November 2022 arXiv papers — page 147

Taeho Ryu, Rosalba Perna, Ruediger Pakmor, Jing-Ze Ma

Strong dynamical interactions among stars and compact objects are expected in a variety of astrophysical settings, such as star clusters and the disks of active galactic nuclei. Via a suite of 3D hydrodynamics simulations using the moving-mesh code AREPO, we investigate the formation of transient phenomena and their properties in close encounters between an

Xuhai Xu, Han Zhang, Yasaman Sefidgar, Yiyi Ren

Recent research has demonstrated the capability of behavior signals captured by smartphones and wearables for longitudinal behavior modeling. However, there is a lack of a comprehensive public dataset that serves as an open testbed for fair comparison among algorithms. Moreover, prior studies mainly evaluate algorithms using data from a single population wit

Zahra Zanjani Foumani, Mehdi Shishehbor, Amin Yousefpour, Ramin Bostanabad

Bayesian optimization (BO) is increasingly employed in critical applications such as materials design and drug discovery. An increasingly popular strategy in BO is to forgo the sole reliance on high-fidelity data and instead use an ensemble of information sources which provide inexpensive low-fidelity data. The overall premise of this strategy is to reduce t

Jonathan G. Raybin, Rebecca B. Wai, Naomi S. Ginsberg

We examine the organization and dynamics of binary colloidal monolayers composed of micron-scale silica particles interspersed with smaller-diameter silica particles that serve as minority component impurities. These binary monolayers are prepared at the surface of ionic liquid droplets over a range of size ratios ($\sigma=0.16-0.66$) and are studied with lo

Patrick Kaiser, Christoph Kern, David Rügamer

Both industry and academia have made considerable progress in developing trustworthy and responsible machine learning (ML) systems. While critical concepts like fairness and explainability are often addressed, the safety of systems is typically not sufficiently taken into account. By viewing data-driven decision systems as socio-technical systems, we draw on

Adam Nik, Ge Zhang, Xingran Chen, Mingyu Li

This paper details our participation in the Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE) workshop @ EMNLP 2022, where we take part in Subtask 1 of Shared Task 3. We approach the given task of event causality detection by proposing a self-training pipeline that follows a teacher-student classifier method. More

Gonzalo Muñoz, Joseph Paat, Álinson S. Xavier

A branch-and-bound (BB) tree certifies a dual bound on the value of an integer program. In this work, we introduce the tree compression problem (TCP): Given a BB tree T that certifies a dual bound, can we obtain a smaller tree with the same (or stronger) bound by either (1) applying a different disjunction at some node in T or (2) removing leaves from T? We

Diego Ortega, Javier Rodríguez-Laguna, Elka Korutcheva

Half of the world population resides in cities and urban segregation is becoming a global issue. One of the best known attempts to understand it is the Schelling model, which considers two types of agents that relocate whenever a transfer rule depending on the neighbor distribution is verified. The main aim of the present study is to broaden our understandin

Alperen Gündogan, Akın Badalıoglu, Panagiotis Spapis, Ahmad Awada

One of upcoming mobility enhancements in 5G-Advanced networks is to execute handover based on Layer 1 (L1) measurements using the so called lower layer mobility procedure. In this paper, we provide a system model for lower layer mobility procedure and we evaluate it against existing higher layer mobility procedures, such as baseline and conditional handover,

Alexander Lenz, Jakob Müller, Maria Laura Piscopo, Aleksey V. Rusov

Inspired by the recently observed tensions between the experimental data and the theoretical predictions, based on QCD factorisation, for several colour-allowed non-leptonic $B$-meson decays, we study the potential size of new physics (NP) effects in the decay channels $b \to c \bar{u} d(s)$. Starting from the most general effective Hamiltonian describing th

Yanzeng Zhang, Xian-Zhu Tang

For plasma velocity space instabilities driven by particle distributions significantly deviated from a Maxwellian, weak collisions can damp the instabilities by an amount that is significantly beyond the collisional rate itself. This is attributed to the dual role of collisions that tend to relax the plasma distribution toward a Maxwellian and to suppress th

V. Witzke, H. B. Duehnen, A. I. Shapiro, D. Przybylski

All cool main sequence stars including our Sun are thought to have magnetic fields. Observations of the Sun revealed that even in quiet regions small-scale turbulent magnetic fields are present. Simulations further showed that such magnetic fields affect the subsurface and photospheric structure, and thus the radiative transfer and emergent flux. Since small

