November 2020 arXiv papers — page 43

Jie Gao, Weihua Zhuang, Mushu Li, Xuemin

In this two-part paper, we propose a novel medium access control (MAC) protocol for machine-type communications in the industrial internet of things. The considered use case features a limited geographical area and a massive number of devices with sporadic data traffic and different priority types. We target at supporting the devices while satisfying their q

Vivek Tewary

We study Bloch wave homogenization of periodically heterogeneous media with fourth order singular perturbations. We recover different homogenization regimes depending on the relative strength of the singular perturbation and length scale of the periodic heterogeneity. The homogenized tensor is obtained in terms of the first Bloch eigenvalue. The higher Bloch

Amir Mohammad Esmaieeli Sikaroudi, Md Habibor Rahman

In this research, a model is proposed to learn from event log and predict future events of a system. The proposed PEDF model learns based on events' sequences, durations, and extra features. The PEDF model is built by a network made of standard clusterers and classifiers, and it has high flexibility to update the model iteratively. The model requires to extr

Ivan D. Chipchakov

Let $K$ be a global or local field, $E/K$ a Galois extension, and Br$(E)$ the Brauer group of $E$. This paper shows that if $K$ is a local field, $v$ is its natural discrete valuation, $v'$ is the valuation of $E$ extending $v$, and $q$ is the characteristic of the residue field $\widehat E$ of $(E, v')$, then Br$(E) = \{0\}$ if and only if the following con

Yuanxin Zhong

With the growth of machine learning algorithms with geometry primitives, a high-efficiency library with differentiable geometric operators are desired. We present an optimized Differentiable Geometry Algorithm Library (DGAL) loaded with implementations of differentiable operators for geometric primitives like lines and polygons. The library is a header-only

Rita Maji, Eleonora Luppi, Nathalie Capron, Elena Degoli

Multi-crystalline silicon is widely used for producing low-cost and high-efficiency solar cells. During crystal growth and device fabrication, silicon solar cells contain grain boundaries (GBs) which are preferential segregation sites for atomic impurities such as oxygen atoms. GBs can induce charge carriers recombination significantly reducing carrier lifet

Soham Basu

Achieving large bandwidth at strong mode conversion strengths is a central problem in few-mode optical waveguides. The most uncomplicated modification of a standard mode-converting grating is to incorporate a single extra gap. Such simple design has not been applied yet for broadening conversion spectrum between core modes of any few-mode waveguide e.g. few-

Nadia Kausar, Ijaz Ahmed, Ather M. W

The observability of charged Higgs $ H^{\pm} $ has been investigated at future lepton collider by assuming type-I 2HDM, at a centre of mass energy $ \sqrt{s}=1.5$ TeV. The signal process chain is $ e^{+}e^{-} \rightarrow Z^{*}/ \gamma^{*}\rightarrow H^{+} H^{-}\rightarrow H W^{+} H W^{-}\rightarrow b \overline{b} jjb \overline{b} jj$. The process proceed thr

Cyrus Cousins, Shahrzad Haddadan, Eli Upfal

We introduce a novel statistical measure for MCMC-mean estimation, the inter-trace variance ${\rm trv}^{(\tau_{rel})}({\cal M},f)$, which depends on a Markov chain ${\cal M}$ and a function $f:S\to [a,b]$. The inter-trace variance can be efficiently estimated from observed data and leads to a more efficient MCMC-mean estimator. Prior MCMC mean-estimators rec

Shu Gong, Kaibo Xing, Andrzej Cichocki, Junhua Li

Deep learning has achieved excellent performance in a wide range of domains, especially in speech recognition and computer vision. Relatively less work has been done for EEG, but there is still significant progress attained in the last decade. Due to the lack of a comprehensive and topic widely covered survey for deep learning in EEG, we attempt to summarize

Mustafa Tosun, Umut Can Cabuk, Vahid Khalilpour Akram, Orhan Dagdeviren

Drone networks are becoming increasingly popular in recent years and they are being used in many applications such as area coverage, delivery systems, military operations, etc. Area coverage is a broad family of applications where a group of connected drones collaboratively visit the whole or parts of an area to fulfill a specific objective and is widely bei

The Jefferson Lab Hall A Collaboration, M. Dlamini, B. Karki, S. F. Ali

We report measurements of the exclusive neutral pion electroproduction cross section off protons at large values of $x_B$ (0.36, 0.48 and 0.60) and $Q^2$ (3.1 to 8.4 GeV$^2$) obtained from Jefferson Lab Hall A experiment E12-06-014. The corresponding structure functions $d\sigma_L/dt+\epsilon d\sigma_T/dt$, $d\sigma_{TT}/dt$, $d\sigma_{LT}/dt$ and $d\sigma_{

