January 2022 arXiv papers — page 43

A. N. Kosarev, A. V. Trifonov, I. A. Yugova, I. I. Yanibekov

The ability to extend the time scale of the coherent optical response from large ensembles of quantum emitters is highly appealing for applications in quantum information devices. In semiconductor nanostructures, spin degrees of freedom can be used as auxiliary, powerful tools to modify the coherent optical dynamics. Here, we apply this approach to negativel

Ahsan Waqas, Khoa Nguyen, Gottfried Lechner, Terence Chan

This paper presents an algorithm for iterative joint channel parameter (carrier phase, Doppler shift and Doppler rate) estimation and decoding of transmission over channels affected by Doppler shift and Doppler rate using a distributed receiver. This algorithm is derived by applying the sum-product algorithm (SPA) to a factor graph representing the joint a p

Andrés Villa, Kumail Alhamoud, Juan León Alcázar, Fabian Caba Heilbron

Continual learning (CL) is under-explored in the video domain. The few existing works contain splits with imbalanced class distributions over the tasks, or study the problem in unsuitable datasets. We introduce vCLIMB, a novel video continual learning benchmark. vCLIMB is a standardized test-bed to analyze catastrophic forgetting of deep models in video cont

Tat Dat Tô

In this note, we study a degenerate twisted J-flow on compact K\"ahler manifolds. We show that it exists for all time, it is unique and converges to a weak solution of a degenerate twisted J-equation. In particular, this confirms an expectation formulated by Song-Weinkove for the J-flow. As a consequence, we establish the properness of the Mabuchi K-energy t

Manuela Aguiar, Christian Bick, Ana Dias

Network interactions that are nonlinear in the state of more than two nodes - also known as higher-order interactions - can have a profound impact on the collective network dynamics. Here we develop a coupled cell hypernetwork formalism to elucidate the existence and stability of (cluster) synchronization patterns in network dynamical systems with higher-ord

Mauricio A. Londoño, Francisco J. Rodríguez-Cortés

Full waveform inversion (FWI) is one of a family of methods that allows the reconstruction of earth subsurface parameters from measurements of waves at or near the surface. This is a numerical optimization problem that uses the whole waveform information of all arrivals to update the subsurface parameters that govern seismic wave propagation. We apply FWI in

Darren Abramson, Ali Emami

Language models built using semi-supervised machine learning on large corpora of natural language have very quickly enveloped the fields of natural language generation and understanding. In this paper we apply a zero-shot approach independently developed by a number of researchers now gaining recognition as a significant alternative to fine-tuning for evalua

Pengfei Guo, Yiqun Mei, Jinyuan Zhou, Shanshan Jiang

Accelerating magnetic resonance image (MRI) reconstruction process is a challenging ill-posed inverse problem due to the excessive under-sampling operation in k-space. In this paper, we propose a recurrent transformer model, namely ReconFormer, for MRI reconstruction which can iteratively reconstruct high fertility magnetic resonance images from highly under

Dongdong Chen, Mike E. Davies, Mohammad Golbabaee

Magnetic Resonance Fingerprinting (MRF) has emerged as a promising quantitative MR imaging approach. Deep learning methods have been proposed for MRF and demonstrated improved performance over classical compressed sensing algorithms. However many of these end-to-end models are physics-free, while consistency of the predictions with respect to the physical fo

Long B. Nguyen, Gerwin Koolstra, Yosep Kim, Alexis Morvan

The technological development of hardware heading toward universal fault-tolerant quantum computation requires a large-scale processing unit with high performance. While fluxonium qubits are promising with high coherence and large anharmonicity, their scalability has not been systematically explored. In this work, we propose a superconducting quantum informa

Jie Mei, Jingxi Yu, Suzanne Romain, Craig Rose

Much progress has been made in the supervised learning of 3D reconstruction of rigid objects from multi-view images or a video. However, it is more challenging to reconstruct severely deformed objects from a single-view RGB image in an unsupervised manner. Although training-based methods, such as specific category-level training, have been shown to successfu

Isaac Slavitt

Lead pipe remediation budgets are limited and ought to maximize public health impact. This goal implies a non-trivial optimization problem; lead service lines connect water mains to individual houses, but any realistic replacement strategy must batch replacements at a larger scale. Additionally, planners typically lack a principled method for comparing the r

Tsung-Hung Yao, Zhenke Wu, Karthik Bharath, Jinju Li

Accurate identification of synergistic treatment combinations and their underlying biological mechanisms is critical across many disease domains, especially cancer. In translational oncology research, preclinical systems such as patient-derived xenografts (PDX) have emerged as a unique study design evaluating multiple treatments administered to samples from

