May 2022 arXiv papers — page 10

Radouan Hab-arrih, Ahmed Jellal, El Hassan El Kinani

We study the intrinsic decoherence of coupled harmonic oscillators. The Milburn master equation is solved exactly, and the dynamics of virtual ground state excitations are investigated. The interaction of quantum correlations and virtual excitation was then studied. The following is a summary of our major findings. (i) The damped oscillatory profile of all t

Stratis Markou

The challenge of simulating random variables is a central problem in Statistics and Machine Learning. Given a tractable proposal distribution $P$, from which we can draw exact samples, and a target distribution $Q$ which is absolutely continuous with respect to $P$, the A* sampling algorithm allows simulating exact samples from $Q$, provided we can evaluate

Mayukh R. Gangopadhyay, Nilanjana Kumar, Ankan Mukherjee, Mohit K. Sharma

A pseudo-Nambu Goldstone Boson (pNGB) arising from the breaking of a global symmetry ($G\rightarrow H$) can be one of the most promising candidates for the quintessence model, to explain the late-time acceleration of our universe. Motivated from the Composite Higgs scenario, we have investigated the case where the pNGB associated with $SO(N)/ SO(N-1)$ develo

Falk-Richard G. Winkelmann, Carrie A. Weidner, Gautam Ramola, Wolfgang Alt

We present a scheme that uses Ramsey interferometry to directly probe the Wigner function of a neutral atom confined in an optical trap. The proposed scheme relies on the well-established fact that the Wigner function at a given point $(x,p)$ in phase space is proportional to the expectation value of the parity operator relative to that point. In this work,

Markus B. Fröb

We study the renormalization group flow equations for correlation functions of weakly coupled quantum field theories in AdS. Taking the limit where the external points approach the conformal boundary, we obtain a flow of conformally invariant correlation functions. We solve the flow for one- and two-point functions and show that the corrections to the confor

Benoit Charbonneau, Ákos Nagy

We produce finite energy BPS monopoles with arbitrary prescribed symmetry breaking from a new class of Nahm data.

Rafael Pina, Varuna De Silva, Joosep Hook, Ahmet Kondoz

Multi-Agent Reinforcement Learning (MARL) is useful in many problems that require the cooperation and coordination of multiple agents. Learning optimal policies using reinforcement learning in a multi-agent setting can be very difficult as the number of agents increases. Recent solutions such as Value Decomposition Networks (VDN), QMIX, QTRAN and QPLEX adher

Nele Callebaut, Gilad Lifschytz

In the framework of bulk reconstruction, we elucidate the relationship between the action of CFT modular Hamiltonians on bulk operators, the possible equation of motion for the bulk operators, and the charge distribution at infinity corresponding to such bulk fields. In particular for scalar fields interacting with gravity or with gauge fields, we show how C

Stefan Hollands

Given a unitary fusion category, one can define the Hilbert space of a so-called ``anyonic spin-chain'' and nearest neighbor Hamiltonians providing a real-time evolution. There is considerable evidence that suitable scaling limits of such systems can lead to $1+1$-dimensional conformal field theories (CFTs), and in fact, can be used potentially to construct

Xiaohan Ding, Honghao Chen, Xiangyu Zhang, Kaiqi Huang

The well-designed structures in neural networks reflect the prior knowledge incorporated into the models. However, though different models have various priors, we are used to training them with model-agnostic optimizers such as SGD. In this paper, we propose to incorporate model-specific prior knowledge into optimizers by modifying the gradients according to

Kuang-Huei Lee, Ofir Nachum, Mengjiao Yang, Lisa Lee

A longstanding goal of the field of AI is a method for learning a highly capable, generalist agent from diverse experience. In the subfields of vision and language, this was largely achieved by scaling up transformer-based models and training them on large, diverse datasets. Motivated by this progress, we investigate whether the same strategy can be used to

Geoffrey Cruttwell, Michael Lambert, Dorette Pronk, Martin Szyld

This paper defines double fibrations (fibrations of double categories) and describes their key examples and properties. In particular, it shows how double fibrations relate to existing fibrational notions such as monoidal fibrations and discrete double fibrations, proves a representation theorem for double fibrations, and shows how double fibrations are a ty

Julian Lienen, Caglar Demir, Eyke Hüllermeier

In semi-supervised learning, the paradigm of self-training refers to the idea of learning from pseudo-labels suggested by the learner itself. Across various domains, corresponding methods have proven effective and achieve state-of-the-art performance. However, pseudo-labels typically stem from ad-hoc heuristics, relying on the quality of the predictions thou

Patricio Gallardo, Benjamin Schmidt

We study compactifications of the moduli space of unordered points in the plane via variation of GIT quotients of their corresponding Hilbert scheme. Our VGIT considers linearizations outside the ample cone and within the movable cone. For that purpose, we use the description of the Hilbert scheme as a Mori dream space, and the moduli interpretation of its b

Wangchunshu Zhou, Yan Zeng, Shizhe Diao, Xinsong Zhang

Recent advances in vision-language pre-training (VLP) have demonstrated impressive performance in a range of vision-language (VL) tasks. However, there exist several challenges for measuring the community's progress in building general multi-modal intelligence. First, most of the downstream VL datasets are annotated using raw images that are already seen dur

Yu Gong, Greg Mori, Frederick Tung

Data imbalance, in which a plurality of the data samples come from a small proportion of labels, poses a challenge in training deep neural networks. Unlike classification, in regression the labels are continuous, potentially boundless, and form a natural ordering. These distinct features of regression call for new techniques that leverage the additional info

Udaya Ghai, Zhou Lu, Elad Hazan

We study an algorithmic equivalence technique between non-convex gradient descent and convex mirror descent. We start by looking at a harder problem of regret minimization in online non-convex optimization. We show that under certain geometric and smoothness conditions, online gradient descent applied to non-convex functions is an approximation of online mir

Wenyu Zhang, Li Shen, Wanyue Zhang, Chuan-Sheng Foo

Deep networks are prone to performance degradation when there is a domain shift between the source (training) data and target (test) data. Recent test-time adaptation methods update batch normalization layers of pre-trained source models deployed in new target environments with streaming data to mitigate such performance degradation. Although such methods ca

Francesco Longo, Letizia Nicoletti, Antonio Padovano

While the Industry 4.0 is idolizing the potential of an artificial intelligence embedded into "things", it is neglecting the role of the human component, which is still indispensable in different manufacturing activities, such as a machine setup or maintenance operations. The present research study first proposes an Industrial Internet pyramid as emergent hu

Nat Gopalswamy, Sachiko Akiyama, Pertti Mäkelä, Seiji Yashiro

An intense type III radio storm has been disrupted by a fast halo coronal mass ejection (CME) on 2000 April 4. The CME is also associated with a large solar energetic particle (SEP) event. The storm recovers after about10 hrs. We identified another CME that occurs on 2003 November 11 with similar CME properties but there is no type III storm in progress. The

Mrinal Sarkar, Shamik Gupta

We consider biased random walks on random networks constituted by a random comb comprising a backbone with quenched-disordered random-length branches. The backbone and the branches run in the direction of the bias. For the bare model as also when the model is subject to stochastic resetting, whereby the walkers on the branches reset with a constant rate to t

Jordan Meadows, Andre Freitas

Informal mathematical text underpins real-world quantitative reasoning and communication. Developing sophisticated methods of retrieval and abstraction from this dual modality is crucial in the pursuit of the vision of automating discovery in quantitative science and mathematics. We track the development of informal mathematical language processing approache

Hadiseh Nasari, Gisela Lopez-Galmiche, Helena E. Lopez-Aviles, Alexander Schumer

The adiabatic theorem, a corollary of the Schr\"odinger equation, manifests itself in a profoundly different way in non-Hermitian arrangements, resulting in counterintuitive state transfer schemes that have no counterpart in closed quantum systems. In particular, the dynamical encirclement of exceptional points (EPs) in parameter space has been shown to lead

Ludwik Adamowicz, Simen Kvaal, Caroline Lasser, Thomas Bondo Pedersen

Laser-induced molecular alignment is well understood within the framework of the Born-Oppenheimer (BO) approximation Without the BO approximation, however, the concept of molecular structure is lost, making alignment hard to define precisely. In this work, we demonstrate the emergence of alignment from the first-ever non-BO quantum dynamics simulations, usin

Xiaofeng Gu, Muhuo Liu

Let $\beta>0$. Motivated by jumbled graphs defined by Thomason, the celebrated expander mixing lemma and Haemers's vertex separation inequality, we define that a graph $G$ with $n$ vertices is a weakly $(n,\beta)$-graph if $\frac{|X| |Y|}{(n-|X|)(n-|Y|)} \le \beta^2$ holds for every pair of disjoint proper subsets $X, Y$ of $V(G)$ with no edge between $X$ an

Kohei Yoshimura, Artemy Kolchinsky, Andreas Dechant, Sosuke Ito

We propose a housekeeping/excess decomposition of entropy production for general nonlinear dynamics in a discrete space, including chemical reaction networks and discrete stochastic systems. We exploit the geometric structure of thermodynamic forces to define the decomposition; this does not rely on the notion of a steady state, and even applies to systems t