Li Wang, Lei-Hong Zhang, Chungen Shen, Ren-Cang Li

Multi-view datasets are increasingly collected in many real-world applications, and we have seen better learning performance by existing multi-view learning methods than by conventional single-view learning methods applied to each view individually. But, most of these multi-view learning methods are built on the assumption that at each instance no view is mi

Beste Hamiye Beyaztas, Soutir Bandyopadhyay

The panel data regression models have gained increasing attention in different areas of research including but not limited to econometrics, environmental sciences, epidemiology, behavioral and social sciences. However, the presence of outlying observations in panel data may often lead to biased and inefficient estimates of the model parameters resulting in u

Matteo Ravasi, Ivan Vasconcelos

Numerical integral operators of convolution type form the basis of most wave-equation-based methods for processing and imaging of seismic data. As several of these methods require the solution of an inverse problem, multiple forward and adjoint passes of the modelling operator must be performed to converge to a satisfactory solution. This work highlights the

Haoteng Yin, Yanbang Wang, Pan Li

Graph neural networks (GNNs) are widely used in the applications based on graph structured data, such as node classification and link prediction. However, GNNs are often used as a black-box tool and rarely get in-depth investigated regarding whether they fit certain applications that may have various properties. A recently proposed technique distance encodin

Antoine Dailly, Adriana Hansberg, Laura Eslava, Denae Ventura

Given a graph $G$, a 2-coloring of the edges of $K_n$ is said to contain a balanced copy of $G$ if we can find a copy of $G$ such that half of its edges is in each color class. If there exists an integer $k$ such that, for $n$ sufficiently large, every 2-coloring of $K_n$ with more than $k$ edges in each color contains a balanced copy of $G$, then we say tha

Wayes Tushar, Chau Yuen, Tapan Saha, Thomas Morstyn

After a century of relative stability of the electricity industry, extensive deployment of distributed energy resources and recent advances in computation and communication technologies have changed the nature of how we consume, trade, and apply energy. The power system is facing a transition from its traditional hierarchical structure to a more deregulated

El Mehdi Saad, Gilles Blanchard, Sylvain Arlot

Greedy algorithms for feature selection are widely used for recovering sparse high-dimensional vectors in linear models. In classical procedures, the main emphasis was put on the sample complexity, with little or no consideration of the computation resources required. We present a novel online algorithm: Online Orthogonal Matching Pursuit (OOMP) for online s

Dimas J. Gonçalves, Mateus E. Salomão

Let $K$ be a field (finite or infinite) of char$(K)\neq 2$ and let $UT_n=UT_n(K)$ be the $n\times n$ upper triangular matrix algebra over $K$. If $\cdot $ is the usual product on $UT_n$ then with the new product $a\circ b=(1/2)(a\cdot b +b\cdot a)$ we have that $UT_n$ is a Jordan algebra, denoted by $UJ_n=UJ_n(K)$. In this paper, we describe the set of all $

Haemanth Santhi Ponnusamy, Detmar Meurers

How can a learner systematically prepare for reading a book they are interested in? In this paper,we explore how computational linguistic methods such as distributional semantics, morphological clustering, and exercise generation can be combined with graph-based learner models to answer this question both conceptually and in practice. Based on the highly str

D. D. Solnyshkov, G. Malpuech

Analogue physics has successfully tackled the problems of chromodynamics, event horizons, Big Bang and Universe expansion, and many others. Here, we suggest a photonic model system for a "time machine" based on the paraxial beam approximation. We demonstrate how the closed time-like curves and the well-known grandfather paradox can be studied experimentally

George A. Gontcharov, Aleksandr V. Mosenkov

We consider a complete sample of 101810 giants with Gaia DR2 parallaxes $\varpi$ within the red clump domain of the Hertzsprung-Russell diagram in the space cylinder with a radius of 700 pc around the Sun and a height of $|Z|=1800$ pc. We use the Gaia DR2 $G_\mathrm{BP}$, $G_\mathrm{RP}$ and WISE $W3$ photometry. We describe the spatial variations of the mod

Shadrack Awah Buo

This paper introduces Business Email Compromise (BEC) and why it is becoming a major issue to businesses worldwide. It also presents a case study of a BEC incident against Unatrac Holding Ltd and analyses the techniques used by the cybercriminals to defraud the company. A critical analysis of the psychological and sociotechnical impacts of BEC to both the co

