Euclid preparation. XXXV. Covariance model validation for the two-point correlation function of galaxy cluster

A Fumagalli; A Saro; S Borgani; T Castro; M Costanzi; P Monaco; E Munari; E Sefusatti; AMC Le Brun; N Aghanim; N Auricchio; M Baldi; C Bodendorf; D Bonino; E Branchini; M Brescia; J Brinchmann; S Camera; V Capobianco; C Carbone; J Carretero; FJ Castander; M Castellano; S Cavuoti; R Cledassou; G Congedo; CJ Conselice; L Conversi; Y Copin; L Corcione; F Courbin; M Cropper; A Da Silva; H Degaudenzi; F Dubath; X Dupac; S Dusini; S Farrens; S Ferriol; M Frailis; E Franceschi; P Franzetti; S Galeotta; B Garilli; W Gillard; B Gillis; C Giocoli; A Grazian; F Grupp; SVH Haugan; W Holmes; A Hornstrup; P Hudelot; K Jahnke; M Kümmel; S Kermiche; A Kiessling; M Kilbinger; T Kitching; M Kunz; H Kurki-Suonio; S Ligori; PB Lilje; I Lloro; O Mansutti; O Marggraf; K Markovic; F Marulli; R Massey; S Maurogordato; E Medinaceli; S Mei; M Meneghetti; G Meylan; M Moresco; L Moscardini; SM Niemi; C Padilla; S Paltani; F Pasian; K Pedersen; WJ Percival; V Pettorino; S Pires; G Polenta; M Poncet; F Raison; R Rebolo-Lopez; A Renzi; J Rhodes; G Riccio; E Romelli; M Roncarelli; R Saglia; D Sapone; B Sartoris; P Schneider; A Secroun; G Seidel; C Sirignano; G Sirri; L Stanco; P Tallada-Crespi; AN Taylor; I Tereno; R Toledo-Moreo; F Torradeflot; I Tutusaus; L Valenziano; T Vassallo; Y Wang; J Weller; A Zacchei; G Zamorani; J Zoubian; S Andreon; S Bardelli; A Boucaud; E Bozzo; C Colodro-Conde; D Di Ferdinando; G Fabbian; M Farina; V Lindholm; D Maino; N Mauri; C Neissner; V Scottez; E Zucca; C Baccigalupi; A Balaguera-Antolínez; M Ballardini; F Bernardeau; A Biviano; A Blanchard; AS Borlaff; C Burigana; R Cabanac; CS Carvalho; S Casas; G Castignani; K Chambers; AR Cooray; J Coupon; HM Courtois; S Davini; S de la Torre; G Desprez; H Dole; JA Escartin; S Escoffier; PG Ferreira; F Finelli; J Garcia-Bellido; K George; G Gozaliasl; H Hildebrandt; I Hook; AJ Muñoz; B Joachimi; V Kansal; E Keihänen; CC Kirkpatrick; A Loureiro; M Magliocchetti; R Maoli; S Marcin; M Martinelli; N Martinet; S Matthew; M Maturi; L Maurin; RB Metcalf; G Morgante; S Nadathur; AA Nucita; L Patrizii; JE Pollack; V Popa; C Porciani; D Potter; A Pourtsidou; M Pöentinen; AG Sánchez; Z Sakr; M Schirmer; M Sereno; AS Mancini; J Stadel; J Steinwagner; C Valieri; J Valiviita; A Veropalumbo; M Viel

doi:10.1051/0004-6361/202245540

Euclid preparation. XXXV. Covariance model validation for the two-point correlation function of galaxy cluster

