This is the actual image data we have (from a large radio-telescope array), of what is thought to be a "tidal disruption event" - a black-hole eating a star. At first, the 1997 and 2007 images (across the spectrum, shown in visible light in upper left) looked to be a supernova - an exploding star. But the radio-image data, from 2005, 2012, 2013 and 2015, (shown on the right, in a topological graphic), suggest that we are seeing a "tidal disruption event", which is basically a star being chewed up and eaten by a black-hole. The theory suggests that as the mass is pulled into the hole, and the atoms are torn apart, significant - and visible as radio radiation - energy streams are generated. The original article is in the June 15, 2018 issue of Science, but it is behind a paywall, and is not accessable to the people (taxpayers) who fund this research.

Results from Kepler and other Exoplanet Searches

Kepler Exoplanet Search Results

This is *really* impressive.  The Kepler Telescope has identified 2525 confirmed exoplanets - many of which are Earth-sized.  The total confirmed number of exoplanets is 3567.   What is particularly interesting, is that the machine-learning tool used was a TensorFlow application (very similar to MINST-type classification), which used a training set of roughly 15,000-case observations.  This is a sufficiently small enough training set that the entire model can run on a desktop personal computer - total training time was only a few hours. 

What this shows is that machine-learning can be used to effectively to augment and extend the ability of human astronomers in a elegant and effective way, as the Kepler dataset is already large and will continue to grow.  Given we have training cases where humans accurately found planets, we can apply the machine-learning tool to expand the search, and specifically focus on weak signals which are typically the kinds of signals that smaller, Earth-size planets will create. 

The researcher are: Chris Shallue & Andrew Vanderburg.  Their paper on this research is at:

They are using logistic neurons, I notice.  Their TensorFlow model will be released to the open-source community, according to the NASA press conference.  Looks like very good work, which can find immediate application in other areas.


Elon Musk's Amazing Adventure - with "Starman" at the wheel of Mr. Musk's Telsa Roadster - off to see Mars! I screen-captured this *live* image, as I watched the video-feed of the Falcon Heavy first test-launch. Bravo to Mr. Musk and the whole SpaceX team! Well done, folks. You lit up the World's imagination with this successful test flight.