Search Results - Ferragamo A.

Impact of filaments on galaxy cluster properties in The Three Hundred simulation by Santoni S., De Petris M., Ferragamo A., Yepes G., Cui W.

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Galaxy clusters morphology with Zernike polynomials: The first application on Planck Compton parameter maps by Capalbo V., De Petris M., Cui W., Ferragamo A., Ruppin F., Yepes G.

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The Three Hundred project: Contrasting clusters optical and IR properties in hydrodynamical and dark matter only simulations by Muñoz A. Jiménez, Macías-Pérez J.F., Yepes G., Gómez J.S., Cui W., De Petris M., Ferragamo A.

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A machine learning method to infer clusters of galaxies mass radial profiles from mock Sunyaev-Zel’dovich maps with The Three Hundred clusters by Ferragamo A., de Andres D., Sbriglio A., Cui W., De Petris M., Yepes G., Dupuis R., Jarraya M., Lahouli I., De Luca F., Gianfagna G., Rasia E.

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3D scaling laws and projection effects in The300-NIKA2 Sunyaev-Zeldovich Large Program Twin Samples by Paliwal A., Cui W., de Andrés D., De Petris M., Ferragamo A., Hanser C., Macías-Pérez J.-F., Mayet F., Moyer-Anin A., Muñoz-Echeverría M., Perotto L., Rasia E., Yepes G.

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Estimation of the hydrostatic-to-lensing mass bias from resolved cluster masses by Muñoz-Echeverría M., Macías-Pérez J.F., Pratt G.W., Pointecouteau E., Bartalucci I., De Petris M., Ferragamo A., Hanser C., Kéruzoré F., Mayet F., Moyer-Anin A., Paliwal A., Perotto L., Yepes G.

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The Three Hundred–NIKA2 Sunyaev–Zeldovich Large Program twin samples: Synthetic clusters to support real observations by Paliwal A., Artis E., Cui W., De Petris M., Désert F.-X., Ferragamo A., Gianfagna G., Kéruzoré F., Macías-Pérez J.-F., Mayet F., Muñoz-Echeverría M., Perotto L., Rasia E., Ruppin F., Yepes G.

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Multi-probe analysis of the galaxy cluster CL J1226.9+3332: Hydrostatic mass and hydrostatic-to-lensing bias by Muñoz-Echeverría M., Adam R., Ade P., Ajeddig H., André P., Arnaud M., Artis E., Aussel H., Bartalucci I., Beelen A., Benoît A., Berta S., Bing L., Bourrion O., Calvo M., Catalano A., De Petris M., Désert F.-X., Doyle S., Driessen E. F. C., Ferragamo A., Gomez A., Goupy J., Kéruzoré F., Kramer C., Ladjelate B., Lagache G., Leclercq S., Lestrade J.-F., Macías-Pérez J.-F., Maury A., Mauskopf P., Mayet F., Monfardini A., Paliwal A., Perotto L., Pisano G., Pointecouteau E., Ponthieu N., Pratt G. W., Revéret V., Rigby A. J., Ritacco A., Romero C., Roussel H., Ruppin F., Schuster K., Shu S., Sievers A., Tucker C., Yepes G.

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Towards the first mean pressure profile estimate with the NIKA2 Sunyaev-Zeldovich Large Program by Hanser C., Adam R., Ade P., Ajeddig H., André P., Artis E., Aussel H., Bartalucci I., Beelen A., Benoît A., Berta S., Bing L., Bourrion O., Calvo M., Catalano A., De Petris M., Désert F.-X., Doyle S., Driessen E.F.C., Ejlali G., Ferragamo A., Gomez A., Goupy J., Katsioli S., Kéruzoré F., Kramer C., Ladjelate B., Lagache G., Leclercq S., Lestrade J.-F., Macías-Pérez J.F., Madden S.C., Maury A., Mauskopf P., Mayet F., Monfardini A., Moyer-Anin A., Muñoz-Echeverría M., Paliwal A., Payerne C., Perotto L., Pisano G., Pointecouteau E., Ponthieu N., Pratt G. W., Revéret V., Rigby A.J., Ritacco A., Romero C., Roussel H., Ruppin F., Schuster K., Sievers A., Tucker C.

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The NIKA2 Sunyaev-Zeldovich Large Program by Perotto L., Adam R., Ade P., Ajeddig H., André P., Artis E., Aussel H., Barrena R., Bartalucci I., Beelen A., Benoît A., Berta S., Bing L., Bourrion O., Calvo M., Catalano A., De Petris M., Désert F.-X., Doyle S., Driessen E. F. C., Ejlali G., Ferragamo A., Gomez A., Goupy J., Hanser C., Katsioli S., Kéruzoré F., Kramer C., Ladjelate B., Lagache G., Leclercq S., Lestrade J.-F., Macías-Pérez J.F., Madden S. C., Maury A., Mauskopf P., Mayet F., Monfardini A., Moyer-Anin A., Muñoz-Echeverría M., Paliwal A., Pisano G., Pointecouteau E., Ponthieu N., Pratt G.W., Revéret V., Rigby A. J., Ritacco A., Romero C., Roussel H., Ruppin F., Schuster K., Sievers A., Tucker C., Yepes G.

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