Hang Chi, Jagadeesh S. Moodera

The quantum anomalous Hall effect refers to the quantization of Hall effect in the absence of applied magnetic field. The quantum anomalous Hall effect is of topological nature and well suited for field-free resistance metrology and low-power information processing utilizing dissipationless chiral edge transport. In this Perspective, we provide an overview o

Townim Chowdhury, Ali Cheraghian, Sameera Ramasinghe, Sahar Ahmadi

Few-shot class-incremental learning (FSCIL) aims to incrementally fine-tune a model (trained on base classes) for a novel set of classes using a few examples without forgetting the previous training. Recent efforts address this problem primarily on 2D images. However, due to the advancement of camera technology, 3D point cloud data has become more available

Francesco Longo, Letizia Nicoletti, Antonio Padovano, Gianfranco d'Atri

Despite Information and Communication Technologies (ICT) have reduced the information asymmetry and increased the degree of interorganizational collaboration, the companies participating a supply chain are less inclined to share data when information is sensible and partners cannot be fully trusted. In such a context, Blockchain is a decentralized certificat

Youssef Fattasse, Miloud Mekkaoui, Ahmed Jellal, Abdelhadi Bahaoui

The group delay time of Dirac fermions subjected to a tilting barrier potential along the $ x $-axis is investigated in graphene. We start by finding the eigenspinor solution of the Dirac equation and then relating it to incident, reflected, and transmitted beam waves. This relationship allows us to compute the group delay time in transmission and reflection

Nat Gopalswamy, Pertti Mäkelä, Seiji Yashiro, Sachiko Akiyama

We report on a study that compares energetic particle fluxes in corotating interaction regions (CIRs) associated with type III radio storm with those in nonstorm CIRs. In a case study, we compare the CIR particle events on 2010October 21 and 2005 November 2. The two events have similar solar and solar wind circumstances, except that the former is associated

Mengzhou Xia, Mikel Artetxe, Jingfei Du, Danqi Chen

Pre-trained masked language models successfully perform few-shot learning by formulating downstream tasks as text infilling. However, as a strong alternative in full-shot settings, discriminative pre-trained models like ELECTRA do not fit into the paradigm. In this work, we adapt prompt-based few-shot learning to ELECTRA and show that it outperforms masked l

G. E. Volovik

The paper is devoted to the memory of Igor E. Dzyaloshinsky. In our common paper I.E. Dzyaloshinskii and G.E. Volovick, Poisson brackets in condensed matter, Ann. Phys. {\bf 125} 67--97 (1980), we discussed the elasticity theory described in terms of the gravitational field variables -- the elasticity vielbein $E_\mu^a$. They come from the phase fields, whic

M. Kazemi, V. A. Shahnazaryan, Y. V. Zhumagulov, P. F. Bessarab

Novel 2D material CrI3 reveals unique combination of 2D ferromagnetism and robust excitonic response. We demonstrate that the possibility of the formation of magnetic topological defects, such as Neel skyrmions, together with large excitonic Zeeman splitting, leads to giant scattering asymmetry, which is the necessary prerequisite for the excitonic anomalous

Muhuo Liu, Shumei Pang, Francesco Belardo, Akbar Ali

For a connected graph $G$ on at least three vertices, the augmented Zagreb index (AZI) of $G$ is defined as $$AZI(G)=\sum_{uv\in E(G)}\left(\frac{d(u)d(v)}{d(u)+d(v)-2}\right)^{3},$$ being a topological index well-correlated with the formation heat of heptanes and octanes. A $k$-apex tree $G$ is a connected graph admitting a $k$-subset $X\subset V(G)$ such t

Mengxue Zhang, Sami Baral, Neil Heffernan, Andrew Lan

Automatic short answer grading is an important research direction in the exploration of how to use artificial intelligence (AI)-based tools to improve education. Current state-of-the-art approaches use neural language models to create vectorized representations of students responses, followed by classifiers to predict the score. However, these approaches hav

Jianzhong Qi, Zhuowei Zhao, Egemen Tanin, Tingru Cui

Traffic prediction is an important and yet highly challenging problem due to the complexity and constantly changing nature of traffic systems. To address the challenges, we propose a graph and attentive multi-path convolutional network (GAMCN) model to predict traffic conditions such as traffic speed across a given road network into the future. Our model foc

Rolandos Alexandros Potamias, Alexandros Neofytou, Kyriaki-Margarita Bintsi, Stefanos Zafeiriou

