Physical Sciences and Mathematics Commons^™

Data Analysis And Key Science Results Of Lhaaso-Wcda, Min Zha, Chuandong Gao, Shicong Hu, Shujie Lin, Zhen Wang, Guangman Xiang, Zhiguo Yao, Hao Zhou, F. Aharonian, Q. An, Axikegu, L. X. Bai, Y. X. Bai, Y. W. Bao, D. Bastieri, X. J. Bi, Y. J. Bi, H. Cai, J. T. Cai, Z. Cao, Z. Cao, J. Chang, J. F. Chang, X. C. Chang, B. M. Chen, J. Chen, L. Chen, L. Chen, L. Chen, M. J. Chen, M. L. Chen, Q. H. Chen, S. H. Chen, S. Z. Chen, T. L. Chen, X. L. Chen, Y. Chen, N. Cheng, Y. D. Cheng, S. W. Cui, X. H. Cui, Y. D. Cui, B. Z. Dai, H. L. Dai, Z. G. Dai, Danzen Gluobu, D. Della Volpe, B. D'Ettorre Piazzoli, X. J. Dong, J. H. Fan, Y. Z. Fan, Z. X. Fan, J. Fang, K. Fang, C. F. Feng, L. Feng, S. H. Feng, Y. L. Feng, B. Gao, C. D. Gao, Q. Gao, W. Gao, M. M. Ge, L. S. Geng, G. H. Gong, Q. B. Gou, M. H. Gu, J. G. Guo, X. L. Guo, Y. Q. Guo, Y. Y. Guo, Y. A. Han, H. H. He, H. N. He, J. C. He, S. L. He, X. B. He, Y. He, M. Heller, Y. K. Hor, C. Hou, X. Hou, H. B. Hu, S. Hu, S. C. Hu, X. J. Hu, D. H. Huang, Q. L. Huang, W. H. Huang, X. T. Huang, Z. C. Huang, F. Ji, X. L. Ji, H. Y. Jia, K. Jiang, Z. J. Jiang, C. Jin, D. Kuleshov, K. Levochkin, B. B. Li, C. Li, C. Li, F. Li, H. B. Li, H. C. Li, H. Y. Li, J. Li, K. Li, W. L. Li, X. Li, X. Li, X. R. Li, Y. Li, Y. Z. Li, Z. Li, Z. Li, E. W. Liang, Y. F. Liang, S. J. Lin, B. Liu, C. Liu, D. Liu, H. Liu, H. D. Liu, J. Liu, J. L. Liu, J. S. Liu, J. Y. Liu, M. Y. Liu, R. Y. Liu, S. M. Liu, W. Liu, Y. N. Liu, Z. X. Liu, W. J. Long, R. Lu, H. K. Lv, B. Q. Ma, L. L. Ma, X. H. Ma, J. R. Mao, A. Masood, W. Mitthumsiri, T. Montaruli, Y. C. Nan, B. Y. Pang, P. Pattarakijwanich, Z. Y. Pei, M. Y. Qi, B. Q. Qiao, D. Ruffolo, V. Rulev, A. Saiz, L. Shao, O. Shchegolev, X. D. Sheng, J. R. Shi, H. C. Song, Yu. V. Stenkin, V. Stepanov, Q. N. Sun, X. N. Sun, Z. B. Sun, P. H. T. Tam, Z. B. Tang, W. W. Tian, B. D. Wang, C. Wang, H. Wang, H. G. Wang, J. C. Wang, J. S. Wang, L. P. Wang, L. Y. Wang, R. N. Wang, W. Wang, W. Wang, X. G. Wang, Xiaojie Wang, X. Y. Wang, Y. D. Wang, Y. J. Wang, Y. P. Wang, Z. Wang, Z. Wang, Z. H. Wang, Z. X. Wang, D. M. Wei, J. J. Wei, Y. J. Wei, T. Wen, C. Y. Wu, H. R. Wei, S. Wu, W. X. Wu, X. F. Wu, S. Q. Xi, J. Xia, J. J. Xia, G. M. Xiang, G. Xiao, H. B. Xiao, G. G. Xin, Y. L. Xin, Y. Xing, D. L. Xu, R. X. Xu, L. Xue, D. H. Yan, C. W. Yang, F. F. Yang, J. Y. Yang, L. L. Yang, M. J. Yang, R. Z. Yang, S. B. Yang, Y. H. Yao, Z. G. Yao, Y. M. Ye, L. Q. Yin, N. Yin, X. H. You, Z. Y. You, Q. Yuan, H. D. Zeng, T. X. Zeng, W. Zeng, Z. K. Zeng, M. Zha, X. X. Zhai, B. B. Zhang, H. M. Zhang, H. Y. Zhang, J. L. Zhang, J. W. Zhang, L. Zhang, L. Zhang, L. X. Zhang, P. F. Zhang, P. P. Zhang, R. Zhang, S. R. Zhsng, S. S. Zhang, X. Zhang, X. P. Zhang, Y. Zhang, Y. Zhang, Y. F. Zhang, Y. L. Zhang, B. Zhao, J. Zhao, L. Zhao, L. Z. Zhao, S. P. Zhao, F. Zheng, Y. Zheng, B. Zhou, H. Zhou, J. N. Zhou, P. Zhou, R. Zhou, X. X. Zhou, C. G. Zhu, F. R. Zhu, H. Zhu, K. J. Zhu, X. Zuo

Physics Faculty Research & Creative Works

The Water Cherenkov Detector Array (WCDA) is an important component of Large High Altitude Air Shower Observatory (LHAASO). The main scientific target of WCDA is continuously surveying the northern sky at the level of few percent of Crab unit. In this proceeding, based on its first-year data of WCDA-1 data, the result about the Crab Nebular observation and its energy spectrum measurement have been presented. And with WCDA full array data taking since Mar. 2021, some preliminary results have been reported.