Philip P. J. Schrinner, Jan Olthaus, Doris E. Reiter, Carsten Schuck

The nitrogen vacancy center in diamond in its negative charge state is a promising candidate for quantum optic experiments that require single photon emitters. Important benefits of the NV center are its high brightness and photo-stability, even at room temperature. Engineering the emission properties of NV centers with optical resonators is a widely followe

Vsevolod Nedora, Federico Schianchi, Sebastiano Bernuzzi, David Radice

We present fitting formulae for the dynamical ejecta properties and remnant disk masses from the largest to date sample of numerical relativity simulations. The considered data include some of the latest simulations with microphysical nuclear equations of state (EOS) and neutrino transport as well as other results with polytropic EOS available in the literat

Nicola Parolini, Giovanni Ardenghi, Luca Dede', Alfio Quarteroni

An analysis of the COVID-19 epidemic is proposed on the basis of the epiMOX dashboard (publicly accessible at https://www.epimox.polimi.it) that deals with data of the epidemic trends and outbreaks in Italy from late February 2020. Our analysis provides an immediate appreciation of the past epidemic development, together with its current trends by fostering

Mohammadreza Salehi, Niousha Sadjadi, Soroosh Baselizadeh, Mohammad Hossein Rohban

Unsupervised representation learning has proved to be a critical component of anomaly detection/localization in images. The challenges to learn such a representation are two-fold. Firstly, the sample size is not often large enough to learn a rich generalizable representation through conventional techniques. Secondly, while only normal samples are available a

Markus Thuresson

We exhibit an isomorphism of associative algebras between the $\operatorname{Ext}$-algebra $\operatorname{Ext}_\Lambda^\ast(\Delta,\Delta)$ of standard modules over the dual extension algebra $\Lambda$ of two directed algebras $B$ and $A$ and the dual extension algebra of the $\operatorname{Ext}$-algebra $\operatorname{Ext}_B^\ast(\mathbb{L},\mathbb{L})$ wit

Luke Chamandy, Eric G. Blackman, Jason Nordhaus, Emily Wilson

Many stars harbour multi-planet systems. As these stars expand late in their evolutions, the innermost planet may be engulfed, leading to a common envelope (CE) event. Even if this is insufficient to eject the envelope, it may expand the star further, causing additional CE events, with the last one unbinding what remains of the envelope. This multi-planet CE

I. Turk Cakir, O. Cakir, H. Denizli, A. Senol

After the recent discovery of a neutral Higgs boson with a mass about 125 GeV, we assess the extend of discovery potential of future circular hadron collider (FCC-hh) for a charged Higgs boson in the bottom and top quark decay channel. The charged Higgs boson can be produced through the pp->h^{-}t+X process with a subsequent decay h^{-}->b bar{t} channel. Th

Huan Nguyen, Mina Kamel, Kostas Alexis, Roland Siegwart

This paper presents a review of the design and application of model predictive control strategies for Micro Aerial Vehicles and specifically multirotor configurations such as quadrotors. The diverse set of works in the domain is organized based on the control law being optimized over linear or nonlinear dynamics, the integration of state and input constraint

Connor Awe, Phillip Barbeau, Alireza Haghighat, Sam Hedges

The non-linear energy response of the plastic scintillator EJ-260 is measured with the MicroCHANDLER detector, using neutron beams of energy 5 to 27 MeV at the Triangle Universities Nuclear Laboratory. The first and second order Birks' constants are extracted from the data, and found to be $k_B = (8.70 \pm 0.93)\times 10^{-3}\ {\rm g/cm^2/MeV}$ and $k_C = (1

Luke Hicks, Ariel Ruiz-Garcia, Vasile Palade, Ibrahim Almakky

Providing care for ageing populations is an onerous task, and as life expectancy estimates continue to rise, the number of people that require senior care is growing rapidly. This paper proposes a methodology based on Transformer Neural Networks to classify the activities of a resident within an ambient sensor based environment. We also propose a methodology

Elissaios Stavrou, Michael Bagge-Hansen, Joshua A. Hammons, Michael H. Nielsen

We explore the response of the insensitive high explosive (IHE) 1,3,5-Triamino-2,4,6- trinitrobenzene (TATB) under detonation-induced shock conditions using in-situ synchrotron X-ray diffraction in the 100 ns time scale using either a conventional or a colliding detonation drive. In all of the detonation experiments on various sizes and morphologies of TATB,

