I am a third year PhD student (my how time has flown...) working within the ATLAS Collaboration, which is one of the multi-purpose detectors installed at the Large Hadron Collider in CERN. I have completed a period of 18 monthes living and working out at CERN on a long-term attachement from my home institution (Royal Holloway, Univeristy of London). This tumblr is a platform from which I can try to educate and inform others interested in particle physics and wonderful science, as well as provide some insight into the workings of a PhD. Click here to see the kinds of things I like. You can find my personal tumblr here.
I’m currently attending a summer school at Fermilab (which is awesome, I know) and means I am getting to experience American culture for the first time.
I can only assume self-reblogging is frowned upon, but I came upon an article I wrote explaining some of the mathematics behind the Higgs mechanism a couple of years ago. After attending some lectures on spontaneous symmetry breaking (and general Standard Model theory) I think the explanation still holds true, so good going past-me :)
Thought I’d share it anyway. I’ll post some pictures of Fermilab (FNAL) some point soon too :)
Spontaneous Symmetry Breaking and the Higgs Mechanism - Some Notes
One of the things I have always found interesting in Particle Physics is Spontaneous Symmetry Breaking. When I was in Sixth Form, it was articles on the unification which I enjoyed reading the most.
As I have done a couple of courses now on the Standard Model and the unification within it, I thought I would try my hand at writing up some notes which try to explain the methodology behind the Higgs mechanism, because in truth, it is not too difficult.
There are some parts that people may not be able to fully comprehend as I have probably assumed to much knowledge of quantum field theory nomenclature.
If you are vaguely aware of index notation, it should be straight forward to follow.
If you understand differentiation, and not index notation, it should still be accessible.
If you want an overview of the maths behind the Higgs mechanism, instead of just reading Higgs boson everywhere and not understanding why there is even a boson, please have a read.
I have tried to explain things clearly as I have gone along.
As always, if you have questions about this, please ask, as I would be more than willing to expand on some points if people want to learn more.
(Note: the video is actually an embeded pdf and you should be able to download it via issuu if you desire.)
If you’ve ever wanted to get involved with a particle physics analysis but not had the opportunity to work with one of the largest scientific collaborations in the world, your luck has changed!
The ATLAS experiment is running a machine learning challenge to try and gain input and expertise from people all over, who might have a new way of looking at our data to discover the Higgs particle.
Machine learning encompasses the branch of computer science where you use clever algorithms (such as boosted decision trees and neural networks) which learn from known data to help classify unknown data.
Here in the particle physics community, the known data falls into two categories (a binomial problem) - signal and background. The signal is the process we want to discover. The background is all the other processes which look almost identical to the process we really want to see.
If our signal was so unique and different from the background continuum then we would not need to work out ways to discriminate between the two. Sadly Nature is not that kind to us, and often if we are looking for one particle physics process to produce a final state of particles, there will always be other ways (other Feynman diagrams) which could produce the same outcome.
The challenge here has simulated data from Higgs to di-tau events as the signal. From a statistical standpoint, if you can correctly categorise the signal and background into their respective categories then you can evaluate the discovery sensitivity or discovery significance. Information is provided on calculating this, and this will be the marker with which to rank the entrants.
People wishing to participate have until the 15th September 2014 to submit an application, and you can submit a limited number per day. Further information about the machine learning tools which are freely available is provided on the webpages and the tutorial pages.
If you are good enough you could win up to $7000. Not a bad prize for doing some coding. Already there have been over 800 entrants and the great thing about this is that you don’t need to understand the physics involved to manipulate the data, extract information from the variables, and combine it all together to correctly classify data. The only benefit particle physicists get is knowing what kind of correlations to expect between these variables, but in fact, a perfect machine learning algorithm should be able to find and exploit these correlations anyway.
In 2011, Dublin-based physics student David Whyte began a Tumblr called Bees & Bombs where he posted humorous images and quirky GIFs of his own creation, borrowing heavily from videos and pop culture icons. One day he decided to start playing with Processing, a popular open source progr
Fun fact: The reason why the Deep Space Network antennae are in Madrid, Goldstone, and Canberra is so that they can always be in touch with distant craft like Voyager 1, no matter which side of Earth is facing the spacecraft.
Physicists have exploited the laws of quantum mechanics to generate random numbers on a Nokia N9 smartphone, a breakthro…
This work looks genuinely interesting for cyber-security. Using inherently quantum processes (generating photons and recording the number entering each pixel detector) has been shown to be able to produce random numbers. The tests to check how “random” such number strings are, appear to be very convincing.
It wouldn’t be a huge step to imagine this technology implemented within new range of mobile phones, as well as within specific tools for banks (such as those used often by banks for users to access their online services) and governments (to encrypt information).
The linked article gives a very interesting review.
The Large Hadron Collider beauty (LHCb) collaboration today announced results that confirm the existence of exotic hadrons – a type of matter that cannot be classified within the traditional quark model.
Following on from the excitement of the IOP conference, the LHCb experiment at CERN has today released results which appear to conclusively reveal a four-quark state of matter in the Universe.
This resonance had been seen back in 2008 by the BELLE Collaboration, and LHCb has unambiguously confirmed that the resonance is a particle with four quarks inside. This confirmation is very important as it has been found by two independent groups and datasets.
Our current understanding of hadrons, that is to say bound quark states confined by the nature of the strong nuclear force, is that they are composed of a quark-antiquark pair (meson) or are composed of three quarks (or three antiquarks) (baryons). This state of matter has been shown to have four quarks which will either hint at a bound state of two mesons, or some hitherto undefined state of two quarks and two antiquarks bound together by the strong nuclear force.
The interesting result here is that the quark structure has been probed by LHCb to show the particle consists of a charm, an anti-charm, a down and an anti-up quark.