June 2020 arXiv papers — page 22

Arjan Singh, Okan Koksal, Nicholas Tanen, Jonathan McCandless

$β$-Ga$_2$O$_3$ is an ultra-wide bandgap semiconductor and is thus expected to be optically transparent to light of sub-bandgap wavelengths well into the ultraviolet. Contrary to this expectation, it is found here that free electrons in n-doped $β$-Ga$_2$O$_3$ absorb light from the IR to the UV wavelength range via intra- and inter-conduction band optical tr

Alberto Olmo, Sailik Sengupta, Subbarao Kambhampati

Deep Neural Networks are often brittle on image classification tasks and known to misclassify inputs. While these misclassifications may be inevitable, all failure modes cannot be considered equal. Certain misclassifications (eg. classifying the image of a dog to an airplane) can perplex humans and result in the loss of human trust in the system. Even worse,

Marina A. Ferreira, Jani Lukkarinen, Alessia Nota, Juan J. L. Velázquez

We consider the multicomponent Smoluchowski coagulation equation under non-equilibrium conditions induced either by a source term or via a constant flux constraint. We prove that the corresponding stationary non-equilibrium solutions have a universal localization property. More precisely, we show that these solutions asymptotically localize into a direction

V. A. Traag, M. Malgarini, S. Sarlo

In the past decades, many countries have started to fund academic institutions based on the evaluation of their scientific performance. In this context, post-publication peer review is often used to assess scientific performance. Bibliometric indicators have been suggested as an alternative to peer review. A recurrent question in this context is whether peer

Pjotr Buys, Andreas Galanis, Viresh Patel, Guus Regts

We study the computational complexity of approximating the partition function of the ferromagnetic Ising model with the external field parameter $λ$ on the unit circle in the complex plane. Complex-valued parameters for the Ising model are relevant for quantum circuit computations and phase transitions in statistical physics, but have also been key in the re

Xiangyu Zhao, Haochen Liu, Hui Liu, Jiliang Tang

Practical large-scale recommender systems usually contain thousands of feature fields from users, items, contextual information, and their interactions. Most of them empirically allocate a unified dimension to all feature fields, which is memory inefficient. Thus it is highly desired to assign different embedding dimensions to different feature fields accord

Gunnar S. Bali, Luca Castagnini, Markus Diehl, Jonathan R. Gaunt

We perform a lattice study of double parton distributions in the pion, using the relationship between their Mellin moments and pion matrix elements of two local currents. A good statistical signal is obtained for almost all relevant Wick contractions. We investigate correlations in the spatial distribution of two partons in the pion, as well as correlations

Long-Bin Chen, Wei Wang, Ruilin Zhu

We present the next-to-next-to-leading order (NNLO) calculation of quark quasi parton distribution functions (PDFs) in the large momentum effective theory. The nontrivial factorization at this order is established explicitly and the full analytic matching coefficients between the quasi distribution and the lightcone distribution are derived. We demonstrate t

Adriana-Simona Mihaita, Zac Papachatgis, Marian-Andrei Rizoiu

Traffic flow prediction, particularly in areas that experience highly dynamic flows such as motorways, is a major issue faced in traffic management. Due to increasingly large volumes of data sets being generated every minute, deep learning methods have been used extensively in the latest years for both short and long term prediction. However, such models, de

Antonin Monteil, Rémy Rodiac, Jean Van Schaftingen

We define renormalised energies for maps that describe the first-order asymptotics of harmonic maps outside of singularities arising due to obstructions generated by the boundary data and the mutliple connectedness of the target manifold. The constructions generalise the definition by Bethuel, Brezis and Hélein for the circle (Ginzburg-Landau vortices, 1994)

Shruti Jadon

Image Segmentation has been an active field of research as it has a wide range of applications, ranging from automated disease detection to self-driving cars. In the past five years, various papers came up with different objective loss functions used in different cases such as biased data, sparse segmentation, etc. In this paper, we have summarized some of t

Ferran Garcia, Frank R. N. Chambers, Anna L. Watts

The Cassini and Juno probes have revealed large coherent cyclonic vortices in the polar regions of Saturn and Jupiter, a dramatic contrast from the east-west banded jet structure seen at lower latitudes. Debate has centered on whether the jets are shallow, or extend to greater depths in the planetary envelope. Recent experiments and observations have demonst

Weiwen Jiang, Jinjun Xiong, Yiyu Shi

Despite the pursuit of quantum advantages in various applications, the power of quantum computers in neural network computations has mostly remained unknown, primarily due to a missing link that effectively designs a neural network model suitable for quantum circuit implementation. In this article, we present the co-design framework, namely QuantumFlow, to p

YG Liang, Sergio Da Silva, Yang Zhang

We provide a nontrivial bound on the rank of any tensor $T$ over the quaternions $\mathbb{H}$ in the $n_1\times n_2\times n_3$ cases where $2\leq n_i\leq 3$. We describe a decomposition of $T$ into $3$ simple tensors in the $2\times 2\times 2$ case. We also show that the upper bound is the best possible for some of the cases, and we provide various partial r

Yudier Peña Pérez, Juan Bory Reyes

This article deals with the study of electromagnetic waves equations and the Lorentz condition, as emergent properties of Maxwell's system in the context of systems theory. To do this, the wave equations and the Helmholtz equation are first deduced. Using the displaced Dirac operator, which is closely related to the main vector calculation operators, it

Myungho Kim, Doyun Koo

We identify the dimension of the centralizer of the symmetric group $\mathfrak{S}_d$ in the partition algebra $\mathcal{A}_d(δ)$ and in the Brauer algebra $\mathcal{B}_d(δ)$ with the number of multidigraphs with $d$ arrows and the number of disjoint union of directed cycles with $d$ arrows, respectively. Using Schur-Weyl duality as a fundamental theory, we c

Al-Waleed El-Sayed, Stephen Hughes

We introduce a quasinormal mode theory of mechanical open-cavity modes for optomechanical resonators, and demonstrate the importance of using a generalized (complex) effective mode volume and the phase of the quasinormal mode. We first generalize and fix the normal mode theories of the elastic Purcell factor, and then show a striking example of coupled quasi

Xiang Deng, Huan Sun, Alyssa Lees, You Wu

Relational tables on the Web store a vast amount of knowledge. Owing to the wealth of such tables, there has been tremendous progress on a variety of tasks in the area of table understanding. However, existing work generally relies on heavily-engineered task-specific features and model architectures. In this paper, we present TURL, a novel framework that int

Ray P. Norris, Huib T. Intema, Anna D. Kapinska, Baerbel S. Koribalski

We have found a class of circular radio objects in the Evolutionary Map of the Universe Pilot Survey, using the Australian Square Kilometre Array Pathfinder telescope. The objects appear in radio images as circular edge-brightened discs, about one arcmin diameter, that are unlike other objects previously reported in the literature. We explore several possibl

Lin Guan, Mudit Verma, Sihang Guo, Ruohan Zhang

Human explanation (e.g., in terms of feature importance) has been recently used to extend the communication channel between human and agent in interactive machine learning. Under this setting, human trainers provide not only the ground truth but also some form of explanation. However, this kind of human guidance was only investigated in supervised learning t

Hendrik Ranocha, Dimitrios Mitsotakis, David I. Ketcheson

We develop a general framework for designing conservative numerical methods based on summation by parts operators and split forms in space, combined with relaxation Runge-Kutta methods in time. We apply this framework to create new classes of fully-discrete conservative methods for several nonlinear dispersive wave equations: Benjamin-Bona-Mahony (BBM), Forn

Qian Qin, Galin L. Jones

Component-wise MCMC algorithms, including Gibbs and conditional Metropolis-Hastings samplers, are commonly used for sampling from multivariate probability distributions. A long-standing question regarding Gibbs algorithms is whether a deterministic-scan (systematic-scan) sampler converges faster than its random-scan counterpart. We answer this question when

Randall C. O'Reilly, Jacob L. Russin, Maryam Zolfaghar, John Rohrlich

How do humans learn from raw sensory experience? Throughout life, but most obviously in infancy, we learn without explicit instruction. We propose a detailed biological mechanism for the widely-embraced idea that learning is based on the differences between predictions and actual outcomes (i.e., predictive error-driven learning). Specifically, numerous weak

Asli Celikyilmaz, Elizabeth Clark, Jianfeng Gao

The paper surveys evaluation methods of natural language generation (NLG) systems that have been developed in the last few years. We group NLG evaluation methods into three categories: (1) human-centric evaluation metrics, (2) automatic metrics that require no training, and (3) machine-learned metrics. For each category, we discuss the progress that has been

Tolga Ergen, Mert Pilanci

We study training of Convolutional Neural Networks (CNNs) with ReLU activations and introduce exact convex optimization formulations with a polynomial complexity with respect to the number of data samples, the number of neurons, and data dimension. More specifically, we develop a convex analytic framework utilizing semi-infinite duality to obtain equivalent

