April 2023 arXiv papers — page 7

Kaari Landry, Olivier Tremblay-Savard, Manuel Lafond

Phylogenetic networks are increasingly being considered as better suited to represent the complexity of the evolutionary relationships between species. One class of phylogenetic networks that has received a lot of attention recently is the class of orchard networks, which is composed of networks that can be reduced to a single leaf using cherry reductions. C

Jesse Donkervliet, Javier Ron, Junyan Li, Tiberiu Iancu

Online games with modifiable virtual environments (MVEs) have become highly popular over the past decade. Among them, Minecraft -- supporting hundreds of millions of users -- is the best-selling game of all time, and is increasingly offered as a service. Although Minecraft is architected as a distributed system, in production it achieves this scale by partit

Fan Yang, Paolo Molignini, Emil J. Bergholtz

We devise a generic and experimentally accessible recipe to prepare boundary states of topological or nontopological quantum systems through an interplay between coherent Hamiltonian dynamics and local dissipation. Intuitively, our recipe harnesses the spatial structure of boundary states which vanish on sublattices where losses are suitably engineered. This

Jorge Ovalle

In general relativity, nonsingular black holes contain (at least) a Cauchy horizon, a null hypersurface beyond which determinism breaks down. Even though the strong cosmic censorship conjecture establishes the impossibility of extending spacetime beyond this region, in this paper we investigate how far we can go, without invoking this conjecture, in the buil

Simone Dall'Osso, Giulia Stratta, Rosalba Perna, Giovanni de Cesare

Gamma-ray bursts (GRBs), both long and short, are explosive events whose inner engine is generally expected to be a black hole or a highly magnetic neutron star (magnetar) accreting high density matter. Recognizing the nature of GRB central engines, and in particular the formation of neutron stars (NSs), is of high astrophysical significance. A possible sign

Basabendu Barman, Anish Ghoshal, Bohdan Grzadkowski, Anna Socha

We investigate the reach of future gravitational wave (GW) detectors in probing inflaton couplings with visible sector particles that can either be bosonic or fermionic in nature. Assuming reheating takes place through perturbative quantum production from vacuum in presence of classical inflaton background field, we find that the spectral energy density of t

Alberto Baccini, Federica Baccini, Lucio Barabesi, Martina Cioni

In order to explore the suitability of a fine-grained classification of journal articles by exploiting multiple sources of information, articles are organized in a two-layer multiplex. The first layer conveys similarities based on the full-text of articles, and the second similarities based on cited references. The information of the two layers are only weak

V. Agalianou, K. N. Gourgouliatos

While the dipole magnetic field axis of neutron stars is usually postulated to cross the star's centre, it may be displaced from this location, as it has been recently indicated in the millisecond pulsar J0030+0451. Under these conditions, the electromagnetic rocket effect may be activated, where the magnetic field exerts a net force, accelerating the star.

Han Lei, Francesco Valentino, Georgios E. Magdis, Vasily Kokorev

We present new CO ($J=5-4$ and $7-6$) and [CI] ($^3P_2\,-\, ^3P_1$ and $^3P_1\,-\, ^3P_0$) emission line observations of the star-forming galaxy D49 at the massive end of the Main Sequence at $z=3$. We incorporate previous CO ($J=3-2$) and optical-to-millimetre continuum observations to fit its spectral energy distribution (SED). Our results hint at high-$J$

Reza Monadi, Ming-Feng Ho, Kathy L. Cooksey, Simeon Bird

We assemble the largest CIV absorption line catalogue to date, leveraging machine learning, specifically Gaussian processes, to remove the need for visual inspection for detecting CIV absorbers. The catalogue contains probabilities classifying the reliability of the absorption system within a quasar spectrum. Our training set was a sub-sample of DR7 spectra

Rimpei Chiba

Current theories of dynamical friction on galactic bars are based either on linear perturbation theory, which is valid only in the fast limit where the bar changes its pattern speed rapidly, or on adiabatic theory, which is applicable only in the slow limit where the bar's pattern speed is near-constant. In this paper, we study dynamical friction on galactic

Andrzej J. Buras

During the last three decades the determination of the Unitarity Triangle (UT) was dominated by the measurements of its sides $R_b$ and $R_t$ through tree-level $B$ decays and the $\Delta M_d/\Delta M_s$ ratio, respectively, with some participation of the measurements of the angle $\beta$ through the mixing induced CP-asymmetries like $S_{\psi K_S}$ and $\va

Aida Ahmadi, H. Beuther, F. Bosco, C. Gieser

The fragmentation mode of high-mass molecular clumps and the accretion processes that form the most massive stars ($M\gtrsim 8M_\odot$) are still not well understood. To this end, we have undertaken a large observational program (CORE) making use of interferometric observations from the Northern Extended Millimetre Array (NOEMA) for a sample of 20 luminous (

Martin A. Bourne, Hsiang-Yi Karen Yang

Radio jets and the lobes they inflate are common in cool-core clusters and are known to play a critical role in regulating the heating and cooling of the intracluster medium (ICM). This is an inherently multi-scale problem, and much effort has been made to understand the processes governing the inflation of lobes and their impact on the cluster, as well as t

Gonzalo Alonso-Álvarez, James M. Cline, Tianzhuo Xiao

We argue that demanding a consistent cosmological history, including the absence of domain walls and strongly interacting relics at the Peccei-Quinn scale, singles out two concrete realizations of hadronic QCD axions as viable dark matter models. These realizations generally feature flavor-violating axion couplings to Standard Model quarks that are unsuppres

Seyda Ipek, Douglas Tuckler

In $U(1)_R$ extensions of supersymmetric models, the bino and its Dirac partner, the singlino, can play the role of right-handed neutrinos. The bino and the singlino form a pseudo-dirac pair, dubbed the `bi$\nu$o', which can generate Standard Model neutrino masses via the inverse seesaw mechanism. We investigate the prospects for detecting long-lived bi$\nu$

Sven Krippendorf, Nicolas Baron Perez, Esra Bulbul, Melih Kara

We develop a neural network based pipeline to estimate masses of galaxy clusters with a known redshift directly from photon information in X-rays. Our neural networks are trained using supervised learning on simulations of eROSITA observations, focusing in this paper on the Final Equatorial Depth Survey (eFEDS). We use convolutional neural networks which are

Giuliano Giacalone, Govert Nijs, Wilke van der Schee

Emergent bulk properties of matter governed by the strong nuclear force give rise to physical phenomena across vastly different scales, ranging from the shape of atomic nuclei to the masses and radii of neutron stars. They can be accessed on Earth by measuring the spatial extent of the outer skin made of neutrons that characterises the surface of heavy nucle

Niko Koivunen, Martti Raidal

The CMS experiment at CERN has reported a possible signal for a resonance at 146 GeV decaying into the $e\mu$ final state which, presently, is the only experimental hint for lepton flavour violation in any low- and high-energy experiment. The Froggatt-Nielsen mechanism naturally predicts the existence of new scalars, the flavons, with flavour off-diagonal co

Samuel D. Lane, Hye-Sung Lee, Ian M. Lewis

Many new physics scenarios predict multi-photon Higgs resonances. One such scenario is the dark axion portal model. The primary decay chain that we study is the Higgs to dark photon ($\gamma_D$) pairs that subsequently decay into a photon ($\gamma$) and an axion-like particle ($a$). The axion-like particles then decay into photon pairs. Hence, the signal is

Peng Gao, Jiaming Han, Renrui Zhang, Ziyi Lin

How to efficiently transform large language models (LLMs) into instruction followers is recently a popular research direction, while training LLM for multi-modal reasoning remains less explored. Although the recent LLaMA-Adapter demonstrates the potential to handle visual inputs with LLMs, it still cannot generalize well to open-ended visual instructions and

Daniel J. Salib, Vladimir Juričić, Bitan Roy

Topological lattice defects, such as dislocations and grain boundaries (GBs), are ubiquitously present in the bulk of quantum materials and externally tunable in metamaterials. In terms of robust modes, localized near the defect cores, they are instrumental in identifying topological crystals, featuring the hallmark band inversion at a finite momentum (trans

Stefano Baiguera, Rotem Berman, Shira Chapman, Robert C. Myers

The volume behind the black hole horizon was suggested as a holographic dual for the quantum computational complexity of the boundary state in AdS/CFT. This identification is strongly motivated by the switchback effect: a characteristic delay of complexity growth in reaction to an inserted perturbation, modelled as a shockwave in the bulk. Recent proposals o

Edoardo Mainini, Danilo Percivale

We show that the solution of the Cauchy problem for the classical ode $m \mathbf y''=\mathbf f$ can be obtained as limit of minimizers of exponentially weighted convex variational integrals. This complements the known results about weighted inertia-energy approach to Lagrangian mechanics and hyperbolic equations.

