分类： 天文学 >> 天文学 提交时间： 2023-02-19
Michael Bertolacci
Andrew Zammit-Mangion
Andrew Schuh
Beata Bukosa
Jenny Fisher
Yi Cao
Aleya Kaushik
Noel Cressie
摘要： The natural cycles of the surface-to-atmosphere fluxes of carbon dioxide (CO$_2$) and other important greenhouse gases are changing in response to human influences. These changes need to be quantified to understand climate change and its impacts, but this is difficult to do because natural fluxes occur over large spatial and temporal scales. To infer trends in fluxes and identify phase shifts and amplitude changes in flux seasonal cycles, we construct a flux-inversion system that uses a novel spatially varying time-series decomposition of the fluxes, while also accommodating physical constraints on the fluxes. We incorporate these features into the Wollongong Methodology for Bayesian Assimilation of Trace-gases (WOMBAT, Zammit-Mangion et al., Geosci. Model Dev., 15, 2022), a hierarchical flux-inversion framework that yields posterior distributions for all unknowns in the underlying model. We apply the new method, which we call WOMBAT v2.0, to a mix of satellite observations of CO$_2$ mole fraction from the Orbiting Carbon Observatory-2 (OCO-2) satellite and direct measurements of CO$_2$ mole fraction from a variety of sources. We estimate the changes to CO$_2$ fluxes that occurred from January 2015 to December 2020, and compare our posterior estimates to those from an alternative method based on a bottom-up understanding of the physical processes involved. We find substantial trends in the fluxes, including that tropical ecosystems trended from being a net source to a net sink of CO$_2$ over the study period. We also find that the amplitude of the global seasonal cycle of ecosystem CO$_2$ fluxes increased over the study period by 0.11 PgC/month (an increase of 8%), and that the seasonal cycle of ecosystem CO$_2$ fluxes in the northern temperate and northern boreal regions shifted earlier in the year by 0.4-0.7 and 0.4-0.9 days, respectively (2.5th to 97.5th posterior percentiles).
分类： 物理学 >> 凝聚态:电子结构、电、磁和光学性质 提交时间： 2021-12-18
摘要： True random number generator (TRNG) is an important component for modern information security technologies. Among the candidates, TRNG with spin-orbit torque (SOT)-induced probabilistic magnetization switching is competitive for its advantages in anti-radiation, unlimited endurance, robust stability, and broad temperature range. However, realization of a SOT-TRNG requires intensive understanding of the magnetic dynamic process under a spin-orbit current. Here, we performed micromagnetic simulation of the SOT-induced probabilistic magnetization switching by using Mumax 3. Without thermal noise, identical magnetic moment precessions were found between repeated simulation cycles, resulting in deterministic magnetization switching. When thermal noises were taken into account, stochastic precession trails and thereby probabilistic magnetization switching were finally obtained. Our results suggest the Mumax 3 to be a practical tool for simulating the probabilistic magnetization switching behavior of a SOT-TRNG, as well as highlighting the crucial role of thermal noise during the during the simulation.
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