January 2022 arXiv papers — page 72

Libo Huang, Zhulin An, Xiang Zhi, Yongjun Xu

Generative models often incur the catastrophic forgetting problem when they are used to sequentially learning multiple tasks, i.e., lifelong generative learning. Although there are some endeavors to tackle this problem, they suffer from high time-consumptions or error accumulation. In this work, we develop an efficient and effective lifelong generative model

Rajiblochan Sahoo, Ligesh Theeyancheri, Rajarshi Chakrabarti

Active transport of biomolecules assisted by motor proteins is imperative for the proper functioning of cellular activities. Inspired by the diffusion of active agents in crowded cellular channels, we computationally investigate the transport of an active tracer through a polymer grafted cylindrical channel by varying the activity of the tracer and stickines

Cleaven Chia, Bartholomeus Machielse, Amirhassan Shams-Ansari, Marko Loncar

Diamond offers good optical properties and hosts bright color centers with long spin coherence times. Recent advances in angled-etching of diamond, specifically with reactive ion beam angled etching (RIBAE), have led to successful demonstration of quantum photonic devices operating at visible wavelengths. However, larger devices operating at telecommunicatio

Jonas Löhdefink, Tim Fingscheidt

In recent years, semantic segmentation has taken benefit from various works in computer vision. Inspired by the very versatile CycleGAN architecture, we combine semantic segmentation with the concept of cycle consistency to enable a multitask training protocol. However, learning is largely prevented by the so-called steganography effect, which expresses itse

Victor Ayala, Danilo A. García Hernández, Adriano Da Silva

In this paper we study Almost-Riemannian Structures (ARS) on the class of nonnilpotent, solvable, conneted 3D Lie groups. The nice structures present in such groups allow us to show that the singular locus of ARSs on such groups are always embedded submanifolds.

A. Ranjan, R. Srianand, P. Petitjean, G. Shaw

We present the results of a spectroscopic analysis of extremely strong damped Lyman-{\alpha} absorbers (ESDLAs, log N(Hi)>=21.7) observed with VLT-XShooter. ESDLAs probe gas from within the star-forming disk of the associated galaxies and thus ESDLAs provide a unique opportunity to study the interstellar medium of galaxies at high-redshift. We report column

Jin-Feng Wang, Qing-xin Dong, Yi-Fei Huang, Zhao-Sheng Wang

The interplay between magnetism and the topology of electronic band structure may generate new exotic quantum states. Here we report on a new type of quantum oscillations in the temperature dependent electrical resistivity and specific heat at a constant magnetic field in a polar magnetic Weyl semimetal (WSM) NdAlSi. These novel quantum phenomena arise from

Chang-Sheng Zha, Hanyu Liu, Zhongwu Wang, William A. Bassett

A vast amount of Raman spectroscopic data, obtained using diamond anvil cell technique under in situ high pressure-temperature conditions, has been used for mapping the phase transitions of hydrogen in the temperature range of 300 K to 900 K and pressure up to 300 gigapascal, a pressure-temperature region in which most phase information was unknown previousl

Fulvio Melia

The evidence for a Big Bang origin of the Universe is truly compelling, though its cause remains a complete mystery. As the cosmic spacetime is revealed to us with ever improving detail, however, we are beginning to refine the range of its possible initial conditions -- at least within the framework of current physical theories. The Universe, it seems, is sp

Dan Halbersberg, Matan Halevi, Moshe Salhov

Online advertising is a major source of income for many online companies. One common approach is to sell online advertisements via waterfall auctions, through which a publisher makes sequential price offers to ad networks. The publisher controls the order and prices of the waterfall in an attempt to maximize his revenue. In this work, we propose a methodolog

Graham Manuell

Spectrum constructions appear throughout mathematics as a way of constructing topological spaces from algebraic data. Given a commutative localic semiring R (the pointfree analogue of a topological semiring), we define a spectrum of R which generalises the Stone spectrum of a distributive lattice, the Zariski spectrum of a commutative ring, the Gelfand spect

Ning Qi, Pierre Pinson, Mads R. Almassalkhi, Lin Cheng

Compared with large-scale physical batteries, aggregated and coordinated generic energy storage (GES) resources provide low-cost, but uncertain, flexibility for power grid operations. While GES can be characterized by different types of uncertainty, the literature mostly focuses on decision-independent uncertainties (DIUs), such as exogenous stochastic distu

Sevim Cengiz, Mohammad Yaqub

To assess fetal health during pregnancy, doctors use the gestational age (GA) calculation based on the Crown Rump Length (CRL) measurement in order to check for fetal size and growth trajectory. However, GA estimation based on CRL, requires proper positioning of calipers on the fetal crown and rump view, which is not always an easy plane to find, especially

