November 2022 arXiv papers — page 137

Robert Vertesi

This contribution summarizes a selection of recent results from the ALICE experiment. We show the cross-section of beauty jets in pp collisions, as well as the charmed baryon-to-meson production ratios, down to unprecedentedly low momenta, at $\sqrt{s_{\rm NN}} = 5.02$ and 13 TeV collision energies. We present the nuclear modification of ${\rm D}^0$-jets and

N. V. Krylov

We prove the existence of strong solutions of It\^o's stochastic time dependent equations with irregular diffusion and drift terms of Morrey spaces. Strong uniqueness is also discussed.

Dileep Chandran, Andrea Zampiron, Amirreza Rouhi, Matt K. Fu

Here, we present measurements of turbulent drag reduction in boundary layers at high friction Reynolds numbers in the range of $4500 \le Re_\tau \le 15000$. The efficacy of the approach, using streamwise travelling waves of spanwise wall oscillations, is studied for two actuation regimes: (i) inner-scaled actuation (ISA), as investigated in Part 1 of this st

Adam H. Walker, Chris J. Pickard, Andrew G. Green

Density functional theory in the local or semi-local density approximation is a powerful tool for materials simulation, yet it struggles in many cases to describe collective electronic order that is driven by electronic interactions. In this work it is shown how arbitrary, fluctuation-driven electronic order may be introduced into density functional theory u

Monika Henzinger, Ami Paz, Arash Pourdamghani, Stefan Schmid

Emerging software-defined networking technologies enable more adaptive communication infrastructures, allowing for quick reactions to changes in networking requirements by exploiting the workload's temporal structure. However, operating networks adaptively is algorithmically challenging, as meeting networks' stringent dependability requirements relies on mai

Lizhi Xiang, Miao Yin, Chengming Zhang, Aravind Sukumaran-Rajam

Tucker decomposition is one of the SOTA CNN model compression techniques. However, unlike the FLOPs reduction, we observe very limited inference time reduction with Tucker-compressed models using existing GPU software such as cuDNN. To this end, we propose an efficient end-to-end framework that can generate highly accurate and compact CNN models via Tucker d

Daniel Steinberg, Paul Munro

Deep learning has been a popular topic and has achieved success in many areas. It has drawn the attention of researchers and machine learning practitioners alike, with developed models deployed to a variety of settings. Along with its achievements, research has shown that deep learning models are vulnerable to adversarial attacks. This finding brought about

Robert Cardona, Francisco Presas

Given a class of embeddings into a contact or a symplectic manifold, we give a sufficient condition, that we call isocontact or isosymplectic realization, for this class to satisfy a general $h$-principle. The flexibility follows from the $h$-principles for isocontact and isosymplectic embeddings, it provides a framework for classical results, and we give tw

G. Lodato, L. Rampinelli, E. Viscardi, C. Longarini

ALMA observations of line emission from planet forming discs have demonstrated to be an excellent tool to probe the internal disc kinematics, often revealing subtle effects related to important dynamical processes occurring in them, such as turbulence, or the presence of planets, that can be inferred from pressure bumps perturbing the gas motion, or from det

Marco Seracini, Stephen R. Brown

In this article, using an exemplar-based approach, we investigate the inpainting problem, introducing a new mathematical functional, whose minimization determines the quality of the reconstructions. The new functional expression takes into account of fnite differences terms, in a similar fashion to what happens in the theoretical Sobolev spaces. Moreover, we

Huidong Liang, Xingjian Du, Bilei Zhu, Zejun Ma

Existing graph contrastive learning methods rely on augmentation techniques based on random perturbations (e.g., randomly adding or dropping edges and nodes). Nevertheless, altering certain edges or nodes can unexpectedly change the graph characteristics, and choosing the optimal perturbing ratio for each dataset requires onerous manual tuning. In this paper

Iván Pan, Alvaro Rittatore

Let $\Bbbk$ be a perfect field with algebraic closure $\overline{\Bbbk}$. If $H$ is a subgroup of plane automorphisms over $\Bbbk$ and $p\in\overline{\Bbbk}^2$ is a point, we describe the subgroup consisting of plane automorphisms which stabilize the orbit of $p$ under $H$, when this orbit has irreducible closure in $\overline{\Bbbk}^2$. As an application, w

Jakob Hedicke

We show that the natural conjugation invariant cone structure on the linear symplectic group $\mathrm{Sp}(2n)$ is globally hyperbolic in the positively elliptic region $\mathrm{Sp}_{\mathrm{ell}}^{+}(2n)$. This answers a question by Abbondandolo, Benedetti and Polterovich and shows a formula for a bi-invariant Lorentzian distance function dened by these auth

W. Dednam, C. Sabater, A. E. Botha, E. B. Lombardi

The spin and lattice dynamics of a ferromagnetic nanoparticle are studied via molecular dynamics and with semi-classical spin dynamics simulations where spin and lattice degrees of freedom are coupled via a dynamic uniaxial anisotropy term. We show that this model conserves total angular momentum, whereas spin and lattice angular momentum are not conserved.

