April 2023 arXiv papers — page 71

A. de Giorgi, L. Merlo, S. Pokorski

In this short talk, we present a renormalizable model that can i) generate neutrino masses via a low-scale seesaw mechanism and ii) solve the long-standing $(g-2)_\mu$ and the more recent CDF II $M_W$-anomalies. This is minimally achieved by introducing two sterile neutrinos and a single electroweak-doublet vector-like lepton, with masses $< 2$ TeV. We focus

Ilijas Farah, Saeed Ghasemi

Tensoring with type I algebras preserves elementary equivalence in the category of tracial von Neumann algebras. The proof involves a novel and general Feferman--Vaught-type theorem for direct integrals of metric structures.

Katya Gozman, Eric F. Bell, Adam Smercina, Paul Price

It is not yet settled how the combination of secular processes and merging gives rise to the bulges and pseudobulges of galaxies. The nearby ($D\sim$ 4.2 Mpc) disk galaxy M94 (NGC 4736) has the largest pseudobulge in the local universe, and offers a unique opportunity for investigating the role of merging in the formation of its pseudobulge. We present a fir

Khushhall Chandra Mahajan, Aditya Palnitkar, Ameya Raul, Brad Schumitsch

Many recommendation systems rely on point-wise models, which score items individually. However, point-wise models generating scores for a video are unable to account for other videos being recommended in a query. Due to this, diversity has to be introduced through the application of heuristic-based rules, which are not able to capture user preferences, or ma

Marc-Philipp Funk, Nassim Chloe Eghtebas

Having a computer do the work for you has become more and more common over time. But in the entertainment area, where a human is a creator, we want to avoid having too much influence on technology. On the other hand, inspiration is still important; we developed a virtual conductor that can generate an emotionally associated interpretation of known music work

Maher Berzig

We introduce the concept of $b$-suprametric spaces and establish a fixed point result for mappings satisfying a nonlinear contraction in such spaces. The obtained result generalizes a fixed point theorem of Czerwik and a recent result of the author.

Shuwei Jin, Kunlun Dai, Joris Verstraten, Maxime Dixmerias

Atom-based quantum simulators have had tremendous success in tackling challenging quantum many-body problems, owing to the precise and dynamical control that they provide over the systems' parameters. They are, however, often optimized to address a specific type of problems. Here, we present the design and implementation of a $^6$Li-based quantum gas platfor

Chengzhi Wu, Junwei Zheng, Julius Pfrommer, Jürgen Beyerer

Modeling a 3D volumetric shape as an assembly of decomposed shape parts is much more challenging, but semantically more valuable than direct reconstruction from a full shape representation. The neural network needs to implicitly learn part relations coherently, which is typically performed by dedicated network layers that can generate transformation matrices

Dirk Bergemann, Alessandro Bonatti, Nicholas Wu

We present a model of digital advertising with three key features: (i) advertisers can reach consumers on and off a platform, (ii) additional data enhances the value of advertiser-consumer matches, and (iii) bidding follows auction-like mechanisms. We contrast data-augmented auctions, which leverage the platform's data advantage to improve match quality, and

Václav Hanžl, Adléta Hanžlová

Labeling speech down to the identity and time boundaries of phones is a labor-intensive part of phonetic research. To simplify this work, we created a free open-source tool generating phone sequences from Czech text and time-aligning them with audio. Low architecture complexity makes the design approachable for students of phonetics. Acoustic model ReLU NN w

Lawrence Ein, Wenbo Niu

We study fundamental forms of algebraic varieties using the sheaves of principal parts of line bundles and establish a vanishing theorem for any order fundamental forms. We also give connection of fundamental forms with the higher order Gauss map and higher order tangent varieties.

Anubhab Baksi, Ahmed Ibrahim Samir Khalil, Anupam Chattopadhyay

In recent times, the research works relating to smart traffic infrastructure have gained serious attention. As a result, research has been carried out in multiple directions to ensure that such infrastructure can improve upon our existing (mostly) human-controlled traffic infrastructure, without violating the safety margins. For this reason, cyber security i

Yi-feng Yang

One parameter scaling of the Hall coefficient of cuprates has been well known for almost three decades, but still lacks a simple mathematical expression. Motivated by the recent phenomenological prediction of the universal scaling of the thermal Hall conductivity, we propose here a simple scaling function for the Hall coefficient in cuprates that varies expo

