July 2023 arXiv papers — page 136

Emmanouil Karystinaios, Gerhard Widmer

Roman Numeral analysis is the important task of identifying chords and their functional context in pieces of tonal music. This paper presents a new approach to automatic Roman Numeral analysis in symbolic music. While existing techniques rely on an intermediate lossy representation of the score, we propose a new method based on Graph Neural Networks (GNNs) t

Naoise Holohan

Differential Privacy (DP) relies on random numbers to preserve privacy, typically utilising Pseudorandom Number Generators (PRNGs) as a source of randomness. In order to allow for consistent reproducibility, testing and bug-fixing in DP algorithms and results, it is important to allow for the seeding of the PRNGs used therein. In this work, we examine the la

Sam Adriaensen, Jan De Beule, Giovanni Giuseppe Grimaldi, Jonathan Mannaert

In this paper, we provide a construction of $(q+1)$-ovoids of the hyperbolic quadric $Q^+(7,q)$, $q$ an odd prime power, by glueing $(q+1)/2$-ovoids of the elliptic quadric $Q^-(5,q)$. This is possible by controlling some intersection properties of (putative) $m$-ovoids of elliptic quadrics. It yields eventually $(q+1)$-ovoids of $Q^+(7,q)$ not coming from a

Seo-Jin Kim, Jihang Zhu, Mario M. Piva, Marcus Schmidt

Progress in magnetoelectric materials is hindered by apparently contradictory requirements for time-reversal symmetry broken and polar ferroelectric electronic structure in common ferromagnets and antiferromagnets. Alternative routes could be provided by recent discoveries of a time-reversal symmetry breaking anomalous Hall effect in noncollinear magnets and

Francesco Catino, Marzia Mazzotta, Paola Stefanelli

We prove that any set-theoretic solution of the Yang-Baxter equation associated to a dual weak brace is a strong semilattice of non-degenerate bijective solutions. This fact makes use of the description of any dual weak brace $S$ we provide in terms of strong semilattice $Y$ of skew braces $B_\alpha$, with $\alpha \in Y$. Additionally, we describe the ideals

Benjamin Clavié, Guillaume Soulié

Understanding labour market dynamics requires accurately identifying the skills required for and possessed by the workforce. Automation techniques are increasingly being developed to support this effort. However, automatically extracting skills from job postings is challenging due to the vast number of existing skills. The ESCO (European Skills, Competences,

Xiaoyi Ji, Richard Salmon, Nita Mulliqi, Umair Khan

The potential of artificial intelligence (AI) in digital pathology is limited by technical inconsistencies in the production of whole slide images (WSIs), leading to degraded AI performance and posing a challenge for widespread clinical application as fine-tuning algorithms for each new site is impractical. Changes in the imaging workflow can also lead to co

Xiao Liu, Guangyi Chen, Yansong Tang, Guangrun Wang

Composing simple elements into complex concepts is crucial yet challenging, especially for 3D action generation. Existing methods largely rely on extensive neural language annotations to discern composable latent semantics, a process that is often costly and labor-intensive. In this study, we introduce a novel framework to generate compositional actions with

Virginie Ehrlacher, Frederic Legoll, Benjamin Stamm, Shuyang Xiang

In this article, we extend the study of embedded corrector problems, that we have previously introduced in the context of the homogenization of scalar diffusive equations, to the context of homogenized elastic properties of materials. This extension is not trivial and requires mathematical arguments specific to the elasticity case. Starting from a linear ela

Chenping Fu, Wanqi Yuan, Jiewen Xiao, Risheng Liu

Underwater degraded images greatly challenge existing algorithms to detect objects of interest. Recently, researchers attempt to adopt attention mechanisms or composite connections for improving the feature representation of detectors. However, this solution does \textit{not} eliminate the impact of degradation on image content such as color and texture, ach

Jiaxing Xu, Qingtian Bian, Xinhang Li, Aihu Zhang

Functional magnetic resonance imaging (fMRI) is a commonly used technique to measure neural activation. Its application has been particularly important in identifying underlying neurodegenerative conditions such as Parkinson's, Alzheimer's, and Autism. Recent analysis of fMRI data models the brain as a graph and extracts features by graph neural networks (GN

Xiaoyu Bai, Fan Bai, Xiaofei Huo, Jia Ge

Radiotherapists require accurate registration of MR/CT images to effectively use information from both modalities. In a typical registration pipeline, rigid or affine transformations are applied to roughly align the fixed and moving images before proceeding with the deformation step. While recent learning-based methods have shown promising results in the rig

