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In this study, we explored the fundamental contrast limit of NIRCam coronagraphy observations, representing the achievable performance with post-processing techniques. This limit is influenced by photon noise and readout noise, with complex noise propagation through post-processing methods like principal component analysis. We employed two approaches: developing a formula based on simplified scenarios and using Markov Chain Monte Carlo (MCMC) methods, assuming Gaussian noise properties and uncorrelated pixel noise. Tested on datasets HIP\,65426, AF\,Lep, and HD\,114174, the MCMC method provided accurate but computationally intensive estimates. The analytical approach offered quick, reliable estimates closely matching MCMC results in simpler scenarios. Our findings showed the fundamental contrast curve is significantly deeper than the current achievable contrast limit obtained with post-processing techniques at shorter separations, being 10 times deeper at $0.5''$ and 4 times deeper at $1''$. At greater separations, increased exposure time improves sensitivity, with the transition between photon and readout noise dominance occurring between $2''$ and $3''$. We conclude the analytical approach is a reliable estimate of the fundamental contrast limit, offering a faster alternative to MCMC. These results emphasize the potential for greater sensitivity at shorter separations, highlighting the need for improved or new post-processing techniques to enhance JWST NIRCam sensitivity or contrast curve., Comment: Proceeding of the SPIE July 2024

In this work, we have employed Monte Carlo calculations to study the Ising model on a 2D additive small-world network with long-range interactions depending on the geometric distance between interacting sites. The network is initially defined by a regular square lattice and with probability $p$ each site is tested for the possibility of creating a long-range interaction with any other site that has not yet received one. Here, we used the specific case where $p=1$, meaning that every site in the network has one long-range interaction in addition to the short-range interactions of the regular lattice. These long-range interactions depend on a power-law form, $J_{ij}=r_{ij}^{-\alpha}$, with the geometric distance $r_{ij}$ between connected sites $i$ and $j$. In current two-dimensional model, we found that mean-field critical behavior is observed only at $\alpha=0$. As $\alpha$ increases, the network size influences the phase transition point of the system, i.e., indicating a crossover behavior. However, given the two-dimensional system, we found the critical behavior of the short-range interaction at $\alpha\approx2$. Thus, the limitation in the number of long-range interactions compared to the globally coupled model, as well as the form of the decay of these interactions, prevented us from finding a regime with finite phase transition points and continuously varying critical exponents in $0<\alpha<2$., Comment: 7 pages, 8 figures, 2 tables

The search for biosignatures in potentially habitable exoplanets is one of the major astrophysics' drivers for the coming decades, and the prime science goal of the HWO NASA mission, a large UV-Optical-IR space telescope to be launched in the 2040s. To reach this goal, it will be equipped with state-of-the-art high-contrast spectro-imaging capabilities enabling the detection of exoplanets 10^10 times fainter than their host stars, a formidable challenge given today's best detection limits at ~10^-6 contrast levels. This goal puts stringent constraints on the entire observatory, and demands the optimization at the system level to leverage the performance of individual sub-systems. However, while image processing techniques are a key asset to reach the ultimate performance, the science and technological definition of the mission concepts mostly rely on the coronagraph and wavefront control to reject the starlight, assuming a conservative gain of ~10 in sensitivity from image processing, extrapolated from performance obtained with classical techniques on Hubble observations. In the ESCAPE project, we investigate integrated solutions for optimizing the observing methods and data processing techniques with future space telescopes, making use of their wavefront sensors and deformable mirrors. The Roman Space Telescope, scheduled for launch in 2026, will be a critical milestone to demonstrate key technologies ahead of HWO with the Coronagraph instrument, and is thus a unique opportunity to also test and validate innovative image processing techniques. Here we present the rational, methodology, and timeline of the ESCAPE project., Comment: Proceedings of the 2024 SPIE Astronomical Telescopes + Instrumentation conference