Jeongin Moon, David Valcin, Michael Rashkovetskyi, Christoph Saulder

We present the first detection of the baryon acoustic oscillations (BAO) signal obtained using unblinded data collected during the initial two months of operations of the Stage-IV ground-based Dark Energy Spectroscopic Instrument (DESI). From a selected sample of 261,291 Luminous Red Galaxies spanning the redshift interval 0.4 < z < 1.1 and covering 1651 squ

Kazi Amit Hasan, Marcos Macedo, Yuan Tian, Bram Adams

The pull-based development is widely adopted in modern open-source software (OSS) projects, where developers propose changes to the codebase by submitting a pull request (PR). However, due to many reasons, PRs in OSS projects frequently experience delays across their lifespan, including prolonged waiting times for the first response. Such delays may signific

Ketankumar Jadav, Sukanta Panda, Abbas Altafhussain Tinwala

It is known that Vilkovisky-DeWitt's effective action is gauge invariant off-shell and independent of quantum field parametrization. In this work, we perform the calculation of the divergences in two-loop Vilkovisky-DeWitt's effective action for the theory of a massive scalar field minimally coupled to gravity. We quantize both gravity and scalar field aroun

Abhimanyu Das, Weihao Kong, Andrew Leach, Shaan Mathur

Recent work has shown that simple linear models can outperform several Transformer based approaches in long term time-series forecasting. Motivated by this, we propose a Multi-layer Perceptron (MLP) based encoder-decoder model, Time-series Dense Encoder (TiDE), for long-term time-series forecasting that enjoys the simplicity and speed of linear models while

O. W. Sandvik, A. M. Müller, H. W. Ånes, M. Zahn

Mechanical pressure controls the structural, electric, and magnetic order in solid state systems, allowing to tailor and improve their physical properties. A well-established example is ferroelastic ferroelectrics, where the coupling between pressure and the primary symmetry breaking order parameter enables hysteretic switching of the strain state and ferroe

Masahiro Kadosawa, Masaaki Nakamura, Yukinori Ohta, Satoshi Nishimoto

We estimate phase boundaries of four ordered and two spin-liquid phases for the spin-$\frac{1}{2}$ Kitaev-Heisenberg (KH) model using four kinds of relatively-small clusters, based on the second derivative of ground-state energy. The estimated values are compared between the clusters as well as the previous iPEPS results. We thus find that the boundaries can

Alexei A. Deriglazov

We have revised the problem of the motion of a heavy symmetric top. When formulating equations of the Lagrange top with the diagonal inertia tensor, the potential energy has more complicated form as compared with that assumed in the literature on dynamics of a rotating body. This implies the corresponding improvements in equations of motion. Using the Liouvi

Lorenzo Ferreri, Gianmaria Verzini

We consider a shape optimization problem related to the persistence threshold for a biological species, the unknown shape corresponding to the zone of the habitat which is favorable to the population. Analytically, this translates in the minimization of a weighted eigenvalue of the Dirichlet Laplacian, with respect to a bang-bang indefinite weight. For such

Charlie Carlson, Zackary Jorquera, Alexandra Kolla, Steven Kordonowy

We compare the performance of a quantum local algorithm to a similar classical counterpart on a well-established combinatorial optimization problem LocalMaxCut. We show that a popular quantum algorithm first discovered by Farhi, Goldstone, and Gutmannn [1] called the quantum optimization approximation algorithm (QAOA) has a computational advantage over compa

Jack A. Hall, Tim C. D. Lucas

Disaggregation modelling is a method of predicting disease risk at high resolution using aggregated response data. High resolution disease mapping is an important public health tool to aid the optimisation of resources, and is commonly used in assisting responses to diseases such as malaria. Current disaggregation regression methods are slow, inflexible, and

Akira Dohi, Emanuele Greco, Shigehiro Nagataki, Masaomi Ono

Observations collected with the Atacama Large Millimeter/submillimeter Array (ALMA) and analysis of broadband X-ray spectra have recently suggested the presence of a central compact object (CCO) in SN 1987A. However, no direct evidence of the CCO has been found yet. Here we analyze Chandra X-ray observations of SN 1987A collected in 2007 and 2018, and synthe

Martin Kalck

We observe that there exists an associative finite dimensional $\mathbb{C}$-algebra $A$ of finite global dimension, such that the bounded derived category $D^b(A)$ of finite dimensional $A$-modules admits an admissible subcategory $\mathcal{P}$ with vanishing Grothendieck group $K_0(\mathcal{P})$. In other words, $\mathcal{P} \subseteq D^b(A)$ is a phantom.