Current Status Of Electromagnetic Particle Detectors For Lhaaso-Km2a, Jia Liu, Xiaopeng Zhang, Xiangdong Sheng, Zhen Cao, F. Aharonian, Q. An, Axikegu, L. X. Bai, L. X. Bai, Y. X. Bai, Y. X. Bai, Y. W. Bao, D. Bastieri, X. J. Bi, Y. J. Bi, H. Cai, J. T. Cai, Zhe Cao, J. Chang, J. F. Chang, B. M. Chen, E. S. Chen, J. Chen, Liang Chen, Liang Chen, Long Chen, M. J. Chen, M. L. Chen, Q. H. Chen, S. H. Chen, S. Z. Chen, T. L. Chen, X. L. Chen, Y. Chen, N. Cheng, Y. D. Cheng, S. W. Cui, X. H. Cui, Y. D. Cui, B. D'Ettorre Piazzoli, B. Z. Dai, H. L. Dai, Z. G. Dai, Danzen Gluobo, D. Della Volpe, X. J. Dong, K. K. Duan, J. H. Fan, Y. Z. Fan, Z. X. Fan, J. Fang, K. Fang, C. F. Feng, S. H, Feng, Y. L. Feng, B. Gao, C. D. Gao, L. Q. Gao, Q. Gao, W. Gao, M. M. Ge, L. S. Geng, G. H. Gong, Q. B. Gou, M. H. Gu, F. L. Guo, J. G. Guo, X. L. Guo, Y. Q. Gao, Y. Y. Guo, Y. A. Han, H. H. He, H. N. He, J. C. He, S. L. He, X. B. He, Y. He, M. Heller, Y. K. Hor, C. Hou, H. B. Hu, S. Hu, S. C. Hu, X. J. Hu, D. H. Huang, Q. L. Huang, W. H. Huang, X. T. Huang, X. Y. Huang, Z. C. Huang, F. Ji, X. L. Ji, H. Y. Jia, K. Jiang, Z. J. Jiang, C. Jin, T. Ke, D. Kuleshov, K. Levochkin, B. B. Li, Cheng Li, Cong Li, F. Li, H. B. Li, H. C. Li, H. Y. Li, J. Li, K. Li, W. L. Li, X. R. Li, Xin Li, Xin Li, Y. Li, Y. Z. Li, Zhe Li, Zhuo Li, E. W. Liang, Y. F. Liang, S. J. Lin, B. Liu, C. Liu, D. Liu, H. Liu, H. D. Liu, J. Liu, J. L. Liu, J. S. Liu, J. Y. Liu, M. Y. Liu, R. Y. Liu, S. M. Liu, W. Liu, Y. Liu, Y. N. Liu, Z. X. Liu, W. J. Long, R. Lu, H. K. Lv, B. Q. Ma, L. L. Ma, X. H. Ma, J. R. Mao, A. Masood, Z. Min, W. Mitthumsiri, T. Montaruli, Y. C. Nan, B. Y. Pang, P. Pattarakijwanich, Z. Y. Pei, M. Y. Qi, Y. Q. Qi, B. Q. Qiao, J. J. Qin, D. Ruffolo, V. Rulev, A. Saiz, L. Shao, O. Shchegolev, X. D. Sheng, J. Y. Shi, H. C. Song, Yu. V. Stenkin, V. Stepanov, Y. Su, Q. N. Sun, X. N. Sun, Z. B. Sun, P. H. T. Tam, Z. B. Tang, W. W. Tian, B. D. Wang, C. Wang, H. Wang, H. G. Wang, J. C. Wang, J. S. Wang, L. P. Wang, L. Y. Wang, R. N. Wang, W. Wang, W. Wang, X. G. Wang, Xiaojie Wang, X. Y. Wang, Y. Wang, Y. D. Wang, Y. J. Wang, Y. P. Wang, Z. H. Wang, Z. X. Wang, Zhen Wang, Zheng Wang, D. M. Wei, J. J. Wei, Y. J. Wei, T. Wen, C. Y. Wu, H. R. Wu, S. Wu, W. X. Wu, X. F. Wu, S. Q. Xi, J. Xia, J. J. Xia, G. M. Xiang, D. X. Xiao, G. Xiao, H. B. Xiao, G. G. Xin, Y. L. Xin, Y. Xing, D. L. Xu, R. X. Xu, L. Xue, D. H. Yan, J. Z. Yan, C. W. Yang, F. F. Yang, J. Y. Yang, L. L. Yang, M. J. Yang, R. Z. Yang, S. B. Yang, Y. H. Yao, Z. G. Yao, Y. M. Ye, L. Q. Yin, N. Yin, X. H. You, Z. Y. You, Y. H. Yu, Q. Yuan, H. D. Zeng, T. X. Zeng, W. Zeng, Z. K. Zeng, M. Zha, X. X. Zhai, B. B. Zhang, H. M. Zhang, H. Y. Zhang, J. L. Zhang, J. W. Zhang, L. X. Zhang, Li Zhang, Lu Zhang, P. F. Zhang, P. P. Zhang, R. Zhang, S. R. Zhang, S. S. Zhang, X. Zhang, X. P. Zhang, Y. F. Zhang, Y. L. Zhang, Yi Zhang, Yong Zhang, B. Zhao, J. Zhao, L. Zhao, L. Z. Zhao, S. P. Zhao, F. Zheng, Y. Zheng, B. Zhou, H. Zhou, J. N. Zhou, P. Zhou, R. Zhou, X. X. Zhou, C. G. Zhu, F. R. Zhu, H. Zhu, K. J. Zhu, X. Zuo

Physics Faculty Research & Creative Works

The Large High Altitude Air Shower Observatory (LHAASO) is a new generation hybrid cosmic ray observatory which is expected to reveal the mystery of the origin of cosmic rays. The one square kilometer array (KM2A) containing 5195 Electromagnetic particle Detectors (ED) and 1188 Muon Detectors (MD) is a sub-array of the LHAASO. The EDs are designed to measure the density and arriving time of the secondary particles of cosmic rays. KM2A reaches its 3/4 scale by December 2020. 3978 electromagnetic particle detectors (EDs) and 917 muon detectors (MDs) are now in stable operation. In this paper, we will introduce the …

Search For Correlations Between High-Energy Gamma Rays And Neutrinos With The Hawc And Antares Detectors, A. Albert, S. Alves, M. André, M. Anghinolfi, G. Anton, M. Ardid, S. Ardid, J. J. Aubert, J. Aublin, B. Baret, S. Basa, B. Belhorma, M. Bendahman, V. Bertin, S. Biagi, M. Bissinger, J. Boumaaza, M. Bouta, M. C. Bouwhuis, H. Branzas, R. Bruijn, J. Brunner, J. Busto, B. Caiffi, A. Capone, L. Caramete, J. Carr, V. Carretero, S. Celli, M. Chabab, T. N. Chau, R. Cherkaoui El Moursli, T. Chiarusi, M. Circella, A. Coleiro, M. Colomer-Molla, R. Coniglione, P. Coyle, A. Creusot, A. F. Diaz, G. De Wasseige, A. Deschamps, C. Distefano, I. Di Palma, A. Domi, C. Donzaud, D. Dornic, D. Drouhin, T. Eberl, T. Van Eeden, D. Van Eijk, N. El Khayati, A. Enzenhofer, P. Fermani, G. Ferrara, F. Filippini, L. A. Fusco, Y. Gatelet, P. Gay, H. Glotin, R. Gozzini, R. Garcia Ruiz, K. Graf, C. Guidi, S. Hallmann, H. Van Haren, A. J. Heijboer, Y. Hello, J. J. Hernandez-Rey, J. Hobl, J. Hofestadt, F. Huang, G. Illuminati, C. W. James, B. Jisse-Jung, M. De Jong, P. De Jong, M. Kadler, O. Kalekin, U. Katz, N. R. Khan-Chowdhury, A. Kouchner, I. Kreykenbohm, V. Kulikovskiy, R. Lahmann, R. Le Breton, D. Lefevre, E. Leonora, G. Levi, M. Lincetto, D. Lopez-Coto, S Loucatos, L. Maderer, J. Manczak, M. Marcelin, A. Margiotta, A. Marinelli, J. A. Martinez-Mora, K. Melis, P. Migliozzi, A. Moussa, R. Muller, L. Nauta, S. Navas, E. Nezri, B. O'Fearraigh, A. Paun, G. E. Pavalas, C. Pellegrino, M. Perrin-Terrin, V. Pestel, P. Piatelli, C. Pieterse, C. Poire, V. Popa, T. Pradier, N. Randazzo, S. Reck, G. Riccobene, A. Romanov, A. Sanchez-Losa, D. F. E. Samtleben, M. Sanguineti, P. Sapienza, J. Schnabel, J. Schumann, F. Schussler, M. Spurio, Th. Stolarczyk, M. Taiuti, Y. Tayalati, S. J. Tingay, B. Vallage, V. Van Elewyck, F. Versari, S. Viola, D. Vivolo, J. Wilms, S. Zavatarelli, A. Zagarelli, J. D. Zornoza, J. Zuniga, A. U. Abeysekara, A. Albert, R. Alfaro, C. Alvarez, J. D. Alvarez, J. R. Angeles Camacho, J. C. Arteaga-Velazquez, K. P. Arunbabu, D. Avila Rojas, H. A. Ayala Solares, R. Babu, V. Baghmanyan, A. S. Barber, J. Becerra Gonzalez, E. Belmont-Moreno, S. Y. Benzvi, D. Berley, C. Brisbois, K. S. Caballero-Mora, T. Capistran, A. Carraminana, S. Casanova, O. Chaparro-Amaro, U. Cotti, J. Cotzomi, S. Coutino De Leon, E. De La Fuente, C. De Leon, L. Diaz-Cruz, R. Diaz Hernandez, J. C. Diaz-Velez, B. L. Gingus, M. Durocher, M. A. Duvernois, R. W. Ellsworth, K. Engel, C. Espinoza, K. L. Fan, K. Fang, M. Fernandez Alonso, B. Fick, H. Fleischhack, J. L. Flores, N. I. Fraija, D. Garcia, J. A. Garcia-Gonzalez, J. L. Garcia-Luna, G. Garcia-Torales, F. Garfias, G. Giaconti, H. Goksu, M. M. Gonzalez, J. A. Goodman, J. P. Harding, S. Hernandez, I. Herzog, J. Hinton, B. Hona, D. Huang, F. Hueyotl-Zahuantitla, C. M. Hui, B. Humensky, P. Huntemeyer, A. Iriarrte, A. Jardin-Blicq, H. Jhee, V. Joshi, D. Kieda, G. J. Kunde, S. Kunwar, A. Lara, J. Lee, W. H. Lee, D. Lennarz, H. Leon Vargas, J. Linnemann, A. L. Longinotti, R. Lopez-Coto, G. Luis-Raya, J. Lundeen, K. Malone, V. Marandon, O. Martinez, I. Martinez-Castellanos, H. Martinez-Huerta, J. Martinez-Castro, J. A. J. Matthews, J. Mcenery, P. Miranda-Romagnoli, J. A. Morales-Soto, E. Moreno, M. Mostafa, A. Nayerhoda, L. Nellen, M. Newbold, M. U. Nisa, R. Noriega-Papaqui, L. Olivera-Nieto, N. Omodei, A. Peisker, Y. Perez Araujo, E. G. Perez-Perez, C. D. Rho, C. Riviere, D. Rosa-Gonzalez, E. Ruiz-Velasco, J. Ryan, H. Salazar, F. Salesa Greus, A. Sandoval, M. Schneider, H. Schoorlemmer, J. Serna-Franco, G. Sinnis, A. J. Smith, R. W. Springer, P. Surajbali, I. Taboada, M. Tanner, K. Tollefson, I. Torres, R. Torres-Escobedo, R. Turner, F. Urena-Mena, L. Villasenor, Xiaojie Wang, I. J. Watson, T. Weisgarber, F. Werner, E. Willox, J. Wood, G. B. Yodh, A. Zepeda, H. Zhou

