October 2020 arXiv papers — page 32

Yen Dieu Pham, Lloyd Montgomery, Walid Maalej

Legacy software systems typically include vital data for organizations that use them and should thus to be regularly maintained. Ideally, organizations should rely on Requirements Engineers to understand and manage changes of stakeholder needs and system constraints. However, due to time and cost pressure, and with a heavy focus on implementation, organizati

Haiguang Liao, Qingyi Dong, Weiyi Qi, Elias Fallon

Detailed routing is one of the most critical steps in analog circuit design. Complete routing has become increasingly more challenging in advanced node analog circuits, making advances in efficient automatic routers ever more necessary. In this work, we propose a machine learning driven method for solving the track-assignment detailed routing problem for adv

Sara Casao, Abel Naya, Ana C. Murillo, Eduardo Montijano

Most recent works on multi-target tracking with multiple cameras focus on centralized systems. In contrast, this paper presents a multi-target tracking approach implemented in a distributed camera network. The advantages of distributed systems lie in lighter communication management, greater robustness to failures and local decision making. On the other hand

Gabriele Sicuro, Lenka Zdeborová

We consider the problem of recovering an unknown $k$-factor, hidden in a weighted random graph. For $k=1$ this is the planted matching problem, while the $k=2$ case is closely related to the planted travelling salesman problem. The inference problem is solved by exploiting the information arising from the use of two different distributions for the weights on

Felix Lüpke, Dacen Waters, Anh D. Pham, Jiaqiang Yan

The quantum spin Hall (QSH) effect, characterized by topologically protected spin-polarized edge states, was recently demonstrated in monolayers of the transition metal dichalcogenide (TMD) WTe$_2$. However, the robustness of this topological protection remains largely unexplored in van der Waals heterostructures containing one or more layers of a QSH insula

P. M. Ferreira, B. Grzadkowski, O. M. Ogreid, P. Osland

Symmetries of the Two-Higgs-Doublet Model (2HDM) potential that can be extended to the whole Lagrangian, i.e. the CP-symmetries CP1, CP2, CP3 and the Higgs-family symmetries Z2, U(1) and SO(3) are discussed. Sufficient and necessary conditions in terms of constraints on masses and physical couplings for the potential to respect each of these symmetries are f

Kristina Wolfe, Douglas Swanson, Rupert Till

The Hal Saflieni Hypogeum is a unique subterranean Maltese Neolithic sanctuary with a well-documented history of interest in its acoustics. Previous studies have noted its unusual strongly-defined frequency spectrum, but it is unknown if this was coincidental. In this paper, we present evidence that the Hypogeum's creators shaped the site's geometry to creat

Shengquan Xiang

We provide explicit time-varying feedback laws that locally stabilize the two dimensional internal controlled incompressible Navier-Stokes equations in arbitrarily small time. We also obtain quantitative rapid stabilization via stationary feedback laws, as well as quantitative null controllability with explicit controls having $e^{C/T}$ costs.

Shyam Sundar Ghoshal, John D. Towers, Ganesh Vaidya

In this article, we consider scalar conservation laws with fluxes having spatial discontinuities and possible flat regions and study the following three aspects: (i) existence, (ii) uniqueness and (iii) BV regularity of solutions. We propose a uniqueness condition and prove existence of a weak solution via the method of wave front tracking. In the later part

Brandon Mattingly, Abinash Kar, Matthew Gorban, William Julius

A process for using curvature invariants is applied to evaluate the metrics for the Alcubierre and the Natario warp drives at a constant velocity.Curvature invariants are independent of coordinate bases, so plotting these invariants will be free of coordinate mapping distortions. As a consequence, they provide a novel perspective into complex spacetimes such

Paul Seidel

We (re)consider how the Fukaya category of a Lefschetz fibration is related to that of the fibre. The distinguishing feature of the approach here is a more direct identification of the bimodule homomorphism involved.