Amy de Castro, Hyesuk Lee, Margaret M. Wiecek

This work presents a strongly coupled partitioned method for fluid-structure interaction (FSI) problems based on a monolithic formulation of the system which employs a Lagrange multiplier. We prove that both the semi-discrete and fully discrete formulations are well-posed. To derive a partitioned scheme, a Schur complement equation, which implicitly expresse

Rylan Schaeffer, Brando Miranda, Sanmi Koyejo

Recent work claims that large language models display emergent abilities, abilities not present in smaller-scale models that are present in larger-scale models. What makes emergent abilities intriguing is two-fold: their sharpness, transitioning seemingly instantaneously from not present to present, and their unpredictability, appearing at seemingly unforese

Dhruv Mubayi, Liana Yepremyan

Given two $r$-uniform hypergraphs $G$ and $H$ the Tur\'an number $\rm{ex}(G, H)$ is the maximum number of edges in an $H$-free subgraph of $G$. We study the typical value of $\rm{ex}(G, H)$ when $G=G_{n,p}^{(r)}$, the Erd\H{o}s-R\'enyi random $r$-uniform hypergraph, and $H=C_{2\ell}^{(r)}$, the $r$-uniform linear cycle of length $2\ell$. The case of graphs (

Juanita Antilen, Simon Casassus, Lucas A. Cieza, Camilo González-Ruilova

The $^{12}$CO rotational lines in protoplanetary discs are good tracers of the total spatial extension of the gas component, and potentially planet-disc interactions. We present ALMA long baseline observations of the $^{12}$CO(2-1) line of ten protoplanetary discs from the Ophiuchus DIsc Survey Employing ALMA (ODISEA) project, aiming to set constraints on th

Alberto Nocera, Adrian Feiguin

We present a time-dependent computational approach to study Auger electron spectroscopy (AES) beyond the ultra-short core-hole relaxation time approximation and, as a test case, we apply it to the paradigmatic example of a one-dimensional Mott insulator represented by a half-filled Hubbard chain. The Auger spectrum is usually calculated by assuming that, aft

Charles Yuan, Agnes Villanyi, Michael Carbin

Quantum algorithms for tasks such as factorization, search, and simulation rely on control flow such as branching and iteration that depends on the value of data in superposition. High-level programming abstractions for control flow, such as switches, loops, and higher-order functions, are ubiquitous in classical languages. By contrast, many quantum language

George Pu, Anirudh Jain, Jihan Yin, Russell Kaplan

As foundation models continue to exponentially scale in size, efficient methods of adaptation become increasingly critical. Parameter-efficient fine-tuning (PEFT), a recent class of techniques that require only modifying a small percentage of the model parameters, is currently the most popular method for adapting large language models (LLMs). Several PEFT te

Md. Masudur Rahman, Toukir Ahammed, Md. Mahbubul Alam Joarder, Kazi Sakib

Fault-proneness is an indication of programming errors that decreases software quality and maintainability. On the contrary, code smell is a symptom of potential design problems which has impact on fault-proneness. In the literature, negative impact of code smells on fault-proneness has been investigated. However, it is still unclear that how frequency of ea

Stella L. Harrison, Anton Nalitov, Pavlos G. Lagoudakis, Helgi Sigurðsson

We propose a vortex Chern insulator, motivated by recent experimental demonstrations on programmable arrangements of cavity polariton vortices by [Alyatkin et al., ArXiv:2207.01850 (2022)] and [Wang et al., National Sci. Rev. 10, Nwac096 (2022)]. In the absence of any external fields, time-reversal symmetry is spontaneously broken through polariton condensat

Arthur Conmy, Augustine N. Mavor-Parker, Aengus Lynch, Stefan Heimersheim

Through considerable effort and intuition, several recent works have reverse-engineered nontrivial behaviors of transformer models. This paper systematizes the mechanistic interpretability process they followed. First, researchers choose a metric and dataset that elicit the desired model behavior. Then, they apply activation patching to find which abstract n

Joanna Delicaris, Stefan Schupp, Erika Ábrahám, Anne Remke

This paper proposes an algorithm to maximize reachability probabilities for rectangular automata with random clocks via a history-dependent prophetic scheduler. This model class incorporates time-induced nondeterminism on discrete behavior and nondeterminism in the dynamic behavior. After computing reachable state sets via a forward flowpipe construction, we

Marc Finzi, Andres Potapczynski, Matthew Choptuik, Andrew Gordon Wilson

Unlike conventional grid and mesh based methods for solving partial differential equations (PDEs), neural networks have the potential to break the curse of dimensionality, providing approximate solutions to problems where using classical solvers is difficult or impossible. While global minimization of the PDE residual over the network parameters works well f

Ishika Joshi, Ritvik Budhiraja, Harshal Dev, Jahnvi Kadia

ChatGPT is an AI language model developed by OpenAI that can understand and generate human-like text. It can be used for a variety of use cases such as language generation, question answering, text summarization, chatbot development, language translation, sentiment analysis, content creation, personalization, text completion, and storytelling. While ChatGPT