Abhishek Goswami

A non perturbative proof of the mass generation of fermions via the Higgs mechanism is given. This is done by showing exponential decay of the two point fermionic correlation function in a weakly coupled U(1) Higgs-Yukawa theory on a unit lattice in $d=4$. This decay implies that the Higgs boson, the photon and the fermion all have a non zero physical mass a

Yuqing Du, Stas Tiomkin, Emre Kiciman, Daniel Polani

One difficulty in using artificial agents for human-assistive applications lies in the challenge of accurately assisting with a person's goal(s). Existing methods tend to rely on inferring the human's goal, which is challenging when there are many potential goals or when the set of candidate goals is difficult to identify. We propose a new paradigm f

Cristopher Salvi, Thomas Cass, James Foster, Terry Lyons

Recently, there has been an increased interest in the development of kernel methods for learning with sequential data. The signature kernel is a learning tool with potential to handle irregularly sampled, multivariate time series. In "Kernels for sequentially ordered data" the authors introduced a kernel trick for the truncated version of this kernel

Na Lei, Jisui Huang, Yuxue Ren, Emil Saucan

The auditory ossicles that are located in the middle ear are the smallest bones in the human body. Their damage will result in hearing loss. It is therefore important to be able to automatically diagnose ossicles' diseases based on Computed Tomography (CT) 3D imaging. However CT images usually include the whole head area, which is much larger than the bo

Zezhou Cheng, Jong-Chyi Su, Subhransu Maji

Given a collection of images, humans are able to discover landmarks by modeling the shared geometric structure across instances. This idea of geometric equivariance has been widely used for the unsupervised discovery of object landmark representations. In this paper, we develop a simple and effective approach by combining instance-discriminative and spatiall

Yinglun Zhu, Robert Nowak

We study a regret minimization problem with the existence of multiple best/near-optimal arms in the multi-armed bandit setting. We consider the case when the number of arms/actions is comparable or much larger than the time horizon, and make no assumptions about the structure of the bandit instance. Our goal is to design algorithms that can automatically ada

Peter Z. Vaillancourt, J. Eric Coulter, Richard Knepper, Brandon Barker

Container technologies such as Docker have become a crucial component of many software industry practices especially those pertaining to reproducibility and portability. The containerization philosophy has influenced the scientific computing community, which has begun to adopt - and even develop - container technologies (such as Singularity). Leveraging cont

Fulin Chen, Naihuan Jing, Fei Kong, Shaobin Tan

In this paper, for an arbitrary Kac-Moody Lie algebra $\mathfrak g$ and a diagram automorphism $μ$ of $\mathfrak g$ satisfying certain natural linking conditions, we introduce and study a $μ$-twisted quantum affinization algebra $\mathcal U_\hbar\left(\hat{\mathfrak g}_μ\right)$ of $\mathfrak g$. When $\mathfrak g$ is of finite type, $\mathcal U_\hbar\left(\

Gagan Bansal, Tongshuang Wu, Joyce Zhou, Raymond Fok

Many researchers motivate explainable AI with studies showing that human-AI team performance on decision-making tasks improves when the AI explains its recommendations. However, prior studies observed improvements from explanations only when the AI, alone, outperformed both the human and the best team. Can explanations help lead to complementary performance,

Yuri Bahturin, Sjusan Montgomery

We study actions of pointed Hopf algebras on matrix algebras. Our approach is based on known facts about group gradings of matrix algebras.

Jiawei Liu, Kumar Vijay Mishra, Mohammad Saquib

We consider a spectral sharing problem in which a statistical (or widely distributed) multiple-input multiple-output (MIMO) radar and an in-band full-duplex (IBFD) multi-user MIMO (MU-MIMO) communications system concurrently operate within the same frequency band. Prior works on joint MIMO-radar-MIMO-communications (MRMC) systems largely focus on either colo

Mitchell Wortsman, Vivek Ramanujan, Rosanne Liu, Aniruddha Kembhavi

We present the Supermasks in Superposition (SupSup) model, capable of sequentially learning thousands of tasks without catastrophic forgetting. Our approach uses a randomly initialized, fixed base network and for each task finds a subnetwork (supermask) that achieves good performance. If task identity is given at test time, the correct subnetwork can be retr

Alexander Levine, Soheil Feizi

Adversarial poisoning attacks distort training data in order to corrupt the test-time behavior of a classifier. A provable defense provides a certificate for each test sample, which is a lower bound on the magnitude of any adversarial distortion of the training set that can corrupt the test sample's classification. We propose two novel provable defenses