Christopher Torres-Lugo, Kai-Cheng Yang, Filippo Menczer

A growing body of evidence points to critical vulnerabilities of social media, such as the emergence of partisan echo chambers and the viral spread of misinformation. We show that these vulnerabilities are amplified by abusive behaviors associated with so-called "follow trains" on Twitter, in which long lists of like-minded accounts are mentioned for others

R. Engels, M. Büscher, P. Buske, Y. Gan

The origin of quantum physics was the discovery of the base unit of electromagnetic action $h$ by Max Planck in 1900 when he analyzed the experimental results of the black body radiation. This permitted Albert Einstein a few years later to explain the photoelectric effect by the absorption of photons with an energy of $E = h \cdot f$. We exploit the Planck-E

Marcela Peláez, Urko Reinosa, Julien Serreau, Matthieu Tissier

We investigate the spontaneous breaking of chiral symmetry in QCD by means of a recently proposed approximation scheme in the Landau-gauge Curci-Ferrari model, which combines an expansion in the Yang-Mills coupling and in the inverse number of colors, without expanding in the quark-gluon coupling. The expansion allows for a consistent treatment of ultraviole

Laura Rado, Victor O. Rivelles, Renato Sánchez

We consider three-parameter Yang-Baxter deformations of the $AdS_5\times T^{1,1}$ superstring for abelian $r$-matrices which are solutions of the classical Yang-Baxter equation. We find two new backgrounds which are dual to the dipole deformed Klebanov-Witten gauge theory and to the nonrelativistic Klebanov-Witten gauge theory with Schr\"odinger symmetry

Alexander Kalinowski, Yuan An

Neural embedding approaches have become a staple in the fields of computer vision, natural language processing, and more recently, graph analytics. Given the pervasive nature of these algorithms, the natural question becomes how to exploit the embedding spaces to map, or align, embeddings of different data sources. To this end, we survey the current research

Stéphane Guerrier, Mucyo Karemera, Samuel Orso, Maria-Pia Victoria-Feser

An important challenge in statistical analysis lies in controlling the bias of estimators due to the ever-increasing data size and model complexity. Approximate numerical methods and data features like censoring and misclassification often result in analytical and/or computational challenges when implementing standard estimators. As a consequence, consistent

Gaétan Laurens, Malalatiana Rabary, Julien Lam, Daniel Peláez

The Interest in polycyclic aromatic hydrocarbons (PAHs) spans numerous fields and infrared spectroscopy is usually the method of choice to disentangle their molecular structure. In order to compute vibrational frequencies, numerous theoretical studies employ either quantum calculation methods, or empirical potentials, but it remains difficult to combine the

Veronica Chelu, Doina Precup, Hado van Hasselt

We address the problem of credit assignment in reinforcement learning and explore fundamental questions regarding the way in which an agent can best use additional computation to propagate new information, by planning with internal models of the world to improve its predictions. Particularly, we work to understand the gains and peculiarities of planning empl

Colin Werner, Lloyd Montgomery, Sanja Dodos, Gabriel Tapuc

Software support ticket escalations can be an extremely costly burden for software organizations all over the world. Consequently, there exists an interest in researching how to better enable support analysts to handle such escalations. In order to do so, we need to develop tools to reliably predict if, and when, a support ticket becomes a candidate for esca

Jérémie Quevillon, Christopher Smith

The simultaneous embeddings of an axion state and a seesaw mechanism within the SU(5) Grand Unification Theory, both minimal and flipped, are systematically studied. It is shown that whenever B-L is active as a global symmetry, the PQ charges of the fermions are ambiguous. Various realizations of the seesaw mechanism are then found to differ only in the way

Timothy DeLise

This research proposes a data segmentation algorithm which combines t-SNE, DBSCAN, and Random Forest classifier to form an end-to-end pipeline that separates data into natural clusters and produces a characteristic profile of each cluster based on the most important features. Out-of-sample cluster labels can be inferred, and the technique generalizes well on

Vaastav Anand, Matheus Stolet, Thomas Davidson, Ivan Beschastnikh

Performance issues in cloud systems are hard to debug. Distributed tracing is a widely adopted approach that gives engineers visibility into cloud systems. Existing trace analysis approaches focus on debugging single request correctness issues but not debugging single request performance issues. Diagnosing a performance issue in a given request requires comp

Weiyao Ke, Xin-Nian Wang

We study inclusive jet suppression and modifications in the quark-gluon plasma (QGP) with a transport-based model. The model includes vacuum-like parton shower evolution at high-virtuality, a linearized transport for jet-medium interactions, and a simple ansatz for the jet-induced hydrodynamic response of the medium. Model parameters are calibrated to nuclea

Alexandra Carpentier, Olivier Collier, Laetitia Comminges, Alexandre B. Tsybakov

We consider the related problems of estimating the $l_2$-norm and the squared $l_2$-norm in sparse linear regression with unknown variance, as well as the problem of testing the hypothesis that the regression parameter is null under sparse alternatives with $l_2$ separation. We establish the minimax optimal rates of estimation (respectively, testing) in thes

