March 2023 arXiv papers — page 52

Zikui Cai, Zhongpai Gao, Benjamin Planche, Meng Zheng

With the rise of cameras and smart sensors, humanity generates an exponential amount of data. This valuable information, including underrepresented cases like AI in medical settings, can fuel new deep-learning tools. However, data scientists must prioritize ensuring privacy for individuals in these untapped datasets, especially for images or videos with face

O. P. M. Aslam, M. S. Potgieter, Xi Luo, M. D. Ngobeni

The precision measurements of galactic cosmic ray protons from PAMELA and AMS are reproduced using a well-established 3D numerical model for the period July 2006 - November 2019. The resulting modulation parameters are applied to simulate the modulation for cosmic antiprotons over the same period, which includes times of minimum modulation before and after 2

Tao Wang

A graph is $k$-degenerate if every subgraph $H$ has a vertex $v$ with $d_{H}(v) \leq k$. The class of degenerate graphs plays an important role in the graph coloring theory. Observed that every $k$-degenerate graph is $(k + 1)$-choosable and $(k + 1)$-DP-colorable. Bernshteyn and Lee defined a generalization of $k$-degenerate graphs, which is called \emph{we

Pierluigi Colli, Gianni Gilardi, Andrea Signori, Jürgen Sprekels

In this note, we study the optimal control of a nonisothermal phase field system of Cahn-Hilliard type that constitutes an extension of the classical Caginalp model for nonisothermal phase transitions with a conserved order parameter. It couples a Cahn-Hilliard type equation with source term for the order parameter with the universal balance law of internal

Sebastian Karl, Stefan Richter, Joachim von Zanthier

Intensity interferometry is a re-emerging interferometry tool that alleviates some of the challenges of amplitude interferometry at the cost of reduced sensitivity. We demonstrate the feasibility of intensity interferometry with fast single photon counting detectors at small telescopes by utilising a telescope of diameter of merely $0.5$\,m. The entire measu

Jialing Liao, Roope Vehkalahti, Tefjol Pllaha, Wei Han

We consider high-dimensional MIMO transmissions in frequency division duplexing (FDD) systems. For precoding, the frequency selective channel has to be measured, quantized and fed back to the base station by the users. When the number of antennas is very high this typically leads to prohibitively high quantization complexity and large feedback. In 5G New Rad

Thomas Bland, Giacomo Lamporesi, Manfred J. Mark, Francesca Ferlaino

Quantized vortices are the hallmark of superfluidity, and are often sought out as the first observable feature in new superfluid systems. Following the recent experimental observation of vortices in Bose-Einstein condensates comprised of atoms with inherent long-range dipole-dipole interactions [Nat. Phys. 18, 1453-1458 (2022)], we thoroughly investigate vor

V. M. Moskvitin, N. Semenova

In recent years, more and more researchers in the field of neural networks are interested in creating hardware implementations where neurons and the connection between them are realized physically. The physical implementation of ANN fundamentally changes the features of noise influence. In the case hardware ANNs, there are many internal sources of noise with

Sabri Koraltan, Christin Schmitt, Florian Bruckner, Claas Abert

We propose a novel device concept using spin-orbit-torques to realize a magnetic field sensor, where we eliminate the sensor offset using a differential measurement concept. We derive a simple analytical formulation for the sensor signal and demonstrate its validity with numerical investigations using macrospin simulations. The sensitivity and the measurable

Vincent E. Coll,, Nicholas Russoniello

A celebrated result of Gromov ensures the existence of a contact structure on any connected, non-compact, odd dimensional Lie group. In general, such structures are not invariant under left translation. The problem of finding which Lie groups admit a left-invariant contact structure resolves to the question of determining when a Lie algebra $\mathfrak{g}$ is

Damianos Iosifidis

In analogy to the concept of a non-metric dual connection, which is essential in defining statistical manifolds, we develop that of a torsion dual connection. Consequently, we illustrate the geometrical meaning of such a torsion dual connection and show how the use of both connections preserves the cracking of parallelograms in spaces equipped with a connect

Sebastián Urciuoli

We present a framework for the formal meta-theory of lambda calculi in first-order syntax, with two sorts of names, one to represent both free and bound variables, and the other for constants, and by using Stoughton's multiple substitutions. On top of the framework we formalize Girard's proof of the Strong Normalization Theorem for both the simply-typed lamb

Dohan Kim

Although reasoning about equations over strings has been extensively studied for several decades, little research has been done for equational reasoning on general clauses over strings. This paper introduces a new superposition calculus with strings and present an equational theorem proving framework for clauses over strings. It provides a saturation procedu