M. H. M. Christianen, J. Cruise, A. J. E. M. Janssen, S. Shneer

We compare stability regions for different power flow models in the process of charging electric vehicles (EVs) by considering their random arrivals, their stochastic demand for energy at charging stations, and the characteristics of the electricity distribution network. We assume the distribution network is a line with charging stations located on it. We co

Min Li, Shichun Huang, Zhaohuan Zhu, Michail I. Petaev

The maximum temperature and radial temperature profile in a protoplanetary disc are important for the condensation of different elements in the disc. We simulate the evolution of a set of protoplanetary discs from the collapse of their progenitor molecular cloud cores as well as the dust decoupling within the discs as they evolve. We show how the initial pro

Matheus Bernardini, Wanderson Tenório, Guilherme Tizziotti

In this paper we introduce the concept of corner element of a generalized numerical semigroup, which extends in a sense the idea of conductor of a numerical semigroup to generalized numerical semigroups in higher dimensions. We present properties of this new notion and its relations with existing invariants in the literature, and provide an algorithm to comp

Tiago J. Fonseca, Nils Matthes

We study differential forms on the universal vector extension $A^\natural$ of an abelian scheme $A$ in characteristic zero, and derive a new construction of the $D$-group scheme structure on $A^\natural$. This gives, in particular, a rather simple description of the Gauss--Manin connection on the de Rham cohomology of $A$ in terms of global algebraic differe

Dennis J. N. J. Soemers, Éric Piette, Matthew Stephenson, Cameron Browne

In many board games and other abstract games, patterns have been used as features that can guide automated game-playing agents. Such patterns or features often represent particular configurations of pieces, empty positions, etc., which may be relevant for a game's strategies. Their use has been particularly prevalent in the game of Go, but also many other ga

Zhuang Ni, Wei Hu, Qinghua Zhang, Yanmin Zhang

The family of titanium oxide superconductors exhibits many intriguing phenomena comparable to cuprates and iron pnictides/chalcogenides, and thus provides an ideal platform to contrastively study the unconventional pairing mechanism of high-temperature superconductors. Here, we successfully deposit superconducting Mg-Ti-O films on MgAl$_2$O$_4$ substrates wi

Zhiyong Sun, Marcus Greiff, Anders Robertsson, Rolf Johansson

We consider the problem of cooperative motion coordination for multiple heterogeneous mobile vehicles subject to various constraints. These include nonholonomic motion constraints, constant speed constraints, holonomic coordination constraints, and equality/inequality geometric constraints. We develop a general framework involving differential-algebraic equa

Hao Wang, Yuxuan Qin, ChonLam Lao, Yanfang Le

As the scale of distributed training grows, communication becomes a bottleneck. To accelerate the communication, recent works introduce In-Network Aggregation (INA), which moves the gradients summation into network middle-boxes, e.g., programmable switches to reduce the traffic volume. However, switch memory is scarce compared to the volume of gradients tran

Wanqi Xue, Bo An, Chai Kiat Yeo

How resources are deployed to secure critical targets in networks can be modelled by Network Security Games (NSGs). While recent advances in deep learning (DL) provide a powerful approach to dealing with large-scale NSGs, DL methods such as NSG-NFSP suffer from the problem of data inefficiency. Furthermore, due to centralized control, they cannot scale to sc

Qingsong Gu, Xueping Huang, Yuhua Sun

Let $(V,\mu)$ be an infinite, connected, locally finite weighted graph. We study the problem of existence or non-existence of positive solutions to a semi-linear elliptic inequality \begin{equation*} \Delta u+u^{\sigma}\leq0\quad \text{in}\,\,V, \end{equation*} where $\Delta$ is the standard graph Laplacian on $V$ and $\sigma>0$. For $\sigma\in(0,1]$, the in

Fabian Walter, Marcel Neeleman, Roberto Decarli, Bram Venemans

We present 0".035 resolution (~200 pc) imaging of the 158 um [CII] line and the underlying dust continuum of the z=6.9 quasar J234833.34-305410.0. The 18 h ALMA observations reveal extremely compact emission (diameter ~1 kpc) that is consistent with a simple, almost face-on, rotation-supported disk with a significant velocity dispersion of ~160 km/s. The gas

