Data Quality for the LUX-ZEPLIN detector, and HV performance R&D

Data quality studies in the LZ direct dark matter detector fall into two broad categories: issues that require eliminating certain time periods from analysis, and issues that require cutting particular events from analysis. This student will participate in studying data quality in the first LZ science run, and take a leading role in data quality assessment and cuts in subsequent science runs. The aim of this analysis task is to maximize LZ sensitivity to dark matter signals with the appropriate exclusion of non-dark matter backgrounds and inclusion of potential signal events in the dataset. Machine learning techniques looking for new background event populations that may leak into the signal region be evaluated to see if they save time and effort of human analysts, and are more effective than human analysts. Such cuts require studying event populations that generally fall far from our analysis region and are usually cut by energy or position reconstruction, but may contain many more examples of data quality problems than can be seen in the restricted search dataset. the LUX, ZEPLIN, and LZ analysis teams have not yet utilized machine learning in data quality studies, and other groups are primarily looking for waveform anomalies, or anomalies within the restricted dataset, not within the greater dataset. Data quality studies are required for all new detectors, and every new data taking period of the detector. Performing these analysis cuts is often the most resource intensive part of the science searches.


The high voltage performance of the detector is a significant contributor to data quality issues with additional electron emission from HV components being the primary concern. The student will embark on a design, engineering, and testing project to prepare for high voltage electrode grids for future time projection chambers. A new experiment will require modular grids that can be assembled in situ, and engineering such electrodes with the maximization of light collection and electric field uniformity will be performed with light collection, engineering, and electric field simulations. Engineering prototypes of varies scales will be produced and tested. In addition, small scale test electrodes will be operated to build statistics on initial grid operation and burn in/conditioning to understand what the optimal commissioning plan is for a large scale electrode grid. multiple electrode technologies may be studied, from wires woven by experimentalists, commercial meshes, etched meshes, and thin film depositions.