论文标题
JCMT瞬态调查:单个时期瞬变和微弱源的可变性
The JCMT Transient Survey: Single Epoch Transients and Variability of Faint Sources
论文作者
论文摘要
毫米波长的短耐耀斑为恒星冠状动脉中最强的磁重新连接事件提供了独特的见解,并与长期变化相结合,将并发症引入下一代宇宙学调查。我们分析了5。5年的JCMT瞬态调查850微米亚费表监测观测值,向八个古尔德带恒星形成区域,以寻找瞬时事件或淡淡来源的长期变化的证据。已经观察到八个区域(30个Arcmin直径场),包括〜1200个红外选择的YSO,平均观察到47次,整合约半小时,或一天的总分布在5.5年中。在此大数据集中,仅恢复了两个可靠的淡淡源检测:OMC 2/3中的JW 566和NGC 2023中的MGM12 2864。 mjy/beam。如果较小的事件比较大的事件更常见,则缺乏JW 566和我们的检测限制之间的其他回收耀斑令人困惑。相比之下,在我们的分析中确定的其他亚毫升变量,Source 2864,在所有观察到的时间尺度上都是高度可变的。尽管Source 2864偶尔被归类为YSO,但该来源很可能是Blazar。电磁光谱之间的可变性程度可用于帮助源分类。
Short-duration flares at millimeter wavelengths provide unique insights into the strongest magnetic reconnection events in stellar coronae, and combine with longer-term variability to introduce complications to next-generation cosmology surveys. We analyze 5.5 years of JCMT Transient Survey 850 micron submillimeter monitoring observations toward eight Gould Belt star-forming regions to search for evidence of transient events or long-duration variability from faint sources. The eight regions (30 arcmin diameter fields), including ~1200 infrared-selected YSOs, have been observed on average 47 times with integrations of approximately half an hour, or one day total spread over 5.5 years. Within this large data set, only two robust faint source detections are recovered: JW 566 in OMC 2/3 and MGM12 2864 in NGC 2023. JW 566, a Class II TTauri binary system previously identified as an extraordinary submillimeter flare, remains unique, the only clear single-epoch transient detection in this sample with a flare eight times bright than our ~4.5 sigma detection threshold of 55 mJy/beam. The lack of additional recovered flares intermediate between JW 566 and our detection limit is puzzling, if smaller events are more common than larger events. In contrast, the other submillimeter variable identified in our analysis, Source 2864, is highly variable on all observed timescales. Although Source 2864 is occasionally classified as a YSO, the source is most likely a blazar. The degree of variability across the electromagnetic spectrum may be used to aid source classification.