Mine PWM

Check physics artifacts — L1 Principles, L2 Specs, L3 Benchmarks, L4 Solutions — using AI agents. Submit verified contributions. After the founder review, your work goes to mainnet and you earn PWM. PWM is required to use AI4Science, so mine first.

▶ Watch demo →

Pick an artifact

Browse L1–L4 below and choose what to work on

Check with AI agent

Use ChatGPT / Claude / Gemini with our template

Submit for review

Founder reviews → mainnet deploy → PWM earned

L1 Principles

169

L2 Specs (Imaging Systems)

169

L3 Benchmarks

L4 Open Slots

🤖

Step 2 — Check with an AI Agent

Before submitting, use an AI agent to verify your work. Paste the artifact content + the template prompt below into any of these tools. If the AI confirms it looks correct, you're ready to submit.

💬 ChatGPT

Paste the check prompt + artifact into GPT-4o or o3

Open ChatGPT ↗

⚡ Claude Code

Run /check in Claude Code CLI with the template

Open Claude Code ↗

✦ Gemini

Use Gemini Advanced with the artifact markdown

Open Gemini ↗

🦅 OpenClaw

Open-source LLM checker for PWM artifacts

Open OpenClaw ↗

📋 Copy the AI check prompt template

Paste this prompt into any AI agent, then append the artifact content below it.

You are reviewing a Physics World Model (PWM) artifact submission.
PWM is a decentralized registry for verifiable physics solutions in computational imaging.

Artifact layers:
- L1 Principle: a fundamental physics law or theorem
- L2 Spec: an imaging system configuration (forward model DAG)
- L3 Benchmark: a test dataset + scoring metric tied to an L2 Spec
- L4 Solution: a reconstruction algorithm result on an L3 Benchmark

Please check the following artifact against these criteria:
1. Is the physics/math correct and internally consistent?
2. Does it follow the PWM layer structure (builds on the correct parent layer)?
3. Is it sufficiently novel — not a duplicate of existing content?
4. Is the notation and description clear enough to reproduce?
5. For L4: does the method description match the reported PSNR/SSIM metrics?

Respond with: PASS / FAIL / NEEDS REVISION, then a brief explanation.

--- ARTIFACT CONTENT BELOW ---
[paste your L1/L2/L3/L4 content here]

Open Solution Slots — Start Here

Benchmarks with fewer than 5 solutions = most opportunity. No stake required.

