[Hps-analysis] Vertex Chisq Probability Cut?

Thu Jan 31 12:24:03 EST 2019

Great!  Thanks Maurik.

On Jan 31, 2019, at 10:20 AM, maurik <maurik at physics.unh.edu<mailto:maurik at physics.unh.edu>> wrote:

Matt, Norman,

I started iss398 branch and am testing the code right now. It seems to be passing the Integration tests.

I will process an EVIO file locally and send it to Jlab or SLAC. Let me know where to put that at SLAC.
Should have it available at the end of the day for testing.

Best,
Maurik

On Jan 31, 2019, at 12:06 PM, maurik <maurik at physics.unh.edu<mailto:maurik at physics.unh.edu>> wrote:

Thanks Miriam! That is really helpful.

I am going to start an issue with a new branch, just to suggest how we could modify this part of the code so the chisquared check is ONLY on the UNCONSTRAINED vertexes. If it passes the unconstrained vertex, then all versions of constrained are written out.

- Maurik

On Jan 31, 2019, at 11:49 AM, Diamond, Miriam <mdiamond at slac.stanford.edu<mailto:mdiamond at slac.stanford.edu>> wrote:

It is indeed part of the MOUSE cuts: MinVertexChisqProb.  The cut value can be set via <https://na01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2FJeffersonLab%2Fhps-java%2Fblob%2Fmaster%2Frecon%2Fsrc%2Fmain%2Fjava%2Forg%2Fhps%2Frecon%2Fparticle%2FReconParticleDriver.java%23L395&data=02%7C01%7Chps-analysis%40jlab.org%7C06d1e9c195364f24a69908d687a0e912%7Cb4d7ee1f4fb34f0690372b5b522042ab%7C1%7C0%7C636845522506496288&sdata=dMvs1TTNJGfoGwH9W4WfOeilgnEnG4FGXJMWm1Xck3Q%3D&reserved=0>
https://na01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2FJeffersonLab%2Fhps-java%2Fblob%2Fmaster%2Frecon%2Fsrc%2Fmain%2Fjava%2Forg%2Fhps%2Frecon%2Fparticle%2FHpsReconParticleDriver.java%23L281&data=02%7C01%7Chps-analysis%40jlab.org%7C06d1e9c195364f24a69908d687a0e912%7Cb4d7ee1f4fb34f0690372b5b522042ab%7C1%7C0%7C636845522506496288&sdata=VeC99ZTPpp%2F8amIiDkewvk9QZei9KVhtmmP5zOVlUf0%3D&reserved=0<https://na01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2FJeffersonLab%2Fhps-java%2Fblob%2Fmaster%2Frecon%2Fsrc%2Fmain%2Fjava%2Forg%2Fhps%2Frecon%2Fparticle%2FHpsReconParticleDriver.java%23L281&data=02%7C01%7Chps-analysis%40jlab.org%7C06d1e9c195364f24a69908d687a0e912%7Cb4d7ee1f4fb34f0690372b5b522042ab%7C1%7C0%7C636845522506496288&sdata=VeC99ZTPpp%2F8amIiDkewvk9QZei9KVhtmmP5zOVlUf0%3D&reserved=0> .; you could essentially disable it by setting it to 0.

The cut is applied here: https://na01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2FJeffersonLab%2Fhps-java%2Fblob%2Fmaster%2Frecon%2Fsrc%2Fmain%2Fjava%2Forg%2Fhps%2Frecon%2Fparticle%2FHpsReconParticleDriver.java%23L626&data=02%7C01%7Chps-analysis%40jlab.org%7C06d1e9c195364f24a69908d687a0e912%7Cb4d7ee1f4fb34f0690372b5b522042ab%7C1%7C0%7C636845522506506285&sdata=wr1Fob6Dy4zPyQ9%2F6A9IfnQZeKzpwenKkWw%2F1qHfAf8%3D&reserved=0<https://na01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2FJeffersonLab%2Fhps-java%2Fblob%2Fmaster%2Frecon%2Fsrc%2Fmain%2Fjava%2Forg%2Fhps%2Frecon%2Fparticle%2FHpsReconParticleDriver.java%23L626&data=02%7C01%7Chps-analysis%40jlab.org%7C06d1e9c195364f24a69908d687a0e912%7Cb4d7ee1f4fb34f0690372b5b522042ab%7C1%7C0%7C636845522506506285&sdata=wr1Fob6Dy4zPyQ9%2F6A9IfnQZeKzpwenKkWw%2F1qHfAf8%3D&reserved=0>

There are no grave consequences to removing this cut, you'll just get more junk vertices in the lcio.

-- Miriam

________________________________
From: Solt, Matthew Reagan <mrsolt at slac.stanford.edu<mailto:mrsolt at slac.stanford.edu>>
Sent: Thursday, January 31, 2019 12:15:15 AM
To: hps-analysis at jlab.org<mailto:hps-analysis at jlab.org>
Cc: Diamond, Miriam; Nelson, Timothy Knight; Graham, Mathew Thomas; Graf, Norman A.
Subject: Vertex Chisq Probability Cut?

Hi all,

Long email, executive summary: we should remove the vertex chisq probability cut in the reconstruction. Details below.

There is a cut in the reconstruction on the vertex chisq probability, which I think is part of the MOUSE cuts, that is causing issues for displaced A's. Where has this cut been verified (specifically for displaced A's)? Plots are attached that show the following story.

There is currently a cut at 1.7e-16 for the current reconstruction which seems fine, except the distributions for the beamspot constrained and unconstrained probabilities look crazy, with bsc having a significant number events at a probability of 0 and the unconstrained distributions have events closer to 1 (I didn't check target constrained). For the same vertex, the reconstruction can write an unconstrained vertex that passes the cut, but not a bsc that doesn't pass the cut (which is definitely not what we want). This particularly effects high z events, including clean signal events, as bsc probability is highly anti-correlated with z. This is actually how I just noticed it today, while looking at displaced A's which have very few reconstructed high z events. This effect is not noticeable in either data or MC because the it really only effects high z events (both good signal and background).

What's worse is that apparently the tuple maker requires a vertex to have both a bsc and unconstrained collection, so if it doesn't have a bsc vertex it throws them both away even if the unconstrained passes the cut (not true in the lcio). I first noticed it in the displaced A' tuples (which have the default cut of 0.00001, so even worse than the data reconstruction).

What affect does this have on current pass4? It doesn't effect the core distributions much at all, which is why I didn't catch it yet. It only really affects high z signal and background (which is obviously important). The unconstrained collection is probably ok in the lcio files, it's more just the beamspot constrained collection and the ntuples.

So, why do the vertex chisq probability distributions look weird? I don't know, I haven't had time to dig that far. But since I don't think we understand this effect, and we are trying to compute our data ASAP, we should remove the cut in the reconstruction for now. If there are consequences to removing this cut, someone should speak up (Tim, Miriam, Matt, Norman?).

I hope I was clear, but I'm sure some of you will have questions. Also, if someone gets a chance, can someone verify these probability plots? Thanks.

Matt Solt
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