How to Write an Astronomy Paper with Bibby AI

Astronomy papers have a recognizable rhythm: motivation, observations, data reduction, measurements, interpretation, and comparison with prior work. The writing is technical, but the structure is stable. That makes astronomy a strong fit for Bibby AI: you can use AI to draft, refine, format tables, manage citations, and review the manuscript while keeping scientific control over the claims.

This guide shows a practical workflow for writing an astronomy paper in LaTeX. It uses AASTeX-style conventions, but the same structure works for most observational and computational astronomy manuscripts.

1. Start from the scientific question

Do not start with the telescope, the pipeline, or the plot. Start with the question:

What physical system are we studying, what property are we measuring, and why does it matter?

Examples:

• How does stellar activity affect the transit depth of a nearby exoplanet?
• What does the rotation curve of a dwarf galaxy imply about its mass distribution?
• How does dust extinction vary across a star-forming region?

A useful Bibby AI prompt:

Help me turn this astronomy project into a paper outline.
Scientific question: [paste your question]
Data: [telescope/instrument/survey]
Measurements: [photometry/spectroscopy/light curves/catalog matching]
Target journal style: AASTeX.
Return section headings and the key claim each section must support.

2. Use an AASTeX-style LaTeX skeleton

Many astronomy journals accept AASTeX, the LaTeX package used across AAS journals. A compact starting point:

\documentclass[twocolumn]{aastex631}

\shorttitle{A Bibby AI Astronomy Paper}
\shortauthors{Your Name et al.}

\begin{document}

\title{Measuring [Quantity] in [Astronomical System] with [Instrument or Survey]}

\author{Your Name}
\affiliation{Your Institution}

\begin{abstract}
% Context, data, method, main measurement, implication.
\end{abstract}

\keywords{astronomy data analysis, stars, galaxies, exoplanets}

\section{Introduction}
\section{Observations}
\section{Data Reduction}
\section{Analysis}
\section{Results}
\section{Discussion}
\section{Conclusions}

\acknowledgments
% Funding, telescope time, software, archive acknowledgments.

\bibliography{references}{}
\bibliographystyle{aasjournal}

\end{document}

If your local template uses a newer AASTeX class name, keep the journal's official template. The structure above is the important part: it separates raw observations from analysis and interpretation.

3. Write the abstract as a measurement story

Astronomy abstracts usually follow this pattern:

1. Context: why the object or population matters.
2. Data: instrument, survey, wavelength, or sample.
3. Method: photometry, spectroscopy, modeling, or simulation.
4. Result: the main measured value with uncertainty.
5. Interpretation: what the result implies physically.

Prompt Bibby AI like this:

Write a 220-word astronomy abstract.
Use this structure: context, data, method, measured result with uncertainty,
and physical interpretation.
Do not invent values. Use placeholders where numbers are missing.

That last line matters. In a science paper, AI should never invent a luminosity, redshift, metallicity, transit depth, or uncertainty. Use placeholders until your analysis is complete.

4. Make the observations section concrete

The observations section should let another astronomer understand exactly what data entered the analysis. Include target identifiers, coordinates if relevant, instrument, filters or wavelength range, exposure time, observing date, seeing or resolution, and archive source.

A table is often the clearest format:

\begin{deluxetable}{lcccc}
\tablecaption{Example Observation Log\label{tab:obs-log}}
\tablehead{
\colhead{Target} & \colhead{Instrument} & \colhead{Filter}
& \colhead{Exposure (s)} & \colhead{Date}
}
\startdata
Target A & ExampleCam & g & 3 $\times$ 300 & 2026 Jan 12 \\
Target A & ExampleCam & r & 3 $\times$ 300 & 2026 Jan 12 \\
Target B & ExampleSpec & 4500--7500 \AA & 1800 & 2026 Jan 13 \\
\enddata
\end{deluxetable}

Use Bibby AI's table tools to generate the LaTeX table from CSV or a pasted spreadsheet, then check every number manually against your observing log.

5. Keep data reduction separate from analysis

Data reduction explains how raw data became usable data. Analysis explains how usable data became scientific measurements. Mixing them makes papers hard to review.

For imaging data, the reduction section might include:

• bias subtraction and flat-field correction;
• astrometric calibration;
• photometric calibration against catalog stars;
• source extraction and aperture selection;
• quality cuts and uncertainty propagation.

A precise paragraph template:

We reduced the imaging data using [pipeline/software].
Each exposure was bias-subtracted, flat-field corrected, and aligned to
[reference catalog]. Aperture photometry was performed with an aperture
radius of [value], and the background was estimated from [annulus/model].
Photometric calibration used [catalog] stars within [selection criteria].
Uncertainties include photon noise, background variance, and calibration error.

6. Add figures that answer one question each

Every figure should have one job. A light curve figure answers "how did brightness change with time?" A spectrum answers "which features are present?" A color-magnitude diagram answers "where does the object sit relative to a population?"

\begin{figure}[t]
  \centering
  \includegraphics[width=\columnwidth]{figures/light_curve.pdf}
  \caption{Example light curve for the target in the $r$ band.
  Points show calibrated photometry and the shaded region marks the
  best-fit event window. Error bars represent 1$\sigma$ uncertainties.}
  \label{fig:light-curve}
\end{figure}

Ask Bibby AI to improve captions, not to infer results from plots it cannot verify:

Improve this astronomy figure caption.
Make it clear what is plotted, what the error bars mean,
and what conclusion the reader should draw.
Do not add numerical claims that are not in the caption.

7. Report measurements with units and uncertainties

Astronomy writing lives or dies on units and uncertainty. Use math mode consistently:

We measure a period of $P = 3.214 \pm 0.006\,\mathrm{days}$
and a transit depth of $\delta = 1.8 \pm 0.2\%$.
Assuming a stellar radius of $R_\star = 0.84 \pm 0.03\,R_\odot$,
this corresponds to a planet radius of $R_p = 1.12 \pm 0.09\,R_J$.

When using Bibby AI, paste the exact values and ask it to check consistency:

Check this Results paragraph for unit consistency, uncertainty notation,
and whether every symbol is defined before use.

8. Build the discussion around physical interpretation

The Results section says what you measured. The Discussion says what it means. Good discussion sections compare your measurement with prior studies, explain possible systematics, and identify what future observations would resolve.

Useful paragraph structure:

1. State the main interpretation.
2. Compare with previous measurements or models.
3. Discuss one plausible source of bias.
4. Explain what new observation would test the interpretation.

9. Add citations and acknowledgments carefully

Astronomy papers often cite instruments, surveys, software, and data archives. Keep those references in the same BibTeX file as papers:

@article{astropy2013,
  title   = {Astropy: A community Python package for astronomy},
  author  = {Astropy Collaboration},
  journal = {Astronomy and Astrophysics},
  year    = {2013}
}

Then cite software and methods where they appear:

Data processing used the Astropy ecosystem \citep{astropy2013}
and custom Python scripts archived with the analysis repository.

Bibby AI's citation search can help populate entries, but you should verify official preferred citations for telescopes, archives, and software packages.

10. Run a submission-focused review

Before exporting, ask Bibby AI for a review pass tailored to astronomy:

Review this astronomy manuscript before submission.
Check whether the abstract includes the main result,
the observations section is reproducible,
units and uncertainties are consistent,
figures are cited in order,
and the discussion distinguishes results from interpretation.

Final checklist

• The scientific question is clear by the end of the introduction.
• Observations and data reduction are separate sections.
• Every measurement includes units and uncertainty.
• Figures answer one scientific question each.
• Tables are readable in two-column format.
• Software, surveys, instruments, and archives are cited or acknowledged.
• The PDF compiles cleanly in Bibby AI before submission.

Start faster: use Bibby AI templates for the manuscript skeleton, the table generator for observation logs, and paper review before you submit.