Code used to aggregate pulsar parameters and estimate the TOA uncertainty referenced to the infinite frequency TOA (as described in Lam et al. 2018) for NANOGrav 15-yr pulsars with a variety of telescopes including:
- Arecibo 430 & L-band
- Arecibo L-band and S-band
- GBT 800 & L-band
- GBT L-band & VLA S-band
- CHIME & GBT L-band
- CHIME & GBT UWBR
NG15yr_totRMS.txt contains the total RMS for each pulsar at each telescope, assuming 30 min integration time per band per epoch, except at CHIME where the integration time is dec-dependent and at most 30 hours / epoch. Pulsars not visible to CHIME have their CHIME sigmas
set to -2. Total noise can be scaled to different integration time using the individual noise components. See Example Usage to get individual noise components.
Best telescope (excluding Arecibo and GBT UWBR) for each pulsar based on RMS estimates taking into consideration declination-limits.
Pulsar | Best Telescope(s) | Total RMS (μs) | 2nd Best Telescope(s) | Total RMS (μs) |
---|---|---|---|---|
B1855+09 | CHIME-GBTL | 0.4579 | GBT_Rcvr_800-Rcvr_1_2 | 0.6280 |
B1937+21 | GBT_Rcvr_1_2_VLAS | 0.1365 | GBT_Rcvr_800-Rcvr_1_2 | 0.3972 |
B1953+29 | GBT_Rcvr_800-Rcvr_1_2 | 3.4353 | GBT_Rcvr_1_2_VLAS | 5.6623 |
J0023+0923 | CHIME-GBTL | 1.4126 | GBT_Rcvr_800-Rcvr_1_2 | 2.2837 |
J0030+0451 | CHIME-GBTL | 0.8110 | GBT_Rcvr_800-Rcvr_1_2 | 1.2065 |
J0125-2327 | GBT_Rcvr_1_2_VLAS | 0.2866 | GBT_Rcvr_800-Rcvr_1_2 | 0.3791 |
J0154+1833 | CHIME-GBTL | 1.3340 | GBT_Rcvr_800-Rcvr_1_2 | 2.8961 |
J0340+4130 | GBT_Rcvr_800-Rcvr_1_2 | 2.0188 | CHIME-GBTL | 2.6424 |
J0406+3039 | GBT_Rcvr_800-Rcvr_1_2 | 1.2742 | CHIME-GBTL | 1.4583 |
J0509+0856 | CHIME-GBTL | 1.9387 | GBT_Rcvr_800-Rcvr_1_2 | 2.7891 |
J0557+1551 | GBT_Rcvr_1_2_VLAS | 5.3571 | CHIME-GBTL | 9.4253 |
J0605+3757 | CHIME-GBTL | 1.1552 | GBT_Rcvr_800-Rcvr_1_2 | 2.0358 |
J0610-2100 | GBT_Rcvr_800-Rcvr_1_2 | 1.6001 | GBT_Rcvr_1_2_VLAS | 2.2534 |
J0613-0200 | GBT_Rcvr_800-Rcvr_1_2 | 0.3512 | CHIME-GBTL | 0.5378 |
J0614-3329 | GBT_Rcvr_800-Rcvr_1_2 | 0.6971 | GBT_Rcvr_1_2_VLAS | 0.9803 |
J0636+5128 | CHIME-GBTL | 0.3880 | GBT_Rcvr_800-Rcvr_1_2 | 0.9103 |
J0645+5158 | CHIME-GBTL | 1.4743 | GBT_Rcvr_800-Rcvr_1_2 | 2.9557 |
J0709+0458 | CHIME-GBTL | 8.7690 | GBT_Rcvr_1_2_VLAS | 12.1082 |
J0732+2314 | CHIME-GBTL | 2.0457 | GBT_Rcvr_800-Rcvr_1_2 | 2.7689 |
J0740+6620 | CHIME-GBTL | 0.5070 | GBT_Rcvr_800-Rcvr_1_2 | 1.1347 |
J0751+1807 | CHIME-GBTL | 0.8289 | GBT_Rcvr_800-Rcvr_1_2 | 1.1757 |
J0931-1902 | CHIME-GBTL | 1.1971 | GBT_Rcvr_800-Rcvr_1_2 | 1.5985 |
J1012+5307 | CHIME-GBTL | 0.2555 | GBT_Rcvr_800-Rcvr_1_2 | 0.5858 |
J1012-4235 | GBT_Rcvr_1_2_VLAS | 1.1461 | GBT_Rcvr_800-Rcvr_1_2 | 1.6197 |
J1022+1001 | CHIME-GBTL | 0.5194 | GBT_Rcvr_800-Rcvr_1_2 | 0.6706 |
J1024-0719 | CHIME-GBTL | 0.6790 | GBT_Rcvr_800-Rcvr_1_2 | 0.9731 |
J1125+7819 | CHIME-GBTL | 0.3854 | GBT_Rcvr_800-Rcvr_1_2 | 1.5188 |
J1312+0051 | CHIME-GBTL | 2.5590 | GBT_Rcvr_800-Rcvr_1_2 | 3.7960 |
J1327+3423 | CHIME-GBTL | 7.5790 | GBT_Rcvr_800-Rcvr_1_2 | 13.8936 |
J1453+1902 | CHIME-GBTL | 3.6239 | GBT_Rcvr_800-Rcvr_1_2 | 5.6557 |
