE experiments. One scenario to account for the hardenings of secondary-to-primary ratios is the nuclear fragmentation of freshly ac

Gino Perrotta, Luca Scheuer, Yocheved Kopel, Max Basescu

Achieving precise, highly-dynamic maneuvers with Unmanned Aerial Vehicles (UAVs) is a major challenge due to the complexity of the associated aerodynamics. In particular, unsteady effects -- as might be experienced in post-stall regimes or during sudden vehicle morphing -- can have an adverse impact on the performance of modern flight control systems. In thi

Annika Burmester

We present the $\tau$-invariant balanced quasi-shuffle algebra $\mathcal{G}^{\operatorname{f}}$, whose elements formalize (combinatorial) multiple Eisenstein series as well as multiple q-zeta values. In particular, $\mathcal{G}^{\operatorname{f}}$ has natural maps into these two algebras, and we expect these maps to be isomorphisms. Racinet studied the algeb

Sayak Guha Roy, Kevin Slagle

Although spatial locality is explicit in the Heisenberg picture of quantum dynamics, spatial locality is not explicit in the Schr\"odinger picture equations of motion. The gauge picture is a modification of Schr\"odinger's picture such that locality is explicit in the equations of motion. In order to achieve this explicit locality, the gauge picture utilizes

Sajjad Emdadi Mahdimahalleh

In this paper I focused on resource scheduling in the downlink of LTE-Advanced with aggregation of multiple Component Carriers (CCs). When Carrier Aggregation (CA) is applied, a well-designed resource scheduling scheme is essential to the LTE-A system. Joint User Scheduling (JUS), Separated Random User Scheduling (SRUS), Separated Burst-Level Scheduling (SBL

Steven Goldenberg, Malachi Schram, Kishansingh Rajput, Thomas Britton

Providing accurate uncertainty estimations is essential for producing reliable machine learning models, especially in safety-critical applications such as accelerator systems. Gaussian process models are generally regarded as the gold standard method for this task, but they can struggle with large, high-dimensional datasets. Combining deep neural networks wi

Fernando Diaz, Michael Madaio

Recent work has advocated for training AI models on ever-larger datasets, arguing that as the size of a dataset increases, the performance of a model trained on that dataset will correspondingly increase (referred to as "scaling laws"). In this paper, we draw on literature from the social sciences and machine learning to critically interrogate these claims.

Luisa Fiorot, Riccardo Gilblas, Alberto Tonolo

We study, through new recurrence relations for certain binomial coefficients modulo a power of a prime, the evolution of the primitives of a modular periodic sequence. We prove that we can reduce to study primitives of constant sequences and that the latter are controlled by modular binomial coefficients. Finally we apply our results to describe the dynamics

Deepika Venkattu, Peter Lundqvist, Miguel Pérez-Torres, Leah Morabito

We present an International LOFAR Telescope sub-arcsecond resolution image of the nearby galaxy M 51 with a beam size of 0.436" x 0.366" and rms of 46 $\mu$Jy. We compare this image with an European VLBI Network study of M 51, and discuss the supernovae in this galaxy, which have not yet been probed at these low radio frequencies. We find a flux density of 0

Wei Li, Likang Zhang, Hao Tan, Yichen Lu

Quantum key distribution (QKD) can provide fundamentally proven security for secure communication. Toward application, the secret key rate (SKR) is a key figure of merit for any QKD system. So far, the SKR has been limited to about a few megabit-per-second. Here we report a QKD system that is able to generate key at a record high SKR of 115.8 Mb/s over 10-km

Karthik Adimurthi, Harsh Prasad, Vivek Tewary

In this paper, we prove local H\"older continuity for the spatial gradient of weak solutions to $$u_t - \text{div} (|\nabla u|^{p-2}\nabla u) + \text{P.V.} \int_{\mathbb{R}^n} \frac{|u(x,t) - u(y,t)|^{p-2}(u(x,t)-u(y,t))}{|x-y|^{n+ps}} \ dy = 0.$$ It is easy to see that parabolic quasilinear equations are not scaling invariant and this led to the development

Jeffrey M. Hyde

The active galaxy NGC 1068 was recently identified by the IceCube neutrino observatory as the first known steady-state, extragalactic neutrino point source, associated with about 79 events over ten years. We use the IceCube data to place limits on possible neutrino self-interactions mediated by scalar particles with mass between 1 - 10 MeV. We find that cons

Daria Gazizova, J. P. F. LeBlanc

We compute the perturbative expansion for the effective interaction $W$ of the half-filled 2-dimensional Hubbard model. We derive extensions of standard RPA resummations that include arbitrarily high order contributions in the $W_{\uparrow\uparrow}$ and $W_{\uparrow\downarrow}$ basis. Using algorithmic tools we explore the static $Q$-dependent interaction as