Liye Guo, Deivid Vale

Time complexity in rewriting is naturally understood as the number of steps needed to reduce terms to normal forms. Establishing complexity bounds to this measure is a well-known problem in the rewriting community. A vast majority of techniques to find such bounds consist of modifying termination proofs in order to recover complexity information. This has be

Edward H. Lee, Brendan Kelly, Emre Altinmakas, Hakan Dogan

While it is well known that population differences from genetics, sex, race, and environmental factors contribute to disease, AI studies in medicine have largely focused on locoregional patient cohorts with less diverse data sources. Such limitation stems from barriers to large-scale data share and ethical concerns over data privacy. Federated learning (FL)

Michelangelo Diligenti, Francesco Giannini, Stefano Fioravanti, Caterina Graziani

Knowledge Graph Embeddings (KGE) have become a quite popular class of models specifically devised to deal with ontologies and graph structure data, as they can implicitly encode statistical dependencies between entities and relations in a latent space. KGE techniques are particularly effective for the biomedical domain, where it is quite common to deal with

Erick Grilo, Bruno Lopes

Critical systems require high reliability and are present in many domains. They are systems in which failure may result in financial damage or even loss of lives. Standard techniques of software engineering are not enough to ensure the absence of unacceptable failures and/or that critical requirements are fulfilled. Reo is a component-based modelling languag

Ana Cruz, Alexandre Madeira, LuÂ-Ã-s Soares Barbosa

Often in Software Engineering, a modeling formalism has to support scenarios of inconsistency in which several requirements either reinforce or contradict each other. Paraconsistent transition systems are proposed in this paper as one such formalism: states evolve through two accessibility relations capturing weighted evidence of a transition or its absence,

Juan Margalef-Bentabol, Leigh Herman, Ivan Booth

Understanding degrees of freedom in classical mechanics is fundamental to characterizing physical systems. Counting them is usually easy, especially if we can assign them a clear meaning. However, the precise definition of a degree of freedom is not usually presented in first-year physics courses since it requires mathematical knowledge only learned in more

Miguel Pagano, José E. Solsona

In this paper we present our current development on a new formalization of nominal sets in Agda. Our first motivation in having another formalization was to understand better nominal sets and to have a playground for testing type systems based on nominal logic. Not surprisingly, we have independently built up the same hierarchy of types leading to nominal se

Weijie Tu, Weijian Deng, Tom Gedeon, Liang Zheng

This work investigates dataset vectorization for two dataset-level tasks: assessing training set suitability and test set difficulty. The former measures how suitable a training set is for a target domain, while the latter studies how challenging a test set is for a learned model. Central to the two tasks is measuring the underlying relationship between data

Paola Marziani, Swayamtrupta Panda, Alice Deconto Machado, Ascension Del Olmo

Optical and UV properties of radio-quiet (RQ) and radio-loud (RL, relativistically "jetted") active galactic nuclei (AGN) are known to differ markedly; however, it is still unclear what is due to a sample selection and what is associated with intrinsic differences in the inner workings of their emitting regions. Chemical composition is an important parameter

Tim Schwägerl, Cigdem Issever, Karl Jansen, Teng Jian Khoo

The reconstruction of trajectories of charged particles is a key computational challenge for current and future collider experiments. Considering the rapid progress in quantum computing, it is crucial to explore its potential for this and other problems in high-energy physics. The problem can be formulated as a quadratic unconstrained binary optimization (QU

Konstantinos Spiliotis, Lucia Russo, Francesco Giannino, Constantinos Siettos

We study the mechanisms of pattern formation for vegetation dynamics in water-limited regions. Our analysis is based on a set of two partial differential equations (PDEs) of reaction-diffusion type for the biomass and water and one ordinary differential equation (ODE) describing the dependence of the toxicity on the biomass. We perform a linear stability ana

Gian Carlo Maffettone, Maurizio Porfiri, Mario di Bernardo

We investigate the stability and robustness properties of a continuification-based strategy for the control of large-scale multiagent systems. Within continuation-based strategy, one transforms the microscopic, agent-level description of the system dynamics into a macroscopic continuum-level, for which a control action can be synthesized to steer the macrosc

Thomas Stegmüller, Tim Lebailly, Behzad Bozorgtabar, Tinne Tuytelaars

Learning dense visual representations without labels is an arduous task and more so from scene-centric data. We propose to tackle this challenging problem by proposing a Cross-view consistency objective with an Online Clustering mechanism (CrOC) to discover and segment the semantics of the views. In the absence of hand-crafted priors, the resulting method is