Geodesic paths and distances are among the most popular intrinsic properties of 3D surfaces. Traditionally, geodesic paths on discrete polygon surfaces were computed using shortest path algorithms, such as Dijkstra. However, such algorithms have two major limitations. They are non-differentiable which limits their direct usage in learnable pipelines and they

Keiju Sono

In this paper, we prove that for any $1/2<t<1$, there exists a positive integer $N_{0}$ depending on $t$ such that for any $n_{0}\geq N_{0}$, squares of sidelength $f(n)^{-t}$ for $n\geq n_{0}$ can be packed with disjoint interiors into a square of area $\sum_{n=n_{0}}^{\infty}f(n)^{-2t}$, if the function $f$ satisfies some suitable conditions. The main theo

Hanbyul Lee, Qifan Song, Jean Honorio

We study a practical algorithm for sparse principal component analysis (PCA) of incomplete and noisy data. Our algorithm is based on the semidefinite program (SDP) relaxation of the non-convex $l_1$-regularized PCA problem. We provide theoretical and experimental evidence that SDP enables us to exactly recover the true support of the sparse leading eigenvect

Michael Stephan, Thomas Stadelmayer, Avik Santra, Georg Fischer

This paper presents a parametric variational autoencoder-based human target detection and localization framework working directly with the raw analog-to-digital converter data from the frequency modulated continous wave radar. We propose a parametrically constrained variational autoencoder, with residual and skip connections, capable of generating the cluste

M. Mierla, A. N. Zhukov, D. Berghmans, S. Parenti

We report observations of a unique, large prominence eruption that was observed in the He II 304 {\AA} passband of the the Extreme Ultraviolet Imager/Full Sun Imager telescope aboard Solar Orbiter on 15-16 February 2022. Observations from several vantage points (Solar Orbiter, the Solar-Terrestrial Relations Observatory, the Solar and Heliospheric Observator

Subham Sekhar Sahoo, Anselm Paulus, Marin Vlastelica, Vít Musil

Embedding discrete solvers as differentiable layers has given modern deep learning architectures combinatorial expressivity and discrete reasoning capabilities. The derivative of these solvers is zero or undefined, therefore a meaningful replacement is crucial for effective gradient-based learning. Prior works rely on smoothing the solver with input perturba

Marcel Algueró, Bernat Capdevila, Andreas Crivellin, Joaquim Matias

In this letter we propose a strategy for discerning if new physics in the Wilson coefficient ${\cal C}_{9\mu}$ is dominantly lepton flavour universality violating or if it contains a sizable lepton flavour universal component (${\cal C}_9^{\rm U}$). Distinguishing among these two cases, for which the model independent fit of the related scenarios exhibits si

Alcides Fonseca, Guilherme Espada

Type systems provide software developers immediate feedback about a subset of correctness properties of their programs. IDE integrations often take advantage of type systems to present errors, suggest completions and even improve navigation. On the other hand, understanding the time and energy consumption of the execution of a program requires manual testing

Ronghan Chen, Yang Cong

Rotation-invariant (RI) 3D deep learning methods suffer performance degradation as they typically design RI representations as input that lose critical global information comparing to 3D coordinates. Most state-of-the-arts address it by incurring additional blocks or complex global representations in a heavy and ineffective manner. In this paper, we reveal t

L Bozec, G Cinque, M Reading, H M Pollock

The purpose was two-fold: To explore the capability of the Diamond Synchrotron infra-red so as to include near-field photothermal microspectroscopy (PTMS); and Toward a quantitative nanohistology - investigation of scleroderma using synchrotron radiation (mu- FTIR). With recent advances in AFM, the integration of an IR temperature-based system on an IR beaml

Bálint Máté, Samuel Klein, Tobias Golling, François Fleuret

The two key characteristics of a normalizing flow is that it is invertible (in particular, dimension preserving) and that it monitors the amount by which it changes the likelihood of data points as samples are propagated along the network. Recently, multiple generalizations of normalizing flows have been introduced that relax these two conditions. On the oth

Thomas Voß

We construct a Kitaev model with defects using twists or 2-cocycles of semi-simple, finite-dimensional Hopf algebras as defect data. This data is derived by applying Tannaka duality to Turaev-Viro topological quantum field theories with defects. From this we also derive additional conditions for moving, fusing and braiding excitations in the Kitaev model wit

Narakorn Kaewkhao, Phongpichit Channuie

Oscillating or cyclic models of the universe were inspired by Friedmann's seminal paper of 1922. The model supposes a closed universe. In this work, we study Friedmann closed universe using the adiabatic invariant approach. We start revisiting the cosmological force proposed by N. Rosen and derive the Lagrangian density from Rosen's concepts of cosmological