Layered two-dimensional (2D) semiconductors have shown enhanced ion migration capabilities along their van der Waals (vdW) gaps and on their surfaces. This effect can be employed for resistive switching (RS) in devices for emerging memories, selectors, and neuromorphic computing. To date, all lateral molybdenum disulfide (MoS${_2}$)-based volatile RS devices with silver (Ag) ion migration have been demonstrated using exfoliated, single-crystal MoS${_2}$ flakes requiring a forming step to enable RS. Here, we present volatile RS with multilayer MoS${_2}$ grown by metal-organic chemical vapor deposition (MOCVD) with repeatable forming-free operation. The devices show highly reproducible volatile RS with low operating voltages of approximately 2 V and fast switching times down to 130 ns considering their micrometer scale dimensions. We investigate the switching mechanism based on Ag ion surface migration through transmission electron microscopy, electronic transport modeling, and density functional theory. Finally, we develop a physics-based compact model and explore the implementation of our volatile memristors as artificial neurons in neuromorphic systems., Comment: 43 pages

In this paper, we study the mechanical system associated with rolling a Lorentzian manifold $(M,g)$ of dimension $n+1\geq2$ on flat Lorentzian space $\widehat{M}={\mathbb R}^{n,1}$, without slipping or twisting. Using previous results, it is known that there exists a distribution $\mathcal{D}_R$ of rank $(n+1)$ defined on the configuration space $Q(M,\widehat{M})$ of the rolling system, encoding the no-slip and no-twist conditions. Our objective is to study the problem of complete controllability of the control system associated with $\mathcal{D}_R$. The key lies in examining the holonomy group of the distribution $\mathcal{D}_R$ and, following the approach of \cite{ChKok}, establishing that the rolling problem is completely controllable if and only if the holonomy group of $(M,g)$ equals $SO_0(n,1)$., Comment: 13 pages

There is interest in learning about the causal effect of family planning (FP) on empowerment related outcomes. Experimental data related to this question are available from trials in which FP programs increase access to FP. While program assignment is unconfounded, FP uptake and subsequent empowerment may share common causes. We use principal stratification to estimate the causal effect of an intermediate FP outcome on a primary outcome of interest, among women affected by a FP program. Within strata defined by the potential reaction to the program, FP uptake is unconfounded. To minimize the need for parametric assumptions, we propose to use Bayesian Additive Regression Trees (BART) for modeling stratum membership and outcomes of interest. We refer to the combined approach as Prince BART. We evaluate Prince BART through a simulation study and use it to assess the causal effect of modern contraceptive use on employment in six cities in Nigeria, based on quasi-experimental data from a FP program trial during the first half of the 2010s. We show that findings differ between Prince BART and alternative modeling approaches based on parametric assumptions.

Occupancy Grids have been widely used for perception of the environment as they allow to model the obstacles in the scene, as well as free and unknown space. Recently, there has been a growing interest in the unknown space due to the necessity of better understanding the situation. Although Occupancy Grids have received numerous extensions over the years to address emerging needs, currently, few works go beyond the delimitation of the unknown space area and seek to incorporate additional information. This work builds upon the already well-established LiDAR-based Dynamic Occupancy Grid to introduce a complementary Categorized Grid that conveys its estimation using semantic labels while adding new insights into the possible causes of unknown space. The proposed categorization first divides the space by occupancy and then further categorizes the occupied and unknown space. Occupied space is labeled based on its dynamic state and reliability, while the unknown space is labeled according to its possible causes, whether they stem from the perception system's inherent constraints, limitations induced by the environment, or other causes. The proposed Categorized Grid is showcased in real-world scenarios demonstrating its usefulness for better situation understanding., Comment: Submitted to the 27th IEEE International Conference on Intelligent Transportation Systems

Let $G$ and $H$ be locally compact groups. We will show that each contractive Jordan isomorphism $\Phi\colon L^1(G)\to L^1(H)$ is either an isometric isomorphism or an isometric anti-isomorphism. We will apply this result to study isometric two-sided zero product preservers on group algebras and, further, to study local and approximately local isometric automorphisms of group algebras.

This article explores Multimodal Analytics' use in assessing communication within agile software development, particularly through planning poker, to understand collaborative behavior. Multimodal Analytics examines verbal, paraverbal, and non-verbal communication, crucial for effective collaboration in software engineering, which demands efficient communication, cooperation, and coordination. The study focuses on how planning poker influences speaking time and attention among team members by utilizing advanced audiovisual data analysis technologies. Results indicate that while planning poker doesn't significantly change total speaking or attention time, it leads to a more equitable speaking time distribution, highlighting its benefit in enhancing equitable team participation. These findings emphasize planning poker's role in improving software team collaboration and suggest multimodal analytics' potential to explore new aspects of team communication. This research contributes to better understanding coordination techniques' impact in software development and team education, proposing future investigations into optimizing team collaboration and performance through alternative coordination techniques and multimodal analysis across different collaborative settings.

