March 2023 arXiv papers — page 62

Yue Guan, Mohammad Afshari, Panagiotis Tsiotras

This work studies the behaviors of two large-population teams competing in a discrete environment. The team-level interactions are modeled as a zero-sum game while the agent dynamics within each team is formulated as a collaborative mean-field team problem. Drawing inspiration from the mean-field literature, we first approximate the large-population team gam

Jared Miller, Tianyu Dai, Mario Sznaier, Bahram Shafai

This paper presents a linear-programming based algorithm to perform data-driven stabilizing control of linear positive systems. A set of state-input-transition observations is collected up to magnitude-bounded noise. A state feedback controller and dual linear copositive Lyapunov function are created such that the set of all data-consistent plants is contain

Kaiwu Zhang, Shiqiang Du, Baokai Liu, Shengxia Gao

Incomplete multi-view clustering (IMVC) is an unsupervised approach, among which IMVC via contrastive learning has received attention due to its excellent performance. The previous methods have the following problems: 1) Over-reliance on additional projection heads when solving the dimensional collapse problem in which latent features are only valid in lower

Christine Heitsch

The Kreweras complementation map is an anti-isomorphism on the lattice of noncrossing partitions. We consider an analogous operation for plane trees motivated by the molecular biology problem of RNA folding. In this context, we explicitly count the orbits of Kreweras' map according to their length as the number of appropriate symmetry classes of trees in the

N. Tomassetti, E. Fiandrini, B. Bertucci, F. Donnini

Understanding the time-dependent relationship between the Sun's variability and cosmic rays (GCR) is essential for developing predictive models of energetic radiation in space. When traveling inside the heliosphere, GCRs are affected by magnetic turbulence and solar wind disturbances which result in the so-called solar modulation effect. To investigate this

Mitsuru Tsukagoshi, Suguru Kishida, Kenshin Kurauchi, Daichi Ito

Crystal field level scheme of a uniaxial chiral helimagnet YbNi$_3$Al$_9$, exhibiting a chiral magnetic soliton lattice state by Cu substitution for Ni, has been determined by inelastic neutron scattering. The ground and the first excited doublets are separated by 44 K and are simply expressed as $α|\pm 7/2\rangle + β|\mp 5/2\rangle$ with $α$ and $β$ nearly

Yanshen Sun, Kaiqun Fu, Chang-Tien Lu

The prompt estimation of traffic incident impacts can guide commuters in their trip planning and improve the resilience of transportation agencies' decision-making on resilience. However, it is more challenging than node-level and graph-level forecasting tasks, as it requires extracting the anomaly subgraph or sub-time-series from dynamic graphs. In this pap

Pulkit Khandelwal, Michael Tran Duong, Shokufeh Sadaghiani, Sydney Lim

Postmortem MRI allows brain anatomy to be examined at high resolution and to link pathology measures with morphometric measurements. However, automated segmentation methods for brain mapping in postmortem MRI are not well developed, primarily due to limited availability of labeled datasets, and heterogeneity in scanner hardware and acquisition protocols. In

Juil Koo, Seungwoo Yoo, Minh Hieu Nguyen, Minhyuk Sung

We present a cascaded diffusion model based on a part-level implicit 3D representation. Our model achieves state-of-the-art generation quality and also enables part-level shape editing and manipulation without any additional training in conditional setup. Diffusion models have demonstrated impressive capabilities in data generation as well as zero-shot compl

X. H. Mo, P. Wang, J. Y. Zhang

In the light of SU(3) flavor symmetry, the effective interaction Hamiltonian in tensor form is obtained by virtue of group representation theory. The strong and electromagnetic breaking effects are treated as a spurion octet so that the flavor singlet principle can be utilized as the criterion to determine the form of effective Hamiltonian. Two body decays o

Ahmad AlMughrabi, Umair Haroon, Ricardo Marques, Petia Radeva

Neural radiance fields (NeRF) appeared recently as a powerful tool to generate realistic views of objects and confined areas. Still, they face serious challenges with open scenes, where the camera has unrestricted movement and content can appear at any distance. In such scenarios, current NeRF-inspired models frequently yield hazy or pixelated outputs, suffe

Joshua C. Zhao, Atul Sharma, Ahmed Roushdy Elkordy, Yahya H. Ezzeldin

Federated learning was introduced to enable machine learning over large decentralized datasets while promising privacy by eliminating the need for data sharing. Despite this, prior work has shown that shared gradients often contain private information and attackers can gain knowledge either through malicious modification of the architecture and parameters or