Physics Faculty Research & Creative Works

ANTARES is an underwater neutrino detector in the Mediterranean Sea. Its location, reconstruction accuracy for all-flavor neutrino interactions, and low energy threshold, make it the most sensitive neutrino observatory for searches below 100 TeV over large parts of the sky. The HAWC experiment is a water Cherenkov gamma-ray detector located in Mexico. Thanks to its large field of view, it is an excellent instrument to observe the very-high energy gamma-ray sky and perform high-sensitivity surveys of the Galactic Plane. The 10-year ANTARES data set and 3-year HAWC point source surveys are used to search for all-flavor neutrino emission in correlation …

Measurement Of Muon Contents In Cosmic Ray Shower With Lhaaso-Km2a Around Knee Region, Hengying Zhang, Cunfeng Feng, Cunfeng Feng, Xiaoting Feng, Liping Wang, Huihai He, Huihai He, Lingling Ma, Songzhan Chen, Songzhan Chen, Cong Li, Zhen Cao, F. Aharonian, Q. An, Axikegu, L. X. Bai, Y. X. Bai, Y. W. Bao, D. Bastieri, X. J. Bi, Y. J. Bi, H. Cai, J. T. Cai, Zhe Cao, J. Chang, J. F. Chang, B. M. Chen, E. S. Chen, J. Chen, Liang Chen, Liang Chen, Long Chen, M. J. Chen, M. L. Chen, Q. H. Chen, S. H. Chen, S. Z. Chen, T. L. Chen, X. L. Chen, Y. Chen, N. Cheng, Y. D. Cheng, S. W. Cui, X. H. Cui, Y. D. Cui, B. D'Ettorre Piazzoli, B. Z. Dai, H. L. Dai, Z. G. Dai, Danzen Gluobu, D. Della Volpe, X. J. Dong, K. K. Duan, J. H. Fan, Y. Z. Fan, Z. X. Fan, J. Fang, K. Fang, C. F. Feng, L. Feng, S. H. Feng, Y. L. Feng, B. Gao, C. D. Gao, L. Q. Gao, Q. Gao, W. Gao, M. M. Ge, L. S. Geng, G. H. Gong, Q. B. Gou, M. H. Gu, F. L. Guo, J. G. Guo, X. L. Guo, Y. Q. Gao, Y. Y. Guo, Y. A. Han, H. H. He, H. N. He, J. C. He, S. L. He, X. B. He, Y. He, M. Heller, Y. K. Hor, C. Hou, H. B. Hu, S. Hu, S. C. Hu, X. J. Hu, D. H. Huang, Q. L. Huang, W. H. Huang, X. T. Huang, X. Y. Huang, Z. C. Huang, F. Ji, X. L. Ji, H. Y. Jia, K. Jiang, Z. J. Jiang, C. Jin, T. Ke, D. Klueshov, K. Levochkin, B. B. Li, Cheng Li, Cong Li, F. Li, H. B. Li, H. C. Li, H. Y. Li, J. Li, K. Li, W. L. Li, X. R. Li, Xin Li, Xin Li, Y. Li, Y. Z. Li, Zhe Li, Zhuo Li, E. W. Liang, Y. F. Liang, S. J. Lin, B. Liu, C. Liu, D. Liu, H. Liu, H. D. Liu, J. Liu, J. L. Liu, J. S. Liu, J. Y. Liu, M. Y. Liu, R. Y. Liu, S. M. Liu, W. Liu, Y. Liu, Y. N. Liu, Z. X. Liu, W. J. Long, R. Lu, H. K. Lv, B. Q. Ma, L. L. Ma, X. H. Ma, J. R. Mao, A. Masood, Z. Min, W. Mitthumsiri, T. Montaruli, Y. C. Nan, B. Y. Pang, P. Pattarakijwanich, Z. Y. Pei, M. Y. Qi, Y. Q. Qi, B. Q. Qiao, J. J. Qin, D. Ruffolo, V. Rulev, A. Saiz, L. Shao, O. Shchegolev, X. D. Sheng, J. Y. Shi, H. C. Song, Yu. V. Stenkin, V. Stepanov, Y. Su, Q. N. Sun, X. N. Sun, Z. B. Sun, P. H. T. Tam, Z. B. Tang, W. W. Tian, B. D. Wang, C. Wang, H. Wang, H. G. Wang, J. C. Wang, J. S. Wang, L. P. Wang, L. Y. Wang, R. N. Wang, W. Wang, W. Wang, X. G. Wang, Xiaojie Wang, X. Y. Wang, Y. Wang, Y. D. Wang, Y. J. Wang, Y. P. Wang, Z. H. Wang, Z. X. Wang, Zhen Wang, Zheng Wang, D. M. Wei, J. J. Wei, Y. J. Wei, T. Wen, C. Y. Wu, H. R. Wu, S. Wu, W. X. Wu, X. F. Wu, S. Q. Xi, J. Xia, J. J. Xia, G. M. Xiang, D. X. Xiao, G. Xiao, H. B. Xiao, G. G. Xin, Y. L. Xin, Y. Xing, D. L. Xu, R. X. Xu, L. Xue, D. H. Yan, J. Z. Yan, C. W. Yang, F. F. Yang, J. Y. Yang, L. L. Yang, M. J. Yang, R. Z. Yang, S. B. Yang, Y. H. Yao, Z. G. Yao, Y. M. Ye, L. Q. Yin, N. Yin, X. H. You, Z. Y. You, Y. H. Yu, Q. Yuan, H. D. Zeng, T. X. Zeng, W. Zeng, Z. K. Zeng, M. Zha, X. X. Zhai, B. B. Zhang, H. M. Zhang, H. Y. Zhang, J. L. Zhang, J. W. Zhang, L. X. Zhang, Li Zhang, Lu Zhang, P. F. Zhang, P. P. Zhang, R. Zhang, S. R. Zhang, S. S. Zhang, X. Zhang, X. P. Zhang, Y. F. Zhang, Y. L. Zhang, Yi Zhang, Yong Zhang, B. Zhao, J. Zhao, L. Zhao, L. Z. Zhao, S. P. Zhao, F. Zheng, Y. Zheng, B. Zhou, H. Zhou, J. N. Zhou, P. Zhou, R. Zhou, X. X. Zhou, C. G. Zhu, F. R. Zhu, H. Zhu, K. J. Zhu, X. Zuo