Gefen Baranes, Shiran Even-Haim, Ron Ruimy, Alexey Gorlach

We show that the coherent interaction between free electrons and photons can be used for universal control of continuous-variable photonic quantum states in the form of Gottesman-Kitaev-Preskill (GKP) qubits. Specifically, we find that electron energy combs enable non-destructive measurements of the photonic state and can induce arbitrary gates. Moreover, a

Kai Liu, Hailiang Xiong, Gangqiang Yang, Zhengfeng Du

As one of the major branches of automatic speech recognition, attention-based models greatly improves the feature representation ability of the model. In particular, the multi-head mechanism is employed in the attention, hoping to learn speech features of more aspects in different attention subspaces. For speech recognition of complex languages, on the one h

Stefan Teufel, Roderich Tumulka, Cornelia Vogel

We consider a closed macroscopic quantum system in a pure state $\psi_t$ evolving unitarily and take for granted that different macro states correspond to mutually orthogonal subspaces $\mathcal{H}_\nu$ (macro spaces) of Hilbert space, each of which has large dimension. We extend previous work on the question what the evolution of $\psi_t$ looks like macrosc

Maximilian Ulmer, Maximilian Durner, Martin Sundermeyer, Manuel Stoiber

We present a novel technique to estimate the 6D pose of objects from single images where the 3D geometry of the object is only given approximately and not as a precise 3D model. To achieve this, we employ a dense 2D-to-3D correspondence predictor that regresses 3D model coordinates for every pixel. In addition to the 3D coordinates, our model also estimates

Sheikh Parvez Mandal

This MS thesis explores the effects and origins of a 'noise with memory' in the dynamics of an open quantum system. The system considered here is a multi-qubit register performing the Grover's quantum search algorithm. We show that a Markovian-correlated noise can enhance the efficiency of the algorithm over a time correlation-less noise. We also analyticall

Anton A. Klyachko, Mikhail A. Mikheenko, Vitaly A. Roman'kov

Not any nonsingular equation over a metabelian group has solution in a larger metabelian group. However, any nonsingular equation over a solvable group with a subnormal series with abelian torsion-free quotients has a solution in a larger group with a similar subnormal series of the same length (and an analogous fact is valid for systems of equations).

Suren Danielyan, Alexander Guterman, Elena Kreines, Fedor Pakovich

The concepts of differentiation and integration for matrices are known. As far as each matrix is differentiable, it is not clear a priori whether a given matrix is integrable or not. Recently some progress was obtained for diagonalizable matrices, however general problem remained open. In this paper, we present a full solution of the integrability problem. N

Ofer Cohen, Cecilia Garraffo, Jeremy Drake, Kristina Monsch

We present a three-dimensional, time-dependent, MHD simulation of the short-term interaction between a protoplanetary disk and the stellar corona in a T Tauri system. The simulation includes the stellar magnetic field, self-consistent coronal heating and stellar wind acceleration, and a disk rotating at sub-Keplerian velocity to induce accretion. We find tha

C. J. R. Murphy-Barltrop, J. L. Wadsworth, E. F. Eastoe

Modelling the extremal dependence of bivariate variables is important in a wide variety of practical applications, including environmental planning, catastrophe modelling and hydrology. The majority of these approaches are based on the framework of bivariate regular variation, and a wide range of literature is available for estimating the dependence structur

Yuki Kurokawa

The optimal lifespan estimates of a solution to weakly coupled systems of wave equations have been investigated by many works, except for the lower bound in even space dimensions. Our aim is to prove the open part under the assumption of radial symmetry on the solution. The odd dimensional case was already obtained in our previous paper by long time existenc

Chao-Ben Zhao, Jian-Zhao Wu, Bo-Fu Wang, Tienchong Chang

Exhaled droplet and aerosol-mediated transmission of respiratory diseases, including SARS-CoV-2, is exacerbated in poorly ventilated environments where body heat-driven airflow prevails. Employing large-scale simulations, we reveal how the human body heat can potentially spread pathogenic species between occupants in a room. Morphological phase transition in

M. Ibrahim, M. Usman, Khalid Khan

We have computed the global quantum discord and von Neumann entropy of multipartite two-level atomic systems interacting with a single-mode Fock field. We use Tavis-Cumming model. We have explored how quantum correlations and quantum entanglement evolve with time in such systems. The quantum system is prepared initially in a mixed state and different paramet

Qifan Yu, Juncheng Li, Yu Wu, Siliang Tang

Scene Graph Generation (SGG) aims to extract <subject, predicate, object> relationships in images for vision understanding. Although recent works have made steady progress on SGG, they still suffer long-tail distribution issues that tail-predicates are more costly to train and hard to distinguish due to a small amount of annotated data compared to frequent p

Zicheng Zhang, Yinglu Liu, Congying Han, Yingwei Pan

Recent advances in 3D scene representation and novel view synthesis have witnessed the rise of Neural Radiance Fields (NeRFs). Nevertheless, it is not trivial to exploit NeRF for the photorealistic 3D scene stylization task, which aims to generate visually consistent and photorealistic stylized scenes from novel views. Simply coupling NeRF with photorealisti

Yao Lei Xu, Kriton Konstantinidis, Danilo P. Mandic

Despite the omnipresence of tensors and tensor operations in modern deep learning, the use of tensor mathematics to formally design and describe neural networks is still under-explored within the deep learning community. To this end, we introduce the Graph Tensor Network (GTN) framework, an intuitive yet rigorous graphical framework for systematically design

Christoph Hofmeister, Luis Maßny, Eitan Yaakobi, Rawad Bitar

We consider gradient coding in the presence of an adversary, controlling so-called malicious workers trying to corrupt the computations. Previous works propose the use of MDS codes to treat the inputs of the malicious workers as errors and correct them using the error-correction properties of the code. This comes at the expense of increasing the replication,

Ramesh Narayan, Eliot Quataert

Recent developments have ushered in a new era in the field of black hole astrophysics, providing our first direct view of the remarkable environment near black hole event horizons. These observations have enabled astronomers to confirm long-standing ideas on the physics of gas flowing into black holes with temperatures that are hundreds of times greater than

Rahul Nellikkath, Spyros Chatzivasileiadis

Machine learning algorithms, especially Neural Networks (NNs), are a valuable tool used to approximate non-linear relationships, like the AC-Optimal Power Flow (AC-OPF), with considerable accuracy -- and achieving a speedup of several orders of magnitude when deployed for use. Often in power systems literature, the NNs are trained with a fixed dataset genera

Johanna P. Müller, Matthew Baugh, Jeremy Tan, Mischa Dombrowski

Universal anomaly detection still remains a challenging problem in machine learning and medical image analysis. It is possible to learn an expected distribution from a single class of normative samples, e.g., through epistemic uncertainty estimates, auto-encoding models, or from synthetic anomalies in a self-supervised way. The performance of self-supervised

Shengzhe Wang, Zihang Lin, Suzhen Wu, Hong Jiang

We present LearnedFTL, a new on-demand page-level flash translation layer (FTL) design, which employs learned indexes to improve the address translation efficiency of flash-based SSDs. The first of its kind, it reduces the number of double reads induced by address translation in random read accesses. LearnedFTL proposes three key techniques: an in-place-upda

Hong-Zhe Zhang, Wan-Zhe Feng, Jun-Bao Wu

In this paper, we compute the correlation functions of Wilson(-'t~Hooft) loops with chiral primary operators in $\mathcal{N}=4$ supersymmetric Yang-Mills theory with $SO(N)$ gauge symmetry, which has a holographic dual description of Type IIB superstring theory on the $AdS_{5}\times\mathbf{RP}^{5}$ background. Specifically, we compute the coefficients of the

Feihao Pan, Xunwu Hu, Jiale Huang, Bingxian Shi

The sawtooth lattice shares some structural similarities with the kagome lattice and may attract renewed research interest. Here, we report a comprehensive study on the physical properties of Fe$_2$SiSe$_4$, an unexplored member in the olivine chalcogenides with the sawtooth lattice of Fe. Our results show that Fe$_2$SiSe$_4$ is a magnetic semiconductor with

Zixuan Ding, Ao Wang, Hui Chen, Qiang Zhang

Multi-label recognition (MLR) with incomplete labels is very challenging. Recent works strive to explore the image-to-label correspondence in the vision-language model, \ie, CLIP, to compensate for insufficient annotations. In spite of promising performance, they generally overlook the valuable prior about the label-to-label correspondence. In this paper, we

H. Andréka, J. van Benthem, I. Németi

This note contains some material promised in our earlier papers on submodel preservation and the guarded fragment, along with some information on the current status of the problems mentioned in these papers. Section 1 contains an early example of failure of Los-Tarski for finite-variable fragments with binary relations from a 1992 manuscript, with no substan

Nitin Nitsure

We give a short proof that any smooth (means formally smooth and finitely presented) homomorphism of rings can be obtained by base change from a smooth homomorphism of noetherian rings. Together with the elegant short proof by J. Conde-Lago that smooth homomorphisms of noetherian rings are flat, this gives a short and elementary proof of the theorem of Groth

