Speaker
Description
Accurate reconstruction of charged-particle tracks in active-target time projection chambers (AT-TPCs) is essential for extracting reaction kinematics. A common approach in high energy physics is the use of a Kalman Filter (KF); however, KFs developed for high energy experiments (e.g., GEN-FIT) typically treat the energy loss of particles as a Gaussian process noise term in the propagator. This assumption can break down at low energies. A new Unscented Kalman Filter (UKF) has been developed that explicitly incorporates both deterministic average energy loss and stochastic energy straggling into the particle propagator. In the UKF framework, different energy loss models can be easily incorporated allowing for the exploration of the effect of energy loss models on reconstructed kinematics. In contrast, when no magnetic field is present, such as in a 2020 fusion-fission experiment, one must rely on event geometry and energy loss information from recorded traces for this same task. For this case, a new Monte-Carlo based fitting method was developed, independent of the UKF framework. The MC method can determine the element number (Z) of fission fragments along with other observables such as the beam energy at the vertex point and, by extension, the excitation energy of the fissioning nucleus. The MC method can handle complex detector effects such as missing channels in the pad plane and electric field distortions due to space-charge buildup. We present validation of both techniques against simulated data using ATTPCROOT and show preliminary reconstructed Z distributions for 204At using the MC method.