Physics Faculty Research & Creative Works

The number of muons observed at the ground from air showers is sensitive to the mass composition of cosmic ray and hadronic interaction model. Large High Altitude Air Shower Observatory is a hybrid extensive air shower array and the KM2A is a sub-array covering an area of 1 km², consisting of electromagnetic detectors and muon detectors, can measure the muon content and shower size of the air shower simultaneously with high precision for cosmic rays in the knee region. The muon detector of KM2A is the most powerful muon detector in the current cosmic ray observatory on the …

A 3d Likelihood Analysis Tool For Lhaaso-Km2a Data, Zhen Cao, F. Aharonian, Q. An, Axikegu, L. X. Bai, Y. X. Bai, Y. W. Bao, D. Bastieri, X. J. Bi, Y. J. Bi, H. Cai, J. T. Cai, Zhe Cao, J. Chang, J. F. Chang, B. M. Chen, E. S. Chen, J. Chen, Liang Chen, Long Chen, M. J. Chen, M. L. Chen, Q. H. Chen, S. H. Chen, S. Z. Chen, T. L. Chen, X. L. Chen, Y. Chen, N. Cheng, Y. D. Cheng, S. W. Cui, X. H. Cui, Y. D. Cui, B. D'Ettorre Piazzoli, B. Z. Dai, H. L. Dai, Z. G. Dai, Danzen Gluobu, D. Della Volpe, X. J. Dong, K. K. Duan, J. H. Fan, Y. Z. Fan, Z. X. Fan, J. Fang, K. Fang, C. F. Feng, L. Feng, S. H. Feng, Y. L. Feng, B. Gao, C. D. Gao, L. Q. Gao, Q. Gao, W. Gao, M. M. Ge, L. S. Geng, G. H. Gong, Q. B. Gou, M. H. Gu, F. L. Guo, J. G. Guo, X. L, Guo, Y. Q. Guo, Y. Y. Guo, Y. A. Han, H. H. He, H. N. He, J. C. He, S. L. He, X. B. He, Y. He, M. Heller, Y. K. Hor, C. Hou, X. Hou, H. B. Hu, S. Hu, S. C. Hu, X. J. Hu, D. H. Huang, Q. L. Huang, W. H. Huang, X. T. Huang, X. Y. Huang, Z. C. Huang, F. Ji, X. L. Ji, H. Y. Jia, K. Jiang, Z. J. Jiang, C. Jin, T. Ke, D. Kuleshov, K. Levochkin, B. B. Li, Cheng Li, Cong Li, F. Li, H. B. Li, H. C. Li, H. Y. Li, Jian Li, Jie Li, K. Li, W. L. Li, X. R. Li, Xin Li, Y. Li, Y. Z. Li, Zhe Li, Zhuo Li, E. W. Liang, Y. F. Liang, S. J. Lin, B. Liu, C. Liu, D. Liu, H. Liu, H. D. Liu, J. Liu, J. L. Liu, J. S. Liu, J. Y. Liu, M. Y. Liu, R. Y. Liu, S. M. Liu, W. Liu, Y. Liu, Y. N. Liu, Z. X. Liu, W. J. Long, R. Lu, H. K. Lv, B. Q. Ma, L. L. Ma, X. H. Ma, J. R. Mao, A. Masood, Z. Min, W. Mitthumsiri, T. Montaruli, Y. C. Nan, B. Y. Pang, P. Pattarakijwanich, Z. Y. Pei, M. Y. Qi, Y. Q. Qi, B. Q. Qiao, J. J. Qin, D. Ruffolo, V. Rulev, A. Saiz, L. Shao, O. Shchegolev, X. D. Sheng, J. R. Shi, H. C. Song, Yu. V. Stenkin, V. Stepanov, Y. Su, Q. N. Sun, X. N. Sun, Z. B. Sun, P. H. T. Tam, Z. B. Tang, W. W. Tian, B. D. Wang, C. Wang, H. Wang, H. G. Wang, J. C. Wang, J. S. Wang, L. P. Wang, L. Y. Wang, R. N. Wang, W. Wang, X. G. Wang, Xiaojie Wang, X. Y. Wang, Y. Wang, Y. D. Wang, Y. J. Wang, Y. P. Wang, Z. H. Wang, Z. X. Wang, Zhen Wang, Zheng Wang, D. M. Wei, J. J. Wei, Y. J. Wei, T. Wen, C. Y. Wu, H. R. Wu, S. Wu, W. X. Wu, X. F. Wu, S. Q. Xi, J. Xia, J. J. Xia, G. M. Xiang, D. X. Xiao, G. Xiao, H. B. Xiao, G. G. Xin, Y. L. Xin, Y. Xing, D. L. Xu, R. X. Xu, L. Xue, D. H. Yan, J. Z. Yan, C. W. Yang, F. F. Yang, J. Y. Yang, L. L. Yang, M. J. Yang, R. Z. Yang, S. B. Yang, Y. H. Yao, Z. G. Yao, Y. M. Ye, L. Q. Yin, N. Yin, X. H. You, Z. Y. You, Y. H. Yu, Q. Yuan, H. D. Zeng, T. X. Zeng, W. Zeng, Z. K. Zeng, M. Zha, X. X. Zhai, B. B. Zhang, H. M. Zhang, H. Y. Zhang, J. L. Zhang, J. W. Zhang, L. X. Zhang, Li Zhang, Lu Zhang, P. F. Zhang, P. P. Zhang, R. Zhang, S. R. Zhang, S. S. Zhang, X. Zhang, X. P. Zhang, Y. F. Zhang, Y. L. Zhang, Yi Zhang, Yong Zhang, B. Zhao, J. Zhao, L. Zhao, L. Z. Zhao, S. P. Zhao, F. Zheng, Y. Zheng, B. Zhou, H. Zhou, J. N. Zhou, P. Zhou, R. Zhou, X. X. Zhou, C. G. Zhu, F. R. Zhu, H. Zhu, K. J. Zhu, X. Zuo

Physics Faculty Research & Creative Works

The square kilometer array (KM2A) is the main array of the Large High Altitude Air Shower Observatory (LHAASO), which is the most sensitive gamma-ray detector for energies above a few tens of TeV. We are developing a software pipeline based on the experimental data, Monte-Carlo simulations and the pointing track of the arrays. The pipeline is able to perform 3D (sky images at different energies) fits of KM2A data, similar to those used for Fermi-LAT and DAMPE gamma-ray analysis. This 3D likelihood analysis could fit source models of arbitrary morphology to the sky images and get energy spectra information and …