Carlo Marzo, Aurora Melis

It is tempting to interpret the minuscule scale of neutrino masses as a symptom of its radiative origin. In light of the notable leap in precision expected at the Future Circular Collider, we explore areas of the parameter space that can simultaneously support the detectable Higgs-strahlung signal with parallel ones from forthcoming measurements in low-energ

Thomas Pfeifer, Matthias Wollenhaupt, Manfred Lein

We train a model atom to recognize hand-written digits between 0 and 9, employing intense light--matter interaction as a computational resource. For training, individual images of hand-written digits in the range 0-9 are converted into shaped laser pulses (data input pulses). Simultaneously with an input pulse, another shaped pulse (program pulse), polarized

Evgeny Abakumov, Arafat Abbar

We show that the bilateral backward shift on $\ell^p(\mathbb{Z},\omega)$ that has a projective orbit with a non-zero limit point is supercyclic. This phenomenon holds also for $\Gamma$-supercyclicity, which extends a result obtained for the first time by Chan and Seceleanu. Moreover, we show that if $K$ is a compact subset of $\ell^p(\mathbb{N},\omega)$ such

Rahul Basu, Dipanjan Mitra, George I. Melikidze

A novel scheme has been developed to show that the observed phase behaviour associated with subpulse drifting from two pulsars, J1034$-$3224 and J1720$-$2933, can be used to obtain the magnetic field configuration in the partially screened gap (PSG). The outflowing plasma along the open magnetic field line region of pulsars is generated due to spark discharg

Christine Heitsch, Chi N. Y. Huynh, Greg Johnston

The branching of an RNA molecule is an important structural characteristic yet difficult to predict correctly, especially for longer sequences. Using plane trees as a combinatorial model for RNA folding, we consider the thermodynamic cost, known as the barrier height, of transitioning between branching configurations. Using branching skew as a coarse energy

M. Au, M. Athanasakis-Kaklamanakis, L. Nies, R. Heinke

Accelerator-based techniques are one of the leading ways to produce radioactive nuclei. In this work, the Isotope Separation On-Line method was employed at the CERN-ISOLDE facility to produce neptunium and plutonium from a uranium carbide target material using 1.4-GeV protons. Neptunium and plutonium were laser-ionized and extracted as 30-keV ion beams. A Mu

Fabio Schittler Neves, Marc Timme

How spiking neuronal networks encode memories in their different time and spatial scales constitute a fundamental topic in neuroscience and neuro-inspired engineering. Much attention has been paid to large networks and long-term memory, for example in models of associative memory. Smaller circuit motifs may play an important complementary role on shorter tim

Noam Buckman, Shiva Sreeram, Mathias Lechner, Yutong Ban

Intelligent intersection managers can improve safety by detecting dangerous drivers or failure modes in autonomous vehicles, warning oncoming vehicles as they approach an intersection. In this work, we present FailureNet, a recurrent neural network trained end-to-end on trajectories of both nominal and reckless drivers in a scaled miniature city. FailureNet

Ilsa R. Cooke, Ci Xue, P. Bryan Changala, Hannah Toru Shay

We report the detection of the lowest energy conformer of $E$-1-cyano-1,3-butadiene ($E$-1-C$_4$H$_5$CN), a linear isomer of pyridine, using the fourth data reduction of the GOTHAM deep spectral survey toward TMC-1 with the 100 m Green Bank Telescope. We performed velocity stacking and matched filter analyses using Markov chain Monte Carlo simulations and fi

Rob Eagle

With the proliferation of devices that display augmented reality (AR), now is the time for scholars and practitioners to evaluate and engage critically with emerging applications of the medium. AR mediates the way users see their bodies, hear their environment and engage with places. Applied in various forms, including social media, e-commerce, gaming, enter

Kira Droganova, Daniel Zeman

This paper analyzes multiple deep-syntactic frameworks with the goal of creating a proposal for a set of universal semantic role labels. The proposal examines various theoretic linguistic perspectives and focuses on Meaning-Text Theory and Functional Generative Description frameworks. For the purpose of this research, data from four languages is used -- Span

Daniele Corradetti, David Chester, Raymond Aschheim, Klee Irwin

In this paper we present a general setting for aperiodic Jordan algebras arising from icosahedral quasicrystals that are obtainable as model sets of a cut-and-project scheme with a convex acceptance window. In these hypothesis, we show the existence of an aperiodic Jordan algebra structure whose generators are in one-to-one correspondence with elements of th

Ryan Po, Gordon Wetzstein

Designing complex 3D scenes has been a tedious, manual process requiring domain expertise. Emerging text-to-3D generative models show great promise for making this task more intuitive, but existing approaches are limited to object-level generation. We introduce \textbf{locally conditioned diffusion} as an approach to compositional scene diffusion, providing

