Scholar iON
Academic Synthesis
The papers presented address significant advancements in two distinct but technically related areas: analog front-end electronics for particle detection and stochastic simulations of reaction-diffusion processes. Nakazawa et al. discuss the development of a versatile analog front-end ASIC, designed to enhance the performance of negative-ion and dual-phase liquid argon time projection chambers (TPCs), crucial for dark matter searches and neutrino studies. This research emphasizes the importance of achieving a wide dynamic range and low noise levels in different operating conditions. Meanwhile, Erban et al. provide a comprehensive introduction to stochastic modeling in reaction-diffusion processes, illustrating the transition from deterministic to stochastic frameworks using the Gillespie algorithm and related methods. Collectively, these works underscore the importance of precise electronic design in experimental physics and the growing relevance of stochastic approaches for modeling complex chemical systems, highlighting ongoing efforts to refine and integrate these techniques into broader scientific inquiries.
We report on the recent development of a versatile analog front-end compatible with a negative-ion $μ$-TPC for a directional dark matter search as well as a dual-phase, next-generation $\mathcal{O}$(10~kt) liquid argon TPC to study neutrino oscillations, nucleon decay, and astrophysical neutrinos. Although the operating conditions for negative-ion and liquid argon TPCs are quite different (room temperature \textit{vs.} $\sim$88~K operation, respectively), the readout electronics requirements are similar. Both require a wide-dynamic range up to 1600 fC, and less than 2000--5000 e$^-$ noise for a typical signal of 80 fC with a detector capacitance of $C_{\rm det} \approx 300$~pF. In order to fulfill such challenging requirements, a prototype ASIC was newly designed using 180-nm CMOS technology. Here, we report on the performance of this ASIC, including measurements of shaping time, dynamic range, and equivalent noise charge (ENC). We also demonstrate the first operation of this ASIC on a low-pressure negative-ion $μ$-TPC.
A practical introduction to stochastic modelling of reaction-diffusion processes is presented. No prior knowledge of stochastic simulations is assumed. The methods are explained using illustrative examples. The article starts with the classical Gillespie algorithm for the stochastic modelling of chemical reactions. Then stochastic algorithms for modelling molecular diffusion are given. Finally, basic stochastic reaction-diffusion methods are presented. The connections between stochastic simulations and deterministic models are explained and basic mathematical tools (e.g. chemical master equation) are presented. The article concludes with an overview of more advanced methods and problems.