Identification Of Proton And Gamma In Lhaaso-Km2a Simulation Data With Deep Learning Algorithms, F. Zhang, F. R. Zhu, S. M. Liu, Y. C. Hao, C. He, J. Hou, Z. Li, Zhen Cao, F. Aharonian, Q. An, Axikegu, L. X. Bai, Y. X. Bai, Y. W. Bao, D. Bastieri, X. J. Bi, Y. J. Bi, H. Cai, J. T. Cai, Zhe Cao, J. Chang, J. F. Chang, B. M. Chen, E. S. Chen, J. Chen, Liang Chen, Liang Chen, Long Chen, M. J. Chen, M. L. Chen, Q. H. Chen, S. H. Chen, S. Z. Chen, T. L. Chen, X. L. Dai, Z. G. Dai, Danzen Gluobu, D. Della Volpe, X. J. Dong, K. K. Duan, J. H. Fan, Y. Z. Fan, Z. X. Fan, J. Fang, K. Fang, C. F. Feng, L. Feng, S. H. Feng, Y. L. Feng, B. Gao, C. D. Gao, L. Q. Gao, Q. Gao, W. Gao, M. M. Ge, L S. Geng, G. H. Gong, Q. B. Gou, M. H. Gu, F. L. Guo, J. G. Guo, X. L. Guo, Y. Q. Guo, Y. Y. Guo, Y. A. Han, H. H. He, H. N. He, J. C. He, S. L. He, X. B. He, Y. He, M. Heller, Y. K. Hor, C. Hou, H. B. Hu, S. Hu, S. C. Hu, X. J. Hu, D. H. Huang, Q. L. Huang, W. H. Huang, X. T. Huang, X. Y. Huang, Z. C. Huang, F. Ji, X. L. Ji, H. Y. Jia, K. Jiang, Z. J. Jiang, C. Jin, T. Ke, D. Kuleshov, K. Levochkin, B. B. Li, Cheng Li, Cong Li, F. Li, H. B. Li, H. C. Li, H. Y. Li, J. Li, K. Li, W. L. Li, X. R. Li, Xin Li, Xin Li, Y. Li, Y. Z. Li, Zhe Li, Zhuo Li, E. W. Liang, Y. F. Liang, S. J. Lin, B. Liu, C. Liu, D. Liu, H. Liu, H. D. Liu, J. Liu, J. L. Liu, J. S. Liu, J. Y. Liu, M. Y. Liu, R. Y. Liu, S. M. Liu, W. Liu, Y. Liu, Y. N. Liu, Z. X. Liu, W. J. Long, R. Lu, H. K. Lv, B. Q. Ma, L. L. Ma, X. H. Ma, J. R. Mao, A. Masood, Z. Min, W. Mitthumsiri, T. Montaruli, Y. C. Nan, B. Y. Pang, P. Pattarakijwanich, Z. Y. Pei, M. Y. Qi, Y. Q. Qi, B. Q. Qiao, J. J. Qin, D. Ruffolo, V. Rulev, A. Saiz, L. Shao, O. Shchegolev, X. D. Sheng, J. Y. Shi, H. C. Song, Yu. V. Stenkin, V. Stepanov, Y. Su, Q. N. Sun, X. N. Sun, Z. B. Sun, P. H. T. Tam, Z. B. Tang, W. W. Tian, B. D. Wang, C. Wang, H. Wang, H. G. Wang, J. C. Wang, J. S. Wang, L. P. Wang, L. Y. Wang, R. N. Wang, W. Wang, W. Wang, X. G. Wang, Xiaojie Wang, X. Y. Wang, Y. Wang, Y. D. Wang, Y. J. Wang, Y. P. Wang, Z. H. Wang, Z. X. Wang, Zhen Wang, Zheng Wang, D. M. Wei, J. J. Wei, Y. J. Wei, T. Wen, C. Y. Wu, H. R. Wu, S. Wu, W. X. Wu, X. F. Wu, S. Q. Xi, J. Xia, J. J. Xia, G. M. Xiang, D. X. Xiao, G. Xiao, H. B. Xiao, G. G. Xin, Y. L. Xin, Y. Xing, D. L. Xu, R. X. Xu, L. Xue, D. H. Yan, J. Z. Yan, C. W. Yang, F. F. Yang, J. Y. Yang, L. L. Yang, M. J. Yang, R. Z. Yang, S. B. Yang, Y. H. Yao, Z. G. Yao, Y. M. Ye, L. Q. Yin, N. Yin, X. H. You, Z. Y. You, Y. H. Yu, Q. Yuan, H. D. Zeng, T. X. Zeng, W. Zeng, Z. K. Zeng, M. Zha, X. X. Zhai, B. B. Zhang, H. M. Zhang, H. Y. Zhang, J. L. Zhang, J. W. Zhang, L. X. Zhang, Li Zhang, Lu Zhng, P. F. Zhang, P. P. Zhang, R. Zhang, S. R. Zhang, S. S. Zhng, X. Zhang, X. P. Zhang, Y. F. Zhang, Y. L. Zhang, Yi Zhang, Yong Zhang, B. Zhao, J. Zhao, L. Zhao, L. Z. Zhao, S. P. Zhao, F. Zheng, Y. Zheng, B. Zhou, H. Zhou, J. N. Zhou, P. Zhou, R. Zhou, X. X. Zhou, C. G. Zhu, F. R. Zhu, H. Zhu, K. J. Zhu, X. Zuo

Physics Faculty Research & Creative Works

Identification of proton and gamma plays an essential role in ultra-high energy gamma-ray astronomy with LHAASO-KM2A. In this work, two neural networks (deep neural networks (DNN) and graph neural networks (GNN)) are applied to distinguish proton and gamma in the LHAASOKM2A simulation data. The receiver operating characteristic (ROC) curves are used to evaluate the quality of the model. Both KM2A-DNN and KM2A-GNN models give higher Area Under Curve (AUC) scores than the traditional baseline model.

The Laser Calibration System For Lhaaso-Wfcta, Y. Wang, L. Chen, H. Liu, Q. N. Sun, X. Li, J. J. Xia, F. R. Zhu, L. S. Geng, S. S. Zhang, Y. Zhang, Zhen Cao, F. Aharonian, Q. An, Axikegu, L. X. Bai, Y. X. Bai, L. X. Bai, Y. X. Bai, Y. W. Bao, D. Bastieri, X. J. Bi, Y. J. Bi, H. Cai, J. T. Cai, Zhe Cao, J. Chang, J. F. Chang, B. M. Chen, E. S. Chen, J. Chen, Liang Chen, Liang Chen, Long Chen, M. J. Chen, M. L. Chen, Q. H. Chen, S. H. Chen, S. Z. Chen, T. L. Chen, X. L. Chen, Y. Chen, N. Cheng, Y. D. Cheng, S. W. Cui, X. H. Cui, Y. D. Cui, B. D'Ettore Piazzoli, B. Z. Dai, H. L. Dai, Z. G. Dai, Danzen Gluobu, D. Della Volpe, X. J. Dong, K. K. Duan, J. H. Fan, Y. Z. Fan, Z. X. Fan, J. Fang, K. Fang, C. F. Feng, L. Feng, S. H. Feng, Y. L. Feng, B. Gao, C. D. Gao, L. Q. Gao, Q. Gao, W. Gao, M. M. Ge, L. S. Geng, G. H. Gong, Q. B. Gou, M. H. Gu, F. L. Guo, J. G. Guo, X. L. Guo, Y. Q. Guo, Y. Y. Guo, Y. A. Han, H. H. He, H. N. He, J. C. He, S. L. He, X. B. He, Y. He, M. Heller, Y. K. Hor, C. Hou, H. B. Hu, S. Hu, S. C. Hu, X. J. Hu, D. H. Huang, Q. L. Huang, W. H. Huang, X. T. Huang, X. Y. Huang, Z. C. Huang, F. Ji, X. L. Ji, H. Y. Jia, K. Jiang, Z. J. Jiang, C. Jin, T. Ke, D. Kuleshov, K. Levochkin, B. B. Li, Cheng Li, Cong Li, F. Li, H. B. Li, H. C. Li, H. Y. Li, J. Li, K. Li, W. L. Li, X. R. Li, Xin Li, Xin Li, Y. Li, Y. Z. Li, Zhe Li, Zhuo Li, E. W. Liang, Y. F. Liang, S. J. Lin, B. Liu, C. Liu, D. Liu, H. Liu, H. D. Liu, J. Liu, J. L. Liu, J. S. Liu, J. Y. Liu, M. Y. Liu, R. Y. Liu, S. M. Liu, W. Liu, Y. Liu, Y. N. Liu, Z. X. Liu, W. J. Long, R. Lu, H. K. Lv, B. Q. Ma, L. L. Ma, X. H. Ma, J. R. Mao, A. Masood, Z. Min, W. Mitthumsiri, T. Montaruli, Y. C. Nan, B. Y. Pang, P. Pattarakijwanich, Z. Y. Pei, M. Y. Qi, Y. Q. Qi, B. Q. Qiao, J. J. Qin, D. Ruffolo, V. Rulev, A. Saiz, L. Shao, O. Shchegolev, X. D. Sheng, J. Y. Shi, H. C. Song, Yu. V. Stenkin, V. Stepanov, Y. Su, Q. N. Sun, X. N. Sun, Z. B. Sun, P. H. T. Tam, Z. B. Tang, W. W. Tian, B. D. Wang, C. Wang, H. Wang, H. G. Wang, J. C. Wang, J. S. Wang, L. P. Wang, L. Y. Wang, R. N. Wang, W. Wang, W. Wang, X. G. Wang, Xiaojie Wang, X. Y. Wang, Y. Wang, Y. D. Wang, Y. J. Wang, Y. P. Wang, Z. H. Wang, Z. X. Wang, Zhen Wang, Zheng Wang, D. M. Wei, J. J. Wei, Y. J. Wei, T. Wen, C. Y. Wu, H. R. Wu, S. Wu, W. X. Wu, X. F. Wu, S. Q. Xi, J. Xia, J. J. Xia, G. M. Xiang, D. X. Xiao, G. Xiao, H. B. Xiao, G. G. Xin, Y. L. Xin, Y. Xing, D. L. Xu, R. X. Xu, L. Xue, D. H. Yan, J. Z. Yan, C. W. Yang, F. F. Yang, J. Y. Yang, L. L. Yang, M. J. Yang, R. Z. Yang, S. B. Yang, Y. H. Yao, Z. G. Yao, Y. M. Ye, L. Q. Yin, N. Yin, Y. H. You, Z. Y. You, Y. H. Yu, Q. Yuan, H. D. Zeng, T. X. Zeng, W. Zeng, Z. K. Zeng, M. Zha, X. X. Zhai, B. B. Zhang, H. M. Zhang, H. Y. Zhang, J. L. Zhang, J. W. Zhang, L. X. Zhang, Li Zhang, Lu Zhang, P. F. Zhang, P. P. Zhang, R. Zhang, S. R. Zhang, S. S. Zhang, X. Zhang, X. P. Zhang, Y. F. Zhang, Y. L. Zhang, Yi Zhang, Yong Zhang, B. Zhao, J. Zhao, L. Zhao, L. Z. Zhao, S. P. Zhao, F. Zheng, Y. Zheng, B. Zhou, H. Zhou, J. N. Zhou, P. Shou, R. Zhou, X. X. Zhou, C. G. Zhu, F. R. Zhu, H. Zhu, K. J. Zhu, X. Zuo

