Scholar iON
Academic Synthesis
The scholarly articles focus on advancements in specific scientific technologies and methodologies, highlighting both practical implementations and theoretical frameworks. Nakazawa et al. (2019) discuss the development of a versatile analog front-end for TPCs (Time Projection Chambers), emphasizing its significance in experiments related to dark matter searches and neutrino studies. This development is pivotal as it addresses the challenge of operating under diverse conditions with high dynamic range and low noise requirements. In contrast, Erban et al. (2007) provide a foundational guide to stochastic simulations in reaction-diffusion processes, detailing methodologies such as the Gillespie algorithm and bridging stochastic simulations with deterministic models. Both papers contribute significantly to their respective fields by enhancing experimental capabilities and offering comprehensive methods for simulating complex processes, thus broadening the scope of experimental and theoretical research in physics and chemistry.
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.