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1. Association of Six Complex Inflammatory Indicators with Prognosis in Patients with Intravenous Thrombolysis Stroke

Author

Li Y, Xi L, Sun H, Yu F, Liang Q, Qie T, and Dai B

Subjects
acute ischemic stroke, neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, systemic immune inflammation index, systemic inflammation response index., Medicine (General), R5-920
Abstract

Yinglei Li,1,* Lingyun Xi,2,* Haichuan Sun,1 Feifei Yu,1 Qing Liang,1 Tao Qie,1 Bing Dai1 1Department of Emergency Medicine, Baoding NO.1 Central Hospital, Baoding, People’s Republic of China; 2Department of Laboratory and Pathology, The Hospital of 82nd Group Army PLA, Baoding, People’s Republic of China*These authors contributed equally to this workCorrespondence: Bing Dai, Department of Emergency Medicine, Baoding NO.1 Central Hospital, Baoding, People’s Republic of China, Email 447023235@qq.comObjective: The objective of this study is to examine the correlation between neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), systemic immune inflammation index (SII), systemic inflammation response index (SIRI) and pan-immune-inflammation value (PIV) with the outcome following 3 months of thrombolysis in individuals diagnosed with acute ischemic stroke.Methods: A retrospective analysis was conducted on a cohort of 762 patients who received intravenous thrombolysis between January 2019 and December 2022. The values of NLR, PLR, LMR, SII, SIRI and PIV were calculated based on relevant blood indices obtained upon admission. Logistic regression analysis using R software was employed to examine the correlation between SIRI, SII, PIV, and poor prognosis following 3 months of thrombolysis, with their distribution analyzed across the study population and various outcomes. Receiver operating characteristic (ROC) curves were utilized to analyze and evaluate their predictive efficacy for adverse outcomes.Results: The unfavorable prognosis group exhibited significant differences from the favorable prognosis group in various hematological markers, including PLR, NLR, LMR, SII, SIRI, and PIV, as indicated by ROC values of 0.613 (95% confidence interval (CI), 0.564– 0.661), 0.707 (95% CI, 0.663– 0.751), 0.614 (95% CI, 0.567– 0.662), 0.715 (95% CI, 672– 0.758), 0.631 (95% CI, 0.584– 0.679), and 0.569 (95% CI, 0.520– 0.619) respectively. (4) Conclusions: PLR, NLR, LMR, SII, SIRI, and PIV demonstrated associations with adverse outcomes at the 3-month mark in patients who underwent intravenous thrombolysis, with NLR (ROC is 0.707) and SII (ROC is 0.715) showing the most pronounced significance and PIV (ROC is 0.569) exhibiting the least significance.Keywords: acute ischemic stroke, neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, systemic immune inflammation index, systemic inflammation response index

Published
2024

2. Adaptation of a Chinese Version of the Relational Needs Satisfaction Scale Based on Item Response Theory Among Chinese Adults Aged 18–30

Author

Yu Y, Dai B, Lin L, and Zhang C

Subjects
relational needs satisfaction scale, item response theory, cross culture, measurement invariance, Psychology, BF1-990, Industrial psychology, HF5548.7-5548.85
Abstract

Yahui Yu,1,2 Buyun Dai,1 Lingkai Lin,1 Chao Zhang1,2 1School of Psychology, Jiangxi Normal University, Nanchang, Jiangxi, People’s Republic of China; 2School of Psychology, South China Normal University, Guangzhou, Guangdong, People’s Republic of ChinaCorrespondence: Buyun Dai, School of Psychology, Jiangxi Normal University, 99 Ziyang Ave, Nanchang, Jiangxi, People’s Republic of China, Tel +86-13870055780, Email biweijianpsy@qq.comPurpose: The satisfaction of relational needs is an important indicator of the quality of interpersonal relationships, but few studies on this topic have been conducted in China. The Relational Needs Satisfaction Scale (RNSS) was developed and used in three countries.Patients and Methods: In this study, the scale was standardized. A total of 2136 Chinese adults aged 18– 30 years were recruited to complete the RNSS-Chinese (RNSS-C) and the Satisfaction with Life Scale (SWLS) online, and classical test theory and item response theory (IRT) were used to analyze the psychometric characteristics of the RNSS-C. The measurement invariance of the Chinese and Czech RNSSs was analyzed.Results: (1) The RNSS still has good reliability (Cronbach’s alpha = 0.935) and validity (CFI=0.948, TLI=0.940, RMSEA=0.049, and SRMR=0.032) in China. (2) The RNSS-C revealed differences in the perceptions of relational needs construct between the two groups (ΔCFI=0.014> 0.01).Conclusion: These findings contribute to a deeper understanding of the cultural factors that shape interpersonal relationships and satisfaction in China.Keywords: relational needs satisfaction scale, item response theory, cross culture, measurement invariance

Published
2024

3. Distinct Clusters of HIV-1 CRF01_AE in Zhejiang, China: High-Risk Transmission Cluster 4 Requires Heightened Surveillance

Author

Dai B, Peng X, Sun J, Zhu X, Liu X, Xiong Y, Wan Z, Xiang D, Hui J, Ying C, Liu H, and Zhu B

Subjects
hiv-1, crf01_ae, drug resistance mutation, transmission cluster, Infectious and parasitic diseases, RC109-216
Abstract

Bohao Dai,1,&ast; Xiaorong Peng,1,&ast; Jia Sun,1 Xueling Zhu,1 Xiang Liu,1 Ye Xiong,1 Zhikai Wan,1 Dairong Xiang,1 Jiangjin Hui,1 Chenxi Ying,2 Huiting Liu,1 Biao Zhu1,&ast; 1The Department of Infectious Diseases, State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, the First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, People’s Republic of China; 2Cardivascular Surgery, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Biao Zhu, The Department of Infectious Diseases, State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, the First Affiliated Hospital, School of Medicine, Zhejiang University, 79 Qing Chun Road, Hangzhou, 310006, People’s Republic of China, Email zhubiao1207@zju.edu.cnBackground: HIV-1 CRF01_AE is becoming the predominant HIV-1 subtype among patients in China. The distribution and characteristics of transmission clusters of HIV-1 CRF01_AE in Zhejiang, Eastern China remains unclear. This study analyzed the epidemiologic characteristics and transmission clusters of HIV-1 CRF01_AE in Zhejiang.Methods: Plasma samples obtained from 152 patients of HIV-1 CRF01_AE not undergoing ART were used to amplify HIV-1 pol and env gene. CRF01_AE drug resistance mutations (DRM) prevalence was analysed using Stanford University’s HIV Drug Resistance Database. A phylogenetic tree was constructed using FastTree (version 2.1.11) based on the GTR nucleotide substitution model and visualized using Figtree (version 1.4.4) and The Interactive Tree of Life; the Chinese HIV Gene Sequence Data Platform was used to construct genetic transmission networks.Results: Majority samples could be grouped into CRF01_AE transmission Clusters 1 (11.2%), 4 (64.5%), and 5 (7.2%). The CD4+ T-cell counts in Cluster 1, 4a, 4b are lower than 5 were 15, 38, 30, and 248 cells/mm3, respectively (P < 0.05). The high X4 tropism rates were 13.2%, 11.8%, 20.0%, and 0.0% in Clusters 1, 4a, 4b, and 5, respectively. DRM rates in Clusters 4a and 4b were 17.6%, and 25.45% respectively (P < 0.05), whereas they were 17.6% and 18.2% in Clusters 1 and 5, respectively. In total, 24 transmission genetic networks, comprising 72 sequences and 61 links, were discovered; of them, 61.2%, 11.7%, and 18.2% were from Clusters 4, 1, and 5, respectively (P < 0.05).Conclusion: In Zhejiang, different CRF01_AE clusters displayed unique clinic features. Cluster 4, particularly Cluster 4b, was considered a high-risk transmission cluster. The surveillance of epidemiology of HIV-1 should be enhanced to minimize its transmission.Keywords: HIV-1 CRF01_AE, drug resistance mutation, transmission cluster

Published
2024

4. Effect of Common Cold on Serum Clozapine Concentrations in Hospitalized Patients with Schizophrenia

Author

Cao Y, Xia Q, Liang J, Wang J, Shan F, and Dai B

Subjects
clozapine, blood drug concentration, schizophrenia, white blood cell count, neutrophil count, common cold, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571, Neurology. Diseases of the nervous system, RC346-429
Abstract

Yin Cao,1– 4 Qingrong Xia,1– 4 Jun Liang,1– 4 Jiequan Wang,1– 4 Feng Shan,1– 4 Biao Dai1– 4 1Department of Pharmacy, Affiliated Psychological Hospital of Anhui Medical University, Hefei, People’s Republic of China; 2Department of Pharmacy, Hefei Fourth People’s Hospital, Hefei, People’s Republic of China; 3Psychopharmacology Research Laboratory, Anhui Mental Health Center, Hefei, People’s Republic of China; 4Department of Clinical Pharmacy, Anhui Clinical Research Center for Mental Disorders, Hefei, People’s Republic of ChinaCorrespondence: Jun Liang, Department of Pharmacy, Hefei Fourth People’s Hospital, 316 Huangshan Road, Hefei, 230000, People’s Republic of China, Email amhcliangj@163.comObjective: The present study aims to investigate the effect of common cold on the serum clozapine concentrations in hospitalized patients with schizophrenia.Methods: A total of 65 schizophrenic patients with common cold receiving clozapine treatment were retrospectively enrolled. The demographic data, medication situation, clozapine concentration, and parameters of routine haematological and biochemical laboratory tests were obtained from the medical record system. The serum clozapine concentration and clozapine concentration/dose (C/D) ratios between the baseline period and cold period were compared by paired-sample t tests. Association between the changes in serum concentration and C/D ratios of clozapine and changes in white blood cell (WBC) and neutrophil (NE) counts was evaluated using Pearson correlation analysis.Results: The serum clozapine concentration (t = − 9.856, P < 0.001) and clozapine C/D ratios (t = − 10.071, P < 0.001) were found to be significantly elevated in the cold period compared to the baseline period. Moreover, the changes in the serum clozapine concentration were found to be significantly elevated in female patients compared to male patients (t = − 2.483, P = 0.017). Furthermore, changes in the serum clozapine concentration were positively correlated to the changes in WBC (r = 0.303, P = 0.014) and NE (r = 0.315, P = 0.011) counts. Similarly, changes in clozapine C/D ratios were positively correlated to the changes in WBC (r = 0.275, P = 0.027) and NE (r = 0.328, P = 0.008) counts.Conclusion: The serum clozapine concentrations in patients with schizophrenia during the common cold period were increased, which might by related to the elevated WBC and NE counts.Keywords: clozapine, blood drug concentration, schizophrenia, white blood cell count, neutrophil count, common cold

Published
2024

5. Response of Psoriasis with Systemic Lupus Erythematosus to Secukinumab: A Case Report and Review of the Literature

Author

Dai B, Bai Y, Yu H, Huang Q, and Wang L

Subjects
psoriasis, systemic lupus erythematosus, secukinumab, Dermatology, RL1-803
Abstract

Bowen Dai,1,2 Yanping Bai,2 HongDa Yu,1,2 Qiuchen Huang,1,2 Lei Wang2 1Graduate School, Beijing University of Chinese Medicine, Beijing, 100029, People’s Republic of China; 2Department of Dermatology and Venerology, China-Japan Friendship Hospital, Beijing, 100029, People’s Republic of ChinaCorrespondence: Lei Wang, Department of Dermatology and Venereology, China-Japan Friendship Hospital, No. 2, Yinghua East Street, Chaoyang District, Beijing, 100029, People’s Republic of China, Email wanglei010zyy@163.comAbstract: Although psoriasis and systemic lupus erythematosus are both immune abnormalities, there are few reports on Ps combined with SLE in China and abroad. We present a case of a 23-year-old female with a 10-year history of psoriasis, who had a relapse with significant joint symptoms and a PASI score of 35.6, along with several positive antibodies, including antinuclear antibodies, elevated CRP and ESR, and was diagnosed with psoriasis and SLE. She has been treated with secukinumab 300 mg subcutaneously, improving her condition. She is currently being followed up. The PubMed, SCOPUS, and ISI Web of Science databases were thoroughly searched for English studies reporting psoriasis with systemic lupus erythematosus and treated using biologics. Three case reports/series were included after the screening. Our case report provides a reference for clinicians using secukinumab to treat psoriasis combined with SLE. However, further research is needed to determine whether it can be widely used or if there are common signaling pathways that can be interfered with the pathogenesis of the diseases.Keywords: psoriasis, systemic lupus erythematosus, secukinumab

Published
2023

6. Validation of a Chinese Version of the Digital Stress Scale and Development of a Short Form Based on Item Response Theory Among Chinese College Students

Author

Zhang C, Dai B, and Lin L

Subjects
digital stress scale, item response theory, measurement invariance, short form, Psychology, BF1-990, Industrial psychology, HF5548.7-5548.85
Abstract

Chao Zhang, Buyun Dai, Lingkai Lin School of Psychology, Jiangxi Normal University, Nanchang, Jiangxi, People’s Republic of ChinaCorrespondence: Buyun Dai, Jiangxi Normal University, 99 Ziyang Ave, Nanchang, Jiangxi, 330022, People’s Republic of China, Tel +86-13870055780, Email biweijianpsy@qq.comPurpose: In 2021, Hall et al developed the Digital Stress Scale (DSS), but its psychometric characteristics were only tested using classical test theory (CTT). In this study, we use item response theory (IRT) and CTT to develop and verify a Chinese version of the DSS and its short version, which can improve the reliability and effectiveness of the digital stress measurement tool for Chinese college students.Methods: In this study, we developed a Chinese version of the DSS (DSS-C) and recruited 1506 Chinese college students as participants to analyze its psychometric characteristics based on CTT and item response theory methods. First, we used CTT, including common method bias, construct validity, criterion-related validity, internal consistency, test-retest reliability and measurement invariance. Then, we adopted the IRT approach to examine the item parameters, item characteristics, item information, differential item function, test information, and test reliability of the DSS-C. Finally, a short form (DSS-C-S) was constructed, and the psychometric characteristics of the DSS-C-S were examined.Results: (1) The five-factor structure of the DSS-C was verified. The DSS-C shows good internal reliability, test-retest reliability, criterion-related validity and measurement invariance between urban college students and rural college students. (2) All 24 items had reasonable discrimination parameters and location parameters and were DIF-free by gender. Except for Items 4 and 10, all the other items had high information and measurement reliability at medium θ levels. (3) Compared with the DSS-C, the 22-item short form also has good reliability and validity and maintains sufficient measurement accuracy while reducing items of poor quality.Conclusion: Both the DSS-C and the DSS-C-S have good psychometric characteristics and are accurate and effective tools for measuring the digital stress of Chinese college students.Keywords: digital stress scale, item response theory, measurement invariance, short form

Published
2023

7. Diagnostic Value of Metagenomic Next-Generation Sequencing for Multi-Pathogenic Pneumonia in HIV-Infected Patients

Author

Xie Y, Dai B, Zhou X, Liu H, Wu W, Yu F, and Zhu B

Subjects
hiv, multi-pathogenic pneumonia, metagenomic next-generation sequencing, conventional microbiological tests, bronchoalveolar lavage fluid, Infectious and parasitic diseases, RC109-216
Abstract

Yirui Xie,1 Bohao Dai,1 Xiaotang Zhou,1 Huiting Liu,1 Wei Wu,2 Fei Yu,3 Biao Zhu1 1State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The Department of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310003, People’s Republic of China; 2State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310003, People’s Republic of China; 3Key Laboratory of Clinical in vitro Diagnostic Techniques of Zhejiang Province, Department of Laboratory Medicine, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, People’s Republic of ChinaCorrespondence: Yirui Xie; Biao Zhu, State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The Department of Infectious Diseases, The First Affiliated Hospital, School of Medicine, Zhejiang University, 79, QingChun Road, Hangzhou, 310003, People’s Republic of China, Tel/Fax +86-571-87236416, Email 1312019@zju.edu.cn; zhubiao1207@zju.edu.cnBackground: To evaluate the value and challenges of real-world clinical application of metagenomic next-generation sequencing (mNGS) for bronchoalveolar lavage fluid (BALF) in HIV-infected patients with suspected multi-pathogenic pneumonia.Methods: Fifty-seven HIV-infected patients with suspected mixed pneumonia who were agreed to undergo the bronchoscopy were recruited and retrospectively reviewed the results of mNGS and conventional microbiological tests (CMTs) of BALF from July 2020 to June 2022.Results: 54 patients were diagnosed with pneumonia including 49 patients with definite pathogens and five patients with probable pathogens. mNGS exhibited a higher diagnostic accuracy for fungal detection than CMTs in HIV-infected patients with suspected pulmonary infection. The sensitivity of mNGS in diagnosis of pneumonia in HIV-infected patients was much higher than that of CMTs (79.6% vs 61.1%; P < 0.05). Patients with mixed infection had lower CD4 T-cell count and higher symptom duration before admitting to the hospital than those with single infection. The detection rate of mNGS for mixed infection was significantly higher than that of CMTs and more co-pathogens could be identified by mNGS. The most common pattern of mixed infection observed was fungi-virus (11/29, 37.9%), followed by fungi-virus-bacteria (6/29, 20.7%) coinfection in HIV-infected patients with multi-pathogenic pneumonia.Conclusion: mNGS improved the pathogens detection rate and exhibited advantages in identifying multi-pathogenic pneumonia in HIV-infected patients. Early performance of bronchoscopy and mNGS are recommended in HIV-infected patients with low CD4 T cell counts and long duration of symptoms. The most common pattern of mixed infection observed was fungi-virus, followed by fungi-virus-bacteria coinfection in HIV infected patients with multi-pathogenic pneumonia.Keywords: HIV, multi-pathogenic pneumonia, metagenomic next-generation sequencing, conventional microbiological tests, bronchoalveolar lavage fluid