Lorenzo Perissé, Anthony Onillon, Xavier Mougeot, Matthieu Vivier

The summation method for the calculation of reactor $\bar{\nu}_e$ fluxes and spectra is methodically revised and improved. For the first time, a complete uncertainty budget accounting for all known effects likely to impact these calculations is proposed. Uncertainties of a few percents at low energies and ranging up to 20% at high energies are obtained on th

Prashant Kumar, F. D. M. Haldane

We numerically compute the guiding center static structure factor $\bar S(\bf k)$ of various fractional quantum Hall (FQH) states to $\mathcal{O}\left((k\ell)^6\right)$ where $k$ is the wavenumber and $\ell$ is the magnetic length. Employing density matrix renormalization group on an infinite cylinder of circumference $L_y$, we study the two-dimensional limi

Jiarui Gan, Minbiao Han, Jibang Wu, Haifeng Xu

This paper provides a systematic study of the robust Stackelberg equilibrium (RSE), which naturally generalizes the widely adopted solution concept of the strong Stackelberg equilibrium (SSE). The RSE accounts for any possible up-to-$\delta$ suboptimal follower responses in Stackelberg games and is adopted to improve the robustness of the leader's strategy.

Hao Qin, Kwang-Sung Jun, Chicheng Zhang

We study $K$-armed bandit problems where the reward distributions of the arms are all supported on the $[0,1]$ interval. It has been a challenge to design regret-efficient randomized exploration algorithms in this setting. Maillard sampling \cite{maillard13apprentissage}, an attractive alternative to Thompson sampling, has recently been shown to achieve comp

Pavan Kumar Yerra, Chandrasekhar Bhamidipati, Sudipta Mukherji

Computation of topological charges of the Schwarzschild and charged black holes in AdS in canonical and grand canonical ensembles allows for a classification of the phase transition points via the Bragg-Williams off-shell free energy. We attempt a topological classification of the critical points and the equilibrium phases of the dual gauge theory via a phen

Xinjun Zhu, Yuntao Du, Yuren Mao, Lu Chen

Knowledge graph (KG), which contains rich side information, becomes an essential part to boost the recommendation performance and improve its explainability. However, existing knowledge-aware recommendation methods directly perform information propagation on KG and user-item bipartite graph, ignoring the impacts of \textit{task-irrelevant knowledge propagati

Michele Cafagna, Lina M. Rojas-Barahona, Kees van Deemter, Albert Gatt

When applied to Image-to-text models, interpretability methods often provide token-by-token explanations namely, they compute a visual explanation for each token of the generated sequence. Those explanations are expensive to compute and unable to comprehensively explain the model's output. Therefore, these models often require some sort of approximation that

Misty A. Wahl, Andrea Mari, Nathan Shammah, William J. Zeng

In this work, we migrate the quantum error mitigation technique of Zero-Noise Extrapolation (ZNE) to fault-tolerant quantum computing. We employ ZNE on logically encoded qubits rather than physical qubits. This approach will be useful in a regime where quantum error correction (QEC) is implementable but the number of qubits available for QEC is limited. Apar

Matteo Scandi, Paolo Abiuso, Jacopo Surace, Dario De Santis

The importance of the quantum Fisher information metric is testified by the number of applications that this has in very different fields, ranging from hypothesis testing to metrology, passing through thermodynamics. Still, from the rich range of possible quantum Fisher information, only a handful are typically used and studied. This review aims at collectin

David Chataur, Martintxo Saralegi-Aranguren, Daniel Tanré

Intersection homology of Goresky and MacPherson can be defined from the Deligne sheaf, obtained from truncations of complexes of sheaves. As intersection homology is not the homology of a particular space, the search for a family of spaces whose homologies have properties analogous to intersection homology has developed. For some stratified spaces, M. Banagl

Omer Rana, Theodoros Spyridopoulos, Nathaniel Hudson, Matt Baughman

Federated learning has shown enormous promise as a way of training ML models in distributed environments while reducing communication costs and protecting data privacy. However, the rise of complex cyber-physical systems, such as the Internet-of-Things, presents new challenges that are not met with traditional FL methods. Hierarchical Federated Learning exte

Marcelo Menezes Morato, Amir Naspolini, Julio Elias Normey-Rico

Recent works have demonstrated how Linear Parameter Varying Model Predictive Control (LPV MPC) algorithms are able to control nonlinear systems with precision and reduced computational load. Specifically, these schemes achieve comparable performances to state-of-the-art nonlinear MPCs, while requiring the solution of only one quadratic programming problem (t