Fevziye Irem Eyiokur, Alperen Kantarcı, Mustafa Ekrem Erakın, Naser Damer

The emergence of COVID-19 has had a global and profound impact, not only on society as a whole, but also on the lives of individuals. Various prevention measures were introduced around the world to limit the transmission of the disease, including face masks, mandates for social distancing and regular disinfection in public spaces, and the use of screening ap

J. Nesetril, P. Ossona de Mendez, S. Siebertz

We prove that, on bounded expansion classes, every first-order formula with modulo counting is equivalent, in a linear-time computable monadic expansion, to an existential first-order formula. As a consequence, we derive, on bounded expansion classes, that first-order transductions with modulo counting have the same encoding power as existential first-order

Latif U. Khan, Ibrar Yaqoob, Khaled Salah, Choong Seon Hong

Today's wireless systems are posing key challenges in terms of quality of service and quality of physical experience. Metaverse has the potential to reshape, transform, and add innovations to the existing wireless systems. A metaverse is a collective virtual open space that can enable wireless systems using digital twins, digital avatars, and interactive exp

Marco Rampazzo

We produce counterexamples to the birational Torelli theorem for Calabi-Yau manifolds in arbitrarily high dimension: this is done by exhibiting a series of non birational pairs of Calabi-Yau $(n^2-1)$-folds which, for $n \geq 2$ even, admit an isometry between their middle cohomologies. These varieties also satisfy an $\mathbb L$-equivalence relation in the

Mohammad Bagher Heydari, Majid Karimipour, Morteza Mohammadi Shirkolaei

In recent years, the hybridization of hyperbolic van der Waals heterostructures with plasmonic two-dimensional nano-materials is one of the interesting research areas at THz frequencies due to the coupled features of the hybrid structure. This article investigates the propagation of tunable surface phonon-plasmon polaritons in grounded hybrid graphene-hexago

Xingqian Xu, Shant Navasardyan, Vahram Tadevosyan, Andranik Sargsyan

Image completion with large-scale free-form missing regions is one of the most challenging tasks for the computer vision community. While researchers pursue better solutions, drawbacks such as pattern unawareness, blurry textures, and structure distortion remain noticeable, and thus leave space for improvement. To overcome these challenges, we propose a new

Yuhan Liu, Pengyu Wang, Roland Tóth

An important issue in model-based control design is that an accurate dynamic model of the system is generally nonlinear, complex, and costly to obtain. This limits achievable control performance in practice. Gaussian process (GP) based estimation of system models is an effective tool to learn unknown dynamics directly from input/output data. However, convent

Haleh Hayati, Carlos Murguia, Nathan van de Wouw

We present a framework for designing distorting mechanisms that allow remotely operating anomaly detectors while preserving privacy. We consider the problem setting in which a remote station seeks to identify anomalies using system input-output signals transmitted over communication networks. However, disclosing true data of the system operation is not desir

Kaixiang Zhang, Yang Zheng, Chao Shang, Zhaojian Li

In this letter, we propose a simple yet effective singular value decomposition (SVD) based strategy to reduce the optimization problem dimension in data-enabled predictive control (DeePC). Specifically, in the case of linear time-invariant systems, the excessive input/output measurements can be rearranged into a smaller data library for the non-parametric re

Gianluca Fontanesi, Anding Zhu, Mahnaz Arvaneh, Hamed Ahmadi

The connectivity-aware path design is crucial in the effective deployment of autonomous Unmanned Aerial Vehicles (UAVs). Recently, Reinforcement Learning (RL) algorithms have become the popular approach to solving this type of complex problem, but RL algorithms suffer slow convergence. In this paper, we propose a Transfer Learning (TL) approach, where we use

Jakub Tětek

The exponential increase in the amount of available data makes taking advantage of them without violating users' privacy one of the fundamental problems of computer science. This question has been investigated thoroughly under the framework of differential privacy. However, most of the literature has not focused on settings where the amount of data is so lar