Sarenne Wallbridge, Peter Bell, Catherine Lai

Speech is a fundamental means of communication that can be seen to provide two channels for transmitting information: the lexical channel of which words are said, and the non-lexical channel of how they are spoken. Both channels shape listener expectations of upcoming communication; however, directly quantifying their relative effect on expectations is chall

Simon Leglaive, Léonie Borne, Efthymios Tzinis, Mostafa Sadeghi

Supervised speech enhancement models are trained using artificially generated mixtures of clean speech and noise signals, which may not match real-world recording conditions at test time. This mismatch can lead to poor performance if the test domain significantly differs from the synthetic training domain. This paper introduces the unsupervised domain adapta

Carlos Calderón, John Cotrina

We deal with the generalized Nash game proposed by Rosen, which is a game with strategy sets that are coupled across players through a shared constraint. A reduction to a classical game is shown, and as a consequence, Rosen's result can be deduced from the one given by Arrow and Debreu. We also establish necessary and sufficient conditions for a point to be

Junyao Pan

Let $(\mathcal{F},\mathcal{G})$ be a pair of families of $[n]$, where $[n]=\{1,2,...,n\}$. If $A\not\subset B$ and $B\not\subset A$ hold for all $A\in\mathcal{F}$ and $B\in\mathcal{G}$, then $(\mathcal{F},\mathcal{G})$ is called a Cross-Sperner pair. P. Frankl and Jian Wang introduced the extremal problem that $m(n)={\rm{max}}\{|\mathcal{I}(\mathcal{F},\math

Priyankur Chaudhuri, Omprokash Das

We show that if $\mathcal{F}$ is an algebraically integrable foliation on a $\mathbb{Q}$-factorial normal projective variety $X$, $ A, B \geq 0$ are $\mathbb{Q}$-divisors on $X$ with $A$ ample such that $(\mathcal{F}, B)$ is foliated dlt and $K_{\mathcal{F}}+ A+B$ is nef, then $K_{\mathcal{F}}+A+B$ is semiample. We also provide some applications of this and

Ying Feng, David P. Woodruff

We study streaming algorithms in the white-box adversarial stream model, where the internal state of the streaming algorithm is revealed to an adversary who adaptively generates the stream updates, but the algorithm obtains fresh randomness unknown to the adversary at each time step. We incorporate cryptographic assumptions to construct robust algorithms aga

Claudio B. Caporusso, Giuseppe Gonnella, Demian Levis

We study a model chiral fluid in two dimensions composed of Brownian disks interacting via a Lennard-Jones potential and a non-conservative transverse force, mimicking colloids spinning at a rate $\omega$. The system exhibits a phase separation between a chiral liquid and a dilute gas phase that can be characterized using a thermodynamic framework. We comput

Alexandru Kristály

In their seminal work, Cordero-Erausquin, Nazaret and Villani [Adv. Math., 2004] proved sharp Sobolev inequalities in Euclidean spaces via Optimal Mass Transportation, raising the question whether their approach is powerful enough to produce sharp Sobolev inequalities also on Riemannian manifolds. In this paper we affirmatively answer their question for Riem

Sw. Banerjee, A. Yu. Korchin, E. Richter-Was, Z. Was

Anomalous contributions to the electric and magnetic dipole moments of the $\tau$ lepton from new physics scenarios have brought renewed interest in the development of new charge-parity violating signatures in $\tau$-pair production at Belle II energies, and also at higher energies of the Large Hadron Collider and the Future Circular Collider. In this paper,

Sean Dewar, Georg Grasegger, Kaie Kubjas, Fatemeh Mohammadi

In this note we study the uniqueness problem for collections of pennies and marbles. More generally, consider a collection of unit $d$-spheres that may touch but not overlap. Given the existence of such a collection, one may analyse the contact graph of the collection. In particular we consider the uniqueness of the collection arising from the contact graph.

Christine Hegedues, Joao Pedro Dias Constantino, Laurits Dixen, Paolo Burelli

Game difficulty is a crucial aspect of game design, that can be directly influenced by tweaking game mechanics. Perceived difficulty can however also be influenced by simply altering the graphics to something more threatening. Here, we present a study with 12 participants playing 4 different minigames with either altered graphics or mechanics to make the gam

Roberto Montemanni, Mauro Dell'Amico, Andrea Corsini

We study last-mile delivery problems where trucks and drones collaborate to deliver goods to final customers. In particular, we focus on problem settings where either a single truck or a fleet with several homogeneous trucks work in parallel to drones, and drones have the capability of collaborating for delivering missions. This cooperative behaviour of the