Xuan Kien Phung, Sylvie Hamel

The important Kemeny problem, which consists of computing median consensus rankings of an election with respect to the Kemeny voting rule, admits important applications in biology and computational social choice and was generalized recently via an interesting setwise approach by Gilbert et. al. Our first results establish optimal quantitative extensions of t

Lei Zhang, Yuge Zhang, Kan Ren, Dongsheng Li

The field of machine learning (ML) has gained widespread adoption, leading to significant demand for adapting ML to specific scenarios, which is yet expensive and non-trivial. The predominant approaches towards the automation of solving ML tasks (e.g., AutoML) are often time-consuming and hard to understand for human developers. In contrast, though human eng

Félix Dusabirane, Kai Leckron, Baerbel Rethfeld, Hans Christian Schneider

This paper presents a theoretical investigation of electron-magnon scattering processes in the ultrafast demagnetization in itinerant ferromagnets. In the framework of a ferromagnetic model system, we compute the spin-dependent dynamics of electrons in itinerant Bloch states by including electron-magnon and electron-electron scattering processes on an equal

Yosuke Hashidate, Keisuke Yoshihara

This study proposes a tractable stochastic choice model to identify motivations for prosocial behavior, and to explore alternative motivations of deliberate randomization beyond ex-ante fairness concerns. To represent social preferences, we employ an additively perturbed utility model consisting of the sum of expected utility and a nonlinear cost function, w

Zahra Hafezi Kafshgari, Chamani Shiranthika, Parvaneh Saeedi, Ivan V. Bajić

SplitFed Learning, a combination of Federated and Split Learning (FL and SL), is one of the most recent developments in the decentralized machine learning domain. In SplitFed learning, a model is trained by clients and a server collaboratively. For image segmentation, labels are created at each client independently and, therefore, are subject to clients' bia

Peter Wilczynski, Taylor Gregoire-Wright, Daniel Jackson

Developers have long recognized the importance of the concepts underlying the systems they build, and the primary role concepts play in shaping user experience. To date, however, concepts have tended to be only implicit in software design with development being organized instead around more concrete artifacts (such as wireframes and code modules). Palantir,

M. Asadolah Salmanpour, M. Mosleh, S. M. Hamidi

Use of hot atomic vapor as a new tool for tracing the complex nature of light has become a knowledge-based topic in recent years. In this paper, we examine the polarization ellipse of the Bloch surface wave (BSW) through the effect of a magnetic field on the coupling of these surface waves in BSW-hot atomic vapor cell. For this purpose, we fabricate a one-di

Yukito Tsunoda, Akira Oyama

An evolutionary multi-objective aerodynamic design optimization method using the computational fluid dynamics (CFD) simulations incorporating deep neural network (DNN) to reduce the required computational time is proposed. In this approach, the DNN infers the flow field from the grid data of a design and the CFD simulation starts from the inferred flow field

Xin Chen, Anzhu Yu, Qun Sun, Wenyue Guo

A road is the skeleton of a city and is a fundamental and important geographical component. Currently, many countries have built geo-information databases and gathered large amounts of geographic data. However, with the extensive construction of infrastructure and rapid expansion of cities, automatic updating of road data is imperative to maintain the high q

Hao Liao, Sheng Bi, Jiao Wu, Wei Zhang

In this paper, we present an algorithmic study on how to surpass competitors in popularity by strategic promotions in social networks. We first propose a novel model, in which we integrate the Preferential Attachment (PA) model for popularity growth with the Independent Cascade (IC) model for influence propagation in social networks called PA-IC model. In PA

Krzysztof Cichy, Shohini Bhattacharya, Martha Constantinou, Jack Dodson

In recent years, there has been a breakthrough in lattice calculations of $x$-dependent partonic distributions. This encompasses also distributions describing the 3D structure of the nucleon, such as generalized parton distributions (GPDs). We report a new method of accessing GPDs in asymmetric frames of reference, relying on a novel Lorentz-covariant parame

Takayuki Hayashi, Hideyuki Mori, Koji Mukai, Yukikatsu Terada

Gravitational redshift is a fundamental parameter that allows us to determine the mass-to-radius ratio of compact stellar objects, such as black holes, neutron stars, and white dwarfs (WDs). In the X-ray spectra of the close binary system, RX J1712.6$-$2414, obtained from the Chandra High-Energy Transmission Grating observation, we detected significant redsh

Daniel Strano, Benn Bollay, Aryan Blaauw, Nathan Shammah

We benchmark the performances of Qrack, an open-source software library for the high-performance classical simulation of (gate-model) quantum computers. Qrack simulates, in the Schr\"odinger picture, the exact quantum state of $n$ qubits evolving under the application of a circuit composed of elementary quantum gates. Moreover, Qrack can also run approximate

