Hasil untuk "Astronomy"

U. Fayyad

C. H. Lucas Patty, Jonathan Grone, Brice-Olivier Demory et al.

In recent decades, the relevance of polarimetry in planetary sciences and astronomy has increased rapidly. Polarization is a fundamental property of light and can be modified by any scattering event. As such, polarization yields additional information that cannot be obtained by only assessing light's scalar properties. For instance, the polarization state of starlight scattered by planetary surfaces can provide useful insights on the composition, size, morphology, and porosity of regolith particles and might even indicate the presence of life. Beside being useful for characterization, polarimetry can also greatly enhance the detection of exoplanets. Here, polarization can be harnessed to enhance the contrast between the bright light of a star, which can be considered to be fully unpolarized, and the very dim but polarized light reflected by an exoplanet. In this paper, we discuss and review the current developments and advances in optical polarimetry and polarimetric instrumentation in Switzerland within the framework of the National Centre of Competence in Research PlanetS. We focus on their implications for the vast range of science cases that polarimetry can address within the research fields of planetary science and astronomy.

Alexander Venner, Andrew Vanderburg, Chelsea X. Huang et al.

The transit method is currently one of our best means for the detection of potentially habitable “Earth-like” exoplanets. In principle, given sufficiently high photometric precision, cool Earth-sized exoplanets orbiting Sun-like stars could be discovered via single transit detections; however, this has not previously been achieved. In this work, we report a 10 hr long single transit event which occurred on the V = 10.1 K-dwarf HD 137010 during K2 Campaign 15 in 2017. This transit is comparatively shallow (225 ± 10 ppm) but is detected at high signal-to-noise thanks to the exceptionally high photometric precision achieved for the target. Our analysis of the K2 photometry, historical and new imaging observations, and archival radial velocities and astrometry strongly indicate that the event was astrophysical, occurred on-target, and can be best explained by a transiting planet candidate, which we designate HD 137010 b. The single observed transit implies a radius of $1.0{6}_{-0.05}^{+0.06}\,{R}_{\oplus }$ , and assuming negligible orbital eccentricity we estimate an orbital period of $35{5}_{-59}^{+200}$ days ( $a=0.8{8}_{-0.10}^{+0.32}$ au), properties comparable to Earth. We project an incident flux of $0.2{9}_{-0.13}^{+0.11}\,{I}_{\oplus }$ , which would place HD 137010 b near the outer edge of the habitable zone. This is the first planet candidate with Earth-like radius and orbital properties transiting a Sun-like star bright enough for substantial follow-up observations.

F. Zaniboni, L. Sabino, C. Angeli et al.

<p>Campi Flegrei, one of the most monitored and studied volcanic areas in the world, has recently attracted significant attention due to the reactivation of its peculiar activity, consisting of small earthquakes, geothermal phenomena and slow subsidence/rapid uplift cycles, known as bradyseism. While much of the research and of the attention focuses on potential eruptions or other volcanic-related activities, the potential hazard posed by gravitational instabilities has received little consideration. The interaction of the destabilized masses with water can trigger tsunamis, potentially affecting the whole coastline of the Gulf of Pozzuoli, which lies above the Campi Flegrei caldera. Moving from the limited available geomorphological studies of the area, a set of four landslide-tsunami scenarios (one subaerial and three submarine sources) are reconstructed. These are simulated through a sequence of numerical codes, accounting for all the phases of the tsunami process, providing insights into the distribution of tsunami energy and identifying the most affected coastal stretches. Additionally, the study explores the influence of dispersion effects in the tsunami propagation and the occurrence of resonance effects in some minor inlets of the Gulf, emphasizing the importance of accounting for complex and non-linear coastal processes when treating landslide-generated tsunamis.</p>

