July 2022 arXiv papers — page 108

Guowen Xu, Guanlin Li, Shangwei Guo, Tianwei Zhang

Decentralized deep learning plays a key role in collaborative model training due to its attractive properties, including tolerating high network latency and less prone to single-point failures. Unfortunately, such a training mode is more vulnerable to data privacy leaks compared to other distributed training frameworks. Existing efforts exclusively use diffe

Wang Yan-Ling, Chen Wei, Li Mao-Sheng

A set of orthogonal states in multipartite systems is called to be locally stable if to preserving the orthogonality of the states, only trivial local measurement can be performed from each partite. Locally stable set of states are always locally indistinguishable yielding a form of nonlocality which is different from the Bell type nonlocality. In this work,

Xinyu Lyu, Lianli Gao, Pengpeng Zeng, Heng Tao Shen

The performance of current Scene Graph Generation (SGG) models is severely hampered by hard-to-distinguish predicates, e.g., woman-on/standing on/walking on-beach. As general SGG models tend to predict head predicates and re-balancing strategies prefer tail categories, none of them can appropriately handle hard-to-distinguish predicates. To tackle this issue

Chongjun Ouyang, Hao Xu, Xujie Zang, Hongwen Yang

Physical layer (PHY) security in decode-and-forward (DF) relay systems is discussed. Based on the types of wiretap links, the secrecy performance of three typical secure DF relay models is analyzed. Different from conventional works in this field, rigorous derivations of the secrecy channel capacity are provided from an information-theoretic perspective. Mea

Zhongyuan Lyu, Dong Xia

This paper investigates the computational and statistical limits in clustering matrix-valued observations. We propose a low-rank mixture model (LrMM), adapted from the classical Gaussian mixture model (GMM) to treat matrix-valued observations, which assumes low-rankness for population center matrices. A computationally efficient clustering method is designed

Saieed Akbari, Hossein Dabirian, S. Mahmood Ghasemi

Let $G$ be a graph of order $n$ with adjacency matrix $A(G)$. The \textit{energy} of graph $G$, denoted by $\mathcal{E}(G)$, is defined as the sum of absolute value of eigenvalues of $A(G)$. It was conjectured that if $A(G)$ is non-singular, then $\mathcal{E}(G)\geq\Delta(G)+\delta(G)$. In this paper we propose a stronger conjecture as for $n \geq 5$, $\math

Peter F. Halpin

This paper proposes a method for assessing differential item functioning (DIF) in item response theory (IRT) models. The method does not require pre-specification of anchor items, which is its main virtue. It is developed in two main steps, first by showing how DIF can be re-formulated as a problem of outlier detection in IRT-based scaling, then tackling the

Liu-Jun Guo, Hai Xu, Zi-Yu Fang, Tao Chen

Geometric quantum gates are performed by using the geometric phase, making them particularly robust to the pulse amplitude error due to the intrinsic global property. However, in many systems, such as the silicon-based spin qubits, the off-resonance error is the dominant noise, which can cause dephasing and is always difficult to deal with for a geometric ga

Zhaowei Chang, Jianhua Zhang, Pan Tang, Lei Tian

Terahertz (THz) channel propagation characteristics are vital for the design, evaluation, and optimization for THz communication systems. Moreover, reflection plays a significant role in channel propagation. In this letter, the reflection coefficient of the THz channel is researched based on extensive measurement campaigns. Firstly, we set up the THz channel

Giuseppe Storti, Chao Wang

We develop a novel multivariate semi-parametric framework for joint portfolio Value-at-Risk (VaR) and Expected Shortfall (ES) forecasting. Unlike existing univariate semi-parametric approaches, the proposed framework explicitly models the dependence structure among portfolio asset returns through a dynamic conditional correlation (DCC) parameterization. To e

Nader Alfares, George Kesidis, Ata Fatahi Baarzi, Aman Jain

Over the past ten years, many different approaches have been proposed for different aspects of the problem of resources management for long running, dynamic and diverse workloads such as processing query streams or distributed deep learning. Particularly for applications consisting of containerized microservices, researchers have attempted to address problem

Zhi-Wei Wang, Samuel L. Braunstein

Port-based teleportation (PBT) is a variation of regular quantum teleportation that operates without a final unitary correction. However, its behavior for higher-dimensional systems has been hard to calculate explicitly beyond dimension $d=2$. Indeed, relying on conventional Hilbert-space representations entails an exponential overhead with increasing dimens