Adesh Singh, G. Sharma

Electronic transport in the $\alpha-\mathcal{T}_3$ model of pseudospin-1 fermions with a finite gap is studied within the semiclassical Boltzmann approximation. We show that coupling of the orbital magnetic moment to the external magnetic field, which is otherwise absent in the massless model, breaks valley symmetry, results in finite and measurable correcti

Minaspi Bantawa, Bavand Keshavarz, Michela Geri, Mehdi Bouzid

Soft particulate gels include materials we can eat, squeeze, or 3D print. From foods to bio-inks to cement hydrates, these gels are composed of a small amount of particulate matter (proteins, polymers, colloidal particles, or agglomerates of various origins) embedded in a continuous fluid phase. The solid components assemble to form a porous matrix, providin

A. P. Balachandran

The theta vacuum in QCD is the standard vacuum, twisted by the exponential of the Chern-Simons term. But what is the quantum operator $U(g)$ for winding number $1$? We construct $U(g)$ in this note. The Poincare' rotation generators commute with it only if they are augmented by the spin 1/2 representation of the Lorentz group coming from large gauge transfor

Yuxuan Wei, Jiaming Le, Chuanshan Tian

The intense terahertz (THz) pulses facilitate the observation of various nonlinear optical effects and manipulation of material properties. In this work, we report a convenient approach that can produce strong broadband terahertz pulses with center frequency tunable between 2-4 THz. The coherent THz light source with pulse energy of 1.2 microjoule can be gen

Chengkai Yu, Charles Fleming, Hai-Ning Liang

Video surveillance has become ubiquitous in the modern world. Mobile devices, surveillance cameras, and IoT devices, all can record video that can violate our privacy. One proposed solution for this is privacy-preserving video, which removes identifying information from the video as it is produced. Several algorithms for this have been proposed, but all of t

Diego Ruiz, Ronan Gautier, Jérémie Guillaud, Mazyar Mirrahimi

Kerr nonlinear oscillators driven by a two-photon process are promising systems to encode quantum information and to ensure a hardware-efficient scaling towards fault-tolerant quantum computation. In this paper, we show that an extra control parameter, the detuning of the two-photon drive with respect to the oscillator resonance, plays a crucial role in the

Zixin Yang, Richard Simon, Cristian A. Linte

Purpose: In laparoscopic liver surgery (LLS), pre-operative information can be overlaid onto the intra-operative scene by registering a 3D pre-operative model to the intra-operative partial surface reconstructed from the laparoscopic video. To assist with this task, we explore the use of learning-based feature descriptors, which, to our best knowledge, have

A. Bernardo, L. Paulucci, L. M. de Sá, J. E. Horvath

The Strange Quark matter (SQM) hypothesis states that at extreme pressure and density conditions a new ground state of matter would arise, in which half of the \textit{down} quarks become strange quarks. If true, it would mean that at least the core of neutron stars is made of SQM. In this hypothesis, SQM would be released in the inter-stellar medium when tw

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

Consider search on an infinite line involving an autonomous robot starting at the origin of the line and an oblivious moving target at initial distance $d \geq 1$ from it. The robot can change direction and move anywhere on the line with constant maximum speed $1$ while the target is also moving on the line with constant speed $v>0$ but is unable to change i

Costanza Catalano, Maria Castaldo, Giacomo Como, Fabio Fagnani

We study a network formation game where $n$ players, identified with the nodes of a directed graph to be formed, choose where to wire their outgoing links in order to maximize their PageRank centrality. Specifically, the action of every player $i$ consists in the wiring of a predetermined number $d_i$ of directed out-links, and her utility is her own PageRan

Thiago R. F. P. Tomei

The High-Luminosity LHC (HL-LHC) will usher in a new era in high-energy physics. The HL-LHC experimental conditions entail an instantaneous luminosity of up to $7.5 \times 10^{34}$ cm$^{-2}$ s$^{-1}$ and up to 200 simultaneous collisions per bunch crossing (pileup). To cope with those conditions, the CMS detector will undergo a series of improvements, in wha

Parvathy Sobha

India, being one of the fastest growing economies of the world, must take a sustainable path for development. India is responsible for 7 percent of global CO2 emissions. The electricity sector accounts for nearly 35 percent of emissions from the country. The switch from fossil fuels to renewable sources is the key in decarbonizing this sector and is consider

Jakob Bæk Tejs Houen, Rasmus Pagh, Stefan Walzer

Imagine handling collisions in a hash table by storing, in each cell, the bit-wise exclusive-or of the set of keys hashing there. This appears to be a terrible idea: For $\alpha n$ keys and $n$ buckets, where $\alpha$ is constant, we expect that a constant fraction of the keys will be unrecoverable due to collisions. We show that if this collision resolution