Yen-Hsun Lin, Tsung-Han Tsai, Guey-Lin Lin, Henry Tsz-King Wong

Supernova neutrino boosted dark matter (SN$\nu$ BDM) and its afterglow effect have been shown to be a promising signature for beyond Standard Model (bSM) physics. The time-evolution feature of SN$\nu$ BDM allows for %the possibly direct inference of DM mass $m_\chi$, and results in significant background suppression with improving sensitivity. This paper ext

Lilia Correa Magnus, Britton D. Smith, Sadegh Khochfar, Brian W. O'Shea

We present a study of the co-evolution of a population of primordial star-forming minihalos at Cosmic Dawn. In this study, we highlight the influence of individual Population III stars on the ability of nearby minihalos to form sufficient molecular hydrogen to undergo star formation. In the absence of radiation, we find the minimum halo mass required to brin

Anna Pachoł, Aneta Wojnar

We investigate the application of an equation of state that incorporates corrections derived from the Snyder model (and the Generalized Uncertainty Principle) to describe the behavior of matter in a low-mass star. Remarkably, the resulting equations exhibit striking similarities to those arising from modified Einstein gravity theories. By modeling matter wit

Federico Malizia, Santiago Lamata-Otín, Mattia Frasca, Vito Latora

Recent studies have shown that novel collective behaviors emerge in complex systems due to the presence of higher-order interactions. However, how the collective behavior of a system is influenced by the microscopic organization of its higher-order interactions remains still unexplored. In this Letter, we introduce a way to quantify the overlap among the hyp

Thomas Volden, Djordje Grbic, Paolo Burelli

This paper focuses on procedurally generating rules and communicating them to players to adjust the difficulty. This is part of a larger project to collect and adapt games in educational games for young children using a digital puzzle game designed for kindergarten. A genetic algorithm is used together with a difficulty measure to find a target number of sol

Christian Komusiewicz, Jannik Schestag

In the Generalized Noah's Ark Problem, one is given a phylogenetic tree on a set of species X and a set of conservation projects for each species. Each project comes with a cost and raises the survival probability of the corresponding species. The aim is to select a conservation project for each species such that the total cost of the selected projects does

Shrinivas Chimmalgi, Andrej Rode, Luca Schmid, Laurent Schmalen

The blind phase search (BPS) algorithm for carrier phase estimation is known to have sub-optimal performance for probabilistically shaped constellations. We present a belief propagation based approximate maximum a posteriori carrier phase estimator and compare its performance with the standard and an improved BPS algorithm.

Pyotr N. Ivanshin, Elena A. Shirokova

The method of boundary curve reparametrization is applied to construction of the approximate analytical conformal mapping of the unit disk onto an arbitrary given finite domain with a boundary smooth at every point but fininte number of acute angle points. The method is based on both the Fredholm equation solution and spline-interpolation. This approach cons

Afsana Khan, Marijn ten Thij, Frank Thuijsman, Anna Wilbik

Vertical federated learning (VFL) is a promising approach for collaboratively training machine learning models using private data partitioned vertically across different parties. Ideally in a VFL setting, the active party (party possessing features of samples with labels) benefits by improving its machine learning model through collaboration with some passiv

Carsten Güttler, Martin Rose, Holger Sierks, Wolfgang Macher

The diffusion of gas through porous material is important to understand the physical processes underlying cometary activity. We study the diffusion of a rarefied gas (Knudsen regime) through a packed bed of monodisperse spheres via experiments and numerical modelling, providing an absolute value of the diffusion coefficient and compare it to published analyt

Stephan Baier, Sayantan Roy

In this note, we give a summary of the article ``The distribution of prime ideals of imaginary quadratic fields'' by G. Harman, A. Kumchev and P. A. Lewis and establish analogous results for real quadratic fields based on the same method.

Gregory Sech, Paolo Soleni, Wouter B. Verschoof-van der Vaart, Žiga Kokalj

When applying deep learning to remote sensing data in archaeological research, a notable obstacle is the limited availability of suitable datasets for training models. The application of transfer learning is frequently employed to mitigate this drawback. However, there is still a need to explore its effectiveness when applied across different archaeological

Valentina Nigro, Roberta Angelini, Stephen King, Silvia Franco

Dynamic Light Scattering (DLS) and Small-Angle Neutron Scattering (SANS) are two key tools with which to probe the dynamic and static structure factor, respectively, in soft matter. Usually DLS and SANS measurements are performed separately, in different laboratories, on different samples and at different times. However, this methodology has particular disad

