Julie Hogan: To the next lesson.
Julie Hogan: So let me get my screen share up.
Julie Hogan: Okay, I think you're seeing my web browsers with the basic physics objects lesson.
Julie Hogan: And let me get all of your faces back on my other screen, so I can see hands that are raised and things like that okay.
Julie Hogan: super so.
Julie Hogan: You had a couple of pre exercises a couple of pre exercises related to physics objects, you went through some background information that we had on the cms website, the cms dot certain site about.
Julie Hogan: electrons photons I can we add links there for some nuance and projects and we talked a little bit about the the particle flow process, which is how cms takes detector information and reconstructs things that we recognize as as particles and so we're going to follow off of that.
Julie Hogan: we're going to fall off of that and we are going to take an actual dive into the software platform.
Julie Hogan: That we have put together as our example framework, so this is what we're going to what is going to follow us through the rest of the workshop.
Julie Hogan: For actually working with these ao D files and processing them so that you, the user could do some analysis on particles that you're familiar with.
Julie Hogan: So we're going to blitz a little bit here's our here's our schedule.
Julie Hogan: we're going to get down to the break in the next 45 minutes so we're going to start by looking at this tool, which I have up here in the github.
Julie Hogan: web page that you can see, and then we're going to kind of step through those physics objects again that you learned about and talk about some of their specific software features.
Julie Hogan: And then, after the break when we do hands on will run some things will investigate histograms and so will actually will actually do some hands on exercises.
Julie Hogan: Okay, so let's let's get started we're going to talk about first the physics object extractor tool which is a tool, so that you can extract physics objects and their information from the cms route files into a format that's a little bit more human understandable.
Julie Hogan: And so, as you learned in the pre exercise when we say physics object we're speaking very broadly and we mean almost anything.
Julie Hogan: That would represent a particle in the cms detector nuance electrons TAOs photons jets missing transverse momentum.
Julie Hogan: Which is is on the bucket that we unfortunately have to stick all of our neutrinos or dark matter particles or supersymmetric partner lightest supersymmetric partners or all of those good things in that bucket.
Julie Hogan: So.
Julie Hogan: What we're what we've already learned is how to find the information about some of these different objects in the data file, so this first panel here on the lesson page you've already seen we've just talked about this with matt the output of an edm dump event content.
Julie Hogan: And so you know if in doubt, the first thing I would do would be to look and see you know, can I can I if i'm interested.
Julie Hogan: In you once I find something in here that's just called nuance and maybe it's c++ class type looks like it might be a new one.
Julie Hogan: that's that's going to be a promising place for me to begin for this physics object and the tool here will teach you which ones are kind of the basics, the defaults that you should go for.
Julie Hogan: So we've learned how to list out objects in the file and all of the physics objects that you wouldn't want to extract using the tool can be found in these eod files.
Julie Hogan: So let's jump to the actual poet tool we have a happy accident in the acronym here so i'll refer to this tool as poet.
Julie Hogan: And here is the link which brings you to the github page that you can see, on the screen here.
Julie Hogan: So if you have this is the setup material for this part of the lesson is basically to go into your container So if you still have your virtual machine or your container open i'm going to start mine, you can go into yours or start it.
Julie Hogan: And we land in the cms sw five area where we need to be.
Julie Hogan: So what i'm going to do is clone.
Julie Hogan: The physics object extractor tool.
Julie Hogan: whoa.
Julie Hogan: not like that.
Julie Hogan: i'm gonna hit copy first and then I will paste it in.
Julie Hogan: So we can clone the physics object extractor tool and go into this folder that it's produced.
Julie Hogan: And now you guys have access to all of the code that we're getting us today and i'll show you things on github, which is a little bit easier to read, but i'll go ahead and set this to compile while we talk about the features of this song.
Julie Hogan: Okay, so one of the other important things you learned about in the pre exercises, that this is building on is the idea of an EDI analyzer.
Julie Hogan: So the physics object extractor tool is set up using a series of ED analyzers and they all live here in the source.
Julie Hogan: folder so we've got 10 ish 15 of them all different ED analyzers and you can see that they correspond to different physics objects electrons jets nuance photons towels etc.
Julie Hogan: So I always like to start thinking about my ED analyzers from the inside out maybe I like to look at the at the source code first.
Julie Hogan: So we're going to look at new on analyzer kind of as our example and here in the lesson page i've pulled out some specific lines that are just a refresh on the ED analyzer system for the accessing a certain type of object.
Julie Hogan: So if i'm interested in analyzing nuance I actually I need to access from the cms software stack all of the information about the new on class that exists, by including including these c++ header files.
Julie Hogan: And then you learned about the analyze function so i'm going to skip over the constructors and look straight at the analyze function.
Julie Hogan: Which is the function that's called on every event.
Julie Hogan: In this cms system you file.
Julie Hogan: And so, for every event, this is basically a duplicate of what you had in your DEMO analyzer in the pre exercise, where we are opening we're opening a collection and, in this case we're going to call it my new ons.
Julie Hogan: And we're going to use our configuration file for this ED analyzer when you use this configuration idea, so that we can tell a different file the specific name of the new on collection, we would like to open.
Julie Hogan: button this line, right here will get the nuance for us out of the event.
Julie Hogan: and the last thing i'll highlight for you again, this is a refresh from the from the cms sw pre exercise if.
Julie Hogan: That worked and we actually got some new ones from that get by label command, we can loop over them and we can do whatever we want to do, using all of the Member functions that exist up for a new on.
Julie Hogan: In cms sw.
Julie Hogan: So that's the super broad overview refresh of how to work with one of these ED analyzers and this structure repeats itself in all of the other analyzers that you saw in the in the folder that.
Julie Hogan: So what's, the first thing that we actually do with these new ons, the first thing that we actually do is store there for vector information.
Julie Hogan: This is, you know, especially if you're coming from let's say a theory background, these are these are Member functions that that will probably be immediately recognizable to you and comforting to you.
Julie Hogan: This is this is information that you're that you're used to pulling out, so we can access energy momentum in the plane that's transverse to the colliding beings extraction why directions, the direction if that's your preference for a coordinate system.
Julie Hogan: angles two angles sooner rapidity, and the azimuth whole angle.
Julie Hogan: And we can actually even ask for charge and mass of these objects.
Julie Hogan: And the reason I wanted to point this out first is because these are completely common these the format of these Member functions here like the spelling the capitalization.
Julie Hogan: Is not special to nuance This is something you can do for electrons for jets for towels for any any cms reconstructed object So those are common features for all of our physics objects.
Julie Hogan: Okay.
Julie Hogan: The last thing I want to look out before we take a tiny pause for for questions is how we configure the physics object extractor.
Julie Hogan: So i'm going to come back to the Python folder.
Julie Hogan: And i'm going to look at the only file inside the Python folder, which is our poet that configuration file.
Julie Hogan: And you saw examples of this in your pre exercise about how to configure a one of these configuration files, we have a couple of the command line arguments actually which are described here in the comments.
Julie Hogan: And here, is where we're going to define the name of the art process, so we were talking about this in the last lesson the process called Sim the process called Rico we're going to have a process here called poet.
Julie Hogan: And so that's that's what we're going to call everything we're about to do.
Julie Hogan: And after we set up some things for input files and and sort of the standard cms tools that we need to run like global tags that you've learned about.
Julie Hogan: Then we start to actually configure all of the physics object extractor modules and what we care about right now are the new ones.
Julie Hogan: So here we go process up my new ones, we can tell it which ED analyzer we're going to run and the only piece of information, we need to configure for this ED analyzer is which input tag.
Julie Hogan: to grab out of the file, which is based on our edm dump event content from up here new ones, there we go.
Julie Hogan: Now, just in case I added a note here, just in case you're opening, something that has where there's multiple identical names, you can actually get more specific.
Julie Hogan: Here you can you could say nuance colon some specific label Colin some specific process if you needed to be more specific, in the name of the collection, that you open.
Julie Hogan: So at this point let's see my poet, was able to compile if yours happens to be in a similar state, you could try to execute this line, just to see as we go through the next couple of pages see if we run successfully.
Julie Hogan: So, in order to run our physics object extractor tool.