★ START HERE

Imaging System	Benchmark	Solutions	Network	Action
Electrical Impedance Tomography (EIT)	Blind Reconstruction Challenge	4	TESTNET	Mine →
FPM	Blind Reconstruction Challenge	4	TESTNET	Mine →
Full-Waveform Inversion (FWI)	Blind Reconstruction Challenge	4	TESTNET	Mine →
Functional Near-Infrared Spectroscopy (fNIRS)	Blind Reconstruction Challenge	4	TESTNET	Mine →
Fundus	Blind Reconstruction Challenge	4	TESTNET	Mine →
Gravitational Wave Detection	Blind Reconstruction Challenge	4	TESTNET	Mine →
Ground-Penetrating Radar (GPR)	Blind Reconstruction Challenge	4	TESTNET	Mine →
Hyperspectral Remote Sensing	Blind Reconstruction Challenge	4	TESTNET	Mine →
Industrial CT	Blind Reconstruction Challenge	4	TESTNET	Mine →
Integral	Blind Reconstruction Challenge	4	TESTNET	Mine →
Interferometric SAR (InSAR)	Blind Reconstruction Challenge	4	TESTNET	Mine →
Lensless	Blind Reconstruction Challenge	4	TESTNET	Mine →
LiDAR	Blind Reconstruction Challenge	4	TESTNET	Mine →
Light Field	Blind Reconstruction Challenge	4	TESTNET	Mine →
Lucky Imaging	Blind Reconstruction Challenge	4	TESTNET	Mine →
MINFLUX Nanoscopy	Blind Reconstruction Challenge	4	TESTNET	Mine →
MR Fingerprinting (MRF)	Blind Reconstruction Challenge	4	TESTNET	Mine →
Machine Vision / AOI	Blind Reconstruction Challenge	4	TESTNET	Mine →
Neutron Diffraction	Blind Reconstruction Challenge	4	TESTNET	Mine →
Ocean Color Remote Sensing	Blind Reconstruction Challenge	4	TESTNET	Mine →
Optical Diffraction Tomography (ODT)	Blind Reconstruction Challenge	4	TESTNET	Mine →
PALM/STORM	Blind Reconstruction Challenge	4	TESTNET	Mine →
Panorama	Blind Reconstruction Challenge	4	TESTNET	Mine →
Particle Calorimetry	Blind Reconstruction Challenge	4	TESTNET	Mine →
Passive Microwave Radiometry	Blind Reconstruction Challenge	4	TESTNET	Mine →
Phase Contrast Microscopy	Blind Reconstruction Challenge	4	TESTNET	Mine →
Photoacoustic	Blind Reconstruction Challenge	4	TESTNET	Mine →
Photometric Stereo	Blind Reconstruction Challenge	4	TESTNET	Mine →
Proton Radiography	Blind Reconstruction Challenge	4	TESTNET	Mine →
Ptychography	Blind Reconstruction Challenge	4	TESTNET	Mine →
Pump-Probe Microscopy	Blind Reconstruction Challenge	4	TESTNET	Mine →
Quantum Illumination	Blind Reconstruction Challenge	4	TESTNET	Mine →
Radio Aperture Synthesis	Blind Reconstruction Challenge	4	TESTNET	Mine →
Radio Interferometry (VLBI)	Blind Reconstruction Challenge	4	TESTNET	Mine →
SEM	Blind Reconstruction Challenge	4	TESTNET	Mine →
SIM	Blind Reconstruction Challenge	4	TESTNET	Mine →
SPC-Block	Blind Reconstruction Challenge	4	TESTNET	Mine →
SPECT/CT	Blind Reconstruction Challenge	4	TESTNET	Mine →
STEM	Blind Reconstruction Challenge	4	TESTNET	Mine →
Shearography	Blind Reconstruction Challenge	4	TESTNET	Mine →

How to submit an L4 Solution:

Pick a benchmark above and download the public test set
Run your reconstruction algorithm on the test data
Use the AI check prompt to verify your results look correct
Fill the submission form below and paste your PSNR / SSIM + method description

L3 Benchmarks — Extend an Existing Imaging System

Each benchmark is a fixed test dataset + scoring metric tied to an L2 Spec. Contribute a new benchmark if you have novel test data for an existing system.