Milan Hladík, David Hartman

We deal with linear programming problems involving absolute values in their formulations, so that they are no more expressible as standard linear programs. The presence of absolute values causes the problems to be nonconvex and nonsmooth, so hard to solve. In this paper, we study fundamental properties on the topology and the geometric shape of the solution

Stefano Duranti, Sören Wengerowsky, Leo Feldmann, Alessandro Seri

We report on the high-efficiency storage and retrieval of weak coherent optical pulses and photonic qubits in a cavity-enhanced solid-state quantum memory. By using an atomic frequency comb (AFC) memory in a $Pr^{3+}:Y_2 SO_5$ crystal embedded in a low-finesse impedance-matched cavity, we stored weak coherent pulses at the single photon level with up to 62%

Tamás Szidarovszky

The consequences of enforcing permutational symmetry, as required by the Pauli principle (spin-statistical theorem), on the state space of molecular ensembles interacting with the quantized radiation mode of a cavity are discussed. The Pauli-allowed collective states are obtained by means of group theory, i.e., by projecting the state space onto the appropri

Leonardo Cianfanelli, Giacomo Como

We study the asymptotic stability of the logit evolutionary dynamics in population games, possibly with multiple heterogenous populations. For general population games, we prove that, on the one hand, strict Nash equilibria are asymptotically stable under the logit dynamics for low enough noise levels, on the other hand, a globally exponentially stable logit

Dean Ninalga

Recent work suggests that interpolating between the weights of two specialized language models can transfer knowledge between tasks in a way that multi-task learning cannot. However, very few have explored interpolation between more than two models, where each has a distinct knowledge base. In this paper, we introduce Derivative Free Weight-space Ensembling

Ben Chen, Caihua Xiong, Quanlin Li, Zhonghua Wan

Accurate detection and localization of X-corner on both planar and non-planar patterns is a core step in robotics and machine vision. However, previous works could not make a good balance between accuracy and robustness, which are both crucial criteria to evaluate the detectors performance. To address this problem, in this paper we present a novel detection

Katsushi Ito, Jingjing Yang

We apply the exact WKB analysis to a couple of one-dimensional Schroedinger-type equations reduced from the Stark effect of hydrogen in a uniform electric field. By introducing Langer's modification and incorporating the Stokes graphs, we prove the exactness of the Bohr-Sommerfeld quantization conditions for the Borel-resummed quantum WKB periods in the spec

Fleurianne Bertrand, Vitoriano Ruas

Several physical problems modeled by second-order elliptic equations can be efficiently solved using mixed finite elements of the Raviart-Thomas family RTk for N-simplexes, introduced in the seventies. In case Neumann conditions are prescribed on a curvilinear boundary, the normal component of the flux variable should preferably not take up values at nodes s

Zhaobing Fan, Jicheng Geng, Shaolong Han

We construct a unique braid group action on modified $q$-Weyl algebra $\mathbf A_q(S)$. Under this action, we give a realization of the braid group action on quasi-split $\imath$quantum groups $^{\imath}\mathbf U(S)$ of type $\mathrm{AIII}$. Furthermore, we directly construct a unique braid group action on polynomial ring $\mathbb P$ which is compatible with

Daegun Yoon, Sangyoon Oh

Gradient sparsification is a widely adopted solution for reducing the excessive communication traffic in distributed deep learning. However, most existing gradient sparsifiers have relatively poor scalability because of considerable computational cost of gradient selection and/or increased communication traffic owing to gradient build-up. To address these ch

Álvaro Cartea, Fayçal Drissi, Marcello Monga

Automated market makers (AMMs) are a new prototype of decentralised exchanges which are revolutionising market interactions. The majority of AMMs are constant product markets (CPMs) where exchange rates are set by a trading function. This work studies optimal trading and statistical arbitrage in CPMs where balancing exchange rate risk and execution costs is

Patrick Vincent N. Lubenia, Eduardo R. Mendoza, Angelyn R. Lao

Several studies have developed dynamical models to understand the underlying mechanisms of insulin signaling, a signaling cascade that leads to the translocation of glucose, the human body's main source of energy. Fortunately, reaction network analysis allows us to extract properties of dynamical systems without depending on their model parameter values. Thi

Galina L. Klimchitskaya, Vladimir M. Mostepanenko

The Casimir-Polder force acting on atoms and nanoparticles spaced at large separations from real graphene sheet possessing some energy gap and chemical potential is investigated in the framework of the Lifshitz theory. The reflection coefficients expressed via the polarization tensor of graphene found based on the first principles of thermal quantum field th