Shagufta Mehnaz, Sayanton V. Dibbo, Ehsanul Kabir, Ninghui Li

Increasing use of machine learning (ML) technologies in privacy-sensitive domains such as medical diagnoses, lifestyle predictions, and business decisions highlights the need to better understand if these ML technologies are introducing leakage of sensitive and proprietary training data. In this paper, we focus on model inversion attacks where the adversary

Mark Beliaev, Payam Delgosha, Hamed Hassani, Ramtin Pedarsani

In the past two decades we have seen the popularity of neural networks increase in conjunction with their classification accuracy. Parallel to this, we have also witnessed how fragile the very same prediction models are: tiny perturbations to the inputs can cause misclassification errors throughout entire datasets. In this paper, we consider perturbations bo

Luoqin Liu, Lucas Franceschini, Daniel F. Oliveira, Flavio C. C. Galeazzo

We evaluate the accuracy of the actuator line model (ALM) approach by performing simulations for the NREL~5~MW wind turbine in uniform inflow using three large eddy simulation codes. The power and thrust coefficients obtained using the three codes agrees within $1\%$ when the grid spacing $\Delta_{\rm grid} \le 5.25$~m, and are cross-validated against blade

Zhi Deng, Yang Liu, Hao Pan, Wassim Jabi

The freeform architectural modeling process often involves two important stages: concept design and digital modeling. In the first stage, architects usually sketch the overall 3D shape and the panel layout on a physical or digital paper briefly. In the second stage, a digital 3D model is created using the sketch as a reference. The digital model needs to inc

Ruibo Tu, Kun Zhang, Hedvig Kjellström, Cheng Zhang

To determine causal relationships between two variables, approaches based on Functional Causal Models (FCMs) have been proposed by properly restricting model classes; however, the performance is sensitive to the model assumptions, which makes it difficult to use. In this paper, we provide a novel dynamical-system view of FCMs and propose a new framework for

Jan Hubička, Jaroslav Nešetřil, Pablo Oviedo, Oriol Serra

A partial order is universal if it contains every countable partial order as a suborder. In 2017, Fiala, Hubi\v{c}ka, Long and Ne\v{s}et\v{r}il showed that every interval in the homomorphism order of graphs is universal, with the only exception being the trivial gap $[K_1,K_2]$. We consider the homomorphism order restricted to the class of oriented paths and

Eric Lescano, Sourav Roychowdhury

We present a formulation of heterotic Double Field Theory (DFT), where the fundamental fields are in $O(D,D)$ representations. The theory is obtained splitting an $O(D,D+K)$ duality invariant DFT. This procedure produces a Green-Schwarz mechanism for the generalized metric, and a fundamental gauge field which transforms as a gauge connection only to leading

Adam Gregosiewicz

We consider diffusion processes on metric graphs with semipermeable sticky membranes in each vertex. We prove that the process is governed by a Feller semigroup and find its asymptotic behavior as diffusion's speed increases to infinity with the same rate as permeability coefficients decreases to zero.

Fabio Gironella, Vicente Muñoz, Zhengyi Zhou

We extend Donaldson's asymptotically holomorphic techniques to symplectic orbifolds. More precisely, given a symplectic orbifold such that the symplectic form defines an integer cohomology class, we prove that there exist sections of large tensor powers of the prequantizable line bundle such that their zero sets are symplectic suborbifolds. We then derive a

Martin Avanzini, Georg Moser, Romain Péchoux, Simon Perdrix

We introduce a new kind of expectation transformer for a mixed classical-quantum programming language. Our semantic approach relies on a new notion of a cost structure, which we introduce and which can be seen as a specialisation of the Kegelspitzen of Keimel and Plotkin. We show that our weakest precondition analysis is both sound and adequate with respect

Tomasz Szczepański, Arkadiusz Sitek, Tomasz Trzciński, Szymon Płotka

A critical step in the fight against COVID-19, which continues to have a catastrophic impact on peoples lives, is the effective screening of patients presented in the clinics with severe COVID-19 symptoms. Chest radiography is one of the promising screening approaches. Many studies reported detecting COVID-19 in chest X-rays accurately using deep learning. A

Jacob Morra, Mark Daley

Can connectome-derived constraints inform computation? In this paper we investigate the contribution of a fruit fly connectome's topology on the performance of an Echo State Network (ESN) -- a subset of Reservoir Computing which is state of the art in chaotic time series prediction. Specifically, we replace the reservoir layer of a classical ESN -- normally

Mary Lou P. Bailey, Susan E. Pratt, Yongdeng Zhang, Michael Hinrichsen

We present and analyze video-microscopy-based single-particle-tracking measurements of the budding yeast (Saccharomyces cerevisiae) membrane protein, Pma1, fluorescently-labeled either by direct fusion to the switchable fluorescent protein, mEos3.2, or by a novel, light-touch, labeling scheme, in which a 5 amino acid tag is directly fused to the C-terminus o

Sadeq Bani Melhem, Hina Tabassum

This paper provides a comprehensive framework to analyze the performance of non-orthogonal multiple access (NOMA) in the downlink transmission of a single-carrier and multi-carrier terahertz (THz) network. Specifically, we first develop a novel user pairing scheme for the THz-NOMA network which ensures the performance gains of NOMA over orthogonal multiple a

Bastien Confais, Şuayb Ş. Arslan, Benoît Parrein

Locating data efficiently is a key process in every distributed data storage solution and particularly those deployed in multi-site environments, such as found in Cloud and Fog computing. Nevertheless, the existing protocols dedicated to this task are not compatible with the requirements of the infrastructures that underlie such computing paradigms. In this

Malsha V. Perera, Wele Gedara Chaminda Bandara, Jeya Maria Jose Valanarasu, Vishal M. Patel

Synthetic Aperture Radar (SAR) images are usually degraded by a multiplicative noise known as speckle which makes processing and interpretation of SAR images difficult. In this paper, we introduce a transformer-based network for SAR image despeckling. The proposed despeckling network comprises of a transformer-based encoder which allows the network to learn

Moritz Drobnitzky, Jonas Friederich, Bernhard Egger, Patrick Zschech

Strong demand for autonomous vehicles and the wide availability of 3D sensors are continuously fueling the proposal of novel methods for 3D object detection. In this paper, we provide a comprehensive survey of recent developments from 2012-2021 in 3D object detection covering the full pipeline from input data, over data representation and feature extraction

Lin Yang, Yu-zhen Janice Chen, Mohammad Hajiesmaili, John CS Lui

This paper tackles a multi-agent bandit setting where $M$ agents cooperate together to solve the same instance of a $K$-armed stochastic bandit problem. The agents are \textit{heterogeneous}: each agent has limited access to a local subset of arms and the agents are asynchronous with different gaps between decision-making rounds. The goal for each agent is t

Anugya Srivastava, Shriya Jain, Mugdha Thigle

Out of distribution (OOD) detection is a crucial part of making machine learning systems robust. The ImageNet-O dataset is an important tool in testing the robustness of ImageNet trained deep neural networks that are widely used across a variety of systems and applications. We aim to perform a comparative analysis of OOD detection methods on ImageNet-O, a fi

Kendrick Kay

Experimental datasets are growing rapidly in size, scope, and detail, but the value of these datasets is limited by unwanted measurement noise. It is therefore tempting to apply analysis techniques that attempt to reduce noise and enhance signals of interest. In this paper, we draw attention to the possibility that denoising methods may introduce bias and le

Ruodu Wang

We collect self-contained elementary proofs of four results in the literature on the false discovery rate of the Benjamini-Hochberg (BH) procedure for independent or positive-regression dependent p-values, the Benjamini-Yekutieli correction for arbitrarily dependent p-values, and the e-BH procedure for arbitrarily dependent e-values. As a corollary, the abov

Robert I. Citron, Sarah T. Stewart

Late accretion onto the Hadean Earth included large impacts that could have influenced early habitability, either by sterilizing the planet or alternatively catalyzing the origin of life by delivering iron required to create a reducing environment/atmosphere. We present 3D numerical simulations of 1500-3400 km diameter impacts on the early Earth in order to

Yuheng Li, Asmee M. Prabhu, Tej S. Choksi, Pieremanuele Canepa

Understanding the reactivity of ubiquitous molecules on complex oxides has broad impacts in energy applications and catalysis. The garnet-type Li$_7$La$_3$Zr$_2$O$_{12}$ is a promising solid-state electrolyte for lithium(Li)-ion batteries, and it readily reacts with H$_2$O and CO$_2$ when exposed to ambient air. Such reactions form a contamination layer on L

Yimin Ding, Xi Chen, Yao Duan, Haiyang Huang

We show that a metasurface-coated two-dimensional (2D) slab waveguide enables the generation of arbitrary complex light fields by combining the extreme versatility and freedom on wavefront control of optical metasurfaces with the compactness of photonic integrated circuits. We demonstrated off-chip 2D focusing and holographic projection with our metasurface-

Hanna Gruber, Moritz Jirak

We consider a time-varying first-order autoregressive model with irregular innovations, where we assume that the coefficient function is H\"{o}lder continuous. To estimate this function, we use a quasi-maximum likelihood based approach. A precise control of this method demands a delicate analysis of extremes of certain weakly dependent processes, our main re

Marcin Makowski, Edward W. Piotrowski, Piotr Frąckiewicz, Marek Szopa

The principle of minimum Fisher information states that in the set of acceptable probability distributions characterizing the given system, it is best done by the one that minimizes the corresponding Fisher information. This principle can be applied to transaction processes, the dynamics of which can be interpreted as the market tendency to minimize the info

Shailesh Lal

We review recent work in machine learning aspects of conformal field theory and Lie algebra representation theory using neural networks.

Valerio Di Giulio, P. A. D. Gonçalves, F. Javier García de Abajo

The modification of electronic band structures and the subsequent tuning of electrical, optical, and thermal material properties is a central theme in the engineering and fundamental understanding of solid-state systems. In this scenario, atomically thin materials offer an appealing platform because they are extremely susceptible to electric and magnetic gat

Helmut Abels, Mingwen Fei

We discuss the sharp interface limit of a coupled Navier-Stokes/Allen-Cahn system in a two dimensional, bounded and smooth domain, when a parameter $\varepsilon>0$ that is proportional to the thickness of the diffuse interface tends to zero rigorously. We prove convergence of the solutions of the Navier-Stokes/Allen-Cahn system to solutions of a sharp interf

V. M. Gorkavenko, T. V. Gorkavenko, Yu. A. Sitenko, M. S. Tsarenkova

A topological defect in the form of the Abrikosov-Nielsen-Olesen vortex in a space of arbitrary dimension is considered as a gauge-flux-carrying tube that is impenetrable for quantum matter. Charged scalar matter field is quantized in the vortex background with the perfectly rigid (Neumann) boundary condition imposed at the side surface of the vortex. We sho

Yuxuan Lin, Zafer Mutlu, Gabriela Borin Barin, Jenny Hong

Bottom-up assembled nanomaterials and nanostructures allow for the studies of rich and unprecedented quantum-related and mesoscopic transport phenomena. However, it can be difficult to quantify the correlations between the geometrical or structural parameters obtained from advanced microscopy and measured electrical characteristics when they are made into ma

Jesper Nederlof, Michał Pilipczuk, Karol Węgrzycki

We study Koebe orderings of planar graphs: vertex orderings obtained by modelling the graph as the intersection graph of pairwise internally-disjoint discs in the plane, and ordering the vertices by non-increasing radii of the associated discs. We prove that for every $d\in \mathbb{N}$, any such ordering has $d$-admissibility bounded by $O(d/\ln d)$ and weak

Effat Ara Easmin Lucky, Md. Mahadi Hasan Sany, Mumenunnesa Keya, Md. Moshiur Rahaman

By trade we usually mean the exchange of goods between states and countries. International trade acts as a barometer of the economic prosperity index and every country is overly dependent on resources, so international trade is essential. Trade is significant to the global health crisis, saving lives and livelihoods. By collecting the dataset called "Effects

Aleksander P. Woźniak, Michał Przybytek, Maciej Lewenstein, Robert Moszyński

In this paper, we investigate the effects of full electronic correlation on the high harmonic generation in the helium atom subjected to laser pulses of extremely high intensity. To do this, we perform real-time propagations of the helium atom wavefunction using quantum chemistry methods coupled to Gaussian basis sets. The calculations are done within the re

Yohan Beugin, Quinn Burke, Blaine Hoak, Ryan Sheatsley

Millions of consumers depend on smart camera systems to remotely monitor their homes and businesses. However, the architecture and design of popular commercial systems require users to relinquish control of their data to untrusted third parties, such as service providers (e.g., the cloud). Third parties therefore can (and in some instances have) access the v

Yuri Tavares dos Passos, Xavier Duquesne, Leandro Soriano Marcolino

When a large number of robots try to reach a common area, congestions happen, causing severe delays. To minimise congestion in a robotic swarm system, traffic control algorithms must be employed in a decentralised manner. Based on strategies aimed to maximise the throughput of the common target area, we developed two novel algorithms for robots using artific