A. S. Kuraptsev, I. M. Sokolov

We report the investigation of the influence of atomic motion on the fluorescence dynamics of dilute atomic ensemble driven by resonant pulse radiation. We show that even for sub-Doppler temperatures, the motion of atoms can significantly affect the nature of both superradiation and subradiation. We also demonstrate that, in the case of an ensemble of moving

Giulia Valvano, Rai Machado Oliveira, Othon Cabo Winter, Rafael Sfair

The aim of this work is to verify the stability of the proposed orbital solutions for the third moonlet (Delta) taking into account a realistic gravitational potential for the central body of the quadruple system (Alpha). We also aim to estimate the location and size of a stability region inside the orbit of Gamma. First, we created a set of test particles w

Huaping He, Fuyuan Xiao

Dempster rule of combination (DRC) is widely used for uncertainty reasoning in intelligent information system, which is generalized to complex domain recently. However, as the increase of identification framework elements, the computational complexity of Dempster Rule of Combination increases exponentially. To address this issue, we propose a novel quantum D

Zhenyao Fang, Andrew M. Rappe

Despite recent advances of layered square-net topological material models that possess ideal semimetallic electronic structures and promising potential in material applications, the identification of experimentally accessible two-dimensional square-net materials with related topological properties has proven challenging. Due to the highly tunable physical an

Carlo Lucibello, Marc Mézard

Recent generalizations of the Hopfield model of associative memories are able to store a number $P$ of random patterns that grows exponentially with the number $N$ of neurons, $P=\exp(\alpha N)$. Besides the huge storage capacity, another interesting feature of these networks is their connection to the attention mechanism which is part of the Transformer arc

Malte Algren, Tobias Golling, Manuel Guth, Chris Pollard

We present an alternative to reweighting techniques for modifying distributions to account for a desired change in an underlying conditional distribution, as is often needed to correct for mis-modelling in a simulated sample. We employ conditional normalizing flows to learn the full conditional probability distribution from which we sample new events for con

Terézia Fulová, Mária Trnovská

Procrustes problems are matrix approximation problems searching for a~transformation of the given dataset to fit another dataset. They find applications in numerous areas, such as factor and multivariate analysis, computer vision, multidimensional scaling or finance. The known methods for solving Procrustes problems have been designed to handle specific sub-

Rafael Mena-Yedra, Juana L. Redondo, Horacio Pérez-Sánchez, Pilar M. Ortigosa

Searching for potential active compounds in large databases is a necessary step to reduce time and costs in modern drug discovery pipelines. Such virtual screening methods seek to provide predictions that allow the search space to be narrowed down. Although cheminformatics has made great progress in exploiting the potential of available big data, caution is

Sugandha Srivastav, Ryan Rafaty

Great socio-economic transitions see the demise of certain industries and the rise of others. The losers of the transition tend to deploy a variety of tactics to obstruct change. We develop a political-economy model of interest group competition and garner evidence of tactics deployed in the global climate movement. From this we deduce a set of strategies fo

Charles Alexandre Bédard

Quantum teleportation is the name of a problem: how can the real-valued parameters encoding the state at Alice's location make their way to Bob's location via shared entanglement and only two bits of classical communication? Without an explanation, teleportation appears to be a conjuring trick. Investigating the phenomenon with Schr\"odinger states and reduc

Stefan Giron, Nikita Polin, Esmaeil Adabifiroozjaei, Yangyiwei Yang

Permanent magnets draw their properties from a complex interplay of chemical composition and phase, each with their associated intrinsic magnetic properties. Gaining an understanding of these interactions is the key to deciphering the origins of a permanent magnets' magnetic performance and facilitate the engineering of much improved-performing magnets. Here

Simon Häuser, Sebastian T. Weber, Christopher Seibel, Marius Weber

Optically driven intersite and interlayer spin transfer are individually known as the fastest processes for manipulating the spin order of magnetic materials on the sub 100 fs time scale. However, their competing influence on the ultrafast magnetization dynamics remains unexplored. In our work, we show that optically induced intersite spin transfer (also kno

Max D. Champneys, Timothy J. Rogers

A great deal of research has been conducted in the consideration of meta-heuristic optimisation methods that are able to find global optima in settings that gradient based optimisers have traditionally struggled. Of these, so-called particle swarm optimisation (PSO) approaches have proven to be highly effective in a number of application areas. Given the mat

Maria Patrizia Carello, Alberto Marchetti Spaccamela, Leonardo Querzoni, Marco Angelini