Sutapa Mandal, Snehashish Sarkar, Pinaki Pal

We investigate the effect of an external horizontal magnetic field on the K\"{u}ppers-Lortz instability (KLI) in rotating Rayleigh-B\'{e}nard convection of Boussinesq fluids using weakly nonlinear theory along with linear theory. By KLI, we mean the instability where the two-dimensional roll solutions of the system occurring at the onset of convection become

Shira Haber, Michal Leskes

The increasing need for portable and large-scale energy storage systems requires development of new, long lasting and highly efficient battery systems. Solid state NMR spectroscopy has emerged as an excellent method for characterizing battery materials. Yet, it is limited when it comes to probing thin interfacial layers which play a central role in the perfo

Anastasios N. Zachos

In this paper, we prove that D'Alembert-Lagrange principle for point masses using Lagrange-Mach's mechanical construction yields a weighted balancing condition of unit vectors in $\mathbb{E}^{3}.$

Jia-Qi Zhang, Hao-Bin Duan, Jun-Long Chen, Ariel Shamir

The task of lane detection has garnered considerable attention in the field of autonomous driving due to its complexity. Lanes can present difficulties for detection, as they can be narrow, fragmented, and often obscured by heavy traffic. However, it has been observed that the lanes have a geometrical structure that resembles a straight line, leading to impr

Gamze İslamoğlu, Moritz Scherer, Gianna Paulin, Tim Fischer

Transformer networks have emerged as the state-of-the-art approach for natural language processing tasks and are gaining popularity in other domains such as computer vision and audio processing. However, the efficient hardware acceleration of transformer models poses new challenges due to their high arithmetic intensities, large memory requirements, and comp

Feibo Jiang, Yubo Peng, Li Dong, Kezhi Wang

Semantic communication (SC) is an emerging intelligent paradigm, offering solutions for various future applications like metaverse, mixed reality, and the Internet of Everything. However, in current SC systems, the construction of the knowledge base (KB) faces several issues, including limited knowledge representation, frequent knowledge updates, and insecur

Abhinav Benagi, Dhanyatha Narayan, Charith Rage, A Sushmitha

The main backbone of our Artificial Eye model is the Raspberry pi3 which is connected to the webcam ,ultrasonic proximity sensor, speaker and we also run all our software models i.e object detection, Optical Character recognition, google text to speech conversion and the Mycroft voice assistance model. At first the ultrasonic proximity sensor will be measuri

Marvin Lücke, Stefanie Winkelmann, Jobst Heitzig, Nora Molkenthin

Collective variables (CVs) are low-dimensional projections of high-dimensional system states. They are used to gain insights into complex emergent dynamical behaviors of processes on networks. The relation between CVs and network measures is not well understood and its derivation typically requires detailed knowledge of both the dynamical system and the netw

Yong Xu, Fan Zhang, Albert Fert, Henri-Yves Jaffres

Orbitronics is based on the use of orbit currents as information carriers. Up to now, orbit currents were created from the conversion of charge or spin currents, and inversely, they could be converted back to charge or spin currents. Here we demonstrate that orbit currents can also be generated by femtosecond light pulses on Ni. In multilayers associating Ni

Paulo J. Cavalcanti, John H. Selby, Ana Belén Sainz

In this work we show that the set of non-signalling resources of a locally-tomographic generalised probabilistic theory (GPT), such as quantum and classical theory, coincides with its set of GPT-common-cause realizable resources, where the common causes come from an associated GPT. From a causal perspective, this result provides a reason for, in the study of

Zhengdao Li, Wei Li, Kai Hwang

Traffic flow forecasting is a highly challenging task due to the dynamic spatial-temporal road conditions. Graph neural networks (GNN) has been widely applied in this task. However, most of these GNNs ignore the effects of time-varying road conditions due to the fixed range of the convolution receptive field. In this paper, we propose a novel Adaptive Graph

Vishwanath R. Singireddy, Manjanna Basappa, N. R. Aravind

Suppose we are given a set $\cal B$ of blue points and a set $\cal R$ of red points, all lying above a horizontal line $\ell$, in the plane. Let the weight of a given point $p_i\in {\cal B}\cup{\cal R}$ be $w_i>0$ if $p_i\in {\cal B}$ and $w_i<0$ if $p_i\in {\cal R}$, $|{\cal B}\cup{\cal R}|=n$, and $d^0$($=d\setminus\partial d$) be the interior of any geome