Imaging System (L2)	Benchmark Title	Type	Solutions	Action
CASSI	Blind Reconstruction Challenge	challenge	5	View →
CACTI	Blind Reconstruction Challenge	challenge	5	View →
SPC-Block	Blind Reconstruction Challenge	challenge	4	View →
SPC-Kronecker	Blind Reconstruction Challenge	challenge	6	View →
Matrix	Blind Reconstruction Challenge	challenge	14	View →
CT	Blind Reconstruction Challenge	challenge	24	View →
CBCT	Blind Reconstruction Challenge	challenge	9	View →
PET	Blind Reconstruction Challenge	challenge	10	View →
SPECT	Blind Reconstruction Challenge	challenge	10	View →
X-ray Radiography	Blind Reconstruction Challenge	challenge	13	View →
Mammography	Blind Reconstruction Challenge	challenge	13	View →
Fluoroscopy	Blind Reconstruction Challenge	challenge	9	View →
X-ray Angiography	Blind Reconstruction Challenge	challenge	9	View →
DEXA	Blind Reconstruction Challenge	challenge	9	View →
DOT	Blind Reconstruction Challenge	challenge	9	View →
Photoacoustic	Blind Reconstruction Challenge	challenge	4	View →
MRI	Blind Reconstruction Challenge	challenge	35	View →
fMRI	Blind Reconstruction Challenge	challenge	35	View →
Diffusion MRI	Blind Reconstruction Challenge	challenge	9	View →
MRS	Blind Reconstruction Challenge	challenge	35	View →
Ultrasound	Blind Reconstruction Challenge	challenge	14	View →
Doppler Ultrasound	Blind Reconstruction Challenge	challenge	9	View →
Elastography	Blind Reconstruction Challenge	challenge	9	View →
Holography	Blind Reconstruction Challenge	challenge	14	View →
Ptychography	Blind Reconstruction Challenge	challenge	4	View →
CDI	Blind Reconstruction Challenge	challenge	14	View →
Widefield	Blind Reconstruction Challenge	challenge	13	View →
Widefield Low-Dose	Blind Reconstruction Challenge	challenge	13	View →
Confocal Live-Cell	Blind Reconstruction Challenge	challenge	9	View →
Confocal 3D	Blind Reconstruction Challenge	challenge	9	View →
Light-Sheet	Blind Reconstruction Challenge	challenge	13	View →
Two-Photon	Blind Reconstruction Challenge	challenge	13	View →
STED	Blind Reconstruction Challenge	challenge	13	View →
TIRF	Blind Reconstruction Challenge	challenge	13	View →
Fundus	Blind Reconstruction Challenge	challenge	4	View →
SIM	Blind Reconstruction Challenge	challenge	4	View →
FPM	Blind Reconstruction Challenge	challenge	4	View →
FLIM	Blind Reconstruction Challenge	challenge	9	View →
PALM/STORM	Blind Reconstruction Challenge	challenge	4	View →
Polarization	Blind Reconstruction Challenge	challenge	13	View →
SEM	Blind Reconstruction Challenge	challenge	4	View →
TEM	Blind Reconstruction Challenge	challenge	4	View →
STEM	Blind Reconstruction Challenge	challenge	4	View →
Electron Tomo	Blind Reconstruction Challenge	challenge	9	View →
4D-STEM	Blind Reconstruction Challenge	challenge	9	View →
Electron Holography	Blind Reconstruction Challenge	challenge	9	View →
EBSD	Blind Reconstruction Challenge	challenge	9	View →
EELS	Blind Reconstruction Challenge	challenge	9	View →
OCT	Blind Reconstruction Challenge	challenge	13	View →
OCTA	Blind Reconstruction Challenge	challenge	13	View →
Endoscopy	Blind Reconstruction Challenge	challenge	9	View →
Light Field	Blind Reconstruction Challenge	challenge	4	View →
Integral	Blind Reconstruction Challenge	challenge	4	View →
Lensless	Blind Reconstruction Challenge	challenge	4	View →
Panorama	Blind Reconstruction Challenge	challenge	4	View →
NeRF	Blind Reconstruction Challenge	challenge	11	View →
3DGS	Blind Reconstruction Challenge	challenge	11	View →
ToF Camera	Blind Reconstruction Challenge	challenge	4	View →
Structured Light	Blind Reconstruction Challenge	challenge	4	View →
LiDAR	Blind Reconstruction Challenge	challenge	4	View →

To contribute a new L3 Benchmark:

Pick an existing L2 Spec (imaging system) from the L2 tab
Prepare novel test data (public + hidden splits)
Use the L3 Benchmark template to write the benchmark definition
Check with AI agent using the prompt above, then submit below

L2 Specs — Imaging System Configurations

Each L2 Spec is an imaging system defined by a forward model DAG of 11 primitives (P, M, Π, F, C, Σ, D, S, W, R, Λ). The 169 systems below are the genesis set. If your imaging system isn't listed, propose a new L2 Spec.