Hou-Jun Lü, Hao-Yu Yuan, Ting-Feng Yi, Xiang-Gao Wang

Long-duration gamma-ray bursts (GRBs) associated with supernovae (SNe) are believed to originate from massive star core-collapse events, whereas short-duration GRBs that are related to compact star mergers are expected to be accompanied by kilonovae. GRB 211227A, which lasted about 84 s, had an initial short/hard spike followed by a series of soft gamma-ray

Jianhua Wang, Lu Qin, Baofeng Wu

In this paper, we improve the cube attack by exploiting low-degree factors of the superpoly w.r.t. certain "special" index set of cube (ISoC). This can be viewed as a special case of the correlation cube attack proposed at Eurocrypt 2018, but under our framework more beneficial equations on the key variables can be obtained in the key-recovery phase. To moun

Qin-Song Zhou, Jun-Zhang Wang, Xiang Liu, Takayuki Matsuki

The properties of the light vector meson states around 2.0 GeV have been poorly understood for a long time, which has become a barrier to the expansion to higher light vector meson spectrum. Recently, the BESIII collaboration released the measurements of the $e^+ e^- \to \omega\pi^0$ and $e^+ e^- \to \rho\eta^{\prime}$ reactions above 2.0 GeV, both of which

Jendrik Voss, Robert J. Martin, Oliver Sander, Siddhant Kumar

Deciding whether a given function is quasiconvex is generally a difficult task. Here, we discuss a number of numerical approaches that can be used in the search for a counterexample to the quasiconvexity of a given function $W$. We will demonstrate these methods using the planar isotropic rank-one convex function \[ W_{\rm magic}^+(F)=\frac{\lambda_{\rm max}

Luca Insolia, Domenico Perrotta

We address general-shaped clustering problems under very weak parametric assumptions with a two-step hybrid robust clustering algorithm based on trimmed k-means and hierarchical agglomeration. The algorithm has low computational complexity and effectively identifies the clusters also in presence of data contamination. We also present natural generalizations

Alabi Bojesomo, Hasan Al Marzouqi, Panos Liatsis

Traffic forecasting is an important element of mobility management, an important key that drives the logistics industry. Over the years, lots of work have been done in Traffic forecasting using time series as well as spatiotemporal dynamic forecasting. In this paper, we explore the use of vision transformer in a UNet setting. We completely remove all convolu

Holger Drees

We analyze the extreme value dependence of independent, not necessarily identically distributed multivariate regularly varying random vectors. More specifically, we propose estimators of the spectral measure locally at some time point and of the spectral measures integrated over time. The uniform asymptotic normality of these estimators is proved under suita

Saverio Rossi, Gilles Tarjus

We study the mean-field limit of an elasto-plastic model introduced to describe the yielding transition of athermally and quasi-statically sheared amorphous solids. We focus on the sample-to-sample fluctuations, which we characterize analytically, and investigate in detail the analogy with the athermally driven random-field Ising model. We stress that the ra

Karl Friston, Lancelot Da Costa, Noor Sajid, Conor Heins

This paper provides a concise description of the free energy principle, starting from a formulation of random dynamical systems in terms of a Langevin equation and ending with a Bayesian mechanics that can be read as a physics of sentience. It rehearses the key steps using standard results from statistical physics. These steps entail (i) establishing a parti

Alex Bäuerle, Aybuke Gul Turker, Ken Burke, Osman Aka

While the need for well-trained, fair ML systems is increasing ever more, measuring fairness for modern models and datasets is becoming increasingly difficult as they grow at an unprecedented pace. One key challenge in scaling common fairness metrics to such models and datasets is the requirement of exhaustive ground truth labeling, which cannot always be do

Karel Devriendt, Renaud Lambiotte

This article introduces a new approach to discrete curvature based on the concept of effective resistances. We propose a curvature on the nodes and links of a graph and present the evidence for their interpretation as a curvature. Notably, we find a relation to a number of well-established discrete curvatures (Ollivier, Forman, combinatorial curvature) and s

Chris Emmery, Ákos Kádár, Grzegorz Chrupała, Walter Daelemans

A limited amount of studies investigates the role of model-agnostic adversarial behavior in toxic content classification. As toxicity classifiers predominantly rely on lexical cues, (deliberately) creative and evolving language-use can be detrimental to the utility of current corpora and state-of-the-art models when they are deployed for content moderation.

