Particle Physics Knowledge Graph API
A structured, queryable API that transforms the comprehensive Particle Data Group (PDG) tables and reviews into a machine-readable knowledge graph for automated research.
Concept
Instead of relying on static PDF or web-based tables, this product provides a high-performance API that allows researchers to programmatically query the properties of gauge bosons, leptons, quarks, and the Higgs boson. It would map the relationships between particles, their measured properties, and the search limits for hypothetical particles (like axions or dark photons) into a graph database. This enables automated cross-referencing and rapid data retrieval for theoretical modeling.
Why now
The Review of Particle Physics [0] aggregates thousands of new measurements and hundreds of reviews into a massive, two-volume dataset. As the volume of data grows (2,717 new measurements in the latest edition), the manual lookup of Summary Tables becomes a bottleneck for computational physicists who need these constants for simulations.
AI assessment
A useful utility for the physics community that lacks a strong commercial moat and a clear paying customer base, as the data is already public and the user base is small.
- Evidence strength 5/5
- The idea is directly based on the PDG's comprehensive and authoritative dataset, which is the gold standard for the field.
- Market pull 2/5
- The target users are academic researchers and national labs who typically build their own internal tools or rely on free open-source data rather than paying for API access.
- Novelty & moat 2/5
- Converting a public dataset into a graph API is a technical implementation detail rather than a defensible intellectual property moat.
- Feasibility 5/5
- The data is already structured in tables and available online, making the creation of a knowledge graph and API highly feasible for a small team.
- Wedge clarity 4/5
- The focus on programmatic access to PDG constants for simulations is a sharp, specific entry point.
- Simplicity / focus 5/5
- The product is a single, well-defined tool with a clear function: transforming static tables into a queryable API.
Scored by AI against a fixed rubric (evidence, market, novelty, feasibility, wedge, simplicity). A prior estimate to compare ideas before real-world signal arrives.
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Who benefits
- CERNorganization
Researchers at the Large Hadron Collider need instant, programmatic access to the latest averaged particle properties to calibrate detectors and analyze collision data.
- Fermi National Accelerator Laboratoryorganization
Facilitates faster theoretical comparisons between new experimental results and the established PDG averages.
- Wolfram Researchcompany
Integrating a structured, up-to-date particle physics dataset would enhance the scientific capabilities of Wolfram|Alpha and Mathematica.
Research it builds on
- Review of Particle PhysicsS. Navas, C. Amsler, Th. Gutsche et al. · 2024 · 3212 citationsAll ideas from this paper →
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A commercial-grade API that provides programmatic, real-time access to the averaged measured properties of gauge bosons, leptons, quarks, and the Higgs boson, replacing manual table lookups with structured data queries.
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