Imaging System	Spec Notation	Benchmarks	Solutions	Network
3DGS	Π(splat) → Σ(alpha) → D(g, η₁)	1	11	TESTNET
4D-STEM	P(e⁻) → F(diffraction) → D(g, η₁)	1	9	TESTNET
Acoustic Emission Testing (AE)	P → S → D	1	9	TESTNET
Active Thermography (IR)	P → D	1	8	TESTNET
Adaptive Optics (AO) Imaging	M → C → D	1	8	TESTNET
Arterial Spin Labeling (ASL) MRI	M → F → S → D	1	9	TESTNET
Atom Probe Tomography (APT)	S → D	1	9	TESTNET
Atomic Force Microscopy (AFM)	S → D	1	7	TESTNET
Bioluminescence Tomography (BLT)	Src → R → P → D	1	9	TESTNET
Brachytherapy Imaging	Π → D	1	9	TESTNET
Brillouin Microscopy	M → R → D	1	9	TESTNET
CACTI	M(m_t) → Σ_t → D(g, η₄)	1	5	⬡ MAINNET
CASSI	M(mask) → W(α, a) → Σ_λ → D(g, η₄)	1	5	⬡ MAINNET
CBCT	R(θ) → Π(cone) → D(g, η₁)	1	9	TESTNET
CDI	P(far-field) → D(g, η₁)	1	14	TESTNET
CEST MRI	M → F → S → D	1	9	TESTNET
CT	R(θ) → Π(fan) → D(g, η₁)	1	24	TESTNET
CT + Fluorescence (FLIT)	(Π → D) + (M → R → P → D) → ⊕	1	9	TESTNET
Cathodoluminescence (CL) Imaging	M → R → D	1	9	TESTNET
Coded Exposure / Flutter Shutter	M → C → D	1	9	TESTNET
Coherent Anti-Stokes Raman (CARS) Microscopy	M → R → D	1	9	TESTNET
Compressed Ultrafast Photography (CUP)	M → Σ → D	1	9	TESTNET
Confocal 3D	C(PSF_3D) → D(g, η₃)	1	9	TESTNET
Confocal Laser Endomicroscopy (CLE)	M → C → D	1	9	TESTNET
Confocal Live-Cell	C(PSF_confocal) → D(g, η₃)	1	9	TESTNET
Contrast-Enhanced Ultrasound (CEUS)	P → R → D	1	9	TESTNET
Correlative Light-Electron Microscopy (CLEM)	(C → D) + (C → D) → ⊕	1	9	TESTNET
Cryo-EM Single Particle Analysis	C → D	1	9	TESTNET
Cryo-Electron Tomography (Cryo-ET)	Π → D	1	9	TESTNET
DESI Mass Spectrometry Imaging	S → D	1	9	TESTNET
DEXA	Λ(E₁,E₂) → Π(proj) → D(g, η₁)	1	9	TESTNET
DNA-PAINT Super-Resolution	M → D	1	9	TESTNET
DOT	P(diffuse) → Σ → D(g, η₃)	1	9	TESTNET
Dark-Field Microscopy	C → D	1	9	TESTNET
Differential Interference Contrast (DIC)	M → C → D	1	9	TESTNET
Diffusion MRI	F(EPI) → D(g, η₁)	1	9	TESTNET
Digital Breast Tomosynthesis (DBT)	Π → D	1	9	TESTNET
Doppler Ultrasound	P(acoustic) → Σ_t → D(g, η₂)	1	9	TESTNET
EBSD	P(e⁻) → Π(backscatter) → D(g, η₁)	1	9	TESTNET
EELS	P(e⁻) → Λ(energy) → D(g, η₁)	1	9	TESTNET
Eddy Current Imaging	F → D	1	9	TESTNET
Elastography	P(shear) → Σ_t → D(g, η₂)	1	9	TESTNET
Electrical Impedance Tomography (EIT)	M → D	1	4	TESTNET
Electron Holography	P(e⁻) → Σ(interference) → D(g, η₁)	1	9	TESTNET
Electron Tomo	R(θ) → P(e⁻) → Π(proj) → D(g, η₁)	1	9	TESTNET
Endoscopy	C(PSF_fiber) → D(g, η₁)	1	9	TESTNET
