Advanced Concepts Team

Lucky astronomist watches star go boom.

Great engineering feat from Capasso's idea - an integrated flat lens electrically controlled enabling dynamic beam steering. Reconfigurabilility is the aim. The lens can be used microscope systems, holographic and projection imaging, LIDAR and laser printing. Besides working now on the mid-IR, visible light is the target.

Cameras sure have evolved these days...

Showing why epycicles worked so well

I would troll the world and do a GR theory using epicycles :)

The paper I talked about with the proof of a gigantic lava tube discovered in 2017 from data of the Japanese lunar mission

Given the size of this thing we may consider a project on city urban planning inside. I would see a rocket-port outside the crater, some lift systems to get in, a closed dome with artificial atmosphere where to develop the city possible trekking routes on the lunar surface, a mirror system to get sunlight in, an energy factory just outside the entry.

Here, we show that quasar microlensing provides a means to probe extragalactic planets in the lens galaxy, by studying the microlensing properties of emission close to the event horizon of the supermassive black hole of the background quasar, using the current generation telescopes

These are lasers whose lasing mode exhibits topologically-protected transport without magnetic fields. The underlying topological properties lead to a highly efficient laser, robust to defects and disorder, with single mode lasing even at very high gain values.

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

Pretty cool this was never spotted before!!

any papers or insights on methods available?

Couldn't find a paper for Alibaba's results but Microsoft Research's performance on this dataset was very close. The paper is here: https://www.microsoft.com/en-us/research/wp-content/uploads/2017/05/r-net.pdf Btw the 'reading test' is a publicly available dataset called 'Stanford Question Answering Dataset (SQuAD)'. Their website shows a leaderboard: https://rajpurkar.github.io/SQuAD-explorer/

interesting idea to produce O2 differently on Mars

Also, let's see how MOXIE does onboard the Mars2020 rover! https://mars.nasa.gov/mars2020/mission/instruments/moxie/for-scientists/

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

No GUTs, no glory

Some locations on Mars are known to have water ice just below the surface, but how much has remained unclear. Dundas et al. used data from two orbiting spacecraft to examine eight locations where erosion has occurred. This revealed cliffs composed mostly of water ice, which is slowly sublimating as it is exposed to the atmosphere. The ice sheets extend from just below the surface to a depth of 100 meters or more and appear to contain distinct layers, which could preserve a record of Mars' past climate. They might even be a useful source of water for future human exploration of the red planet.

An overview of all the neurotech companies messing with the brain. When reading this I really wonder why we need ethical approval for everything in human research.

impressive achievement - extremely absorbant feather almost as black as our most "black" material

38 degree core body temp in microgravity stabilised after 2 months - due to reduced conv. heat transfer+evaporation https://www.nature.com/articles/s41598-017-15560-w

so that's hypopyrexia (augmented concentrations of interleukin-1 receptor antagonist) AND hypothermia (convection/evaportation)? what puzzles me is that temperatures take so long to return to baseline after astronauts return to earth.

" The goal of the APT program is to control and direct plant physiology to detect chemical, biological, radiological, and/or nuclear threats, as well as electromagnetic signals. " Now that is an advanced concept...

and look at this exceptional insight: "plants are easily deployed, self-powering, and ubiquitous in the environment, and the combination of these native abilities with specifically engineered sense-and-report traits will produce sensors occupying new and unique operational spaces" :-)

"...the European Commission announced in 2016 that it was investing one billion euros in a research effort known as the Quantum Technology Flagship. The goal for this project is to develop four technologies: quantum communication, quantum simulation, quantum computing, and quantum sensing. After almost two years, how is it going?" arxiv link to the actual report: http://arxiv.org/abs/1712.03773

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