Deep Learning Based Event Reconstruction for Cyclotron Radiation Emission Spectroscopy

Autor: Esfahani, A. Ashtari, Böser, S., Buzinsky, N., Carmona-Benitez, M. C., Cervantes, R., Claessens, C., de Viveiros, L., Fertl, M., Formaggio, J. A., Gaison, J. K., Gladstone, L., Grando, M., Guigue, M., Hartse, J., Heeger, K. M., Huyan, X., Jones, A. M., Kazkaz, K., Li, M., Lindman, A., Marsteller, A., Matthé, C., Mohiuddin, R., Monreal, B., Morrison, E. C., Mueller, R., Nikkel, J. A., Novitski, E., Oblath, N. S., Peña, J. I., Pettus, W., Reimann, R., Robertson, R. G. H., Saldaña, L., Schram, M., Slocum, P. L., Stachurska, J., Sun, Y. -H., Surukuchi, P. T., Telles, A. B., Thomas, F., Thomas, M., Thorne, L. A., Thümmler, T., Tvrznikova, L., Van De Pontseele, W., VanDevender, B. A., Weiss, T. E., Wendler, T., Zayas, E., Ziegler, A.

Publikováno v: Machine Learning: Science and Technology, 5 (2024) 025026

The objective of the Cyclotron Radiation Emission Spectroscopy (CRES) technology is to build precise particle energy spectra. This is achieved by identifying the start frequencies of charged particle trajectories which, when exposed to an external ma

Externí odkaz: http://arxiv.org/abs/2402.13256

Cyclotron Radiation Emission Spectroscopy of Electrons from Tritium Beta Decay and $^{83\rm m}$Kr Internal Conversion

Autor: Project 8 Collaboration, Esfahani, A. Ashtari, Böser, S., Buzinsky, N., Carmona-Benitez, M. C., Claessens, C., de Viveiros, L., Doe, P. J., Fertl, M., Formaggio, J. A., Gaison, J. K., Gladstone, L., Guigue, M., Hartse, J., Heeger, K. M., Huyan, X., Jones, A. M., Kazkaz, K., LaRoque, B. H., Li, M., Lindman, A., Machado, E., Marsteller, A., Matthé, C., Mohiuddin, R., Monreal, B., Mueller, R., Nikkel, J. A., Novitski, E., Oblath, N. S., Peña, J. I., Pettus, W., Reimann, R., Robertson, R. G. H., De Jesús, D. Rosa, Rybka, G., Saldaña, L., Schram, M., Slocum, P. L., Stachurska, J., Sun, Y. -H., Surukuchi, P. T., Tedeschi, J. R., Telles, A. B., Thomas, F., Thomas, M., Thorne, L. A., Thümmler, T., Tvrznikova, L., Van De Pontseele, W., VanDevender, B. A., Weintroub, J., Weiss, T. E., Wendler, T., Young, A., Zayas, E., Ziegler, A.

Project 8 has developed a novel technique, Cyclotron Radiation Emission Spectroscopy (CRES), for direct neutrino mass measurements. A CRES-based experiment on the beta spectrum of tritium has been carried out in a small-volume apparatus. We provide a

Externí odkaz: http://arxiv.org/abs/2303.12055

Tritium Beta Spectrum and Neutrino Mass Limit from Cyclotron Radiation Emission Spectroscopy

Autor: Project 8 Collaboration, Esfahani, A. Ashtari, Böser, S., Buzinsky, N., Carmona-Benitez, M. C., Claessens, C., de Viveiros, L., Doe, P. J., Fertl, M., Formaggio, J. A., Gaison, J. K., Gladstone, L., Grando, M., Guigue, M., Hartse, J., Heeger, K. M., Huyan, X., Johnston, J., Jones, A. M., Kazkaz, K., LaRoque, B. H., Li, M., Lindman, A., Machado, E., Marsteller, A., Matthé, C., Mohiuddin, R., Monreal, B., Mueller, R., Nikkel, J. A., Novitski, E., Oblath, N. S., Peña, J. I., Pettus, W., Reimann, R., Robertson, R. G. H., De Jesús, D. Rosa, Rybka, G., Saldaña, L., Schram, M., Slocum, P. L., Stachurska, J., Sun, Y. -H., Surukuchi, P. T., Tedeschi, J. R., Telles, A. B., Thomas, F., Thomas, M., Thorne, L. A., Thümmler, T., Tvrznikova, L., Van De Pontseele, W., VanDevender, B. A., Weintroub, J., Weiss, T. E., Wendler, T., Young, A., Zayas, E., Ziegler, A.

