July 2022 arXiv papers — page 19

Stephen R. McMillan, Guido Burkard

A critical element towards the realization of scalable quantum processors is non-local coupling between nodes. Scaling connectivity beyond nearest-neighbor interactions requires the implementation of a mediating interaction often termed a 'quantum bus'. Cavity photons have long been used as a bus by the superconducting qubit community, but it has only recent

E. Bakos, N. de Groot, N. Vranjes

In this paper we present two machine learning algorithms to identify $D$ mesons produced in a color singlet state from radiative $W$ boson decays at the LHC. The combined network algorithm is able to identify $D$ mesons via its hadronic decays with an efficiency of 47% while suppressing a background of quark and gluon jets by a factor of 100. Using the devel

Lucie Charlotte Magister, Pietro Barbiero, Dmitry Kazhdan, Federico Siciliano

The opaque reasoning of Graph Neural Networks induces a lack of human trust. Existing graph network explainers attempt to address this issue by providing post-hoc explanations, however, they fail to make the model itself more interpretable. To fill this gap, we introduce the Concept Encoder Module, the first differentiable concept-discovery approach for grap

Simanraj Sadana, Lorenzo Maccone, Urbasi Sinha

We use quantum computers to test the foundations of quantum mechanics through quantum algorithms that implement some of the experimental tests as the basis of the theory's postulates. These algorithms can be used as a test of the physical theory under the premise of a perfect hardware or as a test of the hardware under the premise that quantum theory is corr

Cédric Mezrag

These lecture notes on Generalised Parton Distributions aim at providing a general picture of the field on the theoretical and phenomenological sides to master and Ph.D. students. They go along with the lecture given at the Baryon International School of Physics in 2021.

Sidney Pontes-Filho, Kristoffer Olsen, Anis Yazidi, Michael A. Riegler

In this work, we argue that the search for Artificial General Intelligence (AGI) should start from a much lower level than human-level intelligence. The circumstances of intelligent behavior in nature resulted from an organism interacting with its surrounding environment, which could change over time and exert pressure on the organism to allow for learning o

Zhenji Wu, Lu Guo, Zhong Liu, Guangxiong Peng

The production of new proton-rich nuclei in the vicinity of 100Sn is investigated via multinucleon transfer reactions within the framework of microscopic time-dependent Hartree-Fock (TDHF) and statistical model GEMINI++. The TDHF+GEMINI method has demonstrated the reliable description in the multinucleon transfer dynamics and the agreement between theoretica

Cédric Travelletti, David Ginsbourger

Gaussian processes appear as building blocks in various stochastic models and have been found instrumental to account for imprecisely known, latent functions. It is often the case that such functions may be directly or indirectly evaluated, be it in static or in sequential settings. Here we focus on situations where, rather than pointwise evaluations, evalua

Luis J. Mendoza Herrera, Myrian C. Tebaldi, Lucía B. Scaffardi, Daniel C. Schinca

There is an ever increasing interest in the development of plasmonic 2D nanomaterials, with widespread applications in optoelectronics, high resolution microscopy, imaging and sensing, among others. With the current ability of ultrathin noble metal film deposition down to a few monolayers in thickness, there is a need for an analytical expression of the thic

Valentin Gebhart, Augusto Smerzi

Genuine multipartite nonlocality (GMN), the strongest form of multipartite nonlocality that describes fully collective nonlocal correlations among all experimental parties, can be observed when different distant parties each locally measure a particle from a shared entangled many-particle state. For the demonstration of GMN, the experimentally observed stati

Mingqing Liu, Shuaifan Xia, Mingliang Xiong, Mengyuan Xu

Simultaneous lightwave information and power transfer (SLIPT) is a potential way to meet the demands of sustainable power supply and high-rate data transfer in next-generation networks. Although resonant beam-based SLIPT (RB-SLIPT) can realize high-power energy transfer, high-rate data transfer, human safety, and self-alignment simultaneously, mobile transmi

Mathias Fleury, Armin Biere

We give a first account of our new parallel SAT solver Gimsatul. Its key feature is to share clauses physically in memory instead of copying them, which is the method of other state-of-the-art multi-threaded SAT solvers to exchange clauses logically. Our approach keeps information about which literals are watched in a clause local to a solving thread but sha

Benjamin Bally, Giuliano Giacalone, Michael Bender

Recently, values for the Kumar quadrupole deformation parameters of the nucleus $^{130}$Xe have been computed from the results of a Coulomb excitation experiment, indicating that this xenon isotope has a prominent triaxial ground state. Within a different context, it was recently argued that the analysis of particle correlations in the final states of ultra-