Julie Hogan: We need to call cms run Python poet config.pi and if we choose to we can give that to command line arguments so i'm going to choose to run on simulation, which is the default.
Julie Hogan: And i'm going to choose to use this setting for the physics analysis tool kit which we're going to talk about a little bit later, so you can choose whatever, oh no.
Matthew Bellis: Julie, I think the Python directory is in physical objects extractor.
Julie Hogan: So that I need to go in either point more specifically or go inside this folder.
Julie Hogan: So la.
Julie Hogan: Have the joy of click down so that my.
Julie Hogan: And i'll use tab complete so that I know it knows where I am.
Julie Hogan: There we go.
Julie Hogan: Okay, so if you see anything remotely like this that's a great sign and, if not obviously you can post in the matter most channel, or we can try to help you out.
Julie Hogan: So let's briefly pause it does anyone have questions.
Julie Hogan: that have not already been answered, I will try to find the chat in my screen here.
Julie Hogan: Okay, I don't see any hands raised immediately so let's carry on while that runs.
Julie Hogan: electrons and photons are the are the next block that I want to look at.
Julie Hogan: So for electrons and protons and again this is going to be a little bit of a blitz of of information which will come back to you in the hands on exercise.
Julie Hogan: For electrons and protons we have two important and ED analyzers we have an electron analyzer.
Julie Hogan: And we have a photon analyzer.
Julie Hogan: And their setup very similarly.
Julie Hogan: So i'm going to open the electron analyzer to begin with i'm going to scroll down past the declarations and the constructors to the analyze function.
Julie Hogan: Because that's where we'll we'll do our interesting work.
Julie Hogan: Okay.
Julie Hogan: So here's proof of what I just said, being true.
Julie Hogan: The for vector information for electrons happens right here.
Julie Hogan: So as we're looping over electrons we happen to put this near near the bottom of the of the.
Julie Hogan: analyze loop rather than at the top, but we have all of the same for vector access functions that we saw for nuance energy.
Julie Hogan: transverse momentum xyz Ada and fi angles chart and charge we've decided not to we're not interested in storing the mass here for electronics, but you certainly could.
Julie Hogan: So all of those are the same, and then we have a lot of branches, that you can see that we're saving that are custom to electronic electrons.
Julie Hogan: And one of them that I want to point out, has to do with the electron track.
Julie Hogan: So this is something that we have access to for are charged particles.
Julie Hogan: We have access to the track in the innermost layers of the cms detector that actually appointed to the electromagnetic shower that we've identified as being from an electron, and so we can ask for.
Julie Hogan: We can ask this electron for its associated goshen some filter track workout and some filter is the name of the algorithm that is used to build the track.
Julie Hogan: This is on the lesson page if it's easier for you to keep track of.
Julie Hogan: Because, sometimes we have other code lines in between the the important things, so, if you prefer to look at the code snippets on the lesson page they've been slimmed down a little bit compared to compared to the actual.cc file that you see in your area or here on github.
Julie Hogan: So we can ask an electron for its track, and then we can ask that track.
Julie Hogan: For some information and one most important piece of information, we can ask from the track is how it how closely.
Julie Hogan: It interacted with this primary vertex so the color the actual proton proton collision vertex that we've identified as the hard physics process in this event.
Julie Hogan: We can ask the track how far away, is your is your distance of closest approach in the transverse plane, the XY plane.
Julie Hogan: And we can ask the same question along the beam line, so we can ask in the circle around the beam line or along that being line, how far away, was the impact parameter of this track.
Julie Hogan: And both of those things have uncertainties, so these quantities are very important for asking questions like is this electron associated with this collision vertex was it produced immediately.
Julie Hogan: effectively in the collision maybe from the decay of a very, very short lived particle or or did it come from some other source.
Julie Hogan: The other sections that we have here so that takes care of these variables that we've looked at and also these here at the bottom so what's left in the middle.
Julie Hogan: what's left in the middle here is is stuff thats related to the electronic itself and how it interacted with the cms detector.
Julie Hogan: So we have one branch that we're saving for isolation which we'll talk about what that means, and then we have some.
Julie Hogan: quality levels loose medium and tight quality levels for electronic identification, so the idea here is that.