Angela F. Gao, Oscar Leong, He Sun, Katherine L. Bouman

We consider solving ill-posed imaging inverse problems without access to an explicit image prior or ground-truth examples. An overarching challenge in inverse problems is that there are many undesired images that fit to the observed measurements, thus requiring image priors to constrain the space of possible solutions to more plausible reconstructions. Howev

Hugo Lóio, Andrea De Luca, Jacopo De Nardis, Xhek Turkeshi

We investigate the crucial role played by a global symmetry in the purification timescales and the phase transitions of monitored free fermionic systems separating a mixed and a pure phase. Concretely, we study Majorana and Dirac circuits with $\mathbb{Z}_2$ and U(1) symmetries, respectively. In the first case, we demonstrate the mixed phase of $L$ sites has

M. Au, M. Athanasakis-Kaklamanakis, L. Nies, J. Ballof

The use of radioactive molecules for fundamental physics research is a developing interdisciplinary field limited dominantly by their scarce availability. In this work, radioactive molecular ion beams containing actinide nuclei extracted from uranium carbide targets are produced via the Isotope Separation On-Line technique at the CERN-ISOLDE facility. Two me

Jingwei Zhang, Saarthak Kapse, Ke Ma, Prateek Prasanna

Whole slide image (WSI) classification is a critical task in computational pathology, requiring the processing of gigapixel-sized images, which is challenging for current deep-learning methods. Current state of the art methods are based on multi-instance learning schemes (MIL), which usually rely on pretrained features to represent the instances. Due to the

Erik Carlsson, John Carlsson

For every Gaussian kernel density estimator $f(x)=\sum_i a_i \exp(-\lVert x-x_i\rVert^2/2h^2)$ associated to a point cloud $\mathcal{D}=\{x_1,...,x_N\}\subset \mathbb{R}^d$, we define a nested family of closed subspaces $\mathcal{S}(a)\subset\mathbb{R}^d$, which we interpret as a continuous version of an alpha shape. Using arguments based on Fenchel duality,

Łukasz Brzozowski, Grzegorz Siudem, Marek Gagolewski

Community detection is a critical challenge in analysing real graphs, including social, transportation, citation, cybersecurity, and many other networks. This article proposes three new, general, hierarchical frameworks to deal with this task. The introduced approach supports various linkage-based clustering algorithms, vertex proximity matrices, and graph r

Geert Leus, Antonio G. Marques, José M. F. Moura, Antonio Ortega

Graph signal processing (GSP) generalizes signal processing (SP) tasks to signals living on non-Euclidean domains whose structure can be captured by a weighted graph. Graphs are versatile, able to model irregular interactions, easy to interpret, and endowed with a corpus of mathematical results, rendering them natural candidates to serve as the basis for a t

Amjad Ali, Muhammad Hamraz, Dost Muhammad Khan, Wajdan Deebani

Ensembles based on k nearest neighbours (kNN) combine a large number of base learners, each constructed on a sample taken from a given training data. Typical kNN based ensembles determine the k closest observations in the training data bounded to a test sample point by a spherical region to predict its class. In this paper, a novel random projection extended

Young Shin Kim

This paper proposes analytic forms of portfolio CoVaR and CoCVaR on the normal tempered stable market model. Since CoCVaR captures the relative risk of the portfolio with respect to a benchmark return, we apply it to the relative portfolio optimization. Moreover, we derive analytic forms for the marginal contribution to CoVaR and the marginal contribution to

Sungwoong Kim, Daejin Jo, Donghoon Lee, Jongmin Kim

While generative modeling on multimodal image-text data has been actively developed with large-scale paired datasets, there have been limited attempts to generate both image and text data by a single model rather than a generation of one fixed modality conditioned on the other modality. In this paper, we explore a unified generative vision-and-language (VL)

Rixin Li, Dong Lai

Stellar-mass binary black holes (BBHs) embedded in active galactic nucleus (AGN) discs offer a distinct dynamical channel to produce black hole mergers detected in gravitational waves by LIGO/Virgo. To understand their orbital evolution through interactions with the disc gas, we perform a suite of 2D high-resolution, local shearing box, viscous hydrodynamica

Jackie Baek, Justin J. Boutilier, Vivek F. Farias, Jonas Oddur Jonasson

Behavioral health interventions, delivered through digital platforms, have the potential to significantly improve health outcomes, through education, motivation, reminders, and outreach. We study the problem of optimizing personalized interventions for patients to maximize a long-term outcome, where interventions are costly and capacity-constrained. We assum

D. B. Palakkatharappil, O. L. Creevey

The ages of pulsating stars in clusters can be determined by isochrone fitting and it can be further improved by asteroseismic modelling. We analyse the intermediate-age open cluster NGC2477, known to suffer from differential extinction, to explore if asteroseismology and clusters characteristics can help understand the metallicity, extinction and result in

Karol Kolodziej

PSGen is a new general purpose Fortran program which has been written to facilitate the Monte Carlo phase space integration of the S matrix element of any 2 -> n scattering process, with n=2,...,9, provided by the user. The program is written in Fortran 90/95. It uses a new very fast algorithm that automatically generates calls to Fortran subroutines contain

Levi Corallo, Aparna S. Varde

The Berber, or Amazigh language family is a low-resource North African vernacular language spoken by the indigenous Berber ethnic group. It has its own unique alphabet called Tifinagh used across Berber communities in Morocco, Algeria, and others. The Afroasiatic language Berber is spoken by 14 million people, yet lacks adequate representation in education,

Vishesh Kalvakurthi, Aparna S. Varde, John Jenq

In this paper, we present a demo of an intelligent personal agent called Hey Dona (or just Dona) with virtual voice assistance in student course registration. It is a deployed project in the theme of AI for education. In this digital age with a myriad of smart devices, users often delegate tasks to agents. While pointing and clicking supersedes the erstwhile

Stefano Racioppi, Maosheng Miao, Eva Zurek

Evolutionary searches were employed to predict the most stable structures of perovskites with helium atoms on their A-sites up to pressures of 10 GPa. The thermodynamics associated with helium intercalation into [CaZr]F6, structure that [He]2[CaZr]F6 adopts under pressure, and the mechanical properties of the parent perovskite and helium-bearing phase were s

Hosein Karimi Khozani, Zhang Yao, Yuan Ye

BESIII is the particle detector of the Beijing Electron-Positron Collider, which is a {\tau} -charm factory working at energies around 4 GeV. The first part of the detector, around the collision site, is called the Main Drift Chamber, MDC. The events recorded at MDC are mixed with the background noise of various origins. On average, about 10% of the hits of

Yuval Shklarsh, Ariel Epstein

Metagratings (MGs), sparse (periodic) composites of subwavelength polarizable particles (meta-atoms), have demonstrated highly efficient diffraction engineering capabilities via meticulous tailoring of the interaction between individual scatterers. To date, MGs at microwave frequencies have mostly been devised for either transverse electric (TE) or transvers

Michael Eichmair, Thomas Koerber

Let $(M,g)$ be an $n$-dimensional asymptotically flat Riemannian manifold with nonnegative scalar curvature that admits a noncompact area-minimizing hypersurface $\Sigma \subset M$. In the case where $n = 3$, O. Chodosh and the first-named author have proven that $(M, g)$ is necessarily isometric to Euclidean space, confirming a conjecture of R. Schoen. In t

Masataro Asai

This article is written for pedagogical purposes aiming at practitioners trying to estimate the finite support of continuous probability distributions, i.e., the minimum and the maximum of a distribution defined on a finite domain. Generalized Pareto distribution GP({\theta}, {\sigma}, {\xi}) is a three-parameter distribution which plays a key role in Peaks-

Amani Al-shawabka, Philip Pietraski, Sudhir B Pattar, Pedram Johari

Radio Frequency Fingerprinting through Deep Learning (RFFDL) is a data-driven IoT authentication technique that leverages the unique hardware-level manufacturing imperfections associated with a particular device to recognize (fingerprint) the device based on variations introduced in the transmitted waveform. The proposed SignCRF is a scalable, channel-agnost

Qi Chang, Rebecca Bascom, Jennifer Toth, Danish Ahmad

Because of the significance of bronchial lesions as indicators of early lung cancer and squamous cell carcinoma, a critical need exists for early detection of bronchial lesions. Autofluorescence bronchoscopy (AFB) is a primary modality used for bronchial lesion detection, as it shows high sensitivity to suspicious lesions. The physician, however, must intera

Stefan Decker

Advancements in computer science and AI lead to the development of larger, more complex knowledge bases. These are susceptible to contradictions, particularly when multiple experts are involved. To ensure integrity during changes, procedures are needed. This work addresses the problem from a logical programming perspective. Integrity violations can be interp

Tejas Jayashankar, Jilong Wu, Leda Sari, David Kant

A singing voice conversion model converts a song in the voice of an arbitrary source singer to the voice of a target singer. Recently, methods that leverage self-supervised audio representations such as HuBERT and Wav2Vec 2.0 have helped further the state-of-the-art. Though these methods produce more natural and melodic singing outputs, they often rely on co