Dmitry Tsirkov, Bota Baimurzinova, Vladimir I. Komarov, Anatoly V. Kulikov

We report on measurements of the differential cross section $d\sigma/d\Omega$ in the energy region of $\sqrt{s}$ = 2.5-2.9 GeV of the reaction $pp \to \{pp\}_s \pi^0$ where $\{pp\}_s$ is a $^1\!S_0$ proton pair. The experiment has been performed with the ANKE spectrometer at COSY-J\"ulich. The data reveal a peak in the energy dependence of the forward $\{pp\

Jacob R. Goodman, Leonardo J. Colombo

This paper studies the reduction by symmetry of a variational obstacle avoidance problem. We derive the reduced necessary conditions in the case of Lie groups endowed with a left-invariant metric, and for its corresponding Riemannian homogeneous spaces by considering an alternative variational problem written in terms of a connection on the horizontal bundle

Martin Keller-Ressel

We derive analytic expressions for the variance-optimal hedging strategy and its mean-square hedging error in the lognormal SABR and in the rough Bergomi model. In the SABR model, we show that the variance-optimal hedging strategy coincides with the Delta adjustment of Bartlett [Wilmott magazine 4/6 (2006)]. We show both mathematically and in simulation that

Hamid Jalalzai, Elie Kadoche, Rémi Leluc, Vincent Plassier

The raise of machine learning and deep learning led to significant improvement in several domains. This change is supported by both the dramatic rise in computation power and the collection of large datasets. Such massive datasets often include personal data which can represent a threat to privacy. Membership inference attacks are a novel direction of resear

Boris Hanin, Steve Zelditch

We prove that smooth Wigner-Weyl spectral sums at an energy level $E$ exhibit Airy scaling asymptotics across the classical energy surface $\Sigma_E$. This was proved earlier by the authors for the isotropic harmonic oscillator and the proof is extended in this article to all quantum Hamiltonians $-\hbar^2 \Delta + V$ where $V$ is a confining potential with

Giovanni Fantuzzi, Ian Tobasco

We analyze two recently proposed methods to establish a priori lower bounds on the minimum of general integral variational problems. The methods, which involve either `occupation measures' or a `pointwise dual relaxation' procedure, are shown to produce the same lower bound under a coercivity hypothesis ensuring their strong duality. We then show by a minima

Qi Yang, Saleh Kalantari

This study introduces two methods for continuously measuring uncertainty during human navigation in complex buildings: one using a joystick (RCUA), and the other with annotations on videos of recent navigation activity (CUA). To evaluate the usability, reliability, and validity of both approaches, we conducted a study with 54 participants. We assessed the me

Ivan Horváth, Peter Markoš

We show that critical Anderson electron in 3 dimensions is present in its spatial effective support, which was recently determined to be a region of fractal dimension $\approx \! 8/3$, with probability 1 in infinite volume. Hence, its physics is fully confined to space of this lower dimension. Stated differently, effective description of space occupied by cr

A. A. Zaitsev, P. I. Zarubin, N. G. Peresadko

In this paper, the correlation between the formation of the unstable $^{8}$Be nucleus and accompanying $\alpha$ particles in the fragmentation of relativistic $^{16}$O, $^{22}$Ne, $^{28}$Si, and $^{197}$Au nuclei in a nuclear track emulsion is investigated. The $^{8}$Be decays are identified in a wide energy range by invariant masses calculated from 2$\alpha

Daniele Gaggero, Andrea Ghira, Simone Marzani, Giovanni Ridolfi

Observables involving heavy quarks can be computed in perturbative QCD in two different approximation schemes: either the quark mass dependence is fully retained, or it is retained only where needed to regulate the collinear singularity. The two schemes have different advantages and drawbacks. In particular, it is known that the structure of large logarithms

Komla Elom Adedje, Diakarya Barro

In this paper, we propose a fractional differential equation of order one-half, to model the evolution through time of the dynamics of accumulation and elimination of the contaminant in human organism with a deficient immune system, during consecutive intakes of contaminated food. This process quantifies the exposure to toxins of subjects living with comorbi

Simon D. M. White

I present an analytic model for the early post-collapse evolution of a spherical density peak on the coherence scale of the initial fluctuations in a universe filled with collisionless and pressure-free "dust". On a time-scale which is short compared to the peak's collapse time $t_0$, its inner regions settle into an equilibrium cusp with a power-law density