Physics Faculty Research & Creative Works

The Wide Field-of-view Cherenkov Telescope Array (WFCTA) of Large High Altitude Air Shower Observatory (LHAASO) is designed to measure the Cherenkov and fluorescent light created in the extensive air showers by cosmic rays (CRs) from ∼30 TeV to several EeV. In order to achieve an end-to-end calibration method for WFCTA, three Laser lidar facilities have been installed at LHAASO. They feature two N2 and one YAG Lasers which direct calibrated and pulsed beams into sky. Light scattered from Laser beams produces tracks recorded by the telescope detectors. The Laser calibration systems are used to investigate properties of the atmosphere and …

Study Of Longitudinal Development Of Cosmic-Ray Induced Air Showers With Lhaaso-Wfcta, Hu Liu, Zhen Cao, F. Aharonian, Q. An, Axikegu, L. X. Bai, Y. X. Bai, H. Zhu, K. J. Zhu, Y. W. Bao, D. Bastieri, X. J. Bi, Y. J. Bi, H. Cai, J. T. Cai, Zhe Cao, J. Chang, J. F. Chang, B. M. Chen, E. S. Chen, J. Chen, Liang Chen, Liang Chen, Long Chen, M. J. Chen, M. L. Chen, Q. H. Chen, S. H. Chen, S. Z. Chen, T. L. Chen, X. L. Chen, Y. Chen, N. Cheng, Y. D. Cheng, S. W. Cui, X. H. Cui, Y. D. Cui, B. D'Ettorre Piazzoli, B. Z. Dai, H. L. Dai, Z. G. Dai, Danzen Gluobu, D. Della Volpe, X. J. Dong, K. K. Duan, J. H. Fan, Y. Z. Fan, Z. X. Fan, J. Fang, K. Fang, C. F. Feng, L. Feng, S. H. Feng, Y. L. Feng, B. Gao, C. D. Gao, L. Q. Gao, Q. Gao, W. Gao, M. M. Ge, L. S. Geng, G. H. Gong, Q. B. Gou, M. H. Gu, F. L. Guo, J. G. Guo, X. L. Guo, Y. Q. Guo, Y. Y. Guo, Y. A. Han, H. H. He, H. N. He, J. C. He, S. L. He, X. B. He, Y. He, M. Heller, Y. K. Hor, C. Hou, H. B. Hu, S. Hu, S. C. Hu, X. J. Hu, D. H. Huang, Q. L. Huang, W. H. Huang, X. T. Huang, X. Y. Huang, Z. C. Huang, F. Ji, X. L. Ji, H. Y. Jia, K. Jiang, Z. J. Jiang, C. Jin, T. Ke, D. Kuleshov, K. Levochkin, B. B. Li, Cheng Li, Cong Li, F. Li, H. B. Li, H. C. Li, H. Y. Li, J. Li, K. Li, W. L. Li, X. R. Li, Xin Li, Xin Li, Y. Li, Y. Z. Li, Zhe Li, Zhuo Li, E. W. Liang, Y. F. Liang, S. J. Lin, B. Liu, C. Liu, D. Liu, H. Liu, H. D. Liu, J. Liu, J. L. Liu, J. S. Liu, J. Y. Liu, M. Y. Liu, R. Y. Liu, S. M. Liu, W. Liu, Y. Liu, Y. N. Liu, Z. X. Liu, W. J. Long, R. Lu, H. K. Lv, B. Q. Ma, L. L. Ma, X. H. Ma, J. R. Mao, A. Masood, Z. Min, W. Mitthumsiri, T. Montaruli, Y. C. Nan, B. Y. Pang, P. Pattarakijwanich, Z. Y. Pei, M. Y. Qi, Y. Q. Qi, B. Q. Qiao, J. J. Qin, D. Ruffolo, V. Rulev, A. Saiz, L. Shao, O. Shchegolev, X. D. Sheng, J. Y. Shi, H. C. Song, Yu. V. Stenkin, V. Stepanov, Y. Su, Q. N. Sun, X. N. Sun, Z. B. Sun, P. H. T. Tam, Z. B. Tang, W. W. Tian, B. D. Wang, C. Wang, H. Wang, H. G. Wang, J. C. Wang, J. S. Wang, L. P. Wang, L. Y. Wang, R. N. Wang, W. Wang, W. Wang, X. G. Wang, Xiaojie Wang, X. Y. Wang, Y. Wang, Y. D. Wang, Y. J. Wang, Z. H. Wang, Z. X. Wang, Zhen Wang, Zheng Wang, D. M. Wei, J. J. Wei, Y. J. Wei, T. Wen, C. Y. Wu, H. R. Wu, S. Wu, W. X. Wu, X. F. Wu, S. Q. Xi, J. Xia, J. J. Xia, G. M. Xiang, D. X. Xiao, G. Xiao, H. B. Xiao, G. G. Xin, Y. L. Xing, Y. Xing, D. L. Xu, R. X. Xu, L. Xue, D. H. Yan, J. Z. Yan, C. W. Yang, F. F. Yang, J. Y. Yang, L. L. Yang, M. J. Yang, R. Z. Yang, S. B. Yang, Y. H. Yao, Z. G. Yao, Y. M. Ye, L. Q. Yin, N. Yin, X. H. You, Z. Y. You, Y. H. Yu, Q. Yuan, H. D. Zeng, T. X. Zeng, W. Zeng, Z. K. Zeng, M. Zha, X. X. Zhai, B. B. Zhang, H. M. Zhang, H. Y. Zhang, J. L. Zhang, J. W. Zhang, L. X. Zhang, Li Zhang, Lu Zhang, P. F. Zhang, P. P. Zhang, R. Zhang, S. R. Zhang, S. S. Zhang, X. Zhang, X. P. Zhang, Y. F. Zhang, Y. L. Zhang, Yi Zhang, Yong Zhang, B. Zhao, J. Zhao, L. Zhao, L. Z. Zhao, S. P. Zhao, F. Zheng, Y. Zheng, B. Zhou, H. Zhou, J. N. Zhou, P. Zhou, R. Zhou, X. X. Zhou, C. G. Zhu, F. R. Zhu, H. Zhu, K. J. Zhu, X. Zuo