Jie Song, Huawei Yi, Wenqian Xu, Xiaohui Li

The proposal of perceptual loss solves the problem that per-pixel difference loss function causes the reconstructed image to be overly-smooth, which acquires a significant progress in the field of single image super-resolution reconstruction. Furthermore, the generative adversarial networks (GAN) is applied to the super-resolution field, which effectively im

Soma N. Ghosh, Vineet Sahula, Lava Bhargava

Multi-core processors improve performance, but they can create unpredictability owing to shared resources such as caches interfering. Cache partitioning is used to alleviate the Worst-Case Execution Time (WCET) estimation by isolating the shared cache across each thread to reduce interference. It does, however, prohibit data from being transferred between pa

Felix Finster, Robert H. Jonsson, Niki Kilbertus

The numerical analysis of causal fermion systems is advanced by employing differentiable programming methods. The causal action principle for weighted counting measures is introduced for general values of the integer parameters $f$ (the particle number), $n$ (the spin dimension) and $m$ (the number of spacetime points). In the case $n=1$, the causal relation

Sven Pfeiffer, Valeri Ayvazyan, Julien Branlard, Thorsten Buettner

The free-electron laser FLASH at DESY and the European XFEL are operated with superconducting radio frequency cavities and supply beam to several user experiments. The switching time between experiments is limited to dozens of microseconds. This contribution will show a regulation with a frequency shifted superconducting cavity to manipulate and change the a

Timothée Goubault de Brugière, Marc Baboulin, Benoît Valiron, Simon Martiel

In quantum computing the decoherence time of the qubits determines the computation time available and this time is very limited when using current hardware. In this paper we minimize the execution time (the depth) for a class of circuits referred to as linear reversible circuits, which has many applications in quantum computing (e.g., stabilizer circuits, CN

Hyeon Jeon, Michaël Aupetit, Soohyun Lee, Kwon Ko

Brushing is a common interaction technique in 2D scatterplots, allowing users to select clustered points within a continuous, enclosed region for further analysis or filtering. However, applying conventional brushing to 2D representations of multidimensional (MD) data, i.e., Multidimensional Projections (MDPs), can lead to unreliable cluster analysis due to

Nima Rafiee, Rahil Gholamipoorfard, Nikolas Adaloglou, Simon Jaxy

Detecting whether examples belong to a given in-distribution or are Out-Of-Distribution (OOD) requires identifying features specific to the in-distribution. In the absence of labels, these features can be learned by self-supervised techniques under the generic assumption that the most abstract features are those which are statistically most over-represented

Danielle Angella, Arturas Dubickas, Alexandra Otiman, Jonas Stelzig

We study metric and cohomological properties of Oeljeklaus-Toma manifolds. In particular, we describe the structure of the double complex of differential forms and its Bott-Chern cohomology and we characterize the existence of pluriclosed (aka SKT) metrics in number-theoretic and cohomological terms. Moreover, we prove they do not admit any Hermitian metric

Chen Lin, Zheyang Li, Bo Peng, Haoji Hu

This paper introduces a post-training quantization~(PTQ) method achieving highly efficient Convolutional Neural Network~ (CNN) quantization with high performance. Previous PTQ methods usually reduce compression error via performing layer-by-layer parameters calibration. However, with lower representational ability of extremely compressed parameters (e.g., th

Volker Branding, Georges Habib

We derive various eigenvalue estimates for the Hodge Laplacian acting on differential forms on weighted Riemannian manifolds. Our estimates unify and extend various results from the literature and we provide a number of geometric applications. In particular, we derive an inequality which relates the eigenvalues of the Jacobi operator for (f)-minimal hypersur

Zhouxia Wang, Jiawei Zhang, Runjian Chen, Wenping Wang

Blind face restoration is to recover a high-quality face image from unknown degradations. As face image contains abundant contextual information, we propose a method, RestoreFormer, which explores fully-spatial attentions to model contextual information and surpasses existing works that use local operators. RestoreFormer has several benefits compared to prio

Andreas Bauer, Jasna Omeragic

In this study, we identify the relative standard deviation volatility (RSD volatility) in the individual target time fulfilment of the complete set of comparables (e.g., all individuals in the same organisational structure) as a possible key performance indicator (KPI) for predicting employee job performance. KPIs are a well-established, measurable benchmark

Kyle Fogarty, Evelina Ametova, Genoveva Burca, Alexander M. Korsunsky

Point by point strain scanning is often used to map the residual stress (strain) in engineering materials and components. However, the gauge volume and hence spatial resolution is limited by the beam defining apertures and can be anisotropic for very low and high diffraction (scattering) angles. Alternatively, wavelength resolved neutron transmission imaging

Carsten Kutzner, Christian Kniep, Austin Cherian, Ludvig Nordstrom

We assess costs and efficiency of state-of-the-art high performance cloud computing compared to a traditional on-premises compute cluster. Our use case are atomistic simulations carried out with the GROMACS molecular dynamics (MD) toolkit with a focus on alchemical protein-ligand binding free energy calculations. We set up a compute cluster in the Amazon Web

