May 2023 arXiv papers — page 147

Deviprasath Palani, Florian Hasse, Philip Kiefer, Frederick Boeckling

A variety of physical platforms are investigated for quantum control of many particles, and techniques are extended to access multiple dimensions. Here, we present our experimental study of shuttling single Mg$^+$ ions within a scalable trap-array architecture that contains up to thirteen trapping sites in a three-dimensional arrangement. We shuttle ions fro

Arian Prabowo, Hao Xue, Wei Shao, Piotr Koniusz

A road network, in the context of traffic forecasting, is typically modeled as a graph where the nodes are sensors that measure traffic metrics (such as speed) at that location. Traffic forecasting is interesting because it is complex as the future speed of a road is dependent on a number of different factors. Therefore, to properly forecast traffic, we need

Kasper Engelen, Guillermo A. Pérez, Shrisha Rao

We study the complexity of reductions for weighted reachability in parametric Markov decision processes. That is, we say a state p is never worse than q if for all valuations of the polynomial indeterminates it is the case that the maximal expected weight that can be reached from p is greater than the same value from q. In terms of computational complexity,

Chia-Hao Li, Niraj K. Jha

Modern advances in machine learning (ML) and wearable medical sensors (WMSs) in edge devices have enabled ML-driven disease detection for smart healthcare. Conventional ML-driven methods for disease detection rely on customizing individual models for each disease and its corresponding WMS data. However, such methods lack adaptability to distribution shifts a

Ali Rida, Satish I. Rao, Jaafar A. El-Awady

Slip transmission across $\alpha-\beta$ interfaces is of great significance in understanding the strength of $\alpha-\beta$ Ti alloys for aerospace applications. Molecular statics (MS) and molecular dynamics (MD) simulations were conducted to investigate the mechanisms of slip transmission of $\langle a \rangle$ prismatic screw dislocations across the $\alph

Yuanda Wang, Hanqing Guo, Guangjing Wang, Bocheng Chen

Deep learning based voice synthesis technology generates artificial human-like speeches, which has been used in deepfakes or identity theft attacks. Existing defense mechanisms inject subtle adversarial perturbations into the raw speech audios to mislead the voice synthesis models. However, optimizing the adversarial perturbation not only consumes substantia

Florian Grube, Moritz Kassmann

We prove trace and extension results for Sobolev-type function spaces that are well suited for nonlocal Dirichlet and Neumann problems including those for the fractional $p$-Laplacian. Our results are robust with respect to the order of differentiability. In this sense they are in align with the classical trace and extension theorems.

Jacopo Surace

What would be the consequences if there were fundamental limits to our ability to experimentally explore the world? In this work we seriously consider this question. We assume the existence of statements whose truth value is not experimentally accessible. That is, there is no way, not even in theory, to directly test if these statements are true or false. We

Bogdana Rakova, Roel Dobbe

This paper reframes algorithmic systems as intimately connected to and part of social and ecological systems, and proposes a first-of-its-kind methodology for environmental justice-oriented algorithmic audits. How do we consider environmental and climate justice dimensions of the way algorithmic systems are designed, developed, and deployed? These impacts ar

Yuqi Wang, Jacob A. Macdonald, Katelyn R. Morgan, Danielle Hom

Spleen volumetry is primarily associated with patients suffering from chronic liver disease and portal hypertension, as they often have spleens with abnormal shapes and sizes. However, manually segmenting the spleen to obtain its volume is a time-consuming process. Deep learning algorithms have proven to be effective in automating spleen segmentation, but a

Samuel Judson, Matthew Elacqua, Filip Cano, Timos Antonopoulos

Principled accountability in the aftermath of harms is essential to the trustworthy design and governance of algorithmic decision making. Legal theory offers a paramount method for assessing culpability: putting the agent 'on the stand' to subject their actions and intentions to cross-examination. We show that under minimal assumptions automated reasoning ca

Enrique Alvarado, Qinglan Xia

Classically, Plateau's problem asks to find a surface of the least area with a given boundary $B$. In this article, we investigate a version of Plateau's problem, where the boundary of an admissible surface is only required to partially span $B$. Our boundary data is given by a flat $(m-1)$-chain $B$ and a smooth compactly supported differential $(m-1)$-form

Daniele A. Di Pietro, Marien-Lorenzo Hanot

In this work, following the Discrete de Rham (DDR) paradigm, we develop an arbitrary-order discrete divdiv complex on general polyhedral meshes. The construction rests 1) on discrete spaces that are spanned by vectors of polynomials whose components are attached to mesh entities and 2) on discrete operators obtained mimicking integration by parts formulas. W

