January 2022 arXiv papers — page 54

Minghuan Liu, Menghui Zhu, Weinan Zhang

Goal-conditioned reinforcement learning (GCRL), related to a set of complex RL problems, trains an agent to achieve different goals under particular scenarios. Compared to the standard RL solutions that learn a policy solely depending on the states or observations, GCRL additionally requires the agent to make decisions according to different goals. In this s

Christine Fricker, Hanene Mohamed

The problem of reservation in a large distributed system is analyzed via a new mathematical model. A typical application is a station-based car-sharing system which can be described as a closed stochastic network where the nodes are the stations and the customers are the cars. The user can reserve the car and the parking space. In the paper, we study the evo

Murat Yessenov, Layton A. Hall, Kenneth L. Schepler, Ayman F. Abouraddy

"Space-time" (ST) wave packets constitute a broad class of pulsed optical fields that are rigidly transported in linear media without diffraction or dispersion, and are therefore propagation-invariant in absence of optical nonlinearities or waveguiding structures. Such wave packets exhibit unique characteristics, such as controllable group velocities in free

Ian Foster, Carl Kesselman

Despite much creative work on methods and tools, reproducibility -- the ability to repeat the computational steps used to obtain a research result -- remains elusive. One reason for these difficulties is that extant tools for capturing research processes do not align well with the rich working practices of scientists. We advocate here for simple mechanisms t

Lars Vögtlin, Anna Scius-Bertrand, Paul Maergner, Andreas Fischer

Deep learning methods have shown strong performance in solving tasks for historical document image analysis. However, despite current libraries and frameworks, programming an experiment or a set of experiments and executing them can be time-consuming. This is why we propose an open-source deep learning framework, DIVA-DAF, which is based on PyTorch Lightning

Alberto Racca, Luca Magri

We propose Echo State Networks (ESNs) to predict the statistics of extreme events in a turbulent flow. We train the ESNs on small datasets that lack information about the extreme events. We asses whether the networks are able to extrapolate from the small imperfect datasets and predict the heavy-tail statistics that describe the events. We find that the netw

Ruben Campos Delgado

Starting from an effective action for quantum gravity, we calculate the quantum gravitational corrections to the Wald entropy of a four dimensional non-extremal Reissner-Nordstr\"om (RN) black hole in the limit of small electric charge, generalising a previous calculation carried out by Calmet and Kuipers [1] for a Schwarzschild black hole. We show that, at

Mongi Blel, Jamel Benameur

We study the uniqueness, the continuity in $L^2$ and the large time decay for the Leray solutions of the $3D$ incompressible Navier-Stokes equations with nonlinear exponential damping term $a (e^{b |u|^{\bf 4}}-1)u$, ($a,b>0$).

Qiaoli Yang, Yu Gao, Zhihui Peng

Exploring the mysterious dark matter is a key quest in modern physics. Currently, detecting axions, a hypothetical particle proposed as a primary component of dark matter, remains a significant challenge due to their weakly interacting nature. Here we show at quantum level that in a cavity permeated by a magnetic field, the single axion-photon conversion rat

Albert F. Rigosi, Martina Marzano, Antonio Levy, Heather M. Hill

An algorithm is introduced for predicting quantized resistances in graphene p-n junction devices that utilize more than a single entry and exit point for electron flow. Depending on the configuration of an arbitrary number of terminals, electrical measurements yield fractional multiples of the typical quantized Hall resistance at the $\nu=2$ plateau $R_H \ap

Shane Elipot, Adam Sykulski, Rick Lumpkin, Luca Centurioni

A dataset of sea surface temperature (SST) estimates is generated from the temperature observations of surface drifting buoys of NOAA's Global Drifter Program. Estimates of SST at regular hourly time steps along drifter trajectories are obtained by fitting to observations a mathematical model representing simultaneously SST diurnal variability with three har

Aritra Chakravorty, William S. Cleveland, Patrick J. Wolfe

Data structures known as $k$-d trees have numerous applications in scientific computing, particularly in areas of modern statistics and data science such as range search in decision trees, clustering, nearest neighbors search, local regression, and so forth. In this article we present a scalable mechanism to construct $k$-d trees for distributed data, based

Dimitris Moustos

We consider an Unruh-DeWitt detector modeled as a harmonic oscillator that is coupled to a massless quantum scalar field in the (2+1)-dimensional Minkowski spacetime. We treat the detector as an open quantum system and employ a quantum Langevin equation to describe its time evolution, with the field, which is characterized by a frequency-independent spectral