Siyu Bian, Yi Wang, Zun Wang, Mian Zhu

We investigate obstacles of superluminal "warp drive" travels from interactions with interstellar matter and from curvature effects. The effect of collision of interstellar dust particles and photons with the spacecraft will all lead to a pressure proportional to the apparent velocity of the spaceship $v_s$. The force exerted on the spacecraft from the curva

Tiantian Mao, Ruodu Wang, Qinyu Wu

We introduce a new approach for prudent risk evaluation based on stochastic dominance, which will be called the model aggregation (MA) approach. In contrast to the classic worst-case risk (WR) approach, the MA approach produces not only a robust value of risk evaluation but also a robust distributional model, independent of any specific risk measure. The MA

Bryant Rosado Silva, Rodney Josué Biezuner

When one considers the collection $\mathcal{H}(\mathbb{R}^n)$ of all compact subsets of $\mathbb{R}^n$ and equip it with a topology, many questions can be asked about the topological space one ends up with. This is an example of a hyperspace, a mathematical object which has been studied in a more abstract setting since the beginning of the 20th century. Here

Igor Brandão, Daniel Tandeitnik, Thiago Guerreiro

Simulating quantum states on a classical computer is hard, typically requiring prohibitive resources in terms of memory and computational power. Efficient simulation, however, can be achieved for certain classes of quantum states, in particular the so-called Gaussian quantum states of continuous variable systems. In this work we introduce QuGIT - a python nu

Yixin Liu, Yu Zheng, Daokun Zhang, Hongxu Chen

In recent years, graph neural networks (GNNs) have emerged as a successful tool in a variety of graph-related applications. However, the performance of GNNs can be deteriorated when noisy connections occur in the original graph structures; besides, the dependence on explicit structures prevents GNNs from being applied to general unstructured scenarios. To ad

Fatma Altunbulak Aksu, İpek Tuvay

In 1979, Miller proved that for a group $G$ of odd order, two minimal group codes in $\mathbb{F}_2G$ are $G$-equivalent if and only they have identical weight distribution. In 2014, Ferraz-Guerreiro-Polcino Milies disprove Miller's result by giving an example of two non-$G$-equivalent minimal codes with identical weight distribution. In this paper, we give a

Alberto Giammarino, Juan M. Gandarias, Pietro Balatti, Mattia Leonori

This paper presents a mobile supernumerary robotic approach to physical assistance in human-robot conjoined actions. The study starts with a description of the SUPER-MAN concept. The idea is to develop and utilize mobile collaborative systems that can follow human loco-manipulation commands to perform industrial tasks through three main components: i) an adm

Manoj Kumar Keshari, Maria Ann Mathew

Let $R$ be a commutative noetherian ring of dimension $d$ and $M$ be a commutative$,$ cancellative$,$ torsion-free monoid of rank $r$. Then $S$-$dim(R[M]) \leq max\{1, dim(R[M])-1 \} = max\{1, d+r-1 \}$. Further$,$ we define a class of monoids $\{\mathfrak{M}_n\}_{n \geq 1}$ such that if $M \in \mathfrak{M}_n$ is seminormal$,$ then $S$-$dim(R[M]) \leq dim(R[

Florian Schummer, Maximilian Hyba

Model-Based Systems Engineering aims at creating a model of a system under development, covering the complete system with a level of detail that allows to define and understand its behavior and enables to define any interface and workpackage based on the model. Once such a model is established, further benefits can be reaped, such as the analysis of complex

Matthew Rogers, Kasper Rasmussen

The CAN Bus is crucial to the efficiency, and safety of modern vehicle infrastructure. Electronic Control Units (ECUs) exchange data across a shared bus, dropping messages whenever errors occur. If an ECU generates enough errors, their transmitter is put in a bus-off state, turning it off. Previous work abuses this process to disable ECUs, but is trivial to

E. Håkansson, A. Piveteau, S. Muhammad, M. Bourennane

Quantum correlation between nodes in a network which consist of several independent sources of entanglement and in multipartite entanglement systems are important for general understanding of the nature of nonlocality, quantum information processing and communication. In previous years, demonstrations of network nonlocality for bilocal scenarios have been in

Yu Cui, Xiao-Yi Liu, Xu-Fei Ma, Jia-Pei Deng

The formation of Frohlich polaron in metal halide perovskites, arising from the charge carrierlongitudinal optical (LO) phonon coupling, has been proposed to explain their exceptional properties, but the effective identification of polaron in these materials is still a challenge task. Herein, we theoretically present the infrared optical absorption of Frohli