Hai-Liang Chen, Xuefei Chen, Zhanwen Han

The evolution and stability of mass transfer of CO+He WD binaries are not well understood. Observationally they may emerge as AM CVn binaries and are important gravitational wave (GW) emitters. In this work, we have modeled the evolution of double WD binaries with accretor masses of $0.50 - 1.30\;M_{\odot}$ and donor masses of $0.17\; - 0.45\;M_{\odot}$ usin

Nathan J. Kong, Chuanzheng Li, Aaron M. Johnson

Model Predictive Control (MPC) is a popular strategy for controlling robots but is difficult for systems with contact due to the complex nature of hybrid dynamics. To implement MPC for systems with contact, dynamic models are often simplified or contact sequences fixed in time in order to plan trajectories efficiently. In this work, we extend Hybrid iterativ

Po-Ning Chen, Daniel Paraizo, Robert M. Wald, Mu-Tao Wang

We introduce a notion of "cross-section continuity" as a criterion for the viability of definitions of angular momentum, $J$, at null infinity: If a sequence of cross-sections, ${\mathcal C}_n$, of null infinity converges uniformly to a cross-section ${\mathcal C}$, then the angular momentum, $J_n$, on ${\mathcal C}_n$ should converge to the angular momentum

Huairui Wang, Zhenzhong Chen, Chang Wen Chen

Learned video compression has recently emerged as an essential research topic in developing advanced video compression technologies, where motion compensation is considered one of the most challenging issues. In this paper, we propose a learned video compression framework via heterogeneous deformable compensation strategy (HDCVC) to tackle the problems of un

Cathy Shyr, Pragya Sur, Giovanni Parmigiani, Prasad Patil

Cross-study replicability is a powerful model evaluation criterion that emphasizes generalizability of predictions. When training cross-study replicable prediction models, it is critical to decide between merging and treating the studies separately. We study boosting algorithms in the presence of potential heterogeneity in predictor-outcome relationships acr

Hong-You Chen, Wei-Lun Chao

The effectiveness of unsupervised domain adaptation degrades when there is a large discrepancy between the source and target domains. Gradual domain adaptation (GDA) is one promising way to mitigate such an issue, by leveraging additional unlabeled data that gradually shift from the source to the target. Through sequentially adapting the model along the "ind

Zhi Li, Yitao Bo, Hongbin Xiao

In recent years, microservice architecture has become a popular architectural style in software engineering, with its natural support for DevOps and continuous delivery, as well as its scalability and extensibility, which drive industry practitioners to migrate to microservice architecture. However, there are many challenges in adopting a microservice archit

Hamid Niknazar, Sara C. Mednick

In recent years, deep learning has shown potential and efficiency in a wide area including computer vision, image and signal processing. Yet, translational challenges remain for user applications due to a lack of interpretability of algorithmic decisions and results. This black box problem is particularly problematic for high-risk applications such as medica

Hao Wang, Ce Yu, Jian Xiao, Shanjiang Tang

The challenge to fully exploit the potential of existing and upcoming scientific instruments like large single-dish radio telescopes is to process the collected massive data effectively and efficiently. As a "quasi 2D stencil computation" with the "Moore neighborhood pattern," gridding is the most computationally intensive step in data reduction pipeline for

L. -M. Duan

We propose a scalable design of entangling quantum gates for large ion crystals with the following desirable features: 1) The gate design is universal and applicable for large ion crystals of arbitrary sizes; 2) The gate has no speed limitation and can work outside of the Lamb-Dicke region; 3) The gate operates by driving from either continuous-wave or pulse

Rui Fu, Olga Movilla Miangolarra, Amirhossein Taghvaei, Yongxin Chen

In the present paper, we study the power output and efficiency of overdamped stochastic thermodynamic engines that are in contact with a heat bath having a temperature that varies periodically with time. This is in contrast to most of the existing literature that considers the Carnot paradigm of alternating contact with heat baths having different fixed temp

Jingjing Xu, Jia Zhao, Yanxiang Zhao

The physics informed neural networks (PINNs) has been widely utilized to numerically approximate PDE problems. While PINNs has achieved good results in producing solutions for many partial differential equations, studies have shown that it does not perform well on phase field models. In this paper, we partially address this issue by introducing a modified ph

Edward Small, Wei Shao, Zeliang Zhang, Peihan Liu

With the introduction of machine learning in high-stakes decision making, ensuring algorithmic fairness has become an increasingly important problem to solve. In response to this, many mathematical definitions of fairness have been proposed, and a variety of optimisation techniques have been developed, all designed to maximise a defined notion of fairness. H