Vincent Caudrelier, Matteo Stoppato, Benoit Vicedo

We cast the classical Yang-Baxter equation (CYBE) in a variational context for the first time, by relating it to the theory of Lagrangian multiforms, a framework designed to capture integrability in a variational fashion. This provides a significant connection between Lagrangian multiforms and the CYBE, one of the most fundamental concepts of integrable syst

Ram Sagar, R. K. S. Yadav, S. B. Pandey, Saurabh Sharma

The $UBVRI$ CCD photometric data of open star cluster NGC 1513 are obtained with the 3.6-m Indo-Belgian Devasthal optical telescope (DOT). Analyses of the GAIA EDR3 astrometric data have identified 106 possible cluster members. The mean proper motion of the cluster is estimated as $\mu_{\alpha}Cos{\delta}=1.29\pm0.02$ and $\mu_{\delta}=-3.74\pm0.02$ mas yr$^

Giorgos Chasapis, Salil Singh, Tomasz Tkocz

We establish several Schur-convexity type results under fixed variance for weighted sums of independent gamma random variables and obtain nonasymptotic bounds on their R\'enyi entropies. In particular, this pertains to the recent results by Bartczak-Nayar-Zwara as well as Bobkov-Naumov-Ulyanov, offering simple proofs of the former and extending the latter.

Stefanos Bennett, Mihai Cucuringu, Gesine Reinert

In multivariate time series systems, it has been observed that certain groups of variables partially lead the evolution of the system, while other variables follow this evolution with a time delay; the result is a lead-lag structure amongst the time series variables. In this paper, we propose a method for the detection of lead-lag clusters of time series in

Jing Yang, Adolfo del Campo

The exchange operator formalism (EOF) describes many-body integrable systems using phase-space variables involving an exchange operator that acts on any pair of particles. We establish an equivalence between models described by EOF and the complete infinite family of parent Hamiltonians (PHJ) describing quantum many-body models with ground-states of Jastrow

Sam Coates, Akihisa Koga, Toranosuke Matsubara, Ryuji Tamura

Exploring nonminimal-rank quasicrystals, which have symmetries that can be found in both periodic and aperiodic crystals, often provides new insight into the physical nature of aperiodic long-range order in models that are easier to treat. Motivated by the prevalence of experimental systems exhibiting aperiodic long-range order with hexagonal and trigonal sy

Saul Santos, Monica Ekal, Rodrigo Ventura

With deep learning gaining attention from the research community for prediction and control of real physical systems, learning important representations is becoming now more than ever mandatory. It is of extreme importance that deep learning representations are coherent with physics. When learning from discrete data this can be guaranteed by including some s

Xuantao Chen

We study the initial value problem of the Einstein-Dirac system, and show the stability of the Minkowski solution in the massless case with the use of generalized wave coordinates. This requires the understanding of the Dirac equation in curved spacetime, for which we establish various estimates. The proof is based on the vector-field method which is widely

Méghane Decroocq, Carole Frindel, Pierre Rougé, Makoto Ohta

Computational fluid dynamics (CFD) simulation provides valuable information on blood flow from the vascular geometry. However, it requires extracting precise models of arteries from low-resolution medical images, which remains challenging. Centerline-based representation is widely used to model large vascular networks with small vessels, as it encodes both t

Alexander New, Megan Baker, Eric Nguyen, Gautam Vallabha

The DARPA Lifelong Learning Machines (L2M) program seeks to yield advances in artificial intelligence (AI) systems so that they are capable of learning (and improving) continuously, leveraging data on one task to improve performance on another, and doing so in a computationally sustainable way. Performers on this program developed systems capable of performi

Shamsuddeen Hassan Muhammad, David Ifeoluwa Adelani, Sebastian Ruder, Ibrahim Said Ahmad

Sentiment analysis is one of the most widely studied applications in NLP, but most work focuses on languages with large amounts of data. We introduce the first large-scale human-annotated Twitter sentiment dataset for the four most widely spoken languages in Nigeria (Hausa, Igbo, Nigerian-Pidgin, and Yor\`ub\'a ) consisting of around 30,000 annotated tweets

Simon J. Gay, Diogo Poças, Vasco T. Vasconcelos

Many type systems include infinite types. In session type systems, which are the focus of this paper, infinite types are important because they allow the specification of communication protocols that are unbounded in time. Usually infinite session types are introduced as simple finite-state expressions $\mathsf{rec}\, X.T$ or by non-parametric equational def