Published
2023

8. Serum Cortisol, Nesfatin-1, and IL-1β: Potential Diagnostic Biomarkers in Elderly Patients with Treatment-Resistant Depression

Author

Wu X, Dai B, Yan F, Chen Y, Xu Y, Xia Q, and Zhang X

Subjects
treatment-resistant depression, nesfatin-1, cortisol, pro-inflammatory cytokine, diagnosis, elderly, Geriatrics, RC952-954.6
Abstract

Xiaoping Wu,1,2,&ast; Biao Dai,2,3,&ast; Fanfan Yan,1,2 Yang Chen,2,4 Yayun Xu,5 Qingrong Xia,2,6 Xulai Zhang1,2 1Department of Geriatric Psychology, Hefei Fourth People’s Hospital, Affiliated Psychological Hospital of Anhui Medical University, Hefei, People’s Republic of China; 2Department of Medical Education and Research, Anhui Mental Health Center, Hefei, People’s Republic of China; 3Department of Pharmacy, Hefei Fourth People’s Hospital, Affiliated Psychological Hospital of Anhui Medical University, Hefei, People’s Republic of China; 4Modified Electroconvulsive Therapy Room, Hefei Fourth People’s Hospital, Affiliated Psychological Hospital of Anhui Medical University, Hefei, 230032, People’s Republic of China; 5Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, People’s Republic of China; 6Department of Science and Education, Hefei Fourth People’s Hospital, Affiliated Psychological Hospital of Anhui Medical University, Hefei, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Xulai Zhang, Department of Geriatric Psychology, Hefei Fourth People’s Hospital, Affiliated Psychological Hospital of Anhui Medical University, No. 316 Huangshan Road, Hefei, 230032, People’s Republic of China, Tel +86 551 63616022, Fax +86 551 63616022, Email Xulaizhang@ahmhcentre.comAim: Treatment-resistant depression (TRD) affects approximately 30% of patients with major depressive disorder (MDD), especially elderly patients. As individuals with TRD are at an increased risk of committing suicide and pose a higher risk of relapse, early diagnostic biomarkers of TRD and a better understanding of the resistance mechanism are highly needed. This study aimed to determine whether serum cortisol, nesfatin-1, and pro-inflammatory cytokines can be used as biomarkers for the diagnosis of elderly patients with TRD.Methods: Thirty elderly patients with TRD were selected as the TRD group. Thirty elderly patients with MDD who were effectively treated with conventional antidepressants were selected as the non-TRD group. The baseline levels of serum cortisol, nesfatin-1, and pro-inflammatory cytokines were measured and compared, and their diagnostic values were evaluated using the receiver operating characteristic (ROC) curve method for discriminating patients with TRD from those without TRD.Results: Serum cortisol, C-reactive protein (CRP), tumor necrosis factor-α (TNF-α), and interleukin-6 (IL-6) levels were significantly higher in the non-TRD and TRD groups than in the control group. Moreover, serum cortisol, CRP, TNF-α, and IL-6 levels in the TRD group were significantly lower than those in the non-TRD group. Furthermore, serum nesfatin-1 levels in the non-TRD group were significantly lower than those in the control and TRD groups, while the serum IL-1β levels in the non-TRD group were significantly higher than those in the control and TRD groups. Additionally, an ROC analysis revealed an area under the curve (AUC) of 0.929 for the combination of nesfatin-1 and IL-1β and an AUC of 0.956 for the combination of cortisol, nesfatin-1, and IL-1β in discriminating elderly patients with TRD from those without non-TRD.Conclusion: Serum cortisol, nesfatin-1, and IL-1β may be potential diagnostic biomarkers for discriminating elderly patients with TRD from those without TRD.Keywords: treatment-resistant depression, nesfatin-1, cortisol, pro-inflammatory cytokine, diagnosis, elderly

Published
2022

9. Detection of two TeV gamma-ray outbursts from NGC 1275 by LHAASO

Author

Cao, Zhen, Aharonian, F., Axikegu, Bai, Y. X., Bao, Y. W., Bastieri, D., Bi, X. J., Bi, Y. J., Cai, J. T., Cao, Q., Cao, W. Y., Cao, Zhe, Chang, J., Chang, J. F., Chen, A. M., Chen, E. S., Chen, Liang, Chen, Lin, Chen, Long, Chen, M. J., Chen, M. L., Chen, Q. H., Chen, S. H., Chen, S. Z., Chen, T. L., Chen, Y., Cheng, N., Cheng, Y. D., Cui, M. Y., Cui, S. W., Cui, X. H., Cui, Y. D., Dai, B. Z., Dai, H. L., Dai, Z. G., Danzengluobu, della Volpe, D., Dong, X. Q., Duan, K. K., Fan, J. H., Fan, Y. Z., Fang, J., Fang, K., Feng, C. F., Feng, L., Feng, S. H., Feng, X. T., Feng, Y. L., Gabici, S., Gao, B., Gao, C. D., Gao, L. Q., Gao, Q., Gao, W., Gao, W. K., Ge, M. M., Geng, L. S., Giacinti, G., Gong, G. H., Gou, Q. B., Gu, M. H., Guo, F. L., Guo, X. L., Guo, Y. Q., Guo, Y. Y., Han, Y. A., He, H. H., He, H. N., He, J. Y., He, X. B., He, Y., Heller, M., Hor, Y. K., Hou, B. W., Hou, C., Hou, X., Hu, H. B., Hu, Q., Hu, S. C., Huang, D. H., Huang, T. Q., Huang, W. J., Huang, X. T., Huang, X. Y., Huang, Y., Huang, Z. C., Ji, X. L., Jia, H. Y., Jia, K., Jiang, K., Jiang, X. W., Jiang, Z. J., Jin, M., Kang, M. M., Ke, T., Kuleshov, D., Kurinov, K., Li, B. B., Li, Cheng, Li, Cong, Li, D., Li, F., Li, H. B., Li, H. C., Li, H. Y., Li, J., Li, Jian, Li, Jie, Li, K., Li, W. L., Li, X. R., Li, Xin, Li, Y. Z., Li, Zhe, Li, Zhuo, Liang, E. W., Liang, Y. F., Lin, S. J., Liu, B., Liu, C., Liu, D., Liu, H., Liu, H. D., Liu, J., Liu, J. L., Liu, J. Y., Liu, M. Y., Liu, R. Y., Liu, S. M., Liu, W., Liu, Y., Liu, Y. N., Lu, R., Luo, Q., Lv, H. K., Ma, B. Q., Ma, L. L., Ma, X. H., Mao, J. R., Min, Z., Mitthumsiri, W., Mu, H. J., Nan, Y. C., Neronov, A., Ou, Z. W., Pang, B. Y., Pattarakijwanich, P., Pei, Z. Y., Qi, M. Y., Qi, Y. Q., Qiao, B. Q., Qin, J. J., Ruffolo, D., Sáiz, A., Semikoz, D., Shao, C. Y., Shao, L., Shchegolev, O., Sheng, X. D., Shu, F. W., Song, H. C., Stenkin, Yu. V., Stepanov, V., Su, Y., Sun, Q. N., Sun, X. N., Sun, Z. B., Tam, P. H. T., Tang, Q. W., Tang, Z. B., Tian, W. W., Wang, C., Wang, C. B., Wang, G. W., Wang, H. G., Wang, H. H., Wang, J. C., Wang, K., Wang, L. P., Wang, L. Y., Wang, P. H., Wang, R., Wang, W., Wang, X. G., Wang, X. Y., Wang, Y., Wang, Y. D., Wang, Y. J., Wang, Z. H., Wang, Z. X., Wang, Zhen, Wang, Zheng, Wei, D. M., Wei, J. J., Wei, Y. J., Wen, T., Wu, C. Y., Wu, H. R., Wu, S., Wu, X. F., Wu, Y. S., Xi, S. Q., Xia, J., Xia, J. J., Xiang, G. M., Xiao, D. X., Xiao, G., Xin, G. G., Xin, Y. L., Xing, Y., Xiong, Z., Xu, D. L., Xu, R. F., Xu, R. X., Xu, W. L., Xue, L., Yan, D. H., Yan, J. Z., Yan, T., Yang, C. W., Yang, F., Yang, F. F., Yang, H. W., Yang, J. Y., Yang, L. L., Yang, M. J., Yang, R. Z., Yang, S. B., Yao, Y. H., Yao, Z. G., Ye, Y. M., Yin, L. Q., Yin, N., You, X. H., You, Z. Y., Yu, Y. H., Yuan, Q., Yue, H., Zeng, H. D., Zeng, T. X., Zeng, W., Zha, M., Zhang, B. B., Zhang, F., Zhang, H. M., Zhang, H. Y., Zhang, J. L., Zhang, L. X., Zhang, Li, Zhang, P. F., Zhang, P. P., Zhang, R., Zhang, S. B., Zhang, S. R., Zhang, S. S., Zhang, X., Zhang, X. P., Zhang, Y. F., Zhang, Yi, Zhang, Yong, Zhao, B., Zhao, J., Zhao, L., Zhao, L. Z., Zhao, S. P., Zheng, F., Zhou, B., Zhou, H., Zhou, J. N., Zhou, M., Zhou, P., Zhou, R., Zhou, X. X., Zhu, C. G., Zhu, F. R., Zhu, H., Zhu, K. J., and Zuo., X.

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

The Water Cherenkov Detector Array (WCDA) is one of the components of Large High Altitude Air Shower Observatory (LHAASO) and can monitor any sources over two-thirds of the sky for up to 7 hours per day with >98\% duty cycle. In this work, we report the detection of two outbursts of the Fanaroff-Riley I radio galaxy NGC 1275 that were detected by LHAASO-WCDA between November 2022 and January 2023 with statistical significance of 5.2~$\sigma$ and 8.3~$\sigma$. The observed spectral energy distribution in the range from 500 GeV to 3 TeV is fitted by a power-law with a best-fit spectral index of $\alpha=-3.37\pm0.52$ and $-3.35\pm0.29$, respectively. The outburst flux above 0.5~TeV was ($4.55\pm 4.21)\times~10^{-11}~\rm cm^{-2}~s^{-1}$ and ($3.45\pm 1.78)\times~10^{-11}~\rm cm^{-2}~s^{-1}$, corresponding to 60\%, 45\% of Crab Nebula flux. Variation analysis reveals the variability time-scale of days at the TeV energy band. A simple test by one-zone synchrotron self-Compton model reproduces the data in the gamma-ray band well., Comment: 11 pages, 8 figures, 3 tables

Published
2024

10. LHAASO detection of very-high-energy gamma-ray emission surrounding PSR J0248+6021

Author

Cao, Zhen, Aharonian, F., An, Q., Axikegu, Bai, Y. X., Bao, Y. W., Bastieri, D., Bi, X. J., Bi, Y. J., Cai, J. T., Cao, Q., Cao, W. Y., Cao, Zhe, Chang, J., Chang, J. F., Chen, A. M., Chen, E. S., Chen, Liang, Chen, Lin, Chen, Long, Chen, M. J., Chen, M. L., Chen, Q. H., Chen, S. H., Chen, S. Z., Chen, T. L., Chen, Y., Cheng, N., Cheng, Y. D., Cui, M. Y., Cui, S. W., Cui, X. H., Cui, Y. D., Dai, B. Z., Dai, H. L., Dai, Z. G., Danzengluobu, Dong, X. Q., Duan, K. K., Fan, J. H., Fan, Y. Z., Fang, J., Fang, K., Feng, C. F., Feng, L., Feng, S. H., Feng, X. T., Feng, Y. L., Gabici, S., Gao, B., Gao, C. D., Gao, L. Q., Gao, Q., Gao, W., Gao, W. K., Ge, M. M., Geng, L. S., Giacinti, G., Gong, G. H., Gou, Q. B., Gu, M. H., Guo, F. L., Guo, X. L., Guo, Y. Q., Guo, Y. Y., Han, Y. A., He, H. H., He, H. N., He, J. Y., He, X. B., He, Y., Hor, Y. K., Hou, B. W., Hou, C., Hou, X., Hu, H. B., Hu, Q., Hu, S. C., Huang, D. H., Huang, T. Q., Huang, W. J., Huang, X. T., Huang, X. Y., Huang, Y., Huang, Z. C., Ji, X. L., Jia, H. Y., Jia, K., Jiang, K., Jiang, X. W., Jiang, Z. J., Jin, M., Kang, M. M., Ke, T., Kuleshov, D., Kurinov, K., Li, B. B., Li, Cheng, Li, Cong, Li, D., Li, F., Li, H. B., Li, H. C., Li, H. Y., Li, J., Li, Jian, Li, Jie, Li, K., Li, W. L., Li, X. R., Li, Xin, Li, Y. Z., Li, Zhe, Li, Zhuo, Liang, E. W., Liang, Y. F., Lin, J., Liu, B., Liu, C., Liu, D., Liu, H., Liu, H. D., Liu, J., Liu, J. L., Liu, J. Y., Liu, M. Y., Liu, R. Y., Liu, S. M., Liu, W., Liu, Y., Liu, Y. N., Lu, R., Luo, Q., Lv, H. K., Ma, B. Q., Ma, L. L., Ma, X. H., Mao, J. R., Min, Z., Mitthumsiri, W., Mu, H. J., Nan, Y. C., Neronov, A., Ou, Z. W., Pang, B. Y., Pattarakijwanich, P., Pei, Z. Y., Qi, M. Y., Qi, Y. Q., Qiao, B. Q., Qin, J. J., Ruffolo, D., Sáiz, A., Semikoz, D., Shao, C. Y., Shao, L., Shchegolev, O., Sheng, X. D., Shu, F. W., Song, H. C., Stenkin, Yu. V., Stepanov, V., Su, Y., Sun, Q. N., Sun, X. N., Sun, Z. B., Tam, P. H. T., Tang, Q. W., Tang, Z. B., Tian, W. W., Wang, C., Wang, C. B., Wang, G. W., Wang, H. G., Wang, H. H., Wang, J. C., Wang, K., Wang, L. P., Wang, L. Y., Wang, P. H., Wang, R., Wang, W., Wang, X. G., Wang, X. Y., Wang, Y., Wang, Y. D., Wang, Y. J., Wang, Z. H., Wang, Z. X., Wang, Zhen, Wang, Zheng, Wei, D. M., Wei, J. J., Wei, Y. J., Wen, T., Wu, C. Y., Wu, H. R., Wu, S., Wu, X. F., Wu, Y. S., Xi, S. Q., Xia, J., Xia, J. J., Xiang, G. M., Xiao, D. X., Xiao, G., Xin, G. G., Xin, Y. L., Xing, Y., Xiong, Z., Xu, D. L., Xu, R. F., Xu, R. X., Xu, W. L., Xue, L., Yan, D. H., Yan, J. Z., Yan, T., Yang, C. W., Yang, F., Yang, F. F., Yang, H. W., Yang, J. Y., Yang, L. L., Yang, M. J., Yang, R. Z., Yang, S. B., Yao, Y. H., Yao, Z. G., Ye, Y. M., Yin, L. Q., Yin, N., You, X. H., You, Z. Y., Yu, Y. H., Yuan, Q., Yue, H., Zeng, H. D., Zeng, T. X., Zeng, W., Zha, M., Zhang, B. B., Zhang, F., Zhang, H. M., Zhang, H. Y., Zhang, J. L., Zhang, L. X., Zhang, Li, Zhang, P. F., Zhang, P. P., Zhang, R., Zhang, S. B., Zhang, S. R., Zhang, S. S., Zhang, X., Zhang, X. P., Zhang, Y. F., Zhang, Yi, Zhang, Yong, Zhao, B., Zhao, J., Zhao, L., Zhao, L. Z., Zhao, S. P., Zheng, F., Zheng, J. H., Zhou, B., Zhou, H., Zhou, J. N., Zhou, M., Zhou, P., Zhou, R., Zhou, X. X., Zhu, C. G., Zhu, F. R., Zhu, H., Zhu, K. J., Zou, Y. C., and Zuo, X.

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

We report the detection of an extended very-high-energy (VHE) gamma-ray source coincident with the location of middle-aged (62.4~\rm kyr) pulsar PSR J0248+6021, by using the LHAASO-WCDA data of live 796 days and LHAASO-KM2A data of live 1216 days. A significant excess of \gray induced showers is observed both by WCDA in energy bands of 1-25~\rm TeV and KM2A in energy bands of $>$ 25~\rm TeV with 7.3 $\sigma$ and 13.5 $\sigma$, respectively. The best-fit position derived through WCDA data is R.A. = 42.06$^\circ \pm$ 0.12$^\circ$ and Dec. = 60.24$^\circ \pm $ 0.13$^\circ$ with an extension of 0.69$^\circ\pm$0.15$^\circ$ and that of the KM2A data is R.A.= 42.29$^\circ \pm $ 0.13$^\circ$ and Dec. = 60.38$^\circ \pm$ 0.07$^\circ$ with an extension of 0.37$^\circ\pm$0.07$^\circ$. No clear extended multiwavelength counterpart of this LHAASO source has been found from the radio band to the GeV band. The most plausible explanation of the VHE \gray emission is the inverse Compton process of highly relativistic electrons and positrons injected by the pulsar. These electrons/positrons are hypothesized to be either confined within the pulsar wind nebula or to have already escaped into the interstellar medium, forming a pulsar halo., Comment: 12 pages, 10 figures, Accepted by Sci. China-Phys. Mech. Astron

Published
2024

11. WD Repeat Domain 5 Promotes Invasion, Metastasis and Tumor Growth in Glioma Through Up-Regulated Zinc Finger E-Box Binding Homeobox 1 Expression

Author

Dai B, Xiao Z, Zhu G, Mao B, Huang H, Guan F, Lin Z, Peng W, Liang X, Zhang B, and Hu Z

Subjects
wdr5, zeb1, glioma, migration, metastasis, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Bin Dai, Zhiyong Xiao, Guangtong Zhu, Beibei Mao, Hui Huang, Feng Guan, Zhenyang Lin, Weicheng Peng, Xin Liang, Bolun Zhang, Zhiqiang Hu Department of Neurosurgery, Beijing Shijitan Hospital, Capital Medical University, Peking University Ninth School of Clinical Medicine, Beijing, People’s Republic of ChinaCorrespondence: Zhiqiang HuDepartment of Neurosurgery, Beijing Shijitan Hospital, Capital Medical University, Peking University Ninth School of Clinical Medicine, No. 10 Tieyi Road, Yangfangdian, Haidian District, Beijing 10038, People’s Republic of ChinaTel +86 10 63926627 Email huzhiqbj@sina.comBackground: Glioma is one of the important diseases that threaten human survival in today’s society. WD repeat domain 5 (WDR5) belongs to the components of the lysine methyltransferase complex. WDR5 is involved in gene transcription regulation, cell senescence, cancer and other biological events through methylation modification. However, its expression and function in glioma are still unclear.Materials and Methods: The expression of WDR5 was observed in glioma cells, and then a glioma cell line SW1783 knocked down WDR5 was established. The effects of the decrease of WDR5 expression on proliferation, migration, invasion and EMT of glioma cells were detected, respectively. The downstream regulators of WDR5 were identified by gene expression profiling technology, and the possible molecular mechanisms were identified.Results: In this study, we found that WDR5 could promote glioma cell’s proliferation, migration, invasion and tumor metastasis. In glioma, especially in metastatic glioma tissues, WDR5 levels were significantly increased, the higher expression level could also cause a significant reduction in overall survival of glioma patients. Second, the ability of cells’ proliferation, migration, invasion and tumor metastasis was significantly reduced in WDR5 knockdown cell lines. We also found a significant change in the expression level of epithelial and mesenchymal markers in WDR5 knockdown cell lines. Furthermore, we found that knockdown of WDR5 could inhibit the expression of zinc finger E-box binding homeobox 1 (ZEB1), and knockdown of ZEB1 could inhibit invasion, migration and epithelial–mesenchymal transformation (EMT) in WDR5 over-expression cell line. We also found that WDR5 may regulate ZEB1’s expression through H3K4me3.Conclusion: In summary, in this study, we have studied the relationship between WDR5 and glioma, and found that WDR5’s expression is positively correlated with the proliferation, migration, and invasion of glioma cells, which will help find the potential therapeutic target for glioma patients.Keywords: WDR5, ZEB1, glioma, migration, metastasis

Published
2020

12. Constraints on Ultra Heavy Dark Matter Properties from Dwarf Spheroidal Galaxies with LHAASO Observations

Author

Cao, Zhen, Aharonian, F., An, Q., Axikegu, Bai, Y. X., Bao, Y. W., Bastieri, D., Bi, X. J., Bi, Y. J., Cai, J. T., Cao, Q., Cao, W. Y., Cao, Zhe, Chang, J., Chang, J. F., Chen, A. M., Chen, E. S., Chen, Liang, Chen, Lin, Chen, Long, Chen, M. J., Chen, M. L., Chen, Q. H., Chen, S. H., Chen, S. Z., Chen, T. L., Chen, Y., Cheng, N., Cheng, Y. D., Cui, M. Y., Cui, S. W., Cui, X. H., Cui, Y. D., Dai, B. Z., Dai, H. L., Dai, Z. G., Danzengluobu, della Volpe, D., Dong, X. Q., Duan, K. K., Fan, J. H., Fan, Y. Z., Fang, J., Fang, K., Feng, C. F., Feng, L., Feng, S. H., Feng, X. T., Feng, Y. L., Gabici, S., Gao, B., Gao, C. D., Gao, L. Q., Gao, Q., Gao, W., Gao, W. K., Ge, M. M., Geng, L. S., Giacinti, G., Gong, G. H., Gou, Q. B., Gu, M. H., Guo, F. L., Guo, X. L., Guo, Y. Q., Guo, Y. Y., Han, Y. A., He, H. H., He, H. N., He, J. Y., He, X. B., He, Y., Heller, M., Hor, Y. K., Hou, B. W., Hou, C., Hou, X., Hu, H. B., Hu, Q., Hu, S. C., Huang, D. H., Huang, T. Q., Huang, W. J., Huang, X. T., Huang, X. Y., Huang, Y., Huang, Z. C., Ji, X. L., Jia, H. Y., Jia, K., Jiang, K., Jiang, X. W., Jiang, Z. J., Jin, M., Kang, M. M., Ke, T., Kuleshov, D., Kurinov, K., Li, B. B., Li, Cheng, Li, Cong, Li, D., Li, F., Li, H. B., Li, H. C., Li, H. Y., Li, J., Li, Jian, Li, Jie, Li, K., Li, W. L., Li, X. R., Li, Xin, Li, Y. Z., Li, Zhe, Li, Zhuo, Liang, E. W., Liang, Y. F., Lin, S. J., Liu, B., Liu, C., Liu, D., Liu, H., Liu, H. D., Liu, J., Liu, J. L., Liu, J. Y., Liu, M. Y., Liu, R. Y., Liu, S. M., Liu, W., Liu, Y., Liu, Y. N., Lu, R., Luo, Q., Lv, H. K., Ma, B. Q., Ma, L. L., Ma, X. H., Mao, J. R., Min, Z., Mitthumsiri, W., Mu, H. J., Nan, Y. C., Neronov, A., Ou, Z. W., Pang, B. Y., Pattarakijwanich, P., Pei, Z. Y., Qi, M. Y., Qi, Y. Q., Qiao, B. Q., Qin, J. J., Ruffolo, D., Saiz, A., Semikoz, D., Shao, C. Y., Shao, L., Shchegolev, O., Sheng, X. D., Shu, F. W., Song, H. C., Stenkin, Yu. V., Stepanov, V., Su, Y., Sun, Q. N., Sun, X. N., Sun, Z. B., Tam, P. H. T., Tang, Q. W., Tang, Z. B., Tian, W. W., Wang, C., Wang, C. B., Wang, G. W., Wang, H. G., Wang, H. H., Wang, J. C., Wang, K., Wang, L. P., Wang, L. Y., Wang, P. H., Wang, R., Wang, W., Wang, X. G., Wang, X. Y., Wang, Y., Wang, Y. D., Wang, Y. J., Wang, Z. H., Wang, Z. X., Wang, Zhen, Wang, Zheng, Wei, D. M., Wei, J. J., Wei, Y. J., Wen, T., Wu, C. Y., Wu, H. R., Wu, S., Wu, X. F., Wu, Y. S., Xi, S. Q., Xia, J., Xia, J. J., Xiang, G. M., Xiao, D. X., Xiao, G., Xin, G. G., Xin, Y. L., Xing, Y., Xiong, Z., Xu, D. L., Xu, R. F., Xu, R. X., Xu, W. L., Xue, L., Yan, D. H., Yan, J. Z., Yan, T., Yang, C. W., Yang, F., Yang, F. F., Yang, H. W., Yang, J. Y., Yang, L. L., Yang, M. J., Yang, R. Z., Yang, S. B., Yao, Y. H., Yao, Z. G., Ye, Y. M., Yin, L. Q., Yin, N., You, X. H., You, Z. Y., Yu, Y. H., Yuan, Q., Yue, H., Zeng, H. D., Zeng, T. X., Zeng, W., Zha, M., Zhang, B. B., Zhang, F., Zhang, H. M., Zhang, H. Y., Zhang, J. L., Zhang, L. X., Zhang, Li, Zhang, P. F., Zhang, P. P., Zhang, R., Zhang, S. B., Zhang, S. R., Zhang, S. S., Zhang, X., Zhang, X. P., Zhang, Y. F., Zhang, Yi, Zhang, Yong, Zhao, B., Zhao, J., Zhao, L., Zhao, L. Z., Zhao, S. P., Zheng, F., Zhou, B., Zhou, H., Zhou, J. N., Zhou, M., Zhou, P., Zhou, R., Zhou, X. X., Zhu, C. G., Zhu, F. R., Zhu, H., Zhu, K. J., and Zuo, X.

Subjects
Astrophysics - High Energy Astrophysical Phenomena, High Energy Physics - Phenomenology
Abstract

In this work we try to search for signals generated by ultra-heavy dark matter at the Large High Altitude Air Shower Observatory (LHAASO) data. We look for possible gamma-ray by dark matter annihilation or decay from 16 dwarf spheroidal galaxies in the field of view of LHAASO. Dwarf spheroidal galaxies are among the most promising targets for indirect detection of dark matter which have low fluxes of astrophysical $\gamma$-ray background while large amount of dark matter. By analyzing more than 700 days observational data at LHAASO, no significant dark matter signal from 1 TeV to 1 EeV is detected. Accordingly we derive the most stringent constraints on the ultra-heavy dark matter annihilation cross-section up to EeV. The constraints on the lifetime of dark matter in decay mode are also derived., Comment: 17 pages, 12 figures, accepted by PRL

Published
2024

13. Data quality control system and long-term performance monitor of the LHAASO-KM2A

Author

Cao, Zhen, Aharonian, F., Axikegu, Bai, Y. X., Bao, Y. W., Bastieri, D., Bi, X. J., Bi, Y. J., Bian, W., Bukevich, A. V., Cao, Q., Cao, W. Y., Cao, Zhe, Chang, J., Chang, J. F., Chen, A. M., Chen, E. S., Chen, H. X., Chen, Liang, Chen, Lin, Chen, Long, Chen, M. J., Chen, M. L., Chen, Q. H., Chen, S., Chen, S. H., Chen, S. Z., Chen, T. L., Chen, Y., Cheng, N., Cheng, Y. D., Cui, M. Y., Cui, S. W., Cui, X. H., Cui, Y. D., Dai, B. Z., Dai, H. L., Dai, Z. G., Danzengluobu, Dong, X. Q., Duan, K. K., Fan, J. H., Fan, Y. Z., Fang, J., Fang, J. H., Fang, K., Feng, C. F., Feng, H., Feng, L., Feng, S. H., Feng, X. T., Feng, Y., Feng, Y. L., Gabici, S., Gao, B., Gao, C. D., Gao, Q., Gao, W., Gao, W. K., Ge, M. M., Geng, L. S., Giacinti, G., Gong, G. H., Gou, Q. B., Gu, M. H., Guo, F. L., Guo, X. L., Guo, Y. Q., Guo, Y. Y., Han, Y. A., Hasan, M., He, H. H., He, H. N., He, J. Y., He, Y., Hor, Y. K., Hou, B. W., Hou, C., Hou, X., Hu, H. B., Hu, Q., Hu, S. C., Huang, D. H., Huang, T. Q., Huang, W. J., Huang, X. T., Huang, X. Y., Huang, Y., Ji, X. L., Jia, H. Y., Jia, K., Jiang, K., Jiang, X. W., Jiang, Z. J., Jin, M., Kang, M. M., Karpikov, I., Kuleshov, D., Kurinov, K., Li, B. B., Li, C. M., Li, Cheng, Li, Cong, Li, D., Li, F., Li, H. B., Li, H. C., Li, Jian, Li, Jie, Li, K., Li, S. D., Li, W. L., Li, X. R., Li, Xin, Li, Y. Z., Li, Zhe, Li, Zhuo, Liang, E. W., Liang, Y. F., Lin, S. J., Liu, B., Liu, C., Liu, D., Liu, D. B., Liu, H., Liu, H. D., Liu, J., Liu, J. L., Liu, M. Y., Liu, R. Y., Liu, S. M., Liu, W., Liu, Y., Liu, Y. N., Luo, Q., Luo, Y., Lv, H. K., Ma, B. Q., Ma, L. L., Ma, X. H., Mao, J. R., Min, Z., Mitthumsiri, W., Mu, H. J., Nan, Y. C., Neronov, A., Ou, L. J., Pattarakijwanich, P., Pei, Z. Y., Qi, J. C., Qi, M. Y., Qiao, B. Q., Qin, J. J., Raza, A., Ruffolo, D., Sáiz, A., Saeed, M., Semikoz, D., Shao, L., Shchegolev, O., Sheng, X. D., Shu, F. W., Song, H. C., Stenkin, Yu. V., Stepanov, V., Su, Y., Sun, D. X., Sun, Q. N., Sun, X. N., Sun, Z. B., Takata, J., Tam, P. H. T., Tang, Q. W., Tang, R., Tang, Z. B., Tian, W. W., Wang, C., Wang, C. B., Wang, G. W., Wang, H. G., Wang, H. H., Wang, J. C., Wang, Kai, Wang, L. P., Wang, L. Y., Wang, P. H., Wang, R., Wang, W., Wang, X. G., Wang, X. Y., Wang, Y., Wang, Y. D., Wang, Y. J., Wang, Z. H., Wang, Z. X., Wang, Zhen, Wang, Zheng, Wei, D. M., Wei, J. J., Wei, Y. J., Wen, T., Wu, C. Y., Wu, H. R., Wu, Q. W., Wu, S., Wu, X. F., Wu, Y. S., Xi, S. Q., Xia, J., Xiang, G. M., Xiao, D. X., Xiao, G., Xin, Y. L., Xing, Y., Xiong, D. R., Xiong, Z., Xu, D. L., Xu, R. F., Xu, R. X., Xu, W. L., Xue, L., Yan, D. H., Yan, J. Z., Yan, T., Yang, C. W., Yang, C. Y., Yang, F., Yang, F. F., Yang, L. L., Yang, M. J., Yang, R. Z., Yang, W. X., Yao, Y. H., Yao, Z. G., Yin, L. Q., Yin, N., You, X. H., You, Z. Y., Yu, Y. H., Yuan, Q., Yue, H., Zeng, H. D., Zeng, T. X., Zeng, W., Zha, M., Zhang, B. B., Zhang, F., Zhang, H., Zhang, H. M., Zhang, H. Y., Zhang, J. L., Zhang, Li, Zhang, P. F., Zhang, P. P., Zhang, R., Zhang, S. B., Zhang, S. R., Zhang, S. S., Zhang, X., Zhang, X. P., Zhang, Y. F., Zhang, Yi, Zhang, Yong, Zhao, B., Zhao, J., Zhao, L., Zhao, L. Z., Zhao, S. P., Zhao, X. H., Zheng, F., Zhong, W. J., Zhou, B., Zhou, H., Zhou, J. N., Zhou, M., Zhou, P., Zhou, R., Zhou, X. X., Zhu, B. Y., Zhu, C. G., Zhu, F. R., Zhu, H., Zhu, K. J., Zou, Y. C., and Zuo, X.