Jie Zhang, Ming-Jiu Ni, Jacques Magnaudet

The buoyancy-driven dynamics of a pair of gas bubbles released in line is investigated numerically, focusing on highly inertial conditions under which isolated bubbles follow non-straight paths. In an early stage, the second bubble always drifts out of the wake of the leading one. Then, depending on the ratios of the buoyancy, viscous and capillary forces wh

Yuri Tavares dos Passos, Xavier Duquesne, Leandro Soriano Marcolino

A robotic swarm may encounter traffic congestion when many robots simultaneously attempt to reach the same area. For solving that efficiently, robots must execute decentralised traffic control algorithms. In this work, we propose a measure for evaluating the access efficiency of a common target area as the number of robots in the swarm rises: the common targ

Reetam Biswas, Mrinal K. Sen

Full-Waveform Inversion (FWI) has now become a widely accepted tool to obtain high-resolution velocity models from seismic data. Typically, the velocity model in its discrete form is represented on a rectangular grid, and we solve for the elastic properties at these grid points. FWI is mostly solved employing a local optimization method, where one obtains a

Andrés Gúrpide, Maxime Parra, Olivier Godet, Thierry Contini

The presence of large ionised gaseous nebulae found around some ultraluminous X-ray sources (ULXs) provides the means to assess the mechanical and radiative feedback of the central source, and hence constrain the efficiency and impact on the surroundings of the super-Eddington regime powering most of these sources. NGC 1313 X--1 is an archetypal ULX which ha

Anson Bastos, Abhishek Nadgeri, Kuldeep Singh, Hiroki Kanezashi

The recent works proposing transformer-based models for graphs have proven the inadequacy of Vanilla Transformer for graph representation learning. To understand this inadequacy, there is a need to investigate if spectral analysis of the transformer will reveal insights into its expressive power. Similar studies already established that spectral analysis of

Adar Zeitak, Adam Morrison

We present the Cuckoo Trie, a fast, memory-efficient ordered index structure. The Cuckoo Trie is designed to have memory-level parallelism -- which a modern out-of-order processor can exploit to execute DRAM accesses in parallel -- without sacrificing memory efficiency. The Cuckoo Trie thus breaks a fundamental performance barrier faced by current indexes, w

P. Temi, M. Gaspari, F. Brighenti, N. Werner

We investigate the cold and warm gas content, kinematics, and spatial distribution of six local massive elliptical galaxies to probe the origin of the multiphase gas in their atmospheres. We report new observations, including SOFIA [CII], ALMA CO, MUSE H$\alpha$+[NII] and VLA radio observations. These are complemented by a large suite of multiwavelength arch

Olivier Ezratty

We are in the midst of quantum hype with some excessive claims of quantum computing potential, many vendors' and even some research organizations' exaggerations, and a funding frenzy for very low technology readiness level startups. Governments are contributing to this hype with their large quantum initiatives and their technology sovereignty aspirations. Te

Zheren Wang, Kevin Cruse, Yuxing Fei, Ann Chia

Applying AI power to predict syntheses of novel materials requires high-quality, large-scale datasets. Extraction of synthesis information from scientific publications is still challenging, especially for extracting synthesis actions, because of the lack of a comprehensive labeled dataset using a solid, robust, and well-established ontology for describing sy

A. R. Mirotin

Necessary and sufficient conditions are given for boundedness of Hausdorff operators on generalized Hardy spaces $H^p_E(G)$, real Hardy space $H^1_{\mathbb{R}}(G)$, $BMO(G)$, and $BMOA(G)$ for compact Abelian group $G$. Surprisingly, these conditions turned out to be the same for all groups and spaces under consideration. Applications to Dirichlet series are

Kirill Boguslavski, Babak Kasmaei, Michael Strickland

The imaginary part of the effective heavy-quark potential is related to the total in-medium decay width of heavy quark-antiquark bound states. We extract the static limit of this quantity using classical-statistical simulations of real-time Yang-Mills dynamics by measuring the temporal decay of Wilson loops. By performing the simulations on finer and larger

Itamar Cohen-Matalon

The objective of this paper is to (partially) address the issue of finding an analogue to Khintchine's theorem for IFS Fractals. We study the convergence case for Diophantine approximations, and show an improved result for higher dimensions. This matter has been previously studied by Pollington and Velani in arXiv:math/0401149. Pollington and Velani show a s

Edward Buie, Evan Scannapieco, G. Mark Voit

Absorption-line measurements of the circumgalactic medium (CGM) display a highly non-uniform distribution of lower ionization state species accompanied by more widespread higher ionization state material. This suggests that the CGM is a dynamic, multiphase medium, such as arises in the presence of turbulence. To better understand this evolution, we perform h

