Extremely Large Telescope

Abstract:

The WALOPControl software is designed to facilitate comprehensive control and operation of the Wide Area Linear Optical Polarimeter (WALOP) polarimeters, ensuring safe and concurrent management of various instrument components and functionalities. This software encompasses several critical requirements, including control of the filter wheel, calibration half-wave plate, calibration polarizer, guider positioning, focusers, and four concurrent charge-coupled device cameras. It also manages the host telescope and dome operations while logging operational parameters, user commands, and environmental conditions for troubleshooting and stability. It provides a user-friendly graphical user interface and secure access control, a notification system for errors, and a modular configuration for troubleshooting that are integral to the software's architecture. It is accessible over the internet with the backend developed using NodeJS and ExpressJS, featuring a RESTful API that interacts with a MongoDB database, facilitating real-time status updates and data logging. The frontend utilizes the React.JS framework, with Redux for state management and Material UI for the graphical components. The system also allows for automatic observations based on user-defined schedules. A continuous integration and continuous deployment pipeline ensures the software's reliability through automated testing and streamlined deployment. The WALOPControl software is a key component of the Polar-Areas Stellar Imaging in Polarimetry High Accuracy Experiment project, which aims to study the dust and magnetic field of the Milky Way by observing the polarization of starlight.

Abstract:

Strong gravitational-lensing systems with multiple source planes are powerful tools for probing the density profiles and dark matter substructure of galaxies. The ratio of the Einstein radii is related to the dark energy equation of state through the cosmological scaling factor β . Galaxy-scale double-source-plane lenses (DSPLs) are extremely rare, however. We report the discovery of four new galaxy-scale DSPL candidates in the Euclid Quick Release 1 (Q1) data. These systems were initially identified through a combination of machine-learning lens-finding models and subsequent visual inspection from citizens and experts. We applied the widel -used LensPop lens-forecasting model to predict that the full Euclid survey will discover 1700 DSPLs. This scales to 6 ± 3 DSPLs in 63 deg 2 , which is the area of Q1. The number of discoveries in this work is broadly consistent with this forecast. We present lens models for each DSPL and infer their β values. Our initial Q1 sample demonstrates that Euclid promises to discover these rare objects.