Andre P. Oliveira

The Duffin--Schaeffer Conjecture answers a question on how well one can approximate irrationals by rational numbers in reduced form (an imposed condition) where the accuracy of the approximation depends on the rational number. It can be viewed as an analogue to Khintchine's Theorem with the added restriction of only allowing rationals in reduced form. Ot

Pengfei Guo, Puyang Wang, Jinyuan Zhou, Vishal M. Patel

Data-driven automatic approaches have demonstrated their great potential in resolving various clinical diagnostic dilemmas for patients with malignant gliomas in neuro-oncology with the help of conventional and advanced molecular MR images. However, the lack of sufficient annotated MRI data has vastly impeded the development of such automatic methods. Conven

Anschel Schaffer-Cohen

Following the work of Rosendal and Mann and Rafi, we try to answer the following question: when is the mapping class group of an infinite-type surface quasi-isometric to a graph whose vertices are curves on that surface? With the assumption of tameness as defined by Mann and Rafi, we describe a necessary and sufficient condition, called translatability, for

Yinjun Wu, Edgar Dobriban, Susan B. Davidson

Machine learning models are not static and may need to be retrained on slightly changed datasets, for instance, with the addition or deletion of a set of data points. This has many applications, including privacy, robustness, bias reduction, and uncertainty quantifcation. However, it is expensive to retrain models from scratch. To address this problem, we pr

Si Wu, Yinghao Zhu, Haoshi Gao, Yinguo Xiao

We report on single-crystal growths of the SrTb$_2$O$_4$ compound by a super-necking technique with a laser-floating-zone furnace and study the stoichiometry, growth mode, and structural and magnetic properties by scanning electronic microscopy, neutron Laue, X-ray powder diffraction, and the physical property measurement system. We optimized the growth para

Akhilan Boopathy, Sijia Liu, Gaoyuan Zhang, Cynthia Liu

Recent works have empirically shown that there exist adversarial examples that can be hidden from neural network interpretability (namely, making network interpretation maps visually similar), or interpretability is itself susceptible to adversarial attacks. In this paper, we theoretically show that with a proper measurement of interpretation, it is actually

Laura Dominé, Pierre Côte de Soux, François Drielsma, Dae Heun Koh

Liquid Argon Time Projection Chambers (LArTPC) are particle imaging detectors recording 2D or 3D images of trajectories of charged particles. Identifying points of interest in these images, namely the initial and terminal points of track-like particle trajectories such as muons and protons, and the initial points of electromagnetic shower-like particle traje

Liqun Chen, Zhe Gan, Yu Cheng, Linjie Li

Cross-domain alignment between two sets of entities (e.g., objects in an image, words in a sentence) is fundamental to both computer vision and natural language processing. Existing methods mainly focus on designing advanced attention mechanisms to simulate soft alignment, with no training signals to explicitly encourage alignment. The learned attention matr

John C. Baez

We examine the assumptions behind Noether's theorem connecting symmetries and conservation laws. To compare classical and quantum versions of this theorem, we take an algebraic approach. In both classical and quantum mechanics, observables are naturally elements of a Jordan algebra, while generators of one-parameter groups of transformations are naturall

V. Kireyeu, I. Grishmanovskii, V. Kolesnikov, V. Voronyuk

We study the hadron production in $p+p$, $p+n$ and $n+n$ reactions within the microscopic Parton-Hadron-Dynamics (PHSD) transport approach in comparison to PYTHIA 8.2. We discuss the details of the "PHSD tune" of the Lund string model (realized by event generators FRITIOF and PYTHIA) in the vacuum (as in $N+N$ collisions) as well as its in-medium mod

Chunhui Li, Shihao Yan, Nan Yang, Xiangyun Zhou

We propose to use channel inversion power control (CIPC) to achieve one-way ultra-reliable and low-latency communications (URLLC), where only the transmission in one direction requires ultra reliability and low latency. Based on channel reciprocity, our proposed CIPC schemes guarantee the power of received signal that is used to decode the information to be

Nilabja Guha, Anindya Roy

Estimating the mixing density of a mixture distribution remains an interesting problem in statistics literature. Using a stochastic approximation method, Newton and Zhang (1999) introduced a fast recursive algorithm for estimating the mixing density of a mixture. Under suitably chosen weights the stochastic approximation estimator converges to the true solut