J. Varela, D. A. Spong, Y. Todo, L. Garcia

The aim of the present study is to analyze the saturation regime of the Toroidal Alfven Eigenmodes (TAE) in the LHD plasma, particularly the MHD burst. The linear and nonlinear evolution of the TAEs are simulated by the FAR3d code that uses a reduced MHD model for the thermal plasma coupled with a gyrofluid model for the energetic particles (EP) species. The

Vitaly Gorelov, Lucia Reining, Matteo Gatti

Excitonic effects due to the correlation of electrons and holes in excited states of matter dominate the optical spectra of many interesting materials. They are usually studied in the long-wavelength limit. Here we investigate excitons at non-vanishing momentum transfer, corresponding to shorter wavelengths. We calculate the exciton dispersion in the prototy

Karin Erdmann, Adam Hajduk, Adam Skowyrski

In this paper we are concerned with the structure of tame symmetric algebras of period four (TSP4 algebras, for short). We will mostly focus on the case when the Gabriel quiver of $A$ is biserial, i.e. there are at most two arrows ending and at most two arrows starting at each vertex, but some of the results can be easily extended to the general case. This s

Arman Tekinalp, Noel Naughton, Seung-Hyun Kim, Udit Halder

Muscular hydrostats, such as octopus arms or elephant trunks, lack bones entirely, endowing them with exceptional dexterity and reconfigurability. Key to their unmatched ability to control nearly infinite degrees of freedom is the architecture into which muscle fibers are weaved. Their arrangement is, effectively, the instantiation of a sophisticated mechani

J. Varela, J. Huang, D. A. Spong, J. Chen

The aim of this study is to analyze the stability of Alfven Eigenmodes (AE) in the China Fusion Engineering Test Reactor (CFETR) plasma for steady state operations. The analysis is done using the gyro-fluid code FAR3d including the effect of the acoustic modes, EP Finite Larmor radius damping effects and multiple energetic particle populations. Two high polo

Alexander Warnecke, Julian Speith, Jan-Niklas Möller, Konrad Rieck

Backdoors pose a serious threat to machine learning, as they can compromise the integrity of security-critical systems, such as self-driving cars. While different defenses have been proposed to address this threat, they all rely on the assumption that the hardware on which the learning models are executed during inference is trusted. In this paper, we challe

Bartosz Bednarczyk, Julien Grange

Order-invariant first-order logic is an extension of first-order logic FO where formulae can make use of a linear order on the structures, under the proviso that they are order-invariant, i.e. that their truth value is the same for all linear orders. We continue the study of the two-variable fragment of order-invariant first-order logic initiated by Zeume an

Matt Booth, Andrey Lazarev

We construct a monoidal model structure on the category of all curved coalgebras and show that it is Quillen equivalent, via the extended bar-cobar adjunction, to another model structure we construct on the category of curved algebras. When the coalgebras under consideration are conilpotent and the algebras are dg, i.e. uncurved, this corresponds to the ordi

Siyuan Li, Tobias Fischer, Lei Ke, Henghui Ding

The ability to recognize, localize and track dynamic objects in a scene is fundamental to many real-world applications, such as self-driving and robotic systems. Yet, traditional multiple object tracking (MOT) benchmarks rely only on a few object categories that hardly represent the multitude of possible objects that are encountered in the real world. This l

Zhenghuan Gao, Xi-Nan Ma, Dekai Zhang

In this paper, we consider the homogeneous complex k-Hessian equation in $\Omega\backslash\{0\}$. We prove the existence and uniqueness of the $C^{1,\alpha}$ solution by constructing approximating solutions. The key point for us is to construct the subsolution for approximating problem and establish uniform gradient estimates and complex Hessian estimates wh

Manuel Meyer, Katharina Isleif, Friederike Januschek, Axel Lindner

Axions and axion-like particles are hypothetical particles predicted in extensions of the standard model and are promising cold dark matter candidates. The Any Light Particle Search (ALPS II) experiment is a light-shining-through-the-wall experiment that aims to produce these particles from a strong light source and magnetic field and subsequently detect the

G. Magagnin, C. Lubin, M. Escher, N. Weber

We use photoemission electron microscopy to measure the ferroelastic twin wall angles at the surface of CaTiO$_\mathrm{3}$(001) and deduce the strain ordering. We analyze the angular dependence of the photoelectron emission from different domain surfaces, each with their own characteristic tilt angle in the factory roof-like topography. By considering the su