Shashank Menon, Xiaoyu Song

The large-deformation mechanics and multiphysics of continuous or fracturing partially saturated porous media under static and dynamic loads are significant in engineering and science. This article is devoted to a computational coupled large-deformation periporomechanics paradigm assuming passive air pressure for modeling dynamic failure and fracturing in va

Leping Li, Hardi Peter, Lakshmi Pradeep Chitta, Hongqiang Song

Both observations and simulations suggest that the solar filament eruption is closely related to magnetic flux emergence. It is thought that the eruption is triggered by magnetic reconnection between the filament and the emerging flux. However, the details of such a reconnection are rarely presented. In this study, we report the detailed reconnection between

Anais Möller, Thibault de Boissière

Upcoming surveys such as the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) will detect up to 10 million time-varying sources in the sky every night for ten years. This information will be transmitted in a continuous stream to brokers that will select the most promising events for a variety of science cases using machine learning algorithms

Pengfei Ding, Yan Wang, Guanfeng Liu, Xiaofang Zhou

Semantic relation prediction aims to mine the implicit relationships between objects in heterogeneous graphs, which consist of different types of objects and different types of links. In real-world scenarios, new semantic relations constantly emerge and they typically appear with only a few labeled data. Since a variety of semantic relations exist in multipl

J. Menezes, B. Moura, E. Rangel

We study the generalised rock-paper-scissors game with five species whose organisms face local epidemic outbreaks. As an evolutionary behavioural survival strategy, organisms of one out of the species move in the direction with more enemies of their enemies to benefit from protection against selection. We consider that each organism scans the environment, pe

Steven V Sam, Andrew Snowden

A representation of $\mathfrak{gl}(V)=V \otimes V^*$ is a linear map $\mu \colon \mathfrak{gl}(V) \otimes M \to M$ satisfying a certain identity. By currying, giving a linear map $\mu$ is equivalent to giving a linear map $a \colon V \otimes M \to V \otimes M$, and one can translate the condition for $\mu$ to be a representation to a condition on $a$. This a

Kunni Lin, Jiawei Peng, Chao Xu, Feng Long Gu

The supervised machine learning (ML) approach is applied to realize the trajectory-based nonadiabatic dynamics within the framework of the symmetrical quasi-classical dynamics method based on the Meyer-Miller mapping Hamiltonian (MM-SQC). After the construction of the long short-term memory recurrent neural network (LSTM-RNN) model, it is used to perform the

Kaikai Zhao, Yajie Cui, Zhaoxiang Liu, Shiguo Lian

In the field of waste copper granules recycling, engineers should be able to identify all different sorts of impurities in waste copper granules and estimate their mass proportion relying on experience before rating. This manual rating method is costly, lacking in objectivity and comprehensiveness. To tackle this problem, we propose a waste copper granules r

Mehmet Saygın Seyfioğlu, Zixuan Liu, Pranav Kamath, Sadjyot Gangolli

We propose a novel framework for Alzheimer's disease (AD) detection using brain MRIs. The framework starts with a data augmentation method called Brain-Aware Replacements (BAR), which leverages a standard brain parcellation to replace medically-relevant 3D brain regions in an anchor MRI from a randomly picked MRI to create synthetic samples. Ground truth "ha

Kuang-Yu Wu

We consider slope stability of the canonical extension of the tangent bundle by the trivial line bundle and with the extension class c_1(T_X) on Picard-rank-1 Fano varieties. In cases where the index divides the dimension or the dimension plus one, we show that stability of the tangent bundle implies (semi)stability of the canonical extension. One consequenc

Brandon M. Roach, Steven Rossland, Kenny C. Y. Ng, Kerstin Perez

We present two complementary NuSTAR x-ray searches for keV-scale dark matter decaying to mono-energetic photons in the Milky Way halo. In the first, we utilize the known intensity pattern of unfocused stray light across the detector planes -- the dominant source of photons from diffuse sources -- to separate astrophysical emission from internal instrument ba

Liuxian Zhao, Miao Yu

In this paper, a novel gradient index (GRIN) structural lens based on the concept of generalized Luneburg lens (GLL) is proposed. This lens allows for the realization of double foci and localization of energy flow between the two focal spots, thereby achieving ultralong focusing. The double-foci GRIN lens consists of two concentric circular regions with vary

Masahico Saito, Emanuele Zappala

A rack is a set with a binary operation that is right-invertible and self-distributive, properties diagrammatically corresponding to Reidemeister moves II and III, respectively. A rack is said to be an {\it augmented rack} if the operation is written by a group action. Racks and their cohomology theories have been extensively used for knot and knotted surfac