Elmira Mirzabeigi, Saeed Mortezazadeh, Rezvan Salehi, Hossein Naderi-Manesh

Knowledge-based potentials were developed to investigate the differentiation of native structures from their decoy sets. This work presents the construction of two different distance-dependent potential energy functions based on two fundamental assumptions using mathematical modeling. Here, a model was developed using basic mathematical methods, and the carb

Ursula Ludacka, Jiali He, Shuyu Qin, Manuel Zahn

Direct electron detectors in scanning transmission electron microscopy give unprecedented possibilities for structure analysis at the nanoscale. In electronic and quantum materials, this new capability gives access to, for example, emergent chiral structures and symmetry-breaking distortions that underpin functional properties. Quantifying nanoscale structur

Xiang Li, Congcong Wen, Yuan Hu, Zhenghang Yuan

The remarkable achievements of ChatGPT and GPT-4 have sparked a wave of interest and research in the field of large language models for Artificial General Intelligence (AGI). These models provide intelligent solutions close to human thinking, enabling us to use general artificial intelligence to solve problems in various applications. However, in remote sens

Ibrahim Buba Garba, Tommaso Morresi, Charles Bouillaguet, Michele Casula

We present a robust reciprocal-space implementation of the temperature-dependent effective potential method. Our implementation can scale easily to large cell and long sampling time. It is interoperable with standard ab-initio molecular dynamics and with Langevin dynamics. We prove that both sampling methods can be efficient and accurate if a thermostat is u

Everaldo M. Bonotto, Alexandre N. Carvalho, Marcelo J. D. Nascimento, Eric B. Santiago

The aim of this paper is to study the robustness of the family of pullback attractors associated to a non-autonomous coupled system of strongly damped wave equations, given by the following evolution system $$\left\{ \begin{array}{lr} u_{tt} - \Delta u + u + \eta(-\Delta)^{1/2}u_t + a_{\epsilon}(t)(-\Delta)^{1/2}v_t = f(u), &(x, t) \in\Omega\times (\tau, \in

O. A. Krohn, K. J. Catani, S. P. Sundar, J. Greenberg

The reaction of the acetylene cation (C2H2+) with acetonitrile (CH3CN) is measured in a linear Paul ion trap coupled to a time-of-flight mass spectrometer. C2H2+ and CH3CN are both noted for their astrochemical abundance and predicted relevance for understanding prebiotic chemistry. The observed primary products are c-C3H3+, C3H4+ and C2NH3+. The latter two

Yinan Liu, Xinyu Dong, Weimin Lyu, Richard N. Rosenthal

Class imbalance problems widely exist in the medical field and heavily deteriorates performance of clinical predictive models. Most techniques to alleviate the problem rebalance class proportions and they predominantly assume the rebalanced proportions should be a function of the original data and oblivious to the model one uses. This work challenges this pr

Philip A. Ernst, Hongwei Mei, Goran Peskir

Consider the motion of a Brownian particle in $n$ dimensions, whose coordinate processes are standard Brownian motions with zero drift initially, and then at some random/unobservable time, exactly $k$ of the coordinate processes get a (known) non-zero drift permanently. Given that the position of the Brownian particle is being observed in real time, the prob

Alfredo Cano, David Flores-Flores, Eric Hernández-Martínez

It is well known that Sobolev embeddings can be improved in the presence of symmetries. In this article, we considere the situation in which given a domain $\Omega=\Omega_1 \times \Omega_2$ in $\mathbb{R}^N$ with a cylindrical symmetry, and acting a group $G$ in $\Omega_1$, for this situation it is shown that the critical Sobolev exponent increases in the ca

Miranda Caputo, Archana Soam, B-G Andersson, Remy Dennis

We used high-resolution [C II] 158 $\mu$m mapping of two nebulae IC 59 and IC 63 from SOFIA/upGREAT in conjunction with ancillary data on the gas, dust, and polarization to probe the kinematics, structure, and magnetic properties of their photo-dissociation regions (PDRs). The nebulae are part of the Sh 2-185 H II region illuminated by the B0 IVe star $\gamm

Yung-Fu Chen, Kenneth W. Parker, Anish Arora

Routing in wireless meshes must detour around holes. Extant routing protocols often underperform in minimally connected networks where holes are larger and more frequent. Minimal density networks are common in practice due to deployment cost constraints, mobility dynamics, and/or adversarial jamming. Protocols that use global search to determine optimal path

Ethan Dudley

Necessary and sufficient conditions for the third order Kolmogorov universal scaling flux laws are derived for the stochastically forced incompressible Navier-Stokes equations on the torus in 2d and 3d. This paper rigorously generalizes the result of \cite{bedrossian2019sufficient} to functions which are heavy-tailed in Fourier space or have local finite tim