James Gratrex, Blaženka Melić, Ivan Nišandžić

We provide updated predictions of the lifetimes of singly charmed baryons and mesons within the heavy quark expansion, with all known corrections included. A special attention is devoted to the choice of the charm mass and wavefunctions of heavy baryons. Our results accommodate the experimentally-favoured hierarchy of singly charmed baryon lifetimes \begin{e

Diego G. Bussandri, Pedro W. Lamberti, Karol Życzkowski

We analyze two ways to obtain distinguishability measures between quantum maps by employing the square root of the quantum Jensen-Shannon divergence, which forms a true distance in the space of density operators. The arising measures are the transmission distance between quantum channels and the entropic channel divergence. We investigate their mathematical

C. J. Picken, I. Despard, A. Kelly, J. D. Pritchard

We present new photonics and electronics packages recently developed by M Squared Lasers specifically tailored for scalable neutral atom quantum computing; a high power 1064 nm system for scalable qubit number, a phase locked system for high fidelity single qubit control, and robust cavity locked systems for high fidelity Rydberg operations. We attain driven

Yuxing Yang, Junhao Zhao, Siyi Wang, Xiangyu Min

With the rise of short video platforms as prominent channels for news dissemination, major platforms in China have gradually evolved into fertile grounds for the proliferation of fake news. However, distinguishing short video rumors poses a significant challenge due to the substantial amount of information and shared features among videos, resulting in homog

Benjamin Biggs, Christos-Savvas Bouganis, George A. Constantinides

The continued need for improvements in accuracy, throughput, and efficiency of Deep Neural Networks has resulted in a multitude of methods that make the most of custom architectures on FPGAs. These include the creation of hand-crafted networks and the use of quantization and pruning to reduce extraneous network parameters. However, with the potential of stat

Julius Ross, Hendrik Süß, Thomas Wannerer

We introduce and study a notion of dually Lorentzian polynomials, and show that if $s$ is non-zero and dually Lorentzian then the operator \[s(\partial_{x_1},\ldots,\partial_{x_n}):\mathbb R[x_1,\ldots,x_n] \to \mathbb R[x_1,\ldots,x_n]\] preserves (strictly) Lorentzian polynomials. From this we conclude that any theory that admits a mixed Alexandrov-Fenchel

Da Eun Kang, Victor F. Ksoll, Dominika Itrich, Leonardo Testi

Aims. We introduce a new deep learning tool that estimates stellar parameters (such as effective temperature, surface gravity, and extinction) of young low-mass stars by coupling the Phoenix stellar atmosphere model with a conditional invertible neural network (cINN). Our networks allow us to infer the posterior distribution of each stellar parameter from th

I. Cardinali, L. Giuzzi

Consider the point line-geometry ${\mathcal P}_t(n,k)$ having as points all the $[n,k]$-linear codes having minimum dual distance at least $t+1$ and where two points $X$ and $Y$ are collinear whenever $X\cap Y$ is a $[n,k-1]$-linear code having minimum dual distance at least $t+1$. We are interested in the collinearity graph $\Lambda_t(n,k)$ of ${\mathcal P}

Son Nguyen, Thu-Trang Nguyen, Thanh Trong Vu, Thanh-Dat Do

Attacks against computer systems exploiting software vulnerabilities can cause substantial damage to the cyber-infrastructure of our modern society and economy. To minimize the consequences, it is vital to detect and fix vulnerabilities as soon as possible. Just-in-time vulnerability detection (JIT-VD) discovers vulnerability-prone ("dangerous") commits to p

Guanzhong Li, Lvzhou Li, Jingquan Luo

This work revisits quantum algorithms for the well-known welded tree problem, proposing a very succinct quantum algorithm based on the simplest coined quantum walks. It simply iterates the naturally defined coined quantum walk operator for a predetermined time and finally measure, where the predetermined time can be efficiently computed on classical computer

Chuanfei Hu, Tianyi Xia, Shenghong Ju, Xinde Li

Learning to segmentation without large-scale samples is an inherent capability of human. Recently, Segment Anything Model (SAM) performs the significant zero-shot image segmentation, attracting considerable attention from the computer vision community. Here, we investigate the capability of SAM for medical image analysis, especially for multi-phase liver tum

Rozália Z. Ádám, Tamás Hajdu, Attila Bódi, Róbert Hajdu

Context. The Optical Gravitational Lensing Experiment (OGLE) observed around 450,000 eclipsing binaries (EBs) towards the Galactic Bulge. Decade-long photometric observations such as these provide an exceptional opportunity to thoroughly examine the targets. However, observing dense stellar fields such as the Bulge may result in blends and contamination by c

