Further Progress on Bright Star Photometry
--- 1-D Profile Fitting
CX 10.25.00
This is the third progress report on the recent development of bright star photometry task.I am continuing the 1-d profile fitting (see previous two reports dated 7.20.00 and 9.20.00,
repectively) using a large sample of 502 stars (including many unsaturated stars of
~ 6 mag) provided by Raymond Tam.
I. Assumptions (same as in Report 2):
i) For a given camera (e.g. the J-band camera in northern observatory),
counts of 'good pixels' are proportional to
the brightness of the star in question.
ii) The CIO magnitudes are accurate.
iii) Stars are non-variables.
II. 'Bad pixels' (same as in Report 2 except for items v and vi):
i) Counts < cut_l, where cut_l=min(5*rms, cut_b). rms is
determined using pixels in r > 30 (i.e. > 60").
For very bright
stars, the rms so determined may be affected by
the gradient and
therefore overestimated. Then cut_l=5 rms
will be replaced by
cut=cut_b, where
cut_b=100 DN for J band,
cut_b=80 DN for H band,
cut_b=40 DN for K band.
ii) Counts > 40000DN.
iii) when more than 20 percent of pixels in an annulus (width=1pix)
have
counts < cut_l, all the pixels in that
annulus are excluded.
iv) when more than 20 percent of pixels in an annulus have
counts > 40000DN, all the pixels are dropped.
v) pixels in the adjacent annulus next to the one where more
than 20
percent pixels have counts > 40000DN, will
also be dropped.
vi) for a given annulus, pixels with counts higher than mean+2sigma
or lower than mean-2sigma (i.e. '2sigma+'
pixels) are dropped.
III. Grand 1-d psfs
1) Function form of the grand 1-d psf's (same as in Report 2):
f=f0*exp(-(r/r0)^2) + f1*exp(-(r/r1)^p)
+ f2/(1+(r/r2)^2)^q
Parameters (8): f0, f1, f2, r0, r1, r2, p, q.
2) Procedure (same as in Report 2):
i) Stars are binned according to (a)
hemisphere ('n' or 's') and (b) see_shape (S_sh).
ii) In the first step, 'good pixels' of all
stars in a given bin are included
in the
grand-1d psf. The counts are normalized as following:
cnt_1=cnt*10^(-0.4*(m_cio-m_0))
where
m_0 = 6, 5.5, 5 for J, H, Ks band, respectively.
iii) For each camera and each S_sh bin, a grand
1-d psf is constructed
using
the 'good pixels' of the stars, and an analytical 'best fit' function
of the
form given above (8 parameters) is determined.
iv) This grand 1-d psf is then applyed to
the 'good pixels' (uniform weighting)
of the stars, and an estimate of magnitude is obtained (m_2mass).
v) The deviation between the magnitude
and the CIO magnitude is
calculated (e.g. dj = J_2mass - J_cio).
vi) Stars with magnitude deviation >
0.5 mag are deem outliers.
vii) Dispersion of magnitude deviation is
calculated, with the outliers
exceluded.
xi) 1-d grand psf is then reconstructed
with outliers dropped, and with
the normalization estimated from m_2mass (instead of m_cio).
x) Steps between iv -- xi
are repeated once more.
3) Results:
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4) Grand 1-d PSFs (analystical fit) in one plot:
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IV. Results from 1-d fitting
1) Dispersions. Bin boundaries and number of sources
included in each bin are the same as
in the 1-d grand psf process (previous
table). Outliers are excluded.
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2) Systematic uncertainties:
i) Errors of CIO magnitudes (~0.1 -- 0.2 mag).
ii) Variablity of stars (main reason for the outliers).
iii) Binary stars (affecting the profiles).