Shaobo Lin, Kun Wang, Xingyu Zeng, Rui Zhao

Few-shot object detection (FSOD) aims to expand an object detector for novel categories given only a few instances for training. The few training samples restrict the performance of FSOD model. Recent text-to-image generation models have shown promising results in generating high-quality images. How applicable these synthetic images are for FSOD tasks remain

Vaishali Pal, Carlos Lassance, Hervé Déjean, Stéphane Clinchant

Parameter-Efficient transfer learning with Adapters have been studied in Natural Language Processing (NLP) as an alternative to full fine-tuning. Adapters are memory-efficient and scale well with downstream tasks by training small bottle-neck layers added between transformer layers while keeping the large pretrained language model (PLMs) frozen. In spite of

Michael Albanese, Luca F. Di Cerbo

We show that extended graph 4-manifolds with positive Euler characteristic cannot support a complex structure. This result stems from a new proof of the fact that a closed real-hyperbolic 4-manifold cannot support a complex structure. Finally, we construct infinitely many extended graph 4-manifolds with positive Euler characteristic which support almost comp

Xiaorong Yang, Jia Chen, Degui Li, Runze Li

This paper considers estimating functional-coefficient models in panel quantile regression with individual effects, allowing the cross-sectional and temporal dependence for large panel observations. A latent group structure is imposed on the heterogenous quantile regression models so that the number of nonparametric functional coefficients to be estimated ca

Huan Ma, Changqing Zhang, Yatao Bian, Lemao Liu

Large language models have demonstrated surprising ability to perform in-context learning, i.e., these models can be directly applied to solve numerous downstream tasks by conditioning on a prompt constructed by a few input-output examples. However, prior research has shown that in-context learning can suffer from high instability due to variations in traini

Marcel Grote, Justus Bogner

Today, many systems use artificial intelligence (AI) to solve complex problems. While this often increases system effectiveness, developing a production-ready AI-based system is a difficult task. Thus, solid AI engineering practices are required to ensure the quality of the resulting system and to improve the development process. While several practices have

S. Piantelli, G. Casini, P. Ottanelli, L. Baldesi

An analysis of the asymmetric reactions $^{40,48}$Ca+$^{12}$C at 25 and 40 MeV/nucleon is presented. Data have been collected with six modules of the FAZIA array. The analysis is focused on the breakup channel of sources produced in dissipative collisions, partially corresponding to incomplete fusion processes. The study has been performed both on detected f

Swapan Das

The transparency of the hadrons produced in the $\gamma (n,p) \pi^-$ reaction in nuclei is calculated using the Glauber model modified by including the Fermi motion of the nucleon in the nucleus. Since the calculated results underestimates the measured transparency for $^4$He nucleus, the Glauber model is further modified by incorporating the short-range cor

Baidi Xiao, Rongpeng Li, Fei Wang, Chenghui Peng

Autonomous driving has witnessed incredible advances in the past several decades, while Multi-Agent Reinforcement Learning (MARL) promises to satisfy the essential need of autonomous vehicle control in a wireless connected vehicle networks. In MARL, how to effectively decompose a global feedback into the relative contributions of individual agents belongs to

Ziwei Liu, Yongtao Wang, Xiaojie Chu

Knowledge distillation is a popular technique for transferring the knowledge from a large teacher model to a smaller student model by mimicking. However, distillation by directly aligning the feature maps between teacher and student may enforce overly strict constraints on the student thus degrade the performance of the student model. To alleviate the above

Hasan Abed Al Kader Hammoud, Adel Bibi, Philip H. S. Torr, Bernard Ghanem

In this paper we investigate the frequency sensitivity of Deep Neural Networks (DNNs) when presented with clean samples versus poisoned samples. Our analysis shows significant disparities in frequency sensitivity between these two types of samples. Building on these findings, we propose FREAK, a frequency-based poisoned sample detection algorithm that is sim

Chen-Xu Hao

Consider a simple symmetric random walk on the integer lattice $\mathbb{Z}$. Let $E(n)$ denote a favorite edge of the random walk at time $n$. In this paper, we study the escape rate of $E(n)$, and show that almost surely $\liminf_{n\to\infty}\frac{|E(n)|}{\sqrt{n}\cdot(\log n)^{-\gamma}}$ equals 0 if $\gamma\le 1$, and is infinity otherwise. We also obtain

