FINAL-Bench/OSC-Superconductor

OSC — Open Superconductor Challenge

Screen thousands of 2D materials for unconventional (d-wave) superconductivity — from your own laptop — and climb an open, verified leaderboard.

🏆 Leaderboard, live challenge & submission: https://huggingface.co/spaces/FINAL-Bench/OSC-Leaderboard

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TL;DR (the short answer)

OSC is a free, open-science competition on Hugging Face to find the next candidate twisted-2D superconductor. We provide a computed effective model (t, U, N(E_F)) for each material; you estimate its d-wave pairing tendency with any method — a laptop CPU is enough — and submit a small file. Provisional scores appear instantly; the organizers' precise strongly-correlated solver verifies the top entries and sets the official rank. Prize pool US $3,000 + co-authorship. Season 1 closes 31 December 2026 (23:59 KST). Materials derive from C2DB (CC-BY 4.0). No installation and no GPU are required for the light track.

• What you get: an effective Hubbard model per material — hopping t, interaction U, and the density of states at the Fermi level N(E_F).
• What you do: compute a d-wave (d_x²−y²) pairing estimate and submit it.
• What we do: verify the top submissions with a precise many-body reference solver.
• Who can join: anyone — researchers, students, and AI coding agents.

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What is the Open Superconductor Challenge?

The Open Superconductor Challenge (OSC) is a crowd-sourced materials-screening benchmark for unconventional superconductivity in two-dimensional (2D) materials. Discovering superconductors experimentally is slow and expensive, so OSC screens candidates computationally, before the lab: the community estimates a superconducting-pairing signal for thousands of materials, and a precise reference solver confirms the most promising ones.

OSC targets d-wave (d_x²−y²) pairing tendency — the pairing symmetry associated with cuprates, twisted bilayer graphene, and other strongly-correlated systems — using the doped Hubbard model as the effective description. It is hosted by FINAL-Bench as an open-science initiative and is designed to be reproducible, hard to game, and accessible without specialized hardware.

Why OSC matters

• Compute arbitrage: the crowd screens broadly on laptops; the organizers spend heavy DFT and many-body compute only on the top candidates. This finds promising materials for a fraction of the usual cost.
• Open and fair: the candidate list, protocol, and baseline tools are fully open (GPL/MIT); only the final verification engine is private, which keeps the ranking un-gameable without hiding the science.
• Reproducible science: every material carries a provenance trail to C2DB, and winning methods are shared under a contributor license.

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Dataset contents

File	Description
candidates.csv	The full browsable universe — 4,832 dynamically-stable 2D materials (C2DB-derived) enriched with our tags: chemical family, cost class, is-metal, band gap, and a screening prior.
active_challenge.csv	The active competition set (metallic / small-gap materials) with the provided effective model: t (eV), U (eV), U/t, and nef = N(E_F) (states/eV/atom).
submissions.csv	The baseline leaderboard rows and verified anchor scores (the OSC Pairing Index).
instrument/osc_instrument.py	The participant tool — pure Python, no install, runs in seconds on any laptop.
instrument/pair_baseline.py	An open d-wave pair-susceptibility routine to build a competitive method on.
PROVENANCE.md	Data source and license details (C2DB, CC-BY 4.0).

The effective model (what you receive per material)

For every active material OSC provides a downfolded Hubbard effective model:

• t — nearest-neighbor hopping (eV), from the DFT band structure.
• U — on-site Coulomb interaction (eV); the challenge fixes the strongly-correlated regime at U/t = 8 (cuprate convention).
• N(E_F) (nef) — density of states at the Fermi level (states/eV/atom), the first-order BCS indicator: higher N(E_F) → stronger pairing tendency.

Your task is to do better than the first-order screen by computing an actual, material-specific d-wave pairing estimate.

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How to participate (light track — any laptop, no install)

You do not need a GPU or any installation for the light track. An AI coding agent (Claude Code, Codex) can also do every step for you — just point it at this challenge.

1. Sign in with Hugging Face on the OSC Leaderboard Space — this verifies your identity so entries can't be posted under someone else's handle.

2. Get the instrument (pure Python — Windows / Linux / macOS, nothing to install):

huggingface-cli download FINAL-Bench/OSC-Superconductor \
  instrument/osc_instrument.py instrument/pair_baseline.py \
  --repo-type dataset --local-dir osc
cd osc/instrument

3. Pick a material and run:

python osc_instrument.py --material_id OSC-00129 --author YOUR_NAME
# reads the material's (t, U, N(E_F)); prints an OSC Pairing Index on the leaderboard's scale
# -> writes submission.json

To compete on the gold track, edit estimate_pairing() with your own many-body method — exact diagonalization (ED), variational Monte Carlo (VMC), DMRG, mean-field, or machine learning — that improves on the first-order N(E_F) screen.