Veneta Haralampieva, Ozan Caglayan, Lucia Specia

Recently, there has been a surge in research in multimodal machine translation (MMT), where additional modalities such as images are used to improve translation quality of textual systems. A particular use for such multimodal systems is the task of simultaneous machine translation, where visual context has been shown to complement the partial information pro

Yifeng Xiong, Soon Xin Ng, Gui-Lu Long, Lajos Hanzo

Quantum phase estimation is an important component in diverse quantum algorithms. However, it suffers from spectral leakage, when the reciprocal of the record length is not an integer multiple of the unknown phase, which incurs an accuracy degradation. For the existing single-sample estimation scheme, window-based methods have been proposed for spectral leak

Chengchao Zhao, Ruoyu Yang, Yana Di, Jiwei Zhang

The recently developed technique of DOC kernels has been a great success in the stability and convergence analysis for BDF2 scheme with variable time steps. However, such an analysis technique seems not directly applicable to problems with initial singularity. In the numerical simulations of solutions with initial singularity, variable time-steps schemes lik

G. Stacey Staples

In this paper, spectral properties of matrices with (complex) zeon entries are investigated. It is shown that when $A$ is an $m\times m$ self-adjoint matrix whose characteristic polynomial $\chi_A(u)$ has $m$ ``spectrally simple'' zeros $\lambda_1, \ldots, \lambda_m$ in the zeon algebra ${\mathbb{C}\mathfrak{Z}}$, there exist $m$ linearly independent normali

Erin K. Hamilton, Seonghye Jeon, Pepa Ramirez Cobo, Kichun Sky Lee

A number of approaches have dealt with statistical assessment of self-similarity, and many of those are based on multiscale concepts. Most rely on certain distributional assumptions which are usually violated by real data traces, often characterized by large temporal or spatial mean level shifts, missing values or extreme observations. A novel, robust approa

Nikolas Michael, Mihai Cucuringu, Sam Howison

We investigate the use of the normalized imbalance between option volumes corresponding to positive and negative market views, as a predictor for directional price movements in the spot market. Via a nonlinear analysis, and using a decomposition of aggregated volumes into five distinct market participant classes, we find strong signs of predictability of exc

Anish Lahiri, Marc Klasky, Jeffrey A. Fessler, Saiprasad Ravishankar

Reconstruction of CT images from a limited set of projections through an object is important in several applications ranging from medical imaging to industrial settings. As the number of available projections decreases, traditional reconstruction techniques such as the FDK algorithm and model-based iterative reconstruction methods perform poorly. Recently, d

Mohammadali Razeghi, Merve Üstünçelik, Farzan Shabani, Hilmi Volkan Demir

Photo-bolometric effect is critically important in optoelectronic structures and devices employing metallic electrodes with nanoscale features due to heating caused by the plasmonic field enhancement. One peculiar case is individual silver nanowires (Ag NWs) and their networks. Ag NW-networks exhibit excellent thermal, electrical, and mechanical properties,

Emily Adlam

We undertake a reconstruction of the epistemic significance of research on operational theories in quantum foundations. We suggest that the space of operational theories is analogous to the space of possible worlds employed in the possible world semantics for modal logic, so research of this sort can be understood as probing modal structure. Thus we argue th

Yunfeng Jiang, Hsian-Hua Tseng

We generalize the multiple cover formula of Y. Toda (proved by Maulik-Thomas) for counting invariants for semistable coherent sheaves on local K3 surfaces to semistable twisted sheaves over twisted local K3 surfaces. The formula has an application to prove any rank S-duality conjecture for K3 surfaces.

Sahar Almahfouz Nasser, Saqib Shamsi, Valay Bundele, Bhavesh Garg

Capturing high-resolution magnetic resonance (MR) images is a time consuming process, which makes it unsuitable for medical emergencies and pediatric patients. Low-resolution MR imaging, by contrast, is faster than its high-resolution counterpart, but it compromises on fine details necessary for a more precise diagnosis. Super-resolution (SR), when applied t

Minkyoung Kang, William Auffermann, Brani Vidakovic

To improve diagnostic accuracy of breast cancer detection, several researchers have used the wavelet-based tools, which provide additional insight and information for aiding diagnostic decisions. The accuracy of such diagnoses, however, can be improved. This paper introduces a wavelet-based technique, non-decimated wavelet transform (NDWT)-based scaling esti