Kamran Karimi, Mikko J. Alava, Stefanos Papanikolaou

Sheared multi-component bulk metallic glasses are characterized by both chemical and structural disorder that define their properties. We investigate the behavior of the local, microstructural elastic modulus across the plastic yielding transition in six Ni-based multi-component glasses, that are characterized by compositional features commonly associated wi

Qi Chen, Xinrong Ma, Jin Wang

In this paper, by introducing new matrix operations and using a specific inverse relation, we establish the dual forms of the orthogonality relations for some well-known discrete and continuous $q$-orthogonal polynomials from the Askey-scheme such as the little and big $q$-Jacobi, $q$-Racah, (generalized) $q$-Laguerre, as well as the Askey-Wilson polynomials

Felipe Yukihide Yasumura

In this short note, we describe the so-called homogeneous involution on finite-dimensional graded-division algebra over an algebraically closed field. We also compute their graded polynomial identities with involution. As pointed out by L. Fonseca and T. de Mello, a homogeneous involution naturally appears when dealing with graded polynomial identities and a

Paula Bergero, Laura P. Schaposnik, Grace Wang

A dramatic increase in the number of outbreaks of Dengue has recently been reported, and climate change is likely to extend the geographical spread of the disease. In this context, this paper shows how a neural network approach can incorporate Dengue and COVID-19 data as well as external factors (such as social behaviour or climate variables), to develop pre

Adrian Palcu

After proving, in a previous paper, that the electric charge quantization occurs as a natural consequence in renormalizable $SU(3)_c \otimes SU(n)_{L} \otimes U(1)_{Y}$ gauge models, we take here a step further within the same paradigm in order to obtain the precise weak charges quantization. To this end a viable boson mass spectrum yields first, once a prop

Weiqi Li, Bin Chen, Shuai Liu, Shijie Zhao

By mapping iterative optimization algorithms into neural networks (NNs), deep unfolding networks (DUNs) exhibit well-defined and interpretable structures and achieve remarkable success in the field of compressive sensing (CS). However, most existing DUNs solely rely on the image-domain unfolding, which restricts the information transmission capacity and reco

Seungkwang Lee, Jeong-Nyeo Kim

Power analysis poses a significant threat to the security of cryptographic algorithms, as it can be leveraged to recover secret keys. While various software-based countermeasures exist to mitigate this non-invasive attack, they often involve a trade-off between time and space constraints. Techniques such as masking and shuffling, while effective, can noticea

Rauf A. Mukhamedshin

Coplanarity of subcores of $\gamma$-ray--hadron families found in cosmic-ray experiments at $E_0 \gtrsim 10^{16}$ eV requires appearance of a coplanar generation of most energetic particles. Long-range near-side "ridge" effect in $ pp$ collisions at $\sqrt{s} = 7$ TeV was found by the CMS Collaboration in two-particle $\Delta\eta - \Delta\varphi$ correlation

Akane Kawaharada

Salem's singular function is strictly increasing, continuous, and has a derivative equal to zero almost everywhere in $[0,1]$; it is also known as de Rham's singular function or Lebesgue's singular function. The parameter of Salem's singular function $L_{\alpha}$ is $\alpha \in (0, 1)$ and $\alpha \neq 1/2$. Our previous studies have shown that for some case

Theodore Stanoev

A novel approach to velodrome design for UCI-regulated tracks is presented. The mathematical model uses differential geometry to form a three-dimensional ruled surface. The surface accounts for the safety zone, blue band, and track region, the latter of which is comprised of three types of segments: straight lines, the arcs of circles, and connecting transit

Alina Marian

We show that the classic Verlinde numbers on the moduli space of semistable vector bundles on a smooth projective curve can also be regarded as Segre numbers of natural universal complexes over the moduli space.

Rohit Kannan, Güzin Bayraksan, James R. Luedtke

We study optimization for data-driven decision-making when we have observations of the uncertain parameters within the optimization model together with concurrent observations of covariates. Given a new covariate observation, the goal is to choose a decision that minimizes the expected cost conditioned on this observation. We investigate three data-driven fr

Dongzi Zhao, Jing-Zheng Huang, Tailong Xiao, Hongjing Li

The non-reciprocity of Sagnac interferometer provides ultra-high sensitivity for parameter estimation and offers a wide range of applications, especially for optical fiber sensing. In this work, we study a new type of non-reciprocity existed in optical fiber Sagnac interferometer where the polarization dependent loss is taken into consideration. In particula