Davide D'Angelo, Andrea Zani, Franco Alessandria, Alessandro Andreani

The most discussed topic in direct search for dark matter is arguably the verification of the DAMA claim. In fact, the observed annual modulation of the signal rate in an array of NaI(Tl) detectors can be interpreted as the awaited signature of dark matter interaction. Several experimental groups are currently engaged in the attempt to verify such a game-cha

Ryien Hosseini, Filippo Simini, Austin Clyde, Arvind Ramanathan

The process of screening molecules for desirable properties is a key step in several applications, ranging from drug discovery to material design. During the process of drug discovery specifically, protein-ligand docking, or chemical docking, is a standard in-silico scoring technique that estimates the binding affinity of molecules with a specific protein ta

Oscar López, Özgür Yılmaz

Many empirical studies suggest that samples of continuous-time signals taken at locations randomly deviated from an equispaced grid (i.e., off-the-grid) can benefit signal acquisition, e.g., undersampling and anti-aliasing. However, explicit statements of such advantages and their respective conditions are scarce in the literature. This paper provides some i

Siwen Ding, You Zhang, Zhiyao Duan

Voice anti-spoofing systems are crucial auxiliaries for automatic speaker verification (ASV) systems. A major challenge is caused by unseen attacks empowered by advanced speech synthesis technologies. Our previous research on one-class learning has improved the generalization ability to unseen attacks by compacting the bona fide speech in the embedding space

Daniel Lokshtanov, Fahad Panolan, Saket Saurabh, Jie Xue

We initiate a systematic study of approximation schemes for fundamental optimization problems on disk graphs, a common generalization of both planar graphs and unit-disk graphs. Our main contribution is a general framework for designing efficient polynomial-time approximation schemes (EPTASes) for vertex-deletion problems on disk graphs, which results in EPT

Sadaf Moaveninejad, Andrea Janes, Camillo Porcaro, Luca Barletta

One of the challenges for climbing gyms is to find out popular routes for the climbers to improve their services and optimally use their infrastructure. This problem must be addressed preserving both the privacy and convenience of the climbers and the costs of the gyms. To this aim, a hardware prototype is developed to collect data using accelerometer sensor

Lalit Ghule, Rishikesh Ranade, Jay Pathak

In recent years, Machine learning (ML) techniques developed for Natural Language Processing (NLP) have permeated into developing better computer vision algorithms. In this work, we use such NLP-inspired techniques to improve the accuracy, robustness and generalizability of ML models for simulating transient dynamics. We introduce teacher forcing and curricul

Mohammad Abbasi Eskandari, Seyedeh Sara Ghotb, Mohamed balli, Patrick Fournier

We report a detailed study of the magnetocaloric effect in heterostructures of La2NiMnO6 and La2/3Sr1/3MnO3. The shape, width and magnitude of the temperature dependence of the magnetic entropy change ($\Delta S_{m}$) for these multilayer samples can be tuned and controlled by changing their layout. A large $\Delta S_{m}$ over a wide temperature range which

L. M. de Sá, A. Bernardo, R. R. A. Bachega, L. S. Rocha

Binary population synthesis provides a direct way of studying the effects of different choices of binary evolution models and initial parameter distributions on present-day binary compact merger populations, which can then be compared to empirical properties such as observed merger rates. Samples of zero-age main sequence binaries to be evolved by such codes

Dmitriy Kunisky, Xifan Yu

We prove that the degree 4 sum-of-squares (SOS) relaxation of the clique number of the Paley graph on a prime number $p$ of vertices has value at least $\Omega(p^{1/3})$. This is in contrast to the widely believed conjecture that the actual clique number of the Paley graph is $O(\mathrm{polylog}(p))$. Our result may be viewed as a derandomization of that of

Zhouyuan Huo, Khe Chai Sim, Bo Li, Dongseong Hwang

Self-supervised pre-training of a speech foundation model, followed by supervised fine-tuning, has shown impressive quality improvements on automatic speech recognition (ASR) tasks. Fine-tuning separate foundation models for many downstream tasks are expensive since the foundation model is usually very big. Parameter-efficient fine-tuning methods (e.g. adapt

J. Dabringhausen, M. Fellhauer, S. Mieske

It is well known that Globular cluster systems are different among galaxies. Here we test to which degree these differences remain on the scale of galaxy clusters by comparing the globular clusters (GCs) in optical surveys of the Virgo galaxy cluster (ACSVCS) and the Fornax galaxy cluster (ACSFCS) in Kolmogorov-Smirnoff Tests. Both surveys were obtained with