Deshanee S. Wickramarachchi, Laura Huey Mien Lim, Baoluo Sun

It is often of interest in the health and social sciences to investigate the joint mediation effects of multiple post-exposure mediating variables. Identification of such joint mediation effects generally require no unmeasured confounding of the outcome with respect to the whole set of mediators. As the number of mediators under consideration grows, this key

A. Caranti, Cindy Tsang

Let $G$ be any group. The quotient group $T(G)$ of the multiple holomorph by the holomorph of $G$ has been investigated for various families of groups $G$. In this paper, we shall take $G$ to be a finite $p$-group of class two for any odd prime $p$, in which case $T(G)$ may be studied using certain bilinear forms. For any $n\geq 4$, we exhibit examples of $G

Lu Yin, Vlado Menkovski, Meng Fang, Tianjin Huang

Recent works on sparse neural network training (sparse training) have shown that a compelling trade-off between performance and efficiency can be achieved by training intrinsically sparse neural networks from scratch. Existing sparse training methods usually strive to find the best sparse subnetwork possible in one single run, without involving any expensive

Yanhong A. Liu, Scott D. Stoller, Yi Tong, Bo Lin

Logic rules are powerful for expressing complex reasoning and analysis problems. At the same time, they are inconvenient or impossible to use for many other aspects of applications. Integrating rules in a language with sets and functions, and furthermore with updates to objects, has been a subject of significant study. What's lacking is a language that integ

Beniamino Accattoli

This paper introduces the exponential substitution calculus (ESC), a new presentation of cut elimination for IMELL, based on proof terms and building on the idea that exponentials can be seen as explicit substitutions. The idea in itself is not new, but here it is pushed to a new level, inspired by Accattoli and Kesner's linear substitution calculus (LSC). O

Jianyi Zhang, Leixin Yang, Yuyang Han, Zhi Sun

As a new format of mobile application, mini programs, which function within a larger app and are built with HTML, CSS, and JavaScript web technology, have become the way to do almost everything in China. This paper presents our research on the permissions of mini programs. We conducted a systematic study on 9 popular mobile app ecosystems, which host over 7

Donatien Callon, Ian Lalonde, Mathieu Nadeau, Alexandre Girard

Patient transfer is a challenging, critical task because it exposes caregivers to injury risks. Available transfer devices, like floor lifts, lead to improvements but are far from perfect. They do not eliminate the caregivers risk of musculoskeletal disorders, and they can be burdensome to use due to their poor maneuverability. This paper presents a new moto

Pierre Schumacher, Daniel Häufle, Dieter Büchler, Syn Schmitt

Muscle-actuated organisms are capable of learning an unparalleled diversity of dexterous movements despite their vast amount of muscles. Reinforcement learning (RL) on large musculoskeletal models, however, has not been able to show similar performance. We conjecture that ineffective exploration in large overactuated action spaces is a key problem. This is s

David Criens, Lars Niemann

In this paper we study a family of nonlinear (conditional) expectations that can be understood as a diffusion with uncertain local characteristics. Here, the differential characteristics are prescribed by a set-valued function. We establish its Feller properties and examine how to linearize the associated sublinear Markovian semigroup. In particular, we obse

Tian Wang

Let $A$ be an absolutely simple abelian surface defined over a number field $K$ with a commutative (geometric) endomorphism ring. Let $\pi_{A, \text{split}}(x)$ denote the number of primes $\mathfrak{p}$ in $K$ such that each prime has norm bounded by $x$, of good reduction for $A$, and the reduction of $A$ at $\mathfrak{p}$ splits. It is known that the dens

Chang Nie, Huan Wang, Lu Zhao

Deep neural networks (DNNs) have delivered a remarkable performance in many tasks of computer vision. However, over-parameterized representations of popular architectures dramatically increase their computational complexity and storage costs, and hinder their availability in edge devices with constrained resources. Regardless of many tensor decomposition (TD

Lea Weber

For fixed integer $r\ge 2$, we call a pair $(m,f)$ of integers, $m\geq 1$, $0\leq f \leq \binom{m}{r}$, $absolutely$ $avoidable$ if there is $n_0$, such that for any pair of integers $(n,e)$ with $n>n_0$ and $0\leq e\leq \binom{n}{r}$ there is an $r$-uniform hypergraph on $n$ vertices and $e$ edges that contains no induced sub-hypergraph on $m$ vertices and