Ali Ebrahimzadeh Esfahani, Mehdi Nemati

Let ${\mathcal A}$ be a Banach algebra with the properties that $\mathrm{rad}({\mathcal A})={\rm rann}({\mathcal A})$ and the algebra ${\mathcal A}/\mathrm{rad}({\mathcal A})$ is commutative. We show that a derivation of ${\mathcal A}$ maps ${\mathcal A}$ into ${\rm rad}({\mathcal A})$. Using this, we determine among other things when a generalized derivatio

Yiwen Li, Yunguan Fu, Qianye Yang, Zhe Min

The ability to adapt medical image segmentation networks for a novel class such as an unseen anatomical or pathological structure, when only a few labelled examples of this class are available from local healthcare providers, is sought-after. This potentially addresses two widely recognised limitations in deploying modern deep learning models to clinical pra

Zhitong Xiong, Sining Chen, Yilei Shi, Xiao Xiang Zhu

Monocular height estimation (MHE) from remote sensing imagery has high potential in generating 3D city models efficiently for a quick response to natural disasters. Most existing works pursue higher performance. However, there is little research exploring the interpretability of MHE networks. In this paper, we target at exploring how deep neural networks pre

K. Raspe, M. Müller, N. Iwe, R. N. Wolf

Using the example of metal clusters, an experimental setup and procedure is presented, which allows for the generation of size and charge-state selected polyanions from monoanions in a molecular beam. As a characteristic feature of this modular setup, the further charging process via sequential electron attachment within a 3-state digital trap takes place af

Cristian Alb

A probabilistic alternative to the Gower distance is proposed. The probabilistic distance enables the realization of a generic deodata predictor.

Tom Bewley, Jonathan Lawry, Arthur Richards

We introduce a data-driven, model-agnostic technique for generating a human-interpretable summary of the salient points of contrast within an evolving dynamical system, such as the learning process of a control agent. It involves the aggregation of transition data along both spatial and temporal dimensions according to an information-theoretic divergence mea

Muhammad Ali Siddiqi, Georg Hahn, Said Hamdioui, Wouter A. Serdijn

A Medical Body Area Network (MBAN) is an ensemble of collaborating, potentially heterogeneous, medical devices located inside, on the surface of or around the human body with the objective of tackling one or multiple medical conditions of the MBAN host. These devices -- which are a special category of Wireless Body Area Networks (WBANs) -- collect, process a

Anna Kubin, Luca Lussardi, Marco Morandotti

The existence of minimizers of the Canham--Helfrich functional in the setting of generalized Gauss graphs is proved. As a first step, the Canham--Helfrich functional, usually defined on regular surfaces, is extended to generalized Gauss graphs, then lower semicontinuity and compactness are proved under a suitable condition on the bending constants ensuring c

Fumio Hiroshima, Noriaki Teranishi

A time operator $\hat T_\eps$ of the one-dimensional harmonic oscillator $ \hat h_\eps=\half(p^2+\eps q^2)$ is rigorously constructed. It is formally expressed as $ \hat T_\eps=\half\frac{1}{\sqrt \eps } (\arctan (\sqrt \eps \hat t_0)+\arctan (\sqrt \eps \hat t_1))$ with $\hat t_0=p^{-1}q$ and $\hat t_1=qp^{-1}$. It is shown that the canonical commutation re

Mehmet Önder

This study introduces a new type of general helix called associated helix which is associated to a special surface curve. The basic idea is to determinate the parametric form of an associated helix by means of Darboux frame and surface curvatures of a special surface curve such as helical curve, relatively normal-slant helix or isophote curve. For each surfa

Hosung Kim, Jeong-Seop Kim, Yongnam Lee

In this paper, we study the positivity property of the tangent bundle $T_X$ of a Fano threefold $X$ with Picard number 2. We determine the bigness of the tangent bundle of the whole 36 deformation types. Our result shows that $T_X$ is big if and only if $(-K_X)^3\ge 34$. As a corollary, we prove that the tangent bundle is not big when $X$ has a standard coni

Nanna Zhou Hagström, Michael Schneider, Nico Kerber, Alexander Yaroslavtsev

The advent of X-ray free-electron lasers (XFELs) has revolutionized fundamental science, from atomic to condensed matter physics, from chemistry to biology, giving researchers access to X-rays with unprecedented brightness, coherence, and pulse duration. All XFEL facilities built until recently provided X-ray pulses at a relatively low repetition rate, with

Pooja Yadav, Mamta Kamra, Rajpal

S-metric space was introduced by Sedghi et al. in 2012. We derive some common fixed point results for self-mappings on vector valued complete S-metric space. In support of our results, we also give some examples.