Zhongjie Shi, Zhan Yu, Ding-Xuan Zhou

In this paper, we aim at establishing an approximation theory and a learning theory of distribution regression via a fully connected neural network (FNN). In contrast to the classical regression methods, the input variables of distribution regression are probability measures. Then we often need to perform a second-stage sampling process to approximate the ac

Seungyong Moon, Junyoung Yeom, Bumsoo Park, Hyun Oh Song

Discovering achievements with a hierarchical structure in procedurally generated environments presents a significant challenge. This requires an agent to possess a broad range of abilities, including generalization and long-term reasoning. Many prior methods have been built upon model-based or hierarchical approaches, with the belief that an explicit module

Vinod Kumar, Afreen, K. A. Sree Raj, Pratap mane

Nonlinear optical phenomena play a critical role in understanding microscopic light-matter interactions and have far-reaching applications across various fields, such as biosensing, quantum information, optical switching, and all-optical data processing. Most of these applications require materials with high third-order absorptive and refractive optical nonl

Guy Chanfray, Magda Ericson, Marco Martini

We study the role of short-range correlations, as well as pion and rho loops governing long-range RPA correlations, in nuclear matter properties and response functions. We use an adapted formulation of the Brueckner G-matrix approach to generate a pair correlation function satisfying the Beg--Agassi--Gal theorem, providing a natural cutoff to the loop integr

Vineeth Chintala

We show that an idempotent lies in the center if it commutes with the other idempotents in the ring. Next, we introduce a partition of the set of idempotents and show that the automorphisms of the ring act transitively on each equivalence class.

Benedetta Ferrario, Margherita Zanella

We establish the uniqueness and the asymptotic stability of the invariant measure for the two dimensional Navier Stokes equations driven by a multiplicative noise which is either bounded or with a sublinear or a linear growth. We work on an effectively elliptic setting, that is we require that the range of the covariance operator contains the unstable direct

Armin Nurkanović, Anton Pozharskiy, Jonathan Frey, Moritz Diehl

This paper develops high-accuracy methods for numerically solving optimal control problems subject to nonsmooth differential equations with set-valued step functions. A notable subclass of these systems are Filippov systems. The set-valued step functions are here written as the solution map of a linear program. Using the optimality conditions of this problem

Florian Niedermann, Martin S. Sloth

New Early Dark Energy introduces a new phase of dark energy that decays in a fast-triggered phase transition around matter-radiation equality. The presence of a trigger mechanism sets it apart from other early dark energy models. Here, we will argue that New Early Dark Energy offers a simple and natural framework to extend $\Lambda$CDM while also providing a

Erik Daniel, Marcel Ebert, Florian Tschorsch

IPFS is a content-addressed decentralized peer-to-peer data network, using the Bitswap protocol for exchanging data. The data exchange leaks the information to all neighbors, compromising a user's privacy. This paper investigates the suitability of forwarding with source obfuscation techniques for improving the privacy of the Bitswap protocol. The usage of f

Xingyu Wang, Chang-Han Rhee

This paper introduces novel frameworks for large deviations and metastability analysis in heavy-tailed stochastic dynamical systems. We develop and apply these frameworks within the context of stochastic difference equation $X^\eta_{j+1}(x) = X^\eta_{j}(x) + \eta a\big( X^\eta_{j}(x)\big) + \eta \sigma\big( X^\eta_{j}(x)\big)Z_{j+1}$ and its variation with t

Georg M. von Hippel

The problem of having to reconstruct the decay rates and corresponding amplitudes of the single-exponential components of a noisy multi-exponential signal is common in many other areas of physics and engineering besides lattice field theory, and it can be helpful to study the methods devised and used for that purpose in those contexts in order to get a bette

Stefano Menchiari

Stellar clusters (SC) are fundamental building blocks of galaxies and are among the most studied astronomical objects in the Cosmos. The recent association of diffuse $\gamma$-ray emission detected by different experiments with a dozen young SCs suggests the presence of some process able to accelerate particles at least up to hundreds of TeV. In this Ph.D. t

Yi Wen, Siwei Wang, Qing Liao, Weixuan Liang

Multi-view clustering (MVC), which effectively fuses information from multiple views for better performance, has received increasing attention. Most existing MVC methods assume that multi-view data are fully paired, which means that the mappings of all corresponding samples between views are pre-defined or given in advance. However, the data correspondence i

Jan Brederecke

Freezing of Gait (FOG) is a common motor symptom in patients with Parkinson's disease (PD). During episodes of FOG, patients suddenly lose their ability to stride as intended. Patient-worn accelerometers can capture information on the patient's movement during these episodes and machine learning algorithms can potentially classify this data. The combination