Advait Parulekar, Karthikeyan Shanmugam, Sanjay Shakkottai

One method for obtaining generalizable solutions to machine learning tasks when presented with diverse training environments is to find \textit{invariant representations} of the data. These are representations of the covariates such that the best model on top of the representation is invariant across training environments. In the context of linear Structural

Shimin Zhang, Ziteng Wang, Yukai Ju, Yihui Fu

Deep neural networks (DNNs) have shown promising results for acoustic echo cancellation (AEC). But the DNN-based AEC models let through all near-end speakers including the interfering speech. In light of recent studies on personalized speech enhancement, we investigate the feasibility of personalized acoustic echo cancellation (PAEC) in this paper for full-d

Alina B. Steinberg, Fabian Maucher, Svetlana V. Gurevich, Uwe Thiele

To facilitate the analysis of pattern formation and of the related phase transitions in Bose-Einstein condensates (BECs) we present an explicit approximate mapping from the nonlocal Gross-Pitaevskii equation with cubic nonlinearity to a phase field crystal (PFC) model. This approximation is valid close to the superfluid-supersolid phase transition boundary.

Ryosuke Yoshii, Hisao Hayakawa

We theoretically study the entropy production and the work extracted from a system connected to two reservoirs by periodic modulations of the electrochemical potentials of the reservoirs and the parameter of a system Hamiltonian under isothermal conditions. We find that the modulation of the parameters can drive a geometric state, which is away from a nonequ

Alina Carmen Cojocaru, Tian Wang

Let $g \geq 1$ be an integer and let $A/\mathbb{Q}$ be an abelian variety that is isogenous over $\mathbb{Q}$ to %the product $E_1 \times \ldots \times E_g$ of elliptic curves $E_1/\mathbb{Q}$, $\ldots$, $E_g/\mathbb{Q}$, without complex multiplication and pairwise non-isogenous over $\overline{\mathbb{Q}}$. a product of $g$ elliptic curves defined over $\ma

Peter Keevash, Noam Lifshitz, Dor Minzer

A subset $A$ of a group $G$ is called product-free if there is no solution to $a=bc$ with $a,b,c$ all in $A$. It is easy to see that the largest product-free subset of the symmetric group $S_n$ is obtained by taking the set of all odd permutations, i.e. $S_n \setminus A_n$, where $A_n$ is the alternating group. By contrast, it is a long-standing open problem

Piyush Udhan, Akhilesh Ganeshkar, Poobigan Murugesan, Abhishek Raj Permani

Traditional vehicle routing algorithms do not consider the changing nature of traffic. While implementations of Dijkstra's algorithm with varying weights exist, the weights are often changed after the outcome of algorithm is executed, which may not always result in the optimal route being chosen. Hence, this paper proposes a novel vehicle routing algorithm t

Marco Caoduro, Jana Cslovjecsek, Michał Pilipczuk, Karol Węgrzycki

We prove that for any triangle-free intersection graph of $n$ axis-parallel segments in the plane, the independence number $\alpha$ of this graph is at least $\alpha \ge n/4 + \Omega(\sqrt{n})$. We complement this with a construction of a graph in this class satisfying $\alpha \le n/4 + c \sqrt{n}$ for an absolute constant $c$, which demonstrates the optimal

Mukesh K. Vyas

In this paper, we carry out a semi-analytic general relativistic study of a Gamma-Ray Bursts (GRB) jet that is breaking out of a cocoon or stellar envelope. We solve hydrodynamic equations with the relativistic equation of state that takes care of fluid composition. In short GRBs, a general relativistic approach is required to account for curved spacetime in

Jiachen Yang, Zhuo Zhang, Yicheng Gong, Shukun Ma

Data has now become a shortcoming of deep learning. Researchers in their own fields share the thinking that "deep neural networks might not always perform better when they eat more data," which still lacks experimental validation and a convincing guiding theory. Here to fill this lack, we design experiments from Identically Independent Distribution(IID) and

Kit Shing Ng, Pascal O. Vontobel

The permanent of a non-negative matrix appears naturally in many information processing scenarios. Because of the intractability of the permanent beyond small matrices, various approximation techniques have been developed in the past. In this paper, we study the Bethe approximation of the permanent and add to the body of literature showing that this approxim

Timothy Hosgood

The phrase "(co)simplicial (pre)sheaf" can be reasonably interpreted in multiple ways. In this survey we study how the various notions familiar to the author relate to one another. We end by giving some example applications of the most general of these notions.