Pierre-Olivier Parisé, Thomas Ransford

It is known that there exist functions in certain de Branges--Rovnyak spaces whose Taylor series diverge in norm, even though polynomials are dense in the space. This is often proved by showing that the sequence of Taylor partial sums is unbounded in norm. In this note we show that it can even happen that the Taylor partial sums tend to infinity in norm. We

Johannes Nokelainen, Matthew E. Matzelle, Christopher Lane, Nabil Atlam

Evidence is growing that a second dome of high-$T_\mathrm{c}$ superconductivity can be accessed in the cuprates by increasing the doping beyond the first dome. Here we use \emph{ab initio} methods without invoking any free parameters, such as the Hubbard $U$, to reveal that pressure could turn YBa$_2$Cu$_3$O$_7$ into an ideal candidate for second-dome-superc

Zhanrui Cai

Model selection is critical in the modern statistics and machine learning community. However, most existing works do not apply to heavy-tailed data, which are commonly encountered in real applications, such as the single-cell multiomics data. In this paper, we propose a rank-sum based approach that outputs a confidence set containing the optimal model with g

Leila Badakhshian, Victor Falgas-Ravry, Maryam Sharifzadeh

Let $G$ be an $r$-partite graph such that the edge density between any two parts is at least $\alpha$. How large does $\alpha$ need to be to guarantee that $G$ contains a connected transversal, that is, a tree on $r$ vertices meeting each part in one vertex? And what if instead we want to guarantee the existence of a Hamiltonian transversal? In this paper we

Hélène Esnault

This small text was written for the AMS Notices. It is a survey of integrality properties of complex local systems, where I tried to single out one example which is not entirely explicit in the literature. The focus is on the obstruction it yields for a finitely presented group to be the topological fundamental group of a connected smooth quasi-projective co

Peng Li, Tianxiang Sun, Qiong Tang, Hang Yan

Large language models (LLMs) pre-trained on massive corpora have demonstrated impressive few-shot learning ability on many NLP tasks. A common practice is to recast the task into a text-to-text format such that generative LLMs of natural language (NL-LLMs) like GPT-3 can be prompted to solve it. However, it is nontrivial to perform information extraction (IE

Krzysztof Jodłowski

A number of extensions of the Standard Model predict the existence of new light, weakly-coupled particles that couple to the visible sector through higher-dimensional operators containing one or two photons, suppressed by a high new physics scale, and thus have long lifetimes. In this work, we study the prospects for detecting three $\sim\,$sub-GeV such long

Alessandro Loni, Paolo Serra, Marc Sarzi, Gyula I. G. Józsa

We study the evolutionary path of the Fornax cluster galaxy NGC$~$1436, which is known to be currently transitioning from a spiral into a lenticular morphology. This galaxy hosts an inner star-forming disc and an outer quiescent disc, and we analyse data from the MeerKAT Fornax Survey, ALMA, and the Fornax3D survey to study the interstellar medium and the st

Daniel Flam-Shepherd, Alán Aspuru-Guzik

Language models are powerful tools for molecular design. Currently, the dominant paradigm is to parse molecular graphs into linear string representations that can easily be trained on. This approach has been very successful, however, it is limited to chemical structures that can be completely represented by a graph -- like organic molecules -- while material

Hanfa Song, Tyler Zimmerling, Bo Leng, Vien Van

Conventional topological photonic insulators typically have narrow nontrivial band gaps truncated by broad dispersive bulk bands, resulting in limited edge mode transmission bandwidths that can be exploited for potential applications. Here we propose and demonstrate the first Floquet-Lieb topological photonic insulator with all flat bands which can support c

Chen Bao, Helin Xu, Yuzhe Qin, Xiaolong Wang

To enable general-purpose robots, we will require the robot to operate daily articulated objects as humans do. Current robot manipulation has heavily relied on using a parallel gripper, which restricts the robot to a limited set of objects. On the other hand, operating with a multi-finger robot hand will allow better approximation to human behavior and enabl

Maria Waheed, Michael Milford, Xiaojun Zhai, Klaus McDonald-Maier

Visual Place Recognition has recently seen a surge of endeavours utilizing different ensemble approaches to improve VPR performance. Ideas like multi-process fusion or switching involve combining different VPR techniques together, utilizing different strategies. One major aspect often common to many of these strategies is voting. Voting is widely used in man

