A5070187810- Magnetic confinement fusion research
- Laser-Plasma Interactions and Diagnostics
- Fusion materials and technologies
- Pulsars and Gravitational Waves Research
- Gamma-ray bursts and supernovae
- Nuclear reactor physics and engineering
- Ionosphere and magnetosphere dynamics
- Superconducting Materials and Applications
- Particle physics theoretical and experimental studies
- Gaussian Processes and Bayesian Inference
- Quantum Chromodynamics and Particle Interactions
- Solar and Space Plasma Dynamics
- Astrophysical Phenomena and Observations
- Cosmology and Gravitation Theories
- Black Holes and Theoretical Physics
- Time Series Analysis and Forecasting
- Nuclear Engineering Thermal-Hydraulics
- Anomaly Detection Techniques and Applications
- Nuclear Physics and Applications
- Computational Physics and Python Applications
- Target Tracking and Data Fusion in Sensor Networks
- Viral Infections and Vectors
- Advanced X-ray and CT Imaging
- Meteorological Phenomena and Simulations
- Radioactive Decay and Measurement Techniques
Massachusetts Institute of Technology
2018-2023
Plasma Technology (United States)
2018-2022
Fusion Academy
2021-2022
Fusion (United States)
2021-2022
École Polytechnique Fédérale de Lausanne
2022
Western University
2017
One of the most intensely studied aspects magnetic confinement fusion is edge plasma turbulence which critical to reactor performance and operation. Drift-reduced Braginskii two-fluid theory has for decades been widely applied model boundary plasmas with varying success. Towards better understanding in both experiment, we demonstrate that a physics-informed deep learning framework constrained by partial differential equations can accurately learn turbulent fields consistent from observations...
Abstract Multi-spectral imaging of helium atomic emission (HeMSI) has been used to create 2D poloidal maps <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:msub> <mml:mrow> <mml:mi>T</mml:mi> </mml:mrow> <mml:mi mathvariant="normal">e</mml:mi> </mml:msub> </mml:math> and <mml:mi>n</mml:mi> in TCV’s divertor. To achieve these measurements, MANTIS multispectral cameras (Perek et al 2019 Rev. Sci. Instrum. 90 123514) simultaneously imaged four He I lines (two...
We consider a simple dynamical and relativistic model to explain the spectro-temporal structure often displayed by repeating fast radio bursts (FRBs). show how this can account for downward frequency drift in sequence of sub-bursts increasing arrival time (the "sad trombone" effect) their tendency exhibiting reduced pulse width with observation. Most importantly, also predicts systematic inverse relationship between (steeper) slope observed within single sub-burst its temporal duration....
We study the spectro-temporal characteristics of two repeating fast radio bursts (FRBs), namely, FRB 20180916B and 20180814A, combine results with those from our earlier analysis on 20121102A. The relationship between frequency drift rate, or slope, individual sub-bursts their temporal duration is investigated. consider a broad sample possible dispersion measure (DM) values for each source to understand range valid sub-burst slope measurements all constrain results. find good agreement an...
Fast Radio Bursts (FRBs), characterized by strong bursts of radiation intensity at radio wavelengths lasting on the order a millisecond, have yet to be firmly associated with family, or families, astronomical sources. It follows that despite large number proposed models no well-defined physical process has been identified explain this phenomenon. In paper, we demonstrate how Dicke's superradiance, for which evidence recently found in interstellar medium, can account characteristics FRBs. Our...
In this paper we develop a model for fast radio bursts (FRBs) based on triggered superradiance (SR) and apply it to previously published data of FRB 110220 121102. We show how young pulsar located at ~100 pc or more from an SR/FRB system could initiate the onset powerful burst radiation detectable over cosmological distances. Our models using OH$^2\Pi_{3/2}$ $\left(J=3/2\right)$ 1612 MHz $^2\Pi_{3/2}$ $\left(J=5/2\right)$ 6030 spectral lines match light curves well suggest entanglement than...
The edge density and temperature of tokamak plasmas are strongly correlated with energy particle confinement their quantification is fundamental to understanding dynamics. These quantities exhibit behaviours ranging from sharp plasma gradients fast transient phenomena (e.g. transitions between low high regimes) nominal stationary phases. Analysis experimental measurements therefore require robust fitting techniques capture potentially stiff spatiotemporal evolution. Additionally, fusion...
A key uncertainty in the design and development of magnetic confinement fusion energy reactors is predicting edge plasma turbulence. An essential step overcoming this validation accuracy reduced turbulent transport models. Drift-reduced Braginskii two-fluid theory one such set equations that has for decades simulated boundary plasmas experiment, but significant questions exist regarding its predictive ability. To end, using a novel physics-informed deep learning framework, we demonstrate...
We present two-dimensional turbulent electric field calculations via physics-informed deep learning consistent with (i) drift-reduced Braginskii theory under the framework of an axisymmetric fusion plasma purely toroidal and (ii) experimental estimates fluctuating electron density temperature on open lines obtained from analysis gas puff imaging a discharge Alcator C-Mod tokamak. The inclusion effects locally puffed atomic helium particle energy sources within reduced turbulence model is...
The role of turbulence in setting boundary plasma conditions is presently a key uncertainty projecting to fusion energy reactors. To robustly diagnose edge turbulence, we develop and demonstrate technique translate brightness measurements HeI line radiation into local fluctuations via novel integrated deep learning framework that combines neutral transport physics collisional radiative theory for the 33D - 23P transition atomic helium with unbounded correlation constraints between electron...
Edge plasma turbulence is critical to the performance of magnetic confinement fusion devices. Towards better understanding edge in both theory and experiment, a custom-built physics-informed deep learning framework constrained by partial differential equations developed accurately learn turbulent fields consistent with two-fluid from observations electron pressure. This calculation not otherwise possible using conventional equilibrium models. With this technique, first direct quantitative...
Both 3- and 4-point scattering amplitudes for spin-1 massless particles (gluons) spin-2 (gravitons) are reviewed through self-contained step-by-step derivation. Gluon graviton interactions computed from on-shell diagrams by starting complex momenta introducing spinor-helicity formalism. By Fourier transforming spinor variables in momentum space, binarity is revealed pure Yang-Mills while absent to a certain extent gravity indicating fundamental differences the probability spaces spanned two...
We present 2-dimensional turbulent electric field calculations via physics-informed deep learning consistent with (i) drift-reduced Braginskii theory under the framework of an axisymmetric fusion plasma purely toroidal and (ii) experimental estimates fluctuating electron density temperature on open lines obtained from analysis gas puff imaging a discharge Alcator C-Mod tokamak. The inclusion effects locally puffed atomic helium particle energy sources within reduced turbulence model are...
Abstract Following the results of [1], which demonstrates a novel method to translate 2-dimensional measurements HeI line radiation on turbulent scale into local plasma fluctuations via an integrated deep learning framework, this manuscript investigates when applying two separate techniques for optimization: Adam and L-BFGS. Fundamentally, approaches apply same set constraints loss functions that combine neutral transport physics collisional radiative theory 3 D − 2 P (587.6 nm line)...