Julie Hogan: Whenever we observe something in cms that we're declaring this is an electron that's a statement that's subject to doubt and we try to do our best to make that doubt small.
Julie Hogan: But we can always apply different criteria to get more and more and more and more sure that this is actually an electron as opposed to let's say a photon or some sort of detector noise.
Julie Hogan: And we typically name those sets of criteria that get us more and more and more sure of what we're looking at.
Julie Hogan: With with names like loose too tight so loose is very is is a set of criteria that's that's quite accepting so we're pretty sure that all the real electrons will end up in this list of things that are loose.
Julie Hogan: But we may also grab some non electrons in loose.
Julie Hogan: In contrast to that sets of criteria that we call tight we've chosen to be more picky.
Julie Hogan: were chosen to be more picky so that we're we're much more confidence that anything we've labeled tight is really an electron.
Julie Hogan: And this might come at the risk of missing, some of them there may be some genuine electrons that we, we do not consider in further in the analysis, because they didn't happen to pass these criteria.
Julie Hogan: So it's a trade off and will store the information for multiple what these are called a working points multiple points at which we could work with our electrons.
Julie Hogan: And so that's what all this messy stuff is up here all all of this, that you're seeing on the github page is in is is to calculate those.
Julie Hogan: Flags those true false labels so i'm going to come back over here to the lesson page.
Julie Hogan: And the text here describes what I just tried to say in words about the idea of a loose a tight identification for for objects.
Julie Hogan: And the links here that you see take you to the public web pages, or you can find the actual information that we use to write these lines of code that are in github.
Julie Hogan: So, in the interest of time i'm not i'm not going to like try to read through any of this, you can come back and look at this on your own later, but you can see that what we're working with here is a set of flags, so we have a set of true false flags.
Julie Hogan: And then, if some huge set of criteria are all true, we would call this electron loose.
Julie Hogan: Further if another set of criteria are true, we call it medium and further if another set of criteria are true we'd call it tight so we're we're can successively applying more and more restrictive criteria to decide whether this electronics loose or medium or tight.
Julie Hogan: And each one of these if questions is just is looking at some quantity that.
Julie Hogan: relates to how the electron has interacted with the cms detector and particularly with the electromagnetic cal perimeter so.
Julie Hogan: i've laid out a little description of what each one of these criteria are that you can look through so that you can kind of understand what what features of the detector we're using to make decisions.
Julie Hogan: The very last one in the list isolation.
Julie Hogan: we'll talk about a tiny bit more isolation is important for all our particles, not just for electrons we use it for most particle physics objects and cms.
Julie Hogan: And so isolation is basically it's easy to understand conceptually, the idea is, if I have an electron let's say the electron has been directed straight up on my screen how much energy from other particles, is in a Cone around my electron.
Julie Hogan: Is it a large fraction of the electrons energy is it a small fraction of the electrons energy and this the numbers that we get for that question.
Julie Hogan: Point us to different physics answers for how this electron was produced an electron that's basically on its own in space was probably produced in the decay of some you know interesting particle and maybe a top court movie as he goes on, maybe a higgs boson.
Julie Hogan: An electron that is buried in a cloud of a whole bunch of other particles is probably not from such a decay it's probably something that's been produced oh by had ron's had drones having having weak force decays as they as they move through the material of the protector.
Julie Hogan: And so what we'll see a couple of times our functions like this for isolation will be looking at charged hydrogens which was one of our particle flow labels, if you if you recall the pre exercise will be looking at neutral had drums.
Julie Hogan: And photons.
Julie Hogan: And we'll be subtracting off a contribution from all of the from all of the neutral background the energy that we expect to live in the detector without being caused by this proton collision and that's where that row variable comes in that we mentioned before.
Julie Hogan: So all of this code here is in is in the effort to calculate these few variables that we store here for each electron.
Okay.
Julie Hogan: photons are very similar we haven't looked at the photon analyzer but as electromagnetic calories are objects, you can imagine they're quite similar to electrons in all of their in all of their functions.
Julie Hogan: So i'm gonna hop to the next page.
Julie Hogan: Which is a little more information for nuance and for TAO leptons.