A. C. Aguilar, M. N. Ferreira, J. Papavassiliou, L. R. Santos

We present a detailed exploration of certain outstanding features of the transversely-projected three-gluon vertex, using the corresponding Schwinger-Dyson equation in conjunction with key results obtained from quenched lattice simulations. The main goal of this study is the scrutiny of the approximate property denominated ``planar degeneracy'', unveiled whe

Max Brinkmann, Michele Cicoli, Pietro Zito

Starobinsky inflation is currently one of the best models concerning agreement with cosmological data. Despite this observational success, it is still lacking a robust embedding into a UV complete theory. Previous efforts to derive Starobinsky inflation from string theory have been based on the derivation of higher derivative curvature terms from the low-ene

Alexandre Martin, Nicolas Vaskou

We show that the class of large-type Artin groups is invariant under isomorphism, in stark contrast with the corresponding situation for Coxeter groups. We obtain this result by providing a purely algebraic characterisation of large-type Artin groups (i.e. independent of the presentation graph). As a corollary, we completely describe the Artin groups isomorp

S. Bolaños, R. Smets, C. Courtois, N. Blanchot

The meeting of astrophysical plasmas and their magnetic fields creates many reconnection sites. We experimentally compare the reconnection rate of laser-driven magnetic reconnection when it takes place at a single site and multiple sites. For a single site, where the ram pressure dominates the magnetic pressure, the measured reconnection rate exceeds the wel

David Korda, Tomáš Kohout, Kateřina Flanderová, Jean-Baptiste Vincent

Context. Upcoming space missions will provide us with surface-resolved NEA reflectance spectra. Neural networks are useful tools for analysing reflectance spectra and determining material composition with high precision and low processing time. Aims. We applied neural-network models on disk-resolved spectra of the Eros and Itokawa asteroids observed by the N

Jean-Baptiste Burie, Arnaud Ducrot, Quentin Griette

We investigate the long-time dynamics of a SIR epidemic model with infinitely many pathogen variants infecting a homogeneous host population. We show that the basic reproduction number $\mathcal{R}_0$ of the pathogen can be defined in that case and corresponds to a threshold between the persistence ($\mathcal{R}_0>1$) and the extinction ($\mathcal{R}_0\leq 1

Sapna Mishra, Sowgat Muzahid, Sayak Dutta, Raghunathan Srianand

We present the first detection of cool, neutral gas in the outskirts of low-z galaxy clusters using a statistically significant sample of 3191 z$\approx$0.2 background quasar - foreground cluster pairs by cross-matching the Hubble Spectroscopic Legacy Archive quasar catalog with optically- and SZ-selected cluster catalogs. The median cluster mass of our samp

Peter Gao, Anjali A. A. Piette, Maria E. Steinrueck, Matthew C. Nixon

The near-infrared transmission spectrum of the warm sub-Neptune exoplanet GJ 1214 b has been observed to be flat and featureless, implying a high metallicity atmosphere with abundant aerosols. Recent JWST MIRI LRS observations of a phase curve of GJ 1214 b showed that its transmission spectrum is flat out into the mid-infrared. In this paper, we use the comb

Nils Wittenburg, Pavel Kroupa, Indranil Banik, Graeme Candlish

We present the first hydrodynamical cosmological simulations in the $\nu$HDM framework based on Milgromian dynamics (MOND) with light (11~eV) sterile neutrinos. $\nu$HDM can explain the expansion history, CMB anisotropies, and galaxy cluster dynamics similarly to standard cosmology while preserving MOND's successes on galaxy scales, making this the most cons

Tin Long Sunny Wong, Lars Bildsten

The detonation of an overlying helium layer on a $0.8-1.1\,\mathrm{M}_{\odot}$ carbon-oxygen (CO) white dwarf (WD) can detonate the CO WD and create a thermonuclear supernova (SN). Many authors have recently shown that when the mass of the He layer is low ($\lesssim 0.03\,\mathrm{M}_{\odot}$), the ashes from its detonation minimally impact the spectra and li

Simon Pfeifer, Aurélien Valade, Stefan Gottlöber, Yehuda Hoffman

The aim of cosmological simulations is to reproduce the properties of the observed Universe, serving as tools to test structure and galaxy formation models. Constrained simulations of our local cosmological region up to a few hundred Mpc/h , the local Universe, are designed to reproduce the actual cosmic web of structures as observed. A question that often a

Florent Baume, José Calderón-Infante

Distances in the conformal manifold, the space of CFTs related by marginal deformations, can be measured in terms of the Zamolodchikov metric. Part of the CFT Distance Conjecture posits that points in this manifold where part of the spectrum becomes free, called higher-spin points, can only be at infinite distance from the interior. There, an infinite tower

