Literature research · Preprint landscape · run date
What quantum-materials researchers are posting
Topic clusters, momentum, materials, methods, non-arXiv servers and contested claims in quantum-materials preprints, trailing 12 months vs the 12 months before.
Q1 Landscape · Q2 Momentum
Where the activity is, and which way it is moving
Show data table
Q2 Momentum over time
The three clusters that moved, month by month
Each line is the cluster's share of all in-scope arXiv preprints that month; all three panels use the same scale. Thin gray lines mark each 12-month window's average share. The share ratio R is trailing average ÷ preceding average. The first and last months are partial (2024-09-24 onward; up to 2026-09-22).
Show data table
Q3 Materials
Which materials are gaining or losing attention
Show data table
Leading material families in each cluster (trailing 12 months)
Q4 Methods
Dominant experimental and computational techniques
Trailing-12-month in-scope arXiv preprints tagged with each technique (refined keyword lexicon; a paper can carry several tags). Both panels share one scale.
Show data table
Q5 Beyond arXiv
What the other preprint servers add
Records are phrase-filtered quantum-materials hits in the trailing / preceding window. On-topic and fringe rates come from a hand audit of up to 25 records per server (about ±15–20 points). "Unique" means not found on arXiv; these are upper bounds, because arXiv matching covered only the four harvested cond-mat categories.
Q6 Noise
High-visibility claims that are contested or unreplicated
Noise filter applied
How to read the table
Supportive and critical counts are in-window preprints found in the corpus, with distinct research groups in brackets. Stances are labelled from titles and abstracts, not full texts, so the counts are floors. Claims are sorted by noise score.
Scope, method and caveats
How these numbers were made
Scope
Momentum label rule
Caveats
Citation check
Every preprint ID cited in findings.md was checked against the harvested corpus by verify_citations.py: