인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
The cosmic X-ray background (CXB) is produced by the emission of unresolved active galactic nuclei (AGNs), thus providing key information about the properties of the primary and reprocessed X-ray emission components of the AGN population. Equally important are studies of individual sources that provide additional constraints on the properties of AGNs, such as their luminosity and obscuration. Until now, these constraints have not been self-consistently addressed by intrinsically linking emission, absorption, and reflection. Here, we performed numerical simulations with the ray-tracing code R EFLE X, which allows us to self-consistently model the X-ray emission of AGNs with flexible geometries for the circumnuclear medium. Using the R EFLE X-simulated emission of an AGN population, we attempted to simultaneously reproduce the CXB and absorption properties measured in the X-rays, namely the observed fraction of N H in bins of log( N H ) and the fraction of absorbed AGNs, including their redshift and luminosity evolution. We sampled an intrinsic X-ray-luminosity function and constructed gradually more complex, physically motivated geometrical models. We examined how well each model can match all observational constraints using a simulation-based inference (SBI) approach. We find that, while the simple unification model can reproduce the CXB, a luminosity-dependent dusty torus is needed to reproduce the absorption properties. When adding an accretion disc, the model best matches all constraints simultaneously. Our synthetic population is able to reproduce the dependence of the covering factor on luminosity, the AGN number counts from several surveys, and the observed correlation between reflection and obscuration. Finally, we derived an intrinsic Compton-thick fraction of 21 ± 7%, which is consistent with local observations.
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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