The growing adoption of IT solutions in the healthcare sector is leading to a steady increase in the number of cybersecurity incidents. As a result, organizations worldwide have introduced regulations, standards, and best practices to address cybersecurity and data protection issues in this sector. However, the application of this large corpus of documents p

Dehua Bi, Yuan Ji

We propose the Plaid Atoms Model (PAM), a novel Bayesian nonparametric model for grouped data. Founded on an idea of `atom skipping', PAM is part of a well-established category of models that generate dependent random distributions and clusters across multiple groups. Atom skipping referrs to stochastically assigning 0 weights to atoms in an infinite mixture

Michał Turski, Tomasz Stanisławek, Karol Kaczmarek, Paweł Dyda

In recent years, the field of document understanding has progressed a lot. A significant part of this progress has been possible thanks to the use of language models pretrained on large amounts of documents. However, pretraining corpora used in the domain of document understanding are single domain, monolingual, or nonpublic. Our goal in this paper is to pro

Mahdieh Safarzadehvahed, Farzaneh Abazari, Afsaneh Madani, Fatemeh Shabani

When a threat is observed, one of the most important challenges is to choose the most appropriate and adequate timely decisions in response to the current and near future situation in order to have the least consequences and costs. Making the appropriate and sufficient decisions requires knowing what situations the threat has engendered or may engender. In t

K. Mukherjee, S. Wüster

We show that an exciton on a discrete chain of sites can be guided by effective measurements induced by an ambient, non-equilibrium medium that is synchronised to the exciton transport. For experimental verification, we propose a hybrid cold atom platform, carrying the exciton as electronic excitation on a chain of atoms, which are surrounded by a slow light

Vincent Hue, Randy Gladstone, Corentin K. Louis, Thomas K. Greathouse

Jupiter's satellite auroral footprints are a consequence of the interaction between the Jovian magnetic field with co-rotating iogenic plasma and the Galilean moons. The disturbances created near the moons propagate as Alfv\'en waves along the magnetic field lines. The position of the moons is therefore "Alfv\'enically" connected to their respective auroral

Lorenz Eberhardt, Gustavo J. Turiaci

We derive the Weil-Petersson measure on the moduli space of hyperbolic surfaces with defects of arbitrary opening angles and use this to compute its volume. We conjecture a matrix integral computing the corresponding volumes and confirm agreement in simple cases. We combine this mathematical result with the equivariant localization approach to Jackiw-Teitelb

Mariya Kilina, Tommaso Elia, Syed Yusha Kareem, Alessandro Carfi

Demographic growth and rise in the average age of the population is increasing the demand for the elderly assistance. Health care oriented ambient intelligence technologies are fundamental to support elderly peoples' autonomy. In this paper, we present a smart home system that is able to recognize human activities and is integrated with a proactive vocal ass

Daniel Groves, Jean-François Lafont, Jason Fox Manning, Lorenzo Ruffoni

We prove that many relatively hyperbolic groups obtained by relative strict hyperbolization admit a cocompact action on a CAT(0) cubical complex. Under suitable assumptions on the peripheral subgroups, these groups are residually finite and even virtually special. We include some applications to the theory of manifolds, such as the construction of new non-po

Giulio Romani

In this paper we address some questions about symmetry, radial monotonicity, and uniqueness for a semilinear fourth-order boundary value problem in the ball of $\mathbb R^2$ deriving from the Kirchhoff-Love model of deformations of thin plates. We first show the radial monotonicity for a wide class of biharmonic problems. The proof of uniqueness is based on

Muzhou Yu, Sia Huat Tan, Kailu Wu, Runpei Dong

Knowledge distillation conducts an effective model compression method while holding some limitations:(1) the feature based distillation methods only focus on distilling the feature map but are lack of transferring the relation of data examples; (2) the relational distillation methods are either limited to the handcrafted functions for relation extraction, su

Daniel Macis, Sara Perilli, Cristina Gena

Recently, it has been considering robotics to face world population aging. According to the WHO, in 2050 there will be about 2.1 billion people over 60 years old worldwide causing a persistent growing need of assistance and a shortage of manpower for delivering congruous assistance. Therefore, seniors' QoL is continuously threatened. Socially Assistive Robot

Adam Dukehart, David Mattingly

Entanglement of spatially separated quantum states is usually defined with respect to a reference frame provided by some external observer. Thus, if one wishes to localize the quantum information within a spatially separated entangled state, one must enact an entanglement extraction protocol also defined with respect to that external frame. Entanglement extr

