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$
$dimetaphi 2.3.1 Setup a model and compile with cmz
$zinit 2.3.1 Setup a model and compile with cmz

A
adjoint 4.2.1 Overview of optimisation with Miniker
aspha.data 2.3.3 Running a simulation and using the output
aspha.data’, GTLS 4.6.3 Generalized tangent linear system analysis run and output
aspha.data’, SVD 4.5.3 Singular Value Decomposition run and output

B
Borel sweep 4.4 Feedback gain
Borel sweep graphics 4.4.2 Borel sweep results
Borel sweep results 4.4.2 Borel sweep results

C
cells Introduction
cernlib A.2 Common requisites
command law 4.2.2 Control laws
compilation 2.3.2 Setup a model and compile with make
configuration of source A.4.2 Configuration
controlling the run 2.4 Controlling the run

D
data.data 3.8.2 Data
data.data 4.3.2.2 Kalman filter results
dimetaphi 3.9.1 The explicit size sequence
dimetaphi 3.9.1 The explicit size sequence
dimetaphi’, Kalman filter 4.3.1.1 Kalman filter vectors dimensions
down node 3.3 Describing 1D gridded model
dres.data 2.3.3 Running a simulation and using the output
dres.data Footnotes
dres.data’, GTLS 4.6.3 Generalized tangent linear system analysis run and output

E
equations, grid Grid node equations
error vector dimension 4.3.1.1 Kalman filter vectors dimensions

F
FDL, GNU Free Documentation License C.1 GNU Free Documentation License
feature setting 3.1 Overview of additional features setting
Feedback gain 4.4 Feedback gain
ffl (linearity test) 2.4.1 Executing code at the end of each time step
final cost 4.2.1 Overview of optimisation with Miniker

G
Generalized linear tangent system 4.6 Generalized linear tangent system analysis
gradpj.data 4.2.4 Sensitivity of cost function to parameters
graphics 2.3.4 Doing graphics
graphics with gnuplot 2.3.4 Doing graphics
graphics with PAW 2.3.4 Doing graphics
graphics, Borel sweep 4.4.2 Borel sweep results
GTLS 4.6 Generalized linear tangent system analysis
GTLS output 4.6.3 Generalized tangent linear system analysis run and output
GTLS run 4.6.3 Generalized tangent linear system analysis run and output

H
Heaviside function 3.6 Rule of programming non continuous models

I
initial variance-covariance on states Initial variance-covariance matrix on the state
installation with make A.4.3 Installation with make
integrand cost 4.2.1 Overview of optimisation with Miniker

K
Kalman filter 4.3 Kalman filter
Kalman filter output 4.3.2.2 Kalman filter results
Kalman filter results 4.3.2.2 Kalman filter results

L
lapack A.2 Common requisites
limiting conditions Limiting conditions
linearity test 2.4.1 Executing code at the end of each time step
logical flags 3.1 Overview of additional features setting
Lyapunov exponents 4.6 Generalized linear tangent system analysis

M
Makefile.miniker 5.1 Make variables
Makefile.sltc 4.5.2 Singular Value Decomposition with make
Makefile.sltcirc 4.6.2 Generalized tangent linear system with make
mini_ker.cmz A.3 Miniker with cmz
mod 2.3.1 Setup a model and compile with cmz
model equations 3.9.2 Entering the model equations, with explicit sizes
model size 3.9.1 The explicit size sequence
Model.hlp 2.3.3 Running a simulation and using the output
mortran Introduction
mortran 2.2.1 All you need to know about mortran and cmz directives
mortran, with make A.4.1 Additional requirements for Miniker with make

O
obs.data 3.8.1 Observations
observation function 3.8.1 Observations
observations 4.3.1.2 Error and observation matrices
observations, general 4.3 Kalman filter
optimisation 4.2.1 Overview of optimisation with Miniker
output file 2.3.3 Running a simulation and using the output
output, GTLS 4.6.3 Generalized tangent linear system analysis run and output
output, Kalman filter 4.3.2.2 Kalman filter results
output, sensitivity 4.1 Automatic sensitivity computation
output, SVD 4.5.3 Singular Value Decomposition run and output

P
printing 2.4.2 Controlling the printout and data output
Programming environments A.1 Programming environments
propagator 4.6 Generalized linear tangent system analysis

R
requirements, with make A.4.1 Additional requirements for Miniker with make
res.data 2.3.3 Running a simulation and using the output
results, Borel sweep 4.4.2 Borel sweep results
results, Kalman filter 4.3.2.2 Kalman filter results
run, GTLS 4.6.3 Generalized tangent linear system analysis run and output
run, SVD 4.5.3 Singular Value Decomposition run and output
running model 2.3.3 Running a simulation and using the output

S
select flag 3.1 Overview of additional features setting
selseq.kumac 3.1 Overview of additional features setting
selseq.kumac A.3 Miniker with cmz
sens.data 4.1 Automatic sensitivity computation
sensitivities 4.1 Automatic sensitivity computation
sensitivity, output 4.1 Automatic sensitivity computation
sequence 2.1 General structure of the code
sequences 2 Miniker model programming
sigma.data 4.1 Automatic sensitivity computation
Singular Value Decomposition 4.5 Stability analysis of fastest modes
sltc.exe 4.5 Stability analysis of fastest modes
sltc.exe 4.5.3 Singular Value Decomposition run and output
sltcirc.exe 4.6 Generalized linear tangent system analysis
sltcirc.exe 4.6.3 Generalized tangent linear system analysis run and output
smod 4.5.1 Singular Value Decomposition with cmz
smod 4.6.1 Generalized tangent linear system with cmz
starting point Starting points
state matrix 4.5 Stability analysis of fastest modes
SVD 4.5 Stability analysis of fastest modes
SVD output 4.5.3 Singular Value Decomposition run and output
SVD run 4.5.3 Singular Value Decomposition run and output

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