Julie Hogan: Most important, perhaps on this lesson page or those links so just like we had for electrons and photons, these are the links to the cms reference pages that are publicly accessible that have a lot of the detailed software information, you might need.
Julie Hogan: And so we talked about nuance in terms of their four vectors already let's look at what else is there.
Julie Hogan: new ones are also charged particles.
Julie Hogan: So we can also access a track.
Julie Hogan: that's associated to these neurons, and so we can ask them you on for its associated track it looks a little bit different than the electron track Member function but it provides us with the same type of object, with a track object.
Julie Hogan: And so, if if that track, you know was found, we can ask for the impact parameter and its uncertainties, just as we did before the electron.
Julie Hogan: Now what's really nice about nuance you'll notice, this is a much shorter code snippet than we just saw the electron analyzer there's not anywhere near as much stuff here.
Julie Hogan: And that's because the new on group and cms has already put together their list of detector criteria and they have wrapped it up into one member function, where we can simply ask is tight new one.
Julie Hogan: Is soft me on There are a variety of different identification working points loose medium tight, just like we saw for electrons but all we have to do is ask for the flag from the new on the object itself.
Julie Hogan: With the caveat that we have to actually tell it which vertex we're interested in, as the primary vertex for this event because some of the new on.
Julie Hogan: Identification criteria in terms of the detector information they're interested in they're interested in the nuance relationship to that vertex.
Julie Hogan: So here's two examples of accessing identification information from the new on and they're no much simpler and more compact but we'll dig into them a little bit more in the hands on exercises.
Julie Hogan: And so, lastly, for nuance we can calculate that isolation.
Julie Hogan: And so here's a set of functions that look almost identical to what we saw before some charged hadron energy.
Julie Hogan: Some neutral hadron energy and some photon energy, all of this in a Cone around the new on and we're basically asking the question how much.
Julie Hogan: How much energy is there nearby arm you on to decide whether it's living by itself it's isolated in the detector or it's very near to a lot of other energy deposits in the detector.
Julie Hogan: Okay, real quickly i'm going to show you the towel analyzer.
Julie Hogan: So, mostly so that you start to see the common features again i'm going to scroll down to the analyze function.
Julie Hogan: and
Julie Hogan: This one is even shorter because TAOs do the exact same thing the TAO group and cms has coded up all of their criteria.
Julie Hogan: for identifying towels from different sources and towels it different quality levels into flags that we can just access so here's all the for vector information as promised it's exactly the same as before, and here is.
Julie Hogan: A whole list of identification algorithms.
Julie Hogan: This looks a little bit different because basically these guys live in another collection so we're using this operator notation and we're using an index for how far into the list of towels we are.
Julie Hogan: And every time we do that we're accessing one of these input tags.
Julie Hogan: we've seen the input tags before in our ED analyzer configuration files we've seen the input tags in.
Julie Hogan: For me, for nuance and for other things here we're actually opening some directly, without making them configurable and we'll look in the hands on exercises at what some of these labels meeting.
Julie Hogan: Okay, how close Am I to running out of time, I think we have about seven more minutes in this session.
Julie Hogan: So.
Julie Hogan: we're going to look quickly we're going to pass by unfortunately we're gonna pass by this information about generator little particles, I encourage you to look back over that, as you have time in the homework.
Julie Hogan: And we're going to take a peek.
Edgar Fernando Carrera Jarrin: 10 more minutes or 1012 minutes, that means it's 35.
Edgar Fernando Carrera Jarrin: Okay perfect.
Julie Hogan: Okay.
Julie Hogan: So.
Julie Hogan: let's take a look at our last big chunk of objects which is jets and missing transverse energy.
Julie Hogan: So.
Julie Hogan: we've talked about the leptons in a very in a very broad in quick way we've talked about electrons in new ones and towels we've talked conceptually about photons they're very similar to electrons in all of the software features.
Julie Hogan: And so now, what we need to do, or is move over to the hadron side and so let's talk a little bit about jets.
Julie Hogan: jets.
Julie Hogan: Is.
Julie Hogan: high energy physics experiment language for a Cork was here.
Julie Hogan: Where I had drawn something made out of corks.
