Interstellar dust clouds 
| Quendella quennie
Taylor
from Northern Arizona University REU program-Summer
2003
Research
projects of other REU students
|
Interstellar dust clouds
* In the process of gaining full understanding of astronomy
as a whole , we need to understand the fundamental parts of it. Understanding
star formation will lead into understanding galaxies , in general most parts
of astronomy.
Moreover we will be able to explain other fundamental areas for instance
HR diagram, and more. We will be able to tell how many supergaint
star may form if any , through that we can infer how many supernova
will come about due to this stars. To end this breif introduction , the
possibilities are endless.
As an intern I am currently working with four object
that have some amounts of dust clouds ; pleiades , orion , flame and
m17. My reseach requires that I use the powerspetrum(P(Q)) and the
structurefunction (SF) to explain the behavior of turbulence within the dust
cloud. In general both these functions are made usefull by producing
various slopes . From the slope one can determine if there is more
or less turbulance in that cloud , in other words if a cloud has star within
one will expert that the distrubution of the turbulance would suggest what
happens in the clouds around the star. Whether stars form when there are more
or less turbulane or if turbulace distribution determine the mass of the
star, those are questions we strive to answer.
Understanding what the basic output of the PS and the SF were
the intial stage of the project.
For example lets look at the out put graph of m17(1) . Since the star population
present in m17 is very low in the sub regions. Sub regions in the context
are regions that have their stars removed, hence th e slope will
be flat and if there were stars there will be big jump or bumps. In figure
m17(3), a sin function , a tangent function and three bumps were placed in
the program, as to behave like an actual star., thereby producing picks
and valleys. Also in figure m17 (2) the stars have been removed
but as shown there is still a hump. So the next step will be be to manually
remove them.
In figure m17(4) has relatively no star , so the slope that was
produce is the flatest it can be. As one can infer from the the differences
presented by the various slopes, if one were to take only the star presences
into account then it will be a bump, and if you were to take the region without
star one will aspect the flat slope. . Now with the basic variety of slopes
, the fundamentle aspect will be undestood.
Below are differnt slope with diferent inputs from the powerspectrum and
structfunction.
|
|
|||||||||||||||||||||||||||
m17 with stars removed
m17 with star re- removed
m17with stars |
|
|
ghape
picture
Understanding the out put is important , but understanding what the P(Q)
and SF is also crucial. The Powerspectrum measures the power in a specific
region while the Structfunction measures the spatail difference. In other
woeds the PS measure the amount of power over the region specified and
the Sf measures how much differnce there is from one point to another in
a specified region also.
Powerspetrum P(Q) =| f[Q}|^2 Q[k]=f[Q]= integral (Q(x)e^(-ikx)dx)
f = Le Fourier tranformer x =spatial
coordinate ; V= velocity, k =wave lenght , K=kinetic energy ,
d=density Q=
kinetic energy ,
" what is looked for below is the velosity
, since the density in incompressible, in Kolmogov"
K=1/2 d V^2." In addition V^2= esin .k^(-5/3)
Q is also proportional to k^beta " beta =-1.66
or -2.00
According to the Kolmogovo theory energy
isinjected on a large scale and beta = -1.66
On the other hand Burgeus's is when energy is injected
in shocks and in this case beta= -2.00
Structfunction SF(l) = <(Q(x)-Q(x+l))^2> or integral ( (Q(x)-Q(x+l))^2
dx) l= spatisl distance
"here if Q(x)= Q(x+1), then
SF(l) =0"
One more important relationship between P(Q) and SF is that the wavelength
is the inverse to the spatail distance.
That is why you have a negative slope for the powerspetrum and a positive
for the structfunction.
Since one may be alitle bit formiliar with these function as I was
, it is time tfor it to be put into usefullness.
Since a significent amount of time was spent on the orion nebula,
the estsblishment of the various slopes,of various 1024
by 1024 array were produce form the 2 mass data. In this case
the same region were used but with different wave lenght. To be specific three
region were subtracted ;orion 10 ,20,30, and they are in order of increase
in amount of contents.
