INTRODUCTION

Particle physics is a very interesting field as there is still so much that physicists cannot explain today. Certain phenomena have been explained by what is referred to as the “Standard Model,” but discoveries such as the evidence for dark matter and neutrino mass imply that the Standard Model is yet incomplete. The study of neutrinos could yield many answers to questions about the formation & evolution of the universe and antimatter.

Neutrinos can appear in three different “flavors”: electron neutrinos, muon neutrinos, and tau neutrinos. Much of neutrino study now focuses on the phenomenon of neutrino oscillation, that is, the capability a neutrino has to change “flavors.” They are some of the most abundant particles in the universe, yet they almost never interact with other matter, making the detection of neutrinos a very tricky process. For instance, if you hold out your hand, a trillion neutrinos will pass through it every three seconds. It is a very rare occurrence for a neutrino to interact with an atom in your hand.

In order to detect neutrinos at all, physicists must use high-intensity accelerators and large-scale detectors, some of which are located at Fermilab in Batavia, Illinois. My research this summer involved taking part in ongoing experiments based in Fermilab, specifically MicroBooNE and LBNE. Both of these projects are still in their development stage, and both will utilize what is known as a Liquid Argon Time-Projection Chamber, or LArTPC. The LArTPC is where the neutrinos will be detected -- neutrinos are injected to a large contained of liquid Argon at immense velocities and interact with the Argon atoms -- and while the neutrinos themselves are near-impossible to detect, their interactions and collisions with Argon atoms are detectable. From the information gained by studying the post-collision behaviors of different particles, we are able to determine much about the neutrino itself (e.g. what “flavor” it is).

However, a neutrino could interact with a particle in a very similar manner to how its antineutrino would interact. One of the ways of determining if an observed neutrino is either positively or negatively charged (e.g. an electron vs. a positron) is by employing the use of a magnetic field inside the LArTPC, which was the specific goal of my research this summer.

MAGNETIC FIELD

Since both MicroBooNE and LBNE are still in the development phase, all preliminary work is done by using simulations of these LArTPCs in a program designed specifically for these experiments, called LArSoft. LArSoft is useful in running simulations of neutrino events in experiments like MicroBooNE and LBNE. When I began my research this summer, LArSoft already had the capacity to simulate neutrino interactions in a LArTPC with MicrBooNE/LBNE geometry. One useful aspect of LArSoft is its capability in tracking the particle tracks after a collision, and using this data to identify each particle produced by the collision, as well as their energies.

As previously mentioned, a useful technique in distinguishing between oppositely charged particles is the implementation of a magnetic field, and so this was our first task. Theoretically, the magnetic field should lie on the same axis as the wire plane (the x-axis) to eliminate drift of particles. However, when we first implemented this, our curves were not very useful in the 2-D view. The following two images are both paths of positively charged muons in a simulation of MicroBooNE with a magnetic field in the x-direction (each graph is broken up into three smaller graphs - these are the views from each of the three wire planes).

As you can see, they appear to curve in opposite directions, even though both particles have the same energy, the same charge, and are experiencing the same effects from the same magnetic field vector. But why do they appear to differ in curvature? This is simply an optical illusion; a limitation from viewing a 3-dimensional path with only 2 dimensions. Our next step was to view these events in a 3-D display. Once that was working, we had a much more useable image, which we could rotate and look more closely at the curvature due to the magnetic field.

The next step was to implement tracking in the 3-D view, so that LArSoft could still identify which particles were involved in a neutrino event, even though some are undergoing a curvature due to a magnetic field. In order to do this, we had to intervene in the in-place line tracking methods of LArSoft and adapt it so that instead of only looking for linear paths of particles, it also attempted to find helices and curves. This involved utilizing and changing the Hough transform & Kalman filter to reconstruct helical paths. Eventually, we were able to get LArSoft to track and analyze curved and helical paths of neutrino events due to a magnetic field.

CONCLUSIONS

This contribution to the LArSoft community is a small part of something much larger. There will be many questions to answer about neutrinos and how they relate to the universe, and hopefully this implementation will be another step in answering one. By analyzing simulated neutrino events in a magnetic field, we are able to know just a little bit more about the differences between oppositely charged particles. When experiments such as MicroBooNE and LBNE eventually are underway, we hope that our magnetic field tracking can be used along with the multitude of other available resources in LArSoft. This summer’s research has enabled us to gain valuable knowledge in High Energy Physics, computer programming (LOTS of computer programming), and critical thinking.

Anderson Hall, KSU

Outside Moore Hall, KSU

Inside the Hutchinson Salt Mine