V. Beylin, M. Khlopov, V. Kuksa, N. Volchanskiy

The history of dark universe physics can be traced from processes in the very early universe to the modern dominance of dark matter and energy. Here, we review the possible nontrivial role of strong interactions in cosmological effects of new physics. In the case of ordinary QCD interaction, the existence of new stable colored particles such as new stable qu

Wenqi Huang, Ziwen Ke, Zhuo-Xu Cui, Jing Cheng

In dynamic magnetic resonance (MR) imaging, low-rank plus sparse (L+S) decomposition, or robust principal component analysis (PCA), has achieved stunning performance. However, the selection of the parameters of L+S is empirical, and the acceleration rate is limited, which are common failings of iterative compressed sensing MR imaging (CS-MRI) reconstruction

Zhiqi Kang, Mostafa Sadeghi, Radu Horaud

Face frontalization consists of synthesizing a frontally-viewed face from an arbitrarily-viewed one. The main contribution of this paper is a robust face alignment method that enables pixel-to-pixel warping. The method simultaneously estimates the rigid transformation (scale, rotation, and translation) and the non-rigid deformation between two 3D point sets:

Thomas Colcombet, Daniela Petrişan, Riccardo Stabile

In this paper, we present a categorical approach to learning automata over words, in the sense of the $L^*$-algorithm of Angluin. This yields a new generic $L^*$-like algorithm which can be instantiated for learning deterministic automata, automata weighted over fields, as well as subsequential transducers. The generic nature of our algorithm is obtained by

Thiemo Wambsganss, Christina Niklaus, Matthias Söllner, Siegfried Handschuh

In this paper, we present a novel annotation approach to capture claims and premises of arguments and their relations in student-written persuasive peer reviews on business models in German language. We propose an annotation scheme based on annotation guidelines that allows to model claims and premises as well as support and attack relations for capturing th

Chao Zhang, Jin Zhang, Jin Yang, Barbara Capogrosso-Sansone

Motivated by recent experiments with ultracold magnetic atoms trapped in optical lattices where the orientation of atomic dipoles can be fully controlled by external fields, we study the ground state properties of dipolar bosons trapped in a two-dimensional lattice with density-induced hopping and where the dipoles are tilted along the $xz$ plane. We present

J. Blümlein, A. Maier, P. Marquard, G. Schäfer

We calculate the potential contributions of the motion of binary mass systems in gravity to the fifth post--Newtonian order ab initio using coupling and velocity expansions within an effective field theory approach based on Feynman amplitudes starting with harmonic coordinates and using dimensional regularization. Furthermore, the singular and logarithmic ta

A. Stupakiewicz, C. S. Davies, K. Szerenos, D. Afanasiev

Identifying an efficient pathway to change the order parameter via a subtle excitation of the coupled high-frequency mode is the ultimate goal of the field of ultrafast phase transitions. This is an especially interesting research direction in magnetism, where the coupling between spin and lattice excitations is required for magnetization reversal. Despite s

Adam Leah W. Harvey, Markos Georganopoulos, Eileen T. Meyer

Accretion onto the supermassive black hole in some active galactic nuclei (AGN) drives relativistic jets of plasma, which dissipate a significant fraction of their kinetic energy into gamma-ray radiation. The location of energy dissipation in powerful extragalactic jets is currently unknown, with implications for particle acceleration, jet formation, jet col

Alejandro Vigna-Gómez, Silvia Toonen, Enrico Ramirez-Ruiz, Nathan W. C. Leigh

Stellar triples with massive stellar components are common, and can lead to sequential binary black-hole mergers. Here, we outline the evolution towards these sequential mergers, and explore these events in the context of gravitational-wave astronomy and the pair-instability mass gap. We find that binary black-hole mergers in the pair-instability mass gap ca

Tuomas P. Oikarinen, Daniel C. Hannah, Sohrob Kazerounian

The recent introduction of Graph Neural Networks (GNNs) and their growing popularity in the past few years has enabled the application of deep learning algorithms to non-Euclidean, graph-structured data. GNNs have achieved state-of-the-art results across an impressive array of graph-based machine learning problems. Nevertheless, despite their rapid pace of d

Jie Ma, Long-Tu Yuan

Combining P\'{o}sa's rotation lemma with a technique of Kopylov in a novel approach, we prove a generalization of the Erd\H{o}s-Gallai theorems on cycles and paths. This implies a clique version of the Erd\H{o}s-Gallai stability theorems and also provides alternative proofs for some recent results.

Dallas Wulf, Felix Jaeckel, Dan McCammon, James A Chervenak

Here we present a general algorithm for processing microcalorimeter data with special applicability to data with high photon count rates. Conventional optimal filtering, which has become ubiquitous in microcalorimeter data processing, suffers from its inability to recover overlapped pulses without sacrificing spectral resolution. The technique presented here

Tianqi Xiao, Omer Nguena Timo, Florent Avellaneda, Yasir Malik

Learning algorithms produce software models for realising critical classification tasks. Decision trees models are simpler than other models such as neural network and they are used in various critical domains such as the medical and the aeronautics. Low or unknown learning ability algorithms does not permit us to trust the produced software models, which le

Philippe Gaucher

Erratum, 11 July 2022: This is an updated version of the original paper in which the notion of reparametrization category was incorrectly axiomatized. Details on the changes to the original paper are provided in the Appendix. A reparametrization category is a small topologically enriched semimonoidal category such that the semimonoidal structure induces a st

Prazwal Chhabra, Rizwan Ali, Vikram Pudi

Team Recommendation has always been a challenging aspect in team sports. Such systems aim to recommend a player combination best suited against the opposition players, resulting in an optimal outcome. In this paper, we propose a semi-supervised statistical approach to build a team recommendation system for cricket by modelling players into embeddings. To bui

Lukas Faber, Amin K. Moghaddam, Roger Wattenhofer

Graph Neural Networks achieve remarkable results on problems with structured data but come as black-box predictors. Transferring existing explanation techniques, such as occlusion, fails as even removing a single node or edge can lead to drastic changes in the graph. The resulting graphs can differ from all training examples, causing model confusion and wron

Shun-Cheng Wu, Keisuke Tateno, Nassir Navab, Federico Tombari

Real-time scene reconstruction from depth data inevitably suffers from occlusion, thus leading to incomplete 3D models. Partial reconstructions, in turn, limit the performance of algorithms that leverage them for applications in the context of, e.g., augmented reality, robotic navigation, and 3D mapping. Most methods address this issue by predicting the miss

Marat Akhmet

We find that Markov chains with finite state space are Poincare chaotic. Moreover, finite realizations of the chains are arcs of each unpredictable orbit for sure. An illustrating example with a proper numerical simulation is provided.

Benoît Collins, Razvan Gurau, Luca Lionni

We study a generalization of the Harish-Chandra - Itzykson - Zuber integral to tensors and its expansion over trace-invariants of the two external tensors. This gives rise to natural generalizations of monotone double Hurwitz numbers, which count certain families of constellations. We find an expression of these numbers in terms of monotone simple Hurwitz nu

Konstantinos Ntemos, Virginia Bordignon, Stefan Vlaski, Ali H. Sayed

A common assumption in the social learning literature is that agents exchange information in an unselfish manner. In this work, we consider the scenario where a subset of agents aims at driving the network beliefs to the wrong hypothesis. The adversaries are unaware of the true hypothesis. However, they will "blend in" by behaving similarly to the other agen

Liang Yao, Baosong Yang, Haibo Zhang, Weihua Luo

As a crucial role in cross-language information retrieval (CLIR), query translation has three main challenges: 1) the adequacy of translation; 2) the lack of in-domain parallel training data; and 3) the requisite of low latency. To this end, existing CLIR systems mainly exploit statistical-based machine translation (SMT) rather than the advanced neural machi

Tianchi Bi, Liang Yao, Baosong Yang, Haibo Zhang

Query translation (QT) is a key component in cross-lingual information retrieval system (CLIR). With the help of deep learning, neural machine translation (NMT) has shown promising results on various tasks. However, NMT is generally trained with large-scale out-of-domain data rather than in-domain query translation pairs. Besides, the translation model lacks

Simon Felten, Andrea Petracci

We prove that the log smooth deformations of a proper log smooth saturated log Calabi-Yau space are unobstructed.