Baxi Chong, Tianyu Wang, Eva Erickson, Philip J Bergmann

Although typically possessing four limbs and short bodies, lizards have evolved a diversity of body plans, from short-bodied and fully-limbed to elongate and nearly limbless. Such diversity in body morphology is hypothesized as adaptations to locomotion cluttered terrestrial environments, but the mode of propulsion -- e.g., the use of body and/or limbs to in

Xu Yang, Lei Xian

We apply the Fountain theorem to a class of nonlinear Dirac-Laplace equation on compact spin manifold. We show the standard Ambrosetti-Rabinowitz condition can be replaced by a more natural super-quadratic condition that is enough to obtain the Cerami condition under certain conditions. Multiple solutions of nonlinear Dirac-Laplace equation are obtained in t

Hojjat Salehinejad, Shahrokh Valaee

Anatomical movements of the human body can change the channel state information (CSI) of wireless signals in an indoor environment. These changes in the CSI signals can be used for human activity recognition (HAR), which is a predominant and unique approach due to preserving privacy and flexibility of capturing motions in non-line-of-sight environments. Exis

Erkan Yilmaz, Ozgur Oku, Ekrem Aydiner

In this paper, we use SEIR equations to make predictions for the number of mortality due to COVID-19 in \.Istanbul. Using excess mortality method, we find the number of mortality for the previous three waves in 2020 and 2021. We show that the predictions of our model is consistent with number of moralities for each wave. Furthermore, we predict the number of

Qiang Meng, Xinqian Gu, Xiaqing Xu, Feng Zhou

Softmax-based losses have achieved state-of-the-art performances on various tasks such as face recognition and re-identification. However, these methods highly relied on clean datasets with global labels, which limits their usage in many real-world applications. An important reason is that merging and organizing datasets from various temporal and spatial sce

Tzu-Chieh Wei, Robert Raussendorf, Ian Affleck

Affleck, Kennedy, Lieb, and Tasaki constructed a spin-1 model that is isotropic in spins and possesses a provable finite gap above the ground state more than three decades ago. They also constructed models in two dimensions. Their construction has impacted subsequent research that is still active. In this review article, we review some selected the progresse

Nandan Roy, Sangita Goswami, Sudipta Das

In this work we propose a simple general parametrization scheme of the Hubble parameter for the scalar field dark energy models. In our approach it is possible to incorporate both the quintessence and phantom scalar field in a single analytical scheme and write down relevant cosmological parameters which are independent of the nature of the scalar field. A g

Youngeun Kim, Yuhang Li, Hyoungseob Park, Yeshwanth Venkatesha

Spiking Neural Networks (SNNs) have gained huge attention as a potential energy-efficient alternative to conventional Artificial Neural Networks (ANNs) due to their inherent high-sparsity activation. However, most prior SNN methods use ANN-like architectures (e.g., VGG-Net or ResNet), which could provide sub-optimal performance for temporal sequence processi

John E. Laird

This is a detailed analysis and comparison of the ACT-R and Soar cognitive architectures, including their overall structure, their representations of agent data and metadata, and their associated processing. It focuses on working memory, procedural memory, and long-term declarative memory. I emphasize the commonalities, which are many, but also highlight the

F. C. E. Lima, C. A. S. Almeida

Using a spherically symmetric ansatz, we show that the Chern-Simons O(3)-sigma model with a logarithmic potential admits topological solutions. This result is quite interesting since the Gausson-type logarithmic potential only predicted topological solutions in $(1+1)$D models. To accomplish our goal, the Bogomol'nyi-Prasad-Sommerfield (BPS) method is used,

Tiejun Huang, Yajing Zheng, Zhaofei Yu, Rui Chen

In digital cameras, we find a major limitation: the image and video form inherited from a film camera obstructs it from capturing the rapidly changing photonic world. Here, we present vidar, a bit sequence array where each bit represents whether the accumulation of photons has reached a threshold, to record and reconstruct the scene radiance at any moment. B

Bing He

In this paper, we extend an expansion formula of Liu to multiple basic hypergeometric series over the root system $A_{n}.$ The usefulness of Liu's expansion formula in special functions and number theory has been shown by Liu and many others. We first establish a very general multiple expansion formula over the root system $A_{n}$ and then deduce several $A_

Claudio Esperança, Ronaldo Garcia, Dan Reznik

We explore geometric and topological properties of 3d surfaces swept by Poncelet triangles, as well as tangles formed by associated points.

Nikolaos Adaloglou

We present a new and simpler proof of the fact that any Lagrangian $\mathbb{R}P^2$ in $T^*\mathbb{R}P^2$ is Hamiltonian isotopic to the zero section. Our proof mirrors the one given by Li and Wu for the Hamiltonian uniqueness of Lagrangians in $T^*S^2$, using surgery to turn Lagrangian spheres into symplectic ones. The main novel contribution is a detailed p

Jun Li, Jian Gao, Biwei Jiang, Zesen Lin

The unusual extinction curves of SN 2010jl provide an excellent opportunity to investigate the properties of dust formed by core-collapse supernovae. By using a series of dust models with different compositions and grain size distributions, we fit the extinction curves of SN 2010jl and find that a silicate-graphite mixture dust model characterized by exponen

Alexander Kozachinskiy

A major open problem in the area of infinite-duration games is to characterize winning conditions that are determined in finite-memory strategies. Infinite-duration games are usually studied over edge-colored graphs, with winning conditions that are defined in terms of sequences of colors. In this paper, we investigate a restricted class of finite-memory str

Zhangyong Tang, Tianyang Xu, Xiao-Jun Wu

Visual object tracking with the visible (RGB) and thermal infrared (TIR) electromagnetic waves, shorted in RGBT tracking, recently draws increasing attention in the tracking community. Considering the rapid development of deep learning, a survey for the recent deep neural network based RGBT trackers is presented in this paper. Firstly, we give brief introduc

Deng Wang

A first-order MeV-scale cosmological phase transition (PT) can generate a peak in the power spectrum of stochastic gravitational wave background around nanohertz frequencies. With the recent International Pulsar Timing Array data release two covering nanohertz frequencies, we search for such a phase transition signal. For the standard 4-parameter PT model, w

Mark A. Gorbachev, Marina S. Butuzova, Sergey G. Sergeev, Sergey V. Nazarov

Multiband optical photometry data of blazar S5 0716+714 obtained from 2002 to 2019 reveal stable color index change with flux variability. We analyzed this trend under variability caused by the Doppler factor change in the presence of a curved photon energy spectrum. A break in the energy spectrum of emitting electrons, caused by radiative losses, or log-par

Tatiana Latychevskaia

Conventional three-dimensional (3D) imaging methods require multiple measurements of the sample in different orientation or scanning. When the sample is probed with coherent waves, a single two-dimensional (2D) intensity measurement is sufficient as it contains all the information of the 3D sample distribution. We show a method that allows reconstruction of

Ilya V. Doronin, Evgeny S. Andrianov, Alexander A. Zyablovsky

Existing methods for the localization of light at the nanoscale use either a structure with negative permittivity, by exploiting subwavelength plasmonic resonances, or a dielectric structure with a high refractive index, which reduces the wavelength. In this paper, we provide an alternative to these two methods based on a modification of the modes of dielect

Francesco-Luigi Navarria

SND@LHC is a compact experiment that will detect high energy neutrinos produced by heavy flavour quarks at the LHC in the pseudo-rapidity region 7.2 $< \eta <$ 8.6. It is an hybrid system, comprising nuclear emulsions and electronic detectors, that allows all three $\nu$ flavours to be distinguished, thus opening an unique opportunity to probe the physics of

Chao Feng, Defu Lian, Xiting Wang, Zheng liu

We focus on Maximum Inner Product Search (MIPS), which is an essential problem in many machine learning communities. Given a query, MIPS finds the most similar items with the maximum inner products. Methods for Nearest Neighbor Search (NNS) which is usually defined on metric space don't exhibit the satisfactory performance for MIPS problem since inner produc

Lucio Guerra

Note to a paper of M. Tanabe concerning the classical theorem of M. De Franchis and F. Severi

Sergei Aleshin, Ivan Goriachuk, Dmitry Kolupaev, Konstantin Stepanyantz

We verify a method which allows to obtain the $\beta$-function of supersymmetric theories regularized by higher covariant derivatives by calculating only specially modified vacuum supergraphs. With the help of this method for a general renormalizable ${\cal N}=1$ supersymmetric gauge theory a part of the three-loop $\beta$-function depending on the Yukawa co

Mikhail R. Gabdullin, Vitalii V. Iudelevich, Florian Luca

For a function $f\colon \mathbb{N}\to\mathbb{N}$, define $N^{\times}_{f}(x)=\#\{n\leq x: n=kf(k) \mbox{ for some $k$} \}$. Let $\tau(n)=\sum_{d|n}1$ be the divisor function, $\omega(n)=\sum_{p|n}1$ be the prime divisor function, and $\varphi(n)=\#\{1\leq k\leq n: (k,n)=1 \}$ be Euler's totient function. We prove that \begin{gather*} \!\!\!\!\!\!\!\!\!\!\!\!\