Physics Faculty Research & Creative Works

The Wide Field-of-view Cerenkov Telescope Array (WFCTA) is an important component of Large High Altitude Air Shower Observatory (LHAASO), which aims to measure the individual energy spectra of cosmic rays from ~30 TeV to a couple of EeV. The longitudinal development is one of the main tools to distinguish nuclei from each other. WFCTA is composed of 18 imaging air Cerenkov telescopes, each telescope has 32 x 32 pixels, covers a field of view 16^o x 16^o (each pixel corresponding to 0.5^o x 0.5^o). The first telescope started in operation since February 2019, up to …

Comment Letter: Bpsou Draft Final Rmap Quality Assurance Project Plan (Qapp) (Residential Rmap Parcels) (Dated January 10, 2022), Nikia Greene

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

A Deep Learning-Based Approach To Extraction Of Filler Morphology In Sem Images With The Application Of Automated Quality Inspection, Md. Fashiar Rahman, Tzu-Liang Bill Tseng, Jianguo Wu, Yuxin Wen, Yirong Lin

Engineering Faculty Articles and Research

Automatic extraction of filler morphology (size, orientation, and spatial distribution) in Scanning Electron Microscopic (SEM) images is essential in many applications such as automatic quality inspection in composite manufacturing. Extraction of filler morphology greatly depends on accurate segmentation of fillers (fibers and particles), which is a challenging task due to the overlap of fibers and particles and their obscure presence in SEM images. Convolution Neural Networks (CNNs) have been shown to be very effective at object recognition in digital images. This paper proposes an automatic filler detection system in SEM images, utilizing a Mask Region-based CNN architecture. The proposed system …

Analysis Of Sir Epidemic Models With Sociological Phenomenon, Robert F. Allen, Katherine C. Heller, Matthew A. Pons

Spora: A Journal of Biomathematics

We propose two SIR models which incorporate sociological behavior of groups of individuals. It is these differences in behaviors which impose different infection rates on the individual susceptible populations, rather than biological differences. We compute the basic reproduction number for each model, as well as analyze the sensitivity of R₀ to changes in sociological parameter values.

Numerical Study Of Highly Efficient Centrifugal Cyclones, Murodil Madaliev

Scientific-technical journal

Centrifugal cyclones have been developing for 100 years, while the efficiency of all cyclones for fine dust does not increase by 80%. The widespread use of cyclones in all branches of industrial production is determined by the simplicity of the design and sufficient reliability in operation. Along with this, the process carried out in a cyclone presents a complex scientific problem that has not been solved from the standpoint of aerohydromechanics. This is confirmed by various cyclone designs. Currently, the efficiency of cyclone cleaning of technological flows does not meet the requirements of sanitary standards and largely determines the level …

The Effect Of Adiabatic Compression On Dark Matter Halos And The Radial Acceleration Relation, Pengfei Li, Stacy S. Mcgaugh

Faculty Scholarship

We use a semiempirical model to investigate the radial acceleration relation (RAR) in a cold dark matter (CDM) framework. Specifically, we build 80 model galaxies covering the same parameter space as the observed galaxies in the SPARC database, assigning them to dark matter (DM) halos using abundance-matching and halo mass-concentration relations. We consider several abundance-matching relations, finding some to be a better match to the kinematic data than others. We compute the unavoidable gravitational interactions between baryons and their DM halos, leading to an overall compression of the original Navarro-Frenk-White (NFW) halos. Before halo compression, high-mass galaxies lie approximately on …

Dependence Comparisons Of Order Statistics In The Proportional Hazards Model, Subhash C. Kochar

Mathematics and Statistics Faculty Publications and Presentations

Let X₁,…,X_n be mutually independent exponential random variables with distinct hazard rates λ₁,…,λ_n > 0 and let Y₁,…,Y_n be a random sample from the exponential distribution with hazard rate $\bar \lmd = \sum_{i=1}^n \lmd_i/n$. Also let X_1:n < ⋯ < X_n:n and Y_1:n < ⋯ < Y_n:n be their associated order statistics. It is shown that for 1 ≤ i < j ≤ n, the generalized spacing X_j:n - X _i:n is more dispersed than Y_j:n− Y_i:n according to dispersive ordering. This result is used to solve a long standing open problem …

Using Fine-Scale Aquatic Habitat Data To Construct Dreissenid Sdms In The Laurentian Great Lakes, Grace C. Henderson

USF Tampa Graduate Theses and Dissertations

The invasion of the Laurentian Great Lakes by aquatic invasive species (AIS) has been the subject of investigation for decades, due to their dramatic alterations to the ecosystem and high economic costs. Two AIS with the largest impacts are dreissenid zebra and quagga mussels, and though these species have been studied extensively, questions remain about what factors control their distributions, and whether lake warming will alter these distributions. Species distribution models (SDMs) offer a powerful tool to examine the relationship between species presences and environmental variables, which are typically bioclimactic data. The creation of the Aquatic Habitat (AqHab) dataset containing …

Interpretable Deep Learning For The Prediction Of Icu Admission Likelihood And Mortality Of Covid-19 Patients, Amril Nazir, Hyacinth Kwadwo Ampadu

All Works

The global healthcare system is being overburdened by an increasing number of COVID-19 patients. Physicians are having difficulty allocating resources and focusing their attention on high-risk patients, partly due to the difficulty in identifying high-risk patients early. COVID-19 hospitalizations require specialized treatment capabilities and can cause a burden on healthcare resources. Estimating future hospitalization of COVID-19 patients is, therefore, crucial to saving lives. In this paper, an interpretable deep learning model is developed to predict intensive care unit (ICU) admission and mortality of COVID-19 patients. The study comprised of patients from the Stony Brook University Hospital, with patient information such …

Potassic Volcanism Induced By Mantle Upwelling Through A Slab Window: Evidence From Shear Wave Splitting Analyses In Central Java, Fansheng Kong, Stephen S. Gao, Kelly H. Liu, Jiabiao Li

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

To delineate the mantle flow fields in the vicinity of a previously proposed slab window and the possible roles that they may play in the formation of potassic volcanism in Central Java, we conduct shear wave splitting analyses using both local S and teleseismic XKS waves (including SKS, SKKS, and PKS) recorded by 121 onshore stations and two ocean bottom seismometers (OBSs). The XKS fast orientations from the OBSs are trench normal and in accord with previous subslab anisotropy measurements. In the eastern part of Central Java, the XKS and local S fast orientations from the onshore stations are mostly …

Zero Trust And Advanced Persistent Threats: Who Will Win The War?, Bilge Karabacak, Todd Whittaker

All Faculty and Staff Scholarship

Advanced Persistent Threats (APTs) are state-sponsored actors who break into computer networks for political or industrial espionage. Because of the nature of cyberspace and ever-changing sophisticated attack techniques, it is challenging to prevent and detect APT attacks. 2020 United States Federal Government data breach once again showed how difficult to protect networks from targeted attacks. Among many other solutions and techniques, zero trust is a promising security architecture that might effectively prevent the intrusion attempts of APT actors. In the zero trust model, no process insider or outside the network is trusted by default. Zero trust is also called perimeterless …

Flood Depth Estimation During Hurricane Harvey Using Sentinel-1 And Uavsar Data, Sananda Kundu, Venkat Lakshmi, Raymond Torres

Faculty Publications

In August 2017, Hurricane Harvey was one of the most destructive storms to make landfall in the Houston area, causing loss of life and property. Temporal and spatial changes in the depth of floodwater and the extent of inundation form an essential part of flood studies. This work estimates the flood extent and depth from LiDAR DEM (light detection and ranging digital elevation model) using data from the Synthetic Aperture Radar (SAR)–Unmanned Aerial Vehicle Synthetic Aperture Radar (UAVSAR) and satellite sensor—Sentinel-1. The flood extent showed a decrease between 29–30 August and 5 September 2017. The flood depths estimated using the …