Prabal Adhikari, Jens O. Andersen, Martin A. Mojahed

We consider two-flavor chiral perturbation theory ($\chi$PT) at finite isospin chemical potential $\mu_I$ and finite temperature $T$. We calculate the effective potential and the quark and pion condensates as functions of $T$ and $\mu_I$ to next-to-leading order in the low-energy expansion in the presence of a pionic source. We map out the phase diagram in t

Michele Trabucchi, Peter R. Wood, Nami Mowlavi, Giada Pastorelli

Long-period variability in luminous red giants has several promising applications, all of which require models able to accurately predict pulsation periods. Linear pulsation models have proven successful in reproducing the observed periods of overtone modes in evolved red giants, but they fail to accurately predict their fundamental mode periods. Here, we us

Nicole E. Pashley, Luke W. Miratrix

Several branches of the potential outcome causal inference literature have discussed the merits of blocking versus complete randomization. Some have concluded it can never hurt the precision of estimates, and some have concluded it can hurt. In this paper, we reconcile these apparently conflicting views, give a more thorough discussion of what guarantees no

Antonino De Martino, Arianna Passerini

In most fluid dynamics problems, the governing equations are nonlinear because of the presence of convective terms. Nevertheless, existence of solutions can be shown by direct sum provided one identifies, in the relevant Banach space of solutions, particular subspaces which are invariant under time evolution. As an example, we consider classical convection p

Thomas Winters, Pieter Delobelle

Detecting if a text is humorous is a hard task to do computationally, as it usually requires linguistic and common sense insights. In machine learning, humor detection is usually modeled as a binary classification task, trained to predict if the given text is a joke or another type of text. Rather than using completely different non-humorous texts, we propos

ATLAS Collaboration

A search is presented for the production of the Standard Model Higgs boson in association with a high-energy photon. With a focus on the vector-boson fusion process and the dominant Higgs boson decay into $b$-quark pairs, the search benefits from a large reduction of multijet background compared to more inclusive searches. Results are reported from the analy

Lyne Van de Vyvere, Dominique Sluse, Sampath Mukherjee, Dandan Xu

Strong gravitational lensing is a powerful tool to measure cosmological parameters and to study galaxy evolution mechanisms. However, quantitative strong lensing studies often require mock observations. To capture the full complexity of galaxies, the lensing galaxy is often drawn from high resolution, dark matter only or hydro-dynamical simulations. These ha

Tianbai Xiao, Martin Frank

One of the biggest challenges for simulating the Boltzmann equation is the evaluation of fivefold collision integral. Given the recent successes of deep learning and the availability of efficient tools, it is an obvious idea to try to substitute the evaluation of the collision operator by the evaluation of a neural network. However, it is unlcear whether thi

Giacomo Ferroni, Nicolas Turpault, Juan Azcarreta, Francesco Tuveri

The ranking of sound event detection (SED) systems may be biased by assumptions inherent to evaluation criteria and to the choice of an operating point. This paper compares conventional event-based and segment-based criteria against the Polyphonic Sound Detection Score (PSDS)'s intersection-based criterion, over a selection of systems from DCASE 2020 Challen

S. R. Valluri, V. Dergachev, X. Zhang, F. A. Chishtie

The direct detection of continuous gravitational waves from pulsars is a much anticipated discovery in the emerging field of multi-messenger gravitational wave (GW) astronomy. Because putative pulsar signals are exceedingly weak large amounts of data need to be integrated to achieve desired sensitivity. Contemporary searches use ingenious ad-hoc methods to r

Dongbin Shin, Shunsuke A. Sato, Hannes Hübener, Umberto De Giovannini

Ultrafast optical control of ferroelectricity using intense terahertz fields has attracted significant interest. Here we show that the nonlinear interactions between two optical phonons in SnTe, a two-dimensional in-plane ferroelectric material, enables a dynamical amplification of the electric polarization within subpicoseconds time domain. Our first princi

Maiyu Diaz

Let $f$ be a real-valued function of a single variable such that it is positive over the primes. In this article, we construct a factorial, $n!_f$, associated to $f$, called the associated Legendre formula, or $f$-factorial, and show, subject to certain criteria, that $n!_f$ satisfies a weak Stirling approximation. As an application, we will give weak approx

Nicolò Piccione, Benedetto Militello, Anna Napoli, Bruno Bellomo

Quantum technologies exploiting bipartite entanglement could be made more efficient by using states having the minimum amount of energy for a given entanglement degree. Here, we study how to generate these states in the case of a bipartite system of arbitrary finite dimension either by applying a unitary transformation to its ground state or through a zero-t

