E-LIB Suche - Ergebnisse für: Cabayol-Garcia, L

1

Optimal 1D Ly α forest power spectrum estimation – III. DES..:

Karaçaylı, Naim Göksel ; Martini, Paul ; Guy, Julien...
Monthly Notices of the Royal Astronomical Society. 528 (2024) 3 - p. 3941-3963 , 2024

Link: https://doi.org/10.1093/..

2

The Lyman-α forest catalogue from the Dark Energy Spectrosc..:

Ramírez-Pérez, César ; Pérez-Ràfols, Ignasi ; Font-Ribera, Andreu...
Monthly Notices of the Royal Astronomical Society. 528 (2023) 4 - p. 6666-6679 , 2023

Link: https://doi.org/10.1093/..

3

A neural network emulator for the Lyman-α forest 1D flux po..:

Cabayol-Garcia, L ; Chaves-Montero, J ; Font-Ribera, A.
Monthly Notices of the Royal Astronomical Society. 525 (2023) 3 - p. 3499-3515 , 2023

Link: https://doi.org/10.1093/..

4

The PAU Survey: background light estimation with deep learn..:

Cabayol-Garcia, L ; Eriksen, M ; Alarcón, A...
Monthly Notices of the Royal Astronomical Society. 491 (2019) 4 - p. 5392-5405 , 2019

Link: https://doi.org/10.1093/..

5

The Dark Energy Spectroscopic Instrument: one-dimensional p..:

Ravoux, Corentin ; Abdul Karim, Marie Lynn ; Armengaud, Eric...
Monthly Notices of the Royal Astronomical Society. 526 (2023) 4 - p. 5118-5140 , 2023

Link: https://doi.org/10.1093/..

6

Multi-Band Photometry and Photometric Redshifts from Astron..:

, In: Machine Learning for Astrophysics; Astrophysics and Space Science Proceedings,

Cabayol-Garcia, Laura ; Eriksen, Martin Børstad ; the PAUS Collaboration - p. 159-162 , 2023

Link: https://doi.org/10.1007/..

7

Validation of the Scientific Program for the Dark Energy Sp..:

Adame, A.G ; Aguilar, J ; Ahlen, S...
info:eu-repo/semantics/altIdentifier/arxiv/2306.06307. , 2024

Link: https://hal.science/hal-..

8

Validation of the Scientific Program for the Dark Energy Sp..:

Adame, A.G ; Aguilar, J ; Ahlen, S...
info:eu-repo/semantics/altIdentifier/arxiv/2306.06307. , 2024

Link: https://hal.science/hal-..

9

The Dark Energy Spectroscopic Instrument: one-dimensional p..:

Ravoux, C ; Abdul Karim, ML ; Armengaud, E...
https://discovery.ucl.ac.uk/id/eprint/10181983/1/stad3008.pdf. , 2023

Link: https://discovery.ucl.ac..

10

Optimal 1D Ly$\alpha$ Forest Power Spectrum Estimation -- I..:

Karaçaylı, Naim Göksel ; Martini, Paul ; Guy, Julien...
http://arxiv.org/abs/2306.06316. , 2023

Link: http://arxiv.org/abs/230..

11

Synthetic spectra for Lyman-$\alpha$ forest analysis in the..:

Herrera-Alcantar, Hiram K ; Muñoz-Gutiérrez, Andrea ; Tan, Ting...
http://arxiv.org/abs/2401.00303. , 2023

Link: http://arxiv.org/abs/240..

12

The Early Data Release of the Dark Energy Spectroscopic Ins..:

DESI Collaboration ; Adame, A. G ; Aguilar, J...
http://arxiv.org/abs/2306.06308. , 2023

Link: http://arxiv.org/abs/230..

13

The Lyman-$\alpha$ forest catalog from the Dark Energy Spec..:

Ramírez-Pérez, César ; Pérez-Ràfols, Ignasi ; Font-Ribera, Andreu...
http://arxiv.org/abs/2306.06312. , 2023

Link: http://arxiv.org/abs/230..

14

Validation of the Scientific Program for the Dark Energy Sp..:

DESI Collaboration ; Adame, A. G ; Aguilar, J...
http://arxiv.org/abs/2306.06307. , 2023

Link: http://arxiv.org/abs/230..

15

The PAU Survey: background light estimation with deep learn..:

Cabayol-Garcia, L ; Eriksen, Martin Borstad ; Alarcón, A...
#PLACEHOLDER_PARENT_METADATA_VALUE#. , 2020

Link: http://hdl.handle.net/10..