Scholar iON
Academic Synthesis
The collection of scholarly papers on "math.CV" highlights advancements in both hardware design for physics experiments and computational techniques for modeling complex systems. Nakazawa et al. (2019) focus on the development of an analog front-end for TPCs used in dark matter searches and neutrino studies, emphasizing the challenge of meeting stringent electronic requirements under diverse operational conditions. This work underscores the significance of adaptable and precise electronic components in advancing experimental physics. In contrast, Erban et al. (2007) provide a foundational understanding of stochastic simulations for reaction-diffusion processes, bridging the gap between stochastic and deterministic models. This article is significant for its practical guidance in computational biology, illustrating the utility of stochastic methods in capturing the dynamic behavior of biochemical systems. Together, these studies underscore the interdisciplinary nature of contemporary scientific research, where innovations in electronics and computational methods play crucial roles in advancing our understanding of both physical phenomena and complex biological processes.
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.