Olivier de Gaay Fortman

This thesis intends to make a contribution to the theories of algebraic cycles and moduli spaces over the real numbers. In the study of the subvarieties of a projective algebraic variety, smooth over the field of real numbers, the cycle class map between the Chow ring and the equivariant cohomology ring plays an important role. The image of the cycle class m

Ronald Orozco López

In this paper, we study the existence of solutions of the functional difference equations with proportional delay on deformed generalized Fibonacci polynomials via successive approximation method and Bell polynomials. First, we introduce the deformed generalized Fibonacci polynomials and show that the $q$-numbers can be viewed as "bifurcation" of deformed $(

Robert K. Helmeczi, Mucahit Cevik, Savas Yıldırım

A software requirement specification (SRS) document is an essential part of the software development life cycle which outlines the requirements that a software program in development must satisfy. This document is often specified by a diverse group of stakeholders and is subject to continual change, making the process of maintaining the document and detectin

R. Mirek, M. Furman, M. Król, B. Seredyński

We investigate the spin polarization of localized exciton-polariton condensates. We demonstrate the presence of an effective magnetic field leading to the formation of elliptically polarized condensates. We show that this synthetic field has an entirely photonic origin, which we believe is unique for the CdTe-based microcavities. Moreover, the degree of spin

Yuheng Li, Yijun Li, Jingwan Lu, Eli Shechtman

We introduce a new method for diverse foreground generation with explicit control over various factors. Existing image inpainting based foreground generation methods often struggle to generate diverse results and rarely allow users to explicitly control specific factors of variation (e.g., varying the facial identity or expression for face inpainting results

Nicolas Champagnat, Denis Villemonais

We consider periodic Markov chains with absorption. Applying to iterates of this periodic Markov chain criteria for the exponential convergence of conditional distributions of aperiodic absorbed Markov chains, we obtain exponential estimates for the periodic asymptotic behavior of the semigroup of the Markov chain. This implies in particular the exponential

Rafał Meller

We derive a lower bound for moments of random chaoses of order two with coefficients in arbitrary Banach space F generated by independent symmetric random variables with logarithmically concave tails (which is probably two-sided). We also provide two upper bounds for moments of such chaoses when F = L_q. The first is true under the additional subgaussanity a

R. Caciuffo, G. H. Lander, G. van der Laan

Research on actinide materials, both basic and applied, has been greatly advanced by the general techniques available from high-intensity photon beams from x-ray synchrotron sources. The most important single reason is that such x-ray sources can work with minute (e.g., microgram) samples, and at this level, the radioactive hazards of actinides are much redu

Aditya Bhaskara, Sreenivas Gollapudi, Sungjin Im, Kostas Kollias

We consider the classic online learning and stochastic multi-armed bandit (MAB) problems, when at each step, the online policy can probe and find out which of a small number ($k$) of choices has better reward (or loss) before making its choice. In this model, we derive algorithms whose regret bounds have exponentially better dependence on the time horizon co

Mariana Lima, Niall T. Macpherson, Dmitry Melnikov, Luis Ypanaqué

There has been considerable recent interest in type II string compactifications on AdS$_3\times$S$^3\times$M$_{4}$ due to both new progress in the AdS$_3$/CFT$_2$ correspondence and an independent search for new ${\cal N}=(4,0)$ supergravity solutions. In this work we report a new family of small ${\cal N}=(4,0)$ preserving warped AdS$_3\times$S$^3\times $CY

M. Jorge Cardoso, Wenqi Li, Richard Brown, Nic Ma

Artificial Intelligence (AI) is having a tremendous impact across most areas of science. Applications of AI in healthcare have the potential to improve our ability to detect, diagnose, prognose, and intervene on human disease. For AI models to be used clinically, they need to be made safe, reproducible and robust, and the underlying software framework must b

German Espinosa, Gabrielle E. Wink, Alexander T. Lai, Daniel A. Dombeck

Planning is an extraordinary ability in which the brain imagines and then enacts evaluated possible futures. Using traditional planning models, computer scientists have attempted to replicate this capacity with some level of success but ultimately face a reoccurring limitation: as the plan grows in steps, the number of different possible futures makes it int

Yandong Bai, Pedro P. Cortés, Reza Naserasr, Daniel A. Quiroz

For a graph $G=(V,E)$, its exact-distance square, $G^{[\sharp 2]}$, is the graph with vertex set $V$ and with an edge between vertices $x$ and $y$ if and only if $x$ and $y$ have distance (exactly) $2$ in $G$. The graph $G$ is an exact-distance square root of $G^{[\sharp 2]}$. We give a characterization of graphs having an exact-distance square root, our cha