The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, R. Abbott

Gravitational lensing by massive objects along the line of sight to the source causes distortions of gravitational wave-signals; such distortions may reveal information about fundamental physics, cosmology and astrophysics. In this work, we have extended the search for lensing signatures to all binary black hole events from the third observing run of the LIG

Gerald Kaiser

Positive-energy solutions of the Klein-Gordon equation form a Hilbert space of holomorphic functions on the future tube. This domain is interpreted as an extended phase space for the associated classical particle, the extra dimensions being the time and a new variable related to the inverse equilibrium temperature in an associated canonical ensemble. This gi

James A Sinclair, Thomas K Greathouse, Rohini S Giles, John Lacy

We present mid-infrared spectroscopy of Jupiter's mid-to-high latitudes using Gemini-North/TEXES (Texas Echelon Cross Echelle Spectrograph) on March 17-19, 2017. These observations capture Jupiter's hydrocarbon auroral emissions before, during and after the arrival of a solar wind compression on March 18th, which highlights the coupling between the polar str

Abhijeet Vyas, Brian Bullins

We propose a study of structured non-convex non-concave min-max problems which goes beyond standard first-order approaches. Inspired by the tight understanding established in recent works [Adil et al., 2022, Lin and Jordan, 2022b], we develop a suite of higher-order methods which show the improvements attainable beyond the monotone and Minty condition settin

Alastair J. Litterick, Adam R. Thomas

Let $G$ be a simple algebraic group of exceptional type over an algebraically closed field of characteristic $p > 0$. This paper continues a long-standing effort to classify the connected reductive subgroups of $G$. Having previously completed the classification when $p$ is sufficiently large, we focus here on the case that $p$ is bad for $G$. We classify th

Sanjoy Kumar Mazumder, Tiankai Yao, Anter El-Azab

An atomistically informed mean field cluster dynamics model has been presented to investigate the nucleation and growth of defect loops in irradiated {\alpha}-U. TEM analysis of neutron irradiated {\alpha}-U shows the evolution of SIA and vacancy loops on (010) and (100) crystallographic planes respectively, resulting in an anisotropic swelling of the face-c

Chen Xu, Yuhan Zhu, Haocheng Shen, Boheng Chen

Prompt learning has been designed as an alternative to fine-tuning for adapting Vision-language (V-L) models to the downstream tasks. Previous works mainly focus on text prompt while visual prompt works are limited for V-L models. The existing visual prompt methods endure either mediocre performance or unstable training process, indicating the difficulty of

David Wiedemann, Malte A. Peter

Polyconvexity is an important concept in the analysis of energies related to elasticity. A function $f \colon \R^{d\times d} \to \R$ is called polyconvex if it can be written as a convex function in the minors of the argument. We show that for isotropic functions it suffices to consider diagonal matrices. For $d=3$, this leads to a dimension reduction for th

Yutong Xie, Mingze Yuan, Bin Dong, Quanzheng Li

Though achieving excellent performance in some cases, current unsupervised learning methods for single image denoising usually have constraints in applications. In this paper, we propose a new approach which is more general and applicable to complicated noise models. Utilizing the property of score function, the gradient of logarithmic probability, we define

Peter Berta, Juraj Smieško, Martin Spousta

The hard-scatter processes in hadronic collisions are often largely contaminated with soft background coming from pileup in proton-proton collisions, or underlying event in heavy-ion collisions. There are multiple methods to remove the effect of pileup for jets. Two such methods, Area Subtraction and Constituent Subtraction, use the pileup density as the mai

Kibum Kim, Dongmin Hyun, Sukwon Yun, Chanyoung Park

The long-tailed problem is a long-standing challenge in Sequential Recommender Systems (SRS) in which the problem exists in terms of both users and items. While many existing studies address the long-tailed problem in SRS, they only focus on either the user or item perspective. However, we discover that the long-tailed user and item problems exist at the sam

Sikandar Aftab, Muhammad Arslan Shehzad, Muhammad Salman Ajmal, Fahmid Kabir

In future solar cell technologies, the thermodynamic Shockley-Queisser limit for solar-to-current conversion in traditional p-n junctions could potentially be overcome with a bulk photovoltaic effect by creating an inversion broken symmetry in piezoelectric or ferroelectric materials. Here, we unveiled mechanical distortion-induced bulk photovoltaic behavior