Wenqing Wang, Yawei Luo, Zhiqing Chen, Tao Jiang

Current video-based scene graph generation (VidSGG) methods have been found to perform poorly on predicting predicates that are less represented due to the inherent biased distribution in the training data. In this paper, we take a closer look at the predicates and identify that most visual relations (e.g. sit_above) involve both actional pattern (sit) and s

Sigiswald Barbier, Tom De Medts, Michiel Smet

Kantor pairs, (quadratic) Jordan pairs, and similar structures have been instrumental in the study of $\mathbb{Z}$-graded Lie algebras and algebraic groups. We introduce the notion of an operator Kantor pair, a generalization of Kantor pairs to arbitrary (commutative, unital) rings, similar in spirit as to how quadratic Jordan pairs and algebras generalize l

Hynek Paul, Eric Perlmutter, Himanshu Raj

In four-dimensional $\mathcal{N}=4$ super Yang-Mills theory with gauge group $SU(N)$, we present a closed-form solution for a family of integrated four-point functions involving stress tensor multiplet composites of arbitrary R-charge. These integrated correlators are shown to be equivalent to a one-dimensional semi-infinite lattice of harmonic oscillators w

Jorge Baeza-Ballesteros, Johan Bijnens, Tomáš Husek, Fernando Romero-López

The three-particle $K$-matrix, $\mathcal{K}_{\mathrm{df},3}$, is a scheme-dependent quantity that parametrizes short-range three-particle interactions in the relativistic-field-theory three-particle finite-volume formalism. In this work, we compute its value for systems of three pions at maximal isospin through next-to-leading order (NLO) in Chiral Perturbat

A. Kirwan, C. F. Manara, E. T. Whelan, M. Robberto

In this work we present the highest spatial and spectral resolution integral field observations to date of the bipolar jet from the Orion proplyd 244-440 using MUSE NFM) observations on the VLT. We observed a previously unreported chain of six distinct knots in a roughly S-shaped pattern, and by comparing them with HST images we estimated proper motions in t

Arwa Alromih, John A. Clark, Prosanta Gope

The detection of energy thefts is vital for the safety of the whole smart grid system. However, the detection alone is not enough since energy thefts can crucially affect the electricity supply leading to some blackouts. Moreover, privacy is one of the major challenges that must be preserved when dealing with clients' energy data. This is often overlooked in

Zhe Wang, Aladine Chetouani, Yung Hsin Chen, Yuhua Ru

Knee Osteoarthritis (KOA) is a prevalent musculoskeletal disorder that severely impacts mobility and quality of life, particularly among older adults. Its diagnosis often relies on subjective assessments using the Kellgren-Lawrence (KL) grading system, leading to variability in clinical evaluations. To address these challenges, we propose a confidence-driven

Yong Gao, Lijing Shao, Jan Steinhoff

Universal relations that are insensitive to the equation of state (EoS) are useful in reducing the parameter space when measuring global quantities of neutron stars (NSs). In this paper, we reveal a new universal relation that connects the eccentricity to the radius and moment of inertia of rotating NSs. We demonstrate that the universality of this relation

Qinglin Ouyang, Wei Wang, Meng Zhai, Guo Chen

Transiting planets provide unique opportunities for the atmospheric characterization of exoplanets as they can reveal composition and the temperature structures at the day-night terminator regions in planetary atmospheres, and help understand the atmospheric process and formation environments of exoplanets. Here, we present the optical transmission spectrosc

Mihai Fulger, Nabanita Ray

We give equivalent descriptions for the augmented and diminished base loci of vector bundles in characteristic zero. We show that these base loci behave well under pullback, tensor product, and direct sum. Pathological behavior is observed on some nonsplit exact sequences.

Lewis Marsh, David Beers

The Euler characteristic transform (ECT) is a signature from topological data analysis (TDA) which summarises shapes embedded in Euclidean space. Compared with other TDA methods, the ECT is fast to compute and it is a sufficient statistic for a broad class of shapes. However, small perturbations of a shape can lead to large distortions in its ECT. In this pa

Aristeidis Panos, Yuriko Kobe, Daniel Olmeda Reino, Rahaf Aljundi

In Class-Incremental Learning (CIL) an image classification system is exposed to new classes in each learning session and must be updated incrementally. Methods approaching this problem have updated both the classification head and the feature extractor body at each session of CIL. In this work, we develop a baseline method, First Session Adaptation (FSA), t

Niu Su, Wei-Han Tan, Hua-Xing Chen, Wei Chen

We apply the QCD sum rule method to study the double-gluon hybrid states with the quark-gluon contents $\bar q q gg$ ($q=u/d$) and $\bar s s gg$. We construct twenty-eight double-gluon hybrid currents, eleven of which are found to be zero due to some internal symmetries between the two gluons fields. We concentrate on the non-vanishing currents with the exot