Jia Meng, Somasekhara Goud Sontti, Xuehua Zhang

As the most complex and heaviest component in bitumen, asphaltene precipitation induced by solvent dilution is important in oil sands extraction to remove solids and water from bitumen froth through dilution by paraffinic solvents. This review will compare asphaltene precipitation to dilution-induced solvent shifting in aqueous systems via the ouzo effect. W

Joseph O. Indekeu, Kenichiro Koga

The dihedral contact angles between interfaces in three-fluid-phase equilibria must be continuous functions of the bulk thermodynamic fields. This general argument, which we propose, predicts a nonwetting gap in the phase diagram, challenging the common belief in "critical-point wetting", even for short-range forces. A demonstration is provided by exact solu

Tajuddin Manhar Mohammed, Lakshmanan Nataraj, Satish Chikkagoudar, Shivkumar Chandrasekaran

The number of malware is constantly on the rise. Though most new malware are modifications of existing ones, their sheer number is quite overwhelming. In this paper, we present a novel system to visualize and map millions of malware to points in a 2-dimensional (2D) spatial grid. This enables visualizing relationships within large malware datasets that can b

Hadi Salman, Caleb Parks, Shi Yin Hong, Justin Zhan

Channel Attention reigns supreme as an effective technique in the field of computer vision. However, the proposed channel attention by SENet suffers from information loss in feature learning caused by the use of Global Average Pooling (GAP) to represent channels as scalars. Thus, designing effective channel attention mechanisms requires finding a solution to

Jason Vander Woude, Peter Dixon, A. Pavan, Jamie Radcliffe

Rounding has proven to be a fundamental tool in theoretical computer science. By observing that rounding and partitioning of $\mathbb{R}^d$ are equivalent, we introduce the following natural partition problem which we call the {\em secluded hypercube partition problem}: Given $k\in \mathbb{N}$ (ideally small) and $\epsilon>0$ (ideally large), is there a part

Tianle Wang, Daniel E. Parker, Tomohiro Soejima, Johannes Hauschild

When the two layers of a twisted moir\'e system are subject to different degrees of strain, the effect is amplified by the inverse twist angle, e.g., by a factor of 50 in magic angle twisted bilayer graphene (TBG). Samples of TBG typically have heterostrains of 0.1-0.7%, increasing the bandwidth of the "flat'' bands by as much as tenfold, placing TBG in an i

Gabriele Loli, Giancarlo Sangalli, Paolo Tesini

We propose an innovative isogeometric space-time method for the heat equation, with smooth splines approximation in both space and time. To enhance the stability of the method we add a stabilizing term, based on a linear combination of high-order artificial diffusions. This term is designed in order to make the linear system lower block-triangular, that is,

Johann Ostmeyer

Suzuki-Trotter decompositions of exponential operators like $\exp(Ht)$ are required in almost every branch of numerical physics. Often the exponent under consideration has to be split into more than two operators $H=\sum_k A_k$, for instance as local gates on quantum computers. We demonstrate how highly optimised schemes originally derived for exactly two op

Elisa Tengan, Thomas Dietzen, Santiago Ruiz, Mansour Alkmim

A method is proposed for performing speech enhancement using ego-noise references with a microphone array embedded in an unmanned aerial vehicle (UAV). The ego-noise reference signals are captured with microphones located near the UAV's propellers and used in the prior knowledge multichannel Wiener filter (PK-MWF) to obtain the speech correlation matrix esti

Sivaguru Ravisankar, Samriddho Roy

The Friedrichs operator of a domain (in $\mathbb{C}^n$) is closely related to its Bergman projection and encodes crucial information (geometric, quadrature, potential theoretic etc.) about the domain. We show that the Friedrichs operator of a domain has rank one if the domain can be covered by a circular domain via a proper holomorphic map of finite multipli

Chris Heunen, Andre Kornell, Nesta van der Schaaf

The category of Hilbert spaces and linear contractions is characterised by elementary categorical properties that do not refer to probabilities, complex numbers, norm, continuity, convexity, or dimension.

Yulu Jin, Lifeng Lai

In this paper, we take a first step towards answering the question of how to design fair machine learning algorithms that are robust to adversarial attacks. Using a minimax framework, we aim to design an adversarially robust fair regression model that achieves optimal performance in the presence of an attacker who is able to add a carefully designed adversar

Timothy Riley

We exhibit exponentially distorted subgroups in $\mathbb{Z} \wr ( \mathbb{Z} \wr \mathbb{Z} )$ and $\mathbb{Z} \wr F_2$.