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics, High Energy Physics - Experiment, Physics - Instrumentation and Detectors
Abstract

The KM2A is the largest sub-array of the Large High Altitude Air Shower Observatory (LHAASO). It consists of 5216 electromagnetic particle detectors (EDs) and 1188 muon detectors (MDs). The data recorded by the EDs and MDs are used to reconstruct primary information of cosmic ray and gamma-ray showers. This information is used for physical analysis in gamma-ray astronomy and cosmic ray physics. To ensure the reliability of the LHAASO-KM2A data, a three-level quality control system has been established. It is used to monitor the status of detector units, stability of reconstructed parameters and the performance of the array based on observations of the Crab Nebula and Moon shadow. This paper will introduce the control system and its application on the LHAASO-KM2A data collected from August 2021 to July 2023. During this period, the pointing and angular resolution of the array were stable. From the observations of the Moon shadow and Crab Nebula, the results achieved using the two methods are consistent with each other. According to the observation of the Crab Nebula at energies from 25 TeV to 100 TeV, the time averaged pointing errors are estimated to be $-0.003^{\circ} \pm 0.005^{\circ}$ and $0.001^{\circ} \pm 0.006^{\circ}$ in the R.A. and Dec directions, respectively., Comment: 15 pages, 9 figures

Published
2024

14. Discovery of Very-high-energy Gamma-ray Emissions from the Low Luminosity AGN NGC 4278 by LHAASO

Author

Cao, Zhen, Aharonian, F., An, Q., Axikegu, Bai, Y. X., Bao, Y. W., Bastieri, D., Bi, X. J., Bi, Y. J., Cai, J. T., Cao, Q., Cao, W. Y., Cao, Zhe, Chang, J., Chang, J. F., Chen, A. M., Chen, E. S., Chen, Liang, Chen, Lin, Chen, Long, Chen, M. J., Chen, M. L., Chen, Q. H., Chen, S. H., Chen, S. Z., Chen, T. L., Chen, Y., Cheng, N., Cheng, Y. D., Cui, M. Y., Cui, S. W., Cui, X. H., Cui, Y. D., Dai, B. Z., Dai, H. L., Dai, Z. G., Danzengluobu, Dong, X. Q., Duan, K. K., Fan, J. H., Fan, Y. Z., Fang, J., Fang, K., Feng, C. F., Feng, L., Feng, S. H., Feng, X. T., Feng, Y. L., Gabici, S., Gao, B., Gao, C. D., Gao, L. Q., Gao, Q., Gao, W., Gao, W. K., Ge, M. M., Geng, L. S., Giacinti, G., Gong, G. H., Gou, Q. B., Gu, M. H., Guo, F. L., Guo, X. L., Guo, Y. Q., Guo, Y. Y., Han, Y. A., He, H. H., He, H. N., He, J. Y., He, X. B., He, Y., Hor, Y. K., Hou, B. W., Hou, C., Hou, X., Hu, H. B., Hu, Q., Hu, S. C., Huang, D. H., Huang, T. Q., Huang, W. J., Huang, X. T., Huang, X. Y., Huang, Y., Huang, Z. C., Ji, X. L., Jia, H. Y., Jia, K., Jiang, K., Jiang, X. W., Jiang, Z. J., Jin, M., Kang, M. M., Ke, T., Kuleshov, D., Kurinov, K., Li, B. B., Li, Cheng, Li, Cong, Li, D., Li, F., Li, H. B., Li, H. C., Li, H. Y., Li, J., Li, Jian, Li, Jie, Li, K., Li, W. L., Li, X. R., Li, Xin, Li, Y. Z., Li, Zhe, Li, Zhuo, Liang, E. W., Liang, Y. F., Lin, J., Liu, B., Liu, C., Liu, D., Liu, H., Liu, H. D., Liu, J., Liu, J. L., Liu, J. Y., Liu, M. Y., Liu, R. Y., Liu, S. M., Liu, W., Liu, Y., Liu, Y. N., Lu, R., Luo, Q., Lv, H. K., Ma, B. Q., Ma, L. L., Ma, X. H., Mao, J. R., Min, Z., Mitthumsiri, W., Mu, H. J., Nan, Y. C., Neronov, A., Ou, Z. W., Pang, B. Y., Pattarakijwanich, P., Pei, Z. Y., Qi, M. Y., Qi, Y. Q., Qiao, B. Q., Qin, J. J., Ruffolo, D., Sáiz, A., Semikoz, D., Shao, C. Y., Shao, L., Shchegolev, O., Sheng, X. D., Shu, F. W., Song, H. C., Stenkin, Yu. V., Stepanov, V., Su, Y., Sun, Q. N., Sun, X. N., Sun, Z. B., Tam, P. H. T., Tang, Q. W., Tang, Z. B., Tian, W. W., Wang, C., Wang, C. B., Wang, G. W., Wang, H. G., Wang, H. H., Wang, J. C., Wang, K., Wang, L. P., Wang, L. Y., Wang, P. H., Wang, R., Wang, W., Wang, X. G., Wang, X. Y., Wang, Y., Wang, Y. D., Wang, Y. J., Wang, Z. H., Wang, Z. X., Wang, Zhen, Wang, Zheng, Wei, D. M., Wei, J. J., Wei, Y. J., Wen, T., Wu, C. Y., Wu, H. R., Wu, S., Wu, X. F., Wu, Y. S., Xi, S. Q., Xia, J., Xia, J. J., Xiang, G. M., Xiao, D. X., Xiao, G., Xin, G. G., Xin, Y. L., Xing, Y., Xiong, Z., Xu, D. L., Xu, R. F., Xu, R. X., Xu, W. L., Xue, L., Yan, D. H., Yan, J. Z., Yan, T., Yang, C. W., Yang, F., Yang, F. F., Yang, H. W., Yang, J. Y., Yang, L. L., Yang, M. J., Yang, R. Z., Yang, S. B., Yao, Y. H., Yao, Z. G., Ye, Y. M., Yin, L. Q., Yin, N., You, X. H., You, Z. Y., Yu, Y. H., Yuan, Q., Yue, H., Zeng, H. D., Zeng, T. X., Zeng, W., Zha, M., Zhang, B. B., Zhang, F., Zhang, H. M., Zhang, H. Y., Zhang, J. L., Zhang, L. X., Zhang, Li, Zhang, P. F., Zhang, P. P., Zhang, R., Zhang, S. B., Zhang, S. R., Zhang, S. S., Zhang, X., Zhang, X. P., Zhang, Y. F., Zhang, Yi, Zhang, Yong, Zhao, B., Zhao, J., Zhao, L., Zhao, L. Z., Zhao, S. P., Zheng, F., Zheng, J. H., Zhou, B., Zhou, H., Zhou, J. N., Zhou, M., Zhou, P., Zhou, R., Zhou, X. X., Zhu, C. G., Zhu, F. R., Zhu, H., Zhu, K. J., Zou, Y. C., and Zuo, X.

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

The first source catalog of Large High Altitude Air Shower Observatory reported the detection of a very-high-energy gamma ray source, 1LHAASO J1219+2915. In this paper a further detailed study of the spectral and temporal behavior of this point-like source have been carried. The best-fit position of the TeV source ($\rm{RA}=185.05^{\circ}\pm0.04^{\circ}$, $\rm{Dec}=29.25^{\circ}\pm0.03^{\circ}$) is compatible with NGC 4278 within $\sim0.03$ degree. Variation analysis shows an indication of the variability at a few months level in the TeV band, which is consistent with low frequency observations. Based on these observations, we report the detection of TeV $\gamma$-ray emissions from this low-luminosity AGN NGC 4278. The observations by LHAASO-WCDA during active period has a significance level of 8.8\,$\sigma$ with best-fit photon spectral index $\varGamma=2.56\pm0.14$ and a flux $f_{1-10\,\rm{TeV}}=(7.0\pm1.1_{\rm{sta}}\pm0.35_{\rm{syst}})\times10^{-13}\,\rm{photons\,cm^{-2}\,s^{-1}}$, or approximately $5\%$ of the Crab Nebula. The discovery of VHE from NGC 4278 indicates that the compact, weak radio jet can efficiently accelerate particles and emit TeV photons., Comment: 11 pages, 5 figures

Published
2024

15. LHAASO-KM2A detector simulation using Geant4

Author

Cao, Zhen, Aharonian, F., An, Q., Axikegu, Bai, Y. X., Bao, Y. W., Bastieri, D., Bi, X. J., Bi, Y. J., Cai, J. T., Cao, Q., Cao, W. Y., Cao, Zhe, Chang, J., Chang, J. F., Chen, A. M., Chen, E. S., Chen, Liang, Chen, Lin, Chen, Long, Chen, M. J., Chen, M. L., Chen, Q. H., Chen, S. H., Chen, S. Z., Chen, T. L., Chen, Y., Cheng, N., Cheng, Y. D., Cui, M. Y., Cui, S. W., Cui, X. H., Cui, Y. D., Dai, B. Z., Dai, H. L., Dai, Z. G., Danzengluobu, Dong, X. Q., Duan, K. K., Fan, J. H., Fan, Y. Z., Fang, J., Fang, K., Feng, C. F., Feng, L., Feng, S. H., Feng, X. T., Feng, Y. L., Gabici, S., Gao, B., Gao, C. D., Gao, L. Q., Gao, Q., Gao, W., Gao, W. K., Ge, M. M., Geng, L. S., Giacinti, G., Gong, G. H., Gou, Q. B., Gu, M. H., Guo, F. L., Guo, X. L., Guo, Y. Q., Guo, Y. Y., Han, Y. A., He, H. H., He, H. N., He, J. Y., He, X. B., He, Y., Hor, Y. K., Hou, B. W., Hou, C., Hou, X., Hu, H. B., Hu, Q., Hu, S. C., Huang, D. H., Huang, T. Q., Huang, W. J., Huang, X. T., Huang, X. Y., Huang, Y., Huang, Z. C., Ji, X. L., Jia, H. Y., Jia, K., Jiang, K., Jiang, X. W., Jiang, Z. J., Jin, M., Kang, M. M., Ke, T., Kuleshov, D., Kurinov, K., Li, B. B., Li, Cheng, Li, Cong, Li, D., Li, F., Li, H. B., Li, H. C., Li, H. Y., Li, J., Li, Jian, Li, Jie, Li, K., Li, W. L., Li, X. R., Li, Xin, Li, Y. Z., Li, Zhe, Li, Zhuo, Liang, E. W., Liang, Y. F., Lin, J., Liu, B., Liu, C., Liu, D., Liu, H., Liu, H. D., Liu, J., Liu, J. L., Liu, J. Y., Liu, M. Y., Liu, R. Y., Liu, S. M., Liu, W., Liu, Y., Liu, Y. N., Lu, R., Luo, Q., Lv, H. K., Ma, B. Q., Ma, L. L., Ma, X. H., Mao, J. R., Min, Z., Mitthumsiri, W., Mu, H. J., Nan, Y. C., Neronov, A., Ou, Z. W., Pang, B. Y., Pattarakijwanich, P., Pei, Z. Y., Qi, M. Y., Qi, Y. Q., Qiao, B. Q., Qin, J. J., Ruffolo, D., Sáiz, A., Semikoz, D., Shao, C. Y., Shao, L., Shchegolev, O., Sheng, X. D., Shu, F. W., Song, H. C., Stenkin, Yu. V., Stepanov, V., Su, Y., Sun, Q. N., Sun, X. N., Sun, Z. B., Tam, P. H. T., Tang, Q. W., Tang, Z. B., Tian, W. W., Wang, C., Wang, C. B., Wang, G. W., Wang, H. G., Wang, H. H., Wang, J. C., Wang, K., Wang, L. P., Wang, L. Y., Wang, P. H., Wang, R., Wang, W., Wang, X. G., Wang, X. Y., Wang, Y., Wang, Y. D., Wang, Y. J., Wang, Z. H., Wang, Z. X., Wang, Zhen, Wang, Zheng, Wei, D. M., Wei, J. J., Wei, Y. J., Wen, T., Wu, C. Y., Wu, H. R., Wu, S., Wu, X. F., Wu, Y. S., Xi, S. Q., Xia, J., Xia, J. J., Xiang, G. M., Xiao, D. X., Xiao, G., Xin, G. G., Xin, Y. L., Xing, Y., Xiong, Z., Xu, D. L., Xu, R. F., Xu, R. X., Xu, W. L., Xue, L., Yan, D. H., Yan, J. Z., Yan, T., Yang, C. W., Yang, F., Yang, F. F., Yang, H. W., Yang, J. Y., Yang, L. L., Yang, M. J., Yang, R. Z., Yang, S. B., Yao, Y. H., Yao, Z. G., Ye, Y. M., Yin, L. Q., Yin, N., You, X. H., You, Z. Y., Yu, Y. H., Yuan, Q., Yue, H., Zeng, H. D., Zeng, T. X., Zeng, W., Zha, M., Zhang, B. B., Zhang, F., Zhang, H. M., Zhang, H. Y., Zhang, J. L., Zhang, L. X., Zhang, Li, Zhang, P. F., Zhang, P. P., Zhang, R., Zhang, S. B., Zhang, S. R., Zhang, S. S., Zhang, X., Zhang, X. P., Zhang, Y. F., Zhang, Yi, Zhang, Yong, Zhao, B., Zhao, J., Zhao, L., Zhao, L. Z., Zhao, S. P., Zheng, F., Zheng, J. H., Zhou, B., Zhou, H., Zhou, J. N., Zhou, M., Zhou, P., Zhou, R., Zhou, X. X., Zhu, C. G., Zhu, F. R., Zhu, H., Zhu, K. J., and Zuo, X.

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - High Energy Astrophysical Phenomena
Abstract

KM2A is one of the main sub-arrays of LHAASO, working on gamma ray astronomy and cosmic ray physics at energies above 10 TeV. Detector simulation is the important foundation for estimating detector performance and data analysis. It is a big challenge to simulate the KM2A detector in the framework of Geant4 due to the need to track numerous photons from a large number of detector units (>6000) with large altitude difference (30 m) and huge coverage (1.3 km^2). In this paper, the design of the KM2A simulation code G4KM2A based on Geant4 is introduced. The process of G4KM2A is optimized mainly in memory consumption to avoid memory overffow. Some simpliffcations are used to signiffcantly speed up the execution of G4KM2A. The running time is reduced by at least 30 times compared to full detector simulation. The particle distributions and the core/angle resolution comparison between simulation and experimental data of the full KM2A array are also presented, which show good agreement.

Published
2024
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16. Prognosis of rare pathological primary urethral carcinoma

Author

Abudurexiti M, Wang J, Shao N, Wan FN, Zhu Y, Dai B, and Ye D

Subjects
urethral cancer, Seer, Age, Race, TNM, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Mierxiati Abudurexiti,1,2,* Jun Wang,1,2,* Ning Shao,1,2 Fang-Ning Wan,1,2 Yao Zhu,1,2 Bo Dai,1,2 Ding-Wei Ye1,2 1Department of Urology, Fudan University Shanghai Cancer Center, Shanghai, China; 2Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China *These authors contributed equally to this work Purpose: Urethral carcinoma (UC), as a rare tumor, is not widely studied. There have been no systematic studies of rare pathological types of UC. We conducted this study to further investigate rare pathological types of primary urethral carcinoma (PUC).Materials and methods: We used the population-based Surveillance, Epidemiology, and End Results (SEER) database to evaluate prognostic factors in rare pathological types of PUC. From 1978 to 2015, 2,651 and 257 cases were identified in the SEER database as common and rare pathological types of PUC, respectively. Overall and cancer-specific survival (CSS) times were computed using the Kaplan–Meier method, and the Cox proportional hazards analysis was used to evaluate patient age at diagnosis, gender, race, and TNM stage.Results: The median overall survival (OS) rates were 36 and 59 months for rare and common pathological groups, respectively, and their respective 10-year OS rates were 31.9% and 42.4%, respectively. The median CSS rate was 61 months for the rare pathological group. Through multivariate analysis, it was found that age, race, T stage, and M stage were independent prognostic risk factors for rare pathological type of urethral cancer. In the age group, the HR ratio of patients aged older than 60 years and younger or equal to 60 years was 2.778 (P

Published
2018

17. Measurements of All-Particle Energy Spectrum and Mean Logarithmic Mass of Cosmic Rays from 0.3 to 30 PeV with LHAASO-KM2A

Author

The LHAASO Collaboration, Cao, Zhen, Aharonian, F., An, Q., Axikegu, A., Bai, Y. X., Bao, Y. W., Bastieri, D., Bi, X. J., Bi, Y. J., Cai, J. T., Cao, Q., Cao, W. Y., Cao, Zhe, Chang, J., Chang, J. F., Chen, A. M., Chen, E. S., Chen, Liang, Chen, Lin, Chen, Long, Chen, M. J., Chen, M. L., Chen, Q. H., Chen, S. H., Chen, S. Z., Chen, T. L., Chen, Y., Cheng, N., Cheng, Y. D., Cui, M. Y., Cui, S. W., Cui, X. H., Cui, Y. D., Dai, B. Z., Dai, H. L., Dai, Z. G., Danzengluobu, della Volpe, D., Dong, X. Q., Duan, K. K., Fan, J. H., Fan, Y. Z., Fang, J., Fang, K., Feng, C. F., Feng, L., Feng, S. H., Feng, X. T., Feng, Y. L., Gabici, S., Gao, B., Gao, C. D., Gao, L. Q., Gao, Q., Gao, W., Gao, W. K., Ge, M. M., Geng, L. S., Giacinti, G., Gong, G. H., Gou, Q. B., Gu, M. H., Guo, F. L., Guo, X. L., Guo, Y. Q., Guo, Y. Y., Han, Y. A., He, H. H., He, H. N., He, J. Y., He, X. B., He, Y., Heller, M., Hor, Y. K., Hou, B. W., Hou, C., Hou, X., Hu, H. B., Hu, Q., Hu, S. C., Huang, D. H., Huang, T. Q., Huang, W. J., Huang, X. T., Huang, X. Y., Huang, Y., Huang, Z. C., Ji, X. L., Jia, H. Y., Jia, K., Jiang, K., Jiang, X. W., Jiang, Z. J., Jin, M., Kang, M. M., Ke, T., Kuleshov, D., Kurinov, K., Li, B. B., Li, Cheng, Li, Cong, Li, D., Li, F., Li, H. B., Li, H. C., Li, H. Y., Li, J., Li, Jian, Li, Jie, Li, K., Li, W. L., Li, X. R., Li, Xin, Li, Y. Z., Li, Zhe, Li, Zhuo, Liang, E. W., Liang, Y. F., Lin, S. J., Liu, B., Liu, C., Liu, D., Liu, H., Liu, H. D., Liu, J., Liu, J. L., Liu, J. Y., Liu, M. Y., Liu, R. Y., Liu, S. M., Liu, W., Liu, Y., Liu, Y. N., Lu, R., Luo, Q., Lv, H. K., Ma, B. Q., Ma, L. L., Ma, X. H., Mao, J. R., Min, Z., Mitthumsiri, W., Mu, H. J., Nan, Y. C., Neronov, A., Ou, Z. W., Pang, B. Y., Pattarakijwanich, P., Pei, Z. Y., Qi, M. Y., Qi, Y. Q., Qiao, B. Q., Qin, J. J., Ruffolo, D., Sáiz, A., Semikoz, D., Shao, C. Y., Shao, L., Shchegolev, O., Sheng, X. D., Shu, F. W., Song, H. C., Stenkin, Yu. V., Stepanov, V., Su, Y., Sun, Q. N., Sun, X. N., Sun, Z. B., Tam, P. H. T., Tang, Q. W., Tang, Z. B., Tian, W. W., Wang, C., Wang, C. B., Wang, G. W., Wang, H. G., Wang, H. H., Wang, J. C., Wang, K., Wang, L. P., Wang, L. Y., Wang, P. H., Wang, R., Wang, W., Wang, X. G., Wang, X. Y., Wang, Y., Wang, Y. D., Wang, Y. J., Wang, Z. H., Wang, Z. X., Wang, Zhen, Wang, Zheng, Wei, D. M., Wei, J. J., Wei, Y. J., Wen, T., Wu, C. Y., Wu, H. R., Wu, S., Wu, X. F., Wu, Y. S., Xi, S. Q., Xia, J., Xia, J. J., Xiang, G. M., Xiao, D. X., Xiao, G., Xin, G. G., Xin, Y. L., Xing, Y., Xiong, Z., Xu, D. L., Xu, R. F., Xu, R. X., Xu, W. L., Xue, L., Yan, D. H., Yan, J. Z., Yan, T., Yang, C. W., Yang, F., Yang, F. F., Yang, H. W., Yang, J. Y., Yang, L. L., Yang, M. J., Yang, R. Z., Yang, S. B., Yao, Y. H., Yao, Z. G., Ye, Y. M., Yin, L. Q., Yin, N., You, X. H., You, Z. Y., Yu, Y. H., Yuan, Q., Yue, H., Zeng, H. D., Zeng, T. X., Zeng, W., Zha, M., Zhang, B. B., Zhang, F., Zhang, H. M., Zhang, H. Y., Zhang, J. L., Zhang, L. X., Zhang, Li, Zhang, P. F., Zhang, P. P., Zhang, R., Zhang, S. B., Zhang, S. R., Zhang, S. S., Zhang, X., Zhang, X. P., Zhang, Y. F., Zhang, Yi, Zhang, Yong, Zhao, B., Zhao, J., Zhao, L., Zhao, L. Z., Zhao, S. P., Zheng, F., Zhou, B., Zhou, H., Zhou, J. N., Zhou, M., Zhou, P., Zhou, R., Zhou, X. X., Zhu, C. G., Zhu, F. R., Zhu, H., Zhu, K. J., and Zuo, X.

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

We present the measurements of all-particle energy spectrum and mean logarithmic mass of cosmic rays in the energy range of 0.3-30 PeV using data collected from LHAASO-KM2A between September 2021 and December 2022, which is based on a nearly composition-independent energy reconstruction method, achieving unprecedented accuracy. Our analysis reveals the position of the knee at $3.67 \pm 0.05 \pm 0.15$ PeV. Below the knee, the spectral index is found to be -$2.7413 \pm 0.0004 \pm 0.0050$, while above the knee, it is -$3.128 \pm 0.005 \pm 0.027$, with the sharpness of the transition measured with a statistical error of 2%. The mean logarithmic mass of cosmic rays is almost heavier than helium in the whole measured energy range. It decreases from 1.7 at 0.3 PeV to 1.3 at 3 PeV, representing a 24% decline following a power law with an index of -$0.1200 \pm 0.0003 \pm 0.0341$. This is equivalent to an increase in abundance of light components. Above the knee, the mean logarithmic mass exhibits a power law trend towards heavier components, which is reversal to the behavior observed in the all-particle energy spectrum. Additionally, the knee position and the change in power-law index are approximately the same. These findings suggest that the knee observed in the all-particle spectrum corresponds to the knee of the light component, rather than the medium-heavy components., Comment: 8 pages, 3 figures

Published
2024
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18. Does or did the supernova remnant Cassiopeia A operate as a PeVatron?

Author

Cao, Zhen, Aharonian, F., An, Q., Axikegu, Bai, Y. X., Bao, Y. W., Bastieri, D., Bi, X. J., Bi, Y. J., Cai, J. T., Cao, Q., Cao, W. Y., Cao, Zhe, Chang, J., Chang, J. F., Chen, A. M., Chen, E. S., Chen, Liang, Chen, Lin, Chen, Long, Chen, M. J., Chen, M. L., Chen, Q. H., Chen, S. H., Chen, S. Z., Chen, T. L., Chen, Y., Cheng, N., Cheng, Y. D., Cui, M. Y., Cui, S. W., Cui, X. H., Cui, Y. D., Dai, B. Z., Dai, H. L., Dai, Z. G., Danzengluobu, della Volpe, D., Dong, X. Q., Duan, K. K., Fan, J. H., Fan, Y. Z., Fang, J., Fang, K., Feng, C. F., Feng, L., Feng, S. H., Feng, X. T., Feng, Y. L., Gabici, S., Gao, B., Gao, C. D., Gao, L. Q., Gao, Q., Gao, W., Gao, W. K., Ge, M. M., Geng, L. S., Giacinti, G., Gong, G. H., Gou, Q. B., Gu, M. H., Guo, F. L., Guo, X. L., Guo, Y. Q., Guo, Y. Y., Han, Y. A., He, H. H., He, H. N., He, J. Y., He, X. B., He, Y., Heller, M., Hor, Y. K., Hou, B. W., Hou, C., Hou, X., Hu, H. B., Hu, Q., Hu, S. C., Huang, D. H., Huang, T. Q., Huang, W. J., Huang, X. T., Huang, X. Y., Huang, Y., Huang, Z. C., Ji, X. L., Jia, H. Y., Jia, K., Jiang, K., Jiang, X. W., Jiang, Z. J., Jin, M., Kang, M. M., Ke, T., Kuleshov, D., Kurinov, K., Li, B. B., Li, Cheng, Li, Cong, Li, D., Li, F., Li, H. B., Li, H. C., Li, H. Y., Li, J., Li, Jian, Li, Jie, Li, K., Li, W. L., Li, X. R., Li, Xin, Li, Y. Z., Li, Zhe, Li, Zhuo, Liang, E. W., Liang, Y. F., Lin, S. J., Liu, B., Liu, C., Liu, D., Liu, H., Liu, H. D., Liu, J., Liu, J. L., Liu, J. Y., Liu, M. Y., Liu, R. Y., Liu, S. M., Liu, W., Liu, Y., Liu, Y. N., Lu, R., Luo, Q., Lv, H. K., Ma, B. Q., Ma, L. L., Ma, X. H., Mao, J. R., Min, Z., Mitthumsiri, W., Mu, H. J., Nan, Y. C., Neronov, A., Ou, Z. W., Pang, B. Y., Pattarakijwanich, P., Pei, Z. Y., Qi, M. Y., Qi, Y. Q., Qiao, B. Q., Qin, J. J., Ruffolo, D., Sáiz, A., Semikoz, D., Shao, C. Y., Shao, L., Shchegolev, O., Sheng, X. D., Shu, F. W., Song, H. C., Stenkin, Yu. V., Stepanov, V., Su, Y., Sun, Q. N., Sun, X. N., Sun, Z. B., Tam, P. H. T., Tang, Q. W., Tang, Z. B., Tian, W. W., Wang, C., Wang, C. B., Wang, G. W., Wang, H. G., Wang, H. H., Wang, J. C., Wang, K., Wang, L. P., Wang, L. Y., Wang, P. H., Wang, R., Wang, W., Wang, X. G., Wang, X. Y., Wang, Y., Wang, Y. D., Wang, Y. J., Wang, Z. H., Wang, Z. X., Wang, Zhen, Wang, Zheng, Wei, D. M., Wei, J. J., Wei, Y. J., Wen, T., Wu, C. Y., Wu, H. R., Wu, S., Wu, X. F., Wu, Y. S., Xi, S. Q., Xia, J., Xia, J. J., Xiang, G. M., Xiao, D. X., Xiao, G., Xin, G. G., Xin, Y. L., Xing, Y., Xiong, Z., Xu, D. L., Xu, R. F., Xu, R. X., Xu, W. L., Xue, L., Yan, D. H., Yan, J. Z., Yan, T., Yang, C. W., Yang, F., Yang, F. F., Yang, H. W., Yang, J. Y., Yang, L. L., Yang, M. J., Yang, R. Z., Yang, S. B., Yao, Y. H., Yao, Z. G., Ye, Y. M., Yin, L. Q., Yin, N., You, X. H., You, Z. Y., Yu, Y. H., Yuan, Q., Yue, H., Zeng, H. D., Zeng, T. X., Zeng, W., Zha, M., Zhang, B. B., Zhang, F., Zhang, H. M., Zhang, H. Y., Zhang, J. L., Zhang, L. X., Zhang, Li, Zhang, P. F., Zhang, P. P., Zhang, R., Zhang, S. B., Zhang, S. R., Zhang, S. S., Zhang, X., Zhang, X. P., Zhang, Y. F., Zhang, Yi, Zhang, Yong, Zhao, B., Zhao, J., Zhao, L., Zhao, L. Z., Zhao, S. P., Zheng, F., Zhou, B., Zhou, H., Zhou, J. N., Zhou, M., Zhou, P., Zhou, R., Zhou, X. X., Zhu, C. G., Zhu, F. R., Zhu, H., Zhu, K. J., and Zuo., X.

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

For decades, supernova remnants (SNRs) have been considered the prime sources of Galactic Cosmic rays (CRs). But whether SNRs can accelerate CR protons to PeV energies and thus dominate CR flux up to the knee is currently under intensive theoretical and phenomenological debate. The direct test of the ability of SNRs to operate as CR PeVatrons can be provided by ultrahigh-energy (UHE; $E_\gamma \geq 100$~TeV) $\gamma$-rays. In this context, the historical SNR Cassiopeia A (Cas A) is considered one of the most promising target for UHE observations. This paper presents the observation of Cas A and its vicinity by the LHAASO KM2A detector. The exceptional sensitivity of LHAASO KM2A in the UHE band, combined with the young age of Cas A, enabled us to derive stringent model-independent limits on the energy budget of UHE protons and nuclei accelerated by Cas A at any epoch after the explosion. The results challenge the prevailing paradigm that Cas A-type SNRs are major suppliers of PeV CRs in the Milky Way., Comment: 11 pages, 3 figures, Accepted by the APJL

Published
2023

19. Very high energy gamma-ray emission beyond 10 TeV from GRB 221009A

Author

Cao, Zhen, Aharonian, F., An, Q., Axikegu, A., Bai, Y. X., Bao, Y. W., Bastieri, D., Bi, X. J., Bi, Y. J., Cai, J. T., Cao, Q., Cao, W. Y., Cao, Zhe, Chang, J., Chang, J. F., Chen, A. M., Chen, E. S., Chen, Liang, Chen, Lin, Chen, Long, Chen, M. J., Chen, M. L., Chen, Q. H., Chen, S. H., Chen, S. Z., Chen, T. L., Chen, Y., Cheng, N., Cheng, Y. D., Cui, M. Y., Cui, S. W., Cui, X. H., Cui, Y. D., Dai, B. Z., Dai, H. L., Dai, Z. G., Danzengluobu, della Volpe, D., Dong, X. Q., Duan, K. K., Fan, J. H., Fan, Y. Z., Fang, J., Fang, K., Feng, C. F., Feng, L., Feng, S. H., Feng, X. T., Feng, Y. L., Gabici, S., Gao, B., Gao, C. D., Gao, L. Q., Gao, Q., Gao, W., Gao, W. K., Ge, M. M., Geng, L. S., Giacinti, G., Gong, G. H., Gou, Q. B., Gu, M. H., Guo, F. L., Guo, X. L., Guo, Y. Q., Guo, Y. Y., Han, Y. A., He, H. H., He, H. N., He, J. Y., He, X. B., He, Y., Heller, M., Hor, Y. K., Hou, B. W., Hou, C., Hou, X., Hu, H. B., Hu, Q., Hu, S. C., Huang, D. H., Huang, T. Q., Huang, W. J., Huang, X. T., Huang, X. Y., Huang, Y., Huang, Z. C., Ji, X. L., Jia, H. Y., Jia, K., Jiang, K., Jiang, X. W., Jiang, Z. J., Jin, M., Kang, M. M., Ke, T., Kuleshov, D., Kurinov, K., Li, B. B., Li, Cheng, Li, Cong, Li, D., Li, F., Li, H. B., Li, H. C., Li, H. Y., Li, J., Li, Jian, Li, Jie, Li, K., Li, W. L., Li, X. R., Li, Xin, Li, Y. Z., Li, Zhe, Li, Zhuo, Liang, E. W., Liang, Y. F., Lin, S. J., Liu, B., Liu, C., Liu, D., Liu, H., Liu, H. D., Liu, J., Liu, J. L., Liu, J. Y., Liu, M. Y., Liu, R. Y., Liu, S. M., Liu, W., Liu, Y., Liu, Y. N., Lu, R., Luo, Q., Lv, H. K., Ma, B. Q., Ma, L. L., Ma, X. H., Mao, J. R., Min, Z., Mitthumsiri, W., Mu, H. J., Nan, Y. C., Neronov, A., Ou, Z. W., Pang, B. Y., Pattarakijwanich, P., Pei, Z. Y., Qi, M. Y., Qi, Y. Q., Qiao, B. Q., Qin, J. J., Ruffolo, D., Sáiz, A., Semikoz, D., Shao, C. Y., Shao, L., Shchegolev, O., Sheng, X. D., Shu, F. W., Song, H. C., Stenkin, Yu. V., Stepanov, V., Su, Y., Sun, Q. N., Sun, X. N., Sun, Z. B., Tam, P. H. T., Tang, Q. W., Tang, Z. B., Tian, W. W., Wang, C., Wang, C. B., Wang, G. W., Wang, H. G., Wang, H. H., Wang, J. C., Wang, K., Wang, L. P., Wang, L. Y., Wang, P. H., Wang, R., Wang, W., Wang, X. G., Wang, X. Y., Wang, Y., Wang, Y. D., Wang, Y. J., Wang, Z. H., Wang, Z. X., Wang, Zhen, Wang, Zheng, Wei, D. M., Wei, J. J., Wei, Y. J., Wen, T., Wu, C. Y., Wu, H. R., Wu, S., Wu, X. F., Wu, Y. S., Xi, S. Q., Xia, J., Xia, J. J., Xiang, G. M., Xiao, D. X., Xiao, G., Xin, G. G., Xin, Y. L., Xing, Y., Xiong, Z., Xu, D. L., Xu, R. F., Xu, R. X., Xu, W. L., Xue, L., Yan, D. H., Yan, J. Z., Yan, T., Yang, C. W., Yang, F., Yang, F. F., Yang, H. W., Yang, J. Y., Yang, L. L., Yang, M. J., Yang, R. Z., Yang, S. B., Yao, Y. H., Yao, Z. G., Ye, Y. M., Yin, L. Q., Yin, N., You, X. H., You, Z. Y., Yu, Y. H., Yuan, Q., Yue, H., Zeng, H. D., Zeng, T. X., Zeng, W., Zha, M., Zhang, B. B., Zhang, F., Zhang, H. M., Zhang, H. Y., Zhang, J. L., Zhang, L. X., Zhang, Li, Zhang, P. F., Zhang, P. P., Zhang, R., Zhang, S. B., Zhang, S. R., Zhang, S. S., Zhang, X., Zhang, X. P., Zhang, Y. F., Zhang, Yi, Zhang, Yong, Zhao, B., Zhao, J., Zhao, L., Zhao, L. Z., Zhao, S. P., Zheng, F., Zhou, B., Zhou, H., Zhou, J. N., Zhou, M., Zhou, P., Zhou, R., Zhou, X. X., Zhu, C. G., Zhu, F. R., Zhu, H., Zhu, K. J., and Zuo, X.

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

The highest energy gamma-rays from gamma-ray bursts (GRBs) have important implications for their radiation mechanism. Here we report for the first time the detection of gamma-rays up to 13 TeV from the brightest GRB 221009A by the Large High Altitude Air-shower Observatory (LHAASO). The LHAASO-KM2A detector registered more than 140 gamma-rays with energies above 3 TeV during 230$-$900s after the trigger. The intrinsic energy spectrum of gamma-rays can be described by a power-law after correcting for extragalactic background light (EBL) absorption. Such a hard spectrum challenges the synchrotron self-Compton (SSC) scenario of relativistic electrons for the afterglow emission above several TeV. Observations of gamma-rays up to 13 TeV from a source with a measured redshift of z=0.151 hints more transparency in intergalactic space than previously expected. Alternatively, one may invoke new physics such as Lorentz Invariance Violation (LIV) or an axion origin of very high energy (VHE) signals., Comment: 49pages, 11figures

Published
2023
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20. The First LHAASO Catalog of Gamma-Ray Sources

Author

Cao, Zhen, Aharonian, F., An, Q., Axikegu, Bai, Y. X., Bao, Y. W., Bastieri, D., Bi, X. J., Bi, Y. J., Cai, J. T., Cao, Q., Cao, W. Y., Cao, Zhe, Chang, J., Chang, J. F., Chen, A. M., Chen, E. S., Chen, Liang, Chen, Lin, Chen, Long, Chen, M. J., Chen, M. L., Chen, Q. H., Chen, S. H., Chen, S. Z., Chen, T. L., Chen, Y., Cheng, N., Cheng, Y. D., Cui, M. Y., Cui, S. W., Cui, X. H., Cui, Y. D., Dai, B. Z., Dai, H. L., Dai, Z. G., Danzengluobu, della Volpe, D., Dong, X. Q., Duan, K. K., Fan, J. H., Fan, Y. Z., Fang, J., Fang, K., Feng, C. F., Feng, L., Feng, S. H., Feng, X. T., Feng, Y. L., Gabici, S., Gao, B., Gao, C. D., Gao, L. Q., Gao, Q., Gao, W., Gao, W. K., Ge, M. M., Geng, L. S., Giacinti, G., Gong, G. H., Gou, Q. B., Gu, M. H., Guo, F. L., Guo, X. L., Guo, Y. Q., Guo, Y. Y., Han, Y. A., He, H. H., He, H. N., He, J. Y., He, X. B., He, Y., Heller, M., Hor, Y. K., Hou, B. W., Hou, C., Hou, X., Hu, H. B., Hu, Q., Hu, S. C., Huang, D. H., Huang, T. Q., Huang, W. J., Huang, X. T., Huang, X. Y., Huang, Y., Huang, Z. C., Ji, X. L., Jia, H. Y., Jia, K., Jiang, K., Jiang, X. W., Jiang, Z. J., Jin, M., Kang, M. M., Ke, T., Kuleshov, D., Kurinov, K., Li, B. B., Li, Cheng, Li, Cong, Li, D., Li, F., Li, H. B., Li, H. C., Li, H. Y., Li, J., Li, Jian, Li, Jie, Li, K., Li, W. L., Li, X. R., Li, Xin, Li, Y. Z., Li, Zhe, Li, Zhuo, Liang, E. W., Liang, Y. F., Lin, S. J., Liu, B., Liu, C., Liu, D., Liu, H., Liu, H. D., Liu, J., Liu, J. L., Liu, J. Y., Liu, M. Y., Liu, R. Y., Liu, S. M., Liu, W., Liu, Y., Liu, Y. N., Lu, R., Luo, Q., Lv, H. K., Ma, B. Q., Ma, L. L., Ma, X. H., Mao, J. R., Min, Z., Mitthumsiri, W., Mu, H. J., Nan, Y. C., Neronov, A., Ou, Z. W., Pang, B. Y., Pattarakijwanich, P., Pei, Z. Y., Qi, M. Y., Qi, Y. Q., Qiao, B. Q., Qin, J. J., Ruffolo, D., Sáiz, A., Semikoz, D., Shao, C. Y., Shao, L., Shchegolev, O., Sheng, X. D., Shu, F. W., Song, H. C., Stenkin, Yu. V., Stepanov, V., Su, Y., Sun, Q. N., Sun, X. N., Sun, Z. B., Tam, P. H. T., Tang, Q. W., Tang, Z. B., Tian, W. W., Wang, C., Wang, C. B., Wang, G. W., Wang, H. G., Wang, H. H., Wang, J. C., Wang, K., Wang, L. P., Wang, L. Y., Wang, P. H., Wang, R., Wang, W., Wang, X. G., Wang, X. Y., Wang, Y., Wang, Y. D., Wang, Y. J., Wang, Z. H., Wang, Z. X., Wang, Zhen, Wang, Zheng, Wei, D. M., Wei, J. J., Wei, Y. J., Wen, T., Wu, C. Y., Wu, H. R., Wu, S., Wu, X. F., Wu, Y. S., Xi, S. Q., Xia, J., Xia, J. J., Xiang, G. M., Xiao, D. X., Xiao, G., Xin, G. G., Xin, Y. L., Xing, Y., Xiong, Z., Xu, D. L., Xu, R. F., Xu, R. X., Xu, W. L., Xue, L., Yan, D. H., Yan, J. Z., Yan, T., Yang, C. W., Yang, F., Yang, F. F., Yang, H. W., Yang, J. Y., Yang, L. L., Yang, M. J., Yang, R. Z., Yang, S. B., Yao, Y. H., Yao, Z. G., Ye, Y. M., Yin, L. Q., Yin, N., You, X. H., You, Z. Y., Yu, Y. H., Yuan, Q., Yue, H., Zeng, H. D., Zeng, T. X., Zeng, W., Zha, M., Zhang, B. B., Zhang, F., Zhang, H. M., Zhang, H. Y., Zhang, J. L., Zhang, L. X., Zhang, Li, Zhang, P. F., Zhang, P. P., Zhang, R., Zhang, S. B., Zhang, S. R., Zhang, S. S., Zhang, X., Zhang, X. P., Zhang, Y. F., Zhang, Yi, Zhang, Yong, Zhao, B., Zhao, J., Zhao, L., Zhao, L. Z., Zhao, S. P., Zheng, F., Zhou, B., Zhou, H., Zhou, J. N., Zhou, M., Zhou, P., Zhou, R., Zhou, X. X., Zhu, C. G., Zhu, F. R., Zhu, H., Zhu, K. J., and Zuo., X.

Subjects
Astrophysics - High Energy Astrophysical Phenomena, High Energy Physics - Phenomenology
Abstract

We present the first catalog of very-high energy and ultra-high energy gamma-ray sources detected by the Large High Altitude Air Shower Observatory (LHAASO). The catalog was compiled using 508 days of data collected by the Water Cherenkov Detector Array (WCDA) from March 2021 to September 2022 and 933 days of data recorded by the Kilometer Squared Array (KM2A) from January 2020 to September 2022. This catalog represents the main result from the most sensitive large coverage gamma-ray survey of the sky above 1 TeV, covering declination from $-$20$^{\circ}$ to 80$^{\circ}$. In total, the catalog contains 90 sources with an extended size smaller than $2^\circ$ and a significance of detection at $> 5\sigma$. Based on our source association criteria, 32 new TeV sources are proposed in this study. Among the 90 sources, 43 sources are detected with ultra-high energy ($E > 100$ TeV) emission at $> 4\sigma$ significance level. We provide the position, extension, and spectral characteristics of all the sources in this catalog., Comment: 40 pages, 13 figures, 4 tables

Published
2023
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21. Measurement of ultra-high-energy diffuse gamma-ray emission of the Galactic plane from 10 TeV to 1 PeV with LHAASO-KM2A

Author

Cao, Zhen, Aharonian, F., An, Q., Axikegu, Bai, Y. X., Bao, Y. W., Bastieri, D., Bi, X. J., Bi, Y. J., Cai, J. T., Cao, Q., Cao, W. Y., Cao, Zhe, Chang, J., Chang, J. F., Chen, A. M., Chen, E. S., Chen, Liang, Chen, Lin, Chen, Long, Chen, M. J., Chen, M. L., Chen, Q. H., Chen, S. H., Chen, S. Z., Chen, T. L., Chen, Y., Cheng, N., Cheng, Y. D., Cui, M. Y., Cui, S. W., Cui, X. H., Cui, Y. D., Dai, B. Z., Dai, H. L., Dai, Z. G., Danzengluobu, della Volpe, D., Dong, X. Q., Duan, K. K., Fan, J. H., Fan, Y. Z., Fang, J., Fang, K., Feng, C. F., Feng, L., Feng, S. H., Feng, X. T., Feng, Y. L., Gabici, S., Gao, B., Gao, C. D., Gao, L. Q., Gao, Q., Gao, W., Gao, W. K., Ge, M. M., Geng, L. S., Giacinti, G., Gong, G. H., Gou, Q. B., Gu, M. H., Guo, F. L., Guo, X. L., Guo, Y. Q., Guo, Y. Y., Han, Y. A., He, H. H., He, H. N., He, J. Y., He, X. B., He, Y., Heller, M., Hor, Y. K., Hou, B. W., Hou, C., Hou, X., Hu, H. B., Hu, Q., Hu, S. C., Huang, D. H., Huang, T. Q., Huang, W. J., Huang, X. T., Huang, X. Y., Huang, Y., Huang, Z. C., Ji, X. L., Jia, H. Y., Jia, K., Jiang, K., Jiang, X. W., Jiang, Z. J., Jin, M., Kang, M. M., Ke, T., Kuleshov, D., Kurinov, K., Li, B. B., Li, Cheng, Li, Cong, Li, D., Li, F., Li, H. B., Li, H. C., Li, H. Y., Li, J., Li, Jian, Li, Jie, Li, K., Li, W. L., Li, X. R., Li, Xin, Li, Y. Z., Li, Zhe, Li, Zhuo, Liang, E. W., Liang, Y. F., Lin, S. J., Liu, B., Liu, C., Liu, D., Liu, H., Liu, H. D., Liu, J., Liu, J. L., Liu, J. Y., Liu, M. Y., Liu, R. Y., Liu, S. M., Liu, W., Liu, Y., Liu, Y. N., Lu, R., Luo, Q., Lv, H. K., Ma, B. Q., Ma, L. L., Ma, X. H., Mao, J. R., Min, Z., Mitthumsiri, W., Mu, H. J., Nan, Y. C., Neronov, A., Ou, Z. W., Pang, B. Y., Pattarakijwanich, P., Pei, Z. Y., Qi, M. Y., Qi, Y. Q., Qiao, B. Q., Qin, J. J., Ruffolo, D., Saiz, A., Semikoz, D., Shao, C. Y., Shao, L., Shchegolev, O., Sheng, X. D., Shu, F. W., Song, H. C., Stenkin, Yu. V., Stepanov, V., Su, Y., Sun, Q. N., Sun, X. N., Sun, Z. B., Tam, P. H. T., Tang, Q. W., Tang, Z. B., Tian, W. W., Wang, C., Wang, C. B., Wang, G. W., Wang, H. G., Wang, H. H., Wang, J. C., Wang, K., Wang, L. P., Wang, L. Y., Wang, P. H., Wang, R., Wang, W., Wang, X. G., Wang, X. Y., Wang, Y., Wang, Y. D., Wang, Y. J., Wang, Z. H., Wang, Z. X., Wang, Zhen, Wang, Zheng, Wei, D. M., Wei, J. J., Wei, Y. J., Wen, T., Wu, C. Y., Wu, H. R., Wu, S., Wu, X. F., Wu, Y. S., Xi, S. Q., Xia, J., Xia, J. J., Xiang, G. M., Xiao, D. X., Xiao, G., Xin, G. G., Xin, Y. L., Xing, Y., Xiong, Z., Xu, D. L., Xu, R. F., Xu, R. X., Xu, W. L., Xue, L., Yan, D. H., Yan, J. Z., Yan, T., Yang, C. W., Yang, F., Yang, F. F., Yang, H. W., Yang, J. Y., Yang, L. L., Yang, M. J., Yang, R. Z., Yang, S. B., Yao, Y. H., Yao, Z. G., Ye, Y. M., Yin, L. Q., Yin, N., You, X. H., You, Z. Y., Yu, Y. H., Yuan, Q., Yue, H., Zeng, H. D., Zeng, T. X., Zeng, W., Zha, M., Zhang, B. B., Zhang, F., Zhang, H. M., Zhang, H. Y., Zhang, J. L., Zhang, L. X., Zhang, Li, Zhang, P. F., Zhang, P. P., Zhang, R., Zhang, S. B., Zhang, S. R., Zhang, S. S., Zhang, X., Zhang, X. P., Zhang, Y. F., Zhang, Yi, Zhang, Yong, Zhao, B., Zhao, J., Zhao, L., Zhao, L. Z., Zhao, S. P., Zheng, F., Zhou, B., Zhou, H., Zhou, J. N., Zhou, M., Zhou, P., Zhou, R., Zhou, X. X., Zhu, C. G., Zhu, F. R., Zhu, H., Zhu, K. J., and Zuo, X.

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

The diffuse Galactic $\gamma$-ray emission, mainly produced via interactions between cosmic rays and the interstellar medium and/or radiation field, is a very important probe of the distribution, propagation, and interaction of cosmic rays in the Milky Way. In this work we report the measurements of diffuse $\gamma$-rays from the Galactic plane between 10 TeV and 1 PeV energies, with the square kilometer array of the Large High Altitude Air Shower Observatory (LHAASO). Diffuse emissions from the inner ($15^{\circ}10$~TeV). The energy spectrum in the inner Galaxy regions can be described by a power-law function with an index of $-2.99\pm0.04$, which is different from the curved spectrum as expected from hadronic interactions between locally measured cosmic rays and the line-of-sight integrated gas content. Furthermore, the measured flux is higher by a factor of $\sim3$ than the prediction. A similar spectrum with an index of $-2.99\pm0.07$ is found in the outer Galaxy region, and the absolute flux for $10\lesssim E\lesssim60$ TeV is again higher than the prediction for hadronic cosmic ray interactions. The latitude distributions of the diffuse emission are consistent with the gas distribution, while the longitude distributions show clear deviation from the gas distribution. The LHAASO measurements imply that either additional emission sources exist or cosmic ray intensities have spatial variations., Comment: 12 pages, 8 figures, 5 tables; accepted for publication in Physical Review Letters; source mask file provided as ancillary file

Published
2023
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23. Flux Variations of Cosmic Ray Air Showers Detected by LHAASO-KM2A During a Thunderstorm on 10 June 2021

