Acronyms

Acronym	Description
ACM
ADC
ADM	Alternating directions method
AIC	Akaike information criterion
ALM	Augmented Lagrange multiplier
AMR
AMReX
AND
ANL	Argonne National Laboratory
ANN	Artificial neural network
ANN	Artificial neural network
ANOVA	Analysis of Variance
API	Application Programming Interface
ARMA	Autoregressive moving averaoe
ARMAX	Autoregressive moving average with exogenous input
ASQ	Adaptive sparse quadrature
ATS	Advanced Terrestrial Simulator, previously Arctic Terrestrial Simulator
AUXVAL
BD
BG/L
BIC	Bayesian information criterion
BIM	Empirical interpolation method
BOX
BP
BPOD	Balanced proper orthogonal decomposition
CabanaMD
CCA	Canonical correlation analysis
CD
CEA
CESM
CFD	Computational fluid dynamics
CI
CNN	Convolutional neural network
COGENT
COMPAT
CoSaMP	Compressive sampling matching pursuit
COSMO
COSSAN
CPP
CPU	Central Processing Unit
CRC
CS	Compressed sensing
CSE
CSMP
CTO
CUDA	Compute Unified Device Architecture
CWIPI
CWT	Continuous wavelet transform
DAG	Direct Acyclic Graph
DAKOTA
DCT	Discrete cosine transform
DDA
DEIM	Discrete empirical interpolation method
DFT	Discrete Fourier fransform
DFT	Discrete Fourier Transform
DiMDc	Dynamic mode decomposition with control
DL	Deep learning
DMD	Dynamic mode decomposition
DMDc	Dynamic mode decomposition with control
DNS	Direct numerical simulation
DOE	Department of Energy
DOI	Digital Object Identifier
DSL	Domain-Specific Language
DWT	Discrete wavelet transform
ECOG	Electrocorticography
ECP
ECP-copa
eDMD	Extended DMD
EIRENE
EM	Expectation maximization
EOF	Empirical orthogonal functions
ERA	Eigensystem realization algorithm
ESC	Extremum-seeking control
ESI
ESMF
ETS
EU	European Union
FACETS
FCI	Flux-Coordinate Independent (methods)
FEM	Finite Element Method
FEniCS
FFT	Fast Fourier transform
FFT	Fast Fourier Transform
FFTW	Fastest Fourier Transform in the West (library)
FLASH
GA	General Atomics
GBD
GBS
GDB
GMM	Gaussian mixture model
GMRES	Generalized Minimal Residual method
GNU	GNU’s Not Unix!
gPC	Generalised polynomial chaos
GPU	Graphics Processing Unit
GSA	Global sensitivity analysis
GUI	Graphical User Interface
HAVOK	Hankel alternative view of Koopman
HDF5	Hierarchical Data Format (version 5)
HLA
HPC	High Performance Computing
HVAR
ICA	Independent component analysis
ICON
IEEE
IMAS
IMEX	Implicit-Explicit Methods
IO
ITG	Ion Temperature Gradient
ITM	Ion Tearing Mode
ITPA
JET	Joint European Torus
JL	JohnsonLindensfrauss
JOREK
KL	KullbackLeib1er
KLT	Karhunen-Loeve transform
LAD	Least absolute deviations
LAMMPS	Large-scale Atomic/Molecular Massively Parallel Simulator
LANL	Los Alamos National Laboratory
LASH
LASSO	Least absolute shrinkage and selection operator
LASSO	Least Absolute Shrinkage and Selection Operator
LDA	Linear discriminant analysis
LGPL	GNU Lesser General Public License
LHSamp
LLNL	Lawrence Livermore National Laboratory
LQE	Linear quadratic estimator
LQG	Linear quadratic Gaussian controller
LQR	Linear quadratic regulator
LTI	Linear time invariant system
MAP	Maximium A Posteriori
MC	Monte Carlo (methods)
MCMC	Markov Chain Monte Carlo
MCT
MESAGE
MFMA
MFMC	Multi-fidelity Monte Carlo
MHD	Magnetohydrodynamics
MIMC
MIMO	Multiple input, multiple output
MIT	Massachusetts Institute of Technology
ML	Machine Learning
MLC	Machine learning control
MLMC	Multi-level Monte Carlo
MLMF
MMF
MOOSE
MOR	Model Order Reduction
Most	Common Acronyms
MPE	Missing point estimation
MPI	Message Passing Interface
mrDMD	Multi-resolution dynamic mode decomposition
MSSC
MUMPS
MUSCLE 3	Multiscale Coupling Library and Environment 3
NARMAX	Nonlinear autoregressive model with exogenous inputs
NEMO
NEPTUNE
NLS	Nonlinear Schrdinger equation
NUCODE
OASIS
OASIS4
ODE	Ordinary differential equation
OKID	Observer Kalman filter identification
OLYMPUS
OMFIT
OU	Oxford University
OUU	Optimisation under uncertainty
OUUWA
PASTIX
PBH	PopovBelevitchHautus test
PC	Polynomial chaos
PCA	Principal components analysis
PCE	Polynomial chaos expansion
PCP	Principal component pursuit
PDE	Partial differential equation
PDE-FIND	Partial differential equation functional identification of nonlinear dynamics
PDF	Probability distribution function
PFC
PGD
PICPIF
PID	Proportional-integral-derivative control
PIV	Particle image velocimetry
POD	Proper orthogonal decomposition
POOMA
PP20
PRESET
QA
QCG
QMC	Quasi-Monte-Carlo
QoI	Quantity of interest
RIP	Restricted isometry property
RKF23
RKHS	Reproducing kernel Hilbert space
RNG
RNN	Recurrent neural network
ROM	Reduced order model
ROM	Reduced-order model
RPCA	Robust principal components analysis
rSVD	Randomized SVD
SAMRAI
SGD	Stochastic gradient descent
SIAM	Society for Industrial and Applied Mathematics
SINDy	Sparse identification of nonlinear dynamics
SISO	Single input, single output
SLSQT	Sequential Least-Squares’ Thresholding
SMARDDA
SMART
SMITER
SMwiki
SNOWPAC	Stochastic Nonlinear Optimisation with Path-Augmented Constraints (software package)
SOL	Scrape-Off Layer
SOLEDGE
SOLPS
SRC	Sparse representation for classification
SRS
SSA	Singular spectrum analysis
STARWALL
STFT	Short time Fourier transform
STIXGeneral
STLS	Sequential thresholded least-squares
STRUMPACK
SVD	Singular value decomposition
SVD	Singular value decomposition
SVM	Support vector machine
SVM
TAE
TICA	Time-lagged independent component analysis
TM
TOKAM
TOKAM3X
TOMS
TRIMEG
TUM
UK	United Kingdom
UKAEA	United Kingdom Atomic Energy Authority
UKRI	United Kingdom Research and Innovation
UQ	Uncertainty quantification
US
USA
UTF-8
VAC	Variational approach of conformation dynamics
VDE
VECMAtk
VORPAL
XGC1
XML
XMSF

