Fetching the paper…
Reading the bibliography…
We present an optimized way of producing the fast semi-analytical covariance matrices for the Legendre moments of the two-point correlation function, taking into account survey geometry and mimicking the non-Gaussian effects.
1904
Earlier work this paper cites.
1910
Earlier work this paper cites.
1910
Earlier work this paper cites.
1911
Earlier work this paper cites.
1911
Earlier work this paper cites.
1912
Earlier work this paper cites.
1928
Earlier work this paper cites.
S.D. Landy and A.S. Szalay, Bias and Variance of Angular Correlation Functions , ApJ 412
1993
Earlier work this paper cites.
M.-J. Pons-Bordería, V.J. Martínez, D. Stoyan, H. Stoyan and E. Saar, Comparing Estimators of the Galaxy Correlation Function , ApJ 523
1999
Earlier work this paper cites.
2004
Earlier work this paper cites.
2005
Earlier work this paper cites.
2007
Earlier work this paper cites.
J. Hartlap, P. Simon and P. Schneider, Why your model parameter confidences might be too optimistic. Unbiased estimation of the inverse covariance matrix , A&A 464
2007
Earlier work this paper cites.
F. Perez and B.E. Granger, IPython: A System for Interactive Scientific Computing , Computing in Science and Engineering 9
2007
Earlier work this paper cites.
J.D. Hunter, Matplotlib: A 2d graphics environment , Computing in Science & Engineering 9
2007
Earlier work this paper cites.
2009
Earlier work this paper cites.
G. Van Rossum and F.L. Drake, Python 3 Reference Manual , CreateSpace, Scotts Valley, CA (2009)
2009
Earlier work this paper cites.
2010
Earlier work this paper cites.
2011
Earlier work this paper cites.
F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel et al., Scikit-learn: Machine learning in Python , Journal of Machine Learning Research 12
2011
Earlier work this paper cites.
2012
Earlier work this paper cites.
C.-H. Chuang and Y. Wang, Using multipoles of the correlation function to measure H(z), D A
2013
Earlier work this paper cites.
2013
Earlier work this paper cites.
L. Buitinck, G. Louppe, M. Blondel, F. Pedregosa, A. Mueller, O. Grisel et al., API design for machine learning software: experiences from the scikit-learn project , in ECML PKDD Workshop: Languages for Data Mining and Machine Learning , pp. 108–122, 2013
2013
Earlier work this paper cites.
2014
Earlier work this paper cites.
2015
Earlier work this paper cites.
A. Burden, W.J. Percival and C. Howlett, Reconstruction in Fourier space , MNRAS 453
2015
Earlier work this paper cites.
2016
Earlier work this paper cites.
2016
Earlier work this paper cites.
T. Kluyver, B. Ragan-Kelley, F. Pérez, B.E. Granger, M. Bussonnier, J. Frederic et al., Jupyter notebooks-a publishing format for reproducible computational workflows. , in ELPUB , pp. 87–90, 2016
2016
Earlier work this paper cites.
2018
Earlier work this paper cites.
2018
Cited alongside, same era.
2019
Cited alongside, same era.
C.R. Harris, K.J. Millman, S.J. van der Walt, R. Gommers, P. Virtanen, D. Cournapeau et al., Array programming with NumPy , Nature 585
2020
Cited alongside, same era.
P. Virtanen, R. Gommers, T.E. Oliphant, M. Haberland, T. Reddy, D. Cournapeau et al., SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python , Nature Methods 17
2020
Cited alongside, same era.
2024
Closest in time.
2024
Closest in time.
2024
Closest in time.
2024
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
2021
Cited alongside, same era.
2021
Cited alongside, same era.
2021
Cited alongside, same era.
2021
Cited alongside, same era.
2022
Cited alongside, same era.
2022
Cited alongside, same era.
2022
Cited alongside, same era.
2022
Cited alongside, same era.
C. Zhao et al., Mock catalogues with survey realism for the DESI DR1 , in preparation (2024)
2024
Closest in time.
2024
Closest in time.
O. Alves et al., Analytical covariance matrices of DESI galaxy power spectra , in preparation (2024)
2024
Closest in time.
2024
Closest in time.
A. de Mattia, M. Rashkovetskyi, M. Sinha and L.H. Garrison, “pycorr: Two-point correlation function estimation.” Astrophysics Source Code Library, record ascl:2403.009, Mar., 2024
2024
Closest in time.
2024
Closest in time.
2024
Closest in time.
2024
Closest in time.
D. Valcin et al., Combined tracer analysis for DESI 2024 BAO analysis , in preparation (2024)
2024
Closest in time.
2024
Closest in time.
2024
Closest in time.
2024
Closest in time.
2024
Closest in time.
2024
Closest in time.
2024
Closest in time.
2024
Closest in time.
M. M. S Hanif et al., Fast Fiber Assign: Emulating fiber assignment effects for realistic DESI catalogs , in preparation (2024)
2024
Closest in time.
2024
Closest in time.
2024
Closest in time.
2024
Closest in time.
2024
Closest in time.
2024
Closest in time.
2024
Closest in time.
10.5281/zenodo.13225824
T. Wagg, F. Broekgaarden and K. Gültekin, Tomwagg/software-citation-station: v1.2 , Aug., 2024 · 2024
Closest in time.
10.5281/zenodo.10895161
M. Rashkovetskyi, D.F. Forero Sanchez, A. de Mattia, D. Eisenstein, N. Padmanabhan, H.-J. Seo et al., Semi-analytical covariance matrices for two-point correlation function for DESI 2024 data , Apr., 2024 · 2024
Closest in time.
DESI Collaboration, DESI 2024 I: Data Release 1 of the Dark Energy Spectroscopic Instrument , in preparation (2025)
2025
Closest in time.