A Fumagalli, A Saro, S Borgani, T Castro, M Costanzi, P Monaco, E Munari, E Sefusatti, AMC Le Brun, N Aghanim, N Auricchio, M Baldi, C Bodendorf, D Bonino, E Branchini, M Brescia, J Brinchmann, S Camera, V Capobianco, C CarboneJ Carretero, FJ Castander, M Castellano, S Cavuoti, R Cledassou, G Congedo, CJ Conselice, L Conversi, Y Copin, L Corcione, F Courbin, M Cropper, A Da Silva, H Degaudenzi, F Dubath, X Dupac, S Dusini, S Farrens, S Ferriol, M Frailis, E Franceschi, P Franzetti, S Galeotta, B Garilli, W Gillard, B Gillis, C Giocoli, A Grazian, F Grupp, SVH Haugan, W Holmes, A Hornstrup, P Hudelot, K Jahnke, M Kümmel, S Kermiche, A Kiessling, M Kilbinger, T Kitching, M Kunz, H Kurki-Suonio, S Ligori, PB Lilje, I Lloro, O Mansutti, O Marggraf, K Markovic, F Marulli, R Massey, S Maurogordato, E Medinaceli, S Mei, M Meneghetti, G Meylan, M Moresco, L Moscardini, SM Niemi, C Padilla, S Paltani, F Pasian, K Pedersen, WJ Percival, V Pettorino, S Pires, G Polenta, M Poncet, F Raison, R Rebolo-Lopez, A Renzi, J Rhodes, G Riccio, E Romelli, M Roncarelli, R Saglia, D Sapone, B Sartoris, P Schneider, A Secroun, G Seidel, C Sirignano, G Sirri, L Stanco, P Tallada-Crespi, AN Taylor, I Tereno, R Toledo-Moreo, F Torradeflot, I Tutusaus, L Valenziano, T Vassallo, Y Wang, J Weller, A Zacchei, G Zamorani, J Zoubian, S Andreon, S Bardelli, A Boucaud, E Bozzo, C Colodro-Conde, D Di Ferdinando, G Fabbian, M Farina, V Lindholm, D Maino, N Mauri, C Neissner, V Scottez, E Zucca, C Baccigalupi, A Balaguera-Antolínez, M Ballardini, F Bernardeau, A Biviano, A Blanchard, AS Borlaff, C Burigana, R Cabanac, CS Carvalho, S Casas, G Castignani, K Chambers, AR Cooray, J Coupon, HM Courtois, S Davini, S de la Torre, G Desprez, H Dole, JA Escartin, S Escoffier, PG Ferreira, F Finelli, J Garcia-Bellido, K George, G Gozaliasl, H Hildebrandt, I Hook, AJ Muñoz, B Joachimi, V Kansal, E Keihänen, CC Kirkpatrick, A Loureiro, M Magliocchetti, R Maoli, S Marcin, M Martinelli, N Martinet, S Matthew, M Maturi, L Maurin, RB Metcalf, G Morgante, S Nadathur, AA Nucita, L Patrizii, JE Pollack, V Popa, C Porciani, D Potter, A Pourtsidou, M Pöentinen, AG Sánchez, Z Sakr, M Schirmer, M Sereno, AS Mancini, J Stadel, J Steinwagner, C Valieri, J Valiviita, A Veropalumbo, M Viel

Not published at Aalto University

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

2 Citations (Scopus)

Abstract

Aims. We validate a semi-analytical model for the covariance of the real-space two-point correlation function of galaxy clusters. Methods. Using 1000 PINOCCHIO light cones mimicking the expected Euclid sample of galaxy clusters, we calibrated a simple model to accurately describe the clustering covariance. Then, we used this model to quantify the likelihood-analysis response to variations in the covariance, and we investigated the impact of a cosmology-dependent matrix at the level of statistics expected for the Euclid survey of galaxy clusters. Results. We find that a Gaussian model with Poissonian shot-noise does not correctly predict the covariance of the two-point correlation function of galaxy clusters. By introducing a few additional parameters fitted from simulations, the proposed model reproduces the numerical covariance with an accuracy of 10%, with differences of about 5% on the figure of merit of the cosmological parameters Ωm and σ8. We also find that the covariance contains additional valuable information that is not present in the mean value, and the constraining power of cluster clustering can improve significantly when its cosmology dependence is accounted for. Finally, we find that the cosmological figure of merit can be further improved when mass binning is taken into account. Our results have significant implications for the derivation of cosmological constraints from the two-point clustering statistics of the Euclid survey of galaxy clusters.

Original language	English
Article number	A253
Number of pages	19
Journal	Astronomy & Astrophysics
Volume	683
DOIs	https://doi.org/10.1051/0004-6361/202245540
Publication status	Published - 22 Mar 2024
MoE publication type	A1 Journal article-refereed

Keywords

Cosmological parameters
Galaxies: clusters: general
Large-scale structure of Universe
Methods: statistical

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10.1051/0004-6361/202245540

Cite this

Fumagalli, A., Saro, A., Borgani, S., Castro, T., Costanzi, M., Monaco, P., Munari, E., Sefusatti, E., Le Brun, AMC., Aghanim, N., Auricchio, N., Baldi, M., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., ... Viel, M. (2024). Euclid preparation. XXXV. Covariance model validation for the two-point correlation function of galaxy cluster. Astronomy & Astrophysics, 683, Article A253. https://doi.org/10.1051/0004-6361/202245540