M. Mihovilovič, A. B. Weber, P. Achenbach, M. Bajec

Radiative corrections to elastic scattering represent an important part of the interpretation of electron-induced nuclear reactions at small energy transfers, where they make for a dominant part of background. Here we present and validate a new event generator for mimicking QED radiative processes in electron-carbon scattering that exactly calculates the coh

Philipe De Fabritiis, Itzhak Roditi, Silvio Paolo Sorella

A relativistic Quantum Field Theory framework is devised for Mermin's inequalities. By employing smeared Dirac spinor fields, we are able to introduce unitary operators which create, out of the Minkowski vacuum $| 0 \rangle$, GHZ-type states. In this way, we are able to obtain a relation between the expectation value of Mermin's operators in the vacuum and i

Zixiang Zhou, Dongqiangzi Ye, Weijia Chen, Yufei Xie

There is a recent trend in the LiDAR perception field towards unifying multiple tasks in a single strong network with improved performance, as opposed to using separate networks for each task. In this paper, we introduce a new LiDAR multi-task learning paradigm based on the transformer. The proposed LiDARFormer utilizes cross-space global contextual feature

Jason Ogbebor, John J. Valenza, Peter I. Ravikovitch, Ashoka Karunarathne

Thermodynamic properties of fluids confined in nanopores differ from those observed in the bulk. To investigate the effect of nanoconfinement on water compressibility, we performed water sorption experiments on two nanoporous glass samples while concomitantly measuring the speed of longitudinal and shear ultrasonic waves in these samples. These measurements

D. Baker, P. Demoulin, S. L. Yardley, T. Mihailescu

From 2022 March 18-21, active region (AR) 12967 was tracked simultaneously by Solar Orbiter (SO) at 0.35 au and Hinode/EIS at Earth. During this period, strong blue-shifted plasma upflows were observed along a thin, dark corridor of open field originating at the AR's leading polarity and continuing towards the southern extension of the northern polar coronal

Jörg Hennig

We resume former discussions of the conformally invariant wave equation on a Schwarzschild background, with a particular focus on the behaviour of solutions near the 'cylinder', i.e. Friedrich's representation of spacelike infinity. This analysis can be considered a toy model for the behaviour of the full Einstein equations and the resulting logarithmic sing

Doeko Homan

Ernst Zermelo's axiomatization of set theory (1908) did not exclude `a set that is a member of itself'. We call a set that is a member of itself `an individual'. In this article we prove the elimination of Russell's paradox is equivalent to "For every set S, an individual is a member of S or a set (but not an individual) is not a member of S". This shows the

Sayaka Kochiyama, Benjamin Grossman-Ponemon, Haneesh Kesari

Numerous ingenious engineering designs and devices have been the product of bio-inspiration. Bone, nacre, and other such stiff structural biological materials (SSBMs) are composites that contain mineral and organic materials interlaid together in layers. In nacre, this lamellar architecture is known to contribute to its fracture toughness, and has been inves

Vadim Korolev, Pavel Protsenko

Property prediction accuracy has long been a key parameter of machine learning in materials informatics. Accordingly, advanced models showing state-of-the-art performance turn into highly parameterized black boxes missing interpretability. Here, we present an elegant way to make their reasoning transparent. Human-readable text-based descriptions automaticall

Daniel Faílde, José Daniel Viqueira, Mariamo Mussa Juane, Andrés Gómez

Variational Quantum Algorithms (VQAs) are among the most promising NISQ-era algorithms for harnessing quantum computing in diverse fields. However, the underlying optimization processes within these algorithms usually deal with local minima and barren plateau problems, preventing them from scaling efficiently. Our goal in this paper is to study alternative o

Jesse Windle

We consider how to use Hamiltonian Monte Carlo to sample from a distribution whose log-density is piecewise quadratic, conditioned on the sample lying on the level set of a piecewise affine, continuous function.

Iwo Bialynicki-Birula, Zofia Bialynicka-Birula

In this work we extend the Zeldovich formula, which was originally derived for the free electromagnetic field and was interpreted as the number of photons. We show that our extended formula gives a universal dimensionless measure of the overall strength of electromagnetic fields: free fields and fields produced by various sources, in classical and in quantum

Benton Clark, Varun Hariprasad, Hasan A. Poonawala

This paper develops a provably stable sensor-driven controller for path-following applications of robots with unicycle kinematics, one specific class of which is the wheeled mobile robot (WMR). The sensor measurement is converted to a scalar value (the score) through some mapping (the score function); the latter may be designed or learned. The score is then