Baptiste Blanc, Zhenkun Zhang, Eric Liu, Ning Zhou

We report on a synthesis protocol, experimental characterization and theoretical modeling of active pulsatile Belousov-Zhabotinsky (BZ) hydrogels. Our two-step synthesis technique allows independent optimization of the geometry, the chemical, and the mechanical properties of BZ gels. We identify the role of the surrounding medium chemistry and gel radius for

Thomas Harder, Margherita Turconi, Rémi Soulard, Walid Chaibi

In this paper we propose a novel strategy to control optomechanical parametric instability (PI) in gravitational wave (GW) detectors, based on radiation pressure. The fast deflection of a high power beam is the key element of our approach. We built a 2D deflection system based on a pair of acousto-optic modulators (AOMs) that combines high rapidity and large

R. M. Causey, E. Galego, C. Samuel

We prove that for infinite, countable, compact, Hausdorff spaces $K,L$, $C(K)\widehat{\otimes}_\pi C(L)$ is isomorphic to exactly one of the spaces $C(\omega^{\omega^\xi})\widehat{\otimes}_\pi C(\omega^{\omega^\zeta})$, $0\leqslant \zeta\leqslant \xi<\omega_1$. We also prove that $C(K)\widehat{\otimes}_\pi C(L)$ is not isomorphic to $C(M)$ for any compact, H

ATLAS Collaboration

Measurements of the production cross-sections of the Standard Model (SM) Higgs boson ($H$) decaying into a pair of $\tau$-leptons are presented. The measurements use data collected with the ATLAS detector from $pp$ collisions produced at the Large Hadron Collider at a centre-of-mass energy of $\sqrt{s}=13\,\text{TeV}$, corresponding to an integrated luminosi

Krzysztof Pomorski, Artur Dobrowolski, Bozena Nerlo-Pomorska, Michal Warda

Potential energy surfaces of even-even superheavy nuclei are evaluated within the macroscopic-microscopic approximation. A very rapidly converging analytical Fourier-type shape parametrization is used to describe nuclear shapes throughout the periodic table, including those of fissioning nuclei. The Lublin Strasbourg Drop and another effective liquid-drop ty

Michael Robinson, Letitia W. Li, Cory Anderson, Steve Huntsman

This paper provides an experimentally validated, probabilistic model of file behavior when consumed by a set of pre-existing parsers. File behavior is measured by way of a standardized set of Boolean "messages" produced as the files are read. By thresholding the posterior probability that a file exhibiting a particular set of messages is from a particular di

Quanzhen Wan

A real-time elemental image array (EIA) generation method which does not sacrifice accuracy nor rely on high-performance hardware is developed, through raytracing and pre-stored voxel-pixel lookup table (LUT). Benefiting from both offline and online working flow, experiments will verified the effectiveness.

Kaveh Hassani

We study the problem of few-shot graph classification across domains with nonequivalent feature spaces by introducing three new cross-domain benchmarks constructed from publicly available datasets. We also propose an attention-based graph encoder that uses three congruent views of graphs, one contextual and two topological views, to learn representations of

Paul Hongsuck Seo, Arsha Nagrani, Anurag Arnab, Cordelia Schmid

Recent video and language pretraining frameworks lack the ability to generate sentences. We present Multimodal Video Generative Pretraining (MV-GPT), a new pretraining framework for learning from unlabelled videos which can be effectively used for generative tasks such as multimodal video captioning. Unlike recent video-language pretraining frameworks, our f

Timothy Flavin, Bhaskar Mitra, Vidhyashree Nagaraju, Rounak Meyur

Precise location of faults for large distance power transmission networks is essential for faster repair and restoration process. High Voltage direct current (HVdc) networks using modular multi-level converter (MMC) technology has found its prominence for interconnected multi-terminal networks. This allows for large distance bulk power transmission at lower

Sonali Parbhoo, Shalmali Joshi, Finale Doshi-Velez

Assessing the effects of a policy based on observational data from a different policy is a common problem across several high-stake decision-making domains, and several off-policy evaluation (OPE) techniques have been proposed. However, these methods largely formulate OPE as a problem disassociated from the process used to generate the data (i.e. structural

Paolo Santini, Giulia Rafaiani, Massimo Battaglioni, Franco Chiaraluce

ASBK (named after the authors' initials) is a recent blockchain protocol tackling data availability attacks against light nodes, employing two-dimensional Reed-Solomon codes to encode the list of transactions and a random sampling phase where adversaries are forced to reveal information. In its original formulation, only codes with rate $1/4$ are considered,

Joana Cirici, Scott O. Wilson

We introduce and study Hodge-de Rham numbers for compact almost complex 4-manifolds, generalizing the Hodge numbers of a complex surface. The main properties of these numbers in the case of complex surfaces are extended to this more general setting, and it is shown that all Hodge-de Rham numbers for compact almost complex 4-manifolds are determined by the co