Yuan-Sen Ting, Teaghan O'Briain

We present a study of LLM integration in final-year undergraduate astronomy education, examining how students develop AI literacy through structured guidance and documentation requirements. We developed AstroTutor, a domain-specific astronomy tutoring system enhanced with curated arXiv content, and deployed it alongside general-purpose LLMs in the course. Students documented their AI usage through homework reflections and post-course surveys. We analyzed student evolution in AI interaction strategies and conducted experimental comparisons of LLM-assisted versus traditional grading methods. LLM grading showed strong correlation with human evaluation while providing more detailed and consistent feedback. We also piloted LLM-facilitated interview-based examinations as a scalable alternative to traditional assessments, demonstrating potential for individualized evaluation that addresses common testing limitations. Students experienced decreased rather than increased reliance on LLMs over the semester, developing critical evaluation skills and strategic tool selection. They evolved from basic assistance-seeking to verification workflows, with documentation requirements fostering metacognitive awareness. Students developed effective prompting strategies, contextual enrichment techniques, and cross-verification practices. Our findings suggest that structured LLM integration with transparency requirements and domain-specific tools can enhance astronomy education while building essential AI literacy skills. We provide implementation guidelines for educators and make our AstroTutor repository freely available.

Rafael S. de Souza, Emille E. O. Ishida, Alberto Krone-Martins

In this short review, we trace the evolution of inference in astronomy, highlighting key milestones rather than providing an exhaustive survey. We focus on the shift from classical optimization to Bayesian inference, the rise of gradient-based methods fueled by advances in deep learning, and the emergence of adaptive models that shape the very design of scientific datasets. Understanding this shift is essential for appreciating the current landscape of astronomical research and the future it is helping to build.

Ankan Sur, Adam Burrows, Roberto Tejada Arevalo et al.

Computed using the APPLE planetary evolution code, we present updated evolutionary models for Jupiter and Saturn that incorporate helium rain, nonadiabatic thermal structures, and “fuzzy” extended heavy-element cores. Building on our previous Ledoux-stable models, we implement improved atmospheric boundary conditions that account for composition-dependent effective temperatures and systematically explore the impact of varying the parameter R _ρ , which allows one to explore in an approximate way the efficiency of semiconvection. For both Jupiter and Saturn, we construct models spanning from R _ρ = 1 (Ledoux) to R _ρ = 0 (Schwarzschild), and identify best-fit solutions that match each planet’s effective temperature, equatorial radius, lower-order gravitational moments, and atmospheric composition at 4.56 Gyr. We find that lower R _ρ values lead to stronger convective mixing, resulting in higher surface metallicities and lower deep interior temperatures, while requiring reduced heavy-element masses and lower initial entropies to stabilize the dilute inner cores. Our Saturn models also broadly agree with the observed Brunt–Väisälä frequency profile inferred from Cassini ring seismology, with stable layers arising from both the helium rain region and the dilute core. These findings support the presence of complex, compositionally stratified interiors in both gas giants.

Feng Chen, Wei-Wei Luo, Wei Zhu et al.

Abstract A recent experiment has observed a series of quantum-spin-Hall effects in moiré MoTe2. Among them, the vanishing Hall signal at the filling factor ν  = 3 implies a possible realization of a time-reversal pair of even-denominator fractional Chern insulators. Inspired by this discovery, we numerically investigate whether a robust incompressible quantum-Hall liquid can be stabilized in the half-filled Chern band of twisted MoTe2 bilayers. We use the continuum model with parameters relevant to twisted MoTe2 bilayers and obtain three consecutive nearly flat Chern bands with the same Chern number. Crucially, when the second moiré miniband is half-filled, signatures of a non-Abelian fractional quantum-Hall state are found via exact diagonalization calculations, including a stable six-fold ground-state degeneracy that grows more robust with the lattice size and is consistent with an even-denominator fractional Chern insulator state. Our results signal the potential of realizing the non-Abelian state at zero magnetic field in twisted bilayer MoTe2 at the fractional hole filling of 3/2.

Kartik Sheth, Kevin Govender, Vanessa McBride et al.

Policy Brief on "Workforce Development in Astronomy and Astroinformatics", distilled from the corresponding panel that was part of the discussions during S20 Policy Webinar on Astroinformatics for Sustainable Development held on 6-7 July 2023. The discipline of astronomy and astroinformatics is dynamically evolving thereby creating a compelling opportunity to foster a more inclusive, diverse, and proficient workforce. This is crucial for addressing multifaceted challenges that emerge as we progress and harness the potential therein. To realize this goal, it's imperative to cultivate strategies that promote inclusive practices in STEM education, encourage participation from historically excluded groups, provide training and mentorship, as well as provide active champions, especially for students and early career professionals from (historically) excluded groups. We provide an overview of the current status, resources available, and possible steps especially keeping in mind large international projects. The policy webinar took place during the G20 presidency in India (2023). A summary based on the seven panels can be found here: arxiv:2401.04623.

Thomas Cecconello, Simone Riggi, Ugo Becciani et al.

The upcoming Square Kilometer Array (SKA) telescope marks a significant step forward in radio astronomy, presenting new opportunities and challenges for data analysis. Traditional visual models pretrained on optical photography images may not perform optimally on radio interferometry images, which have distinct visual characteristics. Self-Supervised Learning (SSL) offers a promising approach to address this issue, leveraging the abundant unlabeled data in radio astronomy to train neural networks that learn useful representations from radio images. This study explores the application of SSL to radio astronomy, comparing the performance of SSL-trained models with that of traditional models pretrained on natural images, evaluating the importance of data curation for SSL, and assessing the potential benefits of self-supervision to different domain-specific radio astronomy datasets. Our results indicate that, SSL-trained models achieve significant improvements over the baseline in several downstream tasks, especially in the linear evaluation setting; when the entire backbone is fine-tuned, the benefits of SSL are less evident but still outperform pretraining. These findings suggest that SSL can play a valuable role in efficiently enhancing the analysis of radio astronomical data. The trained models and code is available at: \url{https://github.com/dr4thmos/solo-learn-radio}

Vinícius Barros da Silva, João Peres Vieira, Edson Denis Leonel

The detection of limit cycles of differential equations poses a challenge due to the type of the nonlinear system, the regime of interest, and the broader context of applicable models. Consequently, attempts to solve Hilbert’s sixteenth problem on the maximum number of limit cycles of polynomial differential equations have been uniformly unsuccessful due to failing results and their lack of consistency. Here, the answer to this problem is finally obtained through information geometry, in which the Riemannian metrical structure of the parameter space of differential equations is investigated with the aid of the Fisher information metric and its scalar curvature R. We find that the total number of divergences of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>|</mo><mi mathvariant="normal">R</mi><mo>|</mo></mrow></semantics></math></inline-formula> to infinity provides the maximum number of limit cycles of differential equations. Additionally, we demonstrate that real polynomial systems of degree <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>n</mi><mo>≥</mo><mn>2</mn></mrow></semantics></math></inline-formula> have the maximum number of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>2</mn><mo>(</mo><mi>n</mi><mo>−</mo><mn>1</mn><mo>)</mo><mo>(</mo><mn>4</mn><mo>(</mo><mi>n</mi><mo>−</mo><mn>1</mn><mo>)</mo><mo>−</mo><mn>2</mn><mo>)</mo></mrow></semantics></math></inline-formula> limit cycles. The research findings highlight the effectiveness of geometric methods in analyzing complex systems and offer valuable insights across information theory, applied mathematics, and nonlinear dynamics. These insights may pave the way for advancements in differential equations, presenting exciting opportunities for future developments.

Ruslan Sherstyukov, Samson Moges, Alexander Kozlovsky et al.

Abstract Typical ionosondes operate with >5 min time intervals, which is enough to obtain regular parameters of the ionosphere, but insufficient to observe short‐term processes in the Earth's ionosphere. The key point for this study is to increase the ionosondes data time resolution by automatization of ionogram scaling routine. In this study we show the results of implementation of deep learning approach for ionogram parameters scaling. We trained the model on 13 years ionogram data set of Sodankyla ionosonde at high latitude region (67°N). We tested our autoscaling program tool on 2021 years data set and evaluate errors between operator and automatic parameters scaling. The root mean square errors for critical frequencies foF2, foF1, foE, foEs, fmin, fbEs and virtual heights h′F, h′E, h′Es are estimated as 0.12 MHz (2 pixels), 0.07 MHz (1.16 pixels), 0.15 MHz (2.5 pixels), 0.33 MHz (5.5 pixels), 0.15 MHz (2.5 pixels), 0.17 MHz (2.83 pixels), 7.7 km (1.34 pixels), 7.0 km (1.22 pixels), 7.1 km (1.24 pixels), respectively.