Sean L. Dougherty, C. M. Harrison, Dale D. Kocevski, D. J. Rosario

Observations of the nearby universe reveal an increasing fraction of active galactic nuclei (AGN) with decreasing projected separation for close galaxy pairs, relative to control galaxies. This implies galaxy interactions play a role in enhancing AGN activity. However, the picture at higher redshift is less established, partly due to limited spectroscopic re

Kyriakos Destounis, Federico Angeloni, Massimo Vaglio, Paolo Pani

General relativity predicts that black holes are described by the Kerr metric, which has integrable geodesics. This property is crucial to produce accurate waveforms from extreme-mass-ratio inspirals. Astrophysical environments, modifications of gravity and new fundamental fields may lead to nonintegrable geodesics, inducing chaotic effects. We study geodesi

Gabriela Sato-Polito, Marc Kamionkowski

Anisotropies in the nanohertz gravitational-wave background are a compelling next target for pulsar timing arrays (PTAs). Measurements or informative upper limits to the anisotropies are expected in the near future and can offer important clues about the origin of the background and the properties of the sources. Given that each source is expected (in the si

Markus Dierigl, Jonathan J. Heckman, Miguel Montero, Ethan Torres

R7-branes are a class of recently discovered non-supersymmetric real codimension-two duality defects in type IIB string theory predicted by the Swampland Cobordism Conjecture. For type IIB realizations of 6D SCFTs with $\mathcal{N} = (2,0)$ supersymmetry, wrapping an R7-brane "at infinity" leads to a topological operator associated with a zero-form charge co

Taro V. Brown, Karol Kampf, Umut Oktem, Shruti Paranjape

In this letter, we study tree-level scattering amplitudes of scalar particles in the context of effective field theories. We use tools similar to the soft bootstrap to build an ansatz for cyclically ordered amplitudes and impose the Bern-Carrasco-Johansson (BCJ) relations as a constraint. We obtain a set of BCJ-satisfying amplitudes as solutions to our proce

James Paul Mason, Alexandra Werth, Colin G. West, Allison A. Youngblood

Flare frequency distributions represent a key approach to addressing one of the largest problems in solar and stellar physics: determining the mechanism that counter-intuitively heats coronae to temperatures that are orders of magnitude hotter than the corresponding photospheres. It is widely accepted that the magnetic field is responsible for the heating, b

Robin Yunfei Wen, Achim Kempf

We show that around any $m$-partite product state $\rho_{\rm prod}=\rho_1\otimes...\otimes\rho_m$ of full rank (that is ${\rm det}(\rho_{\rm prod})\neq 0)$, there exists a finite-sized closed ball of separable states centered around $\rho_{\rm prod}$ whose radius is $\beta:=2^{1-m/2}\lambda_{\rm min}(\rho_{\rm prod})$. Here, $\lambda_{\rm min}(\rho_{\rm prod

Kazuki Ikeda, Dmitri E. Kharzeev, Shuzhe Shi

The chiral magnetic wave (CMW) is a macroscopic quantum phenomenon that arises due to the mixing of the electric and chiral charge oscillations induced by the chiral anomaly. In this study we report the first quantum simulation (on classical hardware) of the real-time dynamics of CMWs in Schwinger model. Our quench protocol is the following: at $t=0$ we sudd

Asher Berlin, Raffaele Tito D'Agnolo, Sebastian A. R. Ellis, Jury I. Radkovski

We discuss a novel detection technique for millicharged dark matter that makes use of existing light-shining-through-wall (LSW) experiments searching for massive dark photons. Since millicharged particles interact with both the visible and dark sectors, a small background of such particles enables the search for visible signals even in the limit of a massles

Rhine Samajdar, R. N. Bhatt

The search for ferromagnetism in the Hubbard model has been a problem of outstanding interest since Nagaoka's original proposal in 1966. Recent advances in quantum simulation have today enabled the study of tunable doped Hubbard models in ultracold atomic systems. Employing large-scale density-matrix renormalization group calculations, we establish the exist

Oleg Lebedev, Yann Mambrini, Jong-Hyun Yoon

We study inflationary models based on a non-minimal coupling of a singlet scalar to gravity, focussing on the preheating dynamics and the unitarity issues in this regime. If the scalar does not have significant couplings to other fields, particle production after inflation is far less efficient than that in Higgs inflation. As a result, unitarity violation a

Asher Berlin, Tanner Trickle

Detection of axion dark matter heavier than a meV is hindered by its small wavelength, which limits the useful volume of traditional experiments. This problem can be avoided by directly detecting in-medium excitations, whose $\sim \text{meV} - \text{eV}$ energies are decoupled from the detector size. We show that for any target inside a magnetic field, the a