Lucas Vacossin

In this paper, we study the problem of scattering by several strictly convex obstacles, with smooth boundary and satisfying a non eclipse condition. We show, in dimension 2 only, the existence of a spectral gap for the meromorphic continuation of the Laplace operator outside the obstacles. The proof of this result relies on a reduction to an open hyperbolic

Marius Jürgensen, Sebabrata Mukherjee, Christina Jörg, Mikael C. Rechtsman

In many contexts, the interaction between particles gives rise to emergent and perhaps unanticipated physical phenomena. An example is the fractional quantum Hall effect, where interaction between electrons gives rise to fractionally quantized Hall conductance. In photonic systems, the nonlinear response of an ambient medium acts to mediate interaction betwe

Manoranjan Singha, Ujjal Kumar Hom

Organising the relevant literature and by letting statistical convergence play the main role in the theory of compactness, a variant of compactness called statistical compactness has been achieved. As in case of sequential compactness, one point statistical compactification is studied to some extent too.

Xiaochen Jin, Shunda Chen, Tianshu Li

Short-range chemical order (SRO) has been recently demonstrated to play a decisive role in modulating a wide range of physical properties in medium-entropy alloy (MEA) and high-entropy alloy (HEA). The enormous configurational space of these alloys implies multiple forms of SRO are likely to develop concurrently but such structural diversity has not been rep

Zachary Hamida, Blanche Laurent, James-A. Goulet

This paper describes OpenIPDM software for modelling the deterioration process of infrastructures using network-scale visual inspection data. In addition to the deterioration state estimates, OpenIPDM provides functions for quantifying the effect of interventions, estimating the service life of an intervention, and generating synthetic data for verification

Meng-Lin Du, Miguel Albaladejo, Feng-Kun Guo, Juan Nieves

We have performed a combined analysis of the BESIII data for both the $Z_c(3900)$ and $Z_{cs}(3985)$ structures, assuming that the latter is an SU(3) flavor partner of the former one. We have improved on the previous analysis of Albaladejo $et$ $al.$ [Phys. Lett. B 755, 337 (2016)] by computing the amplitude for the $D_1\bar{D}D^*$ triangle diagram consideri

A. Aharony, O. Entin-Wohlman, A. Kudlis

Perovskites like LaAlO3 (or SrTiO3) undergo displacive structural phase transitions from a cubic crystal to a trigonal (or tetragonal) structure. For many years, the critical exponents in both these types of transitions have been fitted to those of the isotropic three-components Heisenberg model. However, field theoretical calculations showed that the isotro

Nick Huggett, Keizo Matsubara

The modeling of black holes is an important desideratum for any quantum theory of gravity. Not only is a classical black hole metric sought, but also agreement with the laws of black hole thermodynamics. In this paper, we describe how these goals are obtained in string theory. We review black hole thermodynamics, and then explicate the general stringy deriva

Hilla Shinitzky, Yuval Shahar, Dan Avraham, Yizhak Vaisman

The outcome of a collective decision-making process, such as crowdsourcing, often relies on the procedure through which the perspectives of its individual members are aggregated. Popular aggregation methods, such as the majority rule, often fail to produce the optimal result, especially in high-complexity tasks. Methods that rely on meta-cognitive informatio

Bart van Oort, Luís Cruz, Babak Loni, Arie van Deursen

Machine Learning (ML) projects incur novel challenges in their development and productionisation over traditional software applications, though established principles and best practices in ensuring the project's software quality still apply. While using static analysis to catch code smells has been shown to improve software quality attributes, it is only a s

Daniele Bartoli, Giovanni Zini, Ferdinando Zullo

The tensor rank of some Gabidulin codes of small dimension is investigated. In particular, we determine the tensor rank of any rank metric code equivalent to an $8$-dimensional $\mathbb{F}_q$-linear generalized Gabidulin code in $\mathbb{F}_{q}^{4\times4}$. This shows that such a code is never minimum tensor rank. In this way, we detect the first infinite fa

Sameer Kumar, Shradha Mishra

With quenched disorder, we introduce two-dimensional active nematics suspended in an incompressible fluid. We write the coarse-grained hydrodynamic equations of motion for slow variables, viz. density, orientation and flow fields. The quenched disorder is introduced such that it interacts with the local orientation at every point with some strength. Disorder