@article{660a1c35ac344c889a47b3eb08ff3cd2,

title = "Euclid preparation. XXXV. Covariance model validation for the two-point correlation function of galaxy cluster",

abstract = "Aims. We validate a semi-analytical model for the covariance of the real-space two-point correlation function of galaxy clusters. Methods. Using 1000 PINOCCHIO light cones mimicking the expected Euclid sample of galaxy clusters, we calibrated a simple model to accurately describe the clustering covariance. Then, we used this model to quantify the likelihood-analysis response to variations in the covariance, and we investigated the impact of a cosmology-dependent matrix at the level of statistics expected for the Euclid survey of galaxy clusters. Results. We find that a Gaussian model with Poissonian shot-noise does not correctly predict the covariance of the two-point correlation function of galaxy clusters. By introducing a few additional parameters fitted from simulations, the proposed model reproduces the numerical covariance with an accuracy of 10%, with differences of about 5% on the figure of merit of the cosmological parameters Ωm and σ8. We also find that the covariance contains additional valuable information that is not present in the mean value, and the constraining power of cluster clustering can improve significantly when its cosmology dependence is accounted for. Finally, we find that the cosmological figure of merit can be further improved when mass binning is taken into account. Our results have significant implications for the derivation of cosmological constraints from the two-point clustering statistics of the Euclid survey of galaxy clusters.",

keywords = "Cosmological parameters, Galaxies: clusters: general, Large-scale structure of Universe, Methods: statistical",

author = "A Fumagalli and A Saro and S Borgani and T Castro and M Costanzi and P Monaco and E Munari and E Sefusatti and {Le Brun}, AMC and N Aghanim and N Auricchio and M Baldi and C Bodendorf and D Bonino and E Branchini and M Brescia and J Brinchmann and S Camera and V Capobianco and C Carbone and J Carretero and FJ Castander and M Castellano and S Cavuoti and R Cledassou and G Congedo and CJ Conselice and L Conversi and Y Copin and L Corcione and F Courbin and M Cropper and {Da Silva}, A and H Degaudenzi and F Dubath and X Dupac and S Dusini and S Farrens and S Ferriol and M Frailis and E Franceschi and P Franzetti and S Galeotta and B Garilli and W Gillard and B Gillis and C Giocoli and A Grazian and F Grupp and SVH Haugan and W Holmes and A Hornstrup and P Hudelot and K Jahnke and M K{\"u}mmel and S Kermiche and A Kiessling and M Kilbinger and T Kitching and M Kunz and H Kurki-Suonio and S Ligori and PB Lilje and I Lloro and O Mansutti and O Marggraf and K Markovic and F Marulli and R Massey and S Maurogordato and E Medinaceli and S Mei and M Meneghetti and G Meylan and M Moresco and L Moscardini and SM Niemi and C Padilla and S Paltani and F Pasian and K Pedersen and WJ Percival and V Pettorino and S Pires and G Polenta and M Poncet and F Raison and R Rebolo-Lopez and A Renzi and J Rhodes and G Riccio and E Romelli and M Roncarelli and R Saglia and D Sapone and B Sartoris and P Schneider and A Secroun and G Seidel and C Sirignano and G Sirri and L Stanco and P Tallada-Crespi and AN Taylor and I Tereno and R Toledo-Moreo and F Torradeflot and I Tutusaus and L Valenziano and T Vassallo and Y Wang and J Weller and A Zacchei and G Zamorani and J Zoubian and S Andreon and S Bardelli and A Boucaud and E Bozzo and C Colodro-Conde and {Di Ferdinando}, D and G Fabbian and M Farina and V Lindholm and D Maino and N Mauri and C Neissner and V Scottez and E Zucca and C Baccigalupi and A Balaguera-Antol{\'i}nez and M Ballardini and F Bernardeau and A Biviano and A Blanchard and AS Borlaff and C Burigana and R Cabanac and CS Carvalho and S Casas and G Castignani and K Chambers and AR Cooray and J Coupon and HM Courtois and S Davini and {de la Torre}, S and G Desprez and H Dole and JA Escartin and S Escoffier and PG Ferreira and F Finelli and J Garcia-Bellido and K George and G Gozaliasl and H Hildebrandt and I Hook and AJ Mu{\~n}oz and B Joachimi and V Kansal and E Keih{\"a}nen and CC Kirkpatrick and A Loureiro and M Magliocchetti and R Maoli and S Marcin and M Martinelli and N Martinet and S Matthew and M Maturi and L Maurin and RB Metcalf and G Morgante and S Nadathur and AA Nucita and L Patrizii and JE Pollack and V Popa and C Porciani and D Potter and A Pourtsidou and M P{\"o}entinen and AG S{\'a}nchez and Z Sakr and M Schirmer and M Sereno and AS Mancini and J Stadel and J Steinwagner and C Valieri and J Valiviita and A Veropalumbo and M Viel",