Daniele Bartoli, Antonio Cossidente, Giuseppe Marino, Francesco Pavese

Let PG$(r, q)$ be the $r$-dimensional projective space over the finite field ${\rm GF}(q)$. A set $\cal X$ of points of PG$(r, q)$ is a cutting blocking set if for each hyperplane $\Pi$ of PG$(r, q)$ the set $\Pi \cap \cal X$ spans $\Pi$. Cutting blocking sets give rise to saturating sets and minimal linear codes and those having size as small as possible ar

Wallas S. Nascimento, Marcos M. de Almeida, Frederico V. Prudente

The present work studies aspects of the electronic correlation in confined H$^{-}$, He and Li$^+$ atoms in their ground states using the informational entropies. In this way, different variational wavefunctions are employed in order of better take account of Coulomb correlation. The obtained values for the $S_r$, $S_p$ and $S_t$ entropies are sensitive in re

Christopher P. Kempes, Geoffrey B. West, John W. Pepper

Understanding the cross-species behavior of cancer is important for uncovering fundamental mechanisms of carcinogenesis, and for translating results of model systems between species. One of the most famous interspecific considerations of cancer is Peto's paradox, which asserts that organisms with vastly different body mass are expected to have a vastly diffe

Deepti Gupta, Paras Bhatt, Smriti Bhatt

The application of Internet of Things (IoT) and Machine Learning (ML) to the agricultural industry has enabled the development and creation of smart farms and precision agriculture. The growth in the number of smart farms and potential cooperation between these farms has given rise to the Cooperative Smart Farming (CSF) where different connected farms collab

Songze Li, David Tse

Most state machine replication protocols are either based on the 40-years-old Byzantine Fault Tolerance (BFT) theory or the more recent Nakamoto's longest chain design. Longest chain protocols, designed originally in the Proof-of-Work (PoW) setting, are available under dynamic participation, but has probabilistic confirmation with long latency dependent on t

Ryeongkyung Yoon, Harish S. Bhat, Braxton Osting

Certain neural network architectures, in the infinite-layer limit, lead to systems of nonlinear differential equations. Motivated by this idea, we develop a framework for analyzing time signals based on non-autonomous dynamical equations. We view the time signal as a forcing function for a dynamical system that governs a time-evolving hidden variable. As in

Mohammad Reza Mohebbian, Seyed Shahim Vedaei, Khan A. Wahid, Anh Dinh

Non-invasive fetal electrocardiogram (FECG) is used to monitor the electrical pulse of the fetal heart. Decomposing the FECG signal from maternal ECG (MECG) is a blind source separation problem, which is hard due to the low amplitude of FECG, the overlap of R waves, and the potential exposure to noise from different sources. Traditional decomposition techniq

Gevorg Yeghikyan

Against the backdrop of rising anxiety and discussions on the impact of AI on society, I explore in this article the structural possibilities of AI and automation triggering a new social conflict between the current capitalist elites and the emerging "creative class" (R&D scientists, engineers, business developers, etc.), and how this conflict can produce so

Matej Grcić, Petra Bevandić, Siniša Šegvić

Today's deep models are often unable to detect inputs which do not belong to the training distribution. This gives rise to confident incorrect predictions which could lead to devastating consequences in many important application fields such as healthcare and autonomous driving. Interestingly, both discriminative and generative models appear to be equally af

S. H. Hendi, N. Riazi, S. N. Sajadi

In this work, we investigate a new warped five-dimensional, Z2-symmetric thick brane solution in the presence of a real scalar field. We examine the different geometric aspects of the model. We discuss the stability of the solution under gravitational fluctuations and study both the graviton ground state and the continuum of Kaluza-Klein modes to find a corr

Bin Chen, Peng-Xiang Hao, Reiko Liu, Zhe-Fei Yu

In this work, we develop conformal bootstrap for Galilean conformal field theory (GCFT). In a GCFT, the Hilbert space could be decomposed into quasiprimary states and its global descendants. Different from the usual conformal field theory, the quasi-primary states in a GCFT constitute multiplets, which are block-diagonized under the Galilean boost operator.

Carlos Esteve-Yagüe, Borjan Geshkovski, Dario Pighin, Enrique Zuazua

We present a new proof of the turnpike property for nonlinear optimal control problems, when the running target is a steady control-state pair of the underlying system. Our strategy combines the construction of quasi-turnpike controls via controllability, and a bootstrap argument, and does not rely on analyzing the optimality system or linearization techniqu

Yadollah Yaghoobzadeh, Alexandre Rochette, Timothy J. Hazen

Duplicate question detection (DQD) is important to increase efficiency of community and automatic question answering systems. Unfortunately, gathering supervised data in a domain is time-consuming and expensive, and our ability to leverage annotations across domains is minimal. In this work, we leverage neural representations and study nearest neighbors for

Jesse Chan, Yimin Lin, Tim Warburton

Entropy stable schemes ensure that physically meaningful numerical solutions also satisfy a semi-discrete entropy inequality under appropriate boundary conditions. In this work, we describe a discretization of viscous terms in the compressible Navier-Stokes equations which enables a simple and explicit imposition of entropy stable no-slip (adiabatic and isot

Hamza Saad, Nagendra Nagarur

Background and Objective: Breast cancer, which accounts for 23% of all cancers, is threatening the communities of developing countries because of poor awareness and treatment. Early diagnosis helps a lot in the treatment of the disease. The present study conducted in order to improve the prediction process and extract the main causes impacted the breast canc

Yuhao Yi, Liren Shan, Philip E. Paré, Karl H. Johansson

This paper studies algorithmic strategies to effectively reduce the number of infections in susceptible-infected-recovered (SIR) epidemic models. We consider a Markov chain SIR model and its two instantiations in the deterministic SIR (D-SIR) model and the independent cascade SIR (IC-SIR) model. We investigate the problem of minimizing the number of infectio

Hana Saoud, Duco De Beus, Severine Eybrard, Alain Louilot

For almost two decades schizophrenia has been considered to be a functional disconnection disorder. This functional disconnectivity between several brain regions could have a neurodevelopmental origin. Various approaches suggest the ventral subiculum (SUB) is a particular target region for neurodevelopemental disturbances in schizophrenia. It is also commonl

Sergio Cacciatori, Alessio Marrani, Federico Re

Many recent researches have investigated the deviations from the Friedmannian cosmological model, as well as their consequences on unexplained cosmological phenomena, such as dark matter and the acceleration of the Universe. On the one hand, a first order perturbative study of matter inhomogeneity returned a partial explanation of dark matter and dark energy

Renos Karamanis, He-in Cheong, Simon Hu, Marc Stettler

Ride-sourcing platforms enable an on-demand shared transport service by solving decision problems often related to customer matching, pricing and vehicle routing. These problems have been frequently represented using aggregated mathematical models and solved via algorithmic approaches designed by researchers. The increasing complexity of ride-sourcing enviro

Federico Martellosio

We study identifiability of the parameters in autoregressions defined on a network. Most identification conditions that are available for these models either rely on the network being observed repeatedly, are only sufficient, or require strong distributional assumptions. This paper derives conditions that apply even when the individuals composing the network

O. S. Kostromina

The problem of the effect of two-frequency quasi-periodic perturbations on systems close to arbitrary nonlinear two-dimensional Hamiltonian ones is studied in the case when the corresponding perturbed autonomous systems have a double limit cycle. Its solution is important both for the theory of synchronization of nonlinear oscillations and for the theory of

Wassapon Watanakeesuntorn, Keichi Takahashi, Kohei Ichikawa, Joseph Park

Empirical Dynamic Modeling (EDM) is a nonlinear time series causal inference framework. The latest implementation of EDM, cppEDM, has only been used for small datasets due to computational cost. With the growth of data collection capabilities, there is a great need to identify causal relationships in large datasets. We present mpEDM, a parallel distributed i

Junli Cao, B. S., Junyan Wu, M. S.

Background: Margin assessment of basal cell carcinoma using the frozen section is a common task of pathology intraoperative consultation. Although frequently straight-forward, the determination of the presence or absence of basal cell carcinoma on the tissue sections can sometimes be challenging. We explore if a deep learning model trained on mobile phone-ac

H. F. Arellano, G. Blanchon

We investigate the role of high momentum components of optical model potentials for nucleon-nucleus scattering and its incidence on their nonlocal structure in coordinate space. The study covers closed-shell nuclei with mass number in the range $4\leq A\leq 208$, for nucleon energies from tens of MeV up to 1 GeV. To this purpose microscopic optical potential

Martin Rodriguez-Vega, Michael Vogl, Gregory A. Fiete

We review recent work on low-frequency Floquet engineering and its application to quantum materials driven by light, emphasizing van der Waals systems hosting Moir\'e superlattices. These non-equilibrium systems combine the twist-angle sensitivity of the band structures with the flexibility of light drives. The frequency, amplitude, and polarization of light

Filippo Costa, Michele Borgese

A simple but efficient approach for the synthesis of transmission-type wideband polarization converters is presented. The proposed configuration comprises multilayer metasurfaces including resonant particles which are progressively rotated layer by layer. The progressive rotation of the particles allows for a polarization conversion over a large frequency ba