Guangjun Zhu, Yakun Zhao, Shiya Duan, Yulong Yang

An equigenerated monomial ideal $I$ in the polynomial ring $S= K[x_1,\ldots,x_n]$ is a Freiman ideal if $\mu(I^2)=\ell(I)\mu(I)-{\ell(I)\choose 2}$ where $\ell(I)$ is the analytic spread of $I$ and $\mu(I)$ is the number of minimal generators of $I$. In this paper, we classify certain classes of Borel type ideals, including Borel ideals with multiple Borel g

Romal Thoppilan, Daniel De Freitas, Jamie Hall, Noam Shazeer

We present LaMDA: Language Models for Dialog Applications. LaMDA is a family of Transformer-based neural language models specialized for dialog, which have up to 137B parameters and are pre-trained on 1.56T words of public dialog data and web text. While model scaling alone can improve quality, it shows less improvements on safety and factual grounding. We d

J. Haidenbauer, U. -G. Meißner

Studies of the baryon-baryon interaction involving hyperons within chiral effective field theory, so far performed up to next-to-leading order (NLO) in the chiral expansion, have shown that for the strangeness $S=-1$ ($\Lambda N$, $\Sigma N$) and $S=-2$ ($\Lambda \Lambda$, $\Xi N$) sectors a consistent and satisfactory description of the available scattering

Ferhat Yarkin, Justin P. Coon

Due to dependence between codeword elements, index modulation (IM) and related modulation techniques struggle to provide simple solutions for practical problems such as Gray coding between information bits and constellation points; and low-complexity log-likelihood ratio (LLR) calculations for channel-encoded information bits. In this paper, we show that a m

Daomin Cao, Guolin Qin, Weilin Yu, Weicheng Zhan

This paper is concerned with steady vortex rings in an ideal fluid of uniform density, which are special global axi-symmetric solutions of the three-dimensional incompressible Euler equation. We systematically establish the existence, uniqueness and nonlinear orbital stability of steady vortex rings of small cross-section for which the potential vorticity is

Fedor Pakovich

We give lower bounds for genera of components of fiber products of holomorphic maps between compact Riemann surfaces, extending results on genera of components of algebraic curves of the form $A(x)-B(y)=0,$ where $A$ and $B$ are rational functions.

Jory Griffin

It is a fundamental problem in mathematical physics to derive macroscopic transport equations from microscopic models. In this paper we derive the linear Boltzmann equation in the low-density limit of a damped quantum Lorentz gas for a large class of deterministic and random scatterer configurations. Previously this result was known only for the single-scatt

Michael Laufer, Erick Fredj

As the computing power of large-scale HPC clusters approaches the Exascale, the gap between compute capabilities and storage systems is ever widening. In particular, the popular High Performance Computing (HPC) application, the Weather Research and Forecasting Model (WRF) is being currently being utilized for high resolution forecasting and research which ge

Jiayu Chen, Jingdi Chen, Tian Lan, Vaneet Aggarwal

Covering skill (a.k.a., option) discovery has been developed to improve the exploration of reinforcement learning in single-agent scenarios with sparse reward signals, through connecting the most distant states in the embedding space provided by the Fiedler vector of the state transition graph. However, these option discovery methods cannot be directly exten

Yubo Zhuang, Xiaohui Chen, Yun Yang

Semidefinite programming (SDP) is a powerful tool for tackling a wide range of computationally hard problems such as clustering. Despite the high accuracy, semidefinite programs are often too slow in practice with poor scalability on large (or even moderate) datasets. In this paper, we introduce a linear time complexity algorithm for approximating an SDP rel

Hugo Vanneuville

In this paper, we consider Bernoulli percolation on a locally finite, transitive and infinite graph (e.g. the hypercubic lattice $\mathbb{Z}^d$). We prove the following estimate, where $\theta_n(p)$ is the probability that there is a path of $p$-open edges from $0$ to the sphere of radius $n$: \[ \forall p\in [0,1],\forall m,n \ge 1, \quad \theta_{2n} (p-2\t

Andreas Debrouwere, Lenny Neyt

For certain weighted locally convex spaces $X$ and $Y$ of one real variable smooth functions, we characterize the smooth functions $\varphi: \mathbb{R} \to \mathbb{R}$ for which the composition operator $C_\varphi: X \to Y, \, f \mapsto f \circ \varphi$ is well-defined and continuous. This problem has been recently considered for $X = Y$ being the space $\ma

Stefania De Curtis, Luigi Delle Rose, Andrea Guiggiani, Ángel Gil Muyor

First order phase transitions could play a major role in the early universe, providing important phenomenological consequences, such as the production of gravitational waves and the generation of baryon asymmetry. An important aspect that determines the properties of the phase transition is the dynamics of the true-vacuum bubbles, which is controlled by the