Ali Momeni, Xinxin Guo, Herve Lissek, Romain Fleury

Waves, such as light and sound, inherently bounce and mix due to multiple scattering induced by the complex material objects that surround us. This scattering process severely scrambles the information carried by waves, challenging conventional communication systems, sensing paradigms, and wave-based computing schemes. Here, we show that instead of being a h

António Amorim, Diana Guimarães, Tiago Mendonça, Pedro Neto

Robots are increasingly present in our lives, sharing the workspace and tasks with human co-workers. However, existing interfaces for human-robot interaction / cooperation (HRI/C) have limited levels of intuitiveness to use and safety is a major concern when humans and robots share the same workspace. Many times, this is due to the lack of a reliable estimat

Daichi Tsuna, Yuki Takei

Some hydrogen-poor supernovae (SNe) are found to undergo interaction with dense circumstellar matter (CSM) that may originate from mass eruption(s) just prior to core-collapse. We model the interaction between the remaining star and the bound part of the erupted CSM that eventually fall back to the star. We find that while fallback initially results in a con

Aristides Kontogeorgis, Alexios Terezakis

We are investigating the lifting problem for local actions involving semidirect products of a cyclic $p$-group with a cyclic group prime to $p$, where $p$ represents the characteristic of the special fiber. We establish a criterion based on the Harbater-Katz-Gabber compactification of local actions, enabling us to determine whether a given local action can b

Muhammad Imran, Gabor Ivanyos

We propose a method for solving the hidden subgroup problem in nilpotent groups. The main idea is iteratively transforming the hidden subgroup to its images in the quotient groups by the members of a central series, eventually to its image in the commutative quotient of the original group; and then using an abelian hidden subgroup algorithm to determine this

Miguel Neves, Miguel Vieira, Pedro Neto

The development of machine learning algorithms has been gathering relevance to address the increasing modelling complexity of manufacturing decision-making problems. Reinforcement learning is a methodology with great potential due to the reduced need for previous training data, i.e., the system learns along time with actual operation. This study focuses on t

Wenkui Ding, Xiaoguang Wang, Shu Chen

Considering non-Hermitian systems implemented by utilizing enlarged quantum systems, we determine the fundamental limits for the sensitivity of non-Hermitian sensors from the perspective of quantum information. We prove that non-Hermitian sensors do not outperform their Hermitian counterparts (directly couples to the parameter) in the performance of sensitiv

Máté Kormos, Stéphanie van der Pas, Aad van der Vaart

Caliper matching is used to estimate causal effects of a binary treatment from observational data by comparing matched treated and control units. Units are matched when their propensity scores, the conditional probability of receiving treatment given pretreatment covariates, are within a certain distance called caliper. So far, theoretical results on caliper

Gaston Nieuviarts

Non-commutative geometry (NCG) is a mathematical discipline developed in the 1990s by Alain Connes. It is presented as a new generalization of usual geometry, both encompassing and going beyond the Riemannian framework, within a purely algebraic formalism. Like Riemannian geometry, NCG also has links with physics. Indeed, NCG provided a powerful framework fo

Weikun He, Yuxiang Jiao, Disheng Xu

We establish new results on the dimensional properties of measures and invariant sets associated to random walks and group actions by circle diffeomorphisms. This leads to several dynamical applications. Among the applications, we show, strengthening of a recent result of Deroin-Kleptsyn-Navas [24], that the minimal set of a finitely generated group of real-

M. A. Korzeniowska, A. Theodorsen, M. Rypdal, O. E. Garcia

Power spectral density scaling with frequency $f$ as $1/f^\beta$ and $\beta \approx 1$ is widely found in natural and socio-economic systems. Consequently, it has been suggested that such self-similar spectra reflect the universal dynamics of complex phenomena. Here, we show that for a superposition of uncorrelated pulses with a power-law distribution of dur

Peter D. Ditlevsen, Susanne Ditlevsen

Tipping to an undesired state in the climate when a control parameter slowly approaches a critical value is a growing concern with increasing greenhouse gas concentrations. Predictions rely on detecting early warning signals (EWSs) in observations of the system. The primary EWSs are increase in variance, (loss of resilience), and increased autocorrelation (c

Alexis L. Quintana, Nicholas J. Wright, Robin D. Jeffries

OB associations are important probes of recent star formation and Galactic structure. In this study, we focus on the Auriga constellation, an important region of star formation due to its numerous young stars, star-forming regions and open clusters. We show using \textit{Gaia} data that its two previously documented OB associations, Aur OB1 and OB2, are too