Simone Costa, Stefano Della Fiore

The classical Erd\H{o}s-Ginzburg-Ziv constant of a group $G$ denotes the smallest positive integer $\ell$ such that any sequence $S$ of length at least $\ell$ contains a zero-sum subsequence of length $\exp(G)$. In a recent paper, Caro and Schmitt generalized this concept, using the $m$-th degree symmetric polynomial $e_m(S)$ instead of the sum of the elemen

Midhun Xavier, Victor Dubinin, Sandeep Patil, Valeriy Vyatkin

This paper introduces the concept of plant model generation from the recorded traces of events using the process mining technique. The event logs are obtained by visually simulating a simple distributed manufacturing system using the OPC UA communication protocol. The process discovery alpha algorithm is used to extract the process model in Petri net format.

Jonathan Bowden, Fabio Gironella, Agustin Moreno, Zhengyi Zhou

We show that for all $n \ge 3$, any $(2n+1)$-dimensional manifold that admits a tight contact structure, also admits a tight but non-fillable contact structure, in the same almost contact class. For $n=2$, we obtain the same result, provided that the first Chern class vanishes. We further construct Liouville but not Weinstein fillable contact structures on a

Vladimir Somers, Christophe De Vleeschouwer, Alexandre Alahi

Occluded person re-identification (ReID) is a person retrieval task which aims at matching occluded person images with holistic ones. For addressing occluded ReID, part-based methods have been shown beneficial as they offer fine-grained information and are well suited to represent partially visible human bodies. However, training a part-based model is a chal

Elad Zelingher

We find a recursive expression for the Bessel function of S. I. Gelfand for irreducible generic representations of $\operatorname{GL}_n\left(\mathbb{F}_q\right)$. We show that special values of the Bessel function can be realized as the coefficients of $L$-functions associated with exotic Kloosterman sums, and as traces of exterior powers of Katz's exotic Kl

Duncan Bossion, Sutirtha N. Chowdhury, Pengfei Huo

We derive the non-adiabatic ring polymer molecular dynamics (RPMD) approach in the phase space of the SU(N) Lie Group. This method, which we refer to as the spin mapping non-adiabatic RPMD (SM-NRPMD), is based on the spin-mapping formalism for the electronic degrees of freedom (DOFs) and ring polymer path-integral description for the nuclear DOFs. Using the

Shaohan Wu

Techniques have been proposed to estimate unknown antenna impedance due to time-varying near-field loading conditions at multiple-input single-output (MISO) receivers. However, it remains unclear when a change occurs and impedance estimation becomes necessary. In this letter, we address this problem by formulating it as a hypothesis test. Our contributions i

George Liddle, Amanda Turner

We study the anisotropic version of the Hastings-Levitov model AHL$(\nu)$. Previous results have shown that on bounded time-scales the harmonic measure on the boundary of the cluster converges, in the small-particle limit, to the solution of a deterministic ordinary differential equation. We consider the evolution of the harmonic measure on time-scales which

Zhanyuan Zhang, Evgeny Bulgakov, Konstantin Pichugin, Almas Sadreev

Avoided crossing of resonances and merging multiple bound states in the continuum (BICs) are parallel means for tailoring the physical properties of BICs. Herein, we introduce a new concept of super quasi-BIC for photonic crystal (PhC) systems where its quality ($Q$) factor is boosted in both parametric and momentum spaces. A super quasi-BIC with substantial

Stefan Rass, Sandra König, Shahzad Ahmad, Maksim Goman

Given a set of points in the Euclidean space $\mathbb{R}^\ell$ with $\ell>1$, the pairwise distances between the points are determined by their spatial location and the metric $d$ that we endow $\mathbb{R}^\ell$ with. Hence, the distance $d(\mathbf x,\mathbf y)=\delta$ between two points is fixed by the choice of $\mathbf x$ and $\mathbf y$ and $d$. We study

Juan Wang, Thomas Weber, Andreas Aigner, Stefan A. Maier

Tailoring critical light-matter coupling is a fundamental challenge of nanophotonics, impacting diverse fields from higher harmonic generation and energy conversion to surface-enhanced spectroscopy. Plasmonic perfect absorbers (PAs), where resonant antennas couple to their mirror images in adjacent metal films, have been instrumental for obtaining different

Midia Reshadi, David Gregg

Deep neural networks are a promising solution for applications that solve problems based on learning data sets. DNN accelerators solve the processing bottleneck as a domain-specific processor. Like other hardware solutions, there must be exact compatibility between the accelerator and other software components, especially the compiler. This paper presents a