Francesco Calura, Marco Palla, Laura Morselli, Emanuele Spitoni

We introduce a new, multi-zone chemical evolution model of the DustPedia galaxy M74, calibrated by means of MCMC methods. We take into account the observed stellar and gas density profiles and use Bayesian analysis to constrain two fundamental parameters characterising the gas accretion and star formation timescale, i.e. the infall timescale tau and the SF e

Xuejian Shen, Mark Vogelsberger, Michael Boylan-Kolchin, Sandro Tacchella

JWST observations have revealed a population of galaxies bright enough that potentially challenge standard galaxy formation models in the $\Lambda$CDM cosmology. Using a minimal empirical framework, we investigate the influence of variability on the rest-frame ultra-violet (UV) luminosity function (UVLF) of galaxies at $z\geq 9$. Our study differentiates bet

Paul Romatschke

Traditionally, scalar $\phi^4$ theory in four dimensions is thought to be quantum trivial in the continuum. This tradition is apparently well grounded both in physics arguments and mathematical proofs. Digging into the proofs one finds that they do not actually cover all physically meaningful situations, in particular the case of multi-component fields and n

Zhuangfei Wang, Seyed Hamidreza Mirpoorian, Levon Pogosian, Alessandra Silvestri

We present a new version of MGCAMB, a patch for the Einstein-Boltzmann solver CAMB for cosmological tests of gravity. New features include a new cubic-spline parameterization allowing for a simultaneous reconstruction of $\mu$, $\Sigma$ and the dark energy density fraction $\Omega_X$ as functions of redshift, the option to work with a direct implementation o

Prakash Panangaden, Sahand Rezaei-Shoshtari, Rosie Zhao, David Meger

Reinforcement learning (RL) on high-dimensional and complex problems relies on abstraction for improved efficiency and generalization. In this paper, we study abstraction in the continuous-control setting, and extend the definition of Markov decision process (MDP) homomorphisms to the setting of continuous state and action spaces. We derive a policy gradient

Rohit Girdhar, Alaaeldin El-Nouby, Zhuang Liu, Mannat Singh

We present ImageBind, an approach to learn a joint embedding across six different modalities - images, text, audio, depth, thermal, and IMU data. We show that all combinations of paired data are not necessary to train such a joint embedding, and only image-paired data is sufficient to bind the modalities together. ImageBind can leverage recent large scale vi

Swarnim Shirke, Suprovo Ghosh, Debarati Chatterjee, Laura Sagunski

In this work, we perform the first systematic investigation of effects of the presence of dark matter on $r$-mode oscillations in neutron stars (NSs). Using a self-interacting dark matter (DM) model based on the neutron decay anomaly and a hadronic model obtained from the posterior distribution of a recent Bayesian analysis, we impose constraints on the DM s

S. Gerber, H. Markowitz, P. Ernst, Y. Miao

In this brief note, we prove that both forms of the Gerber statistic introduced in Gerber et al. (2022) are positive semi-definite.

Zhaoyang Liu, Yinan He, Wenhai Wang, Weiyun Wang

We present an interactive visual framework named InternGPT, or iGPT for short. The framework integrates chatbots that have planning and reasoning capabilities, such as ChatGPT, with non-verbal instructions like pointing movements that enable users to directly manipulate images or videos on the screen. Pointing (including gestures, cursors, etc.) movements ca

R. Kenny Jones, Paul Guerrero, Niloy J. Mitra, Daniel Ritchie

Programs are an increasingly popular representation for visual data, exposing compact, interpretable structure that supports manipulation. Visual programs are usually written in domain-specific languages (DSLs). Finding "good" programs, that only expose meaningful degrees of freedom, requires access to a DSL with a "good" library of functions, both of which

Bryan Zhao, Andrew Zhang, Blake Watson, Gillian Kearney

Moderation of social media content is currently a highly manual task, yet there is too much content posted daily to do so effectively. With the advent of a number of multimodal models, there is the potential to reduce the amount of manual labor for this task. In this work, we aim to explore different models and determine what is most effective for the Hatefu

Jiajie Chen, Thomas Y. Hou

This is Part II of our paper in which we prove finite time blowup of the 2D Boussinesq and 3D axisymmetric Euler equations with smooth initial data of finite energy and boundary. In Part I of our paper \cite{ChenHou2023a}, we establish an analytic framework to prove nonlinear stability of an approximate self-similar blowup profile using a combination of weig

Dharm Veer

In this article, we prove that if a Hibi ring satisfies property $N_2$, then its Segre product with a polynomial ring in finitely many variables also satisfies property $N_2$. When the polynomial ring is in two variables, we also prove the above statement for $N_3$. Moreover, we study the minimal Koszul relations of the second syzygy module of Hibi rings.