Rafael S. González D'León, Alejandro H. Morales, Eva Philippe, Daniel Tamayo Jiménez

Ceballos and Pons introduced the $s$-weak order on $s$-decreasing trees, for any weak composition $s$. They proved that it has a lattice structure and further conjectured that it can be realized as the $1$-skeleton of a polyhedral subdivision of a polytope. We answer their conjecture in the case where $s$ is a strict composition by providing three geometric

Francesco Cordoni, Alessio Sancetta

A model among many may only be best under certain states of the world. Switching from a model to another can also be costly. Finding a procedure to dynamically choose a model in these circumstances requires to solve a complex estimation procedure and a dynamic programming problem. A Reinforcement learning algorithm is used to approximate and estimate from th

Johanna Jakob

Let $k\in\mathbb{N}_0\cup\{\infty\}$. According to Whitney's extension theorem, each real-valued Whitney $k$-Jet on a closed subset $A\subseteq\mathbb{R}^n$ can be extended to a $C^k$-function on $\mathbb{R}^n$. Based on Whitney's original work, we prove analogous results for jets and functions with values in a real Hausdorff locally convex topological vecto

N. N. Achasov, G. N. Shestakov

Using the result of the VES Collaboration for $Br(J/\psi\to\gamma f_0(1710))$, we estimate the absolute branching fractions for the $f_0(1710)$ decays into $\pi\pi$, $K\bar K$, $\eta\eta$, $\omega\omega$, and $\omega\phi$. In addition, we estimate $Br(\psi(2S)\to\gamma f_0(1710))\approx3.5\times10^{-5}$ and $Br(\Upsilon(1S)\to\gamma f_0(1710))\approx1\times1

Maximilian J. Grill, Jonas Biehler, Karl-Robert Wichmann, David Rudlstorfer

The big crux with drug delivery to human lungs is that the delivered dose at the local site of action is unpredictable and very difficult to measure, even a posteriori. It is highly subject-specific as it depends on lung morphology, disease, breathing, and aerosol characteristics. Given these challenges, computational approaches have shown potential, but hav

Stefano Almi, Ulisse Stefanelli

Progresses in additive manufacturing technologies allow the realization of finely graded microstructured materials with tunable mechanical properties. This paves the way to a wealth of innovative applications, calling for the combined design of the macroscopic mechanical piece and its underlying microstructure. In this context, we investigate a topology opti

A. Mucciarelli, A. Minelli, C. Lardo, D. Massari

The Small Magellanic Cloud (SMC) is the host of a rich system of globular clusters (GCs) that span a wide age range. The chemical composition of the SMC clusters is still poorly understood, despite their significance to chemical evolution studies. Here, we provide the first detailed chemical study of evolved giants in three distinct clusters, NGC 121 (10.5 G

Josephine Evans, Havva Yoldaş

We study the long-time behaviour of a run and tumble model which is a kinetic-transport equation describing bacterial movement under the effect of a chemical stimulus. The experiments suggest that the non-uniform tumbling kernels are physically relevant ones as opposed to the uniform tumbling kernel which is widely considered in the literature to reduce the

Christian Kuehn, Jan Mölter

Moment systems arise in a wide range of contexts and applications, e.g. in network modeling of complex systems. Since moment systems consist of a high or even infinite number of coupled equations, an indispensable step in obtaining a low-dimensional representation that is amenable to further analysis is, in many cases, to select a moment closure. A moment cl

Ben Wooding, Abolfazl Lavaei, Sadegh Soudjani

This work is concerned with an assume-guarantee approach to compositionally control a New England 39-bus Test System (NETS). The proposed scheme is based on the new notion of robust simulation functions with disturbance refinement alongside the composition of multiple subsystems to tackle the difficulties associated with scalability, also known as the curse

Jaemyung Lee, Kyeongtak Han, Jaehoon Kim, Hasun Yu

Consistency and reliability are crucial for conducting AI research. Many famous research fields, such as object detection, have been compared and validated with solid benchmark frameworks. After AlphaFold2, the protein folding task has entered a new phase, and many methods are proposed based on the component of AlphaFold2. The importance of a unified researc

Gioni Mexi, Mathieu Besançon, Suresh Bolusani, Antonia Chmiela

We introduce Scylla, a primal heuristic for mixed-integer optimization problems. It exploits approximate solves of the Linear Programming relaxations through the matrix-free Primal-Dual Hybrid Gradient algorithm with specialized termination criteria, and derives integer-feasible solutions via fix-and-propagate procedures and feasibility-pump-like updates to