Symbols

Symbol	Description
\([a,b]\)	arbitrary finite interval
\(d\)	number of dimensions over which the integral is performed
\(f_0\)	constant in the expansion of \(f\left(x_1,\ldots,x_d\right)\)
\(f\left(x_1,\ldots,x_d\right)\)	joint probability distribution
\(f_i(x_i)\)	coefficient in the expansion of \(f\left(x_1,\ldots,x_d\right)\)
\(f_{ij}(x_i,x_j)\)	coefficient in the expansion of \(f\left(x_1,\ldots,x_d\right)\)
\(p(x)\)	probability distributions
\(r\)	order of higher order term
\(x_i\)	generic parameter or variable
\({\bf x} =\left(x_1,x_2,\dots,x_d\right)\)	is a \(d\)-dimensional vector
\(P(x)\)	Cumulant probability distribution
\(\parallel Q \parallel_E\)	the ‘energy’ norm
\(S_i\)	Sobol sensitivity index, gives a normalised measure of the sensitivity of the distribution of \(f\) to the parameter \(x_i\)
\(S_{ij}\)	Sobol sensitivity index, gives a normalised measure of the sensitivity of the distribution of \(f\) to the parameters \(x_i\) and \(x_j\)
\(\mathrm{Var}(f)\)	variance of the distribution of \(f\) computed by integrating over all variables \(x_i\)
\(V_i\)	variance of the distribution of \(f\) as the parameter \(x_i\) varies
\(V_{ij}\)	variance of the distribution of \(f\) as the parameters \(x_i\) and \(x_j\) vary
\(\mathbb{E}\)	expectation
\(\mathbb{E}_{x_{k\neq i}}\)	expectation computed by integrating over all the \(x_k\) except for \(x_i\)
\(\mathbb{E}_{k\neq i, l\neq j}\)	expectation computed by integrating over all the \(x_k\) except for \(x_i\) and \(x_j\)
\(\xi_i\)	randon number within the unit interval \([0,1]\)