3) Individaul stars:
| scan |Jcio|Hcio|Kcio| jzero| hzero| kzero| jssh | hssh| kssh| J2m | H2m | K2m | dj | dh | dk | | | | | | | | | | | | | | | | | | 990916s_141_211 -3.0 -4.0 -3.9 0.047 0.051 0.065 1.063 1.017 1.050 -3.18 -4.12 -4.80 -0.18 -0.12 -0.90 981019n_073_101 5.7 5.2 5.1 0.055 0.018 0.034 1.051 1.037 1.032 5.66 5.19 5.05 -0.04 -0.01 -0.05 981027n_055_043 5.8 5.5 5.4 -0.016 0.034 0.054 1.038 1.018 0.972 5.75 5.48 5.45 -0.05 -0.02 0.05 000319n_019_035 -0.8 -1.6 -1.9 0.127 0.032 0.067 1.002 0.965 0.974 -0.86 -1.76 -1.96 -0.06 -0.16 -0.06 991011n_115_100 -1.4 -1.7 -1.8 0.047 0.019 0.074 0.996 0.968 0.985 -1.27 -1.67 -1.70 0.13 0.03 0.10 000611n_112_077 99.9 99.9 2.7 0.051 0.032 0.071 1.008 0.958 0.965 99.99 99.99 2.77 99.99 99.99 0.07 000611n_049_120 0.8 -0.3 -0.6 -0.006 0.032 0.071 1.025 0.978 0.981 0.83 0.01 -0.45 0.03 0.31 0.15 991116s_021_300 4.2 3.3 3.1 0.021 0.068 0.086 0.987 0.981 1.000 4.12 3.18 3.35 -0.08 -0.12 0.25 991220n_037_053 2.3 2.3 99.9 0.136 0.040 0.072 1.115 1.059 1.054 2.20 2.34 99.99 -0.10 0.04 99.99 991024s_015_254 2.2 1.7 1.6 -0.138 -0.016 0.013 0.918 0.914 0.947 2.27 1.76 1.55 0.07 0.06 -0.05 991024s_073_265 2.1 1.3 1.1 -0.115 -0.016 0.013 0.922 0.903 0.940 2.02 1.20 0.95 -0.08 -0.10 -0.15 991024s_047_258 2.5 99.9 1.5 -0.125 -0.016 0.013 0.911 0.897 0.936 2.52 99.99 1.47 0.02 99.99 -0.03 000610n_096_054 99.9 99.9 1.7 0.052 0.033 0.073 1.003 0.948 0.962 99.99 99.99 1.82 99.99 99.99 0.12 000610n_066_085 99.9 99.9 1.9 0.025 0.033 0.073 1.037 0.977 0.981 99.99 99.99 1.93 99.99 99.99 0.03 991022n_071_147 99.9 99.9 2.1 0.095 0.041 0.092 1.016 0.998 1.009 99.99 99.99 99.99 99.99 99.99 99.99 000726s_116_301 5.0 5.0 5.0 0.123 0.083 0.100 0.940 0.915 0.959 5.13 4.99 4.98 0.13 -0.01 -0.02 991020s_040_278 3.5 2.5 2.2 0.140 0.049 0.065 0.972 0.949 0.978 3.29 2.37 1.99 -0.21 -0.13 -0.21 981123n_074_089 4.8 4.9 4.9 0.128 0.065 0.069 1.029 1.017 1.025 99.99 99.99 4.62 99.99 99.99 -0.28 991027n_042_148 1.9 1.1 0.8 -0.005 0.010 0.065 0.950 0.939 0.962 2.23 1.39 0.92 0.33 0.29 0.12 991111n_031_135 2.6 99.9 99.9 0.051 0.020 0.068 0.989 0.975 0.986 2.24 99.99 99.99 -0.36 99.99 99.99 991111n_127_062 99.9 99.9 2.4 0.036 0.020 0.068 1.030 0.979 0.989 99.99 99.99 2.26 99.99 99.99 -0.14 991021s_070_279 3.9 3.0 2.5 0.010 0.011 0.036 0.985 0.971 0.993 3.48 2.50 1.91 -0.42 -0.50 -0.59 000728s_151_255 5.2 4.2 4.0 0.096 0.073 0.086 0.940 0.924 0.950 5.08 4.15 4.03 -0.12 -0.05 0.03 000728s_152_256 3.8 2.8 2.6 0.097 0.073 0.086 0.946 0.929 0.954 3.78 2.84 2.52 -0.02 0.04 -0.08 991101n_066_033 99.9 99.9 2.7 0.159 0.041 0.089 0.954 0.917 0.942 99.99 99.99 2.68 99.99 99.99 -0.02 991101n_028_032 3.4 2.4 2.0 0.162 0.041 0.089 0.955 0.917 0.931 3.76 2.72 2.29 0.36 0.32 0.29 991123n_048_024 99.9 99.9 1.8 0.154 0.045 0.086 1.036 0.979 0.988 99.99 99.99 1.64 99.99 99.99 -0.16 991221n_182_025 99.9 99.9 2.7 0.157 0.046 0.080 1.098 1.051 1.045 99.99 99.99 2.65 99.99 99.99 -0.05 991221n_238_091 5.3 4.5 2.7 0.140 0.046 0.080 1.073 1.029 1.034 5.34 3.79 2.50 0.04 -0.71 -0.20 991221n_281_082 4.2 4.1 4.1 0.127 0.046 0.080 1.024 0.983 0.994 4.27 4.10 4.04 0.07 0.00 -0.06 991203s_048_321 5.2 4.3 4.1 0.003 0.068 0.075 0.993 0.975 0.997 5.09 4.13 4.07 -0.11 -0.17 -0.03 991203s_095_213 3.1 99.9 99.9 0.037 0.068 0.075 0.988 0.949 0.995 3.13 99.99 99.99 0.03 99.99 99.99 991203s_101_214 3.7 2.8 2.3 0.044 0.068 0.075 0.989 0.953 0.994 3.75 2.59 2.00 0.05 -0.21 -0.30 991203s_110_215 99.9 99.9 3.0 0.049 0.068 0.075 0.974 0.950 0.987 99.99 99.99 2.94 99.99 99.99 -0.06 991116n_076_164 99.9 99.9 2.1 0.053 0.022 0.074 1.019 0.996 1.005 99.99 99.99 2.33 99.99 99.99 0.23 991116n_034_134 1.8 99.9 99.9 0.053 0.022 0.074 1.003 0.975 0.988 1.65 99.99 99.99 -0.15 99.99 99.99 991026s_030_280 0.8 0.9 0.9 -0.045 0.015 0.034 0.943 0.936 0.966 0.73 0.82 0.79 -0.07 -0.08 -0.11 991002s_091_257 0.5 -0.4 -0.6 -0.088 -0.030 0.001 1.038 1.011 1.033 0.37 -0.39 -0.61 -0.13 0.01 -0.01 991010n_090_107 99.9 99.9 3.0 0.112 0.031 0.083 1.211 1.157 1.144 99.99 99.99 2.58 99.99 99.99 -0.42 991010n_031_154 99.9 99.9 3.0 0.083 0.031 0.083 1.060 1.049 1.052 99.99 99.99 2.97 99.99 99.99 -0.03 991010n_035_155 99.9 99.9 2.3 0.086 0.031 0.083 1.009 0.999 1.008 99.99 99.99 2.41 99.99 99.99 0.11 000729s_157_302 2.3 2.2 2.1 0.077 0.071 0.087 1.053 1.040 1.051 2.18 2.10 2.11 -0.12 -0.10 0.01 980913s_039_228 -1.9 -2.1 -9.2 0.022 -0.005 0.009 0.965 0.950 0.985 5.25 5.42 4.68 7.15 7.52 13.88 991121s_101_221 1.9 1.0 0.5 0.099 0.073 0.078 0.973 0.945 0.984 1.63 0.80 0.44 -0.27 -0.20 -0.06 991121s_017_308 0.6 -0.1 -0.1 -0.005 0.073 0.078 0.986 0.986 1.002 0.56 -0.09 -0.25 -0.04 0.01 -0.15 991027s_060_281 5.0 4.0 3.4 -0.005 0.028 0.043 0.948 0.934 0.963 4.72 3.73 3.13 -0.28 -0.27 -0.27 991027s_112_282 1.9 1.0 0.6 0.006 0.028 0.043 0.963 0.944 0.976 1.67 0.83 0.42 -0.23 -0.17 -0.18 991125n_211_098 99.9 99.9 2.8 0.182 0.040 0.081 1.076 1.023 1.026 99.99 99.99 2.85 99.99 99.99 0.05 991125n_252_152 99.9 99.9 2.3 0.156 0.040 0.081 1.013 0.983 0.989 99.99 99.99 2.25 99.99 99.99 -0.05 991125n_263_153 99.9 99.9 