Yiren Zhao, Ilia Shumailov, Robert Mullins, Ross Anderson

The wide adaption of 3D point-cloud data in safety-critical applications such as autonomous driving makes adversarial samples a real threat. Existing adversarial attacks on point clouds achieve high success rates but modify a large number of points, which is usually difficult to do in real-life scenarios. In this paper, we explore a family of attacks that on

Anshul Gupta, Joydeep Medhi, Aratrik Chattopadhyay, Vikram Gupta

Inferring the 6DoF pose of an object from a single RGB image is an important but challenging task, especially under heavy occlusion. While recent approaches improve upon the two stage approaches by training an end-to-end pipeline, they do not leverage local and global constraints. In this paper, we propose pairwise feature extraction to integrate local const

Ariel Ruiz-Garcia, Ibrahim Almakky, Vasile Palade, Luke Hicks

Generative Adversarial Networks (GANs) have become predominant in image generation tasks. Their success is attributed to the training regime which employs two models: a generator G and discriminator D that compete in a minimax zero sum game. Nonetheless, GANs are difficult to train due to their sensitivity to hyperparameter and parameter initialisation, whic

Mikhail Khovanov, Louis-Hadrien Robert

In the unoriented SL(3) foam theory, singular vertices are generic singularities of two-dimensional complexes. Singular vertices have neighbourhoods homeomorphic to cones over the one-skeleton of the tetrahedron, viewed as a trivalent graph on the two-sphere. In this paper we consider foams with singular vertices with neighbourhoods homeomorphic to cones ove

N. Sánchez-Kuntz, S. Floerchinger

The entanglement between spatial regions in an interacting Bose-Einstein condensate is investigated using a quantum field theoretic formalism. Regions that are small compared to the healing length are governed by a non-relativistic quantum field theory in the vacuum limit, and we show that the latter has vanishing entanglement. In the opposite limit of a reg

Emad Alenany, Abdessamad Ait El Cadi

Recently, the combination of machine learning (ML) and simulation is gaining a lot of attention. This paper presents a novel application of ML within the simulation to improve patient flow within an emergency department (ED). An ML model used within a real ED simulation model to quantify the effect of detouring a patient out of the ED on the length of stay (

Philippe Laurençot, Katerina Nik, Christoph Walker

Energy minimizers to a MEMS model with an insulating layer are shown to converge in its reinforced limit to the minimizer of the limiting model as the thickness of the layer tends to zero. The proof relies on the identification of the $\Gamma$-limit of the energy in this limit.

Simon Gabay, Thibault Clérice, Jean-Baptiste Camps, Jean-Baptiste Tanguy

With the development of big corpora of various periods, it becomes crucial to standardise linguistic annotation (e.g. lemmas, POS tags, morphological annotation) to increase the interoperability of the data produced, despite diachronic variations. In the present paper, we describe both methodologically (by proposing annotation principles) and technically (by

Richie Yeung

Given the rising popularity of quantum machine learning (QML), it is important to develop techniques that effectively simplify commonly adopted families of parameterised quantum circuits (commonly known as ans\"{a}tze). This thesis pioneers the use of diagrammatic techniques to reason with QML ans\"{a}tze. We take commonly used QML ans\"{a}tze and convert th

Tiberiu Harko, Man Kwong Mak, Matthew J. Lake

The Schr\"{o}dinger-Newton model is a nonlinear system obtained by coupling the linear Schr\"{o}dinger equation of canonical quantum mechanics with the Poisson equation of Newtonian mechanics. In this paper we investigate the effects of dark energy on the time-dependent Schr\"{o}dinger-Newton equations by including a new source term with energy density $\rho

Andreea-Maria Oncescu, João F. Henriques, Yang Liu, Andrew Zisserman

We introduce QuerYD, a new large-scale dataset for retrieval and event localisation in video. A unique feature of our dataset is the availability of two audio tracks for each video: the original audio, and a high-quality spoken description of the visual content. The dataset is based on YouDescribe, a volunteer project that assists visually-impaired people by

Stefan Groha, Caroline Weis, Alexander Gusev, Bastian Rieck

Identifying subgroups and properties of cancer biopsy samples is a crucial step towards obtaining precise diagnoses and being able to perform personalized treatment of cancer patients. Recent data collections provide a comprehensive characterization of cancer cell data, including genetic data on copy number alterations (CNAs). We explore the potential to cap

Alessandra Di Gaspare, Eva A. A. Pogna, Luca Salemi, Osman Balci

We present an electrically switchable graphene terahertz (THz) modulator with a tunable-by-design optical bandwidth and we exploit it to compensate the cavity dispersion of a quantum cascade laser (QCL). Electrostatic gating is achieved by a metal-grating used as a gate electrode, with an HfO2/AlOx gate dielectric on top. This is patterned on a polyimide lay