J1455-3330 | GBT_Rcvr_800-Rcvr_1_2 | 2.4215 | GBT_Rcvr_1_2_VLAS | 3.8961 |
J1600-3053 | GBT_Rcvr_1_2_VLAS | 0.2576 | GBT_Rcvr_800-Rcvr_1_2 | 0.3965 |
J1614-2230 | GBT_Rcvr_800-Rcvr_1_2 | 0.9900 | GBT_Rcvr_1_2_VLAS | 1.4292 |
J1630+3550 | CHIME-GBTL | 3.6222 | GBT_Rcvr_800-Rcvr_1_2 | 9.3529 |
J1630+3734 | CHIME-GBTL | 1.0158 | GBT_Rcvr_800-Rcvr_1_2 | 1.9963 |
J1640+2224 | CHIME-GBTL | 0.7894 | GBT_Rcvr_800-Rcvr_1_2 | 1.4290 |
J1643-1224 | GBT_Rcvr_800-Rcvr_1_2 | 0.5250 | GBT_Rcvr_1_2_VLAS | 0.7314 |
J1705-1903 | GBT_Rcvr_1_2_VLAS | 0.5512 | GBT_Rcvr_800-Rcvr_1_2 | 0.6364 |
J1713+0747 | CHIME-GBTL | 0.1602 | GBT_Rcvr_1_2_VLAS | 0.1969 |
J1719-1438 | CHIME-GBTL | 1.4084 | GBT_Rcvr_800-Rcvr_1_2 | 1.8039 |
J1730-2304 | GBT_Rcvr_800-Rcvr_1_2 | 0.8273 | GBT_Rcvr_1_2_VLAS | 1.1629 |
J1738+0333 | GBT_Rcvr_1_2_VLAS | 1.7060 | CHIME-GBTL | 1.7663 |
J1741+1351 | CHIME-GBTL | 1.6546 | GBT_Rcvr_800-Rcvr_1_2 | 2.9330 |
J1744-1134 | CHIME-GBTL | 0.3753 | GBT_Rcvr_800-Rcvr_1_2 | 0.5293 |
J1745+1017 | CHIME-GBTL | 0.7703 | GBT_Rcvr_800-Rcvr_1_2 | 1.0975 |
J1747-4036 | GBT_Rcvr_1_2_VLAS | 2.7376 | GBT_Rcvr_800-Rcvr_1_2 | 8.1213 |
J1751-2857 | GBT_Rcvr_800-Rcvr_1_2 | 2.3538 | GBT_Rcvr_1_2_VLAS | 3.3697 |
J1802-2124 | GBT_Rcvr_1_2_VLAS | 7.9382 | GBT_Rcvr_800-Rcvr_1_2 | 38.9509 |
J1803+1358 | GBT_Rcvr_800-Rcvr_1_2 | 1.6802 | CHIME-GBTL | 4.0567 |
J1811-2405 | GBT_Rcvr_800-Rcvr_1_2 | 1.5610 | GBT_Rcvr_1_2_VLAS | 1.6729 |
J1832-0836 | CHIME-GBTL | 0.7827 | GBT_Rcvr_800-Rcvr_1_2 | 1.0559 |
J1843-1113 | GBT_Rcvr_800-Rcvr_1_2 | 1.0656 | GBT_Rcvr_1_2_VLAS | 1.3051 |
J1853+1303 | CHIME-GBTL | 1.2095 | GBT_Rcvr_800-Rcvr_1_2 | 1.9298 |
J1903+0327 | GBT_Rcvr_1_2_VLAS | 48.3718 | CHIME-GBTL | 245.6239 |
J1909-3744 | GBT_Rcvr_800-Rcvr_1_2 | 0.3791 | GBT_Rcvr_1_2_VLAS | 0.6362 |
J1910+1256 | CHIME-GBTL | 1.5494 | GBT_Rcvr_800-Rcvr_1_2 | 2.3068 |
J1911+1347 | CHIME-GBTL | 0.9963 | GBT_Rcvr_800-Rcvr_1_2 | 1.4606 |
J1918-0642 | CHIME-GBTL | 0.9180 | GBT_Rcvr_800-Rcvr_1_2 | 1.3219 |
J1923+2515 | CHIME-GBTL | 2.0951 | GBT_Rcvr_800-Rcvr_1_2 | 3.4809 |
J1944+0907 | CHIME-GBTL | 1.6993 | GBT_Rcvr_800-Rcvr_1_2 | 2.7582 |
J1946+3417 | GBT_Rcvr_800-Rcvr_1_2 | 1.5064 | GBT_Rcvr_1_2_VLAS | 1.7415 |
J2010-1323 | CHIME-GBTL | 0.7913 | GBT_Rcvr_800-Rcvr_1_2 | 1.1157 |
J2017+0603 | GBT_Rcvr_1_2_VLAS | 1.6264 | CHIME-GBTL | 2.0987 |
J2022+2534 | CHIME-GBTL | 1.0419 | GBT_Rcvr_800-Rcvr_1_2 | 1.1488 |
J2033+1734 | CHIME-GBTL | 2.9154 | GBT_Rcvr_800-Rcvr_1_2 | 5.2802 |
J2039-3616 | GBT_Rcvr_800-Rcvr_1_2 | 1.4707 | GBT_Rcvr_1_2_VLAS | 1.7814 |
J2043+1711 | CHIME-GBTL | 1.3399 | GBT_Rcvr_800-Rcvr_1_2 | 2.2708 |
J2124-3358 | GBT_Rcvr_800-Rcvr_1_2 | 1.0778 | GBT_Rcvr_1_2_VLAS | 1.2549 |
J2145-0750 | CHIME-GBTL | 0.6875 | GBT_Rcvr_800-Rcvr_1_2 | 1.0324 |
J2150-0326 | CHIME-GBTL | 1.0480 | GBT_Rcvr_800-Rcvr_1_2 | 1.6443 |
J2214+3000 | GBT_Rcvr_1_2_VLAS | 2.0539 | CHIME-GBTL | 2.4623 |
J2229+2643 | CHIME-GBTL | 1.2753 | GBT_Rcvr_800-Rcvr_1_2 | 2.6486 |
J2234+0611 | CHIME-GBTL | 1.3866 | GBT_Rcvr_800-Rcvr_1_2 | 2.0389 |