Author

LHAASO Collaboration, Aharonian, F., An, Q., Axikegu, Bai, L. X., Bai, Y. X., Bao, Y. W., Bastieri, D., Bi, X. J., Bi, Y. J., Cai, J. T., Cao, Zhe, Cao, Zhen, Chang, J., Chang, J. F., Chen, E. S., Chen, Liang, Chen, Long, Chen, M. J., Chen, M. L., Chen, S. H., Chen, S. Z., Chen, T. L., Chen, X. J., Chen, Y., Cheng, H. L., Cheng, N., Cheng, Y. D., Cui, S. W., Cui, X. H., Cui, Y. D., Dai, B. Z., Dai, H. L., Dai, Z. G., Danzengluobu, della Volpe, D., Duan, K. K., Fan, J. H., Fan, Y. Z., Fan, Z. X., Fang, J., Fang, K., Feng, C. F., Feng, L., Feng, S. H., Feng, X. T., Feng, Y. L., Gao, B., Gao, C. D., Gao, L. Q., Gao, Q., Gao, W., Gao, W. K., Ge, M. M., Geng, L. S., Gong, G. H., Gou, Q. B., Gu, M. H., Gu, F. L., Guo, J. G., Guo, X. L., Guo, Y. Q., Guo, Y. Y., Han, Y. A., He, H. H., He, H. N., He, S. L., He, X. B., He, Y., Heller, M., Hor, Y. K., Hou, C., Hou, X., Hu, H. B., Hu, Q., Hu, S., Hu, S. C., Hu, X. J., Huang, D. H., Huang, W. H., Huang, X. T., Huang, X. Y., Huang, Y., Huang, Z. C., Ji, X. L., Jia, H. Y., Jia, K., Jiang, K., Jiang, Z. J., Jin, M., Kang, M. M., Ke, T., Kuleshov, D., Li, B. B., Li, Cheng, Li, Cong, Li, F., Li, H. B., Li, H. C., Li, H. Y., Li, J., Li, Jian, Li, Jie, Li, K., Li, W. L., Li, X. R., Li, Xin, Li, Y. Z., Li, Zhe, Li, Zhuo, Liang, E. W., Liang, Y. F., Lin, S. J., Liu, 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., Long, W. J., Lu, R., Luo, Q., Lv, H. K., Ma, B. Q., Ma, L. L., Ma, X. H., Mao, J. R., Masood, A., Min, Z., Mitthumsiri, W., Nan, Y. C., Ou, Z. W., Pang, B. Y., Pattarakijwanich, P., Pei, Z. Y., Qi, M. Y., Qi, Y. Q., Qiao, B. Q., Qin, J. J., Ruffolo, D., Sáiz, A., Shao, C. Y., Shao, L., Shchegolev, O., Sheng, X. D., Shi, J. Y., Song, H. C., Stenkin, Yu. V., Stepanov, V., Su, Y., Sun, Q. N., Sun, X. N., Sun, Z. B., Tam, P. H. T., Tang, Z. B., Tian, W. W., Wang, B. D., Wang, C., Wang, H., Wang, H. G., Wang, J. C., Wang, J. S., Wang, L. P., Wang, L. Y., Wang, R., Wang, R. N., Wang, W., Wang, X. G., Wang, X. Y., Wang, Y., Wang, Y. D., Wang, Y. J., Wang, Y. P., Wang, Z. H. Wang. Z. X., Wang, Zhen, Wang, Zheng, Wei, D. M., Wei, J. J., Wei, Y. J., Wen, T., Wu, C. Y., Wu, H. R., Wu, S., Wu, X. F., W, Y. S., Xi, S. Q., Xia, J., Xia, J. J., Xiang, G. M., Xiao, D. X., Xiao, G., Xin, G. G., Xin, Y. L., Xing, Y., Xiong, Z., Xu, D. L., Xu, R. X., Xue, L., Yan, D. H., Yan, J. Z., Yang, C. W., Yang, F. F., Yang, H. W., Yang, J. Y., Yang, L. L., Yang, M. J., Yang, R. Z., Yang, S. B., Yao, Y. H., Yao, Z. G., Ye, Y. M., Yin, L. Q., Yin, N., You, X. H., You, Z. Y., Yu, Y. H., Yuan, Q., Yue, H., Zeng, H. D., Zeng, T. X., Zeng, W., Zeng, Z. K., Zha, M., Zhai, X. X., Zhang, B. B., Zhang, F., Zhang, H. M., Zhang, H. Y., Zhang, J. L., Zhang, L. X., Zhang, Li, Zhang, Lu, Zhang, P. F., Zhang, P. P., Zhang, R., Zhang, S. B., Zhang, S. R., Zhang, S. S., Zhang, X., Zhang, X. P., Zhang, Y. F., Zhang, Y. L., Zhang, Yi, Zhang, Yong, Zhao, B., Zhao, J., Zhao, L., Zhao, L. Z., Zhao, S. P., Zheng, F., Zheng, Y., Zhou, B., Zhou, H., Zhou, J. N., Zhou, P., Zhou, R., Zhou, X. X., Zhu, C. G., Zhu, F. R., Zhu, H., Zhu, K. J., and Zuo, X.

Subjects
Astrophysics - High Energy Astrophysical Phenomena, High Energy Physics - Experiment
Abstract

The Large High Altitude Air Shower Observatory (LHAASO) has three sub-arrays, KM2A, WCDA and WFCTA. The flux variations of cosmic ray air showers were studied by analyzing the KM2A data during the thunderstorm on 10 June 2021. The number of shower events that meet the trigger conditions increases significantly in atmospheric electric fields, with maximum fractional increase of 20%. The variations of trigger rates (increases or decreases) are found to be strongly dependent on the primary zenith angle. The flux of secondary particles increases significantly, following a similar trend with that of the shower events. To better understand the observed behavior, Monte Carlo simulations are performed with CORSIKA and G4KM2A (a code based on GEANT4). We find that the experimental data (in saturated negative fields) are in good agreement with simulations, assuming the presence of a uniform upward electric field of 700 V/cm with a thickness of 1500 m in the atmosphere above the observation level. Due to the acceleration/deceleration and deflection by the atmospheric electric field, the number of secondary particles with energy above the detector threshold is modified, resulting in the changes in shower detection rate., Comment: 18 pages, 11 figures

Published
2022
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25. Peta-electron volt gamma-ray emission from the Crab Nebula

Author

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

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

The Crab pulsar and the surrounding nebula powered by the pulsar's rotational energy through the formation and termination of a relativistic electron-positron wind is a bright source of gamma-rays carrying crucial information about this complex conglomerate. We report the detection of $\gamma$-rays with a spectrum showing gradual steepening over three energy decades, from $5\times 10^{-4}$ to $1.1$ petaelectronvolt (PeV). The ultra-high-energy photons exhibit the presence of a PeV electron accelerator (a pevatron) with an acceleration rate exceeding 15% of the absolute theoretical limit. Assuming that unpulsed $\gamma$-rays are produced at the termination of the pulsar's wind, we constrain the pevatron's size, between $0.025$ and $0.1$ pc, and the magnetic field $\approx 110 \mu$G. The production rate of PeV electrons, $2.5 \times 10^{36}$ erg $\rm s^{-1}$, constitutes 0.5% of the pulsar's spin-down luminosity, although we do not exclude a non-negligible contribution of PeV protons to the production of the highest energy $\gamma$-rays., Comment: 43 pages, 13 figures, 2 tables; Published in Science

Published
2021
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26. Tensor force role in $\beta$ decays analyzed within the Gogny-interaction shell model

Author

Dai, B., Hu, B. S., Ma, Y. Z., Li, J. G., Wang, S. M., Johnson, C. W., and Xu, F. R.

Subjects
Nuclear Theory, Nuclear Experiment
Abstract

Background: The half-life of the famous $^{14}$C $\beta$ decay is anomalously long, with different mechanisms: the tensor force, cross-shell mixing, and three-body forces, proposed to explain the cancellations that lead to a small transition matrix element. Purpose: We revisit and analyze the role of the tensor force for the $\beta$ decay of $^{14}$C as well as of neighboring isotopes. Methods: We add a tensor force to the Gogny interaction, and derive an effective Hamiltonian for shell-model calculations. The calculations were carried out in a $p$-$sd$ model space to investigate cross-shell effects. Furthermore, we decompose the wave functions according to the total orbital angular momentum $L$ in order to analyze the effects of the tensor force and cross-shell mixing. Results: The inclusion of the tensor force significantly improves the shell-model calculations of the $\beta$-decay properties of carbon isotopes. In particular, the anomalously slow $\beta$ decay of $^{14}$C can be explained by the isospin $T=0$ part of the tensor force, which changes the components of $^{14}$N with the orbital angular momentum $L=0,1$, and results in a dramatic suppression of the Gamow-Teller transition strength. At the same time, the description of other nearby $\beta$ decays are improved. Conclusions: Decomposition of wave function into $L$ components illuminates how the tensor force modifies nuclear wave functions, in particular suppression of $\beta$-decay matrix elements. Cross-shell mixing also has a visible impact on the $\beta$-decay strength. Inclusion of the tensor force does not seem to significantly change, however, binding energies of the nuclei within the phenomenological interaction., Comment: 8 Pages,7 Figures

Published
2021
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27. Calibration of the Air Shower Energy Scale of the Water and Air Cherenkov Techniques in the LHAASO experiment

Author

Aharonian, F., An, Q., Axikegu, Bai, L. X., Bai, Y. X., Bao, Y. W., Bastieri, D., Bi, X. J., Bi, Y. J., Cai, H., Cai, J. T., Cao, Z. Cao Z., Chang, J., Chang, J. F., Chang, X. C., Chen, B. M., Chen, J., 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., Cheng, N., Cheng, Y. D., Cui, S. W., Cui, X. H., Cui, Y. D., Dai, B. Z., Dai, H. L., Dai, Z. G., Danzengluobu, della Volpe, D., Piazzoli, B. DEttorre, Dong, X. J., Fan, J. H., Fan, Y. Z., Fan, Z. X., Fang, J., Fang, K., Feng, C. F., Feng, L., Feng, S. H., Feng, Y. L., Gao, B., Gao, C. D., Gao, Q., Gao, W., Ge, M. M., Geng, L. S., Gong, G. H., Gou, Q. B., Gu, M. H., Guo, J. G., Guo, X. L., Guo, Y. Q., Guo, Y. Y., Han, Y. A., He, H. H., He, H. N., He, J. C., He, S. L., He, X. B., He, Y., Heller, M., Hor, Y. K., Hou, C., Hou, X., Hu, H. B., Hu, S., Hu, S. C., Hu, X. J., Huang, D. H., Huang, Q. L., Huang, W. H., Huang, X. T., Huang, Z. C., Ji, F., Ji, X. L., Jia, H. Y., Jiang, K., Jiang, Z. J., Jin, C., Kuleshov, D., Levochkin, K., Li, B. B., Li, C., Li, F., Li, H. B., Li, H. C., Li, H. Y., Li, J., Li, K., Li, W. L., Li, X., Li, X. R., Li, Y., Li, Y. Z., Li, Z., Liang, E. W., Liang, Y. F., Lin, S. J., Liu, 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., Long, W. J., Lu, R., Lv, H. K., Ma, B. Q., Ma, L. L., Ma, X. H., Mao, J. R., Masood, A., Mitthumsiri, W., Montaruli, T., Nan, Y. C., Pang, B. Y., Pattarakijwanich, P., Pei, Z. Y., Qi, M. Y., Ruffolo, D., Rulev, V., Saiz, A., Shao, L., Shchegolev, O., Sheng, X. D., Shi, J. R., Song, H. C., Stenkin, Yu. V., Stepanov, V., Sun, Q. N., Sun, X. N., Sun, Z. B., Tam, P. H. T., Tang, Z. B., Tian, W. W., Wang, 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, X. J., Wang, X. Y., Wang, Y. D., Wang, Y. J., Wang, Y. P., Wang, Z., Wang, Z. H., Wang, Z. X., Wei, D. M., Wei, J. J., Wei, Y. J., Wen, T., Wu, C. Y., Wu, H. R., Wu, S., Wu, X., Wu, X. F., Xi, S. Q., Xia, J., Xia, J. J., Xiang, G. M., Xiao, G., Xiao, H. B., Xin, G. G., Xin, Y. L., Xing, Y., Xu, D. L., Xu, R. X., Xue, L., Yan, D. H., Yang, C. W., Yang, F. F., Yang, J. Y., Yang, L. L., Yang, M. J., Yang, R. Z., Yang, S. B., Yao, Y. H., Yao, Z. G., Ye, Y. M., Yin, L. Q., Yin, N., You, X. H., You, Z. Y., Yu, Y. H., Yuan, Q., Zeng, H. D., Zeng, T. X., Zeng, W., Zeng, Z. K., Zha, M., Zhai, X. X., Zhang, B. B., Zhang, H. M., Zhang, H. Y., Zhang, J. L., Zhang, J. W., Zhang, L., Zhang, L. X., Zhang, P. F., Zhang, P. P., Zhang, R., Zhang, S. R., Zhang, S. S., Zhang, X., Zhang, X. P., Zhang, Y., Zhang, Y. F., Zhang, Y. L., Zhao, B., Zhao, J., Zhao, L., Zhao, L. Z., Zhao, S. P., Zheng, F., Zheng, Y., Zhou, B., Zhou, H., Zhou, J. N., Zhou, P., Zhou, R., Zhou, X. X., Zhu, C. G., Zhu, F. R., Zhu, H., Zhu, K. J., and Zuo, X.

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - High Energy Astrophysical Phenomena
Abstract

The Wide Field-of-View Cherenkov Telescope Array (WFCTA) and the Water Cherenkov Detector Arrays (WCDA) of LHAASO are designed to work in combination for measuring the energy spectra of various cosmic ray species over a very wide energy range from a few TeV to 10 PeV. The energy calibration of WCDA can be achieved with a proven technique of measuring the westward shift of the Moon shadow of galactic cosmic rays due to the geomagnetic field. This deflection angle $\Delta$ is inversely proportional to the energy of the cosmic rays. The precise measurements of the shifts by WCDA allows us to calibrate its energy scale for energies as high as 35 TeV. The energy scale measured by WCDA can be used to cross calibrate the energy reconstructed by WFCTA, which spans the whole energy range up to 10 PeV. In this work, we will demonstrate the feasibility of the method using the data collected from April 2019 to January 2020 by the WFCTA array and WCDA-1 detector, the first of the three water Cherenkov ponds, already commissioned at LHAASO site.

Published
2021
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28. Construction and On-site Performance of the LHAASO WFCTA Camera

Author

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

Subjects
Physics - Instrumentation and Detectors, Astrophysics - Instrumentation and Methods for Astrophysics, High Energy Physics - Experiment
Abstract

The focal plane camera is the core component of the Wide Field-of-view Cherenkov/fluorescence Telescope Array (WFCTA) of the Large High-Altitude Air Shower Observatory (LHAASO). Because of the capability of working under moonlight without aging, silicon photomultipliers (SiPM) have been proven to be not only an alternative but also an improvement to conventional photomultiplier tubes (PMT) in this application. Eighteen SiPM-based cameras with square light funnels have been built for WFCTA. The telescopes have collected more than 100 million cosmic ray events and preliminary results indicate that these cameras are capable of working under moonlight. The characteristics of the light funnels and SiPMs pose challenges (e.g. dynamic range, dark count rate, assembly techniques). In this paper, we present the design features, manufacturing techniques and performances of these cameras. Finally, the test facilities, the test methods and results of SiPMs in the cameras are reported here., Comment: 45 pages, 21 figures, article

Published
2020
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29. Self-Supervised Domain Adaptation with Consistency Training

Author

Xiao, L., Xu, J., Zhao, D., Wang, Z., Wang, L., Nie, Y., and Dai, B.

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

We consider the problem of unsupervised domain adaptation for image classification. To learn target-domain-aware features from the unlabeled data, we create a self-supervised pretext task by augmenting the unlabeled data with a certain type of transformation (specifically, image rotation) and ask the learner to predict the properties of the transformation. However, the obtained feature representation may contain a large amount of irrelevant information with respect to the main task. To provide further guidance, we force the feature representation of the augmented data to be consistent with that of the original data. Intuitively, the consistency introduces additional constraints to representation learning, therefore, the learned representation is more likely to focus on the right information about the main task. Our experimental results validate the proposed method and demonstrate state-of-the-art performance on classical domain adaptation benchmarks. Code is available at https://github.com/Jiaolong/ss-da-consistency., Comment: ICPR 2020

Published
2020

30. The observation of the Crab Nebula with LHAASO-KM2A for the performance study

Author

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

Subjects
Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Astrophysics of Galaxies, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract

As a sub-array of the Large High Altitude Air Shower Observatory (LHAASO), KM2A is mainly designed to cover a large fraction of the northern sky to hunt for gamma-ray sources at energies above 10 TeV. Even though the detector construction is still underway, a half of the KM2A array has been operating stably since the end of 2019. In this paper, we present the pipeline of KM2A data analysis and the first observation on the Crab Nebula, a standard candle in very high energy gamma-ray astronomy. We detect gamma-ray signals from the Crab Nebula in both energy ranges of 10$-$100 TeV and $>$100 TeV with high significance, by analyzing the KM2A data of 136 live days between December 2019 and May 2020. With the observations, we test the detector performance including angular resolution, pointing accuracy and cosmic ray background rejection power. The energy spectrum of the Crab Nebula in the energy range 10-250 TeV fits well with a single power-law function dN/dE =(1.13$\pm$0.05$_{stat}$$\pm$0.08$_{sys}$)$\times$10$^{-14}$$\cdot$(E/20TeV)$^{-3.09\pm0.06_{stat}\pm0.02_{sys}}$ cm$^{-2}$ s$^{-1}$ TeV$^{-1}$. It is consistent with previous measurements by other experiments. This opens a new window of gamma-ray astronomy above 0.1 PeV through which ultrahigh-energy gamma-ray new phenomena, such as cosmic PeVatrons, might be discovered., Comment: 13 pages, 15 figures,submitted to CPC

Published
2020
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31. Compact Radio Emission from Nearby Galaxies with Mid-infrared Nuclear Outbursts

Author

Dai, B. B., Shu, X. W., Jiang, N., Dou, L. M., Liu, D. Z., Yang, C. W., Zhang, F. B., and Wang, T. G.