Soham Chandra

Trilayered spin-1/2 Ising ferrimagnets are interesting thin systems for compensation phenomenon. In this work, a Metropolis Monte Carlo study is performed on the magnetic and thermodynamic response of such a system on square Bravais lattice, driven by uniform random external magnetic field with spatio-temporal variations. In two distinct configurations, the

Zhiwei Yun

We introduce the notion of minimal reduction type of an affine Springer fiber, and use it to define a map from the set of conjugacy classes in the Weyl group to the set of nilpotent orbits. We show that this map is the same as the one defined by Lusztig, and that the Kazhdan-Lusztig map is a section of our map. This settles several conjectures in the literat

Timo Schick, Helmut Schmid, Hinrich Schütze

A recent approach for few-shot text classification is to convert textual inputs to cloze questions that contain some form of task description, process them with a pretrained language model and map the predicted words to labels. Manually defining this mapping between words and labels requires both domain expertise and an understanding of the language model's

Zijie Zhuang

We prove the existence of non-trivial phase transitions for the intersection of two independent random interlacements and the complement of the intersection. Some asymptotic results about the phase curves are also obtained. Moreover, we show that at least one of these two sets percolates in high dimensions.

Naman Agarwal, Rohan Anil, Tomer Koren, Kunal Talwar

State-of-the-art optimization is steadily shifting towards massively parallel pipelines with extremely large batch sizes. As a consequence, CPU-bound preprocessing and disk/memory/network operations have emerged as new performance bottlenecks, as opposed to hardware-accelerated gradient computations. In this regime, a recently proposed approach is data echoi

Chen Wang, Dian-Wang Hu

In this paper, we prove some supercongruences concerning truncated hypergeometric series. For example, we show that for any prime $p>3$ and positive integer $r$, $$ \sum_{k=0}^{p^r-1}(3k+1)\frac{(\frac12)_k^3}{(1)_k^3}4^k\equiv p^r+\frac76p^{r+3}B_{p-3}\pmod{p^{r+4}} $$ and $$ \sum_{k=0}^{(p^r-1)/2}(4k+1)\frac{(\frac12)_k^4}{(1)_k^4}\equiv p^r+\frac76p^{r+3}

Peng Gao, Fei Shao, Xiaoyuan Liu, Xusheng Xiao

Log-based cyber threat hunting has emerged as an important solution to counter sophisticated attacks. However, existing approaches require non-trivial efforts of manual query construction and have overlooked the rich external threat knowledge provided by open-source Cyber Threat Intelligence (OSCTI). To bridge the gap, we propose ThreatRaptor, a system that

Yuehua Zhu, Muli Yang, Cheng Deng, Wei Liu

Deep metric learning plays a key role in various machine learning tasks. Most of the previous works have been confined to sampling from a mini-batch, which cannot precisely characterize the global geometry of the embedding space. Although researchers have developed proxy- and classification-based methods to tackle the sampling issue, those methods inevitably

Changhui Song, Shicai Zhu, Liran Ma, Yu Tian

One easy-make, flexible information storage and display device is prepared. The device show memory effect, which can record the friction trace in real time through the triboelectric effect, and then reproduce the trajectory under the excitation of any kind of polar liquid droplet, completely display the triboelectric area. The explanation mechanism of this p

Rahul Mohideen Kaja Mohideen, Pascal Peter, Joachim Weickert

Inpainting-based compression represents images in terms of a sparse subset of its pixel data. Storing the carefully optimised positions of known data creates a lossless compression problem on sparse and often scattered binary images. This central issue is crucial for the performance of such codecs. Since it has only received little attention in the literatur

József Balogh, Ander Lamaison

The study of upper density problems on Ramsey theory was initiated by Erd\H{o}s and Galvin in 1993. In this paper we are concerned with the following problem: given a fixed finite graph $F$, what is the largest value of $\lambda$ such that every 2-edge-coloring of the complete graph on $\mathbb{N}$ contains a monochromatic infinite $F$-factor whose vertex se

Erik Bodin, Zhenwen Dai, Neill D. F. Campbell, Carl Henrik Ek

We present a novel approach to Bayesian inference and general Bayesian computation that is defined through a sequential decision loop. Our method defines a recursive partitioning of the sample space. It neither relies on gradients nor requires any problem-specific tuning, and is asymptotically exact for any density function with a bounded domain. The output