Julie Hogan: And, and what they look like in the detector are large showers of particles, so we have spatially grouped collections of long lived particles.
Julie Hogan: By long lives, I mean they can traverse the cms detector before they decay, if they are not stable and and they tend to be produced in the hybridization process of either a Cork or glue on.
Julie Hogan: And we can look at this group, this collection of particles to infer the energy and momentum properties of the initial particle that produced it.
Julie Hogan: And we have a makeup you know there's there's because of the hybridization process there's going to be a different.
Julie Hogan: particles of different types, we have a charge had drones and large in large percentage, but there will always be some photons.
Julie Hogan: We produce a lot of neutral pions and they decay quickly to photons, so there are always a bunch of photons in jets and perhaps other neutral hydrophones as well.
Julie Hogan: We almost never in cms analyze these particles, one by one, because there's hundreds of them so so we, we have no real good way to to break.
Julie Hogan: to reconstruct all the way back to that initial corporate glue on week and we have to use this conglomerate object to do our analysis of how that quarter go on behaved as it left the collision.
Julie Hogan: And so we have to make choices when we've got a messy system with many particles, we have to make choices about how which ones we're going to group together and how we're going to define the conglomerate object.
Julie Hogan: And this is done in a clustering process.
Julie Hogan: This clustering process is not specific to cms so we do use the the fast jet package we use the anti katie algorithm if that name means something to you, then you know exactly what we're talking about.
Julie Hogan: So we use these algorithms that are that are known in the Community to view our jet clustering.
Julie Hogan: what's unique to cms a little more is that we cluster from particle flow candidates and when we have clustered particle flow candidates, we call the resulting jets PF jets, which is a label you'll see in our software.
Julie Hogan: And so the clustering process.
Julie Hogan: The short form, is that you start with all the initial particles and you combine particles that are very close together in an iterative sequence.
Julie Hogan: Subject to these two functions, so we calculate this quantity D which real life depends on the momentum and the separation of the particles and then we have a condition for the magnitude of D that tells us when to keep going or when to stop our our clustering.
Julie Hogan: And so, eventually, if we take all the particles in the detector and we go through this iterative sequence, we would end up with a set of JET objects in the detector OK, I see a hand up from dylan.
Julie Hogan: I don't know do I have to unmute villain.
Probably not.
Everybody should get it.
Dillon Fitzgerald: Was.
Dillon Fitzgerald: Just slow for a second yeah i'm just curious if.
Dillon Fitzgerald: When you.
Dillon Fitzgerald: offer people jets they also have access to the constituent list or do they just have the job.
Julie Hogan: And I will I.
Julie Hogan: Can I believe we can access that can set you up I don't think we've given you an example of doing that, here in the in the extractor tool, but we can we can know.
Julie Hogan: I think it was punching.
Okay.
Julie Hogan: So here's here's the picture of what that might look like in the end anti K T jets have this nice feature of the sort of mostly circular ish so they're easy to kind of conceptualize in our in our heads.
Julie Hogan: One of the things we have to think about when we're identifying jets or we're working with Jeff is, we have to think about all the energy that will end up in this region of space, so one of these colored circles.
Julie Hogan: There is there can be energy here that is caused by other proton collisions that have no association with the proton collusion we're interested in analyzing.
Julie Hogan: And if that energy is from neutral particles, we have no way of using the tracks, to help us get rid of it and so we've mentioned briefly the idea of subtracting off kind of an energy background and that's something we do very commonly for all jets.
Julie Hogan: Okay access that's what you all care about.
Julie Hogan: There are two ways to do this, there are two jet analyzers in poet, one is called jet analyzer and one is called pat get analyzing.
Julie Hogan: i'm going to focus on the path jet analyzer because this method of working with jets has a lot of benefits to it.
Julie Hogan: For the for the user you're totally free to to check out both of them and use whatever fits your needs best I think this one is a little bit more user friendly, in most cases.
Julie Hogan: So for a pat jet and and for it for a regular Rico type of JET we have all of the same suit me there's a lot of helper functions in this code.
Julie Hogan: We have somewhere eventually all of the same type of for vector access options Ada by charge.
Julie Hogan: transverse momentum energy he spy peasy all of those things same here, as they were everywhere else.