Seongyong Park, Shujaat Khan, Abdul Wahab

Understanding E3 ligase and target substrate interactions are important for cell biology and therapeutic development. However, experimental identification of E3 target relationships is not an easy task due to the labor-intensive nature of the experiments. In this article, a sequence-based E3-target prediction model is proposed for the first time. The propose

Ting-Hsiang Wang, Qingquan Song, Xiaotian Han, Zirui Liu

Realistic recommender systems are often required to adapt to ever-changing data and tasks or to explore different models systematically. To address the need, we present AutoRec, an open-source automated machine learning (AutoML) platform extended from the TensorFlow ecosystem and, to our knowledge, the first framework to leverage AutoML for model search and

Ali Ayub, Alan R. Wagner

The two main challenges faced by continual learning approaches are catastrophic forgetting and memory limitations on the storage of data. To cope with these challenges, we propose a novel, cognitively-inspired approach which trains autoencoders with Neural Style Transfer to encode and store images. Reconstructed images from encoded episodes are replayed when

Alexandru Maries, Nafis I Karim, Chandralekha Singh

Many prior studies have found a gender gap between male and female students' performance on conceptual assessments such as the Force Concept Inventory (FCI) and the Conceptual Survey of Electricity and Magnetism (CSEM) with male students performing better than female students. Prior studies have also found that activation of a negative stereotype about a

J. -F. Pommaret

In 1909 the brothers E. and F. Cosserat discovered a new nonlinear group theoretical approach to elasticity (EL), with the only experimental need to measure the EL constants. In a modern language, their idea has been to use the nonlinear Spencer sequence instead of the nonlinear Janet sequence for the Lie groupoid defining the group of rigid motions of space

Hassan Al-Zoubi

In this paper, we continue the classification of finite type Gauss map surfaces in the 3-dimensional Euclidean space $\mathbb{E}^{3}$. We present an important family of surfaces, namely, tubes in $\mathbb{E}^{3}$. We show that the Gauss map of a tube is of an infinite type corresponding to the second fundamental form.

Jun Yan Dai, Jin Yang, Wankai Tang, Ming Zheng Chen

Space-time modulated metasurfaces have attracted significant attention due to the additional degree of freedom in manipulating the electromagnetic (EM) waves in both space and time domains. However, the existing techniques have limited wave control capabilities, leading to just a few feasible schemes like regulation of only one specific harmonic. Here, we pr

Nafis I Karim, Alexandru Maries, Chandralekha Singh

We discuss research involving the Conceptual Survey of Electricity and Magnetism (CSEM) to evaluate one aspect of the pedagogical content knowledge of teaching assistants (TAs): the knowledge of introductory students' alternate conceptions in electricity and magnetism as revealed by the CSEM. For each item on the CSEM, the TAs were asked to (1) identify

Jithin Sunny, Joel Jogy, Rohan Rout, Rakshit Naidu

In the midst of rising positive cases of COVID-19, the hospitals face a newfound difficulty to prioritize on their patients and accommodate them. Moreover, crowding of patients at hospitals pose a threat to the healthcare workers and other patients at the hospital. With that in mind, a non-contact method of measuring the necessary vitals such as heart rate,

Alexandru Maries, Chandralekha Singh

An appropriate diagram is a required element of a solution building process in physics problem solving and it can transform a given problem into a representation that is easier to exploit for solving the problem. A major focus while helping introductory physics students learn problem solving is to help them appreciate that drawing diagrams facilitates proble

C. Royon

We describe the most recent results from the Proton Precision Spectrometer from the CMS and TOTEM collaborations, namely the first observation of exclusive di-lepton production at high mass at the LHC, and the prospects concerning the sensitivity to quartic anomalous couplings..

Mehmet Emin Aktas, Esra Akbas

In this paper, we study the graph classification problem in vertex-labeled graphs. Our main goal is to classify the graphs comparing their higher-order structures thanks to heat diffusion on their simplices. We first represent vertex-labeled graphs as simplex-weighted super-graphs. We then define the diffusion Frechet function over their simplices to encode

Frédéric Barbaresco, Yann Cabanes

The aim is to describe new geometric approaches to define the statistics of spatio-temporal and polarimetric measurements of the states of an electromagnetic wave, using the works of Maurice Fr{é}chet, Jean-Louis Koszul and Jean-Marie Souriau, with in particular the notion of 'average' state of this digital measurement as a Fr{é}chet barycentre in a

