Thursday, December 1, 2011
Thursday, November 10, 2011
Saturday, July 23, 2011
http://www.ibtimes.com/articles/185599/20110723/astronomers-largest-most-distant-reservoir-of-water.htm
look more into the research done for this article, try to find this on xassist
agenda
today
for next time
Monday, July 18, 2011
poster template
http://people.oregonstate.edu/studentgroups/siam/sites/default/files/OSUposter_1.pdf
agenda
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8-
9-
10-
11-
12-
1-
2-
3-
4-
5-
6-
today
for next time
agenda
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-
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8-
9-
10-
11-
12-
1-
2-
3-
4-
5-
6-
today
for next time
Friday, July 8, 2011
To do every morning
STARTING THE DAY
open up window with -gmail, blogger, and google docs
open up another blogger window
open up mkeck folder in windows viewer
open up window with -gmail, blogger, and google docs
open up another blogger window
open up mkeck folder in windows viewer
HOW TO USE BLOG EFFECTIVELY
Use the blog in conjunction with google docs. Take notes on here, and save xspec input and output files, python files, and other notes on google docs.
Thursday, July 7, 2011
agenda
Run through as many models as you can
1.-simulate sources with 2-10 keV flux = 1e-14, 1e-13, 1e-12 and a power-law spectrum with photon index (gamma) = 1.0, 2.0 and an iron line at 6.4 keV with width = 0.001 keV and normalization = 1e-6 and 1e-5.
Then get errors on photon index, gaussian energy, width, norm. for 10, 20, 50, 100 ks exposures.
2-. Grab point source arf, with optical blocking filter.
It would be interesting to try iterating through the different rmfs to see what impact those different designs have but start with the current best estimate one.
3.Models to start with would be
powerlaw + diskline, ignoring 0.0-2.0 and 10.-** (i.e., ignore below 2 keV since the disk line won't have any impact below something like 4 keV and you want to go below where the diskline is contributing strongly to the spectrum to make sure the powerlaw is being fit properly). Then fit this with the input diskline model, trying to unfreeze various parameters to see if they are being constrained. That is a qualitative statement but a quantitative version would be that the parameter errors don't hit boundaries that are built into the model. xspec lets you set a "soft" and a "hard" range for each parameter. I don't recall exactly what soft means but it impacts the fitting procedure in a way that the fit is steered away from the soft boundary. The hard boundary means that the fit parameter is not allowed to go past that point. So for photon index, the default hard boundary is -3 to 10 and the soft boundary is -2 to 9. You can set this when you do "newpar", e.g.,
newpar 1 2.0 0.01 -4 -3 10 15
changes the boundaries to -4 to 15 and -3 to 10.
The default ranges for parameters for xspec models are usually physically motivated and/or based on experience... it is very rare to see a photon index < -2 or > 9. Typical values are 0-3. So if the fit goes to -2 or -3 there is a good chance that something is wrong or that the power-law is really being used to fit something that isn't really a power-law.
4-You can also do the above with absorption (i.e., due to gas between the satellite and the source, again mostly due to gas in the Milky Way and the host galaxy of the source):
model phabs * (powerlaw + diskline)
5-Also try
phabs * apec
6-model phabs * (powerlaw + diskline)
-model phabs * apec # with different values of Nh,kT, and abundance
fakeit none
-Then fits first with the apec model itself and see how constraints on Nh, kT, A come out and then fit with phabs * brem and then add in lines one at time
model phabs * brem
fit
# get errors
7. Take a simple power-law only model, run fakeit a larger number times, get the error on photon index, then plot the histogram of photon index best-fit values. From that histogram see where the 90% of the value are.
today
1 erg = 10^-7 joules!!
1 erg= 10^7 joules!!
1 erg= 10 ^7 joules!!
I need to practice my upper row typing!!!
the units of flux in are either photons*cm^-2*s^-1 or erg*cm^-2*s^-1 in xspec
-----
From the PyXspec website,
A class gives you the type, or definition of an object, and an object is a specific instance of a class.
"
This description uses the standard Python object-oriented terminology, distinguishing between classes and objects. Class is used when referring to the type or definition of an object. An object refers to a specific instance of a class and is normally assigned to a variable. For example a user may load 3 data files by creating 3 spectral data objects s1, s2, and s3, which are all instances of the class Spectrum.
The functions and stored data members that make up the definition of a class are referred to as methods and attributes respectively."