Maria Lombardi, Elisa Maiettini, Vadim Tikhanoff, Lorenzo Natale

Performing joint interaction requires constant mutual monitoring of own actions and their effects on the other's behaviour. Such an action-effect monitoring is boosted by social cues and might result in an increasing sense of agency. Joint actions and joint attention are strictly correlated and both of them contribute to the formation of a precise temporal c

Laura Meneghetti, Nicola Demo, Gianluigi Rozza

As a major breakthrough in artificial intelligence and deep learning, Convolutional Neural Networks have achieved an impressive success in solving many problems in several fields including computer vision and image processing. Real-time performance, robustness of algorithms and fast training processes remain open problems in these contexts. In addition objec

José Niño-Mora

Poisson's equation plays a fundamental role as a tool for performance evaluation and optimization of Markov chains. For continuous-time birth-death chains with possibly unbounded transition and cost rates as addressed herein, when analytical solutions are unavailable its numerical solution can in theory be obtained by a simple forward recurrence. Yet, this m

Kyveli Doveri, Pierre Ganty, Nicolas Mazzocchi

We propose a novel algorithm to decide the language inclusion between (nondeterministic) B\"uchi automata, a PSPACE-complete problem. Our approach, like others before, leverage a notion of quasiorder to prune the search for a counterexample by discarding candidates which are subsumed by others for the quasiorder. Discarded candidates are guaranteed to not co

Rémi Boutonnet, Cyril Houdayer

We prove a noncommutative Bader-Shalom factor theorem for lattices with dense projections in product groups. As an application of this result and our previous works, we obtain a noncommutative Margulis factor theorem for all irreducible lattices $\Gamma < G$ in higher rank semisimple algebraic groups. Namely, we give a complete description of all intermediat

Andrus Giraldo, Stefan Ruschel

We numerically investigate the branching of temporally localized, two-pulse periodic traveling waves from one-pulse periodic traveling waves with non-oscillating tails in delay differential equations (DDEs) with large delay. Solutions of this type are commonly referred to as temporal dissipative solitons (TDSs) in applications, and we adopt this term here. W

Henry Liu

We provide a general framework for wall-crossing of equivariant K-theoretic enumerative invariants of appropriate moduli stacks $\mathfrak{M}$, by lifting Joyce's homological universal wall-crossing arXiv:2111.04694 to K-theory and to include equivariance. The primary new tool is that the operational K-homology of $\mathfrak{M}$ is an equivariant multiplicat

Renzhi Wu, Shen-En Chen, Jieyu Zhang, Xu Chu

To reduce the human annotation efforts, the programmatic weak supervision (PWS) paradigm abstracts weak supervision sources as labeling functions (LFs) and involves a label model to aggregate the output of multiple LFs to produce training labels. Most existing label models require a parameter learning step for each dataset. In this work, we present a hyper l

Ryoutaro Watanabe

This paper reviews the recent progresses of the flavor and collider searches that can probe New Physics effects responsible for the current discrepancy in the lepton flavor universality ratio of $R_{D^{(*)}}$ between the experimental measurements and SM values.

Stephan Alaniz, Massimiliano Mancini, Anjan Dutta, Diego Marcos

Humans show high-level of abstraction capabilities in games that require quickly communicating object information. They decompose the message content into multiple parts and communicate them in an interpretable protocol. Toward equipping machines with such capabilities, we propose the Primitive-based Sketch Abstraction task where the goal is to represent ske

Ameur Louhichi, Marie-Helene Morel, Laurence Ramos, Amelie Banc

Understanding the origin of the unique rheological properties of wheat gluten, the protein fraction of wheat grain, is crucial in bread-making processes and questions scientists since polymeric glutenins. To better understand the respective role of the different classes of proteins in the supramolecular structure of gluten and its link to the material proper

Wim Martens, Matthias Niewerth, Tina Popp, Stijn Vansummeren

Modern graph database query languages such as GQL, SQL/PGQ, and their academic predecessor G-Core promote paths to first-class citizens in the sense that paths that match regular path queries can be returned to the user. This brings a number of challenges in terms of efficiency, caused by the fact that graphs can have a huge amount of paths between a given n

Okke van Garderen

This paper shows that the motivic BPS invariants associated to a noncommutative crepant resolution of a compound Du-Val singularity are controlled by the labelled Dynkin combinatorics appearing in the work of Iyama--Wemyss. In particular, we show that the invariants vanish for dimension vectors which are not a multiple of a restricted root obtained from the