Elena Campillo, Almudena Martínez, Jimena de Hita, Miguel León

In this study, the properties of an oscillating system composed of a pendulum connected to a seesaw and placed on a moving platform with a certain slope are analyzed. Using complex numbers to collect the information contained in the system proves to be crucial in order to observe the properties described by both cross and dot products. The representation of

Moataz Mohammed, Mostafa M. Aref

The conversational agents is one of the most interested topics in computer science field in the recent decade. Which can be composite from more than one subject in this field, which you need to apply Natural Language Processing Concepts and some Artificial Intelligence Techniques such as Deep Learning methods to make decision about how should be the response

Wenning Ren, Kuijuan Jin, Erjia Guo, Chen Ge

Using first-principles calculations, we investigated the magnetic, electronic, and structural properties of oxygen-substituted NaMnF3 (NaMnF1.5O1.5) with in-plane biaxial strain. For simplicity, a structure containing an oxygen octahedron is used to explore the underlying physical mechanism. We found that the oxygen octahedron induces a transition from an in

Hwanil Choi, Wonjoon Chang, Jaesik Choi

Even though Generative Adversarial Networks (GANs) have shown a remarkable ability to generate high-quality images, GANs do not always guarantee the generation of photorealistic images. Occasionally, they generate images that have defective or unnatural objects, which are referred to as 'artifacts'. Research to investigate why these artifacts emerge and how

Junfeng Liu

In this paper, we study a class of nonlinear space-time fractional stochastic kinetic equations in $\mathbb{R}^d$ with Gaussian noise which is white in time and homogeneous in space. This type of equation constitutes an extension of the non-linear stochastic heat equation involving fractional derivative in time and fractional Laplacian in space. We give a ne

Shivin Srivastava, Kenji Kawaguchi, Vaibhav Rajan

A widely used paradigm to improve the generalization performance of high-capacity neural models is through the addition of auxiliary unsupervised tasks during supervised training. Tasks such as similarity matching and input reconstruction have been shown to provide a beneficial regularizing effect by guiding representation learning. Real data often has compl

Mattia Cerrato, Marius Köppel, Alexander Segner, Stefan Kramer

Neural network architectures have been extensively employed in the fair representation learning setting, where the objective is to learn a new representation for a given vector which is independent of sensitive information. Various "representation debiasing" techniques have been proposed in the literature. However, as neural networks are inherently opaque, t

Yuke Li, Victor Steinberg

We report experimental results on elastic instability in a viscoelastic channel shear flow due to only a natural non-smoothed inlet and small holes along the channel for pressure measurements. We show that non-normal mode instability results in elastic waves and chaotic flow self-organized into periodically cycled stream-wise streaks synchronized by elastic

David Bold, Felix Reimold, Holger Niemann, Yu Gao

Modelling the scrape-off layer of a stellarator is challenging due to the complex magnetic 3D geometry. The here presented study analyses simulations of the scrape-off layer (SOL) of the stellarator Wendelstein 7-X (W7-X) using the EMC3-EIRENE code for the magnetic standard configuration. Comparing with experimental observations, the transport model is valid

Aleksandrina V. Kirkova, Diego Porras, Peter A. Ivanov

We investigate signatures of chaos and equilibration in the quantum Rabi model, which exhibits a quantum phase transition when the ratio of the atomic level-splitting to bosonic frequency grows to infinity. We show that out-of-time-order correlator derived from the Loschmidt echo signal quickly saturates in the normal phase and reveals exponential growth in

Mengyu Cao, Mei Lu, Benjian Lv, Kaishun Wang

Let $V$ be an $n$-dimensional vector space over the finite field $\mathbb{F}_q$, and ${V\brack k}$ denote the family of all $k$-dimensional subspaces of $V$. The families $\mathcal{F}_1\subseteq{V\brack k_1},\mathcal{F}_2\subseteq{V\brack k_2},\ldots,\mathcal{F}_r\subseteq{V\brack k_r}$ are said to be $r$-cross $t$-intersecting if $\dim(F_1\cap F_2\cap\cdots

Dominic Atherton, Angelos Michaelides, Stephen J. Cox

In principle, the answer to the posed titular question is undoubtedly 'yes.' But in practice, requisite reference data for homogeneous systems have been obtained with a treatment of intermolecular interactions that is different from that typically employed for heterogeneous systems. In this article, we assess the impact of the choice of truncation scheme whe