Yu-Ru Lin, Shaomei Wu, Winter Mason

Literacy is one of the most fundamental skills for people to access and navigate today's digital environment. This work systematically studies the language literacy skills of online populations for more than 160 countries and regions across the world, including many low-resourced countries where official literacy data are particularly sparse. Leveraging publ

Martin Bäcke

The Chekanov-Eliashberg dg-algebra is an algebraic invariant of Legendrian submanifolds of contact manifolds, whose definition recently has been extended to singular Legendrians. We describe a way of constructing simpler models of this dg-algebra for singular Legendrian knots in $\mathbb{R}^{3}$, and give the first examples of singular knots for which the fu

Stephanie Chen, Juan Pablo Vigneaux

The magnitude of finite categories is a generalization of the Euler characteristic. It is defined using the coarse incidence algebra of rational-valued functions on the given finite category, and a distinguished element in this algebra: the Dirichlet zeta function. The incidence algebra may be identified with the algebra of $n \times n$ matrices over the rat

Yucheng Shi, Mengnan Du, Xuansheng Wu, Zihan Guan

Backdoor attacks inject poisoned samples into the training data, resulting in the misclassification of the poisoned input during a model's deployment. Defending against such attacks is challenging, especially for real-world black-box models where only query access is permitted. In this paper, we propose a novel defense framework against backdoor attacks thro

M. Boninsegni, A. Kuklov, L. Pollet, N. Prokof'ev

We contend that the arguments provided in Phys. Rev. Lett. 130, 016001 (2023), purporting to show the absence of off-diagonal long-range order in hcp $^4$He dislocation cores are misleading and incorrect. In particular, the one-body density matrix averaged over the whole crystalline sample provides no useful information on the possible superfluid behavior in

Z. Y. Xu, M. Madurga, R. Grzywacz, T. T. King

The decay properties of $^{133}$In were studied in detail at the ISOLDE Decay Station (IDS). The implementation of the Resonance Ionization Laser Ion Source (RILIS) allowed separate measurements of its $9/2^+$ ground state ($^{133g}$In) and $1/2^-$ isomer ($^{133m}$In). With the use of $\beta$-delayed neutron and $\gamma$ spectroscopy, the decay strengths ab

Brice Huang, Mark Sellke

We study efficient optimization of the Hamiltonians of multi-species spherical spin glasses. Our results characterize the maximum value attained by algorithms that are suitably Lipschitz with respect to the disorder through a variational principle that we study in detail. We rely on the branching overlap gap property introduced in our previous work and devel

Timo Asikainen, Tomi Männistö, Eetu Huovila

We introduce the nivel2 software for multi-level modelling. Multi-level modelling is a modelling paradigm where a model element may be simultaneously a type for and an instance of other elements under some constraints. This contrasts traditional modelling methods, such as the UML, where an element may not be a class and an object simultaneously. In contrast

Elizabeth Milićević, Kaisa Taipale

We develop the GKM theory for the torus-equivariant cohomology of the affine flag variety using the combinatorics of alcove walks. Dual to the usual GKM setup, which depicts the orbits of the small torus action on a graph, alcove walks take place in tessellations of Euclidean space. Walks in affine rank two occur on triangulations of the plane, providing a m

Shaukat Goderya, Edward Smith, Baylor Fain, Taylor Hutyra

Binary star systems are of particular interest to astronomers because they can be used as astrophysical laboratories to study the properties and processes of stars. Between 70% to 90% of the stars in our galaxy are part of a binary star system. Among the many types of binary systems observed, the dynamics of semi-detached and contact systems are the most int

C. Hawcroft, H. Sana, L. Mahy, J. O. Sundqvist

The winds of massive stars have an impact on stellar evolution and on the surrounding medium. The maximum speed reached by these outflows, the terminal wind speed, is a global wind parameter and an essential input for models of stellar atmospheres and feedback. With the arrival of the ULLYSES programme, a legacy UV spectroscopic survey with HST, we have the

Kian P. Abdolazizi, Kevin Linka, Christian J. Cyron

The constitutive behavior of polymeric materials is often modeled by finite linear viscoelastic (FLV) or quasi-linear viscoelastic (QLV) models. These popular models are simplifications that typically cannot accurately capture the nonlinear viscoelastic behavior of materials. For example, the success of attempts to capture strain rate-dependent behavior has

O. V. Zakhozhay, M. R. Zapatero Osorio, V. J. S. Bejar, J. B. Climent

We obtained deep images of G 196-3 B and VHS J1256-1257 b with the NOrthern Extended Millimeter Array (NOEMA) at 1.3 mm. These data were combined with recently published Atacama Large Millimeter Array (ALMA) and Very Large Array (VLA) data of VHS J1256-1257 b at 0.87 mm and 0.9 cm, respectively. Neither G 196-3 B nor VHS J1256-1257 b were detected in the NOE