The absolute scale of the neutrino mass plays a critical role in physics at every scale, from the particle to the cosmological. Measurements of the tritium endpoint spectrum have provided the most precise direct limit on the neutrino mass scale. In t

Externí odkaz: http://arxiv.org/abs/2212.05048

First Dark Matter Search Results from the LUX-ZEPLIN (LZ) Experiment

Autor: Aalbers, J., Akerib, D. S., Akerlof, C. W., Musalhi, A. K. Al, Alder, F., Alqahtani, A., Alsum, S. K., Amarasinghe, C. S., Ames, A., Anderson, T. J., Angelides, N., Araújo, H. M., Armstrong, J. E., Arthurs, M., Azadi, S., Bailey, A. J., Baker, A., Balajthy, J., Balashov, S., Bang, J., Bargemann, J. W., Barry, M. J., Barthel, J., Bauer, D., Baxter, A., Beattie, K., Belle, J., Beltrame, P., Bensinger, J., Benson, T., Bernard, E. P., Bhatti, A., Biekert, A., Biesiadzinski, T. P., Birch, H. J., Birrittella, B., Blockinger, G. M., Boast, K. E., Boxer, B., Bramante, R., Brew, C. A. J., Brás, P., Buckley, J. H., Bugaev, V. V., Burdin, S., Busenitz, J. K., Buuck, M., Cabrita, R., Carels, C., Carlsmith, D. L., Carlson, B., Carmona-Benitez, M. C., Cascella, M., Chan, C., Chawla, A., Chen, H., Cherwinka, J. J., Chott, N. I., Cole, A., Coleman, J., Converse, M. V., Cottle, A., Cox, G., Craddock, W. W., Creaner, O., Curran, D., Currie, A., Cutter, J. E., Dahl, C. E., David, A., Davis, J., Davison, T. J. R., Delgaudio, J., Dey, S., de Viveiros, L., Dobi, A., Dobson, J. E. Y., Druszkiewicz, E., Dushkin, A., Edberg, T. K., Edwards, W. R., Elnimr, M. M., Emmet, W. T., Eriksen, S. R., Faham, C. H., Fan, A., Fayer, S., Fearon, N. M., Fiorucci, S., Flaecher, H., Ford, P., Francis, V. B., Fraser, E. D., Fruth, T., Gaitskell, R. J., Gantos, N. J., Garcia, D., Geffre, A., Gehman, V. M., Genovesi, J., Ghag, C., Gibbons, R., Gibson, E., Gilchriese, M. G. D., Gokhale, S., Gomber, B., Green, J., Greenall, A., Greenwood, S., van der Grinten, M. G. D., Gwilliam, C. B., Hall, C. R., Hans, S., Hanzel, K., Harrison, A., Hartigan-O'Connor, E., Haselschwardt, S. J., Hertel, S. A., Heuermann, G., Hjemfelt, C., Hoff, M. D., Holtom, E., Hor, J. Y-K., Horn, M., Huang, D. Q., Hunt, D., Ignarra, C. M., Jacobsen, R. G., Jahangir, O., James, R. S., Jeffery, S. N., Ji, W., Johnson, J., Kaboth, A. C., Kamaha, A. C., Kamdin, K., Kasey, V., Kazkaz, K., Keefner, J., Khaitan, D., Khaleeq, M., Khazov, A., Khurana, I., Kim, Y. D., Kocher, C. D., Kodroff, D., Korley, L., Korolkova, E. V., Kras, J., Kraus, H., Kravitz, S., Krebs, H. J., Kreczko, L., Krikler, B., Kudryavtsev, V. A., Kyre, S., Landerud, B., Leason, E. A., Lee, C., Lee, J., Leonard, D. S., Leonard, R., Lesko, K. T., Levy, C., Li, J., Liao, F. -T., Liao, J., Lin, J., Lindote, A., Linehan, R., Lippincott, W. H., Liu, R., Liu, X., Liu, Y., Loniewski, C., Lopes, M. I., Asamar, E. Lopez, Paredes, B. López, Lorenzon, W., Lucero, D., Luitz, S., Lyle, J. M., Majewski, P. A., Makkinje, J., Malling, D. C., Manalaysay, A., Manenti, L., Mannino, R. L., Marangou, N., Marzioni, M. F., Maupin, C., McCarthy, M. E., McConnell, C. T., McKinsey, D. N., McLaughlin, J., Meng, Y., Migneault, J., Miller, E. H., Mizrachi, E., Mock, J. A., Monte, A., Monzani, M. E., Morad, J. A., Mendoza, J. D. Morales, Morrison, E., Mount, B. J., Murdy, M., Murphy, A. St. J., Naim, D., Naylor, A., Nedlik, C., Nehrkorn, C., Neves, F., Nguyen, A., Nikoleyczik, J. A., Nilima, A., O'Dell, J., O'Neill, F. G., O'Sullivan, K., Olcina, I., Olevitch, M. A., Oliver-Mallory, K. C., Orpwood, J., Pagenkopf, D., Pal, S., Palladino, K. J., Palmer, J., Pangilinan, M., Parveen, N., Patton, S. J., Pease, E. K., Penning, B., Pereira, C., Pereira, G., Perry, E., Pershing, T., Peterson, I. B., Piepke, A., Podczerwinski, J., Porzio, D., Powell, S., Preece, R. M., Pushkin, K., Qie, Y., Ratcliff, B. N., Reichenbacher, J., Reichhart, L., Rhyne, C. A., Richards, A., Riffard, Q., Rischbieter, G. R. C., Rodrigues, J. P., Rodriguez, A., Rose, H. J., Rosero, R., Rossiter, P., Rushton, T., Rutherford, G., Rynders, D., Saba, J. S., Santone, D., Sazzad, A. B. M. R., Schnee, R. W., Scovell, P. R., Seymour, D., Shaw, S., Shutt, T., Silk, J. J., Silva, C., Sinev, G., Skarpaas, K., Skulski, W., Smith, R., Solmaz, M., Solovov, V. N., Sorensen, P., Soria, J., Stancu, I., Stark, M. R., Stevens, A., Stiegler, T. M., Stifter, K., Studley, R., Suerfu, B., Sumner, T. J., Sutcliffe, P., Swanson, N., Szydagis, M., Tan, M., Taylor, D. J., Taylor, R., Taylor, W. C., Temples, D. J., Tennyson, B. P., Terman, P. A., Thomas, K. J., Tiedt, D. R., Timalsina, M., To, W. H., Tomás, A., Tong, Z., Tovey, D. R., Tranter, J., Trask, M., Tripathi, M., Tronstad, D. R., Tull, C. E., Turner, W., Tvrznikova, L., Utku, U., Va'vra, J., Vacheret, A., Vaitkus, A. C., Verbus, J. R., Voirin, E., Waldron, W. L., Wang, A., Wang, B., Wang, J. J., Wang, W., Wang, Y., Watson, J. R., Webb, R. C., White, A., White, D. T., White, J. T., White, R. G., Whitis, T. J., Williams, M., Wisniewski, W. J., Witherell, M. S., Wolfs, F. L. H., Wolfs, J. D., Woodford, S., Woodward, D., Worm, S. D., Wright, C. J., Xia, Q., Xiang, X., Xiao, Q., Xu, J., Yeh, M., Yin, J., Young, I., Zarzhitsky, P., Zuckerman, A., Zweig, E. A.

