Related papers: Using Bayesian Analysis and Gaussian Processes to …
We introduce a computational framework to statistically infer thermophysical properties of any given wall from in-situ measurements of air temperature and surface heat fluxes. The proposed framework uses these measurements, within a…
A fully Bayesian treatment of complicated predictive models (such as deep neural networks) would enable rigorous uncertainty quantification and the automation of higher-level tasks including model selection. However, the intractability of…
Measuring the temperature structure of the solar atmosphere is critical to understanding how it is heated to high temperatures. Unfortunately, the temperature of the upper atmosphere cannot be observed directly, but must be inferred from…
We propose a method to probe Landau and Beliaev processes in dilute trapped atomic condensates with a multiple state structure using ultraslow light experimental configurations. Under certain conditions, damping rates from these collisional…
High-precision measurements require optimal setups and analysis tools to achieve continuous improvements. Systematic corrections need to be modeled with high accuracy and known uncertainty to reconstruct underlying physical phenomena. To…
This study presents the first ion temperature (\(T_i\)) measurements from the MAST-U divertor using a Retarding Field Energy Analyzer (RFEA). Embedded within the flat tile of the closed divertor chamber, the RFEA captures \(T_i\) profiles…
Temperature-dependent transport data, including diffusion coefficients and ionic conductivities, are routinely analysed by fitting empirical models such as the Arrhenius equation. These fitted models yield parameters such as the activation…
A polarization-sensitive optical coherence tomography (PS-OCT) system is able to not only show the structure of samples through the analysis of backscattered light, but is also capable of determining their polarimetric properties. This is…
We present measurements of the cooling length $\ell_E$ for hot electrons in a GaAs-based high mobility two-dimensional electron gas (2DEG). The thermal measurements are performed on a long 60 $\mu$m-wide channel, which is Joule-heated at…
Precise determination of thermodynamic parameters in ultracold Bose gases remains challenging due to the destructive nature of conventional measurement techniques and inherent experimental uncertainties. We demonstrate a machine learning…
Predictive and real-time inference capability for the upstream separatrix electron density, $n_\text{e, sep}$, is essential for design and control of core-edge integrated plasma scenarios. In this study, both supervised and semi-supervised…
For machine learning of interatomic potentials a scalable sparse Gaussian process regression formalism is introduced with a data-efficient on-the-fly adaptive sampling algorithm. With this approach, the computational cost is effectively…
We present a cost-effective method for model calibration and solution of source inversion problems in atmospheric dispersion modelling. We use Gaussian process emulations of atmospheric dispersion models within a Bayesian framework for…
The injection of photoelectrons in a gaseous or liquid sample is a widespread technique to produce a cold plasma in a weakly--ionized system in order to study the transport properties of electrons in a dense gas or liquid. We report here…
Accurate temperature measurement at the nanoscale is crucial for thermal management in next-generation microelectronic devices. Existing optical and scanning-probe thermometry techniques face limitations in spatial resolution, accuracy, or…
We present laboratory results on energy partitioning from supercritical, magnetized collisionless shock experiments ($\rm{M_A} \sim 8$, $\rm{M_{ms}}\sim 4$). We report the first observation of fully-developed laboratory shocks that evolve…
Study of the dephasing in electronic systems is not only important for probing the nature of their ground states, but also crucial to harnessing the quantum coherence for information processing. In contrast to well-studied conventional…
The optimal management of a building's microclimate to satisfy the occupants' needs and objectives in terms of comfort, energy efficiency, and costs is particularly challenging. This complexity arises from the non-linear, time-dependent…
We propose classical interferometry with low-intensity thermal radiation for the estimation of nonclassical independent Gaussian processes in material samples. We generally determine the mean square error of the phase-independent parameters…
Local electron and ion heating characteristics during merging reconnection startup on the MAST spherical tokamak have been revealed for the first time using a 130 channel YAG-TS system and a new 32 chord ion Doppler tomography diagnostic.…