We present a methodology for the reduction of archival spectral data together with the description of a newly developed Python-based software package featuring an interactive graphical interface. The work is primarily aimed at processing spectra obtained with electron–optical converters (EOCs), which are characterized by geometric distortions induced by the magnetic field of the registration system. Such data are preserved, in particular, in the archive of the Fesenkov Astrophysical Institute (FAI), which contains about 10,000 photographic plates. These distortions, along with the need to transform the optical density of the photographic material into relative intensity, cannot be corrected by standard astronomical packages such as IRAF and therefore require a dedicated approach. Historically, reductions at FAI were performed using a program written in the Microsoft QuickC language for computing platforms of the 1990s, rendering it incompatible with modern operating systems. The new package is implemented with the PyQt5 framework, retaining the logic of the original code while extending its functionality. The implemented algorithms include image rotation and cropping, geometric distortion correction, construction of the characteristic curve linking optical density and intensity, and direct conversion of pixel values in object spectra. The developed software ensures reproducible reduction of archival spectra and provides a cross-platform environment with potential for further extensions.

We present the computational design and implementation of GalaPy, a hybrid C++/Python library for the spectral energy distribution (SED) modelling of galaxies. Originally introduced in Ronconi et al. (2024), GalaPy has been developed within the Italian galaxy formation and cosmology community as part of the ICSC – Centro Nazionale di Ricerca in High Performance Computing, Big Data e Quantum Computing . The library combines the performance of compiled C++ routines with the flexibility of Python, enabling efficient generation and fitting of physically motivated SED models. We describe the object-oriented architecture of the code, its hybrid parallelisation strategy, and the optimisations that ensure portability and minimal memory overhead. Parallel execution relies on a combination of vectorised array programming, shared-memory concurrency, and distributed-memory message passing. Recent updates include Bayesian evidence-based model selection and a fully analytical, panchromatic active galactic nucleus component. These additions further improve the physical realism and the statistical power of the framework. GalaPy thus provides a modular and extensible platform for galaxy modelling, designed to interface and adapt seamlessly to the next generation of large-scale astrophysical analyses.

The management of observing proposals is a critical operational component for modern astronomical facilities. As missions grow in complexity, the demand for efficient, fair, and adaptable proposal handling systems is increasingly pressing. Existing systems are often monolithic and tightly coupled to a specific observatory, lacking the flexibility to be easily adapted. This paper introduces AstroPropose, a novel, general-purpose framework for creating and managing astronomical observing proposal systems, derived from the architecture of the operational Einstein Probe Observing Proposal System (EOPS). AstroPropose is centered on a powerful visual workflow engine, enabling administrators to define and deploy entire proposal workflows through a graphical interface. Key features include a dynamic form builder, a configurable workflow engine, and a flexible role-based access control (RBAC) system. We present the complete architecture and data model. As validation, we detail how the framework’s design principles are embodied in EOPS, which has successfully managed two annual proposal cycles and handles daily time-critical Target of Opportunity (ToO) submissions for the Einstein Probe mission. To further demonstrate the framework’s generalizability, we present a second case study: its adaptation as the proposal management prototype for the Chinese Space Station Telescope (CSST), a multi-instrument survey mission with a dual-phase review process. AstroPropose, validated through the successful operation of EOPS and the rapid prototyping of the CSST system, is being prepared for an open-source release to the astronomical community.