First of all, Happy New Year to everyone; my best wishes for a healthy, happy and productive 2017!
Let’s hope Particle Physics has in store for us some intriguing stuff in its New Year’s resolutions, and is -of course- consistent enough in keeping them! [this time] The same should hold for Machine Learning, which however has already offered us some very powerful moments in 2016. For me, the two most astonishing and longed-for/ beyond expectations achievements of 2016, science-wise, would be:
1) The double detection of gravitational waves, those impressive ripples in the fabric of space-time propagating at the speed of light, from two pairs of merging black holes; for both, the public announcements were made by LIGO in 2016 (11/02/16 and 15/06/16), and corresponded to observations occurred in 2015 (14/09/15 and 26/12/15, respectively). That proof of Einstein’s audacious prediction has -without a doubt- constituted a perfect celebration of the centenary of General Relativity.
2) The victory of Google’s AlphaGo [computer program] over the 18-time Go world champion, Lee Sedol [9 dan ranked human] on a Go match in March 2016 (5-game final score: 4-1). That is supposed to be a much earlier than expected Artificial Intelligence success, in a game considered to require a general-purpose and intuitive winning strategy, compared to chess or other board games, which makes it extremely hard for a computer algorithm to prevail, defeating human intelligence.
Therefore, in science and research, 2016 ended with this wonderful breakthrough progress. But it also ended with a wonderful -mutatis mutandis- meeting of the AMVA Network in Oxford on 19-20/12/16, where its PhD students had the opportunity to present and discuss their own progress up to now, whilst holding their ESR positions.
Very briefly*, Cecilia described her work on the di-Higgs events, Alessia discussed her project on the use of the MoMEMta tool (Matrix Element Method), Alex presented his studies on the ttH(bb) channel, Pablo talked about his work on the HH(4b) channel, Greg described his project on statistical models, I presented my studies on Deep Learning in HEP, and Giles talked about his work on the di-Higgs events.
But apart from the academic side of the meeting, in terms of which we had the opportunity to attend the very interesting presentations of the other ESRs, ask questions on their projects, learn from their answers, and exchange ideas and tips for our work, this meeting was also a great chance for all the Network group to gather and interact. Slightly before Christmas, we got to spend some time with our supervisors and other members of the Network, discussing our near-future plans and forthcoming secondments, and sharing thoughts on our studies and overall progress. It was a great way of getting more motivated to set higher standards for our work, upon stronger collaboration among us and mutual support.
As Alessia also pointed out in her latest post, for some of us, this year’s start signifies the beginning of our secondment periods. Pablo and I will be heading to California in a few weeks, and will be keeping the blog updated with our west—side research news. But before that, we will both have the chance to meet again with the other ESRs in Padova, Italy, for a Network’s workshop (I guess more related details will be shortly out on the blog) in the very beginning of February, so as to get even more of the valuable training (and interaction opportunities) this Network provides. So see you all, soon! [a bit sooner than before :)]
*All ESRs are currently having some work in progress, parts of which may have already been and/or will (continue to) be discussed over our blog posts; I guess the latter ones shall contain a more clear and accurate summary, driven by the specific way each one of us would prefer presenting it. I am therefore giving here just a rough outline.
PS: Many thanks to Tommaso Dorigo and Daniela Bortoletto for organising this wonderful Oxford Meeting!