%0 Generic %1 fuskeland2023tensortoscalar %A Fuskeland, U. %A Aumont, J. %A Aurlien, R. %A Baccigalupi, C. %A Banday, A. J. %A Eriksen, H. K. %A Errard, J. %A Génova-Santos, R. T. %A Hasebe, T. %A Hubmayr, J. %A Imada, H. %A Krachmalnicoff, N. %A Lamagna, L. %A Pisano, G. %A Poletti, D. %A Remazeilles, M. %A Thompson, K. L. %A Vacher, L. %A Wehus, I. K. %A Azzoni, S. %A Ballardini, M. %A Barreiro, R. B. %A Bartolo, N. %A Basyrov, A. %A Beck, D. %A Bersanelli, M. %A Bortolami, M. %A Brilenkov, M. %A Calabrese, E. %A Carones, A. %A Casas, F. J. %A Cheung, K. %A Chluba, J. %A Clark, S. E. %A Clermont, L. %A Columbro, F. %A Coppolecchia, A. %A D'Alessandro, G. %A de Bernardis, P. %A de Haan, T. %A de la Hoz, E. %A De Petris, M. %A Della Torre, S. %A Diego-Palazuelos, P. %A Finelli, F. %A Franceschet, C. %A Galloni, G. %A Galloway, M. %A Gerbino, M. %A Gervasi, M. %A Ghigna, T. %A Giardiello, S. %A Gjerløw, E. %A Gruppuso, A. %A Hargrave, P. %A Hattori, M. %A Hazumi, M. %A Hergt, L. T. %A Herman, D. %A Herranz, D. %A Hivon, E. %A Hoang, T. D. %A Kohri, K. %A Lattanzi, M. %A Lee, A. T. %A Leloup, C. %A Levrier, F. %A Lonappan, A. I. %A Luzzi, G. %A Maffei, B. %A Martínez-González, E. %A Masi, S. %A Matarrese, S. %A Matsumura, T. %A Migliaccio, M. %A Montier, L. %A Morgante, G. %A Mot, B. %A Mousset, L. %A Nagata, R. %A Namikawa, T. %A Nati, F. %A Natoli, P. %A Nerval, S. %A Novelli, A. %A Pagano, L. %A Paiella, A. %A Paoletti, D. %A Pascual-Cisneros, G. %A Patanchon, G. %A Pelgrims, V. %A Piacentini, F. %A Piccirilli, G. %A Polenta, G. %A Puglisi, G. %A Raffuzzi, N. %A Ritacco, A. %A Rubino-Martin, J. A. %A Savini, G. %A Scott, D. %A Sekimoto, Y. %A Shiraishi, M. %A Signorelli, G. %A Stever, S. L. %A Stutzer, N. %A Sullivan, R. M. %A Takakura, H. %A Terenzi, L. %A Thommesen, H. %A Tristram, M. %A Tsuji, M. %A Vielva, P. %A Weller, J. %A Westbrook, B. %A Weymann-Despres, G. %A Wollack, E. J. %A Zannoni, M. %D 2023 %K tifr %T Tensor-to-scalar ratio forecasts for extended LiteBIRD frequency configurations %U http://arxiv.org/abs/2302.05228 %X LiteBIRD is a planned JAXA-led CMB B-mode satellite experiment aiming for launch in the late 2020s, with a primary goal of detecting the imprint of primordial inflationary gravitational waves. Its current baseline focal-plane configuration includes 15 frequency bands between 40 and 402 GHz, fulfilling the mission requirements to detect the amplitude of gravitational waves with the total uncertainty on the tensor-to-scalar ratio, $r$, down to $r<0.001$. A key aspect of this performance is accurate astrophysical component separation, and the ability to remove polarized thermal dust emission is particularly important. In this paper we note that the CMB frequency spectrum falls off nearly exponentially above 300 GHz relative to the thermal dust SED, and a relatively minor high frequency extension can therefore result in even lower uncertainties and better model reconstructions. Specifically, we compare the baseline design with five extended configurations, while varying the underlying dust modeling, in each of which the HFT (High-Frequency Telescope) frequency range is shifted logarithmically towards higher frequencies, with an upper cutoff ranging between 400 and 600 GHz. In each case, we measure the tensor-to-scalar ratio $r$ uncertainty and bias using both parametric and minimum-variance component-separation algorithms. When the thermal dust sky model includes a spatially varying spectral index and temperature, we find that the statistical uncertainty on $r$ after foreground cleaning may be reduced by as much as 30--50 % by extending the upper limit of the frequency range from 400 to 600 GHz, with most of the improvement already gained at 500 GHz. We also note that a broader frequency range leads to better ability to discriminate between models through higher $\chi^2$ sensitivity. (abridged)