Jimmy Wu, Rika Antonova, Adam Kan, Marion Lepert

For a robot to personalize physical assistance effectively, it must learn user preferences that can be generally reapplied to future scenarios. In this work, we investigate personalization of household cleanup with robots that can tidy up rooms by picking up objects and putting them away. A key challenge is determining the proper place to put each object, as

V. Stepanyan, A. E. Allahverdyan

Quantum mechanics does not provide any ready recipe for defining energy density in space, since the energy and coordinate do not commute. To find a well-motivated energy density, we start from a possibly fundamental, relativistic description for a spin-$\frac{1}{2}$ particle: Dirac's equation. Employing its energy-momentum tensor and going to the non-relativ

Daniella Bar-Lev, Omer Sabary, Ryan Gabrys, Eitan Yaakobi

Although the expenses associated with DNA sequencing have been rapidly decreasing, the current cost of sequencing information stands at roughly $120/GB, which is dramatically more expensive than reading from existing archival storage solutions today. In this work, we aim to reduce not only the cost but also the latency of DNA storage by initiating the study

Joseph Dorta, Samantha Jarvis, Nelson Niu

Recently, there has been renewed interest in the theory and applications of de Paiva's dialectica categories and their relationship to the category of polynomial functors. Both fall under the theory of generalized polynomial categories, which are free coproduct completions of free product completions of (monoidal) categories. Here we extend known monoidal st

Md Ahasanuzzaman, Gustavo A. Oliva, Ahmed E. Hassan

Code review is a key element of quality assurance in software development. Determining the right reviewer for a given code change requires understanding the characteristics of the changed code, identifying the skills of each potential reviewer (expertise profile), and finding a good match between the two. To facilitate this task, we design a code reviewer re

Mark M. Bailey

Where is everybody? This phrase distills the foreboding of what has come to be known as the Fermi Paradox - the disquieting idea that, if extraterrestrial life is probable in the Universe, then why have we not encountered it? This conundrum has puzzled scholars for decades, and many hypotheses have been proposed suggesting both naturalistic and sociological

Long Wu, Xunyuan Yin, Lei Pan, Jinfeng Liu

The close integration of increasing operating units into an integrated energy system (IES) results in complex interconnections between these units. The strong dynamic interactions create barriers to designing a successful distributed coordinated controller to achieve synergy between all the units and unlock the potential for grid response. To address these c

Mikhail Papkov, Pavel Chizhov, Leopold Parts

Self-supervised image denoising implies restoring the signal from a noisy image without access to the ground truth. State-of-the-art solutions for this task rely on predicting masked pixels with a fully-convolutional neural network. This most often requires multiple forward passes, information about the noise model, or intricate regularization functions. In

Alexander Belles, Marjorie Decleir, William P. Bowman, Lea M. Z. Hagen

We present Swift/Ultraviolet Optical Telescope (UVOT) integrated light photometry of the Spitzer Infrared Nearby Galaxies Survey (SINGS) and the Key Insights on Nearby Galaxies: A Far-Infrared Survey with Herschel (KINGFISH) samples of nearby galaxies. Combining the Swift/UVOT data with archival photometry, we investigate a variety of dust attenuation curves

Mohamed Nomeir, Sajani Vithana, Sennur Ulukus

We consider a special case of $X$-secure $T$-private information retrieval (XSTPIR), where the security requirement is \emph{asymmetric} due to possible missing communication links between the $N$ databases considered in the system. We define the problem with a communication matrix that indicates all possible communications among the databases, and propose a

Wei-Hung Weng, Sebastien Baur, Mayank Daswani, Christina Chen

Cardiovascular diseases (CVDs) are responsible for a large proportion of premature deaths in low- and middle-income countries. Early CVD detection and intervention is critical in these populations, yet many existing CVD risk scores require a physical examination or lab measurements, which can be challenging in such health systems due to limited accessibility

Candace Savonen, Carrie Wright, Ava M. Hoffman, Elizabeth M. Humphries

Data science education provides tremendous opportunities but remains inaccessible to many communities. Increasing the accessibility of data science to these communities not only benefits the individuals entering data science, but also increases the field's innovation and potential impact as a whole. Education is the most scalable solution to meet these needs

Isabella R. Graf, Benjamin B. Machta

In various biological systems information from many noisy molecular receptors must be integrated into a collective response. A striking example is the thermal imaging organ of pit vipers. Single nerve fibers in the organ reliably respond to mK temperature increases, a thousand times more sensitive than their molecular sensors, thermo-TRP ion channels. Here,

