Understanding Neutrino Interactions with Liquid Argon Time Projection Chambers (LAr TPC)

                                                                                           Cristian Gaidau

                                                                      Supervisors:  Dr. Tim Bolton, Dr. Glenn Horton-Smith and David McKee

                                                                                                                                      Kansas State University

                                                                                                                                            Physics REU 2010


This program is funded by the National Science Foundation through grant number PHY-0851599.

Hi, this is my project webpage. This page summarizes my research experience during Summer 2010 at Kansas State University in the high energy physics group.


Summary Statement

The neutrino is the least understood fundamental particle. It has a very small mass and currently is the lightest known particle. Neutrinos come in three types (flavors): electron neutrino, muon neutrino and tau neutrino. Neutrinos rarely interact with ordinary matter and because of their tiny masses it is difficult to study their properties. Previous experiments have shown that neutrinos are able to change their flavor. This process, called neutrino oscillation, has become the focus of extensive theoretical and experimental research because it was not initially predicted by the Standard Model, which is currently the most successful framework that describes the physical world at the sub-atomic scale. Studying this “beyond the Standard Model” phenomenon is important because it may lead to the discovery of new physics and help scientists to reach a deeper understanding of the Universe.  



My work lies in the domain of experimental neutrino physics, particularly the MicroBooNE detector, which is currently in the development stage. MicroBooNE is part of a series of experiments which will use the Liquid Argon Time Projection Chamber (LAr TPC). The advantage of LAr TPC’s is that they provide a high resolution – comparable to the resolution of bubble chambers – which will allow an efficient identification of particle tracks and discrimination of events. The challenge associated with using LAr TPCs is that this is a relatively new technique, which means that it has to be carefully studied, before being implemented in large scale detectors. Also, there are certain engineering aspects associated with operating a large volume of cryogenic liquid. In this respect, MicroBooNE serves as an intermediate step between prototype LAr TPC detectors like ArgoNeuT and large scale LBNE (Long-Baseline Neutrino Experiments) that will be built in the future.

The active volume of MicroBooNE consists of  ̴ 100 tons of liquid argon and it will study the neutrinos from the Booster Neutrino Beam (BooNE).The primary goal of the experiment is to investigate the low energy domain of neutrino interactions.


Further Reading

For general reading, these Wikipedia articles are a good start: The Standard Model, Neutrino Oscillations.

This paper is specifically about neutrinos and the current state of affairs in neutrino physics.

I also recommend these textbooks:

“Introduction to Elementary Particles” by David Griffiths.

“The Experimental Foundations of Particle Physics” by Robert Cahn and Gerson Goldhaber, 2nd Edition.


Project Goals:  To construct a hand-scanning systematic procedure for efficient identification of CC (Charged Current) νe events and discrimination of CC νµ and NC (Neutral Current) ν     
                              To test the efficiency of this algorithm. 


Research Strategy

The first step is to become familiar with the characteristic tracks produced by the most common particles created in the neutrino interaction simulations, such as: protons, neutrons, muons, electrons, photons, charged pions and neutral pions. The most important properties of the tracks are: presence or absence of an electromagnetic shower, energy deposition, typical length and shape of the track, signature of any secondary particles.        

The second step is to understand the specific trademarks of the three types of interaction:  CC νe ,CC νµ and NC ν , in the three different scattering modes: quasi-elastic (QE), resonant (RES) and deep inelastic (DIS).

Next, one needs to hand-scan a certain amount of events (I went through  ̴  100 events), in order to gain the experience of event classification. The efficiency of the hand-scan can be evaluated by comparing hand-scanner’s identification of the event to the correct description of the event, which is contained in the truth-view display of the software. Based on this experience, we should be able to formulate a number of consecutive steps which are aimed at rejecting all the events except CC νe . This set of steps constitutes the systematic procedure of event classification.

Finally, we need to hand-scan another set of events by using this procedure. This set of events should be simulated with the configurations of LBNE, in order to be close as possible to the actual beam that will be used in MicroBooNE. Comparing the results of the hand-scan with the information contained in the truth-view display will give an estimate of the efficiency of the algorithm.


Research Progress

Week 1: Introduction to the MicroBooNE experiment. Learning about the theoretical aspects of neutrino interactions and the software that we will use in the simulations and hand-scanning.

Week 2 and 3: Generating and analyzing single particle events (Step 1 of the research strategy) using Monte Carlo simulations with the geometry of the MicroBooNE detector.

Week 4 and 5: Analyzing Monte Carlo Simulations of neutrino events (geometry of MicroBooNE) in truth-view.
                        A brief look at simulations with the ArgoNeuT geometry.  

Week 6:  Examined CC QE νµ, CC RES νµ, and CC QE νe neutrino events. First hand-scanning attempts.

Week 7: Analyzing the NC RES ν, NC DIS ν and all channels of CC ν interactions. The first steps of the algorithm were devised. Hand-scanning procedure in progress.

Week 8: Completed the development of the algorithm. Started the efficiency test. The test was performed on neutrino events which were simulated using the configuration of the LBNE beam.

Week 9: Finished the efficiency test. Presented the hand-scanning results as part of the MicroBooNE collaboration meeting at FermiLab. 

Week 10: Working on the final presentation and project report.


Final Presentation: Download the presentation in pdf format.

Final Report: Download the final report in docx or pdf format.

I have worked on this project with Alexander Yeagle. You can view his webpage here.

About Me: I was born and grew up in Chisinau, Republic of Moldova. I am a rising junior, double majoring in physics and mathematics, at the University of Minnesota Twin Cities. I am primarily interested in theoretical particle physics and abstract mathematics. 

Contact: cristi2206@gmail.com

Sponsored by:  National Science Foundation (grant number PHY-0851599)Kansas State University Physics Department  

Useful Links: 

Physics REU Program at Kansas State

American Physical Society Statements on Ethics

American Institute of Physics                                                                                                                                                                                               

University of Minnesota


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