Salomé A. Sepúlveda-Fontaine, José M. Amigó

Since its origin in the thermodynamics of the 19th century, the concept of entropy has also permeated other fields of physics and mathematics, such as Classical and Quantum Statistical Mechanics, Information Theory, Probability Theory, Ergodic Theory and the Theory of Dynamical Systems. Specifically, we are referring to the classical entropies: the Boltzmann–Gibbs, von Neumann, Shannon, Kolmogorov–Sinai and topological entropies. In addition to their common name, which is historically justified (as we briefly describe in this review), another commonality of the classical entropies is the important role that they have played and are still playing in the theory and applications of their respective fields and beyond. Therefore, it is not surprising that, in the course of time, many other instances of the overarching concept of entropy have been proposed, most of them tailored to specific purposes. Following the current usage, we will refer to all of them, whether classical or new, simply as entropies. In particular, the subject of this review is their applications in data analysis and machine learning. The reason for these particular applications is that entropies are very well suited to characterize probability mass distributions, typically generated by finite-state processes or symbolized signals. Therefore, we will focus on entropies defined as positive functionals on probability mass distributions and provide an axiomatic characterization that goes back to Shannon and Khinchin. Given the plethora of entropies in the literature, we have selected a representative group, including the classical ones. The applications summarized in this review nicely illustrate the power and versatility of entropy in data analysis and machine learning.

L. Canete, S. Giraud, A. Kankainen et al.

Isomers close to the doubly magic nucleus 78Ni (Z=28, N=50) provide essential information on the shell evolution and shape coexistence far from stability. The existence of a long-lived isomeric state in 76Cu has been debated for a long time. We have performed high-precision mass measurements of 76Cu with the JYFLTRAP double Penning trap mass spectrometer at the Ion Guide Isotope Separator On-Line facility and confirm the existence of such an isomeric state with an excitation energy Ex=64.8(25) keV. Based on the ratio of detected ground- and isomeric-state ions as a function of time, we show that the isomer is the shorter-living state previously considered as the ground state of 76Cu. The result can potentially change the conclusions made in previous works related to the spin-parity and charge radius of the 76Cu ground state. Additionally, the new 76Cu(n,γ) reaction Q-value has an impact on the astrophysical rapid neutron-capture process.

Vinicius Sanches, Fabiene Barbosa da Silva

The observation of space seems to have always caused wonder into people's collective consciousness, generating a series of historical myths. More recently specially with the development of better tools alongside the constant refinement of the scientific method Astronomy has consolidated into increasing field of Physics. Yet, representing such field in an accurate manner for beginner students poses a challenge. Appropriate images and descriptions should be chosen, which proves itself a large part of such challenge. Here we perform a technique named Interdisciplinary Image Reading aimed at trying to minimize the problem by improving and therefore promoting better Astronomy Education.

Michal Křížek, Lawrence Somer

We show that masses of binary black hole mergers are overestimated, since a large gravitational redshift is not taken into account. Such a phenomenon occurs due to time dilation in a close neighborhood of any black hole. This fact allows us to explain a high mass gap between observed binary neutron stars and calculated binary black hole mergers. We also present other reasons why masses of black hole mergers are determined incorrectly.

Yong‐Keun Lee, Christopher Grassotti, Quanhua (Mark) Liu et al.

Abstract The National Oceanic and Atmospheric Administration (NOAA) Microwave Integrated Retrieval System (MiRS) algorithm has been producing retrieval products from NOAA‐20 Advanced Technology Microwave Sounder (ATMS) data since shortly after launch in late 2017. Retrieval products from the Suomi National Polar‐orbiting Partnership (SNPP) ATMS data have been similarly available since 2012. Among the products routinely generated is Total Precipitable Water (TPW), based on the vertical integral of the MiRS retrieved water vapor profile. In this study, TPW data from NOAA‐20 ATMS have been the subject of an in‐depth evaluation. The evaluation included characterization of dependence on orbital node (ascending/descending), season, surface type, scan angle, and meridional (zonally averaged) variation. Due to the similarity between NOAA‐20 and SNPP derived TPW, the emphasis here is on the NOAA‐20 evaluation. The globally averaged values of TPW for 2019 are 25.41 and 25.39 mm from NOAA‐20 and SNPP ATMS, respectively, for combined orbits (ascending and descending). For combined orbits, the bias and standard deviation of MiRS NOAA‐20 ATMS TPW with respect to European Centre for Medium‐Range Weather Forecasts/Global Data Assimilation System (ECMWF/GDAS) analyses are 0.79/1.76 mm and 3.65/3.55 mm, respectively, at 10°N where part of annual mean Intertropical Convergence Zone (ITCZ) is located, while at 40°N, corresponding bias and standard deviation values are 0.84/0.67 mm and 3.00/2.55 mm, respectively. The yearly averaged horizontal distribution of MiRS TPW retrieved from NOAA‐20 ATMS is highly correlated with that of ECMWF and GDAS analyses data, with a correlation coefficient of ∼1.