4. Submit your score. Open the material's card in the Active Challenge tab of the Space and submit (you must be signed in), or open a Pull Request adding your submission.json under submissions/ in this dataset. Your provisional score appears on the leaderboard immediately.

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Scoring: the OSC Pairing Index

The leaderboard reports an OSC Pairing Index, a readable screening score:

Pairing Index = N(E_F) × A_ref × 10000

where A_ref = 0.0503 is the reference d-wave pairing amplitude (the max-distance d-wave pair correlation P_d) measured once by the organizers' precise 6×6 doped-Hubbard solver at U/t = 8. The ×10000 factor is a pure, monotone rescale for readability — it never changes any ranking.

• Baseline — first-order N(E_F) screen; the bar to beat.
• Provisional — your submitted estimate, on the same scale; appears instantly.
• Verified — the organizers' precise strongly-correlated solver confirms the top entries under fixed, logged conditions and sets the official rank. Hidden validation set, rotated to prevent overfitting.

Honest interpretation: a higher index means a stronger d-wave pairing tendency by our screen — i.e. a better candidate to investigate — not a guaranteed critical temperature (Tc) or a confirmed superconductor. Because A_ref is currently a fixed constant, the baseline ranking tracks N(E_F); the challenge exists precisely so that participants replace this flat amplitude with real, material-specific many-body calculations.

Tracks & prizes (total US $3,000)

Prize	Amount	Awarded to
Grand	$1,500	highest verified d-wave tendency (any material)
Best Method (Gold)	$1,000	top verified score with an open-sourced method
Best Discovery (Open)	$500	best verified new material you propose

One cash prize per person (the runner-up succeeds on overlap). Ranks 2–5 and all valid entrants receive co-authorship, hall-of-fame listing, and leaderboard credit.

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Frequently asked questions

Do I need a GPU or to install anything?

No. The light track is a single pure-Python script that runs in seconds on any laptop CPU — Windows, Linux, or macOS. A GPU only helps if you choose the advanced full-stack track.

What exactly am I predicting?

A d-wave (d_x²−y²) superconducting pairing tendency for a given 2D material, from its effective Hubbard model. This is a screening signal, not a measured critical temperature.

Does the #1 material mean the best superconductor?

It means the strongest d-wave pairing tendency by our first-order screen — the top candidate to investigate. It is not a confirmed superconductor or the highest Tc.

How are winners verified?

The organizers run a precise strongly-correlated (NQS/GFMC-class) solver on the top submissions under fixed, logged conditions. Verified entries sit above provisional ones and define the official rank.

Do I have to reveal my method or code?

No — you submit only result numbers. Only prize winners share reproducible code, under a contributor license. The verification engine runs on our servers and is never distributed, which is what keeps the ranking un-gameable.

Where does the data come from?

Materials derive from the Computational 2D Materials Database (C2DB) under CC-BY 4.0. We add value (family tags, cost classes, effective models, screening priors) and cite the source in PROVENANCE.md.

When does the challenge close?

Season 1 closes 31 December 2026, 23:59 KST. The leaderboard, instrument, and authenticated submission are live now, and the active set is being expanded.

Can an AI agent enter for me?

Yes. Point an AI coding agent (Claude Code / Codex) at the challenge and it can download the instrument, compute a score, and submit on your behalf.

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Keywords

superconductor discovery · unconventional superconductivity · d-wave pairing · 2D materials · twisted bilayer · moiré materials · strongly-correlated electrons · doped Hubbard model · density of states at the Fermi level · N(E_F) · computational materials science · machine learning for materials · open-science challenge · Hugging Face leaderboard · CPU-only benchmark · crowd-sourced materials screening.

Citation & license

• Baseline tools and protocol: open source (GPL/MIT).
• Materials: derived from C2DB under CC-BY 4.0 — see PROVENANCE.md.
• Verification engine: operated by the organizers (FINAL-Bench), not distributed.

If OSC helps your work, please link the challenge Space (https://huggingface.co/spaces/FINAL-Bench/OSC-Leaderboard) and credit FINAL-Bench — Open Superconductor Challenge.

Hosted by FINAL-Bench as an open-science initiative. Season 1 is open until 31 December 2026 (23:59 KST). Star and watch to follow the leaderboard.