Verena Biener, Travis Gesslein, Daniel Schneider, Felix Kawala

Virtual Reality (VR) has the potential to support mobile knowledge workers by complementing traditional input devices with a large three-dimensional output space and spatial input. Previous research on supporting VR knowledge work explored domains such as text entry using physical keyboards and spreadsheet interaction using combined pen and touch input. Insp

Mattia Cerrato, Marius Köppel, Alexander Segner, Stefan Kramer

The issue of fairness in machine learning stems from the fact that historical data often displays biases against specific groups of people which have been underprivileged in the recent past, or still are. In this context, one of the possible approaches is to employ fair representation learning algorithms which are able to remove biases from data, making grou

Aintzane Mosteiro-Sanchez, Marc Barcelo, Jasone Astorga, Aitor Urbieta

Data exchange among value chain partners provides them with a competitive advantage, but the risk of exposing sensitive data is ever-increasing. Information must be protected in storage and transmission to reduce this risk, so only the data producer and the final consumer can access or modify it. End-to-end (E2E) security mechanisms address this challenge, p

Berta Margalef-Bentabol, Christopher J. Conselice, Boris Haeussler, Kevin Casteel

Many aspects concerning the formation of spiral and disc galaxies remain unresolved, despite their discovery and detailed study over the past $150$ years. As such, we present the results of an observational search for proto-spiral galaxies and their earliest formation, including the discovery of a significant population of spiral-like and clumpy galaxies at

Masahito Hayashi, Naqueeb Ahmad Warsi

We study commitment scheme for classical-quantum channels. To accomplish this we define various notions of commitment capacity for these channels and prove matching upper and lower bound on it in terms of the conditional entropy. Our achievability (lower bound) proof is quantum generalisation of the work of one of the authors (arXiv:2103.11548) which studied

Zeyu Wang, Abdollah Shafieezadeh, Xiong Xiao, Xiaowei Wang

The maturity of structural health monitoring technology brings ever-increasing opportunities for geotechnical structures and underground infrastructure systems to track the risk of structural failure, such as settlement-induced building damage, based on the monitored data. Reliability updating techniques can offer solutions to estimate the probability of fai

Nigel Hitchin

We use the notion of the principal three-dimensional subgroup of a simple Lie group to identify certain special subspaces of the Lie algebra and address the question of whether these are calibrated for invariant forms on the group.

Julia C. Santos, Leonardo Bronfman, Edgar Mendoza, Jacques R. D. Lépine

A spectral survey of methyl acetylene (CH3CCH) was conducted toward the hot molecular core/outflow G331.512-0.103. Our APEX observations allowed the detection of 41 uncontaminated rotational lines of CH3CCH in the frequency range between 172-356 GHz. Through an analysis under the local thermodynamic equilibrium assumption, by means of rotational diagrams, we

Niccoló Marini, Manfredo Atzori, Sebastian Otálora, Stephane Marchand-Maillet

Computational pathology is a domain that aims to develop algorithms to automatically analyze large digitized histopathology images, called whole slide images (WSI). WSIs are produced scanning thin tissue samples that are stained to make specific structures visible. They show stain colour heterogeneity due to different preparation and scanning settings applie

Fabian Flassig, Rasmus Flaschmann, Thomas Kainz, Sven Ernst

Rapid development in integrated optoelectronic devices and quantum photonic architectures creates a need for optical fiber to chip coupling with low losses. Here we present a fast and generic approach that allows temperature stable self-aligning connections of nanophotonic devices to optical fibers. We show that the attainable precision of our approach is eq

Vladimir Spokoiny

The aim of this note is to state a couple of general results about the properties of the penalized maximum likelihood estimators (pMLE) and of the posterior distribution for parametric models in a non-asymptotic setup and for possibly large or even infinite parameter dimension. We consider a special class of stochastically linear smooth (SLS) models satisfyi

Luca Baldesi, Francesco Restuccia, Tommaso Melodia

Today's radio access networks (RANs) are monolithic entities which often operate statically on a given set of parameters for the entirety of their operations. To implement realistic and effective spectrum sharing policies, RANs will need to seamlessly and intelligently change their operational parameters. In stark contrast with existing paradigms, the new O-

Umang Mathur, Andreas Pavlogiannis, Hünkar Can Tunç, Mahesh Viswanathan

Dynamic techniques are a scalable and effective way to analyze concurrent programs. Instead of analyzing all behaviors of a program, these techniques detect errors by focusing on a single program execution. Often a crucial step in these techniques is to define a causal ordering between events in the execution, which is then computed using vector clocks, a si