Slava Andrejev

The paper shows how to optimize a water level sensor consisting of a cylinder with spiraling metal stripes on the side, using a powerful Python library FEniCS. It is shown how to reduce a 3D Laplace equation to a 2D, using a spiraling coordinate system; how to specify the correct boundary conditions for an open region; how to convert the partial differential

K. Zioutas, G. Cantatore, M. Karuza, A. Kryemadhi

The main alternatives of the recent XENON1T observation are solar axions, neutrino magnetic moment and tritium. In this short note we suggest to crosscheck whether the observation is related or not to dark matter (DM) streams, by searching for planetary dependence of the observed excess. If such a correlation is derived, this hint (<3.5sigma) can become the

Anita Graser, Esteban Zimányi, Krishna Chaitanya Bommakanti

Mobility data science lacks common data structures and analytical functions. This position paper assesses the current status and open issues towards a universal API for mobility data science. In particular, we look at standardization efforts revolving around the OGC Moving Features standard which, so far, has not attracted much attention within the mobility

Alexandru Maries, Nafis I. Karim, Chandralekha Singh

Several prior studies in introductory physics have found a gender gap on conceptual assessments such as the Force Concept Inventory (FCI) and the Conceptual Survey of Electricity and Magnetism (CSEM) with male students performing better than female students. Moreover, prior studies in the context of mathematics have also found that activation of a negative s

Xiaoming Li, Chun Wang, Xiao Huang, Yimin Nie

The conventional deep learning approaches for solving time-series problem such as long-short term memory (LSTM) and gated recurrent unit (GRU) both consider the time-series data sequence as the input with one single unit as the output (predicted time-series result). Those deep learning approaches have made tremendous success in many time-series related probl

Maxim S. Kovalev, Lev V. Utkin

A method for counterfactual explanation of machine learning survival models is proposed. One of the difficulties of solving the counterfactual explanation problem is that the classes of examples are implicitly defined through outcomes of a machine learning survival model in the form of survival functions. A condition that establishes the difference between s

Mokhtar Falek, Noureddine Belghar, Mustafa Moumni

We write Schrödinger equation for the Coulomb potential in both de Sitter and Anti-de Sitter spaces using the Extended Uncertainty Principle formulation. We use the Nikiforov-Uvarov method to solve the equations. The energy eigenvalues for both systems are given in their exact forms and the corresponding radial wave functions are expressed in associated Jaco

D. M. Rodkin, Yu. M. Tchuvil&#39;sky

Scrupulous theoretical study of 8Be nucleus states, both clustered and non-clustered, is performed over a wide range of the excitation energies. The quantities which characterize the degree of the alpha-clustering of these states: spectroscopic factors, cluster form factors as well as the alpha-decay widths are computed in the framework of an accurate ab ini

L. Lugosi, T. Kovács

We study the connection between transport phenomenon and escape rate statistics in two-dimensional standard map. For the purpose of having an open phase space, we let the momentum co-ordinate vary freely and restrict only angle with periodic boundary condition. We also define a pair of artificial holes placed symmetrically along the momentum axis where the p

Nalini Joshi, Nobutaka Nakazono

In this paper, we consider a reduction of a new system of partial difference equations, which was obtained in our previous paper (Joshi and Nakazono, arXiv:1906.06650) and shown to be consistent around a cuboctahedron. We show that this system reduces to $A_2^{(1)\ast}$-type discrete Painlevé equations by considering a periodic reduction of a three-dimension

Ivan Chajda, Helmut Länger

We introduce so-called consistent posets which are bounded posets with an antitone involution &#39; where the lower cones of x,x&#39; and of y,y&#39; coincide provided x,y are different form 0,1 and, moreover, if x,y are different form 0 then their lower cone is different form 0, too. We show that these posets can be represented by means of commutative meet-

A. G. Goulart, M. J. Lazo, J. M. S. Suarez

In the present work, we propose an advection-diffusion equation with Hausdorff deformed derivatives to stud the turbulent diffusion of contaminants in the atmosphere. We compare the performance of our model to fit experimental data against models with classical and Caputo fractional derivatives. We found that the Hausdorff equation gives better results than

Ibrahima Bakayoko, Ismail Laraiedh

The aim of this paper is introduce and give some constructions results and examples of n-BiHom-Lie color algebras. Next, we introduce the definition of BiHom-modules over n- BiHom-Lie color algebras and we provide some properties. Moreover we investigate generalized derivations of n-BiHom-Lie color algebras and their BiHom-subalgebras.