Yijie Shen, Bingshi Yu, Haijun Wu, Chunyu Li

Structured light fields embody strong spatial variations of polarisation, phase and amplitude. Understanding, characterization and exploitation of such fields can be achieved through their topological properties. Three-dimensional (3D) topological solitons, such as hopfions, are 3D localized continuous field configurations with nontrivial particle-like struc

Ammar Tahir, Yongzhou Chen, Prashanti Nilayam

Federated learning provides the ability to learn over heterogeneous user data in a distributed manner while preserving user privacy. However, its current client selection technique is a source of bias as it discriminates against slow clients. For starters, it selects clients that satisfy certain network and system-specific criteria, thus not selecting slow c

Xiangting Li, Tom Chou

Under certain cellular conditions, transcription and mRNA translation in prokaryotes appear to be "coupled," in which the formation of mRNA transcript and production of its associated protein are temporally correlated. Such transcription-translation coupling (TTC) has been evoked as a mechanism that speeds up the overall process, provides protection during t

Zhongqian Wang, Shubin Fu, Zishang Li, Eric Chung

In this paper, we develop a local multiscale model reduction strategy for the elastic wave equation in strongly heterogeneous media, which is achieved by solving the problem in a coarse mesh with multiscale basis functions. We use the interior penalty discontinuous Galerkin (IPDG) to couple the multiscale basis functions that contain important heterogeneous

John C. Barentine, Jessica Heim, Aparna Venkatesan, James Lowenthal

Our planet and our species are at an existential crossroads. In the long term, climate change threatens to upend life as we know it, while the ongoing COVID-19 pandemic revealed that the world is unprepared and ill-equipped to handle acute shocks to its many systems. These shocks exacerbate the inequities and challenges already present prior to COVID in ways

Renke Wang, Ifeoma Nwogu

Natural conversations between humans often involve a large number of non-verbal nuanced expressions, displayed at key times throughout the conversation. Understanding and being able to model these complex interactions is essential for creating realistic human-agent communication, whether in the virtual or physical world. As social robots and intelligent avat

Kleanthis Avramidis, Mohammad Rostami, Melinda Chang, Shrikanth Narayanan

Papilledema is an ophthalmic neurologic disorder in which increased intracranial pressure leads to swelling of the optic nerves. Undiagnosed papilledema in children may lead to blindness and may be a sign of life-threatening conditions, such as brain tumors. Robust and accurate clinical diagnosis of this syndrome can be facilitated by automated analysis of f

Quanyu Long, Tianze Luo, Wenya Wang, Sinno Jialin Pan

In this work, we study Unsupervised Domain Adaptation (UDA) in a challenging self-supervised approach. One of the difficulties is how to learn task discrimination in the absence of target labels. Unlike previous literature which directly aligns cross-domain distributions or leverages reverse gradient, we propose Domain Confused Contrastive Learning (DCCL) to

Sina Abedi, A. Hamed Majedi

Graphene can be magnetized through nonlinear response of its orbital angular momentum to an intense circularly polarized light. This optomagnetic effect can be well exemplified by the Inverse Faraday Effect (IFE) where an optically-generated DC magnetization leads to graphene's optical activity. We provide a single-particle quantum mechanical model of an IFE

Frank Julicher, Jacques Prost, John Toner

We show that dislocations in active 2d smectics with underlying rotational symmetry are always unbound in the presence of noise, meaning the active smectic phase does not exist for non-zero noise in $d=2$. The active smectic phase can, like equilibrium smectics in 2d, be stabilized by applying rotational symmetry breaking fields; however, even in the presenc

Kareem T. Elgindy

In its simplest form, a chemostat consists of microorganisms or cells that grow continually in a specific phase of growth while competing for a single limiting nutrient. Under certain conditions of the cell growth rate, substrate concentration, and dilution rate, the theory predicts and numerical experiments confirm that a periodically operated chemostat exh

Frank Hernandez, Ernesto Parra, Jose Maria Sigarreta, Nodari Vakhania

A {\em dominating set} of a graph $G=(V,E)$ is a subset of vertices $S\subseteq V$ such that every vertex $v\in V\setminus S$ has at least one neighbor in $S$. Finding a dominating set with the minimum cardinality in a connected graph $G=(V,E)$ is known to be NP-hard. A polynomial-time approximation algorithm for this problem, described here, works in two st

J. Furtado, C. R. Muniz, M. S. Cunha, J. E. G. Silva

In this paper we study the possibility of non-relativistic quantum particles to traverse the generalized Ellis-Bronnikov wormholes by considering quantum effects, such as tunneling. We have used the generalized Ellis-Bronnikov wormhole metric and found that for $n=2$ we have a single barrier shaped effective potential centered at the throat of the wormhole f

P. G. Bolhuis, Z. F. Brotzakis, B. G. Keller

Empirical force fields employed in molecular dynamics simulations of complex systems can be optimised to reproduce experimentally determined structural and thermodynamic properties. In contrast, experimental knowledge about the rates of interconversion between metastable states in such systems, is hardly ever incorporated in a force field, due to a lack of a

Sai Praneeth Karimireddy, Wenshuo Guo, Michael I. Jordan

Federated learning is typically considered a beneficial technology which allows multiple agents to collaborate with each other, improve the accuracy of their models, and solve problems which are otherwise too data-intensive / expensive to be solved individually. However, under the expectation that other agents will share their data, rational agents may be te

Tarek M. Elgindi, Karim R. Shikh Khalil

We prove strong ill-posedness in $L^{\infty}$ for linear perturbations of the 2d Euler equations of the form: \[\partial_t \omega + u\cdot\nabla\omega = R(\omega),\] where $R$ is any non-trivial second order Riesz transform. Namely, we prove that there exist smooth solutions that are initially small in $L^{\infty}$ but become arbitrarily large in short time.

Alexander Rogozin, Demyan Yarmoshik, Ksenia Kopylova, Alexander Gasnikov

Decentralized optimization is a common paradigm used in distributed signal processing and sensing as well as privacy-preserving and large-scale machine learning. It is assumed that several computational entities locally hold objective functions and are connected by a network. The agents aim to commonly minimize the sum of the local objectives subject by maki

Guillem Tarrach

We study the $S$-arithmetic (co)homology of reductive groups over number fields with coefficients in (duals of) certain locally algebraic and locally analytic representations for finite sets of primes $S$. We use our results to construct eigenvarieties associated to parabolic subgroups at places in $S$ and certain classes of supercuspidal and algebraic repre

Sara R. Heap, I. Hubeny, J. -C. Bouret, T. Lanz

We report on a study of 9 nearby star-forming, very low-metallicity galaxies observed by Hubble's COS far-UV spectrograph that can serve as templates of high-z galaxies to be observed by JWST. We find that the nebular spectra of these primitive galaxies show evidence of irradiation by X-ray emitters. Following Thuan et al. (2004), we identify the sources of

Zhizhang Wang, Ling Xiao

In this paper, we study the $\sigma_k$ curvature flow of noncompact spacelike hypersurfaces in Minkowski space. We prove that if the initial hypersurface satisfies certain conditions, then the flow exists for all time. Moreover, we show that after rescaling, the flow converges to a self-expander.

Kha Gia Quach, Huu Le, Pha Nguyen, Chi Nhan Duong

This paper aims to tackle Multiple Object Tracking (MOT), an important problem in computer vision but remains challenging due to many practical issues, especially occlusions. Indeed, we propose a new real-time Depth Perspective-aware Multiple Object Tracking (DP-MOT) approach to tackle the occlusion problem in MOT. A simple yet efficient Subject-Ordered Dept

Boxiao Chen, Jiashuo Jiang, Jiawei Zhang, Zhengyuan Zhou

We consider a stochastic lost-sales inventory control system with a lead time $L$ over a planning horizon $T$. Supply is uncertain, and is a function of the order quantity (due to random yield/capacity, etc). We aim to minimize the $T$-period cost, a problem that is known to be computationally intractable even under known distributions of demand and supply.

Bradford A. Barker, David A. Strubbe

Open-shell systems such as magnetic molecules or defects with a triplet ground state are challenging to describe in electronic structure methods, but are of great interest for quantum information applications. We demonstrate a spin-flip approach within the Bethe-Salpeter equation to calculate ground and excited states of open-shell molecules and defected sol

Aurélien Bourquard, Jeff Yan

We motivate and develop a new line of digital forensics. In the meanwhile, we propose a novel approach to photographer identification, a rarely explored authorship attribution problem. We report a proof-of-concept study, which shows the feasibility of our method. Our contributions include a new forensic method for photographer de-anonymization and revealing

Antonio Rodrigues, Peter Steenkiste, Ana Aguiar

Vehicles access the Internet via cellular networks, instead of Wi-Fi networks. This choice has been mostly justified by the ubiquitous coverage of cellular networks: Wi-Fi coverage has been shown to be inadequate in the past, even in urban areas. We argue that providing Internet connectivity to vehicles via Wi-Fi is worth a revisit. Motivated by improvements