Subjects
Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Astrophysics of Galaxies
Abstract

We present 5.5 GHz observations with the VLA of a sample of nearby galaxies with energetic nuclear outbursts at mid-infrared (MIR) bands. These observations reach a uniform depth down to a median rms of ~10 uJy, representing one of most sensitive searches for radio emission associated with nuclear transients. We detect radio emission in 12 out of 16 galaxies at a level of >5sigma, corresponding to a detection rate of 75%. Such a high detection is remarkably different from previous similar searches in stellar tidal disruption events. The radio emission is compact and not resolved for the majority of sources on scales of ~<0.5" (<0.9 kpc at z<0.1). We find the possibility of the star-formation contributing to the radio emission is low, but an AGN origin remains a plausible scenario, especially for sources that show evidence of AGN activity in their optical spectra. If the detections could represent radio emission associated with nuclear transient phenomenon such as jet or outflow, we use the blast wave model by analogy with the GRB afterglows to describe the evolution of radio light curves. In this context, the observations are consistent with a decelerating jet with an energy of ~10^{51-52} erg viewed at 30\degree-60\degree off-axis at later times, suggesting that powerful jets may be ubiquitous among MIR-burst galaxies. Future continuous monitoring observations will be crucial to decipher the origin of radio emission through detections of potential flux and spectral evolution. Our results highlight the importance of radio observations to constrain the nature of nuclear MIR outbursts in galaxies., Comment: 8 pages, 4 figures, 1 table, Accepted for publication in ApJ Letters

Published
2020
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32. MADLens, a python package for fast and differentiable non-Gaussian lensing simulations

Author

Böhm, V, Feng, Y, Lee, ME, and Dai, B

Subjects
Information and Computing Sciences, Applied Computing, Machine Learning, Networking and Information Technology R&D (NITRD), Bioengineering, Machine Learning and Artificial Intelligence, Gravitational lensing, Cosmological parameters, Methods, N-body simulations, Astronomical and Space Sciences, Artificial Intelligence and Image Processing, Computer Software, Applied computing, Astronomical sciences
Published
2021

34. Search for gamma-ray emission from the Sun during solar minimum with the ARGO-YBJ experiment

Author

Bartoli, B., Bernardini, P., Bi, X. J., Cao, Z., Catalanotti, S., Chen, S. Z., Chen, T. L., Cui, S. W., Dai, B. Z., D'Amone, A., Danzengluobu, De Mitri, I., Piazzoli, B. D'Ettorre, Di Girolamo, T., Di Sciascio, G., Feng, C. F., Feng, Zhaoyang, Feng, Zhenyong, Gao, W., Gou, Q. B., Guo, Y. Q., He, H. H., Hu, Haibing, Hu, Hongbo, Iacovacci, M., Iuppa, R., Jia, H. Y., Labaciren, Li, H. J., Li, Z., Liu, C., Liu, J., Liu, M. Y., Lu, H., Ma, L. L., Ma, X. ., Mancarella, G., Mari, S. M., Marsella, G., Mastroianni, S., Montini, P., Ning, C. C., Perrone, L., Pistilli, P., Salvini, P., Santonico, R., Shen, P. R., Sheng, X. D., Shi, F., Surdo, A., Tan, Y. H., Vallania, P., Vernetto, S., Vigorito, C., Wang, H., Wu, C. Y., Wu, H. R., Xue, L., Yang, Q. Y., Yang, X. C., Yao, Z. G., Yuan, A. F., Zha, M., Zhang, H. M., Zhang, L., Zhang, X. Y., Zhang, Y., Zhao, J., Zhaxiciren, Zhaxisangzhu, Zhou, X. X., Zhu, F. R., and Zhu, Q. Q.

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

The hadronic interaction of cosmic rays with solar atmosphere can produce high energy gamma rays. The gamma-ray luminosity is correlated both with the flux of primary cosmic rays and the intensity of the solar magnetic field. The gamma rays below 200 GeV have been observed by $Fermi$ without any evident energy cutoff. The bright gamma-ray flux above 100 GeV has been detected only during solar minimum. The only available data in TeV range come from the HAWC observations, however outside the solar minimum. The ARGO-YBJ dataset has been used to search for sub-TeV/TeV gamma rays from the Sun during the solar minimum from 2008 to 2010, the same time period covered by the Fermi data. A suitable model containing the Sun shadow, solar disk emission and inverse-Compton emission has been developed, and the chi-square minimization method was used to quantitatively estimate the disk gamma-ray signal. The result shows that no significant gamma-ray signal is detected and upper limits to the gamma-ray flux at 0.3$-$7 TeV are set at 95\% confidence level. In the low energy range these limits are consistent with the extrapolation of the Fermi-LAT measurements taken during solar minimum and are compatible with a softening of the gamma-ray spectrum below 1 TeV. They provide also an experimental upper bound to any solar disk emission at TeV energies. Models of dark matter annihilation via long-lived mediators predicting gamma-ray fluxes > $10^{-7}$ GeV $cm^{-2}$ $s^{-1}$ below 1 TeV are ruled out by the ARGO-YBJ limits.

Published
2019
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35. High mass and halo resolution from fast low resolution simulations

Author

Dai, B, Feng, Y, Seljak, U, and Singh, S

Subjects
cosmological simulations, dark matter simulations, power spectrum, weak gravitational lensing, astro-ph.CO, Astronomical and Space Sciences, Atomic, Molecular, Nuclear, Particle and Plasma Physics, Nuclear & Particles Physics, Atomic, Molecular, Nuclear, Particle and Plasma Physics
Abstract

Generating mocks for future sky surveys requires large volumes and high resolutions, which is computationally expensive even for fast simulations. In this work we try to develop numerical schemes to calibrate various halo and matter statistics in fast low resolution simulations compared to high resolution N-body and hydrodynamic simulations. For the halos, we improve the initial condition resolution and develop a halo finder "relaxed-FoF", where we allow different linking lengths for different halo mass and velocity dispersions. We show that our relaxed-FoF halo finder improves the common statistics, such as halo bias, halo mass function, halo auto power spectrum, cross correlation coefficient with the reference halo catalog, and halo-matter cross power spectrum. We also calibrate small-scale velocities of small halos to improve the power spectrum in redshift space. For the matter statistics, we incorporate the potential gradient descent (PGD) method into fast simulations to improve the matter distribution at nonlinear scales. By building a lightcone output, we show that the PGD method significantly improves the weak lensing convergence tomographic power spectrum. With these improvements FastPM is comparable to the high resolution full N-body simulation of the same mass resolution, with two orders of magnitude fewer time steps. These techniques can be used to improve the halo and matter statistics of FastPM simulations for mock catalogs of future surveys such as DESI and LSST.

Published
2020

36. Reconstruction of Cherenkov image by multiple telescopes of LHAASO-WFCTA

Author

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

Published
2022
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38. Galactic Cosmic-Ray Anisotropy in the Northern hemisphere from the ARGO-YBJ Experiment during 2008-2012

Author

Bartoli, B., Bernardini, P., Bi, X. J., Cao, Z., Catalanotti, S., Chen, S. Z., Chen, T. L., Cui, S. W., Dai, B. Z., D'Amone, A., Danzengluobu, De Mitri, I., Piazzoli, B. D'Ettorre, Di Girolamo, T., Di Sciascio, G., Feng, C. F., Feng, Z. Y., Gao, W., Gou, Q. B., Guo, Y. Q., He, H. H., Hu, Haibing, Hu, Hongbo, Iacovacci, M., Iuppa, R., Jia, H. Y., Labaciren, Li, H. J., Liu, C., Liu, J., Liu, M. Y., Lu, H., Ma, L. L., Ma, X. H., Mancarella, G., Mari, S. M., Marsella, G., Mastroianni, S., Montini, P., Ning, C. C., Perrone, L., Pistilli, P., Ruffolo, D., Salvini, P., Santonico, R., Shen, P. R., Sheng, X. D., Shi, F., Surdo, A., Tan, Y. H., Vallania, P., Vernetto, S., Vigorito, C., Wang, H., Wu, C. Y., Wu, H. R., Xue, L., Yang, Q. Y., Yang, X. C., Yao, Z. G., Yuan, A. F., Zha, M., Zhang, H. M., Zhang, L., Zhang, X. Y., Zhang, Y., Zhao, J., Zhaxiciren, Zhaxisangzhu, Zhou, X. X., Zhu, F. R., and Zhu, Q. Q.

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

This paper reports on the observation of the sidereal large-scale anisotropy of cosmic rays using data collected by the ARGO-YBJ experiment over 5 years (2008$-$2012). This analysis extends previous work limited to the period from 2008 January to 2009 December,near the minimum of solar activity between cycles 23 and 24.With the new data sample the period of solar cycle 24 from near minimum to maximum is investigated. A new method is used to improve the energy reconstruction, allowing us to cover a much wider energy range, from 4 to 520 TeV. Below 100 TeV, the anisotropy is dominated by two wide regions, the so-called "tail-in" and "loss-cone" features. At higher energies, a dramatic change of the morphology is confirmed. The yearly time dependence of the anisotropy is investigated. Finally, no noticeable variation of cosmic-ray anisotropy with solar activity is observed for a median energy of 7 TeV.

Published
2018
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39. Observation of the thunderstorm-related ground cosmic ray flux variations by ARGO-YBJ

Author

Bartoli, B., Bernardini, P., Bi, X. J., Cao, Z., Catalanotti, S., Chen, S. Z., Chen, T. L., Cui, S. W., Dai, B. Z., Amone, A. D, Luobu, Danzeng, De Mitri, I., Piazzoli, B. D Ettorre, Di Girolamo, T., Di Sciascio, G., Feng, C. F., Feng, Zhaoyang, Feng, Zhenyong, Gao, W., Gou, Q. B., Guo, Y. Q., He, H. H., Hu, Haibing, Hu, Hongbo, Iacovacci, M., Iuppa, R., Jia, H. Y., Ren, Labaci, Li, H. J., Liu, C., Liu, J., Liu, M. Y., Lu, H., Ma, L. L., Ma, X. H., Mancarella, G., Mari, S. M., Marsella, G., Mastroianni, S., Montini, P., Ning, C. C., Perrone, L., Pistilli, P., Salvini, P., Santonico, R., Shen, P. R., Sheng, X. D., Shi, F., Surdo, A., Tan, Y. H., Vallania, P., Vernetto, S., Vigorito, C., Wang, H., Wu, C. Y., Wu, H. R., Xue, L., Yang, Q. Y., Yang, X. C., Yao, Z. G., Yuan, A. F., Zha, M., Zhang, H. M., Zhang, L., Zhang, X. Y., Zhang, Y., Zhao, J., Ren, Zhaxici, Zhu, Zhaxisang, Zhou, X. X., Zhu, F. R., Zhu, Q. Q., and Alessandro, F. D.

Subjects
Astrophysics - Earth and Planetary Astrophysics, Astrophysics - High Energy Astrophysical Phenomena
Abstract

A correlation between the secondary cosmic ray flux and the near-earth electric field intensity, measured during thunderstorms, has been found by analyzing the data of the ARGO-YBJ experiment, a full coverage air shower array located at the Yangbajing Cosmic Ray Laboratory (4300 m a. s. l., Tibet, China). The counting rates of showers with different particle multiplicities, have been found to be strongly dependent upon the intensity and polarity of the electric field measured during the course of 15 thunderstorms. In negative electric fields (i.e. accelerating negative charges downwards), the counting rates increase with increasing electric field strength. In positive fields, the rates decrease with field intensity until a certain value of the field EFmin (whose value depends on the event multiplicity), above which the rates begin increasing. By using Monte Carlo simulations, we found that this peculiar behavior can be well described by the presence of an electric field in a layer of thickness of a few hundred meters in the atmosphere above the detector, which accelerates/decelerates the secondary shower particles of opposite charge, modifying the number of particles with energy exceeding the detector threshold. These results, for the first time, give a consistent explanation for the origin of the variation of the electron/positron flux observed for decades by high altitude cosmic ray detectors during thunderstorms., Comment: 17 pages, 11 figures. The paper has been accepted by PRD

Published
2017
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40. EAS age determination from the study of the lateral distribution of charged particles near the shower axis with the ARGO-YBJ experiment

Author

Collaboration, ARGO-YBJ, Bartoli, B., Bernardini, P., Bi, X. J., Cao, Z., Catalanotti, S., Chen, S. Z., Chen, T. L., Cui, S. W., Dai, B. Z., D'Amone, A., Danzengluobu, De Mitri, I., Piazzoli, B. D'Ettorre, Di Girolamo, T., Di Sciascio, G., Feng, C. F., Feng, Zhaoyang, Feng, Zhenyong, Gou, Q. B., Guo, Y. Q., He, H. H., Hu, Haibing, Hu, Hongbo, Iacovacci, M., Iuppa, R., Jia, H. Y., Labaciren, Li, H. J., Liu, C., Liu, J., Liu, M. Y., Lu, H., Ma, L. L., Ma, X. H., Mancarella, G., Mari, S. M., Marsella, G., Mastroianni, S., Montini, P., Ning, C. C., Perrone, L., Pistilli, P., Salvini, P., Santonico, R., Shen, P. R., Sheng, X. D., Shi, F., Surdo, A., Tan, Y. H., Vallania, P., Vernetto, S., Vigorito, C., Wang, H., Wu, C. Y., Wu, H. R., Xue, L., Yang, Q. Y., Yang, X. C., Yao, Z. G., Yuan, A. F., Zha, M., Zhang, H. M., Zhang, L., Zhang, X. Y., Zhang, Y., Zhao, J., Zhaxiciren, Zhaxisangzhu, Zhou, X. X., Zhu, F. R., and Zhu, Q. Q.

Subjects
Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Instrumentation and Methods for Astrophysics, High Energy Physics - Experiment
Abstract

The ARGO-YBJ experiment, a full coverage extensive air shower (EAS) detector located at high altitude (4300 m a.s.l.) in Tibet, China, has smoothly taken data, with very high stability, since November 2007 to the beginning of 2013. The array consisted of a carpet of about 7000 m$^2$ Resistive Plate Chambers (RPCs) operated in streamer mode and equipped with both digital and analog readout, providing the measurement of particle densities up to few particles per cm$^2$. The unique detector features (full coverage, readout granularity, wide dynamic range, etc) and location (very high altitude) allowed a detailed study of the lateral density profile of charged particles at ground very close to the shower axis and its description by a proper lateral distribution function (LDF). In particular, the information collected in the first 10 m from the shower axis have been shown to provide a very effective tool for the determination of the shower development stage ("age") in the energy range 50 TeV - 10 PeV. The sensitivity of the age parameter to the mass composition of primary Cosmic Rays is also discussed.

Published
2017
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41. Search for Gamma Ray Bursts with the ARGO-YBJ Detector in Shower Mode

Author

Bartoli, B., Bernardini, P., Bi, X. J., Cao, Z., Catalanotti, S., Chen, S. Z., Chen, T. L., Cui, S. W., Dai, B. Z., Amone, A. D, Luobu, Danzeng, De Mitri, I., Piazzoli, B. D Ettorre, Di Girolamo, T., Di Sciascio, G., Feng, C. F., Feng, Zhaoyang, Feng, Zhenyong, Gao, W., Gou, Q. B., Guo, Y. Q., He, H. H., Hu, Haibing, Hu, Hongbo, Iacovacci, M., Iuppa, R., Jia, H. Y., Ren, Labaci, Li, H. J., Liu, C., Liu, J., Liu, M. Y., Lu, H., Ma, L. L., Ma, X. H., Mancarella, G., Mari, S. M., Marsella, G., Mastroianni, S., Montini, P., Ning, C. C., Perrone, L., Pistilli, P., Salvini, P., Santonico, R., Shen, P. R., Sheng, X. D., Shi, F., Surdo, A., Tan, Y. H., Vallania, P., Vernetto, S., Vigorito, C., Wang, H., Wu, C. Y., Wu, H. R., Xue, L., Yang, Q. Y., Yang, X. C., Yao, Z. G., Yuan, A. F., Zha, M., Zhang, H. M., Zhang, L., Zhang, X. Y., Zhang, Y., Zhao, J., Ren, Zhaxici, Zhu, Zhaxisang, Zhou, X. X., Zhu, F. R., and Zhu, Q. Q.

Subjects
Astrophysics - High Energy Astrophysical Phenomena, High Energy Physics - Phenomenology
Abstract

The ARGO-YBJ detector, located at the Yangbajing Cosmic Ray Laboratory (4300 m a. s. l., Tibet, China), was a full coverage air shower array dedicated to gamma ray astronomy and cosmic ray studies. The wide field of view (~ 2 sr) and high duty cycle (> 86%), made ARGO-YBJ suitable to search for short and unexpected gamma ray emissions like gamma ray bursts (GRBs). Between 2007 November 6 and 2013 February 7, 156 satellite-triggered GRBs (24 of them with known redshift) occurred within the ARGO-YBJ field of view. A search for possible emission associated to these GRBs has been made in the two energy ranges 10-100 GeV and 10-1000 GeV. No significant excess has been found in time coincidence with the satellite detections nor in a time window of one hour after the bursts. Taking into account the EBL absorption, upper limits to the energy fluence at 99% of confidence level have been evaluated,with values ranging from ~ 10-5 erg cm-2 to ~10-1 erg cm-2., Comment: 24pages and 12 figures

Published
2017
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45. Line-of-shower trigger method to lower energy threshold for GRB detection using LHAASO-WCDA

Author

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

Published
2021
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46. A dynamic range extension system for LHAASO WCDA-1

Author

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

Published
2021
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