Yu Liu, Ming Chen, Cunhua Pan, Yijin Pan

The emerging reconfigurable intelligent surface (RIS) technology is promising for applications in the millimeter wave (mmWave) communication systems to effectively compensate for propagation loss or tackle the blockage issue. Considering the high mobility of users in realistic scenarios, it is essential to adjust the phase shifts in real time to align the be

Julien Trevisan

We study the error of the number of points of a unimodular lattice that fall in a strictly convex and analytic set having the origin and that is dilated by a factor $t$. The aim is to generalize the result of a previous article. We first show that the study of the error, when it is normalized by $\sqrt{t}$, when this parameter tends to infinity and when the

Mikael Rørdam

In his study of the relative Dixmier property for inclusions of von Neumann algebras and of $C^*$-algebras, Popa considered a certain property of automorphisms on $C^*$-algebras, that we here call the strong averaging property. In this note we characterize when an automorphism on a $C^*$-algebra has the strong averaging property. In particular, automorphisms

Roman N. Lee, Andrey F. Pikelner

We use dimensional recurrence relations and analyticity to calculate four-loop propagator-type master integrals in the heavy-quark effective theory. Compared to previous applications of the DRA method, we apply a new technique of fixing homogeneous solutions from pole parts of integrals evaluated in different rational space-time dimension points. The latter

W. Ryssens, G. Scamps, G. Grams, I. Kullmann

Accurate estimates of the binding energy of nuclei far from stability that cannot be produced in the laboratory are crucial to our understanding of nuclear processes in astrophysical scenarios. Models based on energy density functionals have shown that they are capable of reproducing all known masses with root-mean-square error better than 800 keV, while ret

Jakub Adamczyk

Graph classification is an important area in both modern research and industry. Multiple applications, especially in chemistry and novel drug discovery, encourage rapid development of machine learning models in this area. To keep up with the pace of new research, proper experimental design, fair evaluation, and independent benchmarks are essential. Design of

Minghan Chu, Weicheng Qian

Reynolds-averaged Navier-Stokes (RANS)-based transition modeling is widely used in aerospace applications but suffers inaccuracies due to the Boussinesq turbulent viscosity hypothesis. The eigenspace perturbation method can estimate the accuracy of a RANS model by injecting perturbations to its predicted Reynolds stresses. However, there lacks a reliable met

Wei Shao, Sha Liu, Javier LLorca

The whole Al-Li phase diagram is predicted from first principles calculations and statistical mechanics including the effect of configurational and vibrational entropy. The formation enthalpy of different configurations at different temperatures was accurately predicted by means of cluster expansions that were fitted from first principles calculations. The v

Zhongdao Wang, Zhaopeng Dou, Jingwei Zhang, Liang Zheng

In this paper, we are interested in learning a generalizable person re-identification (re-ID) representation from unlabeled videos. Compared with 1) the popular unsupervised re-ID setting where the training and test sets are typically under the same domain, and 2) the popular domain generalization (DG) re-ID setting where the training samples are labeled, ou

Jiayao Zhang, Hongming Zhang, Zhun Deng, Dan Roth

Double-blind peer review mechanism has become the skeleton of academic research across multiple disciplines including computer science, yet several studies have questioned the quality of peer reviews and raised concerns on potential biases in the process. In this paper, we conduct a thorough and rigorous study on fairness disparities in peer review with the

Fawad Ahmed, Muneeb Ur Rehman, Jawad Ahmad, Muhammad Shahbaz Khan

With the advancement in technology, digital images can easily be transmitted and stored over the Internet. Encryption is used to avoid illegal interception of digital images. Encrypting large-sized colour images in their original dimension generally results in low encryption/decryption speed along with exerting a burden on the limited bandwidth of the transm

Li-Hsiang Shen, Chia-Che Hsieh, An-Hung Hsiao, Kai-Ten Feng

In recent years, the demand for pervasive smart services and applications has increased rapidly. Device-free human detection through sensors or cameras has been widely adopted, but it comes with privacy issues as well as misdetection for motionless people. To address these drawbacks, channel state information (CSI) captured from commercialized Wi-Fi devices

Libo Sun, Jia-Wang Bian, Huangying Zhan, Wei Yin

Self-supervised monocular depth estimation has shown impressive results in static scenes. It relies on the multi-view consistency assumption for training networks, however, that is violated in dynamic object regions and occlusions. Consequently, existing methods show poor accuracy in dynamic scenes, and the estimated depth map is blurred at object boundaries