year = "2024",

month = mar,

day = "22",

doi = "10.1051/0004-6361/202245540",

language = "English",

volume = "683",

journal = "Astronomy & Astrophysics",

issn = "0004-6361",

publisher = "EDP Sciences",

}

Fumagalli, A, Saro, A, Borgani, S, Castro, T, Costanzi, M, Monaco, P, Munari, E, Sefusatti, E, Le Brun, AMC, Aghanim, N, Auricchio, N, Baldi, M, Bodendorf, C, Bonino, D, Branchini, E, Brescia, M, Brinchmann, J, Camera, S, Capobianco, V, Carbone, C, Carretero, J, Castander, FJ, Castellano, M, Cavuoti, S, Cledassou, R, Congedo, G, Conselice, CJ, Conversi, L, Copin, Y, Corcione, L, Courbin, F, Cropper, M, Da Silva, A, Degaudenzi, H, Dubath, F, Dupac, X, Dusini, S, Farrens, S, Ferriol, S, Frailis, M, Franceschi, E, Franzetti, P, Galeotta, S, Garilli, B, Gillard, W, Gillis, B, Giocoli, C, Grazian, A, Grupp, F, Haugan, SVH, Holmes, W, Hornstrup, A, Hudelot, P, Jahnke, K, Kümmel, M, Kermiche, S, Kiessling, A, Kilbinger, M, Kitching, T, Kunz, M, Kurki-Suonio, H, Ligori, S, Lilje, PB, Lloro, I, Mansutti, O, Marggraf, O, Markovic, K, Marulli, F, Massey, R, Maurogordato, S, Medinaceli, E, Mei, S, Meneghetti, M, Meylan, G, Moresco, M, Moscardini, L, Niemi, SM, Padilla, C, Paltani, S, Pasian, F, Pedersen, K, Percival, WJ, Pettorino, V, Pires, S, Polenta, G, Poncet, M, Raison, F, Rebolo-Lopez, R, Renzi, A, Rhodes, J, Riccio, G, Romelli, E, Roncarelli, M, Saglia, R, Sapone, D, Sartoris, B, Schneider, P, Secroun, A, Seidel, G, Sirignano, C, Sirri, G, Stanco, L, Tallada-Crespi, P, Taylor, AN, Tereno, I, Toledo-Moreo, R, Torradeflot, F, Tutusaus, I, Valenziano, L, Vassallo, T, Wang, Y, Weller, J, Zacchei, A, Zamorani, G, Zoubian, J, Andreon, S, Bardelli, S, Boucaud, A, Bozzo, E, Colodro-Conde, C, Di Ferdinando, D, Fabbian, G, Farina, M, Lindholm, V, Maino, D, Mauri, N, Neissner, C, Scottez, V, Zucca, E, Baccigalupi, C, Balaguera-Antolínez, A, Ballardini, M, Bernardeau, F, Biviano, A, Blanchard, A, Borlaff, AS, Burigana, C, Cabanac, R, Carvalho, CS, Casas, S, Castignani, G, Chambers, K, Cooray, AR, Coupon, J, Courtois, HM, Davini, S, de la Torre, S, Desprez, G, Dole, H, Escartin, JA, Escoffier, S, Ferreira, PG, Finelli, F, Garcia-Bellido, J, George, K, Gozaliasl, G, Hildebrandt, H, Hook, I, Muñoz, AJ, Joachimi, B, Kansal, V, Keihänen, E, Kirkpatrick, CC, Loureiro, A, Magliocchetti, M, Maoli, R, Marcin, S, Martinelli, M, Martinet, N, Matthew, S, Maturi, M, Maurin, L, Metcalf, RB, Morgante, G, Nadathur, S, Nucita, AA, Patrizii, L, Pollack, JE, Popa, V, Porciani, C, Potter, D, Pourtsidou, A, Pöentinen, M, Sánchez, AG, Sakr, Z, Schirmer, M, Sereno, M, Mancini, AS, Stadel, J, Steinwagner, J, Valieri, C, Valiviita, J, Veropalumbo, A & Viel, M 2024, 'Euclid preparation. XXXV. Covariance model validation for the two-point correlation function of galaxy cluster', Astronomy & Astrophysics, vol. 683, A253. https://doi.org/10.1051/0004-6361/202245540