Entangled Photon Microscopy	M → R → D	1	9	TESTNET
Event Camera / Dynamic Vision Sensor (DVS)	M → D	1	9	TESTNET
Event Horizon Telescope (EHT) Imaging	F → S → D	1	9	TESTNET
Expansion Microscopy (ExM)	C → D	1	9	TESTNET
FLIM	C(PSF) → Σ_t → D(g, η₃)	1	9	TESTNET
FPM	S(LED array) → C(PSF_NA) → Σ_θ → D(g, η₁)	1	4	TESTNET
FTIR Spectroscopic Imaging	M → Σ → D	1	11	TESTNET
Flash LiDAR	P → D	1	9	TESTNET
Fluoroscopy	Π(proj) → Σ_t → D(g, η₁)	1	9	TESTNET
Focused Ion Beam SEM (FIB-SEM)	S → C → D	1	9	TESTNET
Full-Waveform Inversion (FWI)	P → D	1	4	TESTNET
Functional Near-Infrared Spectroscopy (fNIRS)	M → R → P → D	1	4	TESTNET
Fundus	C(PSF_optic) → D(g, η₁)	1	4	TESTNET
Ghost Imaging	M → Σ → D	1	10	TESTNET
Gravitational Wave Detection	P → Σ → D	1	4	TESTNET
Ground-Penetrating Radar (GPR)	P → D	1	4	TESTNET
High Dynamic Range (HDR) Imaging	M → Σ → D	1	14	TESTNET
Holography	P(Fresnel) → D(g, η₁)	1	14	TESTNET
Hyperspectral Remote Sensing	M → W → Σ → D	1	4	TESTNET
Image Scanning Microscopy (ISM)	C → D	1	13	TESTNET
Industrial CT	R(θ) → B(poly) → S(scatter) → D(g, η)	1	4	TESTNET
Integral	Π(lens-array) → D(g, η₁)	1	4	TESTNET
Interferometric SAR (InSAR)	F → S → D	1	4	TESTNET
Intravascular Ultrasound (IVUS)	P → D	1	14	TESTNET
Laser-Induced Breakdown Spectroscopy (LIBS) Imaging	M → R → D	1	11	TESTNET
Lattice Light-Sheet Microscopy	C → D	1	13	TESTNET
Lensless	P(diffuser) → D(g, η₁)	1	4	TESTNET
LiDAR	P(pulsed) → Σ(return) → D(g, η₁)	1	4	TESTNET
Light Field	Π(micro-lens) → D(g, η₁)	1	4	TESTNET
Light-Sheet	C(PSF_sheet) → D(g, η₃)	1	13	TESTNET
Lucky Imaging	M → C → D	1	4	TESTNET
MALDI Mass Spectrometry Imaging	S → D	1	11	TESTNET
MINFLUX Nanoscopy	C → D	1	4	TESTNET
MR Angiography (MRA)	M → F → S → D	1	35	TESTNET
MR Elastography (MRE)	M → F → S → D	1	35	TESTNET
MR Fingerprinting (MRF)	M → F → S → D	1	4	TESTNET
MRI	F(k-traj) → D(g, η₁)	1	35	TESTNET
MRS	F(FID) → D(g, η₁)	1	35	TESTNET
Machine Vision / AOI	C → D	1	4	TESTNET
Magnetic Force Microscopy (MFM)	S → M → D	1	10	TESTNET
Magnetic Particle Imaging (MPI)	M → F → D	1	11	TESTNET
Mammography	Π(contact) → D(g, η₁)	1	13	TESTNET
Matrix	M(Φ) → D(g, η₁)	1	14	TESTNET
Multispectral Satellite Imaging	M → Σ → D	1	13	TESTNET
Muon Tomo	R(θ_cosmic) → Π(muon) → D(g, η₁)	1	10	TESTNET
NeRF	Π(ray) → Σ(volume) → D(g, η₁)	1	11	TESTNET
Near-field Scanning Optical Microscopy (NSOM)	M → C → D	1	10	TESTNET
Neutron Diffraction	R → S → D	1	4	TESTNET
Neutron Tomo	R(θ) → Π(neutron) → D(g, η₁)	1	10	TESTNET
