Group items tagged

Deconvnets for astro images .... resolving galxies :)

Its doing it again. Anyone wants to play the "explain this" game?

New debates on 'old' topic: https://phys.org/news/2018-01-alien-megastructure-dimming-mysterious-star.html? see blog posts in link for more info

The Nature paper this article is reviewing (behind their paywall) https://www.nature.com/articles/s41563-018-0075-8

no cutting-edge space-related science, but important anyways

The EFF communicate is actually quite inaccurate. This is disappointing from the EFF, though for some part, it is due to the communication from the researchers who "discovered" the attack. PGP itself is not broken, but rather some implementations on some email clients (notably Enigmail, though it was patched several months ago). See https://protonmail.com/blog/pgp-vulnerability-efail/ On the other hand, if you are very keen on security, there is an XSS attack reported on Signal, so… https://thehackernews.com/2018/05/signal-messenger-code-injection.html The *good* recommendation here is actually rather to keep your software stack up to date (surprising, no?) and keep encrypting your emails.

NASA marketing interstellar travel to foreign bodies even without knowing how they actually look like.

Lucky astronomist watches star go boom.

it works! No, of course it doesn't. I've wasted your time just posting this.

Einstein's theory of gravity, General Relativity (GR), has been tested precisely within the Solar System. However, it has been difficult to test GR on the scale of an individual galaxy. Collett et al. exploited a nearby gravitational lens system, in which light from a distant galaxy (the source) is bent by a foreground galaxy (the lens). Mass distribution in the lens was compared with the curvature of space-time around the lens, independently determined from the distorted image of the source. The result supports GR and eliminates some alternative theories of gravity.

How much did Apollo cost?

They want to catch the first stage of the Electron "Mid-air", using a helicopter. Would love to see that!

Another entry by the Planetary Society for the Apollo 11 50th anniversary, this time a podcast series on its political background.

"We examine the possibility that Fast Radio Bursts (FRBs) originate from the activity of extragalactic civilizations"

serious gaming came back!

The rules for a stellar death seem pretty simple. If the star isn't that massive, it burns out into a carbon-rich remnant called a white dwarf. If it's big enough, the star ends in a bang, exploding in a supernova that can leave behind a neutron star or a black hole.

OHB and Luxspace venture to ensure human life on the Moon! Research on O2 production and others.....

Has BH at least completed an orbit yet? Or are they still at 10mins in microgravity?

Paper at http://www.nature.com/nature/journal/v548/n7669/full/nature23463.html?foxtrotcallback=true

Loss of connectivity in the multisensory integration cortical areas after short term microgravity experience, which could explain astronauts decrease of performance in sensorimotor tasks and spatial working memory. However, the effect should wear off after a few days in microgravity and after adaptation to incongruent vestibular information. ISS experiment needed...

This has been around for over a year. The current trend in deep learning is "deeper is better". But a consequence of this is that for a given network depth, we can only feasibly evaluate a tiny fraction of the "search space" of NN architectures. The current approach to choosing a network architecture is to iteratively add more layers/units and keeping the architecture which gives an increase in the accuracy on some held-out data set i.e. we have the following information: {NN, accuracy}. Clearly, this process can be automated by using the accuracy as a 'signal' to a learning algorithm. The novelty in this work is they use reinforcement learning with a recurrent neural network controller which is trained by a policy gradient - a gradient-based method. Previously, evolutionary algorithms would typically be used. In summary, yes, the results are impressive - BUT this was only possible because they had access to Google's resources. An evolutionary approach would probably end up with the same architecture - it would just take longer. This is part of a broader research area in deep learning called 'meta-learning' which seeks to automate all aspects of neural network training.

Btw that techxplore article was cringing to read - if interested read this article instead: https://research.googleblog.com/2017/05/using-machine-learning-to-explore.html