Jonte R. Hance, John Rarity

The combination of interaction-free measurement and the quantum Zeno effect has been shown to both increase the signal-to-noise ratio of imaging, and decrease the light intensity flux through the imaged object. So far though, this has only been considered for discrimination between translucent and opaque areas of an object. In this paper, we extend this to t

Samuel G. G. Johnston

Consider the semi-discrete torus $\mathbb{T}_n := [0,1) \times \{0,1,\ldots,n-1\}$ representing $n$ unit length strings running in parallel. A bead configuration on $\mathbb{T}_n$ is a point process on $\mathbb{T}_n$ with the property that between every two consecutive points on the same string, there lies a point on each of the neighbouring strings. In this

Thomas Mieling

The theory of gauge-fixed Maxwell equations in linear isotropic dielectrics is developed using a generalisation of the standard $R_\xi$ gauge-fixing term. In static space-times, the theory can be quantised using the Gupta-Bleuler method, which is worked out explicitly for optical fibres either in flat space-time or at a constant gravitational potential. This

Xiang-Xiang Sun, Lu Guo, A. S. Umar

We provide a microscopic description of the fusion reactions between $^{40,48}$Ca and $^{78}$Ni. The internuclear potentials are obtained using the density-constrained (DC) time-dependent Hartree-Fock (TDHF) approach and fusion cross sections are calculated via the incoming wave boundary condition method. By performing DC-TDHF calculations at several selecte

Henri Moscovici

We present results relating the Hopf cyclic cohomology of the Hopf algebra of moving frames with that of the DG Hopf algebra of moving coframes, analogous to the van Est isomorphism between Lie algebra cohomology and continuous group cohomology.

Zhidong Yang, Lie-Wen Chen

Due to their weak final state interactions, the $\phi$ meson and $\Omega$ baryon provide unique probes of the properties of the quark-gluon plasma (QGP) formed in relativistic heavy-ion collisions. Using the quark recombination model with the quark phase-space information parameterized in a viscous blastwave, we study the transverse-momentum spectra and elli

Peter Cohen, Justine Dell, Oscar E. González, Simran Khunger

We study the $n^{\rm th}$ centered moments of the $1$-level density for the low-lying zeros of $L$-functions attached to holomorphic cuspidal newforms of large prime level and fixed weight. Assuming the Generalized Riemann Hypotheses, we compute this statistic for any $n\ge 1$ and for all test functions whose Fourier transforms are supported in $\left(-2/n,

Kun Fang, Shao-Qiang Xi, Li-Zhuo Bao, Xiao-Jun Bi

Gamma-ray pulsar halos are ideal indicators of cosmic-ray propagation in localized regions of the Galaxy and electron injection from pulsar wind nebulae. HESS~J1831$-$098 is a candidate pulsar halo observed by both H.E.S.S. and HAWC experiments. We adopt the flux map of the H.E.S.S. Galactic plane survey and the spectrum measurements of H.E.S.S. and \textit{

Alexander Straub, Sebastian Boblest, Grzegorz K. Karch, Filip Sadlo

Line integration of stream-, streak-, and pathlines is widely used and popular for visualizing single-phase flow. In multiphase flow, i.e., where the fluid consists, e.g., of a liquid and a gaseous phase, these techniques could also provide valuable insights into the internal flow of droplets and ligaments and thus into their dynamics. However, since such st

Zhicheng Huang, Xiaojie Jin, Chengze Lu, Qibin Hou

Masked image modeling (MIM) has achieved promising results on various vision tasks. However, the limited discriminability of learned representation manifests there is still plenty to go for making a stronger vision learner. Towards this goal, we propose Contrastive Masked Autoencoders (CMAE), a new self-supervised pre-training method for learning more compre

Angela Borchers, Frank Ohme

The accuracy of gravitational-wave models of compact binaries has traditionally been addressed by the mismatch between the model and numerical-relativity simulations. This is a measure of the overall agreement between the two waveforms. However, the largest modelling error typically appears in the strong-field merger regime and may affect subdominant signal

Goluck Konuko, Stéphane Lathuilière, Giuseppe Valenzise

Deep generative models, and particularly facial animation schemes, can be used in video conferencing applications to efficiently compress a video through a sparse set of keypoints, without the need to transmit dense motion vectors. While these schemes bring significant coding gains over conventional video codecs at low bitrates, their performance saturates q