Melanie Archipley, Hannah S. Dalgleish

The International Astronomical Youth Camp (IAYC) is an astronomy education outreach event with more than 50 years of history and over 1,700 unique participants from 81 nationalities. The International Workshop for Astronomy e.V. (IWA) is the non-profit organization behind the IAYC, established in 1979 and based in Germany. The IAYC's unprecedented longevity in a rapidly globalizing world has meant that financial inequities decreases the reach of the camp to people from the Global South compared to Global North countries. Though nationalities represented per camp has increased steadily since its inception, the share of participants from eastern Europe and Africa has dropped, while those from western Europe and North America have increased. This note examines how camp cost, location, and leadership affects nationality diversity amongst participants, and how astronomy outreach events must reckon with funding for less privileged participants with limited access to resources.

‘When I was your age, Pluto was a planet’ was a popular joke after the celestial body’s reclassification as a ‘dwarf planet’. In many ways, the story of Pluto is an appropriate metaphor for the United Kingdom after Brexit. Just as textbooks on astronomy had to be updated to reflect Pluto’s changed status, legal scholarship needs to adapt to the fact that the UK is relegating itself into the outer orbits of the European system of integration and cooperation, yet remains unable to break free from the centre’s gravitational pull. Crucially, the UK has become an object of EU external action, rather than a subject that can manipulate the levers from the inside. This change is also of particular significance for the scholarship of EU external relations. Highlighting, organising, and explaining the changes that Brexit causes for the field and with a view to charting its way forward, this article argues that the UK’s withdrawal will contribute to the further normalisation of EU external relations law as a field of scholarship. Following a brief explanation of why EU external relations law is a doubly peculiar area of scholarship and an overview of the origins and development of EU external relations law as a field, the article elaborates on three main consequences of Brexit for EU external relations law research and explains how each contributes to normalisation: disposing of the most ‘awkward member’, boosting reforms for greater effectiveness, and infusing a sense of geopolitical realism.

Anthony D. Cho, Rodrigo A. Carrasco, Gonzalo A. Ruz et al.

The ever increasing challenges posed by the science projects in astronomy have skyrocketed the complexity of the new generation telescopes. Due to the climate and sky requirements, these high-precision instruments are generally located in remote areas, suffering from the harsh environments around it. These modern telescopes not only produce massive amounts of scientific data, but they also generate an enormous amount of operational information. The Atacama Large Millimeter/submillimeter Array (ALMA) is one of these unique instruments, generating more than 50 Gb of operational data every day while functioning in conditions of extreme dryness and altitude. To maintain the array working under extreme conditions, the engineering teams must check over 130,000 monitoring points, combing through the massive datasets produced every day. To make this possible, predictive tools are needed to identify, hopefully beforehand, the occurrence of failures in all the different subsystems. This work presents a novel fault detection scheme for one of these subsystems, the Intermediate Frequency Processors (IFP). This subsystem is critical to process the information gathered by each antenna and communicate it, reliably, to the correlator for processing. Our approach is based on echo state networks, a configuration of artificial neural networks, used to learn and predict the signal patterns. These patterns are later compared to the actual signal, to identify failure modes. Additional preprocessing techniques were also added since the signal-to-noise ratio of the data used was very low. The proposed scheme was tested in over seven years of data from 132 IFPs at ALMA, showing an accuracy of over 70%. Furthermore, the detection was done several months earlier, on average, when compared to what human operators did. These results help the maintenance procedures, increasing reliability while reducing humans' exposure to the harsh environment where the antennas are. Although applied to a specific fault, this technique is broad enough to be applied to other types of faults and settings.