1.2 0.150 0.040 0.081 1.108 1.063 1.058 99.99 99.99 1.05 99.99 99.99 -0.15 991125n_306_125 99.9 99.9 2.1 0.122 0.040 0.081 0.997 0.959 0.974 99.99 99.99 1.97 99.99 99.99 -0.13 991125n_182_073 4.6 4.4 4.3 0.201 0.040 0.081 1.064 1.025 1.027 4.82 4.63 4.35 0.22 0.23 0.05 991124n_075_055 2.7 99.9 2.0 0.124 0.038 0.081 1.002 0.960 0.972 2.81 99.99 2.10 0.11 99.99 0.10 991021n_104_136 99.9 99.9 2.9 0.184 0.054 0.101 1.040 1.013 1.017 99.99 99.99 2.78 99.99 99.99 -0.12 991021n_114_137 4.5 99.9 99.9 0.184 0.054 0.101 1.057 1.028 1.033 4.66 99.99 99.99 0.16 99.99 99.99 000203s_015_236 3.2 2.8 2.7 -0.071 0.011 0.027 1.086 1.051 1.059 3.33 2.82 2.81 0.13 0.02 0.11 000203s_073_202 2.4 1.5 1.3 -0.066 0.011 0.027 0.942 0.921 0.959 2.48 1.62 1.31 0.08 0.12 0.01 000203s_076_205 99.9 99.9 2.5 -0.066 0.011 0.027 0.949 0.928 0.971 99.99 99.99 2.39 99.99 99.99 -0.11 991030s_089_233 0.2 0.2 0.2 -0.029 0.017 0.042 0.943 0.920 0.954 0.15 0.23 0.30 -0.05 0.03 0.10 991030s_093_248 4.7 99.9 4.9 -0.031 0.017 0.042 0.948 0.929 0.965 4.96 99.99 4.91 0.26 99.99 0.01 991028n_119_149 99.9 99.9 1.6 0.018 0.013 0.066 0.965 0.945 0.964 99.99 99.99 1.65 99.99 99.99 0.05 991028n_132_150 99.9 99.9 1.9 0.021 0.013 0.066 0.998 0.973 0.986 99.99 99.99 1.64 99.99 99.99 -0.26 991104n_073_026 99.9 99.9 1.3 0.070 0.030 0.076 0.991 0.950 0.965 99.99 99.99 1.29 99.99 99.99 -0.01 991104n_113_111 1.5 0.7 0.5 0.083 0.030 0.076 1.032 1.000 1.007 1.47 0.90 0.64 -0.03 0.20 0.14 991217n_055_001 4.9 99.9 5.0 0.038 0.029 0.067 0.977 0.929 0.949 5.01 99.99 4.87 0.11 99.99 -0.13 991028s_072_283 2.7 1.8 1.6 0.022 0.036 0.051 0.954 0.936 0.968 2.77 1.84 1.49 0.07 0.04 -0.11 991028s_095_284 1.5 0.5 0.1 0.024 0.036 0.051 0.952 0.933 0.968 1.53 0.54 0.17 0.03 0.04 0.07 991207n_059_002 99.9 99.9 2.2 0.111 0.043 0.079 0.980 0.939 0.960 99.99 99.99 2.15 99.99 99.99 -0.05 991207n_079_003 99.9 99.9 2.6 0.115 0.043 0.079 0.984 0.939 0.955 99.99 99.99 2.58 99.99 99.99 -0.02 991207n_106_019 2.2 2.2 2.3 0.119 0.043 0.079 0.977 0.933 0.952 1.97 2.31 2.32 -0.23 0.11 0.02 000212n_018_167 2.9 2.2 1.8 0.095 0.024 0.059 0.996 0.973 0.988 3.00 2.07 1.75 0.10 -0.13 -0.05 000212n_042_020 4.3 3.5 3.0 0.092 0.024 0.059 1.030 0.981 0.990 4.57 3.43 3.05 0.27 -0.07 0.05 000212n_087_022 2.0 99.9 1.5 0.087 0.024 0.059 1.002 0.946 0.962 1.91 99.99 1.60 -0.09 99.99 0.10 000212n_089_023 99.9 99.9 2.3 0.087 0.024 0.059 1.049 0.990 0.997 99.99 99.99 2.23 99.99 99.99 -0.07 000205s_014_168 3.6 3.3 3.3 -0.115 0.003 0.020 1.033 1.008 1.029 3.65 3.29 3.34 