We classify the nilpotent almost abelian Lie algebras admitting complex or symplectic structures. It turns out that if a nilpotent almost abelian Lie algebra admits a complex structure, then it necessarily admits a symplectic structure. Given an even dimensional almost abelian Lie algebra, we show that it always admits a complex structure when it is 2-step nilpotent and it always admits a symplectic structure when it is $k$-step nilpotent for $k=2, \, 3$ or $4$. Several consequences of the classification theorems are obtained.

While the mission's primary goal was focused on exoplanet detection and characterization, Kepler made and continues to make extraordinary advances in stellar physics. Stellar rotation and magnetic activity are no exceptions. Kepler allowed for these properties to be determined for tens of thousands of stars from the main sequence up to the red giant branch. From photometry, this can be achieved by investigating the brightness fluctuations due to active regions, which cause surface inhomogeneities, or through asteroseismology as oscillation modes are sensitive to rotation and magnetic fields. This review summarizes the rotation and magnetic activity properties of the single main-sequence solar-like stars within the Kepler field. We contextualize the Kepler sample by comparing it to known transitions in the stellar rotation and magnetic-activity evolution, such as the convergence to the rotation sequence (from the saturated to the unsaturated regime of magnetic activity) and the Vaughan-Preston gap. While reviewing the publicly available data, we also uncover one interesting finding related to the intermediate-rotation gap seen in Kepler and other surveys. We find evidence for this rotation gap in previous ground-based data for the X-ray luminosity. Understanding the complex evolution and interplay between rotation and magnetic activity in solar-like stars is crucial, as it sheds light on fundamental processes governing stellar evolution, including the evolution of our own Sun., Comment: Review paper, 36 pages, 10 figures

Meta-stable states are identified in the Ising model with competition between the Glauber and Kawasaki dynamics. The model of interaction between magnetic moments was implemented on a network where the degree distribution follows a power-law of the form, $P(k)\sim k^{-\alpha}$. The evolution towards the stationary state occurred through the competition between two dynamics, driving the system out of equilibrium. In this competition, with probability $q$, the system was simulated in contact with a heat bath at temperature $T$ by the Glauber dynamics, while with probability $1-q$, the system experienced an external energy influx governed by the Kawasaki dynamics. The phase diagrams of $T$ versus $q$ were obtained, which are dependent on the initial state of the system, and exhibit first- and second-order phase transitions. In all diagrams, for intermediate values of $T$, the phenomenon of self-organization between the ordered phases was observed. In the regions of second-order phase transitions, we have verified the universality class of the system through the critical exponents of the order parameter $\beta$, susceptibility $\gamma$, and correlation length $\nu$. Furthermore, in the regions of first-order phase transitions, we have demonstrated the instability due to transitions between the ordered phases through hysteresis-like curves of the order parameter, in addition to the existence of absorbing states. We also estimated the value of the tricritical points when the discontinuity in the order parameter in the phase transitions was no longer observed., Comment: 12 pages and 10 figures

Monochromatic gamma-ray signals constitute a potential smoking gun signature for annihilating or decaying dark matter particles that could relatively easily be distinguished from astrophysical or instrumental backgrounds. We provide an updated assessment of the sensitivity of the Cherenkov Telescope Array (CTA) to such signals, based on observations of the Galactic centre region as well as of selected dwarf spheroidal galaxies. We find that current limits and detection prospects for dark matter masses above 300 GeV will be significantly improved, by up to an order of magnitude in the multi-TeV range. This demonstrates that CTA will set a new standard for gamma-ray astronomy also in this respect, as the world's largest and most sensitive high-energy gamma-ray observatory, in particular due to its exquisite energy resolution at TeV energies and the adopted observational strategy focussing on regions with large dark matter densities. Throughout our analysis, we use up-to-date instrument response functions, and we thoroughly model the effect of instrumental systematic uncertainties in our statistical treatment. We further present results for other potential signatures with sharp spectral features, e.g.~box-shaped spectra, that would likewise very clearly point to a particle dark matter origin., Comment: 44 pages JCAP style (excluding author list and references), 19 figures; minor changes to match published version

We give sufficient conditions on a labeled direct graph to determine whether the Tanaka prolongation of its associated Lie algebra is infinite-dimensional. In the case that all directed edges are labeled differently, the corresponding graph Lie algebra is of infinite type if and only if the graph has a vertex of degree one., Comment: 5 pages

Understanding social immunity mechanisms in ant colonies remains crucial to comprehending the evolution of defense strategies in eusocial organisms. This study assumes the absence of the role of memory in the ants' defense strategy, considering that they can make a new exploration of collective cleaning behaviors. We investigate how worker interactions and previous behaviors influence the evolution of social immunity strategies in response to the presence of pathogens and vulnerable colony members. In this context, with the application of Markov transition models it was possible to describe changes in cleaning behavior over time influenced by the presence of vulnerable members and treatment with an entomopathogenic fungus. We found a significant effect on ant behavior when exposed to \it{Metarhizium anisopliae} when a fungus garden fragment and one larva were present. Our findings confirm a link between prophylactic cleaning and the presence of vulnerable members. Remarkably, distinct behaviors and transition times vary among treatments, revealing workers' adaptability to threats. Allogrooming shows adaptive changes when exposed to pathogens, potentially affecting pathogen transmission. In addition, our study elucidates the intricate interaction between internal and external factors shaping worker behavior. The influence of environmental context on decision-making principles emerges, emphasizing the importance of both intrinsic colony organization and external threats. By using a Markov model to understand ant hygiene behavior, we offer insights into social immunity mechanisms in eusocial organisms. Deciphering collective cleaning strategies can aid in understanding disease dynamics and decision-making processes in complex societies., Comment: 22 pages

Previous studies have found that red giants (RGs) in close binary systems undergoing spin-orbit resonance exhibit an enhanced level of magnetic activity with respect to single RGs rotating at the same rate, from measurements of photometric variability $S'_{ph}$ and chromospheric emission S-index $S_{Ca_{II}}$. Here, we consider a sample of 4465 RGs observed by the NASA Kepler mission to measure additional activity indicators that probe different heights in the chromosphere: the near-ultraviolet (NUV) excess from NASA GALEX photometric data, and chromospheric indices based on the depth of H$\alpha$, Mg$_{I}$ and infared Ca$_{II}$ absorption lines from LAMOST spectroscopic data. Firstly, as for Ca$_{II}$ H&K, we observe that RGs belonging to close binaries in a state of spin-orbit resonance display larger chromospheric emission than the cohort of RGs, as illustrated by an NUV excess and shallower H$\alpha$ and infrared Ca$_{II}$ lines. We report no excess of Mg$_{I}$ emission. This result reinforces previous claims that tidal locking leads to enhanced magnetic fields, and allows us to provide criteria to classify active red giants -- single or binary --, based on their rotation periods and magnetic activity indices. Secondly, we strikingly observe that the depths of the Mg$_{I}$ and H$\alpha$ lines are anti-correlated and correlated, respectively, with the amplitude of solar-like oscillations for a given surface gravity $\log g$, regardless of the presence of photometric rotational modulation. Such a correlation opens up future possibilities of estimating the value of magnetic fields at the surface of RG stars, whether quiet or active, by combining spectroscopic and asteroseismic measurements with three-dimensional atmospheric models including radiative transfer., Comment: Accepted for publication in A&A. 16 pages, 9 figures

We investigate the impact of confinement density (i.e the number of individuals in a group per unit area of available space) on transitions from polarized to milling state, using groups of rummy-nose tetra fish (\textit{Hemigrammus rhodostomus}) under controlled experimental conditions. We demonstrate a continuous state transition controlled by confinement density in a group of live animals. During this transition, the school exhibits a bistable state, wherein both polarization and milling states coexist, with the group randomly alternating between them. A simple two-state Markov process describes the observed transition remarkably well. The confinement density influences the statistics of this bistability, shaping the distribution of transition times between states. Our findings suggest that confinement plays a crucial role in state transitions for moving animal groups. More generally, they provide an experimental benchmark for active matter models of macroscopic, self-propelled, confined agents., Comment: 9 pages, 8 figures. One supplementary movie

Implementing insect monitoring systems provides an excellent opportunity to create accurate interventions for insect control. However, selecting the appropriate time for an intervention is still an open question due to the inherent difficulty of implementing on-site monitoring in real-time. This decision is even more critical with insect species that can abruptly increase population size. A possible solution to enhance decision-making is to apply forecasting methods to predict insect abundance. However, another layer of complexity is added when other covariates are considered in the forecasting, such as climate time series collected along the monitoring system. Multiple possible combinations of climate time series and their lags can be used to build a forecasting method. Therefore, this research paper proposes a new approach to address this problem by combining statistics, machine learning, and time series embedding. We used two datasets containing a time series of aphids and climate data collected weekly in Coxilha and Passo Fundo municipalities in Southern Brazil for eight years. We conduct a simulation study based on a probabilistic autoregressive model with exogenous time series based on Poisson and negative binomial distributions to check the influence of incorporating climate time series on the performance of our approach. We pre-processed the data using our newly proposed approach and more straightforward approaches commonly used to train machine learning algorithms in time series problems. We evaluate the performance of the selected machine algorithms by looking at the Root Mean Squared Error obtained using one-step-ahead forecasting. Based on Random Forests, Lasso-regularised linear regression, and LightGBM regression algorithms, our novel approach yields competitive forecasts while automatically selecting insect abundances, climate time series and their lags to aid forecasting., Comment: 27 pages

Major advancements in computer vision can primarily be attributed to the use of labeled datasets. However, acquiring labels for datasets often results in errors which can harm model performance. Recent works have proposed methods to automatically identify mislabeled images, but developing strategies to effectively implement them in real world datasets has been sparsely explored. Towards improved data-centric methods for cleaning real world vision datasets, we first conduct more than 200 experiments carefully benchmarking recently developed automated mislabel detection methods on multiple datasets under a variety of synthetic and real noise settings with varying noise levels. We compare these methods to a Simple and Efficient Mislabel Detector (SEMD) that we craft, and find that SEMD performs similarly to or outperforms prior mislabel detection approaches. We then apply SEMD to multiple real world computer vision datasets and test how dataset size, mislabel removal strategy, and mislabel removal amount further affect model performance after retraining on the cleaned data. With careful design of the approach, we find that mislabel removal leads per-class performance improvements of up to 8% of a retrained classifier in smaller data regimes.

With the increasing number of internet-based resources and applications, the amount of attacks faced by companies has increased significantly in the past years. Likewise, the techniques to test security and emulate attacks need to be constantly improved and, as a consequence, help to mitigate attacks. Among these techniques, penetration test (Pentest) provides methods to assess the security posture of assets, using different tools and methodologies applied in specific scenarios. Therefore, this study aims to present current methodologies, tools, and potential challenges applied to Pentest from an updated systematic literature review. As a result, this work provides a new perspective on the scenarios where penetration tests are performed. Also, it presents new challenges such as automation of techniques, management of costs associated with offensive security, and the difficulty in hiring qualified professionals to perform Pentest., Comment: 11 pages, 2 figures. Paper presented at World Conference on Smart Trends in Systems, Security, and Sustainability (WorldS4 2023)

Computational and data-enabled science and engineering are revolutionizing advances throughout science and society, at all scales of computing. For example, teams in the U.S. DOE Exascale Computing Project have been tackling new frontiers in modeling, simulation, and analysis by exploiting unprecedented exascale computing capabilities-building an advanced software ecosystem that supports next-generation applications and addresses disruptive changes in computer architectures. However, concerns are growing about the productivity of the developers of scientific software, its sustainability, and the trustworthiness of the results that it produces. Members of the IDEAS project serve as catalysts to address these challenges through fostering software communities, incubating and curating methodologies and resources, and disseminating knowledge to advance developer productivity and software sustainability. This paper discusses how these synergistic activities are advancing scientific discovery-mitigating technical risks by building a firmer foundation for reproducible, sustainable science at all scales of computing, from laptops to clusters to exascale and beyond., Comment: 12 pages, 1 figure