Claudio Bonati, Alessio Franchi, Andrea Pelissetto, Ettore Vicari

We address the interplay between global and local gauge nonabelian symmetries in lattice gauge theories with multicomponent scalar fields. We consider two-dimensional lattice scalar nonabelian gauge theories with a local SO(Nc) (Nc >= 3) and a global O(Nf) invariance, obtained by partially gauging a maximally O(Nf x Nc)-symmetric multicomponent scalar model.

I. Dimitrijevic, B. Dragovich, A. S. Koshelev, Z. Rakic

In this paper, we investigate a nonlocal modification of general relativity (GR) with action $S = \frac{1}{16πG} \int [ R- 2Λ+ (R-4Λ) \, \mathcal{F}(\Box) \, (R-4Λ) ] \, \sqrt{-g}\; d^4x ,$ where $\mathcal{F} (\Box) = \sum_{n=1}^{+\infty} f_n \Box^n$ is an analytic function of the d&#39;Alembertian $\Box$. We found a few exact cosmological solutions of the c

Vincent Chin, Noelle I. Samia, Roman Marchant, Ori Rosen

Forecasting models have been influential in shaping decision-making in the COVID-19 pandemic. However, there is concern that their predictions may have been misleading. Here, we dissect the predictions made by four models for the daily COVID-19 death counts between March 25 and June 5 in New York state, as well as the predictions of ICU bed utilisation made

Hidenori Ogata

In this paper, we propose a method of fundamental solutions for the problems of two-dimensional potential flow past a doubly-periodic array of obstacles. The solutions of these problems involve doubly-periodic functions, and it is difficult to apply the conventional method of fundamental solutions to approximate them. The method that we propose gives approxi

Lucía Pedraza, Sebastián Pinto, Juan Pablo Pinasco, Pablo Balenzuela

The Axelrod model of cultural dissemination has been widely studied in the field of statistical mechanics. The traditional version of this agent-based model is to assign a cultural vector of $F$ components to each agent, where each component can take one of $Q$ cultural trait. In this work, we introduce a novel set of mean field master equations to describe

Ming Li, Jacek Klos, Alexander Petrov, Hui Li

The effect of conical intersections (CIs) on electronic relaxation, transitions from excited states to ground states, is well studied, but their influence on hyperfine quenching in a reactant molecule is not known. Here, we report on ultracold collision dynamics of the hydroxyl free-radical OH with Sr atoms leading to quenching of OH hyperfine states. Our qu

Brian K. Kendrick, Hui Li, Ming Li, Svetlana Kotochigova

Electronically non-adiabatic effects play an important role in many chemical reactions. How these effects manifest in cold and ultracold chemistry remain largely unexplored. Here, through first principles non-adiabatic quantum dynamics calculations of the Li + LiNa $\to$ Li$_2$ + Na chemical reaction, it is shown that non-adiabatic dynamics induces quantum i

Kai Diethelm, Roberto Garrappa, Andrea Giusti, Martin Stynes

In recent years, many papers discuss the theory and applications of new fractional-order derivatives that are constructed by replacing the singular kernel of the Caputo or Riemann-Liouville derivative by a non-singular (i.e., bounded) kernel. It will be shown here, through rigorous mathematical reasoning, that these non-singular kernel derivatives suffer fro

Karl Dilcher, Lin Jiu

Using continued fraction expansions of certain polygamma functions as a main tool, we find orthogonal polynomials with respect to the odd-index Bernoulli polynomials $B_{2k+1}(x)$ and the Euler polynomials $E_{2k+ν}(x)$, for $ν=0, 1, 2$. In the process we also determine the corresponding Jacobi continued fractions (or J-fractions) and Hankel determinants. In

Honghua Zhang, Steven Holtzen, Guy Van den Broeck

Scaling probabilistic models to large realistic problems and datasets is a key challenge in machine learning. Central to this effort is the development of tractable probabilistic models (TPMs): models whose structure guarantees efficient probabilistic inference algorithms. The current landscape of TPMs is fragmented: there exist various kinds of TPMs with di

Matthew B. A. McDermott, Tzu Ming Harry Hsu, Wei-Hung Weng, Marzyeh Ghassemi

It is often infeasible or impossible to obtain ground truth labels for medical data. To circumvent this, one may build rule-based or other expert-knowledge driven labelers to ingest data and yield silver labels absent any ground-truth training data. One popular such labeler is CheXpert, a labeler that produces diagnostic labels for chest X-ray radiology repo

