Dhanush Anil Hangal

We demonstrate a contextually aware multimodal roadside radiation measurement detection testbed for traffic monitoring applications in nuclear nonproliferation. Many variables in traffic such as vehicle or cargo size, mass, speed, shape, and distance of closest approach can have significant impacts on the radiation measured from a vehicle-transported radiation source. These factors can lead to uncertainties in the analysis of the radiation source, especially for lower-strength radiation sources of interest. Our testbed, known as the Multimodal Measurement System (MMS) uses non-radiation sensors including magnetometers, geophones, radiofrequency receivers, cameras, and LiDAR to extract contextual information about vehicles passing by the system. These contextual data can then be fused with data from radiation measurements to increase the system’s sensitivity and accuracy in nuclear threat detection applications. This work describes the instrumentation of the MMS and its data acquisition pipeline. Furthermore, we describe the pre-analysis performed on the raw multimodal data streams for data fusion, and the high-level machine learning analyses for detection and characterization. The variety of sensors within the MMS provides a valuable testbed that can be used to identify the combinations of contextual sensors that provide the greatest improvements to radiation source detection and characterization within the restrictions for various proliferation detection applications. The MMS is also modular so that additional combinations of sensors can be explored in the future.

Jet charge, defined as the momentum-weighted sum of the electric charges of particles inside a jet is sensitive to the electric charge of the initiating parton and can be used to study the color charge dependence of the parton energy loss in the QGP. In this paper, the first measurements of jet charge in heavy-ion collisions are presented using lead-lead (PbPb) collision data and compared to results from proton-proton (pp) data at the same collision energy. The measurements are unfolded for detector and background effects and are studied differentially in pT and additionally as a function of collision centrality in PbPb collisions. We also present a template fitting technique for estimating the fractions of quark- and gluon-initiated jets in pp and PbPb collisions based on Monte Carlo templates. This analysis uses pp and PbPb collision data collected by the CMS experiment at sNN=5.02TeV.

We present results on measurements of inclusive jet substructure variables using grooming techniques with pp and PbPb data collected with the CMS detector at a center-of-mass energy of 5.02 TeV per nucleon pair.Jet grooming techniques are used to focus on the hard structure of the jet by extracting the two subjets corresponding to a hard parton splitting.The resulting groomed jets can be used to study modifications to the parton shower evolution in the presence of the hot and dense medium created in heavy ion collisions.The hard jet structure is sensitive to the virtuality evolution of a parton in the medium, as well as the role of (de)coherent gluon emitters.Modifications of shared momentum fraction and jet mass over a wide range of jet transverse momentum and various collision centrality selections are reported and compared to predictions from event generators and analytical calculations.

The momentum-weighted sum of the electric charges of particles inside a jet, known as jet charge, is sensitive to the electric charge of the hard-scattered parton initiating the jet.Jet charge distributions are presented for PbPb and pp collisions recorded by the CMS detector at