Seock-Hwan Noh, Junsang Park, Dahoon Park, Jahyun Koo

When training early-stage deep neural networks (DNNs), generating intermediate features via convolution or linear layers occupied most of the execution time. Accordingly, extensive research has been done to reduce the computational burden of the convolution or linear layers. In recent mobile-friendly DNNs, however, the relative number of operations involved

Salvatore Tirone, Raffaele Salvia, Stefano Chessa, Vittorio Giovannetti

We present a theoretical analysis of the energy recovery efficiency for quantum batteries composed of many identical quantum cells undergoing noise. While the possibility of using quantum effects to speed up the charging processes of batteries have been vastly investigated, In order to traslate these ideas into working devices it is crucial to assess the sta

Thierry N. Kaldenbach, Matthias Heller, Gernot Alber, Vladimir M. Stojanovic

Motivated by the revitalized interest in the digital simulation of medium- and high-energy physics phenomena, we investigate the dynamics following a Yukawa-interaction quench on IBM Q. Adopting the zero-dimensional version of the scalar Yukawa-coupling model as our point of departure, we design low-depth quantum circuits emulating its dynamics with up to th

Simone Bonfrate, Nicolas Ferré, Miquel, Huix-Rotllant

Hybrid quantum mechanics / molecular mechanics (QM/MM) models successfully describe the properties of biological macromolecules. However, most QM/MM methodologies are constrained to unrealistic gas phase models, thus limiting their applicability. In the literature, several works have attempted to define a QM/MM model in periodic boundary conditions (PBC) but

Jacob Wahlgren, Maya Gokhale, Ivy B. Peng

Current HPC systems provide memory resources that are statically configured and tightly coupled with compute nodes. However, workloads on HPC systems are evolving. Diverse workloads lead to a need for configurable memory resources to achieve high performance and utilization. In this study, we evaluate a memory subsystem design leveraging CXL-enabled memory p

Raj Bridgelall

This tutorial is an andragogical guide for students and practitioners seeking to understand the fundamentals and practice of linear programming. The exercises demonstrate how to solve classical optimization problems with an emphasis on spatial analysis in supply chain management and transport logistics. All exercises display the Python programs and optimizat

Ioannis Kontoyiannis

The Bayesian Context Trees (BCT) framework is a recently introduced, general collection of statistical and algorithmic tools for modelling, analysis and inference with discrete-valued time series. The foundation of this development is built in part on some well-known information-theoretic ideas and techniques, including Rissanen's tree sources and Willems et

Morgane Goibert, Thomas Ricatte, Elvis Dohmatob

In this paper, we investigate the impact of neural networks (NNs) topology on adversarial robustness. Specifically, we study the graph produced when an input traverses all the layers of a NN, and show that such graphs are different for clean and adversarial inputs. We find that graphs from clean inputs are more centralized around highway edges, whereas those

Ted M Johnson, Beth L. Klein, D. Koester, Carl Melis

Ultraviolet and optical spectra of the hydrogen-dominated atmosphere white dwarf star G238-44 obtained with FUSE, Keck/HIRES, HST/COS, and HST/STIS reveal ten elements heavier than helium: C, N, O, Mg, Al, Si, P, S, Ca, and Fe. G238-44 is only the third white dwarf with nitrogen detected in its atmosphere from polluting planetary system material. Keck/HIRES

Oscar J. C. Dias, Takaaki Ishii, Keiju Murata, Jorge E. Santos

We investigate the effect of superradiant scattering of gravitational perturbations on the stability of rotating black strings, focusing on the six dimensional equal-spinning Myers-Perry black string. We find that rapidly rotating black strings are unstable to gravitational superradiant modes within a bounded range of string lengths. The instability occurs b

Mario Cadelano, Francesco R. Ferraro, Emanuele Dalessandro, Barbara Lanzoni

We used a combination of high-resolution optical images acquired with the Hubble Space Telescope and near-IR wide-field data to investigate the stellar density profile and the population of blue straggler star (BSS) in the Galactic globular cluster NGC6256, with the aim of probing its current stage of internal dynamical evolution. We found that the inner ste

Patrick L. Kelly, Wenlei Chen, Amruth Alfred, Thomas J. Broadhurst

Once only accessible in nearby galaxies, we can now study individual stars across much of the observable universe aided by galaxy-cluster gravitational lenses. When a star, compact object, or multiple such objects in the foreground galaxy-cluster lens become aligned, they can magnify a background individual star, and the timescale of a magnification peak can

George Mountrichas, Francesco Shankar

It is still a matter of intense debate how supermassive black holes (SMBH) grow, and the role played by feedback from active galactic nuclei (AGN) in the co-evolution of SMBHs and galaxies. To test the coevolution proposed by theoretical models, we compile a large AGN sample of 5639 X-ray detected AGN, over a wide redshift range, spanning nearly three orders

P. A. Nosov, I. S. Burmistrov, S. Raghu

We study the superconducting instability of a two-dimensional disordered Fermi liquid weakly coupled to the soft fluctuations associated with proximity to an Ising-ferromagnetic quantum critical point. We derive interaction-induced corrections to the Usadel equation governing the superconducting gap function, and show that diffusion and localization effects

Risto Vuorio, Pim de Haan, Johann Brehmer, Hanno Ackermann

Standard imitation learning can fail when the expert demonstrators have different sensory inputs than the imitating agent. This is because partial observability gives rise to hidden confounders in the causal graph. In previous work, to work around the confounding problem, policies have been trained using query access to the expert's policy or inverse reinfor

C. A. Argüelles, P. Fernández, I. Martínez-Soler, M. Jin

After two decades of measurements, neutrino physics is now advancing into the precision era. Withthe long-baseline experiments designed to tackle current open questions, a new query arises: can atmospheric neutrino experiments also play a role? To that end, we analyze the expected sensitivity of current and near-future water(ice)-Cherenkov atmospheric neutri

Kun Xu, Y. P. Jing, Yun Zheng, Hongyu Gao

Taking advantage of the Photometric objects Around Cosmic webs (PAC) method developed in Paper I, we measure the excess surface density $\bar{n}_2w_{{\rm{p}}}$ of photometric objects around spectroscopic objects down to stellar mass $10^{8.0}M_{\odot}$, $10^{9.2}M_{\odot}$ and $10^{9.8}M_{\odot}$ in the redshift ranges of $z_s<0.2$, $0.2<z_s<0.4$ and $0.5<z_

Erica Bufanda, Karen J. Meech, Jan T. Kleyna, Olivier R. Hainaut

2009 MS9 is a trans-Neptunian object (TNO) whose perihelion brings it close to the distance where some long period comets are seen to become active. Knowing this, and the fact that this object appears to brighten in excess of it's predicted nucleus brightness suggests that 2009 MS9 has a delayed onset of activity brought on by the sublimation of a species mo

Francisco Machado, Eugene A. Demler, Norman Y. Yao, Shubhayu Chatterjee

The transition between distinct phases of matter is characterized by the nature of fluctuations near the critical point. We demonstrate that noise spectroscopy can not only diagnose the presence of a phase transition, but can also determine fundamental properties of its criticality. In particular, by analyzing a scaling collapse of the decoherence profile, o

Andrea Boido, Jerome P. Gauntlett, Dario Martelli, James Sparks

We derive a gravitational block formula for the supersymmetric action for a general class of supersymmetric AdS solutions, described by GK geometry. Extremal points of this action describe supersymmetric AdS$_3$ solutions of type IIB supergravity, sourced by D3-branes, and supersymmetric AdS$_2$ solutions of $D=11$ supergravity, sourced by M2-branes. In both

Reuven Balkin, Javi Serra, Konstantin Springmann, Stefan Stelzl

We study the effects of exceptionally light QCD axions on the stellar configuration of white dwarfs. At finite baryon density, the non-derivative coupling of the axion to nucleons displaces the axion from its in-vacuum minimum which implies a reduction of the nucleon mass. This dramatically alters the composition of stellar remnants. In particular, the modif

Gert Hütsi, Martti Raidal, Juan Urrutia, Ville Vaskonen

The James Webb Space Telescope has detected surprisingly luminous early galaxies that indicate a tension with the $\Lambda$CDM. Motivated by scenarios including axion miniclusters or primordial black holes, we consider power-law modifications of the matter power spectrum. We show that the tension could be resolved if dark matter consists of $2\times 10^{-18}

Saswata Mandal, Bitan Roy

Linearly dispersing Rarita-Schwinger-Weyl (RSW) fermions featuring two Fermi velocities are the key constituents of itinerant spin-3/2 quantum materials. When doped, RSW metals sustain two Fermi surfaces (FSs), around which one fully gapped $s$-wave and five \emph{mixed-parity} local pairings can take place. The intraband components of four mixed-parity pair

Juan C. Dibene, Enrique Dunn

We present a HoloLens 2 server application for streaming device data via TCP in real time. The server can stream data from the four grayscale cameras, depth sensor, IMU, front RGB camera, microphone, head tracking, eye tracking, and hand tracking. Each sent data frame has a timestamp and, optionally, the instantaneous pose of the device in 3D space. The serv