A Non-Invasive Interpretable Diagnosis Of Melanoma Skin Cancer Using Deep Learning And Ensemble Stacking Of Machine Learning Models, Iftiaz A. Alfi, Mahfuzur Rahman, Mohammad Shorfuzzaman, Amril Nazir

All Works

A skin lesion is a portion of skin that observes abnormal growth compared to other areas of the skin. The ISIC 2018 lesion dataset has seven classes. A miniature dataset version of it is also available with only two classes: malignant and benign. Malignant tumors are tumors that are cancerous, and benign tumors are non-cancerous. Malignant tumors have the ability to multiply and spread throughout the body at a much faster rate. The early detection of the cancerous skin lesion is crucial for the survival of the patient. Deep learning models and machine learning models play an essential role in …

Streamlining Project Development Through Planning & Environmental Linkages, Karen Hadley, Brett Lackey

Purdue Road School

As transportation agencies continue to explore ways to be more efficient in the project development process, they are embracing integrated methodologies like planning and environmental linkages. This tool is practical, yet highly effective and inclusive, and teams across the country are experiencing its value. This presentation will highlight a variety of use cases, discuss lessons learned and best practices, and specifically address how planning and environmental linkages can be applied in Indiana and the Midwest.

How Graduate Student Fellows Enhance What A Center For Digital Scholarship Does, Ben B. Chiewphasa

Transforming Libraries for Graduate Students

Multiple disciplines are increasingly embracing data science and digital scholarship. However, insufficient training for digital and computational methodologies within subject/departmental silos means that these needs often get overlooked. Opportunities for learning how to teach technical concepts (i.e., how to handle troubleshooting, live participatory coding, etc.) are also rare or non-existent via departmental offerings. To respond to these needs, the Navari Family Center for Digital Scholarship launched its Pedagogy Fellowship Program in Fall 2021 where Notre Dame PhD students/candidates build their instructional expertise and experience related to digital scholarship with an added bonus of enhancing their competitiveness on the job market. …

A Decade Later – Us 31 Mitigation, Summer R. Elmore

Purdue Road School

Significant transportation projects are designed and built, but that’s not the end of the story. Wetland and stream mitigation efforts, including monitoring and maintenance, may continue for a decade. This presentation will showcase INDOT mitigation sites—from their creation a decade ago to the awesome results—for projects like US-31. We’ll share timelines, photos, quality data, and challenges identified and addressed over the years.

Symbolic Semantic Memory In Transformer Language Models, Robert Kenneth Morain

Theses and Dissertations

This paper demonstrates how transformer language models can be improved by giving them access to relevant structured data extracted from a knowledge base. The knowledge base preparation process and modifications to transformer models are explained. We evaluate these methods on language modeling and question answering tasks. These results show that even simple additional knowledge augmentation leads to a reduction in validation loss by 73%. These methods also significantly outperform common ways of improving language models such as increasing the model size or adding more data.

Effects Of Pore-Forming Peptides (Melittin And Magainin 2) On The Phospholipid Bilayer Interior, Elmukhtar Ehmed Alhatmi

Dissertations and Theses

Antimicrobial peptides (AMPs) are one of the most promising solutions to drug-resistant bacteria. Melittin and magainin 2 are two of the most representative and extensively studied AMPs. In this research, I investigated the interaction of these two AMPs with three models of cell membranes: 80% POPC 20% POPG, 40%POPC 40% POPE and 20% POPG, and 80%POPC 20%POPG plus 30% mole fraction of cholesterol. Time-resolved fluorescence emission and fluorescence anisotropy decays of the fluorescent probe 1,6-diphenyl-1,3,5-hexatriene (DPH) were analyzed to determine the effects of AMPs on the bilayer headgroup packing and changes in the interior of the phospholipid bilayer during the …

Developing Efficient Transition Metal Catalyzed C-C & C-X Bond Construction, Chiyu Wei

USF Tampa Graduate Theses and Dissertations

This dissertation mainly contains three parts: 1) The synergistic Pd/enamine catalysis for asymmetric hydrocarbon functionalization of unactivated alkenes with ketones; 2) Gold redox catalysis with a selenium cation as mild oxidant; 3) HFIP promoted disulfidation and diselenation of alkyne, alkene, and allene.

Palladium-catalyzed alkene activation has its intrinsic limitation: 1) the requirement of a pre-functionalized alkene to form a Pd π-allyl complex; 2) problematic reversible β-H elimination. It always leads to limited reaction scope and losing of the stereochemical control. Synergistic palladium and enamine catalysis was conducted to promote ketone addition to unactivated olefins. A secondary amine-based organocatalyst was identified …

Growth Kinetics Determine The Polydispersity And Size Of Pbs And Pbse Nanocrystals, Michael P. Campos, Jonathan De Roo, Matthew W. Greenberg, Brandon M. Mcmurtry, Mark P. Hendricks, Ellie Bennett, Natalie Saenz, Matthew Y. Sfeir, Benjamin Abecassis, Sanjit K. Ghose, Jonathan S. Owen

Advanced Science Research Center

A library of thio- and selenourea derivatives is used to adjust the kinetics of PbE (E = S, Se) nanocrystal formation across a 1000-fold range (kr = 10−1 to 10−4 s−1), at several temperatures (80–120 °C), under a standard set of conditions (Pb : E = 1.2 : 1, [Pb(oleate)2] = 10.8 mM, [chalcogenourea] = 9.0 mM). An induction delay (tind) is observed prior to the onset of nanocrystal absorption during which PbE solute is observed using in situ X-ray total scattering. Density functional theory models fit to the X-ray pair distribution function (PDF) support a Pb2(μ2-S)2(Pb(O2CR)2)2 structure. Absorption spectra …

Non-Reciprocal Parity-Time Symmetry Breaking Based On Magneto-Optical And Gain/Loss Double Ring Resonators, Yuma Kawaguchi, Andrea Alù, Alexander B. Khanikaev

Advanced Science Research Center

In this paper, we explore the operation of a nonreciprocal non-Hermitian system consisting of a lossy magneto-optical ring resonator coupled to another ring resonator with gain and loss, and we demonstrate that such a system can exhibit non-reciprocity-based broken parity-time (PT) symmetry and supports one-way exceptional points. The nonreciprocal PT-phase transition is analyzed with the use of both analytical tools based on coupled-mode theory and two-dimensional finite element method simulations. Our calculations show that the response of the system strongly depends on the regime of operation – broken or preserved PT-symmetry. This response is leveraged to show that the system …

Localization Techniques Overview Towards 6g Communication, Nawaid Hasan, Azlan Abd Aziz, Azwan Mahmud, Nur Asyiqin Binte Hamzah, Noor Ziela Abd Rahman

Journal of Informatics and Web Engineering

Worldwide Researchers and scientist have started the investigation of the sixth generation (6G) while the fifth generation (5G) cellular system is being deployed. Under this main investigation the main aim of 6G is to provide intelligent and ubiquitous wireless connectivity with Terabits per second (Tbps) data rates. Accurate location information of the mobile devices is very much useful to accomplish these aims with the improvements of various parameters of wireless communication. The development in communication technology often creates new opportunities to improve the localization efficiency as demonstrated by the expected centimetre-level localization accuracy in 6G. While there are comprehensive literatures …

Continental Break-Up Under A Convergent Setting: Insights From P Wave Radial Anisotropy Tomography Of The Woodlark Rift In Papua New Guinea, Youqiang Yu, Frederik Tilmann, Dapeng Zhao, Stephen S. Gao, Kelly H. Liu

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

To explore the dynamic mechanism of continental rifting within a convergent setting, we determine the first P wave radial anisotropic tomography beneath the Woodlark rift in southeastern Papua New Guinea, which develops within the obliquely colliding zone between the Australian and southwest Pacific plates. The rift zone is depicted as localized low-velocity anomalies with positive radial anisotropy, which rules out a dominant role of active mantle upwelling in promoting the rift development and favors passive rifting with decompression melting as main processes. Downwelling slab relics in the upper mantle bounding the rift zone are revealed based on observed high-velocity anomalies …