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The detection and characterization of Earth-like exoplanets around Sun-like stars is a primary science motivation for the Habitable Worlds Observatory. However, the current best technology is not yet advanced enough to reach the 10^-10 contrasts at close angular separations and at the same time remain insensitive to low-order aberrations, as would be required to achieve high-contrast imaging of exo-Earths. Photonic technologies could fill this gap, potentially doubling exo-Earth yield. We review current work on photonic coronagraphs and investigate the potential of hybridized designs which combine both classical coronagraph designs and photonic technologies into a single optical system. We present two possible systems. First, a hybrid solution which splits the field of view spatially such that the photonics handle light within the inner working angle and a conventional coronagraph that suppresses starlight outside it. Second, a hybrid solution where the conventional coronagraph and photonics operate in series, complementing each other and thereby loosening requirements on each subsystem. As photonic technologies continue to advance, a hybrid or fully photonic coronagraph holds great potential for future exoplanet imaging from space., Comment: Conference Proceedings of SPIE: Techniques and Instrumentation for Detection of Exoplanets XI, vol. 12680 (2023)

As the economy struggles to recover from the pandemic and the ensuing volatility and labor shortages, leaders in the field of young adult talent development are seeing a need to develop approaches that equally address both the talent needs of employers and the education and training aspirations of young adults. This brief explores how personalized learning approaches can be used to support and balance the interests of the supply and demand sides in young adult talent development.

Over the past three years, Jobs for the Future (JFF) has been supporting a community of more than 100 U.S. community colleges (CCs) and over 25 nonprofit organizations (NPOs) worldwide implementing the Google IT Support Professional Certificate training program. During this engagement, JFF has gathered valuable insights about best practices in designing Google IT Certificate training in various settings. Among NPOs, we saw substantial positive outcomes regarding the recruitment of diverse participants, retention of students, and completion of the program due to the networks and approaches the NPOs adopted. During the engagement, JFF was able to draw insights from both direct coaching with the CC and NPO sites as well as through research and evaluation. This brief offers actionable strategies for CCs to apply evidence-based practices developed by NPOs to increase retention, completion, and job placement through short-term and online workforce training opportunities.

The Low Wind Effect (LWE) refers to a phenomenon that occurs when the wind speed inside a telescope dome drops below $3$m/s creating a temperature gradient near the telescope spider. This produces phase discontinuities in the pupil plane that are not detected by traditional Adaptive Optics (AO) systems such as the pyramid wavefront sensor or the Shack-Hartmann. Considering the pupil as divided in 4 quadrants by regular spiders, the phase discontinuities correspond to piston, tip and tilt aberrations in each quadrant of the pupil. Uncorrected, it strongly decreases the ability of high contrast imaging instruments utilizing coronagraphy to detect exoplanets at small angular separations. Multiple focal plane wavefront sensors are currently being developed and tested on the Subaru Coronagraphic Extreme Adaptive Optics (SCExAO) instrument at Subaru Telescope: Among them, the Zernike Asymmetric Pupil (ZAP) wavefront sensor already showed on-sky that it could measure the LWE induced aberrations in focal plane images. The Fast and Furious algorithm, using previous deformable mirror commands as temporal phase diversity, showed in simulations its efficiency to improve the wavefront quality in the presence of LWE. A Neural Network algorithm trained with SCExAO telemetry showed promising PSF prediction on-sky. The Linearized Analytic Phase Diversity (LAPD) algorithm is a solution for multi-aperture cophasing and is studied to correct for the LWE aberrations by considering the Subaru Telescope as a 4 sub-aperture instrument. We present the different algorithms, show the latest results and compare their implementation on SCExAO/SUBARU as real-time wavefront sensors for the LWE compensation.

Project VeSElkA (Vertical Stratification of Element Abundances) has been initiated with the aim to detect and study the vertical stratification of element abundances in the atmosphere of chemically peculiar stars. Abundance stratification occurs in hydrodynamically stable stellar atmospheres due to the migration of the elements caused by atomic diffusion. Two HgMn stars, HD53929 and HD63975 were selected from the VeSElkA sample and analysed with the aim to detect some abundance peculiarities employing the ZEEMAN2 code. We present the results of abundance analysis of HD53929 and HD63975 observed recently with the spectropolarimeter ESPaDOnS at Canada-France-Hawaii Telescope. Evidence of phosphorus vertical stratification was detected in the atmosphere of these two stars. In both cases, phosphorus abundance increases strongly towards the superficial layers. The strong overabundance of Mn found in stellar atmosphere of both stars confirms that they are HgMn type stars., Comment: 7 pages, 3 figures, accepted for publication in MNRAS

Detailed knowledge of the energy needs at relatively high spatial and temporal resolution is crucial for the electricity infrastructure planning of a region. However, such information is typically limited by the scarcity of data on human activities, in particular in developing countries where electrification of rural areas is sought. The analysis of society-wide mobile phone records has recently proven to offer unprecedented insights into the spatio-temporal distribution of people, but this information has never been used to support electrification planning strategies anywhere and for rural areas in developing countries in particular. The aim of this project is the assessment of the contribution of mobile phone data for the development of bottom-up energy demand models, in order to enhance energy planning studies and existing electrification practices. More specifically, this work introduces a framework that combines mobile phone data analysis, socioeconomic and geo-referenced data analysis, and state-of-the-art energy infrastructure engineering techniques to assess the techno-economic feasibility of different centralized and decentralized electrification options for rural areas in a developing country. Specific electrification options considered include extensions of the existing medium voltage (MV) grid, diesel engine-based community-level Microgrids, and individual household-level solar photovoltaic (PV) systems. The framework and relevant methodology are demonstrated throughout the paper using the case of Senegal and the mobile phone data made available for the 'D4D-Senegal' innovation challenge. The results are extremely encouraging and highlight the potential of mobile phone data to support more efficient and economically attractive electrification plans., Comment: 'Data for Development' Challenge Senegal 2014-15. First Prize and Energy Prize