Yiwen Liao, Raphaël Latty, Bin Yang

Feature selection is generally used as one of the most important preprocessing techniques in machine learning, as it helps to reduce the dimensionality of data and assists researchers and practitioners in understanding data. Thereby, by utilizing feature selection, better performance and reduced computational consumption, memory complexity and even data amou

N. S. Gonchar

The general method is proposed for constructing a family of martingale measures for a wide class of evolution of risky assets. The sufficient conditions are formulated for the evolution of risky assets under which the family of equivalent martingale measures to the original measure is a non-empty set. The set of martingale measures is constructed from a set

Saray Busto, Michael Dumbser, Elena Gaburro

We present a simple but efficient concept for the realization of blended teaching of mathematics and its applications in theoretical mechanics that was conceived, tested and implemented at the University of Trento, Italy, during the COVID-19 pandemic. The concept foresees traditional blackboard lectures with a reduced number of students present in the lectur

Junaid Ahmed Ghauri, Sherzod Hakimov, Ralph Ewerth

Videos are a commonly-used type of content in learning during Web search. Many e-learning platforms provide quality content, but sometimes educational videos are long and cover many topics. Humans are good in extracting important sections from videos, but it remains a significant challenge for computers. In this paper, we address the problem of assigning imp

Yong Wang

The software patterns provide building blocks to the design and implementation of a software system, and try to make the software engineering to progress from experience to science. The software patterns were made famous because of the introduction as the design patterns. After that, patterns have been researched and developed widely and rapidly. The series

P. Charlot, C. S. Jacobs, D. Gordon, S. Lambert

A new realization of the International Celestial Reference Frame (ICRF) is presented based on the work achieved by a working group of the International Astronomical Union (IAU) mandated for this purpose. This new realization, referred to as ICRF3, is based on nearly 40 years of data acquired by very long baseline interferometry. The ICRF3 includes positions

Héctor A. Chang-Lara, Edgard A. Pimentel

We study non-convex Hamilton-Jacobi equations in the presence of gradient constraints and produce new, optimal, regularity results for the solutions. A distinctive feature of those equations regards the existence of a lower bound to the norm of the gradient; it competes with the elliptic operator governing the problem, affecting the regularity of the solutio

Pascal Weckesser, Fabian Thielemann, Daniel Hoenig, Alexander Lambrecht

For conventional ion traps, the trapping potential is close to independent of the electronic state, providing confinement for ions dependent primarily on their charge-to-mass ratio $Q/m$. In contrast, storing ions within an optical dipole trap results in state-dependent confinement. Here we experimentally study optical dipole potentials for $^{138}\mathrm{Ba

D. Karinkuzhi, S. Van Eck, S. Goriely, L. Siess

Among Carbon-Enhanced Metal-Poor (CEMP) stars, some are found to be enriched in s-process elements (CEMP-s), in r-process elements (CEMP-r) or in both s- and r-process elements (CEMP-rs). The origin of the abundance differences between CEMP-s and CEMP-rs stars is presently unknown. It has been claimed that the i-process, whose site still remains to be identi

Jonas Dann, Daniel Ritter, Holger Fröning

Recent trends in business and technology (e.g., machine learning, social network analysis) benefit from storing and processing growing amounts of graph-structured data in databases and data science platforms. FPGAs as accelerators for graph processing with a customizable memory hierarchy promise solving performance problems caused by inherent irregular memor

Xiaocong Xu, Yipei Chen, Kun Xu

The non-equilibrium gas dynamics is described by the Boltzmann equation, which can be solved numerically through the deterministic and stochastic methods. Due to the complicated collision term of the Boltzmann equation, many kinetic relaxation models have been proposed and used in the past seventy years for the study of rarefied flow. In order to develop a m

Tobias Vogt, Susanne Horn, Jonathan M. Aurnou

We present the first detailed thermal and velocity field characterization of convection in a rotating cylindrical tank of liquid gallium, which has thermophysical properties similar to those of planetary core fluids. Our laboratory experiments, and a closely associated direct numerical simulation, are all carried out in the regime prior to the onset of stead

F. Greco, M. Arroyo

This paper considers the approximation of partial differential equations with a point collocation framework based on high-order local maximum-entropy schemes (HOLMES). In this approach, smooth basis functions are computed through an optimization procedure and the strong form of the problem is directly imposed at the collocation points, reducing significantly