Andrew Ross, Nathan Leroux, Arnaud de Riz, Danijela Marković

Spintronic nano-synapses and nano-neurons perform complex cognitive computations with high accuracy thanks to their rich, reproducible and controllable magnetization dynamics. These dynamical nanodevices could transform artificial intelligence hardware, provided that they implement state-of-the art deep neural networks. However, there is today no scalable wa

Sydney Dolan, Siddharth Nayak, Hamsa Balakrishnan

We explore space traffic management as an application of collision-free navigation in multi-agent systems where vehicles have limited observation and communication ranges. We investigate the effectiveness of transferring a collision avoidance multi-agent reinforcement (MARL) model trained on a ground environment to a space one. We demonstrate that the transf

Malte Henkel

The long-time behaviour of spin-spin correlators in the slow relaxation of systems undergoing phase-ordering kinetics is studied in geometries of finite size. A phenomenological finite-size scaling ansatz is formulated and tested through the exact solution of the kinetic spherical model, quenched to below the critical temperature, in $2<d<4$ dimensions.

Joshua Lockhart, Nicolas Marchesotti, Daniele Magazzeni, Manuela Veloso

Concept bottleneck models perform classification by first predicting which of a list of human provided concepts are true about a datapoint. Then a downstream model uses these predicted concept labels to predict the target label. The predicted concepts act as a rationale for the target prediction. Model trust issues emerge in this paradigm when soft concept l

Petar Melentijević

\begin{abstract} We obtain sharp $L^p\rightarrow L^q$ hypercontractive inequalities for the weighted Bergman spaces on the unit disk $\mathbb{D}$ with the usual weights \\ $\frac{\alpha-1}{\pi}(1-|z|^2)^{\alpha-2},\alpha>1$ for $q\geq 2,$ thus solving an interesting case of a problem from \cite{JANSON}. We also give some estimates for $0<q<2.$ \end{abstract}

Jan Engelmann, Leon Hetzel, Giovanni Palla, Lisa Sikkema

Single-cell reference atlases are large-scale, cell-level maps that capture cellular heterogeneity within an organ using single cell genomics. Given their size and cellular diversity, these atlases serve as high-quality training data for the transfer of cell type labels to new datasets. Such label transfer, however, must be robust to domain shifts in gene ex

Josef Willsher, Hui-Ke Jin, Johannes Knolle

The dynamical structure factor is an important observable of quantum magnets but due to numerical and theoretical limitations, it remains a challenge to make predictions for Hubbard-like models beyond one dimension. In this work, we study the magnetic excitations of the triangular lattice Hubbard model including next-nearest neighbor hopping. Starting from t

Gianlorenzo D'Angelo, Esmaeil Delfaraz

In the \emph{budgeted rooted node-weighted Steiner tree} problem, we are given a graph $G$ with $n$ nodes, a predefined node $r$, two weights associated to each node modelling costs and prizes. The aim is to find a tree in $G$ rooted at $r$ such that the total cost of its nodes is at most a given budget $B$ and the total prize is maximized. In the \emph{quot

Kana Ito

We give $Z$-monomial generators for the vacuum spaces of certain level 2 standard modules of type $A^{(2)}_{\textrm{odd}}$ with indices running over integer partitions. In particular, we give a Lie theoretic interpretation of the Rogers-Ramanujan type identities of type $A^{(2)}_{9}$, which were conjectured by Kanade-Russell, and proven by Bringmann et al. a

Matteo Costantini, Florestan Martin-Baillon

We study Lyapunov exponents for flat bundles over hyperbolic curves defined via parallel transport over the geodesic flow. We consider them as invariants on the space of Hitchin representations and show that there is a gap between any two consecutive Lyapunov exponents. Moreover we characterize the uniformizing representation of the Riemann surface as the on

Ming Zhang, Jie Jiang

With certain non-minimal coupling between a massless scalar field and the Gauss-Bonnet curvature invariant in the extended scalar-tensor-Gauss-Bonnet (ESTGB) field theory, tachyonic instability of Kerr-Newman (KN) black hole is promoted. Critical spin and charge for the onset of the spontaneous scalarization phenomenon for the KN black hole are calculated in

Nicolas Charpenay, Maël le Treust, Aline Roumy

We study the zero-error source coding problem in which an encoder with Side Information (SI) $g(Y)$ transmits source symbols $X$ to a decoder. The decoder has SI $Y$ and wants to recover $f(X,Y)$ where $f,g$ are deterministic. We exhibit a condition on the source distribution and $g$ that we call "pairwise shared side information", such that the optimal rate

