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Vivek Jain | USLHC | USA

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An “X-ray” of a detector– Part I

Hi everyone, This is my first post on these blogs, and I’ll start off by talking about the ATLAS detector. Let me know what you think. Hope you like it!

Vivian wrote in a previous post,

We simulate how the particles would interact in our detector. To do this we have to have a very complete implementation in software of our detector, including the positions of all the components…Even parts like the cables that bring signals from the inside of the detector out to the electronics that register the data have to be in the simulation since there is some probability that a particle will interact in the cables!

It would be bad if there was material in the detector that we didn’t know about, which threw our measurements off, or, for that matter a bug in the simulation software that did strange things with material description, leading to the interpretation of some garden variety physics effect as a new phenomenon! One can see the headlines, “Oops. Scientists retract discovery of the Higgs boson”.

We carefully account for everything that is installed, down to its weight, composition, position, etc. Remember, the ATLAS detector weighs about 7000 tons and has an extremely large number of individual components that need to be accounted for, so this is a non-trivial task. Another problem is that when you have compound materials, e.g., cables that contain plastic, wires, etc., and we have miles and miles of them snaking their way through and around the detector, it is not easy to accurately describe their properties and precisely know all of their positions. It is also possible to make a mistake while entering this information into a database, e.g., forgetting to enter some support structure or using an incorrect or approximate description, etc.

Since physicists are skeptical by nature, we want an independent way to verify the material. So, how to do this? It turns out that we can use (real) data to “X-ray’ the detector.

This “X-ray” uses a unique property of the photon (aka “the light particle”). As a high energy photon nears a nucleus in the material it is traveling through, it can convert to an electron-positron pair. This effect is known as “photon conversion”. It is the main process by which high-energy photons lose energy as they travel through matter, and the likelihood of a photon converting depends on the material, both the amount and its intrinsic properties, that it is passing through.

In order to convert at all, (a) energy conservation requires that the photon have at least as much energy as the combined mass of the electron and the positron, and, (b) a photon, being massless, has to be near a nucleus.

The likelihood of photon conversions is quantified by a property of the material called the “radiation length” (this quantity also determines how electrons lose energy as they travel through matter); among other things, this variable depends on the atomic weight and atomic number of the element. When you have a compound material, it can be hard to estimate a value for the radiation length, and conversions provide us with an independent measure.

So, when photons encounter denser material, they undergo more conversions, and if we detect these electron-positron pairs, we can get an “X-ray” of the material in the detector. And there will be plenty of high-energy photons in our data.

Using our software, we first identify electron and positron candidates and then check if they come from a common point in space; the latter step also needs sophisticated algorithms. If they do meet at a common point in space, we form a vertex (in 3 dimensions). By looking at the position and the number of these vertices, in both simulation and data, we can decide how well the former mimics the latter.

We are also working on a complementary way to map the material using pions, protons, neutrons, kaons, etc. More about that and other details in a later post!