Julie Hogan: what's cool about the physics analysis tool kit jets that's what pat stands for physics analysis tool kits and we'll talk about this more actually tomorrow we're going to get more into this concept of corrections.
Julie Hogan: They have all the corrections applied for you when they're created.
Julie Hogan: And, as it says here we're going to discuss that more in the upcoming lesson, but you can see how these labels here for for things like energy mass P spy PC they're called corrected and that's what the user typically wants is whatever is the most correct.
Okay.
Julie Hogan: identification is the other thing we're talking about in this lesson so identification for jets is very similar to electrons and new ones in such in concept, there are detector related criteria that determine whether or not this looks like an actual jet from a hadron.
Julie Hogan: Or whether this looks like a jet coming from some type of noise that's what we're really interested in here is identifying the difference between physics object from some Cork, or some glue on we don't care which, at this point.
Julie Hogan: We just care that it was an actual particle as opposed to being noise or something that is not really a particle.
Julie Hogan: And we're going to dig into that in the hands on exercise, we can use the reference information.
Julie Hogan: We can use the reference information to learn about the detector criteria, and we can apply that detector criteria to calculate an idea we haven't already done it for you here because it's going to be part of the exercise.
Julie Hogan: Okay, and the very last guy which we're not going to go over I won't even click into the analyzer there are some examples here we won't be using it as heavily in this workshop.
Julie Hogan: Missing transverse momentum, or sometimes in the same transverse energy, unfortunately, is the more common afternoon we usually call this net.
Julie Hogan: Which fans directly from missing transverse energy, although it's really missing transverse momentum.
Julie Hogan: And so, this is the negative vector some of everything that happened in the event and it represents any particle that was not detected at all in our detector which completely asleep.
Julie Hogan: And so we have several ways of calculating this and correcting this according to that it represents properly all the objects observed in cms tournament.
Julie Hogan: Okay we've almost made it the very last page here, which will, which you know will work we're almost at our time, but this you looked at in a pre exercise, so the trigger information that you really need was in the pre exercise.
Julie Hogan: This page here gives you just the software mapping, how do we, how do we take what you learned in the pre exercise and actually apply it literally in in the poet tool, but it that information is here for you in this page.
Julie Hogan: There are two things that you can pull out about triggers learned about all these pads hl T underscore other stuff underscore other stuff.
Julie Hogan: So we have a way for you to provide some trigger patterns that you want the pass fail information from and you want to be freescale information from which you learned about in the exercise.
Julie Hogan: And we also have a way that you can actually pull out information about specific objects that past a certain triggers.
Julie Hogan: Decision making so, for instance, if I asked for the if I asked for the.
Julie Hogan: ahl team new 12 trigger I could figure out which one had been the new 12 which which made this event interesting to the trigger so we have those two features available for you here in the in the poet tool.
Julie Hogan: Okay.
Julie Hogan: i'm going to stop talking and this was a this was way more lecture style so we're going to take our 15 minute break.
Julie Hogan: And then we're going to come back and look at several hands on exercises where you guys can choose what you want to dig into and try this stuff out but i'm happy to answer any questions, while we begin the break here for everyone else.
Edgar Fernando Carrera Jarrin: there's actually one question about the timing.
Julie Hogan: I don't know the answer to that question off top of my head, I would have to look that up for you.
Edgar Fernando Carrera Jarrin: I have a feeling that.
Edgar Fernando Carrera Jarrin: We yes exactly.
Edgar Fernando Carrera Jarrin: Yes, guess at some point we would try to reproduce some lowly particle analysis and I believe we were trying to search for that information in I think we found it, but I have to double check.
Julie Hogan: yeah even in cms now the folks who are working on long the particle analyses, I think, do the most work of all of us, because all of our default reconstruction methods kind of assume.
Edgar Fernando Carrera Jarrin: Prompt production.
Julie Hogan: So for long winded donation tend to go to go back and dig a little deeper.
Julie Hogan: Okay, we reconvene.
Julie Hogan: For me 10 5071.
Matthew Bellis: i'm going to go ahead and stop the recording for the break and then we'll start it up again for the hands on session.