August 2022 arXiv papers — page 11

David Prinz

We consider (effective) Quantum General Relativity coupled to the Standard Model (QGR-SM) and study its transversality. To this end, we provide all propagator and three-valent vertex Feynman rules. Then, we recall the longitudinal, identical and transversal projection operators for Quantum Yang--Mills theory with a Lorenz gauge fixing. Next, we introduce the

Hua Lu, Siqi Bao, Huang He, Fan Wang

Many open-domain dialogue models pre-trained with social media comments can generate coherent replies but have difficulties producing engaging responses when interacting with real users. This phenomenon might mainly result from the deficiency of annotated human-human conversations and the misalignment with human preference. In this paper, we propose a novel

Ioan Alexandru Puiu, Raphael Andreas Hauser

Spot electricity markets are considered under a Game-Theoretic framework, where risk averse players submit orders to the market clearing mechanism to maximise their own utility. Consistent with the current practice in Europe, the market clearing mechanism is modelled as a Social Welfare Maximisation problem, with zonal pricing, and we consider inflexible dem

Francesco Conte, Gabriele Mosaico, Gianluca Natrella, Matteo Saviozzi

This paper proposes a control strategy for a Reverse Fuel Cell used to manage a Renewable Energy Community. A two-stage scenario-based Model Predictive Control algorithm is designed to define the best economic strategy to be followed during operation. Renewable energy generation and users' demand are forecasted by a suitably defined Discrete Markov Chain bas

Nikolai Opdan, Kay Rülling

These are the notes accompanying three lectures given by the second author at the Motivic Geometry program at CAS, which aim to give an introduction and an overview of some recent developments in the field of reciprocity sheaves.

Yuhang Liu, Zhen Zhang, Dong Gong, Mingming Gong

Multi-source domain adaptation (MSDA) addresses the challenge of learning a label prediction function for an unlabeled target domain by leveraging both the labeled data from multiple source domains and the unlabeled data from the target domain. Conventional MSDA approaches often rely on covariate shift or conditional shift paradigms, which assume a consisten

Anyi Huang, Qian Xie, Zhoutao Wang, Dening Lu

The intricacy of 3D surfaces often results cutting-edge point cloud denoising (PCD) models in surface degradation including remnant noise, wrongly-removed geometric details. Although using multi-scale patches to encode the geometry of a point has become the common wisdom in PCD, we find that simple aggregation of extracted multi-scale features can not adapti

Jörn Dietrich, Dirk Lebiedz

The numerical simulation of realistic reactive flows is a major challenge due to the stiffness and high dimension of the corresponding kinetic differential equations. Manifold-based model reduction techniques address this problem by projecting the full phase space onto manifolds of slow motion, which capture the system's long-term behavior. In this article w

Yume Nishinomiya, Akito Kusaka, Kenji Kiuchi, Tomoki Terasaki

Superconducting Transition-Edge Sensor (TES) bolometers are used for cosmic microwave background (CMB) observations. We used a testbed to evaluate the thermal performance of TES bolometers in regard to the saturation power Psat and intrinsic thermal time constant tau0. We developed an evaluation method that is complementary to methods with electrothermal fee

Shibarchi Majumder, Jens Frederik Dalsgaard Nielsen, Thomas Bak

Real-time embedded platforms with resource constraints can take the benefits of mixed-criticality system where applications with different criticality-level share computational resources, with isolation in the temporal and spatial domain. A conventional software-based isolation mechanism adds additional overhead and requires certification with the highest le

Irene Gómez-Bueno, Sebastiano Boscarino, Manuel Jesús Castro, Carlos Parés

The aim of this work is to design implicit and semi-implicit high-order well-balanced finite-volume numerical methods for 1D systems of balance laws. The strategy introduced by two of the authors in a previous paper for explicit schemes based on the application of a well-balanced reconstruction operator has been applied. The well-balanced property is preserv

Kai Hendriks, Shu-Xu Yi, Gijs Nelemans

In the current multi-messenger astronomy era, it is important that information about joint gravitational wave (GW) and electromagnetic (EM) observations through short gamma-ray burst (sGRBs) remains easily accessible. The possibility for non-experts to execute quick computations of joint GW-sGRB detections should be facilitated. We construct a sGRB model and

Florio M. Ciaglia, Fabio Di Cosmo, Alberto Ibort, Giuseppe Marmo

We go on with the program started in the companion paper [CDI+] of defining a Poisson bracket structure on the space of solutions of the equations of motion of first order Hamiltonian field theories. The case of non-Abelian gauge theories is addressed by using a suitable version of the coisotropic embedding theorem.

Rakshyakar Giri, Rasmus H. Jensen, Deepak Khurana, Juanita Bocquel

Spin-based applications of the negatively charged nitrogen-vacancy (NV) center in diamonds require efficient spin readout. One approach is the spin-to-charge conversion (SCC), relying on mapping the spin states onto the neutral (NV$^0$) and negative (NV$^-$) charge states followed by a subsequent charge readout. With high charge-state stability, SCC enables

Yuhang Liu, Zhen Zhang, Dong Gong, Mingming Gong

The task of causal representation learning aims to uncover latent higher-level causal variables that affect lower-level observations. Identifying the true latent causal variables from observed data, while allowing instantaneous causal relations among latent variables, remains a challenge, however. To this end, we start with the analysis of three intrinsic in

Marcos Escobar-Anel, Yevhen Havrylenko, Rudi Zagst

We solve an expected utility-maximization problem with a Value-at-risk constraint on the terminal portfolio value in an incomplete financial market due to stochastic volatility. To derive the optimal investment strategy, we use the dynamic programming approach. We demonstrate that the value function in the constrained problem can be represented as the expect

Ewa Duda

Education for sustainable development supports the improvement of knowledge, skills, attitudes and behaviors related to global challenges such as climate change, global warming and environmental degradation, among others. It is increasingly taking place through projects based on information and communication technologies. The effectiveness of the actions tak

J. Yoneda, J. S. Rojas-Arias, P. Stano, K. Takeda

Semiconductor qubits are appealing for building quantum processors as they may be densely integrated due to small footprint. However, a high density raises the issue of noise correlated across different qubits, which is of practical concern for scalability and fault tolerance. Here, we analyse and quantify in detail the degree of noise correlation in a pair

Miguel Altamirano Cabrera, Jonathan Tirado, Juan Heredia, Dzmitry Tsetserukou

LinkGlide-S is a novel wearable hand-worn tactile display to deliver multi-contact and multi-modal stimuli at the user's palm.} The array of inverted five-bar linkages generates three independent contact points to cover the whole palm area. \textcolor{black} {The independent contact points generate various tactile patterns at the user's hand, providing multi

Xin Li, Jian Li, Zhihong Jeff Xia, Nikolaos Georgakarakos

In this study, we focus on learning Hamiltonian systems, which involves predicting the coordinate (q) and momentum (p) variables generated by a symplectic mapping. Based on Chen & Tao (2021), the symplectic mapping is represented by a generating function. To extend the prediction time period, we develop a new learning scheme by splitting the time series (q_i

Jianfeng Xie

Let $\Phi_n(X)$ and $\Psi_n(X)=\frac{X^{n}-1}{\Phi_{n}(X)}$ be the $n$-th cyclotomic and inverse cyclotomic polynomials respectively. In this short note, for any pair of divisors $ d_{1} \neq d_{2} $ of $ n $, and integers $l_1$ and $l_2$ such that $ 0 \leq l_{1} \leq \varphi(d_{1})-1 $ and $ 0 \leq l_{2} \leq \varphi(d_{2})-1 $, we show that \[\left \langle

F. Delgado, J. Fernández-Rossier

A scanning tunneling microscope (STM) can probe the inelastic spin excitations of single magnetic atoms in a surface via spin-flip assisted tunneling. A particular and intriguing case is the Mn dimer case. We show here that the existing theories for inelastic transport spectroscopy do not explain the observed spin transitions when both atoms are equally coup

Apostolos Modas

Deep neural networks have achieved impressive results in many image classification tasks. However, since their performance is usually measured in controlled settings, it is important to ensure that their decisions remain correct when deployed in noisy environments. In fact, deep networks are not robust to a large variety of semantic-preserving image modifica

Aloexander V. Kochin

There are a lot of oscillatory motions of various kinds in the atmosphere, for example, internal gravity waves (IGW), which have a period less than the time of flight of the radiosonde. Oscillatory motions lead to adiabatic cooling during the shift of air mass upwards from equilibrium or heat when shifting down. The magnitude and sign of the shift from the e

L. G. Althaus, M. E. Camisassa, S. Torres, T. Battich

We present the first set of constant rest-mass ultra-massive oxygen/neon white dwarf cooling tracks with masses larger than 1.29 Msun which fully take into account the effects of general relativity on their structural and evolutionary properties. We have computed the full evolution sequences of 1.29, 1.31, 1.33, 1.35, and 1.369 Msun white dwarfs with the La