OCT	P(low-coherence) → Σ(interference) → D(g, η₁)	1	13	TESTNET
OCTA	P(low-coherence) → Σ(interference) → D(g, η₁)	1	13	TESTNET
Ocean Acoustic Tomography	P → D	1	11	TESTNET
Ocean Color Remote Sensing	M → Σ → D	1	4	TESTNET
Optical Diffraction Tomography (ODT)	P → D	1	4	TESTNET
PALM/STORM	C(PSF) → D(g, η₃)	1	4	TESTNET
PET	Π(LOR) → Σ_t → D(g, η₃)	1	10	TESTNET
PET/CT	R(θ) → D(μ_ct) → Π(LOR) → D(g, η)	1	13	TESTNET
PET/MR	F(k) → S(coil) → D(μ_mr) → R(θ) → D(g, η)	1	10	TESTNET
Panorama	C(PSF_focus) → Σ_f → D(g, η₁)	1	4	TESTNET
Particle Calorimetry	R → Σ → D	1	4	TESTNET
Passive Microwave Radiometry	Σ → D	1	4	TESTNET
Phase Contrast Microscopy	C → D	1	4	TESTNET
Photoacoustic	P(acoustic) → Σ_t → D(g, η₂)	1	4	TESTNET
Photometric Stereo	M → C → D	1	4	TESTNET
Polarimetric SAR (PolSAR)	F → M → D	1	13	TESTNET
Polarization	M(polarizer) → C(PSF) → D(g, η₁)	1	13	TESTNET
Portal Imaging (EPID)	Π → D	1	13	TESTNET
Proton Radiography	Π(proton) → D(g, η₁)	1	4	TESTNET
Proton Therapy Imaging	Π → D	1	13	TESTNET
Ptychography	P(probe) → D(g, η₁)	1	4	TESTNET
Pump-Probe Microscopy	M → R → D	1	4	TESTNET
Quantum Illumination	M → R → D	1	4	TESTNET
Radio Aperture Synthesis	F → S → D	1	4	TESTNET
Radio Interferometry (VLBI)	F → S → D	1	4	TESTNET
Raman Imaging / Microscopy	M → R → D	1	11	TESTNET
SAR	F(azimuth×range) → D(g, η₁)	1	13	TESTNET
SEM	P(e⁻ beam) → C(probe) → D(g, η₁)	1	4	TESTNET
SIM	S(grating) → C(PSF) → Σ_φ → D(g, η₃)	1	4	TESTNET
SPC-Block	S(block) → M(Φ) → Σ → D(g, η₁)	1	4	TESTNET
SPC-Kronecker	M(H⊗W) → D(g, η₁)	1	6	TESTNET
SPECT	Π(parallel) → Σ_E → D(g, η₃)	1	10	TESTNET
SPECT/CT	R(θ) → D(μ_ct) → H(coll) → D(g, η)	1	4	TESTNET
STED	C(PSF_STED) → D(g, η₃)	1	13	TESTNET
STEM	P(e⁻) → C(probe) → D(g, η₁)	1	4	TESTNET
STEM-EDX Elemental Mapping	M → R → D	1	9	TESTNET
Scanning Acoustic Microscopy (SAM)	P → D	1	8	TESTNET
Scanning Tunneling Microscopy (STM)	S → D	1	10	TESTNET
Second Harmonic Generation (SHG) Microscopy	M → R → D	1	13	TESTNET
Secondary Ion Mass Spectrometry (SIMS) Imaging	S → D	1	11	TESTNET
Seismic Tomography	P → D	1	11	TESTNET
Shearography	M → P → D	1	4	TESTNET
Small-Angle X-ray Scattering (SAXS)	R → D	1	4	TESTNET
Solar EUV/X-ray Imaging	M → P → D	1	4	TESTNET
Sonar	P(acoustic) → Σ_t → D(g, η₂)	1	4	TESTNET
Spectral CT	R(θ) → A(E_low, E_high) → Σ_mat → D(g, η)	1	13	TESTNET
Spinning Disk Confocal Microscopy	C → D	1	13	TESTNET
Stellar Coronagraphy	M → P → D	1	9	TESTNET
