Comet Dust Tail Analysis using the Finson-Probstein Model

<p>The fine-structure detail of several comet dust tails is analysed from amateur and professional comet images using the Finson-Probstein mdoel. Given the date and time of the image taken, the comet’s position in the sky is calculated using an open source algorithm [1] and the comet’s dust tail is simulated for that position and time. This modeled dust tail structure is then projected and overlaid onto the comet image to directly compare and identify similarities and discrepancies between the model and the image. Using the novel analysis method of mapping the image to a dust grain beta against ejection time plot [2], tail structures can be more easily identified and analysed. This also allows for the tracking of tail structure over time, as images of a single comet from different times and observatories can be mapped onto the same plot. This method compensates for the difficulties of investigating tail structures in images as the comet moves across the image and as viewing geometry changes over time.      </p> <p>This is a continuation of the work done previously on Comet C/2006 P1 (McNaught), which ultimately led to the observation of the formation processes of new fine-scale structure features in the comet’s dust tail [2]. This model is now applied to several other comets, including the recent Comet ATLAS (C/2019 Y4), to map their tail structures and to highlight this model’s utility in comet dust tail analysis.</p> <p>Finally, this work will be put into context as the first step in the development of an automated analysis method for cometary dust and ion tails. This automated method is in preparation for the upcoming opening of the Vera Rubin Observatory (LSST), and aims to automatically identify comet tail structures from the Observatory’s stream of comet images. The robustness of this analysis suite enables it to also be implemented on amateur comet images, making use of the abundant and valuable data from amateur astronomers.</p> <p> </p> <p> </p> <p> </p> <p> </p> <p>[1] Lang, Dustin, David W. Hogg, Keir Mierle, Michael Blanton, and Sam Roweis. 2010. "ASTROMETRY.NET: BLIND ASTROMETRIC CALIBRATION OF ARBITRARY ASTRONOMICAL IMAGES". The Astronomical Journal 139 (5): 1782-1800. doi:10.1088/0004-6256/139/5/1782.</p> <p>[2] Price, Oliver, Geraint H. Jones, Jeff Morrill, Mathew Owens, Karl Battams, Huw Morgan, Miloslav Drückmuller, and Sebastian Deiries. 2019. "Fine-Scale Structure In Cometary Dust Tails I: Analysis Of Striae In Comet C/2006 P1 (Mcnaught) Through Temporal Mapping". Icarus 319: 540-557. doi:10.1016/j.icarus.2018.09.013.</p>

Fat Tail Analysis on S&P 100 Stocks-before and after US President Election

The main aim of this paper is to determine whether the volatility in the stocks can be created by events like the US Election and whether it leads to Fat Tail in the stocks. Fat Tail analysis is a key factor in determining volatility and has been used in the economy as well as in many other fields like climate and health. Log return has been used to determine the Fat Tail. To make the work more reliable, two Presidential election periods, that of Barack Obama and Donald Trump is selected and is compared for volatility and Fat Tail. For this study, stocks from the S&P 100 are selected and observed. The results show that the US economy is not at all driven by who comes in power and when but rather by the present economic condition. Stocks showing heavy tails during the Obama presidency are primarily because the economy was under Sub Prime Crisis too.