Software and Foreground Subtraction Dave McGinnis 4/26/2010 - - PowerPoint PPT Presentation

▶
software and foreground
SMART_READER_LITE
LIVE PREVIEW

Software and Foreground Subtraction Dave McGinnis 4/26/2010 - - PowerPoint PPT Presentation

Oct 15, 2022 380 likes •731 views

21cm Instrument Simulation Software and Foreground Subtraction Dave McGinnis 4/26/2010 Foreground Subtraction - McGinnis 1 SKY SIMULATION SOFTWARE 4/26/2010 Foreground Subtraction - McGinnis 2 Code Suite 20 Java classes organized into

slide-1
SLIDE 1

21cm Instrument Simulation Software and Foreground Subtraction

Dave McGinnis

4/26/2010 1 Foreground Subtraction - McGinnis

slide-2
SLIDE 2

SKY SIMULATION SOFTWARE

4/26/2010 2 Foreground Subtraction - McGinnis

slide-3
SLIDE 3

Code Suite

  • 20 Java classes organized into 7 packages
  • Major Packages

– Sky Map Generator – Cylinder Visibility Simulator – Cylinder Visibility Modeler – Sky Reconstructor

4/26/2010 3 Foreground Subtraction - McGinnis

slide-4
SLIDE 4

Sky Map Generator Plotter for Haslam Sky Map at 1.4 GHz

  • Maps in

Healpix format

– Nside = 512

  • Maps use

MIT Angelica 10 parameter frequency fit

  • Maps are

about 100MB in size

4/26/2010 4 Foreground Subtraction - McGinnis

slide-5
SLIDE 5

Cylinder Visibility Formulation

http://projects-docdb.fnal.gov/cgi-bin/ShowDocument?docid=778

4/26/2010 5 Foreground Subtraction - McGinnis

slide-6
SLIDE 6

Cylinder Visibility Simulator

Sky Map Cylinder 1 Description Cylinder 2 Description Scan Parameters Mean & Sigma Generator Noise Generator Resolution Bandwidth Integration Time Visibility Simulation

4/26/2010 6 Foreground Subtraction - McGinnis

slide-7
SLIDE 7

Cylinder Description XML Format

4/26/2010 7 Foreground Subtraction - McGinnis

slide-8
SLIDE 8

Noiseless Pittsburgh Cylinder Visbility due to a Point Source

4/26/2010 8 Foreground Subtraction - McGinnis

slide-9
SLIDE 9

Pittsburgh Cylinders Visibility 25 MHz

  • Res. BW

1 day integration 100 day integration

4/26/2010 9 Foreground Subtraction - McGinnis

slide-10
SLIDE 10

Cylinder Modeler

http://projects-docdb.fnal.gov/cgi-bin/ShowDocument?docid=838

4/26/2010 10 Foreground Subtraction - McGinnis

slide-11
SLIDE 11

Cylinder Visibility Modeler

Cylinder 1 Description Cylinder 2 Description Scan Parameters Modeler Model Mode Matrix Number of RA modes

4/26/2010 11 Foreground Subtraction - McGinnis

slide-12
SLIDE 12

Sky Reconstruction

Visibility 1 Scan Visibility 1 Model

Reconstructor

Sky Map Visibility n Scan Visibility n Model

4/26/2010 12 Foreground Subtraction - McGinnis

slide-13
SLIDE 13

Pair and Auto Pittsburgh Cylinder Haslam Map Reconstruction

4/26/2010 13 Foreground Subtraction - McGinnis

slide-14
SLIDE 14

FOREGROUND SUBTRACTION FLUCTUATING SKY PATCH

4/26/2010 14 Foreground Subtraction - McGinnis

slide-15
SLIDE 15

Sky Model Subtraction Algorithm

  • Take cylinder visibility data and subtract a

simulation of a smooth sky into a cylinder model

  • From the sky difference map, fit each visibility

spectrum “pixel” as a nth order polynomial in frequency

  • Subtract the smoothed pixel trace from the

difference map pixel by pixel

  • Further FFT filter in frequency each the

remaining pixel trace

4/26/2010 15 Foreground Subtraction - McGinnis

slide-16
SLIDE 16

Angelica Sky Map

4/26/2010 16 Foreground Subtraction - McGinnis

slide-17
SLIDE 17
  • Freq. Fluctuation Patch

r.m.s radius = 3 degrees

4/26/2010 17 Foreground Subtraction - McGinnis

slide-18
SLIDE 18
  • Freq. Fluctuation Patch Temperature vs

Frequency

4/26/2010 18 Foreground Subtraction - McGinnis

slide-19
SLIDE 19

Pittsburgh Cylinder Simulations Sky Scan

12 order smooth

  • Freq. Fluctuation Patch

Only Clean Sky + Freq. Fluctuation Patch Imperfect scan – perfect scan

4/26/2010 19 Foreground Subtraction - McGinnis

slide-20
SLIDE 20

RA DFT of Pittsburgh Cylinder Simulations

12 order smooth Freq. Fluctua tion Patch Only Clean Sky + Freq. Fluctuat ion Patch Imperf ect scan – perfect scan

4/26/2010 20 Foreground Subtraction - McGinnis

slide-21
SLIDE 21

Mode Mixing Smoothness

4/26/2010 Foreground Subtraction - McGinnis 21

“Hot Pixel” track before Sky Subtraction “Hot Pixel” track after Sky Subtraction

slide-22
SLIDE 22

Smoothed Sky Subtraction Algorithm

  • Take cylinder visibility data smooth it along the

frequency axis using a N order polynomial for each pixel

  • Subtract the smoothed map from the raw map

producing a difference map

  • From the difference map, fit each visibility spectrum

“pixel” as a nth order polynomial in frequency

  • Subtract the smoothed pixel trace from the difference

map pixel by pixel

  • Further FFT filter in frequency each the remaining

pixel trace

4/26/2010 22 Foreground Subtraction - McGinnis

slide-23
SLIDE 23

Pittsburgh Cylinder Simulations Sky Scan

12 order smooth

  • Freq. Fluctuation Patch

Only Clean Sky + Freq. Fluctuation Patch Raw scan– smoothed scan

4/26/2010 23 Foreground Subtraction - McGinnis

slide-24
SLIDE 24

RA DFT of Pittsburgh Cylinder Simulations

12 order smooth Freq. Fluctua tion Patch Only Clean Sky + Freq. Fluctuat ion Patch Raw scan – smooth ed scan

4/26/2010 24 Foreground Subtraction - McGinnis

slide-25
SLIDE 25

Foreground removal using BAO Simulations

  • For simplicity - “use high resolution telescope

model”

– Pittsburgh telescope cannot resolve first BAO peak

  • Use BAO simulations of the first peak from

Nick Gnedin

– 1000 frequency points from 400-1400MHz – Nside=128

4/26/2010 25 Foreground Subtraction - McGinnis

slide-26
SLIDE 26

BAO Signal First Peak from 400-1400MHz

4/26/2010 26 Foreground Subtraction - McGinnis

slide-27
SLIDE 27

BAO First Peak 3-D K space

4/26/2010 27 Foreground Subtraction - McGinnis

BAO First Peak from 500-1300MHz; Kperp at “k|| = 0 ”; ResBW = 1/128 MHz BAO First Peak from 500-1300MHz; kperp vs “k||” ;ResBW = 1/128 MHz k k BAO First Peak in 3-D k-Space at 750 MHz – ResBw = 1/128 MHz k k kz kperp kz Freq Freq

slide-28
SLIDE 28

BAO + Smooth Sky ResBW = 1/128 MHz

4/26/2010 28 Foreground Subtraction - McGinnis

slide-29
SLIDE 29

BAO + Smooth Sky at 700 MHz ResBW = 1/128 MHz

kperp at k|| = 0 slice kperp vs “k||”

4/26/2010 29 Foreground Subtraction - McGinnis

slide-30
SLIDE 30

Smoothed Sky Algorithm in Reconstructed K-space

  • Work in reconstructed sky transverse kspace

– Removes using up polynomial fitting “horsepower” on mode mixing

  • Smooth in frequency by fitting an N order

polynomial along frequency axis for each transverse k space pixel

  • Subtract smoothed kspace from raw kspace
  • Fourier transform along frequency axis
  • Look the transverse kspace slices at high k||

mode number.

4/26/2010 30 Foreground Subtraction - McGinnis

slide-31
SLIDE 31

BAO + Smooth Sky at 700 MHz with Foreground Removal ResBW = 1/128 MHz

kperp at k|| = 0 slice kperp vs “k||”

4/26/2010 31 Foreground Subtraction - McGinnis

slide-32
SLIDE 32

Foreground Removal (Fermilab)

BAO First Peak in 3-D k-Space (Gnedin) BAO First Peak and Foreground in 3-D k-Space BAO First Peak and Foreground with Foreground Removal in 3-D k-Space k k kz

slide-33
SLIDE 33

Summary

  • We have developed fairly sophisticated

– Instrument modeling software – Sky Reconstruction software – BAO and foreground sky maps

  • We have began initial tests of foreground removal algorithms

– Sky model subtraction algorithm on the raw data cube – Smoothed sky subtraction algorithm on the raw data cube – Smoothed sky subtraction algorithm in reconstructed k-space

  • Initial results look promising

– Can remove 5 orders of magnitude of foreground on a raw data cube – Can see the first BAO peak behind foregrounds in reconstructed k- space (6 orders of magnitude reduction)

4/26/2010 33 Foreground Subtraction - McGinnis

slide-34
SLIDE 34

Future Work

  • Add 2nd and 3rd BAO peaks
  • Try “smooth” cuts of large foregrounds
  • Try pattern recognition of BAO sphere
  • Examine the effects of noise
  • Examine the effects of calibration errors

4/26/2010 Foreground Subtraction - McGinnis 34