astroparticle physics

What twelve years of daily arXiv picks say about my reading

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How has what I read changed over twelve years?

Since February 2014, I have kept a daily list of the arXiv preprints that I find interesting. Since October 2017, the list has been public on this site as My daily arXiv picks. I recently gathered all of it, 18,169 papers, into one table and looked at what it says. Here are the highlights.

I pick three times as many papers. In 2014 I picked 704 papers. In 2025 I picked 2,166, and 2026 is at 1,910 so far. I have also become much stingier with two stars, which I use for papers that are very relevant to my own work: they made up a quarter of my picks in 2014–2017, and about 2% since 2019.

Stacked bar chart of the number of arXiv papers picked per year from 2014 to 2026, split into unstarred, one-star and two-star picks.
Papers I picked each year, split by star level. One star marks a paper I found especially interesting; two stars, one that is very relevant to my own work. 2026 runs to November 7.

From astro-ph towards hep-ph. In 2014, 62% of my picks were listed in astro-ph and 16% in hep-ph. In 2026, the split is 44% and 39%. Most of the shift happened between 2017 and 2021.

Line chart of the share of picks in astro-ph, hep-ph, hep-ex and other arXiv categories from 2014 to 2026.
Share of my picks in each arXiv category, by year.

What I read and what I star have drifted apart. To compare topics fairly across years, I compared how often I star papers on a topic with how often I star papers overall in the same years. The topics I star most often are all about high-energy neutrinos: the 220-PeV KM3NeT event KM3-230213A (3.3 times my average star rate), the Glashow resonance (3.0), NGC 1068 and Seyfert galaxies (2.8), and high-energy astrophysical neutrinos in general (2.3).

Dark matter, on the other hand, is the single largest topic I pick: 3,094 papers, about a fifth of my picks in recent years. Yet I star it at only 0.8 times my average rate. Axions grew from under 1% of my picks to about 5%, and machine learning from almost nothing to 4% in 2026, but I rarely star either. Gamma-ray bursts went the other way, from about 11% of my picks in 2014–2017 to 2% in 2025–2026.

Table of 34 topics showing each topic’s share of picks per year as colored cells, and how often papers on each topic are starred relative to the average.
Each row is a topic, assigned by keywords in paper titles. The colored cells show the share of each year’s picks on that topic. The bars show how often I star papers on that topic compared with my average for the same years. Click to enlarge.

Explore the list. I put all 18,169 picks in a searchable page. You can search by title, author, or arXiv identifier, and filter by stars, year, arXiv category, or topic.

A few caveats: topics are assigned by keyword matches on paper titles, so they are approximate, and years come from arXiv identifiers.

I put together the analysis and the searchable page with the help of Claude.