Artem Badasyan, Matjaz Valant, Joze Grdadolnik, Vladimir N. Uversky

The coil to globule transition of the polypeptide chain is the physical phenomenon behind the folding of globular proteins. Globular proteins with a single domain usually consist of about 30 to 100 amino acid residues, and this finite size extends the transition interval of the coil-globule phase transition. Based on the pedantic derivation of the two-state

Anurag Ajay, Aviral Kumar, Pulkit Agrawal, Sergey Levine

Reinforcement learning (RL) has achieved impressive performance in a variety of online settings in which an agent's ability to query the environment for transitions and rewards is effectively unlimited. However, in many practical applications, the situation is reversed: an agent may have access to large amounts of undirected offline experience data, while ac

Raj Kishore, Bijaylaxmi Sahoo, Debadatta Swain, Kisor Kumar Sahu

The prediction of spread patterns of COVID19 virus in India is very difficult due to its versatile demographic as well as meteorological data distribution. Various researchers across the globe have attempted to correlate the interdependency of these data with the spread pattern of COVID19 cases in India. But it is hard to predict the exact pattern, especiall

Mircea-Adrian Tanase, Dumitru-Clementin Cercel, Costin-Gabriel Chiru

Offensive language detection is one of the most challenging problem in the natural language processing field, being imposed by the rising presence of this phenomenon in online social media. This paper describes our Transformer-based solutions for identifying offensive language on Twitter in five languages (i.e., English, Arabic, Danish, Greek, and Turkish),

Zhun Gou, Nan-jing Huang, Ming-hui Wang, Jian-hao Kang

In this paper, we solve an optimal control problem governed by a system of mean-field stochastic differential equations with multiple defaults (MMFSDEs). We transform the global optimal control problem into several optimal control subproblems governed by a system of mean-field stochastic differential equations with single default (SMFSDEs) and derive both th

Fabian Hofmann

Power system models are a valuable and widely used tool to determine cost-minimal future operation and investment under political or ecological boundary conditions. Yet they are silent about the allocation of costs of single assets, as generators or transmission lines, to consumers in the network. Existing cost-allocation methods hardly suit large networks a

Fei Li, Mubdi Rahman, Norman Murray, Zachary Hafen

Observations of UV metal absorption lines have provided insight into the structure and composition of the circumgalactic medium (CGM) around galaxies. We compare these observations with the low-redshift ($z \leq 0.3$) CGM around dwarf galaxies in high-resolution cosmological zoom-in runs in the FIRE-2 simulation suite. We select simulated galaxies that match

Emmanuel Trélat

The turnpike phenomenon stipulates that the solution of an optimal control problem in large time, remains essentially close to a steady-state of the dynamics, itself being the optimal solution of an associated static optimal control problem. Under general assumptions, it is known that not only the optimal state and the optimal control, but also the adjoint s

Stefan Stein, Rui Feng, Chenlei Leng

For statistical analysis of network data, the $\beta$-model has emerged as a useful tool, thanks to its flexibility in incorporating nodewise heterogeneity and theoretical tractability. To generalize the $\beta$-model, this paper proposes the Sparse $\beta$-Regression Model (S$\beta$RM) that unites two research themes developed recently in modelling homophil

Ely Kerman, Yuanpu Liang

In this paper we prove that the symplectic Brunn-Minkowski inequality, established by Artstein-Avidan and Ostrover for the Ekeland-Hofer-Zehnder capacity, fails to hold for the Gutt-Hutchings capacities of index greater than one.

Vladimir Yu. Rydyak, Artem V. Sergeev, Elena Yu. Kozhunova, Alexander V. Chertovich

It is well-known that the architecture of macromolecules plays an important role in the hydrodynamics and viscosity of its semi-diluted solutions. However, the systematic study of the rheology of macromolecules with complex topology, such as microgels, remains a difficult task. In this work, we use the computer simulations methods of non-equilibrium molecula

Günther Rüdiger, Manfred Küker

In order to explain the variance of the solar rotation law during the activity minima and maxima, the angular momentum transport by rotating magnetoconvection is simulated in a convective box penetrated by an inclined azimuthal magnetic field. Turbulence-induced kinetic and magnetic stresses { and} the Lorentz force of the large-scale magnetic background fie

Elsa Rizk, Stefan Vlaski, Ali H. Sayed

Federated learning involves a mixture of centralized and decentralized processing tasks, where a server regularly selects a sample of the agents and these in turn sample their local data to compute stochastic gradients for their learning updates. This process runs continually. The sampling of both agents and data is generally uniform; however, in this work w