Reflectivity Measurements of Critical Materials for the LUX Dark Matter Experiment Theory My experiment was a cyclic process involving software, engineering, and physics. It began with a Monte Carlo simulation for determining the most efficient geometry for extracting the reflectivity values. The inner geometry is shown below. This was followed by machining of parts and detector construction, an intensive process that is comprised of connecting all the electronics, DAQ, plumbing, and leak-checking. The fully constructed prototype detector is shown to the right. The inner and outer vacuum chambers were then evacuated, and a heater and two thermometers were employed to bake the detector to speed up outgassing and remove impurities. Next, a small amount of Xe gas was added to the vacuum chamber, as a thermal exchange gas so the cooling process could be accelerated. I used liquid nitrogen (LN) to cool the detector to 168 K. I then condensed enough Xe to cover the active region/inner geometry, roughly 1.3 kg. I employed an LED to find the single photo-electron spectrum (SPE) for PMT stability/calibration measurements. I then utilized a 57 Co source to generate scintillation light that gets collected in the PMT. Finally, the cyclic nature emerges when I return to the Monte Carlo to compare my experimental result with the theoretical to determine the reflectivity value. Methodology and Detectors In my first run, I ran into problems with impure Xe affecting the light collection, so I ran the LXe that I had in the active region through a getter (commercial gas purifier), and I was able to increase the light by a factor of ~2. The above figure shows the gain of the PMT versus bias to extrapolate the value of the SPE mean at 875 V, where I have 57 Co data. The large error bars are due to a discrepancy between my SPE data and the expected exponential gain behavior of the PMT. My equipment stopped working, so I was limited in the data I was able to take. I used code I wrote in Matlab to analyze all my data and the Matlab fitting tool to perform the fits. Acknowledgments In order to determine the reflectivity of a certain material, I needed to calculate the single photo-electron spectrum. A photo-electron is an electron in the PMT that is generated by a photon, so it's essentially the primary electron generated in the PMT that becomes amplified by the dynodes. The SPE spectrum is used as a form of calibration for determining how many single photo-electrons are in a pulse of a given energy. I would like to thank Eric Dahl and John Kwong for helping me get started using their prototype detector in the beginning of my experiment. I would also like to thank all of the current and past Shutt group members for putting up with my frustrations. Using the PMT signal equation, I found that approximately 58% of the light generated hits the PMT. Using the LightGuide result and assuming near 100% PTFE reflectivity as proposed by the LIP-Coimbra group, I extrapolated a reflectivity value of (54.4 )% for stainless steel. The uncertainty was calculated from the error in the interpolated SPE mean value. This result will allow for proper selection of materials and full understanding of LUX light collection. It would be interesting to investigate the reflectivity of other materials, e.g. an all-black material or an all-reflective material. S. Zandbergen with Adviser: T. Shutt Physics Department, Case Western Reserve University The peak that I examined was generated by 57 Co source. As I did for the SPE, I needed to measure the spectrum of 57 Co. Once I found the mean of the 57 Co spectrum (to the right), I divided it by the mean of the SPE spectrum to determine how many SPE's are in the 57 Co pulse. Assuming a QE (quantum efficiency) of 20% for the PMT, I can determine the number of photons that hit the PMT according to data. Results and Prospects Abstract Various cosmological observations have found a discrepancy that suggests ~25% of the universe is matter in a form that cannot be seen. The Large Underground Xenon (LUX) Experiment will explore this “dark matter.” The key component of LUX is measuring scintillation light from liquid xenon (LXe) in order to detect particle dark matter in the form of Weakly Interacting Massive Particles (WIMPs). Optimal performance requires highly efficient collection of photons by the photomultiplier tubes (PMTs), so all other materials in the detector should be highly reflective. The two prime materials are a large surface of polytetrafluoroethylene (PTFE) and some metal for electric field producing grids. I used the group’s prototype LXe detector in situ, with LXe scintillation light at a vacuum ultraviolet (VUV) wavelength of 175 nm, to take a PMT signal measurement from a stainless steel sample. This measurement was compared to a light collection Monte Carlo simulation, and assuming a PTFE reflectivity near 100% in contact with LXe as proposed by the LIP-Coimbra group, I extracted a reflectivity of (54.4 )% for stainless steel. This will allow for proper selection of materials and full understanding of LUX light collection. The basic physics is quite straightforward. The 57 Co source emits a 122 keV photon (a gamma), which gets collimated to the active region. This photon interacts with the LXe and generates scintillation light via two mechanisms. Excitation and ionization of the Xe atoms lead to scintillation of these atoms which finally becomes a signal in the PMT. Ionization is the physical process of converting an atom or molecule into an ion by adding or removing charged particles such as electrons or other ions. Gammas scatter from electrons (electron recoil), while heavy neutral particles (such as neutrons and WIMPs) scatter from the nucleus (nuclear recoil). If one of these incident particles has enough energy to ionize a Xe atom, scintillation results. Scintillation is a flash of light produced in a material by an ionization event. Data Analysis The figure to the right is the result of the LightGuide Monte Carlo simulation. LightGuide is a Matlab-based simulation package for propagation of scintillation light. It plots the stainless steel reflectivity versus PMT signal defined above, scanning over various wall (PTFE) reflectivities, which is another unknown. The various curves are the different PTFE reflectivities, and their values are shown in the legend. Dividing the number of photons that hit the PMT by the number generated in the liquid, as seen in the PMT signal equation below, returns the number of photons that hit the PMT according to data, which can be compared to the Monte Carlo simulation to extract the reflectivity of the material. To determine the number of photons generated in the liquid, we use a Matlab function called yieldnew. Given the electric field, it returns light or charge yield values