Songbo Hu, Ivan Vulić, Fangyu Liu, Anna Korhonen

End-to-end (E2E) task-oriented dialogue (ToD) systems are prone to fall into the so-called "likelihood trap", resulting in generated responses which are dull, repetitive, and often inconsistent with dialogue history. Comparing ranked lists of multiple generated responses against the "gold response" (from evaluation data) reveals a wide diversity in response

Lukas Krenz, Sebastian Wolf, Gregor Hillers, Alice-Agnes Gabriel

Seismic waves can couple with the atmosphere and generate sound waves. The influence of faulting mechanisms on earthquake sound patterns provides opportunities for earthquake source characterization. Sound radiated from earthquakes can be perceived as disturbing which can negatively impact the social acceptance of geoengineering applications. Motivated by re

Rahaf Aljundi, Yash Patel, Milan Sulc, Daniel Olmeda

Cross entropy loss has served as the main objective function for classification-based tasks. Widely deployed for learning neural network classifiers, it shows both effectiveness and a probabilistic interpretation. Recently, after the success of self supervised contrastive representation learning methods, supervised contrastive methods have been proposed to l

Abhin Suresh, Branislav K. Nikolic

The interaction of fs light pulses with magnetic materials has been intensely studied for more than two decades in order to understand ultrafast demagnetization in single magnetic layers or THz emission from their bilayers with nonmagnetic spin-orbit (SO) materials. Here we develop a multiscale quantum-classical formalism -- where conduction electrons are de

Samuel Evans, Meers Oppenheim, Juan Martínez-Sykora, Yakov Dimant

Models fail to reproduce observations of the coldest parts of the Sun's atmosphere, where interactions between multiple ionized and neutral species prevent an accurate MHD representation. This paper argues that a meter-scale electrostatic plasma instability develops in these regions and causes heating. We refer to this instability as the Thermal Farley-Bunem

Roshan Sharma, Weipeng He, Ju Lin, Egor Lakomkin

This paper studies audio-visual noise suppression for egocentric videos -- where the speaker is not captured in the video. Instead, potential noise sources are visible on screen with the camera emulating the off-screen speaker's view of the outside world. This setting is different from prior work in audio-visual speech enhancement that relies on lip and faci

Jake Ruotolo, Zi-Xia Song

For a graph $H$ and an integer $k\ge1$, let $r(H;k)$ and $r_\ell(H;k)$ denote the $k$-color Ramsey number and list Ramsey number of $H$, respectively. Alon, Buci\'c, Kalvari, Kuperwasser and Szab\'o in 2021 initiated the systematic study of list Ramsey numbers of graphs and hypergraphs, and conjectured that $ r(K_{1,n};k)$ and $r_\ell(K_{1,n};k)$ are always

L. M. Sarro, A. Berihuete, R. L. Smart, C. Reylé

Aims. In this work we use the Gaia DR3 set of ultracool dwarf candidates and complement the Gaia spectrophotometry with additional photometry in order to characterise its global properties. This includes the inference of the distances, their locus in the Gaia colour-absolute magnitude diagram and the (biased through selection) luminosity function in the fain

Yuri Abramovich, Dan Dickey, Victor Abramovich

The problem of a constant modulus (CM) continuous wave (CW) waveform design with the thumb-tack ambiguity function that meets the NTIA RSEC requirements is addressed. The ad-hoc and alternating projection techniques are proposed to modify the spectrum of a prototype waveform to meet the NTIA RSEC requirements, retaining the "thumb-tack" property of the origi

Joël A. K. L. Picard, T. Speck

Conventional gas-liquid phase transitions feature a coexistence line that has a monotonic and positive slope in line with our intuition that cooling always leads to condensation. Here we study the inverse phenomenon, condensation of adsorbed organic molecules into dense domains upon heating. Our considerations are motivated by recent experiments [Aeschlimann

Leonardo Perotti, Lech A. Grzelak

We propose a new, data-driven approach for efficient pricing of - fixed- and float-strike - discrete arithmetic Asian and Lookback options when the underlying process is driven by the Heston model dynamics. The method proposed in this article constitutes an extension of our previous work, where the problem of sampling from time-integrated stochastic bridges

Damian Matuszewski, Ida-Maria Sintorn

Commonly used AI networks are very self-confident in their predictions, even when the evidence for a certain decision is dubious. The investigation of a deep learning model output is pivotal for understanding its decision processes and assessing its capabilities and limitations. By analyzing the distributions of raw network output vectors, it can be observed