Princessa Cintaqia, Matheus Inoue

This study introduces novel methods for sentiment and opinion classification of tweets to support the New Product Development (NPD) process. Two popular word embedding techniques, Word2Vec and BERT, were evaluated as inputs for classic Machine Learning and Deep Learning algorithms to identify the best-performing approach in sentiment analysis and opinion det

Sania Zahan, Zulqarnain Gilani, Ghulam Mubashar Hassan, Ajmal Mian

Autism diagnosis presents a major challenge due to the vast heterogeneity of the condition and the elusive nature of early detection. Atypical gait and gesture patterns are dominant behavioral characteristics of autism and can provide crucial insights for diagnosis. Furthermore, these data can be collected efficiently in a non-intrusive way, facilitating ear

Mikihiro Fujii

We consider the two-dimensional stationary Navier--Stokes equations on the whole plane $\mathbb{R}^2$. In the higher-dimensional cases $\mathbb{R}^n$ with $n \geqslant 3$, the well-posedness and ill-posedness in scaling critical spaces are well-investigated by numerous papers. However, despite the attention of many researchers, the corresponding problem in t

Haotian Li, Yun Wang, Q. Vera Liao, Huamin Qu

Data storytelling plays an important role in data workers' daily jobs since it boosts team collaboration and public communication. However, to make an appealing data story, data workers spend tremendous efforts on various tasks, including outlining and styling the story. Recently, a growing research trend has been exploring how to assist data storytelling wi

Michael Joswig, Mario Kummer, Andreas Thom, Claudia He Yun

We study the question whether copies of $S^1$ in $\mathrm{SU}(3)$ can be amalgamated in a compact group. This is the simplest instance of a fundamental open problem in the theory of compact groups raised by George Bergman in 1987. Considerable computational experiments suggest that the answer is positive in this case. We obtain a positive answer for a relaxe

Zhe Wang, Aladine Chetouani, Mohamed Jarraya, Didier Hans

Knee OsteoArthritis (KOA) is a widespread musculoskeletal disorder that can severely impact the mobility of older individuals. Insufficient medical data presents a significant obstacle for effectively training models due to the high cost associated with data labelling. Currently, deep learning-based models extensively utilize data augmentation techniques to

Zipeng Wu, Song Cheng, Bei Zeng

Quantum Error-Correcting Codes (QECCs) play a crucial role in enhancing the robustness of quantum computing and communication systems against errors. Within the realm of QECCs, stabilizer codes, and specifically graph codes, stand out for their distinct attributes and promising utility in quantum technologies. This study underscores the significance of devis

X. Cao, Y. Chang, K. Chen, E. Ciuffoli

Observing nuclear neutrinoless double beta (0vbb) decay would be a revolutionary result in particle physics. Observing such a decay would prove that the neutrinos are their own antiparticles, help to study the absolute mass of neutrinos, explore the origin of their mass, and may explain the matter-antimatter asymmetry in our universe by lepton number violati

Sergio Iguri, Nicolas Kovensky, Julian H. Toro

We compute all worldsheet three-point functions involving spectrally-flowed operators in chiral multiplets of the space-time theory for strings in AdS$_3\times$S$^3\times$T$^4$, thus completing the analysis of the full AdS$_3$/CFT$_2$ chiral ring. We make use of techniques recently developed for the bosonic sector, based on holomorphic covering maps from the

Riccardo Martini, Gregorio Paci, Dario Sauro

We propose a functional measure over the torsion tensor. We discuss two completely equivalent choices for the Wheeler-DeWitt supermetric for this field, the first one being based on its algebraic decomposition, the other inspired by teleparallel theories of gravity. The measure is formally defined by requiring the normalization of the Gaussian integral. To a

Raphael Fischer, Matthias Jakobs, Katharina Morik

Advances in artificial intelligence need to become more resource-aware and sustainable. This requires clear assessment and reporting of energy efficiency trade-offs, like sacrificing fast running time for higher predictive performance. While first methods for investigating efficiency have been proposed, we still lack comprehensive results for popular methods

Simone Cammarasana, Paolo Nicolardi, Giuseppe Patanè

We propose a novel deep-learning framework for super-resolution ultrasound images and videos in terms of spatial resolution and line reconstruction. We up-sample the acquired low-resolution image through a vision-based interpolation method; then, we train a learning-based model to improve the quality of the up-sampling. We qualitatively and quantitatively te

Giuliano Basso

We give a complete characterization of all real-valued functions on the unit circle $S^1$ that can be represented by integrating the spherical distance on $S^1$ with respect to a signed measure or a probability measure.