Stimulated Raman Scattering (SRS) Microscopy	M → R → D	1	11	TESTNET
Streak Camera Imaging	M → Σ → D	1	11	TESTNET
Structured Light	S(pattern) → Π(triangulation) → D(g, η₁)	1	4	TESTNET
Susceptibility-Weighted Imaging (SWI)	M → F → S → D	1	35	TESTNET
TEM	P(e⁻) → C(CTF) → D(g, η₁)	1	4	TESTNET
TIRF	C(PSF_TIRF) → D(g, η₃)	1	13	TESTNET
Talbot-Lau X-ray Grating Interferometry	M → P → D	1	4	TESTNET
Terahertz Imaging (THz)	P → D	1	4	TESTNET
Three-Photon Microscopy	C → D	1	13	TESTNET
ToF Camera	P(modulated) → Σ(correlation) → D(g, η₁)	1	4	TESTNET
Two-Photon	C(PSF_2P) → D(g, η₃)	1	13	TESTNET
US/MRI Fusion	(P → D) + (M → F → S → D) → ⊕	1	4	TESTNET
Ultrasonic Phased Array (TFM/FMC)	P → D	1	4	TESTNET
Ultrasound	P(acoustic) → Σ_t → D(g, η₂)	1	14	TESTNET
Weather / Doppler Radar	P → R → D	1	4	TESTNET
Wide-Angle X-ray Scattering (WAXS)	R → D	1	4	TESTNET
Widefield	C(PSF) → D(g, η₃)	1	13	TESTNET
Widefield Low-Dose	C(PSF) → D(g, η₃)	1	13	TESTNET
X-ray Angiography	Π(proj) → D(g, η₁)	1	9	TESTNET
X-ray Crystallography	F → S → D	1	4	TESTNET
X-ray Fluorescence (XRF) Imaging	M → R → D	1	4	TESTNET
X-ray Fluorescence Tomography	Π → R → D	1	11	TESTNET
X-ray NDT (Radiography)	Π → D	1	4	TESTNET
X-ray Radiography	Π(proj) → D(g, η₁)	1	13	TESTNET
XFEL Serial Femtosecond Crystallography (SFX)	M → R → D	1	4	TESTNET
fMRI	F(EPI) → Σ_t → D(g, η₁)	1	35	TESTNET

To contribute a new L2 Spec:

Check the table above — is your imaging system already listed?
If not, pick a parent L1 Principle it builds on
Use the L2 Spec template to define the forward model DAG
Check with AI agent, then submit below

📤

Step 3 — Submit for Review

What happens after you submit

You submit

Artifact + AI check report + your wallet address

Founder reviews

Physics correctness · novelty · template compliance

Mainnet deploy

Artifact registered on Base mainnet by deployer EOA

You earn PWM

Royalties auto-distributed on every downstream query

Layer *

Title *

Parent artifact (L3→ select L2; L2→ select L1)

Artifact content (Markdown) *

AI check result *

Your wallet address (Base) *

Email (for review notification)

Reviews typically take 1–3 days. You'll be notified by email when approved.

PWM royalty split — what you earn per query

55% of SP share

L4 Solution author

15%

L3 Benchmark author

10%

L2 Spec author

L1 Principle author

Rank weights: 1st×40% · 2nd×5% · 3rd×2% · 4–10th×1% each. Paid on cert finalization (7-day challenge window).