Using the same region the stars were removed and hence orionsub 10,20and
30. These slopes were produce by running the PF, and the were measure on the
same scale. In other word s they all have the same k range which
is the log wave number and they are all products of circular averaging.
orion j band
h band k band
|
orion10 k
orion20
k
orion30 k
|
|||||||||||||||
|
|
As one can infer from the above data, it will plausible to say that
regions with more clouds have steeper slopes.
Thi s information can be understood as an increase in turbulance, in regions
with more clouds, which should be accurate.
Although one will be accurate to make the observation that not all the star
were remove, all the possible star that were left
do not have effect on the output of the sub regions. With or without stars
one should be able to notice the trend.
Taking account of the three wave lenght, J, H,K, listed in order
of shortest emission to longest emission, one can
see that in the K band the slope is also steeper . This could be due the
fact that in the K band there is more emission to be seen. Futhermore if everthing
is to be considered it will be again accurate to infer that star formation
will lik;y occur in areas of clouds and some amount of turbulance.
We know what is going on in these region s , but the next thing will be
understanding what is going on in
a more specific spot . In this situation be must imploy the structurefunction
(SF) , in so doing we get more accurate
data . Using orion30k with the stars remove , there are
two main parts that have some form of a star or very brigth emission coming
from it. With these two part analyzied one will have the ability to
comprehend what exactly is goin g
on intside th e clouds that are still surrounding young star in this particular
cloud ,, this specific cloud ,because it may differ in other clouds with
different star formation occuring.
Each part will have a common center , that will be centered on th e star
or the bright emission area . Then between two circles of different
raduis the SF will produce the slope for that particular area. The data
is presented below.
the slopes does increase as it gets near the star , but when it get to a point where the star is right in the area the slope decreases . This maybe due to the fact that the star itself is taking or giving power to the clouds right around it. |
this is the first part of orion
tha t I worked
on . |
Below are the regions I worked with. After viewing the picture below one
can infer that the intensity increases as one gets closer to th e star froming
region or in the case of M17 an evolved supergaint star. This star is about
eleven thousand times as luminous as the sun, therefore it will be acurate
to say it feeds most of the enery in this region.
The MXS data of the flame nebula was
compared to the 2mass data of the
flame nebula, and as expected the was more diffused emission
with the MXS, but of course at alower resulution. The slope field of flame nebula (MXS),
is more
defined compared to the slope field
of flame nebula (2mass). This is due to the star presence in the 2mass
data , which in turn is due to a lower wave lenght .In the slope fields
of power spectrum black means very steep and bright colouring means flat
slope. For the structure function bright means steep and black means flat.
1. The second part of orion that
i worked with
2. orion with slopes overplotted
over it (powerspectrum)
3. The slope field of orion
. The protion of orion that is shown stressed on the center;due
to the luminousity of the star
forming region. Due to that one may not be able
to see some of the diffused emission. Therefore the slope field has
more steepness compare to the slope overplot
or what is present in that picture.
1. The slope of M17 overplotted
on the image (2mass)
2. The slope field of m17(powerspectrum)
"With the powerspectrum black means steep." .
3. The slope of M17
overplotted on the image ( 2mass) SF(l)
4.The slope field of
M17 (structurefunction) "with the powerspectrum black means flat
,brigth means steep."
CONCLUSION
With each region analysized
with the power spectrum and structure function , it will be acurrate
to say that region s
surrounding star forming areas are have high intensity in their turbulence.
My taking out stars , we have learned that the
power spectrum errors will be high compare to that of the structure function.
This is because the structure function does
not need every grid point in other to produce accurate results and it can
it also be used to mask out points within a region.
For future work, we will most definately mask out regions,
since I did not get the chance to do that.
In my reseach we primarily used MXS which is at a wave lenght of 8microns
, but in the future when GLIMPSE bring back its data which extends the wave
lenght of 2 mass ,when viewing at * microns one will have higher resolution
compared to MXS. Being able to analyze one region through 7 different wave
lenght , that is three from 2 mass and four from GLIMPSE, will prove
to be an excellent source of acuracy.
This wed cite is always underconstruction
sorry ,
NASA Astrophysics Data Service