TY - JOUR

T1 - Euclid preparation. XXXV. Covariance model validation for the two-point correlation function of galaxy cluster

AU - Fumagalli, A

AU - Saro, A

AU - Borgani, S

AU - Castro, T

AU - Costanzi, M

AU - Monaco, P

AU - Munari, E

AU - Sefusatti, E

AU - Le Brun, AMC

AU - Aghanim, N

AU - Auricchio, N

AU - Baldi, M

AU - Bodendorf, C

AU - Bonino, D

AU - Branchini, E

AU - Brescia, M

AU - Brinchmann, J

AU - Camera, S

AU - Capobianco, V

AU - Carbone, C

AU - Carretero, J

AU - Castander, FJ

AU - Castellano, M

AU - Cavuoti, S

AU - Cledassou, R

AU - Congedo, G

AU - Conselice, CJ

AU - Conversi, L

AU - Copin, Y

AU - Corcione, L

AU - Courbin, F

AU - Cropper, M

AU - Da Silva, A

AU - Degaudenzi, H

AU - Dubath, F

AU - Dupac, X

AU - Dusini, S

AU - Farrens, S

AU - Ferriol, S

AU - Frailis, M

AU - Franceschi, E

AU - Franzetti, P

AU - Galeotta, S

AU - Garilli, B

AU - Gillard, W

AU - Gillis, B

AU - Giocoli, C

AU - Grazian, A

AU - Grupp, F

AU - Haugan, SVH

AU - Holmes, W

AU - Hornstrup, A

AU - Hudelot, P

AU - Jahnke, K

AU - Kümmel, M

AU - Kermiche, S

AU - Kiessling, A

AU - Kilbinger, M

AU - Kitching, T

AU - Kunz, M

AU - Kurki-Suonio, H

AU - Ligori, S

AU - Lilje, PB

AU - Lloro, I

AU - Mansutti, O

AU - Marggraf, O

AU - Markovic, K

AU - Marulli, F

AU - Massey, R

AU - Maurogordato, S

AU - Medinaceli, E

AU - Mei, S

AU - Meneghetti, M

AU - Meylan, G

AU - Moresco, M

AU - Moscardini, L

AU - Niemi, SM

AU - Padilla, C

AU - Paltani, S

AU - Pasian, F

AU - Pedersen, K

AU - Percival, WJ

AU - Pettorino, V

AU - Pires, S

AU - Polenta, G

AU - Poncet, M

AU - Raison, F

AU - Rebolo-Lopez, R

AU - Renzi, A

AU - Rhodes, J

AU - Riccio, G

AU - Romelli, E

AU - Roncarelli, M

AU - Saglia, R

AU - Sapone, D

AU - Sartoris, B

AU - Schneider, P

AU - Secroun, A

AU - Seidel, G

AU - Sirignano, C

AU - Sirri, G

AU - Stanco, L

AU - Tallada-Crespi, P

AU - Taylor, AN

AU - Tereno, I

AU - Toledo-Moreo, R

AU - Torradeflot, F

AU - Tutusaus, I

AU - Valenziano, L

AU - Vassallo, T

AU - Wang, Y

AU - Weller, J

AU - Zacchei, A

AU - Zamorani, G

AU - Zoubian, J

AU - Andreon, S

AU - Bardelli, S

AU - Boucaud, A

AU - Bozzo, E

AU - Colodro-Conde, C

AU - Di Ferdinando, D

AU - Fabbian, G

AU - Farina, M

AU - Lindholm, V

AU - Maino, D

AU - Mauri, N

AU - Neissner, C

AU - Scottez, V

AU - Zucca, E

AU - Baccigalupi, C

AU - Balaguera-Antolínez, A

AU - Ballardini, M

AU - Bernardeau, F

AU - Biviano, A

AU - Blanchard, A

AU - Borlaff, AS

AU - Burigana, C

AU - Cabanac, R

AU - Carvalho, CS

AU - Casas, S

AU - Castignani, G

AU - Chambers, K

AU - Cooray, AR

AU - Coupon, J

AU - Courtois, HM

AU - Davini, S

AU - de la Torre, S

AU - Desprez, G

AU - Dole, H

AU - Escartin, JA

AU - Escoffier, S

AU - Ferreira, PG

AU - Finelli, F

AU - Garcia-Bellido, J

AU - George, K

AU - Gozaliasl, G

AU - Hildebrandt, H

AU - Hook, I

AU - Muñoz, AJ

AU - Joachimi, B

AU - Kansal, V

AU - Keihänen, E

AU - Kirkpatrick, CC

AU - Loureiro, A

AU - Magliocchetti, M

AU - Maoli, R

AU - Marcin, S

AU - Martinelli, M

AU - Martinet, N

AU - Matthew, S

AU - Maturi, M

AU - Maurin, L

AU - Metcalf, RB

AU - Morgante, G

AU - Nadathur, S

AU - Nucita, AA

AU - Patrizii, L

AU - Pollack, JE

AU - Popa, V

AU - Porciani, C

AU - Potter, D

AU - Pourtsidou, A

AU - Pöentinen, M

AU - Sánchez, AG

AU - Sakr, Z

AU - Schirmer, M

AU - Sereno, M

AU - Mancini, AS

AU - Stadel, J

AU - Steinwagner, J

AU - Valieri, C

AU - Valiviita, J

AU - Veropalumbo, A

AU - Viel, M

PY - 2024/3/22

Y1 - 2024/3/22