Carl Lian

Let X be a smooth projective surface over C and let L be an ample line bundle on X. In this note, we show that, for all sufficiently large d, any number of general double points on X imposes the expected number of conditions on the linear system |L^d|. Equivalently, the space of d-plane sections of X singular at any number of general points has the expected

Karthikeya Ramesh Kaushik, Andrea E. Martin

Human beings possess the most sophisticated computational machinery in the known universe. We can understand language of rich descriptive power, and communicate in the same environment with astonishing clarity. Two of the many contributors to the interest in natural language - the properties of Compositionality and Structure Dependence, are well documented,

Jin-Ke Bao, Christos D. Malliakas, Chi Zhang, Songting Cai

Layered heterostructure materials with two different functional building blocks can teach us about emergent physical properties and phenomena arising from interactions between the layers. We report the intergrowth compounds KLa$M$$_{1-x}$Te$_{4}$ ($M$ = Mn, Zn; $x\approx$ 0.35) featuring two chemically distinct alternating layers [LaTe$_3$] and [K$M$$_{1-x}$

Pratik Mazumder, Pravendra Singh, Vinay P. Namboodiri

Learning from a few examples is an important practical aspect of training classifiers. Various works have examined this aspect quite well. However, all existing approaches assume that the few examples provided are always correctly labeled. This is a strong assumption, especially if one considers the current techniques for labeling using crowd-based labeling

Nicolas Nadisic, Jeremy E Cohen, Arnaud Vandaele, Nicolas Gillis

Nonnegative least squares problems with multiple right-hand sides (MNNLS) arise in models that rely on additive linear combinations. In particular, they are at the core of most nonnegative matrix factorization algorithms and have many applications. The nonnegativity constraint is known to naturally favor sparsity, that is, solutions with few non-zero entries

Chunmei Wang

A modified primal-dual weak Galerkin (M-PDWG) finite element method is designed for the second order elliptic equation in non-divergence form. Compared with the existing PDWG methods proposed in \cite{wwnondiv}, the system of equations resulting from the M-PDWG scheme could be equivalently simplified into one equation involving only the primal variable by el

David Conlon

We give a simple geometric interpretation of an algebraic construction of Wenger that yields $n$-vertex graphs with no cycle of length $4$, $6$ or $10$ and close to the maximum number of edges.

Eli Sennesh

Humans surpass the cognitive abilities of most other animals in our ability to "chunk" concepts into words, and then combine the words to combine the concepts. In this process, we make "infinite use of finite means", enabling us to learn new concepts quickly and nest concepts within each-other. While program induction and synthesis remain at the heart of fou

Marcello Serqueira, Pedro González, Eduardo Bezerra

In recent years, large amounts of data have been generated, and computer power has kept growing. This scenario has led to a resurgence in the interest in artificial neural networks. One of the main challenges in training effective neural network models is finding the right combination of hyperparameters to be used. Indeed, the choice of an adequate approach

Joel Kostensalo, Jouni Suhonen, Juliane Volkmer, Stefan Zatschler

In this article we present an updated spectrum-shape analysis of the $^{113}$Cd fourfold forbidden non-unique $\beta$-decay transition in order to address the quenching of the weak axial-vector coupling $g_{\rm A}$ in low-momentum exchange nuclear processes. The experimental data were collected in a dedicated low-threshold run with the COBRA demonstrator at

Thuy Bui, Gaywalee Yamskulna

We first investigate the algebraic structure of vertex algebroids $B$ when $B$ are simple Leibniz algebras. Next, we use these vertex algebroids $B$ to construct indecomposable non-simple $C_2$-cofinite $\mathbb{N}$-graded vertex algebras $\overline{V_B}$. In addition, we classify $\mathbb{N}$-graded irreducible $\overline{V_B}$-modules and examine conformal

Oleg Lobachev, Takuya Funatomi, Alexander Pfaffenroth, Reinhold Förster

Registration of histological serial sections is a challenging task. Serial sections exhibit distortions and damage from sectioning. Missing information on how the tissue looked before cutting makes a realistic validation of 2D registrations extremely difficult. This work proposes methods for ground-truth-based evaluation of registrations. Firstly, we present

Sabine Tornow, Wolfgang Gehrke, Udo Helmbrecht

Many-body physics is one very well suited field for testing quantum algorithms and for finding working heuristics on present quantum computers. We have investigated the non-equilibrium dynamics of one- and two-electron systems, which are coupled to an environment that introduces decoherence and dissipation. In our approach, the electronic system is represent