David A. Hague

Phase Coded (PC) waveforms possess desirable Auto-Correlation Function (ACF) properties for use in radar and sonar systems. However, their spectra possess high spectral leakage due to the abrupt phase transitions between the chips in the waveform. This paper describes a method of Continuous Phase Modulation (CPM) to reduce a PC waveform's spectral leakage us

Carmina Fjellström

Performance forecasting is an age-old problem in economics and finance. Recently, developments in machine learning and neural networks have given rise to non-linear time series models that provide modern and promising alternatives to traditional methods of analysis. In this paper, we present an ensemble of independent and parallel long short-term memory (LST

Sagar Dey, Bikash Chandra Paul

We obtain a class of new anisotropic relativistic solution in Einstein Gauss-Bonnet (EGB) gravity with Finch-Skea metric in hydrostatic equilibrium. The relativistic solutions are employed to construct anisotropic stellar models for strange star with MIT Bag equation of state $ p_{r}= \frac{1}{3} \left( \rho - 4 B_{g}\right)$, where $B_{g}$ is the Bag consta

Manas Chakrabortty, Kaushik Sarkar, Abhik Kumar Sanyal

As in the case of Lanczos-Lovelock gravity, the main advantage of F(T) gravity is said to be that it leads to second order field equations, while F(R) gravity theory leads to fourth order equations. We show that it is rather a disadvantage, since it leads to the unresolved issue of `Branched Hamiltonian'. The problem is bypassed in F(R,T) gravity theory.

Yutong Wu, Han Qiu, Tianwei Zhang, Jiwei L

Contrastive learning has become a popular technique to pre-train image encoders, which could be used to build various downstream classification models in an efficient way. This process requires a large amount of data and computation resources. Hence, the pre-trained encoders are an important intellectual property that needs to be carefully protected. It is c

Mustapha Amara

In this paper, we show that the global solution of the surface anisotropic two-dimensional quasi-geostrophic equation with fractional horizontal dissipation and vertical thermal diffusion established by the author in [2] is bounded in Sobolev spaces uniformly with respect to time.

Mingye Xu, Yali Wang, Zhipeng Zhou, Hongbin Xu

Self-supervised learning has not been fully explored for point cloud analysis. Current frameworks are mainly based on point cloud reconstruction. Given only 3D coordinates, such approaches tend to learn local geometric structures and contours, while failing in understanding high level semantic content. Consequently, they achieve unsatisfactory performance in

Karolina Stańczak, Lucas Torroba Hennigen, Adina Williams, Ryan Cotterell

The success of pre-trained contextualized representations has prompted researchers to analyze them for the presence of linguistic information. Indeed, it is natural to assume that these pre-trained representations do encode some level of linguistic knowledge as they have brought about large empirical improvements on a wide variety of NLP tasks, which suggest

Kenneth L. Baker, Dorothy Buck, Danielle O'Donnol, Allison H. Moore

We show that if a composite $\theta$-curve has (proper rational) unknotting number one, then it is the order 2 sum of a (proper rational) unknotting number one knot and a trivial $\theta$-curve. We also prove similar results for 2-strand tangles and knotoids.

Henrik Knierim, Konstantin Batygin, Bertram Bitsch

The inflated radii of giant short-period extrasolar planets collectively indicate that the interiors of hot Jupiters are heated by some anomalous energy dissipation mechanism. Although a variety of physical processes have been proposed to explain this heating, recent statistical evidence points to the confirmation of explicit predictions of the Ohmic dissipa

Loke Durocher, Panagiotis Karras, Andreas Pavlogiannis, Josef Tkadlec

The voter process is a classic stochastic process that models the invasion of a mutant trait $A$ (e.g., a new opinion, belief, legend, genetic mutation, magnetic spin) in a population of agents (e.g., people, genes, particles) who share a resident trait $B$, spread over the nodes of a graph. An agent may adopt the trait of one of its neighbors at any time, w

Jean Ruppert, Marharyta Aleksandrova, Thomas Engel

Topological sorting is an important technique in numerous practical applications, such as information retrieval, recommender systems, optimization, etc. In this paper, we introduce a problem of generalized topological sorting with maximization of choice, that is, of choosing a subset of items of a predefined size that contains the maximum number of equally p

Sudipta Sikder, Rennan Barkana, Itamar Reis, Anastasia Fialkov

The cosmic 21-cm line of hydrogen is expected to be measured in detail by the next generation of radio telescopes. The enormous dataset from future 21-cm surveys will revolutionize our understanding of early cosmic times. We present a machine learning approach based on an Artificial Neural Network that uses emulation in order to uncover the astrophysics in t