Reda Chhaibi, Fabrice Gamboa, Slim Kammoun, Mauricio Velasco

The estimation of large covariance matrices has a high dimensional bias. Correcting for this bias can be reformulated via the tool of Free Probability Theory as a free deconvolution. The goal of this work is a computational and statistical resolution of this problem. Our approach is based on complex-analytic methods methods to invert $S$-transforms. In parti

Andrea Di Biagio, Richard Howl, Časlav Brukner, Carlo Rovelli

Locality is a central notion in modern physics, but different disciplines understand it in different ways. Quantum field theory focuses on relativistic locality, based on spacetime regions, while quantum information theory focuses circuit locality, based on the notion of subsystems. Here, we investigate how spacetime and subsystem locality are related in the

Jianyi Zhang, Saeed Vahidian, Martin Kuo, Chunyuan Li

While "instruction-tuned" generative large language models (LLMs) have demonstrated an impressive ability to generalize to new tasks, the training phases heavily rely on large amounts of diverse and high-quality instruction data (such as ChatGPT and GPT-4). Unfortunately, acquiring high-quality data, especially when it comes to human-written data, can pose s

Dmitry V. Strunin, Boris A. Malomed

We consider phase transitions, in the form of spontaneous symmetry breaking (SSB) bifurcations of solitons, in dual-core couplers with fractional diffraction and cubic self-focusing acting in each core, characterized by Levy index $\alpha$. The system represents linearly-coupled optical waveguides with the fractional paraxial diffraction or group-velocity di

Hongrui Chen, Jihao Long, Lei Wu

We consider the problem of learning functions within the $\mathcal{F}_{p,\pi}$ and Barron spaces, which play crucial roles in understanding random feature models (RFMs), two-layer neural networks, as well as kernel methods. Leveraging tools from information-based complexity (IBC), we establish a dual equivalence between approximation and estimation, and then

F. J. Rubio, J. A. Espindola, J. A. Montoya

We study parametric inference on a rich class of hazard regression models in the presence of right-censoring. Previous literature has reported some inferential challenges, such as multimodal or flat likelihood surfaces, in this class of models for some particular data sets. We formalize the study of these inferential problems by linking them to the concepts

Christos Theodoropoulos, Natasha Mulligan, Thaddeus Stappenbeck, Joao Bettencourt-Silva

Knowledge graphs (KGs) are a popular way to organise information based on ontologies or schemas and have been used across a variety of scenarios from search to recommendation. Despite advances in KGs, representing knowledge remains a non-trivial task across industries and it is especially challenging in the biomedical and healthcare domains due to complex in

Michael Baake, Franz Gähler, Lorenzo Sadun

The recently discovered Hat tiling admits a 4-dimensional family of shape deformations, including the 1-parameter family already known to yield alternate monotiles. The continuous hulls resulting from these tilings are all topologically conjugate dynamical systems, and hence have the same dynamics and topology. We construct and analyze a self-similar element

Niklas Jöckel

We study the dispersion-generalized Benjamin-Ono equation in the periodic setting. This equation interpolates between the Benjamin-Ono equation ($\alpha=1$) and the viscous Burgers' equation ($\alpha=0$). We obtain local well-posedness in $H^s$ for $s>3/2-\alpha$ and $\alpha\in(0,1)$ by using the short-time Fourier restriction method.

Christopher Augustine

The research assessed the role of social media in the unfolding of the EndSARS demonstrations in Nigeria. The study was necessary given the persistent call by governments for the strict regulation of social medium platforms. This is given governments' claim that social media is being misused. The study, however, reveals that social media use is determined by

Marianne Akian, Xavier Allamigeon, Stéphane Gaubert, Sergei Sergeev

We study the tropical analogue of the notion of polar of a cone, working over the semiring of tropical numbers with signs. We characterize the cones which arise as polars of sets of tropically nonnegative vectors by an invariance property with respect to a tropical analogue of Fourier-Motzkin elimination. We also relate tropical polars with images by the non

Alistair J. Brash, Jake Iles-Smith

Solid-state emitters such as epitaxial quantum dots have emerged as a leading platform for efficient, on-demand sources of indistinguishable photons, a key resource for many optical quantum technologies. To maximise performance, these sources normally operate at liquid helium temperatures ($\sim 4~\mathrm{K}$), introducing significant size, weight and power

Johanna Casado, Beatriz García

Data analysis in space sciences has been performed exclusively visually for years, despite the fact that the largest amount of data belongs to non-visible portions of the electromagnetic spectrum. This, on the one hand, limits the study of the unknown to the current resolution possibilities of the screens, and on the other hand, it excludes a group of people