class_sz I: Overview

B. Bolliet; A. Kusiak; F. McCarthy; A. Sabyr; K. Surrao; J. C. Hill; J. Chluba; S. Ferraro; B. Hadzhiyska; D. Han; J. F. Macas-Prez; M. Madhavacheril; A. Maniyar; Y. Mehta; S. Pandey; E. Schaan; B. Sherwin; A. Spurio Mancini; Zubeldia

doi:10.1051/epjconf/202429300008

class_sz I: Overview

B. Bolliet
, A. Kusiak
, F. McCarthy
, A. Sabyr
, K. Surrao
, J. C. Hill
, J. Chluba
, S. Ferraro
, B. Hadzhiyska
, D. Han
, J. F. Macas-Prez
, M. Madhavacheril
, A. Maniyar
, Y. Mehta
, S. Pandey
, E. Schaan
, B. Sherwin
, A. Spurio Mancini
, Zubeldia

Research output: Contribution to journal › Article › peer-review

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.

Original language	English
Article number	00008
Number of pages	6
Journal	EPJ Web of Conferences
Volume	293
Early online date	28 Mar 2024
DOIs	https://doi.org/10.1051/epjconf/202429300008
Publication status	Published - 2024

Access to Document

10.1051/epjconf/202429300008Licence: CC BY

https://arxiv.org/abs/2310.18482

Cite this

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title = "class\_sz I: Overview",

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.",

author = "B. Bolliet and A. Kusiak and F. McCarthy and A. Sabyr and K. Surrao and Hill, \{J. C.\} and J. Chluba and S. Ferraro and B. Hadzhiyska and D. Han and Macas-Prez, \{J. F.\} and M. Madhavacheril and A. Maniyar and Y. Mehta and S. Pandey and E. Schaan and B. Sherwin and Mancini, \{A. Spurio\} and Zubeldia",

year = "2024",

doi = "10.1051/epjconf/202429300008",

language = "English",

volume = "293",

journal = "EPJ Web of Conferences",

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TY - JOUR

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T2 - Overview

AU - Bolliet, B.

AU - Kusiak, A.

AU - McCarthy, F.

AU - Sabyr, A.

AU - Surrao, K.

AU - Hill, J. C.

AU - Chluba, J.

AU - Ferraro, S.

AU - Hadzhiyska, B.

AU - Han, D.

AU - Macas-Prez, J. F.

AU - Madhavacheril, M.

AU - Maniyar, A.

AU - Mehta, Y.

AU - Pandey, S.

AU - Schaan, E.

AU - Sherwin, B.

AU - Mancini, A. Spurio

AU - Zubeldia, null

PY - 2024

Y1 - 2024

N2 - 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.

AB - 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.

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DO - 10.1051/epjconf/202429300008

M3 - Article

SN - 2101-6275

VL - 293

JO - EPJ Web of Conferences

JF - EPJ Web of Conferences

M1 - 00008

ER -