Zelun Zhang, Xue Pan

The AllInOne training paradigm squeezes a wide range of tasks into a unified model in a multi-task learning manner. However, optimization in multi-task learning is more challenge than single-task learning, as the gradient norm from different tasks may vary greatly, making the backbone overly biased towards one specific task. To address this issue, we propose

Christian F. Nielsen, Robert Holtzapple, Mads M. Lund, Jeppe H. Surrow

In this paper, we present experimental results and numerical simulations of trident production, $e^-\rightarrow e^-e^+e^-$, in a strong electromagnetic field. The experiment was conducted at CERN for the purpose of probing the strong-field parameter $\chi$ up to 2.4, using a 200 GeV electron beam penetrating a 400 $\mu$m thick germanium crystal oriented alon

Dominik K. Klein, Fabian J. Roth, Iman Valizadeh, Oliver Weeger

In the present work, neural networks are applied to formulate parametrised hyperelastic constitutive models. The models fulfill all common mechanical conditions of hyperelasticity by construction. In particular, partially input-convex neural network (pICNN) architectures are applied based on feed-forward neural networks. Receiving two different sets of input

Maykoll A. Reyes

To unify the standard model of particle physics and general relativity, we may require a quantum description of gravity, which will change our notion of spacetime at very high energies. In this dissertation we explore possible traces of new physics beyond special relativity, using the propagation of high energy astroparticles. For this purpose, the two ways

Eric Grunsky, Michael Greenacre, Bruce Kjarsgaard

Geochemical data are compositional in nature and are subject to the problems typically associated with data that are restricted to the real non-negative number space with constant-sum constraint, that is, the simplex. Geochemistry can be considered a proxy for mineralogy, comprised of atomically ordered structures that define the placement and abundance of e

Konrad Heidler, Lichao Mou, Erik Loebel, Mirko Scheinert

Choosing how to encode a real-world problem as a machine learning task is an important design decision in machine learning. The task of glacier calving front modeling has often been approached as a semantic segmentation task. Recent studies have shown that combining segmentation with edge detection can improve the accuracy of calving front detectors. Buildin

Alain Durmus, Samuel Gruffaz, Miika Kailas, Eero Saksman

There is substantial empirical evidence about the success of dynamic implementations of Hamiltonian Monte Carlo (HMC), such as the No U-Turn Sampler (NUTS), in many challenging inference problems but theoretical results about their behavior are scarce. The aim of this paper is to fill this gap. More precisely, we consider a general class of MCMC algorithms w

Shiyong Zeng, Ping Zhu, Haijun Ren

Recent experiments have demonstrated the species dependence of the impurity poloidal drift direction along with the magnetic island rotation in the poloidal plane. Our resistive MHD simulations have reproduced such a dependence of the impurity poloidal flow, which is found mainly determined by a local plasmoid formation due to the impurity injection. The syn

Daniel Scheffler, Sebastian Beckert, Helena Reichlova, Thomas G. Woodcock

$\tau$-MnAl is interesting for spintronic applications as a ferromagnet with perpendicular magnetic anisotropy due to its high uniaxial magnetocrystalline anisotropy. Here we report on the anomalous Nernst effect of sputter deposited $\tau$-MnAl thin films. We demonstrate a robust anomalous Nernst effect at temperatures of 200 K and 300 K with a hysteresis s

Cataldo Godano, Giuseppe Petrillo, Eugenio Lippiello

The evaluation of the $b$ value of the Gutenberg-Richter (GR) law, for a sample composed of $n$ earthquakes, presents a systematic positive bias $\delta b$ which is proportional to $1/n$, as already observed by Ogata \& Yamashina (1986). In this study we show how to incorporate in $\delta b$ the bias introduced by deviations from the GR law. More precisely w

Sourabh Patil, Gaomin Tang, Wolfgang Belzig

Conventional two-dimensional superconductivity is destroyed when the critical in-plane magnetic field exceeds the so-called Pauli limit. Some monolayer transition-metal dichalcogenides lack inversion symmetry and the strong spin-orbit coupling leads to a valley-dependent Zeeman-like spin splitting. The resulting spin-valley locking lifts the valley degenerac

Jesús D. Cifuentes, Philip Y. Mai, Frédéric Schlattner, H. Ekmel Ercan

The boom of semiconductor quantum computing platforms created a demand for computer-aided design and fabrication of quantum devices. Path integral Monte Carlo (PIMC) can have an important role in this effort because it intrinsically integrates strong quantum correlations that often appear in these multi-electron systems. In this paper we present a PIMC algor