------------------------
practice programming!
http://projecteuler.net/
also, the python function type() tells you what type an object is
how to search for a file type or a file with a certain name
Use the wildcard, *
ls *text* to search for a file in a given name
ls *.doc looks for the doc extension, for example
if you want to remove a bunch of files with fake in their name, type
$ rm *fake*
-------------------------
Would making a dictionary be a better use of my time than a bunch of lists?
for next time
- try pyXspec at home (it appears not to be loaded on this computer)
- learn how to use the OS module in python!!
-go through walk through xspec tutorial on xspec website
-practice upper row typing
-review derivation for power law
-explore using dictionaries to keep models organized
Run through as many models as you can
1.-simulate sources with 2-10 keV flux = 1e-14, 1e-13, 1e-12 and a power-law spectrum with photon index (gamma) = 1.0, 2.0 and an iron line at 6.4 keV with width = 0.001 keV and normalization = 1e-6 and 1e-5.
Then get errors on photon index, gaussian energy, width, norm. for 10, 20, 50, 100 ks exposures.
2-. Grab point source arf, with optical blocking filter.
It would be interesting to try iterating through the different rmfs to see what impact those different designs have but start with the current best estimate one.
3.Models to start with would be
powerlaw + diskline, ignoring 0.0-2.0 and 10.-** (i.e., ignore below 2 keV since the disk line won't have any impact below something like 4 keV and you want to go below where the diskline is contributing strongly to the spectrum to make sure the powerlaw is being fit properly). Then fit this with the input diskline model, trying to unfreeze various parameters to see if they are being constrained. That is a qualitative statement but a quantitative version would be that the parameter errors don't hit boundaries that are built into the model. xspec lets you set a "soft" and a "hard" range for each parameter. I don't recall exactly what soft means but it impacts the fitting procedure in a way that the fit is steered away from the soft boundary. The hard boundary means that the fit parameter is not allowed to go past that point. So for photon index, the default hard boundary is -3 to 10 and the soft boundary is -2 to 9. You can set this when you do "newpar", e.g.,
newpar 1 2.0 0.01 -4 -3 10 15
changes the boundaries to -4 to 15 and -3 to 10.
The default ranges for parameters for xspec models are usually physically motivated and/or based on experience... it is very rare to see a photon index < -2 or > 9. Typical values are 0-3. So if the fit goes to -2 or -3 there is a good chance that something is wrong or that the power-law is really being used to fit something that isn't really a power-law.
4-You can also do the above with absorption (i.e., due to gas between the satellite and the source, again mostly due to gas in the Milky Way and the host galaxy of the source):
model phabs * (powerlaw + diskline)
5-Also try
phabs * apec
6-model phabs * (powerlaw + diskline)
-model phabs * apec # with different values of Nh,kT, and abundance
fakeit none
-Then fits first with the apec model itself and see how constraints on Nh, kT, A come out and then fit with phabs * brem and then add in lines one at time
model phabs * brem
fit
# get errors
7. Take a simple power-law only model, run fakeit a larger number times, get the error on photon index, then plot the histogram of photon index best-fit values. From that histogram see where the 90% of the value are.
today
1 erg = 10^-7 joules!!
1 erg= 10^7 joules!!
1 erg= 10 ^7 joules!!
I need to practice my upper row typing!!!
the units of flux in are either photons*cm^-2*s^-1 or erg*cm^-2*s^-1 in xspec
-----
From the PyXspec website,
A class gives you the type, or definition of an object, and an object is a specific instance of a class.
"
This description uses the standard Python object-oriented terminology, distinguishing between classes and objects. Class is used when referring to the type or definition of an object. An object refers to a specific instance of a class and is normally assigned to a variable. For example a user may load 3 data files by creating 3 spectral data objects s1, s2, and s3, which are all instances of the class Spectrum.
The functions and stored data members that make up the definition of a class are referred to as methods and attributes respectively."
------------------------
practice programming!
http://projecteuler.net/
also, the python function type() tells you what type an object is
how to search for a file type or a file with a certain name
Use the wildcard, *
ls *text* to search for a file in a given name
ls *.doc looks for the doc extension, for example
if you want to remove a bunch of files with fake in their name, type
$ rm *fake*
-------------------------
Would making a dictionary be a better use of my time than a bunch of lists?
for next time
- try pyXspec at home (it appears not to be loaded on this computer)
- learn how to use the OS module in python!!
-go through walk through xspec tutorial on xspec website
-practice upper row typing
-review derivation for power law
-explore using dictionaries to keep models organized
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