S. Martinet, G. Meynet, D. Nandal, S. Ekström

The $^{26}$Al short-lived radioactive nuclide is the source of the observed galactic diffuse $\gamma$-ray emission at 1.8 MeV. While different sources of $^{26}$Al have been explored, such as AGB stars, massive stars winds, and supernovae, the contribution of very massive stars has never been studied. We study the stellar wind contribution of very massive st

M. C. Lam, K. W. Yuen, M. J. Green, W. Li

From data collection to photometric fitting and analysis of white dwarfs to generating a white dwarf luminosity function requires numerous Astrophysical, Mathematical and Computational domain knowledge. The steep learning curve makes it difficult to enter the field, and often individuals have to reinvent the wheel to perform identical data reduction and anal

Felipe Portales-Oliva, André G. S. Landulfo

A great deal of evidence has been mounting over the years showing a deep connection between acceleration, radiation, and the Unruh effect. Indeed, the fact that the Unruh effect can be codified in the Larmor radiation emitted by the charge was used to propose an experiment to experimentally confirm the existence of the Unruh thermal bath. However, such conne

V. N. Velizhanin

We present a simple representation for analytically continued nested harmonic sums for the arbitrary complex argument. This representation can be obtained for a wide range of nested harmonic sums from a precomputed database for the pole expressions of these sums near negative integers. We describe the procedure for the precise numerical evaluations of the co

Chris Holder, Matthew Middlehurst, Anthony Bagnall

Time series clustering is the act of grouping time series data without recourse to a label. Algorithms that cluster time series can be classified into two groups: those that employ a time series specific distance measure; and those that derive features from time series. Both approaches usually rely on traditional clustering algorithms such as $k$-means. Our

Sebastian Krieter, Thomas Thüm, Sandro Schulze, Sebastian Ruland

Sampling techniques, such as t-wise interaction sampling are used to enable efficient testing for configurable systems. This is achieved by generating a small yet representative sample of configurations for a system, which circumvents testing the entire solution space. However, by design, most recent approaches for t-wise interaction sampling only consider c

Francesco Longo, Letizia Nicoletti, Antonio Padovano

As the Industry 4.0 takes shape, human operators experience an increased complexity of their daily tasks: they are required to be highly flexible and to demonstrate adaptive capabilities in a very dynamic working environment. It calls for tools and approaches that could be easily embedded into everyday practices and able to combine complex methodologies with

Samuel Boury, Paco Maurer, Sylvain Joubaud, Thomas Peacock

We present an investigation of the resonance conditions of axisymmetric internal wave sub-harmonics in confined and unconfined domains. In both cases, sub-harmonics can be spontaneously generated from a primary wave field if they satisfy at least a resonance condition on their frequencies, of the form $\omega_0 = \pm \omega_1 \pm \omega_2$. We demonstrate th

Olivier Lecompte, William Therrien, Alexandre Girard

Winter conditions, characterized by the presence of ice and snow on the ground, are more likely to lead to road accidents. This paper presents an experimental proof of concept, with a 1/5th scale car platform, of a maneuver selection scheme for low adhesion conditions. In the proposed approach, a model-based estimator first processes the high-dimensional sen

Isabel Harrysson Rodrigues, Andrey Generalov, Anamul Md Hoque, Miika Soikkeli

Further development of the graphene field-effect transistors (GFETs) for high-frequency electronics requires accurate evaluation and study of the mobility of charge carriers in a specific device. Here, we demonstrate that the mobility in the GFETs can be directly characterized and studied using the geometrical magnetoresistance (gMR) effect. The method is fr

ALICE Collaboration

The interaction of $\rm{K}^{-}$ with protons is characterised by the presence of several coupled channels, systems like ${\rm \overline{K}^0}$n and $\pi\Sigma$ with a similar mass and the same quantum numbers as the $\rm{K}^{-}$p state. The strengths of these couplings to the $\rm{K}^{-}$p system are of crucial importance for the understanding of the nature

Long Sun, Jinshan Pan, Jinhui Tang

Lightweight and efficiency are critical drivers for the practical application of image super-resolution (SR) algorithms. We propose a simple and effective approach, ShuffleMixer, for lightweight image super-resolution that explores large convolution and channel split-shuffle operation. In contrast to previous SR models that simply stack multiple small kernel

Sören Bartels, Max Griehl, Jakob Keck, Stefan Neukamm

We introduce a nonlinear, one-dimensional bending-twisting model for an inextensible bi-rod that is composed of a nematic liquid crystal elastomer. The model combines an elastic energy that is quadratic in curvature and torsion with a Frank-Oseen energy for the liquid crystal elastomer. Moreover, the model features a nematic-elastic coupling that relates the

Jaonary Rabarisoa, Valentin Belissen, Florian Chabot, Quoc-Cuong Pham

We present a new self-supervised pre-training of Vision Transformers for dense prediction tasks. It is based on a contrastive loss across views that compares pixel-level representations to global image representations. This strategy produces better local features suitable for dense prediction tasks as opposed to contrastive pre-training based on global image

Guilherme Moraes Rosa, Luiz Bonifacio, Vitor Jeronymo, Hugo Abonizio

Recent work has shown that language models scaled to billions of parameters, such as GPT-3, perform remarkably well in zero-shot and few-shot scenarios. In this work, we experiment with zero-shot models in the legal case entailment task of the COLIEE 2022 competition. Our experiments show that scaling the number of parameters in a language model improves the

Lukas Hauzenberger, Shahed Masoudian, Deepak Kumar, Markus Schedl

Societal biases are reflected in large pre-trained language models and their fine-tuned versions on downstream tasks. Common in-processing bias mitigation approaches, such as adversarial training and mutual information removal, introduce additional optimization criteria, and update the model to reach a new debiased state. However, in practice, end-users and

Jianyi Zhang, Xuanxi Huang, Yaqi Liu, Yuyang Han

Using generative adversarial network (GAN)\cite{RN90} for data enhancement of medical images is significantly helpful for many computer-aided diagnosis (CAD) tasks. A new attack called CT-GAN has emerged. It can inject or remove lung cancer lesions to CT scans. Because the tampering region may even account for less than 1\% of the original image, even state-

Caston Sigauke, Rosinah Mukhodobwane, Wilbert Chagwiza, Winston Garira

With the use of empirical data, this paper focuses on solving financial and investment issues involving extremal dependence of ten pairwise combinations of the five BRICS (Brazil, Russia, India, China, and South Africa) stock markets. Daily closing equity indices from 5 January 2010 to 6 August 2018 are used in the study. Unlike previous literature, we use b

Harm Derksen, Visu Makam, Jeroen Zuiddam

Since the seminal works of Strassen and Valiant it has been a central theme in algebraic complexity theory to understand the relative complexity of algebraic problems, that is, to understand which algebraic problems (be it bilinear maps like matrix multiplication in Strassen's work, or the determinant and permanent polynomials in Valiant's) can be reduced to

Jessica E. Forsyth, Ali H. Al-Anbaki, Berenika Plusa, Simon L. Cotter

We consider the problem of landmark matching between two unlabelled point sets, in particular where the number of points in each cloud may differ, and where points in each cloud may not have a corresponding match. We invoke a Bayesian framework to identify the transformation of coordinates that maps one cloud to the other, alongside correspondence of the poi

Anna Pomyalov, Yuri Lubomirsky, Lara Braverman, Efim A. Brener

A prominent spatiotemporal failure mode of frictional systems is self-healing slip pulses, which are propagating solitonic structures that feature a characteristic length. Here, we numerically derive a family of steady state slip pulse solutions along generic and realistic rate-and-state dependent frictional interfaces, separating large deformable bodies in

Kate Mallory, Daniela Calzetti, Zesen Lin

Dust emission at 8 micron has been extensively calibrated as an indicator of current star formation rate for galaxies and ~kpc-size regions within galaxies. Yet, the exact link between the 8 micron emission and the young stellar populations in galaxies is still under question, as dust grains can be stochastically heated also by older field stars. In order to

V. V. Ryazanov

The time until the failure of some node of the system or until the end of some stage of the operation of the tribological system is associated with the change in entropy in the system that occurs during this time. Methods of the first-passage time by a random process of some given level are used. We assume that the first-passage time is equal to the time to

Haewoon Kwak

Achievement systems have been actively adopted in gaming platforms to maintain players' interests. Among them, trophies in PlayStation games are one of the most successful achievement systems. While the importance of trophy design has been casually discussed in many game developers' forums, there has been no systematic study of the historical dataset of trop

Alexandre Girard, H. Harry Asada

This paper addresses the closed-loop control of an actuator with both a continuous input variable (motor torque) and a discrete input variable (mode selection). In many applications, robots have to bear large loads while moving slowly and also have to move quickly through the air with almost no load, leading to conflicting requirements for their actuators. A

Adnan A. E. Hajomer, Hossein Mani, Nitin Jain, Hou-Man Chin

We report the first continuous-variable quantum key distribution experiment that enables the generation of secure key over a 60 km fiber channel with locally generated local oscillator. This is achieved by controlling the excess noise using machine learning for phase noise compensation while operating the system at a low modulation variance