James Henderson, Fabio Fehr

We propose a VAE for Transformers by developing a variational information bottleneck regulariser for Transformer embeddings. We formalise the embedding space of Transformer encoders as mixture probability distributions, and use Bayesian nonparametrics to derive a nonparametric variational information bottleneck (NVIB) for such attention-based embeddings. The

Ana Martin, Ruben Ibarrondo, Mikel Sanz

The Harrow-Hassidim-Lloyd quantum algorithm was proposed to solve linear systems of equations $A\vec{x} = \vec{b}$ and it is the core of various applications. However, there is not an explicit quantum circuit for the subroutine which maps the inverse of the problem matrix $A$ into an ancillary qubit. This makes challenging the implementation in current quant

T. Treu, A. Calabro, M. Castellano, N. Leethochawalit

Star-forming galaxies can exhibit strong morphological differences between the rest-frame far-UV and optical, reflecting inhomogeneities in star-formation and dust attenuation. We exploit deep, high resolution NIRCAM 7-band observations to take a first look at the morphology of galaxies in the epoch of reionization ($z>7$), and its variation in the rest-fram

Sivan Toledo

UltimateKalman is a flexible linear Kalman filter and smoother implemented in three popular programming languages: MATLAB, C, and Java. UltimateKalman is a slight simplification and slight generalization of an elegant Kalman filter and smoother that was proposed in 1977 by Paige and Saunders. Their algorithm appears to be numerically superior and more flexib

Cosimo Nigro, Andrea Tramacere

In this review, we discuss various open-source software for modelling the broad-band emission of extragalactic sources from radio up to the highest gamma ray energies. As we provide an overview of the different tools available, we discuss the physical processes such tools implement and detail the computations they can perform. We also examine their conformit

Étienne Artigau, Charles Cadieux, Neil J. Cook, René Doyon

We present a new algorithm for precision radial velocity (pRV) measurements, a line-by-line (LBL) approach designed to handle outlying spectral information in a simple but efficient manner. The effectiveness of the LBL method is demonstrated on two datasets, one obtained with SPIRou on Barnard's star, and the other with HARPS on Proxima Centauri. In the near

Hian Lee Kwa, Victor Babineau, Julien Philippot, Roland Bouffanais

There has been growing interest in the use of multi-robot systems in various tasks and scenarios. The main attractiveness of such systems is their flexibility, robustness, and scalability. An often overlooked yet promising feature is system modularity, which offers the possibility to harness agent specialization, while also enabling system-level upgrades. Ho

Linsui Deng, Yilin Zhang

Feature screening for ultrahigh-dimension, in general, proceeds with two essential steps. The first step is measuring and ranking the marginal dependence between response and covariates, and the second is determining the threshold. We develop a new screening procedure, called SIT-BY procedure, that possesses appealing statistical properties in both steps. By

Shane Dooley, Silvia Pappalardi, John Goold

Although entanglement is a key resource for quantum-enhanced metrology, not all entanglement is useful. For example in the process of many-body thermalisation, bipartite entanglement grows rapidly, naturally saturating to a volume law. This type of entanglement generation is ubiquitous in nature but has no known application in most quantum technologies. The

S. Sadeghi Barzani

Parton branching solutions of QCD evolution equations have recently been studied to construct both collinear and transverse momentum dependent (TMD) parton distributions. In this formalism, a soft-gluon resolution scale is introduced to separate resolvable and non-resolvable branchings, and to take into account soft-gluon coherence effects. In this talk, res

Kimberley M. Timmins, Maarten J. Kamphuis, Iris N. Vos, Birgitta K. Velthuis

The growth of unruptured intracranial aneurysms (UIAs) is a predictor of rupture. Therefore, for further imaging surveillance and treatment planning, it is important to be able to predict if an UIA is likely to grow based on an initial baseline Time-of-Flight MRA (TOF-MRA). It is known that the size and shape of UIAs are predictors of aneurysm growth and/or

Guy Amit, Dana Ben Porath, Sergey V. Buldyrev, Amir Bashan

We study the emergence of a giant component in a spatial network where the distribution of the metric distances between the nodes is scale-invariant, and the interaction between the nodes has a long-range power-law behavior. The nodes are positioned in the metric space using a Levy flight procedure, with an associated scale-invariant step probability density

Steen Markvorsen, Enrique Pendás-Recondo

We study the variational problem of finding the fastest path between two points that belong to different anisotropic media, each with a prescribed speed profile and a common interface. The optimal curves are Finsler geodesics that are refracted -- broken -- as they pass through the interface, due to the discontinuity of their velocities. This "breaking" must