Jianlong Yuan, Qian Qi, Fei Du, Zhibin Wang

In this work, we explore data augmentations for knowledge distillation on semantic segmentation. To avoid over-fitting to the noise in the teacher network, a large number of training examples is essential for knowledge distillation. Imagelevel argumentation techniques like flipping, translation or rotation are widely used in previous knowledge distillation f

Carlos Alegria, Giordano Da Lozzo, Giuseppe Di Battista, Fabrizio Frati

A rectangular drawing of a planar graph $G$ is a planar drawing of $G$ in which vertices are mapped to grid points, edges are mapped to horizontal and vertical straight-line segments, and faces are drawn as rectangles. Sometimes this latter constraint is relaxed for the outer face. In this paper, we study rectangular drawings in which the edges have unit len

Ashkan Pakzad, Mou-Cheng Xu, Wing Keung Cheung, Marie Vermant

Several chronic lung diseases, like idiopathic pulmonary fibrosis (IPF) are characterised by abnormal dilatation of the airways. Quantification of airway features on computed tomography (CT) can help characterise disease progression. Physics based airway measurement algorithms have been developed, but have met with limited success in part due to the sheer di

Mohammad Taghi Dabiri, Mazen Hasna, Nizar Zorba, Tamer Khattab

This paper focuses on providing an analytical framework for the quantification and evaluation of the pointing error for a general case at high-frequency millimeter wave (mmWave) and terahertz (THz) communication links. For this aim, we first derive the the probability density function (PDF) and cumulative distribution functions (CDF) of the pointing error be

Siyu Yuan, Deqing Yang, Jiaqing Liang, Jilun Sun

The concepts in knowledge graphs (KGs) enable machines to understand natural language, and thus play an indispensable role in many applications. However, existing KGs have the poor coverage of concepts, especially fine-grained concepts. In order to supply existing KGs with more fine-grained and new concepts, we propose a novel concept extraction framework, n

He-Wen Yang, Pak-Hin Thomas Tam, Lili Yang

A significant number of double white dwarfs (DWDs) are believed to merge within the Hubble time due to the gravitational wave (GW) emission during their inspiraling phase. The outcome of a DWD system is either a type Ia Supernova as the double-degenerate model, or a massive, long-lasting merger remnant. Expected multi-messenger signals of these events will h

Martin Pawelczyk, Tobias Leemann, Asia Biega, Gjergji Kasneci

As machine learning (ML) models are increasingly being deployed in high-stakes applications, policymakers have suggested tighter data protection regulations (e.g., GDPR, CCPA). One key principle is the "right to be forgotten" which gives users the right to have their data deleted. Another key principle is the right to an actionable explanation, also known as

Florio M. Ciaglia, Fabio Di Cosmo, Alberto Ibort, Giuseppe Marmo

We analyse the problem of defining a Poisson bracket structure on the space of solutions of the equations of motions of first order Hamiltonian field theories. The cases of Hamiltonian mechanical point systems (as a (0 + 1)-dimensional field) and more general field theories without gauge symmetries are addressed by showing the existence of a symplectic (and,

Ioannis Krikidis, Constantinos Psomas, Symeon Chatzinotas

This letter investigates the employment of vector-perturbation (VP) precoding to convey simultaneously information and energy in multiple-user multiple-input single-output (MU-MISO) downlink channel. We show that the conventional VP in addition to the information capacity benefits that provides to linear channel inversion techniques, it enhances the harveste

Mao Ye, Nicolette Formosa, Mohammed Quddus

Vehicle Ad-hoc Networks (VANETs) act as the core of vehicular communications and provide the fundamental wireless communication architecture to support both vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication. Therefore, by leveraging only communication technologies, Connected Vehicles (CVs) can navigate through the dynamic road networ

D. Kuridze, P. Heinzel, J. Koza, R. Oliver

We study off-limb emission of the lower solar atmosphere using high-resolution imaging spectroscopy in the H$\beta$ and Ca II 8542 \r{A} lines obtained with the CHROMospheric Imaging Spectrometer (CHROMIS) and the CRisp Imaging SpectroPolarimeter (CRISP) on the Swedish 1-m Solar Telescope. The H$\beta$ line wing images show the dark intensity gap between the

Yong Zhong, Hongtao Liu, Xiaodong Liu, Fan Bao

Deep generative models (DGMs) are data-eager because learning a complex model on limited data suffers from a large variance and easily overfits. Inspired by the classical perspective of the bias-variance tradeoff, we propose regularized deep generative model (Reg-DGM), which leverages a nontransferable pre-trained model to reduce the variance of generative m

Johannes Blum, Yann Disser, Andreas Emil Feldmann, Siddharth Gupta

We consider the Sparse Hitting Set (Sparse-HS) problem, where we are given a set system $(V,\mathcal{F},\mathcal{B})$ with two families $\mathcal{F},\mathcal{B}$ of subsets of $V$. The task is to find a hitting set for $\mathcal{F}$ that minimizes the maximum number of elements in any of the sets of $\mathcal{B}$. Our focus is on determining the complexity o

Shijie Dong, Kuijie Li, Xu Yuan

On the (1+3) dimensional Minkowski spacetime, for small, regular initial data, it is well-known that the Dirac-Klein-Gordon system admits a global solution. In the present paper, we aim to establish the uniform boundedness of the total energy of the solution for this system. The proof relies on Klainerman's vector field and Alinhac's ghost weight methods. Th

Jorge Ejarque, Pau Andrio, Adam Hospital, Javier Conejero

Developing complex biomolecular workflows is not always straightforward. It requires tedious developments to enable the interoperability between the different biomolecular simulation and analysis tools. Moreover, the need to execute the pipelines on distributed systems increases the complexity of these developments. To address these issues, we propose a meth

Vincent Cohen-Addad, Jason Li

We study the complexity of the classic capacitated k-median and k-means problems parameterized by the number of centers, k. These problems are notoriously difficult since the best known approximation bound for high dimensional Euclidean space and general metric space is $\Theta(\log k)$ and it remains a major open problem whether a constant factor exists. We

Andrea Munari, Leonardo Badia

Scheduling updates from remote sensors is a key task for the internet of things (IoT). In this context, the mathematical concept of age of information is often used to capture the freshness of received data. This is, in turn, relevant to optimize the frequency of the exchanges, especially for resource constrained (e.g., energy-limited) sensors. Most investig

Fangqi Li, Shilin Wang, Yun Zhu

Backdoor-based watermarking schemes were proposed to protect the intellectual property of artificial intelligence models, especially deep neural networks, under the black-box setting. Compared with ordinary backdoors, backdoor-based watermarks need to digitally incorporate the owner's identity, which fact adds extra requirements to the trigger generation and

Giuseppe Di Battista, Walter Didimo, Luca Grilli, Fabrizio Grosso

In a graph story the vertices enter a graph one at a time and each vertex persists in the graph for a fixed amount of time $\omega$, called viewing window. At any time, the user can see only the drawing of the graph induced by the vertices in the viewing window and this determines a sequence of drawings. For readability, we require that all the drawings of t

Dominik J. E. Waibel, Ernst Röell, Bastian Rieck, Raja Giryes

Diffusion models are a special type of generative model, capable of synthesising new data from a learnt distribution. We introduce DISPR, a diffusion-based model for solving the inverse problem of three-dimensional (3D) cell shape prediction from two-dimensional (2D) single cell microscopy images. Using the 2D microscopy image as a prior, DISPR is conditione

Petros Vavaroutsos, Ioannis Oroutzoglou, Dimosthenis Masouros, Dimitrios Soudris

Nowadays, we are living in an era of extreme device heterogeneity. Despite the high variety of conventional CPU architectures, accelerator devices, such as GPUs and FPGAs, also appear in the foreground exploding the pool of available solutions to execute applications. However, choosing the appropriate device per application needs is an extremely challenging

Mario Quiles Pérez, Enrique Tomás Martínez Beltrán, Sergio López Bernal, Eduardo Horna Prat

The primary goal of any company is to increase its profits by improving both the quality of its products and how they are advertised. In this context, neuromarketing seeks to enhance the promotion of products and generate a greater acceptance on potential buyers. Traditionally, neuromarketing studies have relied on a single biosignal to obtain feedback from

David Buil-Gil, Steven Kemp, Stefanie Kuenzel, Lynne Coventry

The connection of home electronic devices to the internet allows remote control of physical devices and involves the collection of large volumes of data. With the increase in the uptake of Internet-of-Things home devices, it becomes critical to understand the digital harms of smart homes. We present a systematic literature review on the security and privacy

Dongming Huang, Feicheng Wang, Donald B. Rubin, S. C. Kou

Catalytic prior distributions provide general, easy-to-use, and interpretable specifications of prior distributions for Bayesian analysis. They are particularly beneficial when the observed data are inadequate to stably estimate a complex target model. A catalytic prior distribution is constructed by augmenting the observed data with synthetic data that are

James E. McClure, Zhe Li

We develop a mesoscopic approach to model the non-equilibrium behavior of membranes at the cellular scale. Relying on lattice Boltzmann methods, we develop a solution procedure to recover the Nernst-Planck equations and Gauss's law. A general closure rule is developed to describe mass transport across the membrane, which is able to account for protein-mediat

Sarah Auster, Yeon-Koo Che, Konrad Mierendorff

This paper studies sequential information acquisition by an ambiguity-averse decision maker (DM), who decides how long to collect information before taking an irreversible action. The agent optimizes against the worst-case belief and updates prior by prior. We show that the consideration of ambiguity gives rise to rich dynamics: compared to the Bayesian DM,

Karl Kunisch, Donato Vásquez-Varas, Daniel Walter

A learning based method for obtaining feedback laws for nonlinear optimal control problems is proposed. The learning problem is posed such that the open loop value function is its optimal solution. This infinite dimensional, function space, problem, is approximated by a polynomial ansatz and its convergence is analyzed. An $\ell_1$ penalty term is employed,

Michele Arzano, Vittorio D'Esposito, Giulia Gubitosi

We show that quantum properties of spacetime, encoded by noncommutativity at the Planck scale, lead to a generalized time evolution of quantum systems in which pure states can evolve into mixed states. Specifically, a decoherence mechanism is obtained in the form of a Lindblad-like time evolution for the density operator when the action of time translations

Luca Capizzi, Sara Murciano, Pasquale Calabrese

We consider the ground state of a theory composed by $M$ species of massless complex bosons in one dimension coupled together via a conformal interface. We compute both the R\'enyi entropy and the negativity of a generic partition of wires, generalizing the approach developed in a recent work for free fermions. These entanglement measures show a logarithmic

Avneet Singh, Maria Alessandra Papa

Most all-sky searches for continuous gravitational waves assume the source to be isolated. In this paper, we allow for an unknown companion object in a long-period orbit and opportunistically use previous results from an all-sky search for isolated sources to constrain the continuous gravitational wave amplitude over a large and unexplored range of binary or

Mohammadreza Doostmohammadian, Usman A. Khan, Alireza Aghasi, Themistoklis Charalambous

This paper considers distributed resource allocation and sum-preserving constrained optimization over lossy networks, where the links are unreliable and subject to packet drops. We define the conditions to ensure convergence under packet drops and link removal by focusing on two main properties of our allocation algorithm: (i) The weight-stochastic condition

P. Lagos, S. I. Loubser, T. C. Scott, E. O'Sullivan

With the goal of a thorough investigation of the ionised gas and its origin in early-type group-dominant galaxies, we present archival MUSE data for 18 galaxies from the Complete Local-Volume Groups Sample (CLoGS). This data allowed us to study the spatially-resolved warm gas properties, including the morphology of the ionised gas, EW(H$\alpha$) and kinemati

Seung Hyun Lee, Gyeongrok Oh, Wonmin Byeon, Sang Ho Yoon

Recent successes suggest that an image can be manipulated by a text prompt, e.g., a landscape scene on a sunny day is manipulated into the same scene on a rainy day driven by a text input "raining". These approaches often utilize a StyleCLIP-based image generator, which leverages multi-modal (text and image) embedding space. However, we observe that such tex

Abhishek Goswami, Erwan Bernard, Wolf Hauser, Frederic Dufaux

A Tone Mapping Operator (TMO) is required to render images with a High Dynamic Range (HDR) on media with limited dynamic capabilities. TMOs compress the dynamic range with the aim of preserving the visually perceptual cues of the scene. Previous literature has established the benefits of TMOs being semantic aware, understanding the content in the scene to pr

Xiao-Xiong Zeng, Ke-Jian He, Guo-Ping Li, En-Wei Liang

Taking the quantum electrodynamics (QED) effect into account, we investigate the geometrical-optics appearance of the Euler-Heisenberg (EH) black hole (BH) under the different accretion flows context, which depends on the BH space-time structure and different sources of light. The more significant magnetic charge leads to the smaller shadow radius for the EH

Hua Gao, Luis C. Ho, Zhao-Yu Li

We measure optical colors for the bulges of 312 disk galaxies from the Carnegie-Irvine Galaxy Survey and convert their previously available $R$-band structural parameters to stellar mass parameters. We also measure their average stellar mass surface density in the central 1 kpc ($\Sigma_{1}$). Comparing the mass-based Kormendy relation with the original one

Haishuo Fang, Ji-Ung Lee, Nafise Sadat Moosavi, Iryna Gurevych

Activation functions can have a significant impact on reducing the topological complexity of input data and therefore improve the performance of the model. Selecting a suitable activation function is an essential step in neural model design. However, the choice of activation function is seldom discussed or explored in Transformer-based language models. Their

Ivan de Martino, Antonaldo Diaferio, Luisa Ostorero

We show that measuring the proper motion of ${{\sim 2000}}$ stars within a dwarf galaxy, with an uncertainty of 1 km/s at most, can establish whether the Dark Matter (DM) density profile of the dwarf has a central core or cusp. We derive these limits by building mock star catalogues similar to those expected from future astrometric {\it Theia}-like missions

Domenico Cotroneo, Luigi De Simone, Roberto Natella

Railway signaling systems provide numerous critical functions at different safety level, to correctly implement the entire transport ecosystem. Today, we are witnessing the increasing use of the cloud and virtualization technologies in such mixed-criticality systems, with the main goal of reducing costs, improving reliability, while providing orchestration c

Félicien Appas, Othmane Meskine, Aristide Lemaître, José Palomo

The ability to combine various advanced functionalities on a single chip is a key issue for both classical and quantum photonic-based technologies. On-chip generation and handling of orthogonally polarized photon pairs, one of the most used resource in quantum information protocols, is a central challenge for the development of scalable quantum photonics cir

Takeru Yokota, Kanta Masuki, Yuto Ashida

A nonperturbative approach is developed to analyze superconducting circuits coupled to quantized electromagnetic continuum within the framework of the functional renormalization group. The formalism allows us to determine complete physical pictures of equilibrium properties in the circuit quantum electrodynamics (cQED) architectures with high-impedance waveg

Tobias Wand, Martin Heßler, Oliver Kamps

Understanding and forecasting changing market conditions in complex economic systems like the financial market is of great importance to various stakeholders such as financial institutions and regulatory agencies. Based on the finding that the dynamics of sector correlation matrices of the S&P 500 stock market can be described by a sequence of distinct state

Fernando Delgado, Nicolás Lorente

The development of electron spin resonance (ESR) combined with scanning tunneling spectroscopy (STM) is undoubtedly one of the main experimental breakthroughs in surface science of the last decade thanks to joining the extraordinarily high energy resolution of ESR (nano-eV scale) with the single-atom spatial resolution of STM (sub-\AA ngstr\"om scale). While

Chengjie Yuan, Yunlei Shi, Qian Feng, Chunyang Chang

Recently, deep reinforcement learning (RL) has shown some impressive successes in robotic manipulation applications. However, training robots in the real world is nontrivial owing to sample efficiency and safety concerns. Sim-to-real transfer is proposed to address the aforementioned concerns but introduces a new issue called the reality gap. In this work, w

Auronil Mukherjee, Arnab Chakraborty

The use of extended surfaces find wide range of applications in heat transfer devices for achieving heat transfer augmentation like gas turbine blade cooling and nuclear reactor core since the last few decades. So, understanding the underlying flow physics physics and the transport phenomenon governing the heat transfer enhancement is the goal of the present

M. Minuti, L. Baldini, R. Bellazzini, A. Brez

While the successful launch and operation in space of the Gas Pixel Detectors onboard the PolarLight cubesat and the Imaging X-ray Polarimetry Explorer demonstrate the viability and the technical soundness of this class of detectors for astronomical X-ray polarimetry, it is clear that the current state of the art is not ready to meet the challenges of the ne

Sindhu M, Medhavi Vishwakarma

Biological systems across various length and time scales are noisy, including tissues. Why are biological tissues inherently chaotic? Does heterogeneity play a role in determining the physiology and pathology of tissues? How do physical and biochemical heterogeneity crosstalk to dictate tissue function? In this review, we begin with a brief primer on heterog

M. Bzowski, M. A. Kubiak, E. Möbius, N. A. Schwadron

We analyze the reasons for the correlation between the temperature, direction, and speed of the interstellar neutral gas inflow into the heliosphere, obtained in analyzes of observations performed by the IBEX-Lo instrument onboard Interstellar Boundary Explorer (IBEX). We point out that this correlation is the combined result of the inability to measure the

Kehan Wu, Yingce Xia, Yang Fan, Pan Deng

Structure-based drug design is drawing growing attentions in computer-aided drug discovery. Compared with the virtual screening approach where a pre-defined library of compounds are computationally screened, de novo drug design based on the structure of a target protein can provide novel drug candidates. In this paper, we present a generative solution named

Alessio Moscariello

We prove that the Cohen-Macaulay type of an almost Gorenstein monomial curve $\mathcal{C} \subseteq \mathbb{A}^5$ is bounded.

Ana Borrego-Sanchez, Jayashrita Debnath, Michele Parrinello

A key step in the development of a new drug is the design of drug-excipient complexes that lead to an optimal drug release kinetics. Computational chemistry, specifically enhanced sampling molecular dynamics methods, can play a key role in this context by minimizing the need for expensive experiments and reducing cost and time. Here, we show that recent adva

Mile Mitrovic, Aleksandr Lukashevich, Petr Vorobev, Vladimir Terzija

The alternating current (AC) chance-constrained optimal power flow (CC-OPF) problem addresses the economic efficiency of electricity generation and delivery under generation uncertainty. The latter is intrinsic to modern power grids because of the high amount of renewables. Despite its academic success, the AC CC-OPF problem is highly nonlinear and computati

Binita Nath, Lorenzo Caprini, Claudio Maggi, Alessandra Zizzari

Sperm motility is a prerequisite for male fertility. Enhancing the concentration of motile sperms in assisted reproductive technologies - for human and animal reproduction - is typically achieved through aggressive methods such as centrifugation. Here we propose a passive technique for the amplification of motile sperm concentration, with no externally impos

Auronil Mukherjee, Arnab Chakraborty

Heat transfer augmentation is an essential requirement in all heat transfer devices, such as heat exchangers used in biomedical applications, electronic cooling, solar air heaters, nuclear reactor cores, and gas turbine blade cooling etc. Extended surfaces, protrusions, dimples, internal ribs or, grooves are among the few which are incorporated in the last t

Benjamin A. Reeves, Myles A. Steiner, Thomas E. Carver, Ze Zhang

Like many optoelectronics, the highest quality III-V solar cells start out as thin single-crystalline multilayers on GaAs substrates. Separating these device layers from their growth substrate enables higher performing devices and wafer reuse, both of which are critical for III-V solar cell viability in a terrestrial market. Here, we remove rigidly-bonded, l

Amyra Meidiana, Seok-Hee Hong, Peter Eades

Shape-based metrics measure how faithfully a drawing D represents the structure of a graph G, using the proximity graph S of D. While some limited graph classes admit proximity drawings (i.e., optimally shape-faithful drawings, where S = G), algorithms for shape-faithful drawings of general graphs have not been investigated. In this paper, we present the fir

Sevak Demirchyan, Igor Chestnov, Kirill Kondratenko, Alexey Kavokin

Recently, split-ring bosonic condensates of exciton polaritons have been proposed for realisation of qubits. We formulate an analytical model of a polariton condensate in a one-dimensional ring split by a delta-function potential. The persistent current is stopped by the potential defect embedded in a scalar condensate of non-interacting particles, however,

P. Mazzetti, A. Carbone

Periodic and nonperiodic components of electrophysiological signals are modelled in terms of syncronized sequences of closed loops of firing neurons correlated in Markov chains. Single closed loops of firing neurons reproduce fundamental and harmonic components, appearing as lines in the power spectra at frequencies ranging about from $0.5 Hz$ to $ 100 Hz$.

Yi Li, Wenjie Pei, Zhenyu He

The traditional homography estimation pipeline consists of four main steps: feature detection, feature matching, outlier removal and transformation estimation. Recent deep learning models intend to address the homography estimation problem using a single convolutional network. While these models are trained in an end-to-end fashion to simplify the homography

Fengxiang He, Dacheng Tao

This paper attempts to establish the theoretical foundation for the emerging super-model paradigm via domain adaptation, where one first trains a very large-scale model, {\it i.e.}, super model (or foundation model in some other papers), on a large amount of data and then adapts it to various specific domains. Super-model paradigms help reduce computational

Shruti Tandon, Raman I. Sujith

Thermoacoustic systems are complex systems where the interactions between the hydrodynamic, acoustic and heat release rate fluctuations lead to diverse dynamics such as chaos, intermittency, and ordered dynamics. Such complex interactions cause catastrophically high-amplitude acoustic pressure oscillations and the emergence of order in the spatio-temporal dy

Marco D'Anna, Alessio Moscariello

Given coprime positive integers $g_1 < \ldots < g_e$, the Frobenius number $F=F(g_1,\ldots,g_e)$ is the largest integer not representable as a linear combination of $g_1,\ldots,g_e$ with non-negative integer coefficients. Let $n$ denote the number of all representable non-negative integers less than $F$; Wilf conjectured that $F+1 \le e n$. We provide bounds

M. Tasevsky, V. A. Khoze, D. L. Milne, M. G. Ryskin

We study the possibility to observe heavy ($M_{\rm inst}> 60$ GeV) QCD instantons at the LHC in events with one or two tagged leading protons including fast simulation of detector and pile-up effects. We show that the expected instanton signal in a single-tagged configuration is strongly affected by central detector and pile-up effects. For double-tagged app

Sunny Vagnozzi, Abraham Loeb

Recent debates around the testability of the inflationary paradigm raise the question of how to model-independently discriminate it from competing scenarios. We argue that a detection of the Cosmic Graviton Background (CGB), the relic radiation from gravitons decoupling around the Planck time, would rule out the inflationary paradigm, as realistic inflationa

Daniele Dorigoni, Axel Kleinschmidt, Rudolfs Treilis

Modular graph functions arise in the calculation of the low-energy expansion of closed-string scattering amplitudes. For toroidal world-sheets, they are ${\rm SL}(2,\mathbb{Z})$-invariant functions of the torus complex structure that have to be integrated over the moduli space of inequivalent tori. We use methods from resurgent analysis to construct the non-

Jing Liu, Ligong Bian, Rong-Gen Cai, Zong-Kuan Guo

We investigate the curvature perturbations induced by the randomness of the quantum tunneling process during cosmological first-order phase transitions (PTs) and for the first time ultilize curvature perturbations to constrain the PT parameters. We find that the observations of the cosmic microwave background spectrum distortion and the ultracompact minihalo

Zicheng Zhang, Wei Sun, Yucheng Zhu, Xiongkuo Min

Point cloud is one of the most widely used digital representation formats for three-dimensional (3D) contents, the visual quality of which may suffer from noise and geometric shift distortions during the production procedure as well as compression and downsampling distortions during the transmission process. To tackle the challenge of point cloud quality ass

G. G. L. Nashed, K. Bamba

We explore an interior solution of a physically symmetric vierbein with two unknown functions in conformal teleparallel gravity. The field equations can be described in a closed system for a particular form of the metric potentials and an appropriate anisotropic function. As a result, we find a new set of configurations consistent with observed pulsars. In p

Pablo Corcho-Caballero, Yago Ascasibar, Sebastián F. Sánchez, Ángel López-Sánchez

We study recent changes on the star formation history (SFH) of galaxies by means of the ageing diagram (AD), tracing the fraction of stars formed during the last $\sim 20$ Myr through the equivalent width of the H$\alpha$ line and $\sim 1-3$ Gyr through the dust-corrected optical colour $(g-r)_0$ or the Balmer break. We provide a physical characterization by

Max Innerbichler, Andrei Militaru, Martin Frimmer, Lukas Novotny

Fluctuation theorems based on time-reversal have provided remarkable insight into the non-equilibrium statistics of thermodynamic quantities like heat, work, and entropy production. These types of laws impose constraints on the distributions of certain trajectory functionals that reflect underlying dynamical symmetries. In this work, we introduce a detailed

L. A. Ostrowski, T. J. Baker, S. N. Saadatmand, H. M. Wiseman

Recently it has been shown that it is possible for a laser to produce a stationary beam with a coherence (quantified as the mean photon number at spectral peak) which scales as the fourth power of the mean number of excitations stored within the laser, this being quadratically larger than the standard or Schawlow-Townes limit [1]. Moreover, this was analytic

L. A. Ostrowski, T. J. Baker, S. N. Saadatmand, H. M. Wiseman

The Heisenberg limit to laser coherence $\mathfrak{C}$ -- the number of photons in the maximally populated mode of the laser beam -- is the fourth power of the number of excitations inside the laser. We generalize the previous proof of this upper bound scaling by dropping the requirement that the beam photon statistics be Poissonian (i.e., Mandel's $Q=0$). W

Michele Pellegrino, Berk Hess

The motion of three-phase contact lines is one of the most relevant research topics of micro- and nano-fluidics. According to many hydrodynamic and molecular models, the dynamics of contact lines is assumed overdamped and dominated by localised liquid-solid friction, entailing the existence of a mobility relation between contact line speed and microscopic co

Valentin Gutev

The countably paracompact normal spaces were characterised by Dowker and Kat\v{e}tov in terms of an insertion property. Dowker also characterised them by normality of their product with the closed unit interval. Michael used the Dowker-Kat\v{e}tov insertion property to motivate his selection characterisation of these spaces. Morita extended in a natural way

Arijit Mondal, Gadha R., Rakesh S. Singh

Liquid water is well-known for its intriguing thermodynamic anomalies in the supercooled state. The phenomenological two-state models - based on the assumption of the existence of two types of competing local states (or, structures) in liquid water - have been extremely successful in describing water's thermodynamic anomalies. However, the precise structural