Linear regression to radii of multiple circles

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Discussion Overview

The discussion revolves around the challenge of performing linear regression on simulated muon trajectories that pass through drift tubes represented as circles. The focus is on reconstructing the most probable path of a muon using noisy radius data derived from these trajectories, with an emphasis on fitting a tangent line to the circles representing the drift tubes.

Discussion Character

  • Exploratory
  • Technical explanation
  • Mathematical reasoning

Main Points Raised

  • One participant seeks assistance in fitting a tangent line to multiple circles based on simulated muon trajectories and noisy radius data.
  • Another participant suggests using a Generalized Linear Model (GLM) with discrete measurements for each row of circles, proposing techniques like Principal Component Analysis and backward selection to manage dependencies.
  • A participant clarifies the need to fit a single trajectory at a time and expresses a desire to develop a custom algorithm for implementation on hardware, specifically mentioning the need to apply linear regression in polar coordinates using only radius data.
  • Further clarification is sought regarding the nature of the radius data, specifically whether it represents the intersection distance from the center of a drift tube.
  • Another participant confirms that the radius data corresponds to the closest point along the trajectory to the center of the respective tube.
  • A question is raised about the variables involved and the relationship being examined, specifically whether it involves angle against radii or another relationship.

Areas of Agreement / Disagreement

Participants have not reached a consensus on the best approach to apply linear regression in this context, and multiple competing views and techniques are being discussed.

Contextual Notes

There are unresolved aspects regarding the specific variables involved in the regression analysis and the exact nature of the relationship between angle and radius data.

Nick.Kallas
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Hi,
I am trying to simulate muon paths through drift tubes and I have ran into a problem performing a linear regression. I have generated simulated muon trajectories in 2 dimensions and they passes through my simulated drift tubes represented as black circles with a '+' in the center. As the trajectories passes through the tubes they leave an omnidirectional radius represented as colored circles. Each color corresponds to a different trajectory. I then take these radii and add noise to them simulating real world effects. Using these noisy radii I need to reconstruct the most probable path that the muon took.

Basically I have a number of circles that I need to fit a tangent line to. If anyone could help point me in the right direction it would be greatly appreciated.

https://decibel.ni.com/content/servlet/JiveServlet/showImage/105-24702-34909/MUON+RUN.jpg
 
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Hey Nick.Kallas.

Are you trying to fit a linear regression on your entire set of simulated data?

If this is the case, then I would suggest you use a GLM where you have discrete measurements for each corresponding "row" of circles (tubes) and in this context you will have four variables corresponding to the four rows.

Then you fit the model using a statistics program (SAS, R, whatever) and you will get an equation that fits the rows.

You'll probably find that you get a lot of dependencies (since it is a straight line) and you can eliminate the dependencies in a few ways.

The first way I would suggest is to look at Principal Component Analysis and the second way is to use back-ward selection and select the best sub-model which doesn't lose too much variability within the model.

Are you familiar with these techniques?
 
I just need to fit a single trajectory at a time, sorry for the ambiguity. I need to make my own algorithm so that I can eventually implement it on my hardware and there are also other factors this algorithm needs to take into account. So I am using a single trajectories information to recreate it that is using the information from a single color radii on this simulation.

So basically I think i just need to figure out a way to apply a linear regression in polar coordinates with only radius data. I am sort of at a loss of how to do this and any pertinent literature would even be helpful.

If you want a better idea of what I am tying to do here is our projects website.
https://decibel.ni.com/content/groups/muon-detector-nmt-senior-design-team-2012-2013
 
Just to clarify, is the radius data the intersection distance from the centre of a drift tube that it passes through?
 
the radii data is represented by the closest point along the trajectory to the center of the respective tube.
 
Sounds like this is going to look like a normal residual against the origin of the tube.

However I need to ask, what variables do you have in total and what are you trying to relate? (Is it angle against radii or vice-versa or something else)?
 

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