Xinyue Sheng, Matt Nicholl, Nicholas Ross

This paper reviews the Stochastic Recurrent Neural Network (SRNN) as applied to the light curves of Active Galactic Nuclei by Sheng et al. (2022). Astronomical data have inherent limitations arising from telescope capabilities, cadence strategies, inevitable observing weather conditions, and current understanding of celestial objects. When applying machine l

Onur Tanil Doganay, Kathrin Klamroth, Bruno Lang, Michael Stiglmayr

We give a short overview of advantages and drawbacks of the classical formulation of minimum cost network flow problems and solution techniques, to motivate a reformulation of classical static minimum cost network flow problems as optimal control problems constrained by port-Hamiltonian systems (pHS). The first-order optimality system for the port-Hamiltonia

Augustus Brown, Congkao Wen, Haitian Xie

We consider the integrated correlators associated with four-point correlation functions $\langle \mathcal{O}_2\mathcal{O}_2\mathcal{O}^{(i)}_p \mathcal{O}^{(j)}_p \rangle$ in four-dimensional $\mathcal{N}=4$ supersymmetric Yang-Mills theory (SYM) with $SU(N)$ gauge group, where $\mathcal{O}^{(i)}_p$ is a superconformal primary with charge (or dimension) $p$

Yunkang Cao, Xiaohao Xu, Weiming Shen

Point cloud (PCD) anomaly detection steadily emerges as a promising research area. This study aims to improve PCD anomaly detection performance by combining handcrafted PCD descriptions with powerful pre-trained 2D neural networks. To this end, this study proposes Complementary Pseudo Multimodal Feature (CPMF) that incorporates local geometrical information

Alexander Black, Simon Jenni, Tu Bui, Md. Mehrab Tanjim

We propose VADER, a spatio-temporal matching, alignment, and change summarization method to help fight misinformation spread via manipulated videos. VADER matches and coarsely aligns partial video fragments to candidate videos using a robust visual descriptor and scalable search over adaptively chunked video content. A transformer-based alignment module then

Bin Li, Yahui Lei

In many applications, ads are displayed together with the prices, so as to provide a direct comparison among similar products or services. The price-displaying feature not only influences the consumers' decisions, but also affects the advertisers' bidding behaviors. In this paper, we study ad auctions with display prices from the perspective of mechanism des

Francesco Cauteruccio, Giorgio Terracina

Detecting sets of relevant patterns from a given dataset is an important challenge in data mining. The relevance of a pattern, also called utility in the literature, is a subjective measure and can be actually assessed from very different points of view. Rule-based languages like Answer Set Programming (ASP) seem well suited for specifying user-provided crit

Weixiao Liu, Yuwei Wu, Sipu Ruan, Gregory S. Chirikjian

Representing complex objects with basic geometric primitives has long been a topic in computer vision. Primitive-based representations have the merits of compactness and computational efficiency in higher-level tasks such as physics simulation, collision checking, and robotic manipulation. Unlike previous works which extract polygonal meshes from a signed di

Yuka Yamaguchi, Naoya Yamaguchi

Let ${\rm C}_{4}$ be the cyclic group of order $4$. We determine all possible values of the integer group determinant of ${\rm C}_{4} \rtimes {\rm C}_{4}$.

Pablo Dorta-González

This paper proposes a three-year average of social attention as a more reliable measure of social impact for journals, since the social attention of research can vary widely among scientific articles, even within the same journal. The proposed measure is used to evaluate a journal's contribution to social attention in comparison to other bibliometric indicat

Dimitrios Ntalampekos

The author has recently introduced the class of CNED sets in Euclidean space, generalizing the classical notion of NED sets, and shown that they are quasiconformally removable. A set $E$ is CNED if the conformal modulus of a curve family is not affected when one restricts to the subfamily intersecting $E$ at countably many points. We prove that several class

Ziyang Lu, Yunqiang Pei, Guoqing Wang, Yang Yang

Aiming to link natural language descriptions to specific regions in a 3D scene represented as 3D point clouds, 3D visual grounding is a very fundamental task for human-robot interaction. The recognition errors can significantly impact the overall accuracy and then degrade the operation of AI systems. Despite their effectiveness, existing methods suffer from

Alexey Semenov, Alexander Shen, Nikolay Vereshchagin

The last theme of Kolmogorov's mathematics research was algorithmic theory of information, now often called Kolmogorov complexity theory. There are only two main publications of Kolmogorov (1965 and 1968-1969) on this topic. So Kolmogorov's ideas that did not appear as proven (and published) theorems can be reconstructed only partially based on work of his s