Pieter Delobelle, Bettina Berendt

Large pre-trained language models are successfully being used in a variety of tasks, across many languages. With this ever-increasing usage, the risk of harmful side effects also rises, for example by reproducing and reinforcing stereotypes. However, detecting and mitigating these harms is difficult to do in general and becomes computationally expensive when

Alan Kostelecky, E. Passemar, N. Sherrill

Lorentz- and CPT-violating effects initiating two-body electromagnetic flavor-changing decays of charged leptons are studied in the framework of Lorentz-violating effective field theory. An analysis of data from experiments at the Paul Scherrer Institute and at the Stanford Linear Accelerator measuring the branching ratios of these decays provides 576 constr

Mireille Boutin, Gregor Kemper

Assume that a source emits a signal in $3$-dimensional space at an unknown time, which is received by at least~$5$ sensors. In almost all cases the emission time and source position can be worked out uniquely from the knowledge of the times when the sensors receive the signal. The task to do so is the multilateration problem. But when there are several emiss

Ateia W. Mahmoud, Elsayed K. Elmaghraby, E. Salama, A. Elghazaly

The absorption of neutrons in media together with its transport properties cause the neutron flux to decrease as it penetrates the material because the absorption of neutrons in the sample itself attenuates the neutrons flux as it goes deeper into the sample. In the present work, the thermal neutron self-shielding factors of indium, gold, zinc, and mercury w

Timothée Lesort, Oleksiy Ostapenko, Diganta Misra, Md Rifat Arefin

Building learning agents that can progressively learn and accumulate knowledge is the core goal of the continual learning (CL) research field. Unfortunately, training a model on new data usually compromises the performance on past data. In the CL literature, this effect is referred to as catastrophic forgetting (CF). CF has been largely studied, and a pletho

Keith Hawkins

Chemical Cartography, or mapping, of our Galaxy has the potential to fully transform our view of its structure and formation. In this work, we use chemical cartography to explore the metallicity distribution of OBAF-type disk stars from the LAMOST survey and a complementary sample of disk giant stars from Gaia DR3. We use these samples to constrain the radia

Riccardo Arpaia, Núria Alcalde-Herraiz, Andrea D'Alessio, Evgeny Stepantsov

In underdoped cuprate high $T_{\mathrm{c}}$ superconductors, various local orders and symmetry breaking states, in addition to superconductivity, reside in the CuO$_2$ planes. The confinement of the CuO$_2$ planes can therefore play a fundamental role in modifying the hierarchy between the various orders and their intertwining with superconductivity. Here we

Mufan Sang, John H. L. Hansen

Recently, attention mechanisms have been applied successfully in neural network-based speaker verification systems. Incorporating the Squeeze-and-Excitation block into convolutional neural networks has achieved remarkable performance. However, it uses global average pooling (GAP) to simply average the features along time and frequency dimensions, which is in

Han Yue, Steve Xia, Hongfu Liu

Corporate credit ratings issued by third-party rating agencies are quantified assessments of a company's creditworthiness. Credit Ratings highly correlate to the likelihood of a company defaulting on its debt obligations. These ratings play critical roles in investment decision-making as one of the key risk factors. They are also central to the regulatory fr

Lionel Bureau, Gwennou Coupier, Thomas Salez

Lift forces are widespread in hydrodynamics. These are typically observed for big and fast objects, and are often associated with a combination of fluid inertia (i.e. large Reynolds numbers) and specific symmetry-breaking mechanisms. In contrast, the properties of viscosity-dominated (i.e. low Reynolds numbers) flows make it more difficult for such lift forc

Shrawan Kumar, Jiale Xie

For any reductive group $G$ and a parabolic subgroup $P$ with its Levi subgroup $L$, the first author [Ku2] introduced a ring homomorphism $ \xi^P_\lambda: Rep^\mathbb{C}_{\lambda-poly}(L) \to H^*(G/P, \mathbb{C})$, where $ Rep^\mathbb{C}_{\lambda-poly}(L)$ is a certain subring of the complexified representation ring of $L$ (depending upon the choice of an i

Maciej Bartłomiej Kruk, Dawid Hryniuk, Mick Kristensen, Toke Vibel

The fluctuations of the atom number between a Bose-Einstein condensate and the surrounding thermal gas have been the subject of a long standing theoretical debate. This discussion is centered around the appropriate thermodynamic ensemble to be used for theoretical predictions and the effect of interactions on the observed fluctuations. Here we introduce the

