[Hps-analysis] Vertex Chisq Probability Cut?

Thu Jan 31 13:49:36 EST 2019

I think I agree with Norman here, that I don't really trust the probabilities now even if it's a simple calculation. Has anyone studied the value in detail? I'm not sure how much data this gets rid of right now, my guess is not a lot. The cut itself is already pretty loose at 1.7e-16, but I don't really know what vertices this gets rid of. I would feel more comfortable if this cut were removed. But if someone shows me that it has been studied and doesn't cut into displaced signal much, I would be happy to keep it in.

I do, however, like Maurik's change that that cut only should apply to unconstrained so that every vertex is guaranteed one type of constraint (whether we apply that cut now or in the future).

Matt Solt

________________________________
From: Graf, Norman A. <ngraf at slac.stanford.edu>
Sent: Thursday, January 31, 2019 10:32:42 AM
To: Solt, Matthew Reagan; Graham, Mathew Thomas; Maurik Holtrop
Cc: Diamond, Miriam; hps-analysis at jlab.org
Subject: Re: [Hps-analysis] Vertex Chisq Probability Cut?

I, for one, don't trust the current chi-squared values for the vertices (nor for the track. And to be honest I'm suspicious about the hit uncertainties, too.) So unless it's a yuge number of vertices that this cut is eliminating I would prefer to loosen/eliminate this cut and try to understand what those vertices are.

Norman

________________________________
From: Solt, Matthew Reagan <mrsolt at slac.stanford.edu>
Sent: Thursday, January 31, 2019 10:11 AM
To: Graham, Mathew Thomas; Maurik Holtrop
Cc: Diamond, Miriam; hps-analysis at jlab.org; Graf, Norman A.
Subject: Re: [Hps-analysis] Vertex Chisq Probability Cut?

Thanks Maurik and Miriam,

I think only having the cut on unconstrained, and writing out other collections based on that, is a viable solution. As long as we trust the unconstrained chisq probabilities enough to do this, which I have never looked at before yesterday. But, the question is do we?

Matt Solt

________________________________
From: Graham, Mathew Thomas <mgraham at slac.stanford.edu>
Sent: Thursday, January 31, 2019 9:24:03 AM
To: Maurik Holtrop
Cc: Solt, Matthew Reagan; Diamond, Miriam; hps-analysis at jlab.org; Graf, Norman A.
Subject: Re: [Hps-analysis] Vertex Chisq Probability Cut?

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%7C0be17faa75a340548c5108d687acdc16%7Cb4d7ee1f4fb34f0690372b5b522042ab%7C1%7C0%7C636845573833733472&sdata=hvYu0vPEzmyqpyQwVtDN1%2BzDsnoK%2FUyJd6Bu%2Fy37zHE%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%7C0be17faa75a340548c5108d687acdc16%7Cb4d7ee1f4fb34f0690372b5b522042ab%7C1%7C0%7C636845573833733472&sdata=s9iAEpYEAbaBtLND4nqqHCvdHK3Q5Pj6N3nfZoQzRew%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%7C0be17faa75a340548c5108d687acdc16%7Cb4d7ee1f4fb34f0690372b5b522042ab%7C1%7C0%7C636845573833733472&sdata=s9iAEpYEAbaBtLND4nqqHCvdHK3Q5Pj6N3nfZoQzRew%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%7C0be17faa75a340548c5108d687acdc16%7Cb4d7ee1f4fb34f0690372b5b522042ab%7C1%7C0%7C636845573833733472&sdata=YNzXb6FFP2ULu8wAiRmXdafkUrihwhavrtTv36UoNY8%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%7C0be17faa75a340548c5108d687acdc16%7Cb4d7ee1f4fb34f0690372b5b522042ab%7C1%7C0%7C636845573833733472&sdata=YNzXb6FFP2ULu8wAiRmXdafkUrihwhavrtTv36UoNY8%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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