Shivi Gupta, Shashi Kant Gupta

It has been found that representations learned by Deep Neural Networks (DNNs) correlate very well to neural responses measured in primates' brains and psychological representations exhibited by human similarity judgment. On another hand, past studies have shown that particular colors can be associated with specific emotion arousal in humans. Do deep neural n

Gili Golan Polak

We prove that under two natural probabilistic models (studied by Cleary, Elder, Rechnitzer and Taback), the probability that a random pair of elements of Thompson's group $F$ generate the entire group is positive. We also prove that for any $k$-generated subgroup $H$ of $F$ which contains a "natural" copy of $F$, the probability of a random $(k+2)$-generated

Zhao-Zhou Li, Lu Li, Zhengyi Shao

The Gaussian process (GP) regression can be severely biased when the data are contaminated by outliers. This paper presents a new robust GP regression algorithm that iteratively trims the most extreme data points. While the new algorithm retains the attractive properties of the standard GP as a nonparametric and flexible regression method, it can greatly imp

Bernhard Heim, Markus Neuhauser

Bessenrodt and Ono's work on additive and multiplicative properties of the partition function and DeSalvo and Pak's paper on the log-concavity of the partition function have generated many beautiful theorems and conjectures. In January 2020, the first author gave a lecture at the MPIM in Bonn on a conjecture of Chern--Fu--Tang, and presented an extension (jo

Ricardo Pérez-Marco

Telegraphic notes on the historical bibliography of the Gamma function and Eulerian integrals. Correction to some classical references. Some topics of the interest of the author. We provide some extensive (but not exhaustive) bibliography. Feedback is welcome, notes will be updated and some references need completion.

Hicham Messaoudi, Ahror Belaid, Mohamed Lamine Allaoui, Ahcene Zetout

3D medical image processing with deep learning greatly suffers from a lack of data. Thus, studies carried out in this field are limited compared to works related to 2D natural image analysis, where very large datasets exist. As a result, powerful and efficient 2D convolutional neural networks have been developed and trained. In this paper, we investigate a w

Zhihua Jin, Yong Wang, Qianwen Wang, Yao Ming

Graph Neural Networks (GNNs) aim to extend deep learning techniques to graph data and have achieved significant progress in graph analysis tasks (e.g., node classification) in recent years. However, similar to other deep neural networks like Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), GNNs behave like a black box with their det

Jeffrey W. Doser, Andrew O. Finley, Aaron S. Weed, Elise F. Zipkin

Monitoring wildlife abundance across space and time is an essential task to study their population dynamics and inform effective management. Acoustic recording units are a promising technology for efficiently monitoring bird populations and communities. We present an integrated modeling framework that combines high-quality but temporally sparse bird point co

Andrea Marinatto

Let $\mathbb{C}$ be the field of complex numbers. Let $k$ be natural number with $k \geq 2$ and let $p$ be a rational prime. In this paper we count the number of conjugacy classes of admissible cyclic subgroups of $\mathrm{PGL}_{k+1}(\mathbb{C})$ of order $p$, where with admissible we intend those finite subgroups that can be contained in the automorphism gr

F. Crasto de Lima, A. Fazzio

Material's geometrical structure is a fundamental part of their properties. The honeycomb geometry of graphene is responsible for the arising of its Dirac cone, while the kagome and Lieb lattice hosts flat bands and pseudospin-1 Dirac dispersion. These features seem to be particular for few 2D systems rather than a common occurrence. Given this correlation b

Luca Ciambelli, Cristóbal Corral, José Figueroa, Gastón Giribet

The method of topological renormalization in anti-de Sitter (AdS) gravity consists in adding to the action a topological term which renders it finite, defining at the same time a well-posed variational problem. Here, we use this prescription to work out the thermodynamics of asymptotically locally anti-de Sitter (AlAdS) spacetimes, focusing on the physical p

Dmitry Budker, Mikhail G. Kozlov

Spin projection noise sets a limit for the sensitivity of spin-based magnetometers and experiments searching for parity- and time-reversal-invariance-violating dipole moments. The limit is described by a simple equation that appears to have universal applicability.

Rune Haugseng, Fabian Hebestreit, Sil Linskens, Joost Nuiten

We prove a universal property for $\infty$-categories of spans in the generality of Barwick's adequate triples, explicitly describe the cocartesian fibration corresponding to the span functor, and show that the latter restricts to a self-equivalence on the class of orthogonal adequate triples, which we introduce for this purpose. As applications of the machi