Thomas Weng, David Held, Franziska Meier, Mustafa Mukadam

We formulate grasp learning as a neural field and present Neural Grasp Distance Fields (NGDF). Here, the input is a 6D pose of a robot end effector and output is a distance to a continuous manifold of valid grasps for an object. In contrast to current approaches that predict a set of discrete candidate grasps, the distance-based NGDF representation is easily

Gaurav Verma, Vishwa Vinay, Ryan A. Rossi, Srijan Kumar

As multimodal learning finds applications in a wide variety of high-stakes societal tasks, investigating their robustness becomes important. Existing work has focused on understanding the robustness of vision-and-language models to imperceptible variations on benchmark tasks. In this work, we investigate the robustness of multimodal classifiers to cross-moda

Baiwei Guo, Yuning Jiang, Maryam Kamgarpour, Giancarlo Ferrari-Trecate

We address black-box convex optimization problems, where the objective and constraint functions are not explicitly known but can be sampled within the feasible set. The challenge is thus to generate a sequence of feasible points converging towards an optimal solution. By leveraging the knowledge of the smoothness properties of the objective and constraint fu

Giuseppe Fava, Andrea Gambassi, Francesco Ginelli

Confining in space the equilibrium fluctuations of statistical systems with long-range correlations is known to result into effective forces on the boundaries. Here we demonstrate the occurrence of Casimir-like forces in the non-equilibrium context provided by flocking active matter. In particular, we consider a system of aligning self-propelled particles in

Mirco Ramo, Guénolé C. M. Silvestre

The Transformer architecture is shown to provide a powerful framework as an end-to-end model for building expression trees from online handwritten gestures corresponding to glyph strokes. In particular, the attention mechanism was successfully used to encode, learn and enforce the underlying syntax of expressions creating latent representations that are corr

José C. Bellido, Javier Cueto, Carlos Mora-Corral

We develop a theory of existence of minimizers of energy functionals in vectorial problems based on a nonlocal gradient under Dirichlet boundary conditions. The model shares many features with the peridynamics model and is also applicable to nonlocal solid mechanics, especially nonlinear elasticity. This nonlocal gradient was introduced in an earlier work, i

Gyuhak Kim, Changnan Xiao, Tatsuya Konishi, Zixuan Ke

Continual learning (CL) learns a sequence of tasks incrementally. There are two popular CL settings, class incremental learning (CIL) and task incremental learning (TIL). A major challenge of CL is catastrophic forgetting (CF). While a number of techniques are already available to effectively overcome CF for TIL, CIL remains to be highly challenging. So far,

Andrew J. Baldwin, Jonathan A. Jones

We consider the problem of efficiently computing the Uhlmann fidelity in the case when explicit density matrix descriptions are available. We derive an alternative formula which is simpler to evaluate numerically, saving a factor of 10 in time for large matrices.

Hannah Kümpel, Sabine Hoffmann

Effect size measures and visualization techniques aimed at maximizing the interpretability and comparability of results from statistical models have long been of great importance and are recently again receiving increased attention in the literature. However, since the methods proposed in this context originate from a wide variety of disciplines and are more

John Prager

In this article, we discuss a novel approach to solving number sequence problems, in which sequences of numbers following unstated rules are given, and missing terms are to be inferred. We develop a methodology of decomposing test sequences into linear combinations of known base sequences, and using the decomposition weights to predict the missing term. We s

Gia Dvali, Lukas Eisemann

In some instances of study of quantum evolution of classical backgrounds it is considered inevitable to resort to non-perturbative methods at the price of treating the system semiclassically. We show that a fully quantum perturbative treatment, in which the background is resolved as a multi-particle state, recovers the semiclassical non-perturbative results

ATLAS Collaboration

A search for heavy Higgs bosons produced in association with a vector boson and decaying into a pair of vector bosons is performed in final states with two leptons (electrons or muons) of the same electric charge, missing transverse momentum and jets. A data sample of proton-proton collisions at a centre-of-mass energy of 13 TeV recorded with the ATLAS detec

Gonzalo Emiliano Ruiz Stolowicz

It is shown that for n bigger than 1, the group of holomorphic isometries of the n dimensional complex hyperbolic space does not admit non-elementary representations into the group of isometries of the infinite dimensional real hyperbolic space.