Publikováno v: Phys. Rev. Lett. 131, 041002 (2023)

The LUX-ZEPLIN experiment is a dark matter detector centered on a dual-phase xenon time projection chamber operating at the Sanford Underground Research Facility in Lead, South Dakota, USA. This Letter reports results from LUX-ZEPLIN's first search f

Externí odkaz: http://arxiv.org/abs/2207.03764

Fast and Flexible Analysis of Direct Dark Matter Search Data with Machine Learning

Autor: LUX Collaboration, Akerib, D. S., Alsum, S., Araújo, H. M., Bai, X., Balajthy, J., Bang, J., Baxter, A., Bernard, E. P., Bernstein, A., Biesiadzinski, T. P., Boulton, E. M., Boxer, B., Brás, P., Burdin, S., Byram, D., Carrara, N., Carmona-Benitez, M. C., Chan, C., Cutter, J. E., de Viveiros, L., Druszkiewicz, E., Ernst, J., Fan, A., Fiorucci, S., Gaitskell, R. J., Ghag, C., Gilchriese, M. G. D., Gwilliam, C., Hall, C. R., Haselschwardt, S. J., Hertel, S. A., Hogan, D. P., Horn, M., Huang, D. Q., Ignarra, C. M., Jacobsen, R. G., Jahangir, O., Ji, W., Kamdin, K., Kazkaz, K., Khaitan, D., Korolkova, E. V., Kravitz, S., Kudryavtsev, V. A., Leason, E., Lenardo, B. G., Lesko, K. T., Liao, J., Lin, J., Lindote, A., Lopes, M. I., Manalaysay, A., Mannino, R. L., Marangou, N., McKinsey, D. N., Mei, D. -M., Morad, J. A., Murphy, A. St. J., Naylor, A., Nehrkorn, C., Nelson, H. N., Neves, F., Nilima, A., Oliver-Mallory, K. C., Palladino, K. J., Rhyne, C., Riffard, Q., Rischbieter, G. R. C., Rossiter, P., Shaw, S., Shutt, T. A., Silva, C., Solmaz, M., Solovov, V. N., Sorensen, P., Sumner, T. J., Swanson, N., Szydagis, M., Taylor, D. J., Taylor, R., Taylor, W. C., Tennyson, B. P., Terman, P. A., Tiedt, D. R., To, W. H., Tvrznikova, L., Utku, U., Vacheret, A., Vaitkus, A., Velan, V., Webb, R. C., White, J. T., Whitis, T. J., Witherell, M. S., Wolfs, F. L. H., Woodward, D., Xian, X., Xu, J., Zhang, C.

Publikováno v: Phys. Rev. D 106 (2022), 072009

We present the results from combining machine learning with the profile likelihood fit procedure, using data from the Large Underground Xenon (LUX) dark matter experiment. This approach demonstrates reduction in computation time by a factor of 30 whe

Externí odkaz: http://arxiv.org/abs/2201.05734