nickswainston / pulsar_spectra Goto Github PK

The following is a list of publications where we have found incorrect ATNF data. We are using this as notes so we cant notify ATNF with a single email.

• Bell_2016: their flux errors are an order of magnitude too small
• Zhao_2019: found an error in a data point for J0953+0755 and J0835-4510. It looks like they input the average value, but it was off by an order of magnitude.
• Mignani_2017: Off by three orders of magnitude as the paper records flux in micro Jy

Appear to be adjusted for the ATNF frequencies based on their spectral index

• Stovall_2015
• Lorimer_1995

it seems that the log_parabolic_spectrum model cann't be adopted.

Make documentation to explain what seeing the ATNF label in references means and why it is inaccurate and needs to be fixed.

It appears that the bandwidth in Bondonneau is not always the full bandwidth so fix it based on the profiles

https://www.aanda.org/articles/aa/pdf/2020/03/aa36829-19.pdf

I am trying to make plots for my pulsars sample, BUT just tried simple example (mentioned in documentation) and experiencing following error

"KeyError: 'gac+20'"

I tried to fix the problem by running following command line as suggested in FAQS in documentation.

''import psrqpy
psrqpy.get_references(updaterefcache=True)
psrqpy.QueryATNF(checkupdate=True)''

BUT nothing seems to be work.
Any suggestions?

The reference frequency used in the models is currently constant at v=1.3 GHz for an unknown reason. To test how this affects the model fits, this should be instead calculated at the centre frequency of the frequency range of a particular fit.

For the fitted parameters that are not dimensionless, add which units they are in to the documentation.

The following docs must be updated to fully explain the changes made in #56

• Update the doc strings in models.py to explain the new functions (integration and Taylor models)
• Improve the explanations in the derivations, so they are clear
• Add links between the functions and the derivations so it's clear where they're used in the code
• Make an example of how to output which functions are being used in model_settings
• Add an explanation of bandwidth integration
• Explain the xerrorbars are the bandwidth, not a frequency uncertainty
• Explain when the bandwidth correction is not used, eg when there is ANTF data

Remember to let the other know once you begin working on a task so we don't both work on the same thing.

Some papers include lower or upper limits on flux density measurements. This is an example of upper limits on a Jankowski 2018 plot. He plotted them but did not include them in the fit.

At some point, it may be useful to implement an option to include censored data in the fit using a statistical method such as the Tobit model. Alternatively, or perhaps as well, we could implement a feature to plot the data (with arrows indicating limits) whilst not including them in the fit, as seen in papers like Jankowski et al and Bilous et al.

Papers with censored data:

• Murphy (2017). ADS: https://ui.adsabs.harvard.edu/abs/2017PASA...34...20M/abstract
• Sieber (1973). ADS: https://ui.adsabs.harvard.edu/abs/1973A%26A....28..237S/abstract
• Bilous (2016). ADS: https://ui.adsabs.harvard.edu/abs/2016A%26A...591A.134B/abstract
• Bilous (2020). ADS: https://ui.adsabs.harvard.edu/abs/2020A%26A...635A..75B/abstract

Useful Links:

• https://en.wikipedia.org/wiki/Censoring_(statistics)#Censored_regression
• https://en.wikipedia.org/wiki/Tobit_model

The peak frequency of an LPS spectrum is not a fit parameter, however it is a useful value to know and to cite in a paper. It is calculated easily using the formula for the peak of a quadratic. We could report it separately to the fit parameters (perhaps in a dictionary alongside other values such as the AIC and p_best)

Sometimes we have fluxes from papers that are also in ANTF so we should remove the redundant ANTF fluxes

These papers need their publication years changed:

• Xue 2017 -> Xue 2018
• van Ommen 1994 2000 -> van Ommen 1997

Our database lacks publications focusing on MSPs, high frequency measurements, and northern-sky pulsars. Here we are keeping a list of publications which may be useful additions to the database.

Flags:

• MSPs: *
• Northern-sky: ^
• Southern-sky: v
• Low-frequencies: L
• High-frequencies: H

List of publications:

• (*^L) Stappers et al. (2008)
• (*^L) Kondratiev et al. (2016)
• (^L) McEwen et al. (2020)
• (^L) Kravtsov et al. (2022)
• (vH) Spiewak et al. (2022)
• (*v) Toscano et al. (2022)
• (*^) Kuzmin & Losovsky (2001)
• (*^) Stairs et al. (1999)

The uncertainties on the model parameters are calculated from the covariance matrix, which assumes that the likelihood is symmetric (i.e. normally distributed) around the best-fit value. This method can lead to underestimated and inaccurate uncertainties.

A more robust method would be to use a Markov Chain Monte Carlo (MCMC) algorithm to sample the probability distributions of the model parameters. It would be beneficial to implement this as an option in the software, although the higher computational cost warrants having option to not use it as well.

We currently have a working double BPL model. However, due to the lack of information available in the literature, this model has been excluded for now. It would be useful to have an option to fit the double BPL.

The Vela pulsar is a perfect example of a pulsar that may potentially be a double BPL. Here is an example fit:

Another fit using pulsar_spectra:

The double BPL was fit in Bilous et al (2016; https://ui.adsabs.harvard.edu/abs/2016A%26A...591A.134B/abstract). See, for example, this plot: