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class_sz I: Overview

Boris Bolliet, Aleksandra Kusiak, Fiona McCarthy, Alina Sabyr, Kristen M. Surrao, J. Colin Hill, Jens Chluba, Simone Ferraro, Boryana Hadzhiyska, Dongwon Han, J. F. Macías–Pérez, Mathew S. Madhavacheril, Abhishek S. Maniyar, Y. Mehta, Shivam Pandey, Emmanuel Schaan, Blake D. Sherwin, A. Spurio Mancini, Íñigo Zubeldía

2024EPJ Web of Conferences13 citationsDOIOpen Access PDF

Abstract

class_sz is a versatile, robust and efficient code, in C and Python, optimized to compute theoretical predictions for a wide range of observables relevant to cross-survey science in the Stage IV era. The code is public at https://github.com/CLASS-SZ/class_sz along with a series of tutorial notebooks ( https://github.com/CLASS-SZ/notebooks ). It will be presented in full detail in paper II. Here we give a brief overview of key features and usage.

Topics & Concepts

Python (programming language)Class (philosophy)Computer scienceObservableCode (set theory)Programming languagePhysicsArtificial intelligenceQuantum mechanicsSet (abstract data type)Computational Physics and Python ApplicationsGamma-ray bursts and supernovaeClimate variability and models
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