Ashutosh Agarwal, Chetan Arora

Attention-based models such as transformers have shown outstanding performance on dense prediction tasks, such as semantic segmentation, owing to their capability of capturing long-range dependency in an image. However, the benefit of transformers for monocular depth prediction has seldom been explored so far. This paper benchmarks various transformer-based

Stefano Cerri, Douglas N. Greve, Andrew Hoopes, Henrik Lundell

In this paper we describe and validate a longitudinal method for whole-brain segmentation of longitudinal MRI scans. It builds upon an existing whole-brain segmentation method that can handle multi-contrast data and robustly analyze images with white matter lesions. This method is here extended with subject-specific latent variables that encourage temporal c

Fabian Kislat

Astrophysical polarization measurements provide some of the strongest constraints on the photon sector of the non-minimal Standard-Model Extension. This paper reviews some recent results obtained by combining optical linear and circular polarization data from a large number of astrophysical objects.

Sergey E. Mikhailov

First, the solution uniqueness, existence and regularity for stationary anisotropic (linear) Stokes and generalised Oseen systems with constant viscosity coefficients in a compressible framework are analysed in a range of periodic Sobolev (Bessel-potential) spaces on $n$-dimensional flat torus. By the Galerkin algorithm, the linear results are employed to sh

Andrea Santi, Dennis The

For the largest exceptional simple Lie superalgebra $F(4)$, having dimension $(24|16)$, we provide two explicit geometric realizations as supersymmetries, namely as the symmetry superalgebra of super-PDE systems of second and third order respectively.

Jonathan F. Schonfeld

The Mott problem asks: Is there a microphysical mechanism - based only on Schroedinger's equation - that explains why an alpha particle emitted in a spherically symmetric nuclear decay produces a non-spherically-symmetric single track in a cloud chamber? This is a variant of the more general quantum measurement problem. Earlier, I proposed such a mechanism,

Niseem Magdy

Recently studies of the differential nature of the flow angle fluctuations, known as event plane angular decorrelation, indicated that measurements that assume a common symmetry plane may need to consider the flow angle fluctuations effect. Using the HIJING and AMPT models, it is shown that the flow angle fluctuations measurements, obtained with the two- and

Damien Dablain, Lilian Huang, Brandon Sepulvado

Synthetic biology is an emerging field that involves the engineering and re-design of organisms for purposes such as food security, health, and environmental protection. As such, it poses numerous ethical, legal, and social implications (ELSI) for researchers and policy makers. Various efforts to ensure socially responsible synthetic biology are underway. Po

Asvin G, Andrew O'Desky

We introduce a generalization of symmetric functions and apply the resulting theory to compute the class in the Grothendieck ring of varieties of the space of geometrically irreducible hypersurfaces of a fixed degree in projective space.

Nawaf Nazir, Mads Almassalkhi

This paper presents a market-based optimization framework wherein Aggregators can compete for nodal capacity across a distribution feeder and guarantee that allocated flexible capacity cannot cause overloads or congestion. This mechanism, thus, allows Aggregators with allocated capacity to pursue a number of services at the whole-sale market level to maximiz

Fred Cooper, Avinash Khare, Efstathios G. Charalampidis, John F. Dawson

In this work, we consider the nonlinear Schr\"odinger equation (NLSE) in $2+1$ dimensions with arbitrary nonlinearity exponent $\kappa$ in the presence of an external confining potential. Exact solutions to the system are constructed, and their stability over their "mass" (i.e., the $L^2$ norm) and the parameter $\kappa$ is explored. We observe both theoreti

Daniel Seichter, Söhnke Benedikt Fischedick, Mona Köhler, Horst-Michael Groß

Semantic scene understanding is essential for mobile agents acting in various environments. Although semantic segmentation already provides a lot of information, details about individual objects as well as the general scene are missing but required for many real-world applications. However, solving multiple tasks separately is expensive and cannot be accompl

Nicholas Carrara

The following three sections and appendices are taken from my thesis "The Foundations of Inference and its Application to Fundamental Physics" from 2021, in which I construct a theory of entropic inference from first principles. The majority of these chapters are not original, but are a collection of various sources through the history of the subject. The fi

Zhiyuan Geng, Arghir Zarnescu

For the Landau-de Gennes functional on 3D domains, \begin{equation*} I_{\varepsilon}(Q,\Omega):=\int_{\Omega}\left\{\frac{1}{2}|\nabla Q|^2+\frac{1}{\varepsilon^2}\left( -\frac{a^2}{2}\mathrm{tr}(Q^2)-\frac{b^2}{3}\mathrm{tr}(Q^3)+\frac{c^2}{4}[\mathrm{tr}(Q^2)]^2 \right) \right\}\,dx, \end{equation*} it is well-known that under suitable boundary conditions,

Rukaiya Khatoon, Zahir Shah, Jyotishree Hota, Ranjeev Misra

We have performed a detailed analysis of the X-ray spectra of the blazar Mkn 421 using Swift-XRT observations taken between 2005 and 2020, to quantify the correlations between spectral parameters for different models. In an earlier work, it has been shown that such spectral parameter correlations obtained from a single short flare of duration $\sim$ 5-days o

Manuel Knott, Fernando Perez-Cruz, Thijs Defraeye

Image-based machine learning models can be used to make the sorting and grading of agricultural products more efficient. In many regions, implementing such systems can be difficult due to the lack of centralization and automation of postharvest supply chains. Stakeholders are often too small to specialize in machine learning, and large training data sets are

Iwan Duursma, Ryan Gabrys, Venkatesan Guruswami, Ting-Chun Lin

Polarization is an unprecedented coding technique in that it not only achieves channel capacity, but also does so at a faster speed of convergence than any other coding technique. This speed is measured by the ``scaling exponent'' and its importance is three-fold. Firstly, estimating the scaling exponent is challenging and demands a deeper understanding of t

Hassan Y. El Arsh, Amr Abdelaziz, Ahmed Elliethy, Hussein A. Aly

Steganography in multimedia aims to embed secret data into an innocent looking multimedia cover object. This embedding introduces some distortion to the cover object and produces a corresponding stego object. The embedding distortion is measured by a cost function that determines the detection probability of the existence of the embedded secret data. A cost

Udayan Mandal, Amelia Regan, Julian Yarkony

We consider an approach for improving the efficiency of column generation (CG) methods for solving vehicle routing problems. We introduce Local Area (LA) route relaxations, an alternative/complement to the commonly used ng-route relaxations and Decremental State Space Relaxations (DSSR) inside of CG formulations. LA routes are a subset of ng-routes and a sup

Z. P. Ye, F. Hu, W. Tian, Q. C. Chang

Next-generation neutrino telescopes with significantly improved sensitivity are required to pinpoint the sources of the diffuse astrophysical neutrino flux detected by IceCube and uncover the century-old puzzle of cosmic ray origins. A detector near the equator will provide a unique viewpoint of the neutrino sky, complementing IceCube and other neutrino tele

Harold McQuaid, David Rutherford, Davide Mariotti, Paul Maguire

We demonstrate a new gas-based OH generation source using a low power RF-driven atmospheric pressure plasma configured to deliver the radical flux into the far effluent region, well away from interference from other plasma factors such as electric fields, currents, and UV radiation. Using He-H2O gas chemistry isolated from the laboratory air, the plasma gene

Astghik Saharyan, Benjamin Rousseaux, Zsolt Kis, Sergiy Stryzhenko

Over the last decades, quantum optics has evolved from high quality factor cavities in the early experiments toward new cavity designs involving leaky modes. Despite very reliable models, in the concepts of cavity quantum electrodynamics, photon leakage is most of the time treated phenomenologically. Here, we take a different approach, and starting from firs

Evgeny Akhmedov, Pablo Martínez-Miravé

The interaction of neutrino transition magnetic dipole moments with magnetic fields can give rise to the phenomenon of neutrino spin-flavour precession (SFP). For Majorana neutrinos, the combined action of SFP of solar neutrinos and flavour oscillations would manifest itself as a small, yet potentially detectable, flux of electron antineutrinos coming from t

Holger Eichelberger, Gregory Palmer, Svenja Reimer, Tat Trong Vu

For a broader adoption of AI in industrial production, adequate infrastructure capabilities are crucial. This includes easing the integration of AI with industrial devices, support for distributed deployment, monitoring, and consistent system configuration. Existing IIoT platforms still lack required capabilities to flexibly integrate reusable AI services an

Akshay Gupte, Yiran Zhu

Computing the maximum size of an independent set in a graph is a famously hard combinatorial problem that has been well-studied for various classes of graphs. When it comes to random graphs, only the classical Erd\H{o}s-R\'enyi-Gilbert random graph $G_{n,p}$ has been analysed and shown to have largest independent sets of size $\Theta(\log{n})$ w.h.p. This cl