Alvaro Carbonero, Patrick Hompe, Benjamin Moore, Sophie Spirkl

We prove that for every $n$, there is a graph $G$ with $\chi(G) \geq n$ and $\omega(G) \leq 3$ such that every induced subgraph $H$ of $G$ with $\omega(H) \leq 2$ satisfies $\chi(H) \leq 4$. This disproves a well-known conjecture. Our construction is a digraph with bounded clique number, large dichromatic number, and no induced directed cycles of odd length

Alexandre Maksoud

We generalize Waldschmidt's bound for Leopoldt's defect and prove a similar bound for Gross's defect for an arbitrary extension of number fields. As an application, we prove new cases of Gross's finiteness conjecture (also known as the Gross-Kuz'min conjecture) beyond the classical abelian case, and we show that Gross's $p$-adic regulator has at least half o

Charalampos Orfanidis, Paul Pop, Xenofon Fafoutis

Time Slotted Channel Hopping (TSCH) is a medium access protocol defined in the IEEE 802.15.4 standard which have been proven to be one of the most reliable options when it comes to industrial applications. TSCH has been designed to be utilized in static network topologies. Thus, if an application scenario requires a mobile network topology, TSCH does not per

Riccardo Rubei, Davide Di Ruscio, Claudio Di Sipio, Juri Di Rocco

During the development of a software project, developers often need to upgrade third-party libraries (TPLs), aiming to keep their code up-to-date with the newest functionalities offered by the used libraries. In most cases, upgrading used TPLs is a complex and error-prone activity that must be carefully carried out to limit the ripple effects on the software

Manuel Meucci

The MEG II experiment at Paul Scherrer Institute (PSI) in Switzerland aims to achieve a sensitivity of $6\times10^{-14}$ on the charged lepton flavor violating decay $\mu^+\to e^+\gamma$. The current upper limit on this decay is $4.2\times10^{-13}$ at 90% Confidence Level (CL), set by the first phase of MEG. This result was achieved using the PSI muon beam a

Olivier Bournez, Quentin Guilmant

Surreal numbers, have a very rich and elegant theory. This class of numbers, denoted by No, includes simultaneously the ordinal numbers and the real numbers, and forms a universal huge real closed field: It is universal in the sense that any real closed field can be embedded in it. Following Gonshor, surreal numbers can also be seen as signs sequences of ord

Feifei Miao, Liguang Wang, Wei Yuan

The product systems over left cancellative small categories are introduced and studied in this paper. We also introduce the notion of compactly aligned product systems over finite aligned left cancellative small categories and its Nica covariant representations. The existence of co-universal algebras for injective, gauge-compatible, Nica covariant representa

Junyan Yang, Yang Jiang, Shuoyao Wang

The rapid development of multimedia and communication technology has resulted in an urgent need for high-quality video streaming. However, robust video streaming under fluctuating network conditions and heterogeneous client computing capabilities remains a challenge. In this paper, we consider an enhancement-enabled video streaming network under a time-varyi

Tommaso Rosati, András Tóbiás

We consider a Fisher-KPP equation with nonlinear selection driven by a Poisson random measure. We prove that the equation admits a unique wave speed $ \mathfrak{s}> 0 $ given by $\frac{\mathfrak{s}^{2}}{2} = \int_{[0, 1]}\frac{ \log{(1 + y)}}{y} \mathfrak{R}( \mathrm d y)$ where $ \mathfrak{R} $ is the intensity of the impacts of the driving noise. Our argum

Z. Ong, P. Agarwal, H. W. Ang, A. H. Chan

The method of horizontal scaled factorial moments as outlined by Bialas and Peschanski was used to conduct intermittency analysis for $pp$ collisions at $\sqrt{s}=$ 0.9, 7 and 8 TeV from the CMS experiment. The data was obtained and processed from the CERN Open Data Portal. It was found from 1D analysis that the intermittency strength decreases with increasi

Stefan H. Sack, Raimel A. Medina, Alexios A. Michailidis, Richard Kueng

Variational quantum algorithms are promising algorithms for achieving quantum advantage on near-term devices. The quantum hardware is used to implement a variational wave function and measure observables, whereas the classical computer is used to store and update the variational parameters. The optimization landscape of expressive variational ans\"atze is ho

Zhen Yu, Xiaosen Wang, Wanxiang Che, Kun He

Existing textual adversarial attacks usually utilize the gradient or prediction confidence to generate adversarial examples, making it hard to be deployed in real-world applications. To this end, we consider a rarely investigated but more rigorous setting, namely hard-label attack, in which the attacker can only access the prediction label. In particular, we

Biagio Cassano, Vladimir Lotoreichik

We consider the massless Dirac operator with the MIT bag boundary conditions on an unbounded three-dimensional circular cone. For convex cones, we prove that this operator is self-adjoint defined on four-component $H^1$--functions satisfying the MIT bag boundary conditions. The proof of this result relies on separation of variables and spectral estimates for

Jialin Hong, Baohui Hou, Qiang Li, Liying Sun

Stochastic Hamiltonian partial differential equations, which possess the multi-symplectic conservation law, are an important and fairly large class of systems. The multi-symplectic methods inheriting the geometric features of stochastic Hamiltonian partial differential equations provide numerical approximations with better numerical stability, and are of vit

Wendong Huo, Chang Liu, Zongliang Du, Xudong Jiang

In the present paper, an integrated paradigm for topology optimization on complex surfaces with arbitrary genus is proposed. The approach is constructed based on the two-dimensional (2D) Moving Morphable Component (MMC) framework, where a set of structural components are used as the basic units of optimization, and computational conformal mapping (CCM) techn

Victor Arnaiz, Chenmin Sun

In this article we study the semiclassical resolvent estimate for the non-selfadjoint Baouendi-Grushin operator on the two-dimensional torus $\mathbb{T}^2=\mathbb{R}^2/(2\pi\mathbb{Z})^2$ with H\"older dampings. The operator is subelliptic degenerating along the vertical direction at $x=0$. We exhibit three different situations: (i) the damping region verifi

K. J. Andersen, D. Herman, R. Aurlien, R. Banerji

We present the intensity foreground algorithms and model employed within the BeyondPlanck analysis framework. The BeyondPlanck analysis is aimed at integrating component separation and instrumental parameter sampling within a global framework, leading to complete end-to-end error propagation in the $Planck$ Low Frequency Instrument (LFI) data analysis. Given

Shiqi Gong, Qi Meng, Jue Zhang, Huilin Qu

Deep learning methods have been increasingly adopted to study jets in particle physics. Since symmetry-preserving behavior has been shown to be an important factor for improving the performance of deep learning in many applications, Lorentz group equivariance - a fundamental spacetime symmetry for elementary particles - has recently been incorporated into a

Simon Bing, Andrea Dittadi, Stefan Bauer, Patrick Schwab

The widespread adoption of electronic health records (EHRs) and subsequent increased availability of longitudinal healthcare data has led to significant advances in our understanding of health and disease with direct and immediate impact on the development of new diagnostics and therapeutic treatment options. However, access to EHRs is often restricted due t

M. H. Oliveira, H. S. Borges, J. A. Souza, C. J. Villas-Boas

We theoretically investigate the optical bistability phenomenon in an ensemble of $N$ non-interacting three-level atoms trapped inside an optical cavity. The atoms are in a $\Lambda$-level configuration, where one atomic transition is coupled by a cavity mode, while the other one is coupled by a classical field. In addition, we consider a pumping field drivi

Agnieszka Kleszcz, Krzysztof Rusek

Nowadays innovation is one of the main determinants of economic development. Patents are a key measure of innovation output, as patent indicators reflect the inventive performance of countries, technologies and firms. This paper provides new insights on the causal effects of the enlargement of the European Union (EU) by investigating the patents performance

Z. Ong, P. Agarwal, H. W. Ang, A. H. Chan

Multifractal analysis was performed on $pp$ collision data at $\sqrt{s}=$ 0.9, 7 and 8 TeV from the CMS experiment at CERN. The data was obtained and processed from the CERN Open Data Portal. Vertical analysis was used to compute the generalised dimensions $D_q$ and the multifractal spectra $f(\alpha)$ of the data, which reveals the level of complexity of it

Konstantinos E. Tatsis, Vasilis K. Dertimanis, Eleni N. Chatzi

In this article, an overview of Bayesian methods for sequential simulation from posterior distributions of nonlinear and non-Gaussian dynamic systems is presented. The focus is mainly laid on sequential Monte Carlo methods, which are based on particle representations of probability densities and can be seamlessly generalized to any state-space representation

Z. Ong, P. Agarwal, H. W. Ang, A. H. Chan

A Chou-Yang type multiplicity distribution comprising a total multiplicity component and a binomial asymmetry component is used to describe charged hadron multiplicity data at $\sqrt{s}=$ 0.9, 7 and 8 TeV from the CMS experiment at CERN. The data was obtained and processed from the CERN Open Data Portal. For the total multiplicity component, it was found tha