0.05 -0.01 0.04 000205s_017_169 4.4 4.1 4.0 -0.114 0.003 0.020 1.006 0.986 1.009 4.41 3.57 3.90 0.01 -0.53 -0.10 000205s_117_251 2.6 1.8 1.2 -0.072 0.003 0.020 0.927 0.909 0.945 1.99 1.16 0.63 -0.61 -0.64 -0.57 981121s_043_237 -0.1 -0.9 -9.2 0.079 0.008 0.013 0.923 0.931 0.957 6.09 99.99 5.35 6.19 99.99 14.55 000204s_016_170 4.9 4.5 4.4 -0.147 -0.011 0.007 1.013 0.999 1.009 4.82 4.38 4.38 -0.08 -0.12 -0.02 991208n_063_004 2.1 99.9 1.6 0.134 0.042 0.073 1.121 1.062 1.059 1.76 99.99 1.28 -0.34 99.99 -0.32 991208n_068_005 3.8 99.9 3.9 0.129 0.042 0.073 1.085 1.026 1.033 3.98 99.99 3.83 0.18 99.99 -0.07 991029n_078_099 4.9 3.0 1.6 0.031 0.026 0.075 0.972 0.945 0.962 4.63 2.55 1.03 -0.27 -0.45 -0.57 000120s_019_171 3.9 3.4 13.2 0.002 0.036 0.047 0.957 0.942 0.983 3.69 3.10 7.73 -0.21 -0.30 -5.47 000120s_046_177 99.9 99.9 1.4 0.002 0.036 0.047 1.008 0.985 1.014 99.99 99.99 1.46 99.99 99.99 0.06 991218n_048_057 4.2 4.2 4.2 0.150 0.049 0.083 0.973 0.938 0.966 4.24 4.34 4.25 0.04 0.14 0.05 991218n_136_039 1.0 0.2 0.0 0.151 0.049 0.083 1.005 0.962 0.977 0.87 0.17 -0.07 -0.13 -0.03 -0.07 991218n_149_029 99.9 99.9 2.6 0.151 0.049 0.083 1.051 1.008 1.016 99.99 99.99 2.59 99.99 99.99 -0.01 000205n_016_006 99.9 99.9 2.6 0.088 0.028 0.065 0.939 0.919 0.936 99.99 99.99 2.59 99.99 99.99 -0.01 000205n_042_037 4.1 3.9 3.8 0.087 0.028 0.065 1.004 0.969 0.975 4.20 3.82 3.81 0.10 -0.08 0.01 000205n_070_122 1.3 99.9 0.1 0.085 0.028 0.065 0.971 0.943 0.962 1.19 99.99 0.24 -0.11 99.99 0.14 991017n_049_130 0.5 -0.3 -0.7 0.051 0.005 0.063 1.042 1.016 1.027 0.44 -0.44 -0.63 -0.06 -0.14 0.07 000126n_033_011 99.9 99.9 2.5 -0.001 0.020 0.060 0.988 0.942 0.954 99.99 99.99 2.46 99.99 99.99 -0.04 000111s_020_235 0.1 -0.7 -0.9 0.043 0.059 0.074 0.927 0.903 0.948 0.10 -0.67 -0.73 0.00 0.03 0.17 991119s_063_303 1.6 0.7 0.5 0.100 0.095 0.100 0.940 0.929 0.957 1.42 0.67 0.46 -0.18 -0.03 -0.04 991119s_077_272 99.9 99.9 0.1 0.109 0.095 0.100 0.947 0.925 0.956 99.99 99.99 0.31 99.99 99.99 0.21 991119s_098_273 1.7 99.9 0.5 0.120 0.095 0.100 0.948 0.923 0.955 1.50 99.99 0.49 -0.20 99.99 -0.01 991126n_076_058 99.9 99.9 2.2 0.027 0.012 0.060 1.050 1.010 1.017 99.99 99.99 2.11 99.99 99.99 -0.09 991126n_089_060 99.9 99.9 1.4 0.030 0.012 0.060 1.003 0.959 0.983 99.99 99.99 1.46 99.99 99.99 0.06 991202s_074_323 1.7 0.7 0.1 0.097 0.092 0.092 1.115 1.083 1.093 1.86 0.83 0.18 0.16 0.13 0.08 000124s_018_172 99.9 99.9 1.9 0.044 0.047 0.053 0.966 0.944 0.978 99.99 99.99 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