Pavan Ahluwalia, Justine Choi, Simba Masters, Austin Mullins

We investigate the production of Higgs bosons in neutral- and charged-current interactions at a future Muon-Ion Collider (MuIC) with emphasis on $H^0 \to c\overline{c}$ decay. In particular, we focus on the leading production mechanisms and explore the impact of a range of Parton Distribution Function (PDF) scenarios, with emphasis on the role of heavy intri

Shahad Al-Khalifa

In this research, we discussed a rising issue for Muslims in today world that involves a financial and technical innovation, namely: cryptocurrencies. We found out through a questionnaire that many Muslims are having a hard time finding the jurisprudence rulings on certain cryptocurrencies. Therefore, the objective of this research is to investigate and iden

Brahayam Ponton, Magda Ferri, Lars Koenig, Marcus Bartels

For an autonomous vehicle, the ability to sense its surroundings and to build an overall representation of the environment by fusing different sensor data streams is fundamental. To this end, the poses of all sensors need to be accurately determined. Traditional calibration methods are based on: 1) using targets specifically designed for calibration purposes

Ganesh Ghalme, Xin Huang, Yuka Machino, Nidhi Rathi

We study the classic problem of \emph{fairly} dividing a heterogeneous and divisible resource -- modeled as a line segment $[0,1]$ and typically called as a \emph{cake} -- among $n$ agents. This work considers an interesting variant of the problem where agents are embedded on a graph. The graphical constraint entails that each agent evaluates her allocated s

Fintan Costello, Paul Watts

Given the well-known and fundamental problems with hypothesis testing via classical (point-form) significance tests, there has been a general move to alternative approaches, often focused on the Bayesian t-test. We show that the Bayesian t-test approach does not address the observed problems with classical significance testing, that Bayesian and classical t-

Samuel Yen-Chi Chen, Daniel Fry, Amol Deshmukh, Vladimir Rastunkov

Recent developments in quantum computing and machine learning have propelled the interdisciplinary study of quantum machine learning. Sequential modeling is an important task with high scientific and commercial value. Existing VQC or QNN-based methods require significant computational resources to perform the gradient-based optimization of a larger number of

Tulsi Satyavir Dabodiya, Somasekhara Goud Sontti, Zixiang Wei, Qiuyun Lu

This work demonstrates an original and ultrasensitive approach for surface-enhanced Raman spectroscopy (SERS) detection based on evaporation of self-lubricating drops containing silver supraparticles. The developed method detects an extremely low concentration of analyte that is enriched and concentrated on sensitive SERS sites of the compact supraparticles

J. M. Hardin, I. Martinez-Soler, A. Diaz, M. Jin

This article reports global fits of short-baseline neutrino data to oscillation models involving light sterile neutrinos. In the commonly-used 3+1 plane wave model, there is a well-known 4.9$\sigma$ tension between data sets sensitive to appearance versus disappearance of neutrinos. We find that models that damp the oscillation prediction for the reactor dat

Fintan Costello, Paul Watts

There is a well-known problem in Null Hypothesis Significance Testing: many statistically significant results fail to replicate in subsequent experiments. We show that this problem arises because standard `point-form null' significance tests consider only within-experiment but ignore between-experiment variation, and so systematically underestimate the degre

Rychard J. Bouwens, Mauro Stefanon, Gabriel Brammer, Pascal A. Oesch

We present the first constraints on the prevalence of z>10 galaxies in the Hubble Ultra Deep Field (HUDF) leveraging new NIRCam observations from JEMS (JWST Extragalactic Medium-band Survey). These NIRCam observations probe redward of 1.6$\mu$m, beyond the wavelength limit of HST, allowing us to search for galaxies to z>10. These observations indicate that t

Kiran Wani, Haritma Gaur

We present a study of the flux distribution of a sample of 15 Intermediate and Low-energy peaked blazars using XMM-Newton observations in a total of 57 epochs on short-term timescales. We characterise the X-ray variability of all of the light curves using excess fractional variability amplitude and found that only 24 light curves in 7 sources are significant

Barbara Dembin, Shuta Nakajima

We consider the supercritical bond percolation on $\mathbb Z^d$ and study the graph distance on the percolation graph called the chemical distance. It is well-known that there exists a deterministic constant $\mu(x)$ such that the chemical distance $\mathcal D(0,nx)$ between two connected points $0$ and $nx$ grows like $n\mu(x)$. Garet and Marchand (Ann. Pro

Eric A. Bergshoeff, Jan Rosseel

We give an overview of the different non-Lorentzian supergravity theories in diverse dimensions that have been constructed in recent years. After giving a detailed discussion of non-Lorentzian geometries as compared to Lorentzian geometries, we outline some of the construction methods that have been applied to obtain non-Lorentzian supergravity. Explicit res