Anita Dąbrowska, Marcin Marciniak

We determine filtering and master equations for a quantum system interacting with wave packet of light in a continuous-mode squeezed number state. We formulate the problem of conditional evolution of a quantum system making use of model of repeated interactions and measurements. In this approach the quantum system undergoes a sequence of interactions with an

Renteng Yuan, Qiaojun Xiang, Zhiheng Fang, Xin Gu

Speeding has been acknowledged as a critical determinant in increasing the risk of crashes and their resulting injury severities. This paper demonstrates that severe speeding-related crashes within the state of Pennsylvania have a spatial clustering trend, where four crash datasets are extracted from four hotspot districts. Two log-likelihood ratio (LR) test

Renteng Yuan, Xin Gu, Zhipeng Peng, Qiaojun Xiang

Rear-end crashes are one of the most common crash types. Passenger cars involved in rear-end crashes frequently produce severe outcomes. However, no study investigated the differences in the injury severity of occupant groups when cars are involved as following and leading vehicles in rear-end crashes. Therefore, the focus of this investigation is to compare

Arash Ghahraman, Gyula Bene

Viscous linear surface waves are studied at arbitrary wavelength, layer thickness, viscosity and surface tension. We find that in shallow enough fluids no surface waves can propagate. This layer thickness is determined for some fluids, water, glycerin and mercury. Even in any thicker fluid layers, propagation of very short and very long waves is forbidden. W

Eric Dexheimer, Andrew J. Davison

We propose learning a depth covariance function with applications to geometric vision tasks. Given RGB images as input, the covariance function can be flexibly used to define priors over depth functions, predictive distributions given observations, and methods for active point selection. We leverage these techniques for a selection of downstream tasks: depth

T. Ghosh, Sangeeta, G. Saxena, B. K. Agrawal

Background: The density dependence of nuclear symmetry energy is crucial in determining several properties of finite nuclei to the neutron stars with mass $\sim$ 1.4 $M_\odot$. The values of neutron skin thickness, isovector giant dipole resonances energies and various nuclear reaction cross-sections in asymmetric nuclei have been utilized to determine the s

L. Gajović, F. Welzmüller, V. Heesen, F. de Gasperin

Weakly interacting massive particles (WIMPs) can self-annihilate, thus providing us with a way to indirectly detect dark matter (DM). Dwarf spheroidal (dSph) galaxies are excellent places to search for annihilation signals because they are rich in DM and background emission is low. If magnetic fields in dSph galaxies exist, the particles produced in DM annih

Joseph Ben Geloun, Sanjaye Ramgoolam

We define the computational task of detecting projectors in finite dimensional associative algebras with a combinatorial basis, labelled by representation theory data, using combinatorial central elements in the algebra. In the first example, the projectors belong to the centre of a symmetric group algebra and are labelled by Young diagrams with a fixed numb

Kevin Lin, Christopher Agia, Toki Migimatsu, Marco Pavone

We propose Text2Motion, a language-based planning framework enabling robots to solve sequential manipulation tasks that require long-horizon reasoning. Given a natural language instruction, our framework constructs both a task- and motion-level plan that is verified to reach inferred symbolic goals. Text2Motion uses feasibility heuristics encoded in Q-functi

Luigi Russo, Siddharth H. Nair, Luigi Glielmo, Francesco Borrelli

We propose a supervised learning framework for computing solutions of multi-parametric Mixed Integer Linear Programs (MILPs) that arise in Model Predictive Control. Our approach also quantifies sub-optimality for the computed solutions. Inspired by Branch-and-Bound techniques, the key idea is to train a Neural Network/Random Forest, which for a given paramet

Johanna Erdmenger, Shao-Kai Jian, Zhuo-Yu Xian

Krylov complexity measures the spread of the wavefunction in the Krylov basis, which is constructed using the Hamiltonian and an initial state. We investigate the evolution of the maximally entangled state in the Krylov basis for both chaotic and non-chaotic systems. For this purpose, we derive an Ehrenfest theorem for the Krylov complexity, which reveals it

Paul Méhaignerie, Clément Sayrin, Jean-Michel Raimond, Michel Brune

Rydberg atoms are remarkable tools for the quantum simulation of spin arrays. Circular Rydberg atoms open the way to simulations over very long time scales, using a combination of laser trapping of the atoms and spontaneous-emission inhibition, as shown in the proposal of a XXZ spin-array simulator based on chains of trapped circular atoms [T.L. Nguyen $\tex