Georgios Peikos, Oscar Espitia, Gabriella Pasi

This contribution summarizes the participation of the UNIMIB team to the TREC 2021 Clinical Trials Track. We have investigated the effect of different query representations combined with several retrieval models on the retrieval performance. First, we have implemented a neural re-ranking approach to study the effectiveness of dense text representations. Addi

Guillaume Dalle, Léo Baty, Louis Bouvier, Axel Parmentier

Combinatorial optimization (CO) layers in machine learning (ML) pipelines are a powerful tool to tackle data-driven decision tasks, but they come with two main challenges. First, the solution of a CO problem often behaves as a piecewise constant function of its objective parameters. Given that ML pipelines are typically trained using stochastic gradient desc

Justus Contzen, Thorsten Dickhaus, Gerrit Lohmann

We present a new approach to modeling the future development of extreme temperatures globally and on a long time-scale by using non-stationary generalized extreme value distributions in combination with logistic functions. This approach is applied to data from the fully coupled climate model AWI-ESM. It enables us to investigate how extremes will change depe

Hengxin Tan, Binghai Yan

The magnetic topological insulator, MnBi$_2$Te$_4$, shows metallic behavior at zero magnetic fields (antiferromagnetic phase, AFM) in thin film transport, which coincides with gapless surface states observed by angle-resolved photoemission spectroscopy, while it can become a Chern insulator at field larger than 6 T (ferromagnetic phase, FM). Thus, the zero-f

Aharon Levy

The LUXE experiment (Laser Und XFEL Experiment) is an experiment in planning at DESY Hamburg using the electron beam of the European XFEL (Eu.XFEL). LUXE is intended to study collisions between a high-intensity optical laser pulse and 16.5 GeV electrons from the Eu.XFEL electron beam, as well as collisions between the laser pulse and high-energy secondary ph

Aaron D. Kaplan, Chandra Shahi, Pradeep Bhetwal, Raj K. Sah

Delocalization errors, such as charge-transfer and some self-interaction errors, plague computationally-efficient and otherwise-accurate density functional approximations (DFAs). Evaluating a semi-local DFA non-self-consistently on the Hartree-Fock (HF) density is often recommended as a computationally cheap remedy for delocalization errors. For sophisticate

Serena Signorelli, Matteo Fontana, Lorenzo Gabrielli, Michele Vespe

The vast amount of data produced everyday (so-called 'digital traces') and available nowadays represent a gold mine for the social sciences, especially in a computational context, that allows to fully extract their informational and knowledge value. In the latest years, statistical offices have made efforts to profit from harnessing the potential offered by

Arghya Ghosh, Subrata Jana, Tomáš Rauch, Fabien Tran

Accurate theoretical prediction of the band offsets at interfaces of semiconductor heterostructures can often be quite challenging. Although density functional theory has been reasonably successful to carry out such calculations and efficient and accurate semilocal functionals are desirable to reduce the computational cost. In general, the semilocal function

Shan Wang, Yanhao Zhang, Ankit Vora, Akhil Perincherry

Existing spatial localization techniques for autonomous vehicles mostly use a pre-built 3D-HD map, often constructed using a survey-grade 3D mapping vehicle, which is not only expensive but also laborious. This paper shows that by using an off-the-shelf high-definition satellite image as a ready-to-use map, we are able to achieve cross-view vehicle localizat

Jianshu Li, Man Luo, Jian Liu, Tao Chen

In this paper, we present the Multi-Forgery Detection Challenge held concurrently with the IEEE Computer Society Workshop on Biometrics at CVPR 2022. Our Multi-Forgery Detection Challenge aims to detect automatic image manipulations including but not limited to image editing, image synthesis, image generation, image photoshop, etc. Our challenge has attracte

Xi-Nan Ma, Dekai Zhang

We study the exterior Dirichlet problem for the homogeneous $k$-Hessian equation. The prescribed asymptotic behavior at infinity of the solution is zero if $k<\frac{n}{2}$, it is $\log|x|+O(1)$ if $k=\frac{n}{2}$ and it is $|x|^{\frac{2k-n}{n}}+O(1)$ if $k>\frac{n}{2}$. By constructing smooth solutions of approximating non-degenerate $k$-Hessian equations wi

Francesco Scotognella

Metal halide perovskites are materials that show unique characteristics for photovoltaics and light emission. Amplified spontaneous emission and stimulated emission has been shown with these materials, together with electroluminescence in light-emitting diodes and light-emitting transistors. An important achievement that combine stimulated emission and elect