N2 - Aims. We validate a semi-analytical model for the covariance of the real-space two-point correlation function of galaxy clusters. Methods. Using 1000 PINOCCHIO light cones mimicking the expected Euclid sample of galaxy clusters, we calibrated a simple model to accurately describe the clustering covariance. Then, we used this model to quantify the likelihood-analysis response to variations in the covariance, and we investigated the impact of a cosmology-dependent matrix at the level of statistics expected for the Euclid survey of galaxy clusters. Results. We find that a Gaussian model with Poissonian shot-noise does not correctly predict the covariance of the two-point correlation function of galaxy clusters. By introducing a few additional parameters fitted from simulations, the proposed model reproduces the numerical covariance with an accuracy of 10%, with differences of about 5% on the figure of merit of the cosmological parameters Ωm and σ8. We also find that the covariance contains additional valuable information that is not present in the mean value, and the constraining power of cluster clustering can improve significantly when its cosmology dependence is accounted for. Finally, we find that the cosmological figure of merit can be further improved when mass binning is taken into account. Our results have significant implications for the derivation of cosmological constraints from the two-point clustering statistics of the Euclid survey of galaxy clusters.

AB - Aims. We validate a semi-analytical model for the covariance of the real-space two-point correlation function of galaxy clusters. Methods. Using 1000 PINOCCHIO light cones mimicking the expected Euclid sample of galaxy clusters, we calibrated a simple model to accurately describe the clustering covariance. Then, we used this model to quantify the likelihood-analysis response to variations in the covariance, and we investigated the impact of a cosmology-dependent matrix at the level of statistics expected for the Euclid survey of galaxy clusters. Results. We find that a Gaussian model with Poissonian shot-noise does not correctly predict the covariance of the two-point correlation function of galaxy clusters. By introducing a few additional parameters fitted from simulations, the proposed model reproduces the numerical covariance with an accuracy of 10%, with differences of about 5% on the figure of merit of the cosmological parameters Ωm and σ8. We also find that the covariance contains additional valuable information that is not present in the mean value, and the constraining power of cluster clustering can improve significantly when its cosmology dependence is accounted for. Finally, we find that the cosmological figure of merit can be further improved when mass binning is taken into account. Our results have significant implications for the derivation of cosmological constraints from the two-point clustering statistics of the Euclid survey of galaxy clusters.

KW - Cosmological parameters

KW - Galaxies: clusters: general

KW - Large-scale structure of Universe

KW - Methods: statistical

UR - https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=aalto_pure&SrcAuth=WosAPI&KeyUT=WOS:001190888500023&DestLinkType=FullRecord&DestApp=WOS_CPL

UR - http://www.scopus.com/inward/record.url?scp=85185558070&partnerID=8YFLogxK

U2 - 10.1051/0004-6361/202245540

DO - 10.1051/0004-6361/202245540

M3 - Article

SN - 0004-6361

VL - 683

JO - Astronomy & Astrophysics

JF - Astronomy & Astrophysics

M1 - A253

ER -

Euclid preparation. XXXV. Covariance model validation for the two-point correlation function of galaxy cluster

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