S. J. Liu, D. Wu, T. X. Hu, T. Y. Liang

The proton-boron (p-$^{11}$B) reaction is regarded as the holy grail of advanced fusion fuels, since the primary reaction produces three $\alpha$ particles with few neutrons and induced radio-activities from second order reactions. Compared to the Deuterium-Tritium reaction a much higher reaction temperature is required. Moreover, bremsstrahlung energy losse

Antonio Cruciani

We present MANTRA, a framework for approximating the temporal betweenness centrality of all nodes in a temporal graph. Our method can compute probabilistically guaranteed high-quality temporal betweenness estimates (of nodes and temporal edges) under all the feasible temporal path optimalities, presented in the work of Bu{\ss} et al. (KDD, 2020). We provide

Mikihiro Fujii

In this paper, we are concerned with bilinear estimates related to the two-dimensional stationary Navier--Stokes equation. By establishing concrete counter examples, we prove the bilinear estimates fail for almost all scaling critical Besov spaces. Our result may be closely related to an open problem whether the two-dimensional stationary Navier--Stokes equa

Yujia Qin, Shengding Hu, Yankai Lin, Weize Chen

Humans possess an extraordinary ability to create and utilize tools, allowing them to overcome physical limitations and explore new frontiers. With the advent of foundation models, AI systems have the potential to be equally adept in tool use as humans. This paradigm, i.e., tool learning with foundation models, combines the strengths of specialized tools and

Robert P Gowers, Magnus J E Richardson

The spatiotemporal stochastic dynamics of the voltage as well as the upcrossing rate are derived for a model neuron comprising a long dendrite with uniformly distributed filtered excitatory and inhibitory synaptic drive. A cascade of ordinary and partial differential equations is obtained describing the evolution of first-order means and second-order spatial

Karol Lynch, Joern Ploennigs, Bradley Eck

The usage of mathematical formulas as concise representations of a document's key ideas is common practice. Correctly interpreting these formulas, by identifying mathematical symbols and extracting their descriptions, is an important task in document understanding. This paper makes the following contributions to the mathematical identifier description readin

E. García Herrera, F. Torres-Leal, B. M. Rodríguez-Lara

The center of mass motion of trapped ions and neutral atoms is suitable for approximation by a time-dependent driven quantum harmonic oscillator whose frequency and driving strength may be controlled with high precision. We show the time evolution for these systems with continuous differentiable time-dependent parameters in terms of the three basic operation

Andreas Kofler, Fabian Altekrüger, Fatima Antarou Ba, Christoph Kolbitsch

We propose a method for fast and automatic estimation of spatially dependent regularization maps for total variation-based (TV) tomography reconstruction. The estimation is based on two distinct sub-networks, with the first sub-network estimating the regularization parameter-map from the input data while the second one unrolling T iterations of the Primal-Du

Rishi Hazra, Luc De Raedt

Despite numerous successes in Deep Reinforcement Learning (DRL), the learned policies are not interpretable. Moreover, since DRL does not exploit symbolic relational representations, it has difficulties in coping with structural changes in its environment (such as increasing the number of objects). Relational Reinforcement Learning, on the other hand, inheri

Haximjan Abdusattar

The $P$-$V$ phase transition of the FRW (Friedmann-Robertson-Walker) universe with a perfect fluid has recently been investigated, revealing that the four critical exponents near the critical point are consistent with the values predicted by mean field theory. Notably, the coexistence phase of the $P$-$V$ phase transition in the FRW universe above the critic

Wen-Bin Liu, Jiang Long

In this paper, we reduce the electromagnetic theory to future null infinity and obtain a vector theory at the boundary. We compute the Poincar\'e flux operators which could be generalized. We quantize the vector theory, and impose normal order on the extended flux operators. It is shown that these flux operators generate the supertranslation and superrotatio

Aaron J. Tyrrell

In this paper we show that a particular extrinsic pointwise hypersurface invariant is always non-positive on minimal hypersurfaces of constant curvature spaces and vanishes identically if and only if the hypersurface is rotational. We show this for hypersurfaces of 5-dimensional spaces of constant curvature but we conjecture that this should generalize to a

Jing Liu, Sihan Chen, Xingjian He, Longteng Guo

In this paper, we propose a Vision-Audio-Language Omni-peRception pretraining model (VALOR) for multi-modal understanding and generation. Different from widely-studied vision-language pretraining models, VALOR jointly models relationships of vision, audio and language in an end-to-end manner. It contains three separate encoders for single modality representa