Romain Lopez, Nataša Tagasovska, Stephen Ra, Kyunghyn Cho

Latent variable models such as the Variational Auto-Encoder (VAE) have become a go-to tool for analyzing biological data, especially in the field of single-cell genomics. One remaining challenge is the interpretability of latent variables as biological processes that define a cell's identity. Outside of biological applications, this problem is commonly refer

Timothy Holder, Mushfiqur Rahman, Emily Summers, David Roberts

Animal Assisted Interventions (AAIs) involve pleasant interactions between humans and animals and can potentially benefit both types of participants. Research in this field may help to uncover universal insights about cross-species bonding, dynamic affect detection, and the influence of environmental factors on dyadic interactions. However, experiments evalu

Huiru Xiao, Xin Liu, Yangqiu Song, Ginny Y. Wong

The choice of geometric space for knowledge graph (KG) embeddings can have significant effects on the performance of KG completion tasks. The hyperbolic geometry has been shown to capture the hierarchical patterns due to its tree-like metrics, which addressed the limitations of the Euclidean embedding models. Recent explorations of the complex hyperbolic geo

Maximilian Spliethöver, Maximilian Keiff, Henning Wachsmuth

News articles both shape and reflect public opinion across the political spectrum. Analyzing them for social bias can thus provide valuable insights, such as prevailing stereotypes in society and the media, which are often adopted by NLP models trained on respective data. Recent work has relied on word embedding bias measures, such as WEAT. However, several

Luis Avilés, Joaquim Gomis, Diego Hidalgo, Jorge Zanelli

We construct the electric and magnetic Newton-Hooke and Carroll Jackiw-Teitelboim gravity theories using the isomorphism of Newton-Hooke$_\pm$ and (A-)dS Carroll algebras in $(1+1)$-spacetime dimensions. The starting point is the non-relativistic and Carroll version of Jackiw-Teitelboim gravity without restrictions on the geometry studied in [15].

Johannes Wirtz

We consider the counting problem of the number of \textit{leaf-labeled increasing trees}, where internal nodes may have an arbitrary number of descendants. The set of all such trees is a discrete representation of the genealogies obtained under certain population-genetical models such as multiple-merger coalescents. While the combinatorics of the binary tree

CRAB Collaboration, NUCLEUS Collaboration, H. Abele, G. Angloher

Coherent elastic neutrino-nucleus scattering and low-mass Dark Matter detectors rely crucially on the understanding of their response to nuclear recoils. We report the first observation of a nuclear recoil peak at around 112 eV induced by neutron capture. The measurement was performed with a CaWO$_4$ cryogenic detector from the NUCLEUS experiment exposed to

Pawel Caputa, Dongsheng Ge

In this work we study families of generalised coherent states constructed from SL(2,R) subalgebras of the Virasoro algebra in two-dimensional conformal field theories. We derive the energy density and entanglement entropy and discuss their equivalence with analogous quantities computed in locally excited states. Moreover, we analyze their dual, holographic g

Vì Kronberg, Martijn Anthonissen, Jan ten Thije Boonkkamp, Wilbert IJzerman

We combine two-dimensional freeform reflector design with a scattering surface modelled using microfacets, i.e., small specular surfaces representing surface roughness. The model results in a convolution integral for the scattered light intensity distribution, which yields an inverse specular problem after deconvolution. Thus, the shape of a reflector with a

Qiheng Lu, Lixiang Lian

With the rapid development of information technologies, centralized data processing is subject to many limitations, such as computational overheads, communication delays, and data privacy leakage. Decentralized data processing over networked terminal nodes becomes an important technology in the era of big data. Dictionary learning is a powerful representatio

Harrison Kurunathan, Hailong Huang, Kai Li, Wei Ni

The ongoing amalgamation of UAV and ML techniques is creating a significant synergy and empowering UAVs with unprecedented intelligence and autonomy. This survey aims to provide a timely and comprehensive overview of ML techniques used in UAV operations and communications and identify the potential growth areas and research gaps. We emphasise the four key co

Carlos Uriarte, David Pardo, Ignacio Muga, Judit Muñoz-Matute

Residual minimization is a widely used technique for solving Partial Differential Equations in variational form. It minimizes the dual norm of the residual, which naturally yields a saddle-point (min-max) problem over the so-called trial and test spaces. In the context of neural networks, we can address this min-max approach by employing one network to seek

Djebril Mekhazni, Maximilien Dufau, Christian Desrosiers, Marco Pedersoli

Systems for person re-identification (ReID) can achieve a high accuracy when trained on large fully-labeled image datasets. However, the domain shift typically associated with diverse operational capture conditions (e.g., camera viewpoints and lighting) may translate to a significant decline in performance. This paper focuses on unsupervised domain adaptatio