J2234+0944 | CHIME-GBTL | 1.1274 | GBT_Rcvr_1_2_VLAS | 1.5500 |
J2302+4442 | CHIME-GBTL | 1.0490 | GBT_Rcvr_800-Rcvr_1_2 | 2.1463 |
J2317+1439 | CHIME-GBTL | 0.7490 | GBT_Rcvr_800-Rcvr_1_2 | 1.5689 |
J2322+2057 | CHIME-GBTL | 2.5864 | GBT_Rcvr_800-Rcvr_1_2 | 4.3082 |
Contains the parameters of each 15yr pulsar. J0437 not included b/c only visible with VLA.
- name
- period (s)
- DM (pc cm^-3)
- DEC: declination (deg)
- dtd: scintillation timescale from NE2001 (s)
- dnud: scintillation bandwidth from NE2001 (GHz)
- taud: scattering timescale from NE2001 (us)
- dist: DM distance from NE2001 (kpc)
- w50: FWHM of the L-band template (us)
- weff: effective width of the L-band template (us)
- uscale: scales intensity across pulse phase
- S_1000: flux density at 1 GHz (mJy)
- spindex: spectral index computed from log(flux ratio)/log(freq ratio) using 800/1400 for GBT pulsars, 430/1400 for AO when available, otherwise 1400/2000. Cutoff at zero
- sig_jitter: single pulse RMS jitter (us) from Lam et al. 2019 or 0.63 * W50 if not in 12.5-yr (from Fig. 7 of same paper)
Class to store an individual 15-yr pulsar
name
: string
pulsar name
period
: float
pulse period in seconds
dm
: float
dispersion measure in pc cm^-3
dec
: float
declination in degrees
dtd
: float
scintillation timescale in seconds
dnud
: float
scintillation bandwidth in GHz
taud
: float
scattering timescale in us
dist
: float
DM distance in kpc
w50
: float
FWHM of L-band pulse profile in us
weff
: float
Effective width of the L-band profile in us
uscale
: float
scaling factor to distribute intensity across pulse profile
s_1000
: float
flux density at 1 GHz in mJy
spindex
: float
spectral index
sig_j_single
: float
single-pulse RMS jitter in us
sigmas
: dict
dictionary of dictionaries of RMS components for each instrument
sigma_jitter(self, t_int)
Return intrinsic jitter noise (in us) for given integration time in seconds
add_sigmas(self, instr_name, sigma_tup)
instr_name : str
name of timing instrument
sigma_tup : tuple
tuple of RMS components
get_instr_keys(self)
returns instrument key names for sigmas dict
Class to store timed pulsars
name
: string (optional)
PTA name
psrlist
: list
list of pulsar.Pulsar objects
get_single_pulsar(self, psr_name)
return pulsar.Pulsar object whose name matches 'psr_name'
sigma_best(self, exclude=[])
Get the best instrument for each pulsar and return list of tuples of (pulsar name, instrument, sigma_tot)
Parameters
exclude
: list (optional, default = [])
list of telescope name substrings to exclude when sorting RMS's
write_to_text(self, filename)
Write total RMS for each pulsar at each instrument to file
To get a particular pulsar's noise estimates at a particular telescope:
import cPickle
with open('NG15yr.pta', 'rb') as f:
pta = cPickle.load(f)
j1713 = pta.get_single_pulsar("J1713+0747")
print(j1713.get_instr_keys()) # get keys for sigmas dict
print(j1713.sigmas["AO_430_Lwide_logain"])
To see which non-Arecibo telescope is best for each pulsar
import cPickle
with open('NG15yr.pta', 'rb') as f:
pta = cPickle.load(f)
print(pta.best_sigma(exclude=["AO"]))