Xinzi He, Alan Wang, Mert R. Sabuncu

Head MRI pre-processing involves converting raw images to an intensity-normalized, skull-stripped brain in a standard coordinate space. In this paper, we propose an end-to-end weakly supervised learning approach, called Neural Pre-processing (NPP), for solving all three sub-tasks simultaneously via a neural network, trained on a large dataset without individ

Muhammad Zakwan, Massimiliano d'Angelo, Giancarlo Ferrari-Trecate

This paper investigates the universal approximation capabilities of Hamiltonian Deep Neural Networks (HDNNs) that arise from the discretization of Hamiltonian Neural Ordinary Differential Equations. Recently, it has been shown that HDNNs enjoy, by design, non-vanishing gradients, which provide numerical stability during training. However, although HDNNs have

Xiying Du, Yanjia Li, Shijie Xie, Xingxing Yu

We say that a graph $G$ is $(2,m)$-linked if, for any distinct vertices $a_1,\ldots, a_m, b_1,b_2$ in $G$, there exist vertex disjoint connected subgraphs $A,B$ of $G$ such that $\{a_1, \ldots, a_m\}$ is contained in $A$ and $\{b_1,b_2\}$ is contained in $B$. A fundamental result in structural graph theory is the characterization of $(2,2)$-linked graphs, wi

Zhuoming Liu, Xuefeng Hu, Ram Nevatia

We propose a new setting for detecting unseen objects called Zero-shot Annotation object Detection (ZAD). It expands the zero-shot object detection setting by allowing the novel objects to exist in the training images and restricts the additional information the detector uses to novel category names. Recently, to detect unseen objects, large-scale vision-lan

L. Benítez-Babilonia, R. Felipe, L. Rubio

Some fixed point results of classical theory, such as Banach's Fixed Point Theorem, have been previously extended by other authors to asymmetric spaces in recent years. The aim of this paper is to extend to asymmetric spaces some others fixed point results for contractions, shrinkage maps and non-expansive maps. In fact, a version of Edelstein type theorem (

M. M. Piva, J. C. Souza, G. A. Lombardi, K. R. Pakuszewski

The Weyl semimetal CeAlGe is a promising material to study nontrivial topologies in real and momentum space due to the presence of a topological magnetic phase. Our results at ambient pressure show that the electronic properties of CeAlGe are extremely sensitive to small stoichiometric variations. In particular, the topological Hall effect (THE) present in C

Damiano F. G. Fiorillo, Georg Raffelt

We consider a dense neutrino gas in the "fast-flavor limit" (vanishing neutrino masses). For the first time, we identify exact solutions of the nonlinear wave equation in the form of solitons. They can propagate with both sub- or superluminal speed, the latter not violating causality. The soliton with infinite speed is a homogeneous solution and coincides wi

Erik Wegner Hodt, Jabir Ali Ouassou, Jacob Linder

Adding a Rashba term to the Hubbard Hamiltonian produces a model which can be used to learn how spin-orbit interactions impact correlated electrons on a lattice. Previous works have studied such a model using a variety of theoretical frameworks, mainly close to half-filling. In this work, we determine the magnetic phase-diagram for the Rashba-Hubbard model f

H. Avdan, E. Sonbas, K. S. Dhuga, A. Vinokurov

Archival {\it XMM-Newton}, {\it Chandra} and {\it Hubble Space Telescope (HST)} data have been used to study the X-ray and optical properties of two candidate ultraluminous X-ray sources (ULXs) in NGC\,4536. In order to search for potential optical counterparts, relative astrometry between {\it Chandra} and {\it HST} was improved, and as a result, optical co

Eduardo S. Fraga, Letícia F. Palhares, Tulio E. Restrepo

We compute the pressure, chiral condensate and strange quark number susceptibility from first principles within perturbative QCD at finite temperature and very high magnetic fields up to next-to-leading order and physical quark masses. The region of validity for our framework is given by $m_s \ll T \ll \sqrt{eB}$, where $m_s$ is the strange quark mass, $e$ i

Thoma Zoto, John C. Bowman

Exponential integrators are explicit methods for solving ordinary differential equations that treat linear behaviour exactly. The stiff-order conditions for exponential integrators derived in a Banach space framework by Hochbruck and Ostermann are solved symbolically by expressing the Runge--Kutta weights as unknown linear combinations of phi functions. Of p

Aaron Heap, Douglas Baldwin, James Canning, Greg Vinal

The study of knot mosaics is based upon representing knot diagrams using a set of tiles on a square grid. This branch of knot theory has many unanswered questions, especially regarding the efficiency with which we draw knots as mosaics. While any knot or link can be displayed as a mosaic, for most of them it is still unknown what size of mosaic (mosaic numbe