Alessio Serra, Fabio Carrara, Maurizio Tesconi, Fabrizio Falchi

Trends and opinion mining in social media increasingly focus on novel interactions involving visual media, like images and short videos, in addition to text. In this work, we tackle the problem of visual sentiment analysis of social media images -- specifically, the prediction of image sentiment polarity. While previous work relied on manually labeled traini

Sugandha Srivastav, Tanmay Singh

Laws that govern land acquisition can lock in old paradigms. We study one such case, the Coal Bearing Areas Act of 1957 (CBAA) which provides minimal social and environmental safegaurds, and deviates in important ways from the Right to Fair Compensation and Transparency in Land Acquisition, Rehabilitation and Resettlement Act 2013 (LARR). The lack of due dil

Hyun-Myung Chun, Sungmin Hwang, Byungnam Kahng, Heiko Rieger

The mean first passage time~(MFPT) of random walks is a key quantity characterizing dynamic processes on disordered media. In a random fractal embedded in the Euclidean space, the MFPT is known to obey the power law scaling with the distance between a source and a target site with a universal exponent. We find that the scaling law for the MFPT is not determi

Madelyne Xiao, Mona Wang, Anunay Kulshrestha, Jonathan Mayer

We investigate how users perceive social media account verification, how those perceptions compare to platform practices, and what happens when a gap emerges. We use recent changes in Twitter's verification process as a natural experiment, where the meaning and types of verification indicators rapidly and significantly shift. The project consists of two comp

Nishant Gupta, Nemani V. Suryanarayana

We show that there are four chiral ${\cal W}$-algebra extensions of $\mathfrak{so}(2,3)$ algebra and construct them explicitly. We do this by a simple identification of each of the inequivalent embeddings of a copy of $\mathfrak{sl}(2,{\mathbb R})$ in the $\mathfrak{so}(2,3)$ algebra and the maximal subalgebra $\mathfrak{h}$ that commutes with it. Then using

James Bungay, Osasenaga Emokpae, Samuel D. Relton, Jane Alty

Background: Physiological tremor is defined as an involuntary and rhythmic shaking. Tremor of the hand is a key symptom of multiple neurological diseases, and its frequency and amplitude differs according to both disease type and disease progression. In routine clinical practice, tremor frequency and amplitude are assessed by expert rating using a 0 to 4 int

Seif Laatiri, Pirashanth Ratnamogan, Joel Tang, Laurent Lam

Advances in the Visually-rich Document Understanding (VrDU) field and particularly the Key-Information Extraction (KIE) task are marked with the emergence of efficient Transformer-based approaches such as the LayoutLM models. Despite the good performance of KIE models when fine-tuned on public benchmarks, they still struggle to generalize on complex real-lif

Shing-Chi Leung, Ken'ichi Nomoto, Tomoharu Suzuki

Rotating massive stars with initial progenitor masses $M_{\rm prog} \sim$ 25 $M_{\odot}$ -- $\sim$140 $M_{\odot}$ can leave rapidly rotating black holes to become collapsars. The black holes and the surrounding accretion disks may develop powerful jets by magneto-hydrodynamics instabilities. The propagation of the jet in the stellar envelope provides the nec

Hari Krishnan P. Anilkumar, Aayush Rajesh, Varun Narayanan, Manoj M. Prabhakaran

We study a secret sharing problem with three secrets where the secrets are allowed to be related to each other, i.e., only certain combinations of the three secrets are permitted. The dealer produces three shares such that every pair of shares reveals a unique secret and reveals nothing about the other two secrets, other than what can be inferred from the re

Yi-Lin Sung, Linjie Li, Kevin Lin, Zhe Gan

Model merging (e.g., via interpolation or task arithmetic) fuses multiple models trained on different tasks to generate a multi-task solution. The technique has been proven successful in previous studies, where the models are trained on similar tasks and with the same initialization. In this paper, we expand on this concept to a multimodal setup by merging t

Michel Brueck, Bork A. Berghoff, Daniel Schindler

Small regulatory RNAs (sRNAs) are short non-coding RNAs in bacteria capable of post-transcriptional regulation. sRNAs have recently gained attention as tools in basic and applied sciences for example to fine-tune genetic circuits or biotechnological processes. Even though sRNAs often have a rather simple and modular structure, the design of functional synthe

Abdurahman Maarouf, Dominik Bär, Dominique Geissler, Stefan Feuerriegel

Online propaganda poses a severe threat to the integrity of societies. However, existing datasets for detecting online propaganda have a key limitation: they were annotated using weak labels that can be noisy and even incorrect. To address this limitation, our work makes the following contributions: (1) We present HQP: a novel dataset (N = 30,000) for detect