Scholar iON
Academic Synthesis
The scholarly papers presented span developments in applied physics and mathematical modeling, highlighting advancements in experimental and computational methodologies. The work by Nakazawa et al. focuses on the development of a versatile analog front-end compatible with different types of time projection chambers (TPCs) used in particle physics, demonstrating the potential for significant advancements in dark matter detection and neutrino research through innovative ASIC design despite differing operational conditions. Conversely, Erban et al. provide a foundational guide to stochastic simulations of reaction-diffusion processes, elucidating methods such as the Gillespie algorithm and bridging stochastic and deterministic modeling paradigms. Collectively, these studies underscore the importance of both technological innovation and robust computational frameworks in advancing understanding and exploration in physical sciences, demonstrating a consensus on the necessity of interdisciplinary approaches to tackle complex scientific challenges.
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.