@misc{fuskeland2023tensortoscalar, abstract = {LiteBIRD is a planned JAXA-led CMB B-mode satellite experiment aiming for launch in the late 2020s, with a primary goal of detecting the imprint of primordial inflationary gravitational waves. Its current baseline focal-plane configuration includes 15 frequency bands between 40 and 402 GHz, fulfilling the mission requirements to detect the amplitude of gravitational waves with the total uncertainty on the tensor-to-scalar ratio, $\delta r$, down to $\delta r<0.001$. A key aspect of this performance is accurate astrophysical component separation, and the ability to remove polarized thermal dust emission is particularly important. In this paper we note that the CMB frequency spectrum falls off nearly exponentially above 300 GHz relative to the thermal dust SED, and a relatively minor high frequency extension can therefore result in even lower uncertainties and better model reconstructions. Specifically, we compare the baseline design with five extended configurations, while varying the underlying dust modeling, in each of which the HFT (High-Frequency Telescope) frequency range is shifted logarithmically towards higher frequencies, with an upper cutoff ranging between 400 and 600 GHz. In each case, we measure the tensor-to-scalar ratio $r$ uncertainty and bias using both parametric and minimum-variance component-separation algorithms. When the thermal dust sky model includes a spatially varying spectral index and temperature, we find that the statistical uncertainty on $r$ after foreground cleaning may be reduced by as much as 30--50 % by extending the upper limit of the frequency range from 400 to 600 GHz, with most of the improvement already gained at 500 GHz. We also note that a broader frequency range leads to better ability to discriminate between models through higher $\chi^2$ sensitivity. (abridged)}, added-at = {2023-02-13T07:21:33.000+0100}, author = {Fuskeland, U. and Aumont, J. and Aurlien, R. and Baccigalupi, C. and Banday, A. J. and Eriksen, H. K. and Errard, J. and Génova-Santos, R. T. and Hasebe, T. and Hubmayr, J. and Imada, H. and Krachmalnicoff, N. and Lamagna, L. and Pisano, G. and Poletti, D. and Remazeilles, M. and Thompson, K. L. and Vacher, L. and Wehus, I. K. and Azzoni, S. and Ballardini, M. and Barreiro, R. B. and Bartolo, N. and Basyrov, A. and Beck, D. and Bersanelli, M. and Bortolami, M. and Brilenkov, M. and Calabrese, E. and Carones, A. and Casas, F. J. and Cheung, K. and Chluba, J. and Clark, S. E. and Clermont, L. and Columbro, F. and Coppolecchia, A. and D'Alessandro, G. and de Bernardis, P. and de Haan, T. and de la Hoz, E. and De Petris, M. and Della Torre, S. and Diego-Palazuelos, P. and Finelli, F. and Franceschet, C. and Galloni, G. and Galloway, M. and Gerbino, M. and Gervasi, M. and Ghigna, T. and Giardiello, S. and Gjerløw, E. and Gruppuso, A. and Hargrave, P. and Hattori, M. and Hazumi, M. and Hergt, L. T. and Herman, D. and Herranz, D. and Hivon, E. and Hoang, T. D. and Kohri, K. and Lattanzi, M. and Lee, A. T. and Leloup, C. and Levrier, F. and Lonappan, A. I. and Luzzi, G. and Maffei, B. and Martínez-González, E. and Masi, S. and Matarrese, S. and Matsumura, T. and Migliaccio, M. and Montier, L. and Morgante, G. and Mot, B. and Mousset, L. and Nagata, R. and Namikawa, T. and Nati, F. and Natoli, P. and Nerval, S. and Novelli, A. and Pagano, L. and Paiella, A. and Paoletti, D. and Pascual-Cisneros, G. and Patanchon, G. and Pelgrims, V. and Piacentini, F. and Piccirilli, G. and Polenta, G. and Puglisi, G. and Raffuzzi, N. and Ritacco, A. and Rubino-Martin, J. A. and Savini, G. and Scott, D. and Sekimoto, Y. and Shiraishi, M. and Signorelli, G. and Stever, S. L. and Stutzer, N. and Sullivan, R. M. and Takakura, H. and Terenzi, L. and Thommesen, H. and Tristram, M. and Tsuji, M. and Vielva, P. and Weller, J. and Westbrook, B. and Weymann-Despres, G. and Wollack, E. J. and Zannoni, M.}, biburl = {https://www.bibsonomy.org/bibtex/21e06c8cdb2d57c82c11008e25f475eff/citekhatri}, description = {Tensor-to-scalar ratio forecasts for extended LiteBIRD frequency configurations}, interhash = {ca3e99db77a25eae862c89566f1a88e6}, intrahash = {1e06c8cdb2d57c82c11008e25f475eff}, keywords = {tifr}, note = {cite arxiv:2302.05228Comment: 18 pages, 13 figures, submitted to A&A}, timestamp = {2023-02-13T07:21:33.000+0100}, title = {Tensor-to-scalar ratio forecasts for extended LiteBIRD frequency configurations}, url = {http://arxiv.org/abs/2302.05228}, year = 2023 }