Amard L., Matt S. P

Rotation period measurements of low-mass stars show that the spin distributions in young clusters do not exhibit the spin-up expected due to contraction, during the phase when a large fraction of stars are still surrounded by accretion discs. During this stage, the stars accrete mass and angular momentum and may experience accretion enhanced-magnetised winds

Julius Bittermann, Lukas Bulla, Sebastian Ecker, Sebastian Philipp Neumann

Quantum technologies have matured to the point that we can test fundamental quantum phenomena under extreme conditions. Specifically, entanglement, a cornerstone of modern quantum information theory, can be robustly produced and verified in various adverse environments. We take these tests further and implement a high-quality Bell experiment during a parabol

Mingze Wei, Yaomin Huang, Zhiyuan Xu, Ning Liu

In this paper, we propose a novel representation for grasping using contacts between multi-finger robotic hands and objects to be manipulated. This representation significantly reduces the prediction dimensions and accelerates the learning process. We present an effective end-to-end network, CMG-Net, for grasping unknown objects in a cluttered environment by

Yutaro Akahoshi, Kazunori Maruyama, Hirotaka Oshima, Shintaro Sato

Quantum computers are expected to bring drastic acceleration to several computing tasks against classical computers. Noisy intermediate-scale quantum (NISQ) devices, which have tens to hundreds of noisy physical qubits, are gradually becoming available, but it is still challenging to achieve useful quantum advantages in meaningful tasks at this moment. On th

Thomas A. A. Venville, Alan R. Duffy, Roland M. Crocker, Oscar Macias

The Sagittarius Dwarf Spheroidal galaxy (Sgr) is investigated as a target for DM annihilation searches utilising J-factor distributions calculated directly from a high-resolution hydrodynamic simulation of the infall and tidal disruption of Sgr around the Milky Way. In contrast to past studies, the simulation incorporates DM, stellar and gaseous components f

Athanassios Tzouvaras

We establish some similarities/analogies between uncountable cardinals or powersets and the class $V$ of all sets. They concern mainly the Boolean algebras ${\cal P}(\kappa)$, for a regular cardinal $\kappa$, and ${\cal C}(V)$ (the class of subclasses of the universe $V$), endowed with some ideals, especially the ideal $[\kappa]^{<\kappa}$ for ${\cal P}(\kap

Charu Goel, Sarah Hess, Salma Kuhlmann

The cone $\mathcal{P}_{n+1,2d}$ ($n,d\in\mathbb{N}$) of all positive semidefinite (PSD) real forms in $n+1$ variables of degree $2d$ contains the subcone $\Sigma_{n+1,2d}$ of those that are representable as finite sums of squares (SOS) of real forms of half degree $d$. In 1888, Hilbert proved that these cones coincide exactly in the Hilbert cases $(n+1,2d)$

Lars Ødegaard Bentsen, Narada Dilp Warakagoda, Roy Stenbro, Paal Engelstad

With an ever-increasing number of sensors in modern society, spatio-temporal time series forecasting has become a de facto tool to make informed decisions about the future. Most spatio-temporal forecasting models typically comprise distinct components that learn spatial and temporal dependencies. A common methodology employs some Graph Neural Network (GNN) t

Matthias Ludewig, Konrad Waldorf

We give a very simple construction of the string 2-group as a strict Fr\'echet Lie 2-group. The corresponding crossed module is defined using the conjugation action of the loop group on its central extension, which drastically simplifies several constructions previously given in the literature. More generally, we construct strict 2-group extensions for a Lie

Hassan Mohamed Muhi-Aldeen, Asma A. Abdulrahman, Jabbar Abed Eleiwy, Fouad S. Tahir

The Internet has turned the entire world into a small village;this is because it has made it possible to share millions of images and videos. However, sending and receiving a huge amount of data is considered to be a main challenge. To address this issue, a new algorithm is required to reduce image bits and represent the data in a compressed form. Neverthele

M. Koussour, Simran Arora, Dhruba Jyoti Gogoi, M. Bennai

On the basis of homogeneous and isotropic Friedmann-Lemaitre-Robertson-Walker (FLRW) geometry, solutions to the issues of cosmic acceleration and dark energy are being put forth within the context of $f\left( Q\right)$ gravity. We take into account a power law $f(Q)$ model using $f\left( Q\right) =\alpha Q^{n}$, where $\alpha $ and $n$ are free model paramet