Jingwen Su, Hujun Yin

Since the advent of generative adversarial networks (GANs), various loss functions have been developed and combined to constitute the overall training objective function, in order to improve model performance or for specific learning tasks. For instance, in image enhancement or restoration, there are often several criteria to consider such as signal-noise ra

John Rogers, Tsung-Han Lee, Sahar Pakdel, Wenhu Xu

A cardinal obstacle to performing quantum-mechanical simulations of strongly-correlated matter is that, with the theoretical tools presently available, sufficiently-accurate computations are often too expensive to be ever feasible. Here we design a computational framework combining quantum-embedding (QE) methods with machine learning. This allows us to bypas

Bin Gao, Nguyen Thanh Son, P. -A. Absil, Tatjana Stykel

The symplectic Stiefel manifold, denoted by $\mathrm{Sp}(2p,2n)$, is the set of linear symplectic maps between the standard symplectic spaces $\mathbb{R}^{2p}$ and $\mathbb{R}^{2n}$. When $p=n$, it reduces to the well-known set of $2n\times 2n$ symplectic matrices. Optimization problems on $\mathrm{Sp}(2p,2n)$ find applications in various areas, such as opti

Rafael L. da Silva, Nathan Starliper, Boxuan Zhong, He Helen Huang

Lower limb prosthesis can benefit from embedded systems capable of applying computer vision techniques to enhance autonomous control and context awareness for intelligent decision making. In order to fill in the gap of current literature of autonomous systems for prosthetic legs employing computer vision methods, we evaluate the performance capabilities of t

Adam Stooke, Valentin Dalibard, Siddhant M. Jayakumar, Wojciech M. Czarnecki

We introduce a new recurrent agent architecture and associated auxiliary losses which improve reinforcement learning in partially observable tasks requiring long-term memory. We employ a temporal hierarchy, using a slow-ticking recurrent core to allow information to flow more easily over long time spans, and three fast-ticking recurrent cores with connection

C. Royon

We describe the most recent results from the TOTEM collaboration at the LHC, namely the elastic cross section measurements at a center-of-mass on 2.76, 7, 8 and 13 TeV. No structure or resonance is observed at high $t$ at high center-of-mass energies. A pure exponential form of $d σ/dt$ is excluded both at 8 and 13 TeV. Accessing the very low $t$ region allo

Y. Muniz, A. Manjavacas, C. Farina, D. A. R. Dalvit

The ability to harness light-matter interactions at the few-photon level plays a pivotal role in quantum technologies. Single photons - the most elementary states of light - can be generated on-demand in atomic and solid state emitters. Two-photon states are also key quantum assets, but achieving them in individual emitters is challenging because their gener

Nompumelelo Mtsweni, Herkulaas MvE Combrink, Vukosi Marivate

When the COVID-19 disease pandemic infiltrated the world, there was an immediate need for accurate information. As with any outbreak, the outbreak follows a clear trajectory, and subsequently, the supporting information for that outbreak needs to address the needs associated with that stage of the outbreak. At first, there was a need to inform the public of

Zhongjun Wang, Mengye Sun, A. M. Elsawah

With the aggravation of the global economic crisis and inflation, the precious metals with safe-haven function have become more popular. An improved MF-DFA method is proposed to analyze price fluctuations of the precious metals market. Based on the widely used multifractal detrended fluctuation analysis method (MF-DFA), we compare these two methods and find

Serge Plata, Sumanas Sarma, Melvin Lancelot, Kristine Bagrova

Taking the context of simulating a retail environment using agent based modelling, a theoretical model is presented that describes the probability distribution of customer &#34;collisions&#34; using a novel space transformation to the Torus $Tor^2$. A method for generating the distribution of customer paths based on historical basket data is developed. Final

Rafael de la Madrid, Fabian Garza, Justin Kirk, Huy Luong

We address the issues raised in [R. Tadmor et al., Langmuir 2020, 36, 475-476]. In particular, we explain why we did not use Tadmor&#39;s theory to explain our results.

F. Deganutti, C. Royon

In this report, we give the Balitsky Fadin Kuraev Lipton formalism for jet gap jet events at hadronic colliders. We also discuss the case where in addition at least one proton is intact in the final state in diffractive events.

C. Royon

In this report, we describe the most recent results on exclusive diffraction from the ATLAS, CMS, LHCb, TOTEM experiments at the LHC concerning exclusive pions, $J/Ψ$, $Ψ(2S)$, dilepton, diphoton, $WW$ productions and prospects concerning the search for anomalous couplings and axion-like particle production.