Related papers: Adapted Swin Transformer-based Real-Time Plasma Sh…
In this paper, we present a Hybrid Spectral Denoising Transformer (HSDT) for hyperspectral image denoising. Challenges in adapting transformer for HSI arise from the capabilities to tackle existing limitations of CNN-based methods in…
I-mode is a promising regime for future fusion reactors due to the high energy confinement and the moderate particle confinement. However, the effect of lithium, which has been widely applied for particle recycling and impurity control, on…
A Scanning Tunneling Microscope (STM) is one of the most important scanning probe tools available to study and manipulate matter at the nanoscale. In a STM, a tip is scanned on top of a surface with a separation of a few \AA. Often, the…
Accurate pressure measurements in micrometric channels are essential for a wide range of microfluidic applications. Existing approaches rely on a variety of sensing mechanisms, but generally require the integration of additional probes or…
Particle therapy is an established method to treat deep-seated tumours using accelerator-produced ion beams. For treatment planning, the precise knowledge of the relative stopping power (RSP) within the patient is vital. Conversion errors…
In this study, the capabilities of the Physics-Informed Neural Network (PINN) method are investigated for three major tasks: modeling, simulation, and optimization in the context of the heat conduction problem. In the modeling phase, the…
This study investigates the feasibility of reconstructing the last closed flux surface (LCFS) in the DIII-D tokamak using neural network models trained on reduced input feature sets, addressing an ill-posed task. Two models are compared:…
Ising machines are emerging as a powerful physical alternative to digital processors for solving combinatorial optimization problems. Among them, spatial photonic Ising machines (SPIMs) offer compact, room-temperature hardware with…
The Large Area Telescope (LAT), the main instrument of the Fermi Gamma-Ray Space Telescope, detects high energy gamma rays with energies from 20 MeV to more than 300 GeV. The two main scientific ob jectives, the study of the Milky Way…
The inherent complexity of boundary plasma, characterized by multi-scale and multi-physics challenges, has historically restricted high-fidelity simulations to scientific research due to their intensive computational demands. Consequently,…
We present methods for analyzing Beam Emission Spectroscopy (BES) data to obtain the plasma density evolution associated with rapid sawtooth crash events at the DIII-D tokamak. BES allows coverage over a 2-D spatial plane, inherently local…
Pre-plasma conditions strongly influence laser-plasma interactions in the multi-petawatt (MPW) regime, increasing the need for reliable early-time plasma evolution diagnostics. Among available pre-plasma diagnostics, interferometry remains…
The steady-state confinement, beta limit, and divertor heat load are among the most concerned issues for toroidal confinement of fusion plasmas. In this work, we show that the negative triangularity tokamak has promising prospects to…
A pulsed oscillating power amplifier has been developed for high frequency biasing\cite{kn:deb1} and real time turbulent feedback experiment in STOR-M tokamak. It is capable to provide output peak to peak oscillating voltage of around…
Efficient frequency conversion techniques are crucial to the development of plasmonic metasurfaces for information processing and signal modulation. In principle, nanoscale electric-field confinement in nonlinear materials enables higher…
Reactor grade plasmas are likely to be fuelled by pellet injection. This technique transiently perturbs the profiles, driving the density profile hollow and flattening the edge temperature profile. After the pellet perturbation, the density…
A recent study [1] about the scaling with the aspect ratio (i.e. the ratio between the major and minor radius of the torus) of the dominant mode in Single Helical (SH) Reverse Field Pinch (RFP) plasmas has shown, at intermediate aspect…
A machine learning approach has been implemented to measure the electron temperature directly from the emission spectra of a tokamak plasma. This approach utilized a neural network (NN) trained on a dataset of 1865 time slices from…
We generalise Spatial Transformer Networks (STN) by replacing the parametric transformation of a fixed, regular sampling grid with a deformable, statistical shape model which is itself learnt. We call this a Statistical Transformer Network…
Simulations using 3D and 2D full-wave codes have shown that edge filaments in tokamak plasmas can significantly affect the propagation of microwaves across a broad frequency spectrum, resulting in scattering angles of up to 46 degrees.…