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(21 Jul 2015,
Scientific Computing Lab
Scientific Computing Lab
The student should achieve a basic understanding of
time series data with stationary noise and signals
statistical concepts (moments, median, higher moments)
template placement, mismatch, ROC curve
sensitivity computational cost analysis
parallelization with a cluster using condor
find the right parameter in data with noise
noise realization, statistical properties of noise, plot different realizations of noise and properties there-of (moments, rms)
properties of simple signal without noise, plot different sample systems, i.e.
work with different files, store these in SCM
adding signal + noise, plot various realizations
learn to use
, our small black box program computing a scalar result based upon input time series and parameter point
start to learn how prober results vary w.r.t. varying input parameters of injected signal while probing the same parameter point
plot/document result findings, e.g. how large may the mismatch between injection and probe parameter may become, what about weak signals?
develop strategy to find signal with prober if signal parameters
with this strategy perform multiple injections to arrive at mismatch graphs (with and without signals) and ROC curve to evaluate template bank properties
repeat with coarser and finer template bank
plot always means a graphical output with proper labels, title
The student should have at least basic knowledge of
C programming language
scripting language (Python is particularly useful)
SCM (software configuration management) tool (git)
basic statistical working knowledge (mean. variance, higher moments), time series analysis
using debugging, profiling and performance monitoring tools
construct a Makefile
writing of programs to solve particular problems
creating data type precision problems
discovering and handle IO problems
software configuration management
download and compile the LAL software
parallel programming skills, such as GPU programming, MPI and
the usage of condor to manage jobs
generating DAG-man jobs
generate a random and a stochastic template bank
generate a mismatch statistic of a random, a stochastic and an optimized template bank, what is the meaning of it
generate a roc curve, explain the consequences in terms of data analysis resources and sensitivity
find an injected signal
find correlation between different signals
Percival, Walden: "Spectral Analysis for Physical Applications : Multitaper and Conventional Univariate Techniques"
Porat "A Course in Digital Signal Processing"
E.T. Jaynes, "Probability. The logic of Science".
- 26 Jun 2015
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