Arnaud Boutillon, Pierre-Henri Conze, Christelle Pons, Valérie Burdin

Clinical diagnosis of the pediatric musculoskeletal system relies on the analysis of medical imaging examinations. In the medical image processing pipeline, semantic segmentation using deep learning algorithms enables an automatic generation of patient-specific three-dimensional anatomical models which are crucial for morphological evaluation. However, the s

F. Arco, S. Heinemeyer, M. J. Herrero

In this letter we study the specific sensitivity and constraints to the soft breaking $Z_2$ parameter $m_{12}$ of the Two Higgs Doublet Model (2HDM). $m_{12}$ is considered here as an input parameter of the model together with the masses of the Higgs bosons, $m_h$, $m_H$, $m_A$, $m_{H^\pm}$, the ratio of the two Higgs vacuum expectation values, $\tan \beta$,

Pallabi Saikia, Kshitij Gundale, Ankit Jain, Dev Jadeja

Detection of fake news is crucial to ensure the authenticity of information and maintain the news ecosystems reliability. Recently, there has been an increase in fake news content due to the recent proliferation of social media and fake content generation techniques such as Deep Fake. The majority of the existing modalities of fake news detection focus on co

Neil K. Chada, Marco A. Iglesias, Shuai Lu, Frank Werner

For numerous parameter and state estimation problems, assimilating new data as they become available can help produce accurate and fast inference of unknown quantities. While most existing algorithms for solving those kind of ill-posed inverse problems can only be used with a single instance of the observed data, in this work we propose a new framework that

Junehyuk Jung, Steve Zelditch

We prove that the real parts of equivariant (but non-invariant) eigenfunctions of generic bundle metrics on nontrivial principal $S^1$ bundles over manifolds of any dimension have connected nodal sets and exactly 2 nodal domains. This generalizes earlier results of the authors in the $3$-dimensional case. The failure of the results on for non-free $S^1$ acti

Hugh S. Hudson, Laura Peticolas, Calvin Johnson, Vivian White

The total solar eclipse of August 21, 2017, crossed the whole width of North America, the first occasion for this during the modern age of consumer electronics. Accordingly, it became a great opportunity to engage the public and to enlist volunteer observers with relatively high-level equipment; our program ("Eclipse Megamovie") took advantage of this as a m

Faruk Göloğlu, Lukas Kölsch

We investigate the isotopy question for Taniguchi semifields. We give a complete characterization when two Taniguchi semifields are isotopic. We further give precise upper and lower bounds for the total number of non-isotopic Taniguchi semifields, proving that there are around $p^{m+s}$ non-isotopic Taniguchi semifields of size $p^{2m}$ where $s$ is the larg

Robert F. Allen, Flavia Colonna, Rubén A. Martínez-Avendaño, Matthew A. Pons

In this paper, we study the hypercyclic composition operators on weighted Banach spaces of functions defined on discrete metric spaces. We show that the only such composition operators act on the "little" spaces. We characterize the bounded composition operators on the little spaces, as well as provide various necessary conditions for hypercyclicity.

Yeon Joo Lee, Antonio García Muñoz, Atsushi Yamazaki, Eric Quémerais

We performed a unique Venus observation campaign to measure the disk brightness of Venus over a broad range of wavelengths in August and September 2020. The primary goal of the campaign is to investigate the absorption properties of the unknown absorber in the clouds. The secondary goal is to extract a disk mean SO$_2$ gas abundance, whose absorption spectra

Siming He

In this paper, we investigate a coupled Patlak-Keller-Segel-Navier-Stokes (PKS-NS) system. We show that globally regular solutions with arbitrary large cell populations exist. The primary blowup suppression mechanism is the shear flow mixing induced enhanced dissipation phenomena.

Jakob Raymaekers, Peter J. Rousseeuw

The usual Minimum Covariance Determinant (MCD) estimator of a covariance matrix is robust against casewise outliers. These are cases (that is, rows of the data matrix) that behave differently from the majority of cases, raising suspicion that they might belong to a different population. On the other hand, cellwise outliers are individual cells in the data ma

Arthur Aubret, Markus Ernst, Céline Teulière, Jochen Triesch

Biological vision systems are unparalleled in their ability to learn visual representations without supervision. In machine learning, self-supervised learning (SSL) has led to major advances in forming object representations in an unsupervised fashion. Such systems learn representations invariant to augmentation operations over images, like cropping or flipp