Related papers: Measuring the Electron Temperature and Identifying…
We solve the Maxwell and heat equations self-consistently for metal nanoparticles under intense continuous wave (CW) illumination. Unlike previous studies, we rely on {\em experimentally}-measured data for the metal permittivity for…
Instead of using current deep-learning segmentation models (like the UNet and variants), we approach the segmentation problem using trained Convolutional Neural Network (CNN) classifiers, which automatically extract important features from…
Luminescence thermometry has been extensively exploited in the last decades both from the fundamental and applied point of views. The application of photoluminescent nanoparticles on the microscopic level based on rare-earth doped (RED)…
In next-step fusion tokamaks such as SPARC and ITER, achieving high levels of scrape-off-layer power dissipation will be essential to protect the divertor while maintaining good core plasma performance. The Lengyel model for power…
In fusion plasmas, where electron temperatures $T_e$ range from keV to hundreds of keV, Bremsstrahlung radiation constitutes a significant energy loss mechanism. While various thermal average fitting formulas exist in the literature, their…
The interaction of light with a material's electronic system creates an out-of-equilibrium (non-thermal) distribution of optically excited electrons. Non-equilibrium dynamics relaxes this distribution on an ultrafast timescale to a hot…
We present a machine learning (ML) method for efficient computation of vibrational thermal expectation values of physical properties from first principles. Our approach is based on the non-perturbative frozen phonon formulation in which…
Temporally-resolved electron density measurements of solar flare plasmas are presented using data from the EUV Variability Experiment (EVE) onboard the Solar Dynamics Observatory (SDO). The EVE spectral range contains emission lines formed…
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…
We present a thermometry scheme to extract the temperature of a 2DEG by monitoring the charge occupation of a weakly tunnel-coupled 'thermometer' quantum dot using a quantum point contact detector. Electronic temperatures between 97 mK and…
The Time Autocorrelation of Auxiliary Wave (TACAW) method has established a framework for modeling angle-resolved electron energy loss spectroscopy (EELS) of phonons and magnons by deriving scattering intensities from the time…
The spectra from Fe-peak elements may be used to determine the temperature and density of various astrophysical objects. Determination of these quantities is underpinned by the accuracy and the comprehensiveness of the underlying atomic…
In this work, ML models were used to predict the plasma temperature using the dataset obtained by implementing the CR-model for Na-like Krypton. The models included in the study are: Linear Regression, Lasso Regression, Support Vector…
Effects of radio-frequency power and driven frequency on the two-dimensional (axial and radial) distributions of electron density and temperature were experimentally investigated in low pressure capacitively coupled argon plasmas. The…
Atomistic simulations provide insights into structure-property relations on an atomic size and length scale, that are complementary to the macroscopic observables that can be obtained from experiments. Quantitative predictions, however, are…
Although tokamaks are one of the most promising devices for realizing nuclear fusion as an energy source, there are still key obstacles when it comes to understanding the dynamics of the plasma and controlling it. As such, it is crucial…
Machine learning (ML) methods provide advanced means for understanding inherent patterns within large and complex datasets. Here, we employ the principal component analysis (PCA) and the diffusion map (DM) techniques to evaluate the glass…
Anti-Stokes photoluminescence of metal nanoparticles, in which emitted photons have a higher energy than the incident photons, is an indicator of the temperature prevalent within a nanoparticle. Previous work has shown how to extract the…
We have developed TorbeamNN: a machine learning surrogate model for the TORBEAM ray tracing code to predict electron cyclotron heating and current drive locations in tokamak plasmas. TorbeamNN provides more than a 100 times speed-up…
This paper presents a numerical investigation of isolated filament dynamics in a simulation geometry representative of the scrape-off layer (SOL) of the Mega Amp Spherical Tokamak (MAST) previously studied in [N.R.Walkden et.al, Plasma…