L1 ⚛ L1-369 ⊙ Testnet

Weak Gravitational Lensing Shear Estimation

Astrophysics · Cosmic shear

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⬇ L1-369.md

# ⚛ L1 Principle — Weak Gravitational Lensing Shear Estimation **ID:** `L1-369` · **Status:** ⊙ Testnet (genesis catalog) > **🌐 Domain:** Astrophysics — *Cosmic shear* > **🎯 Problem class:** statistical inverse · **🧮 Solution space:** 2D convergence map > **📡 Carrier:** photon · **🌫 Noise:** shape noise gaussian > **⚖ Difficulty (δ):** 5 · **⛓ Block:** 41555177 --- ## 🧠 1. Introduction **Weak Gravitational Lensing Shear Estimation** is a **statistical inverse problem** whose unknown lives in **2D convergence map** space, within the **Cosmic shear** sub-domain of **Astrophysics**. Measurements consist of photons collected by an optical detector via a **ellipticity shear correlation** sensing mechanism. The forward operator applies, in order: S · shear · ellipticity operator; F · fourier · e mode operator; O · correlation · 2pcf operator. Observations are corrupted by shape noise gaussian. Existence of the recovered 2D_convergence_map is guaranteed within the declared Omega bounds. Uniqueness holds on the measurement-supported subspace; out-of-support modes are controlled by declared priors. Stability is conditionally stable (kappa_eff ~= 20); PSF_leakage dominates the stability cliff; the remaining mismatch parameters contribute higher-order bias terms. Shape noise gaussian sets the irreducible data-fidelity floor. ## ⚙ 2. Forward Model Physical chain: **x** → S · shear · ellipticity → F · fourier · e mode → O · correlation · 2pcf → **y** (detector). ``` y = `O.correlation.2pcf` `F.fourier.e_mode` `S.shear.ellipticity` x ``` **Measurement DAG:** | Primitive | What it does | |---|---| | `S.shear.ellipticity` | S · shear · ellipticity operator | | `F.fourier.e_mode` | F · fourier · e mode operator | | `O.correlation.2pcf` | O · correlation · 2pcf operator | ## 🔬 3. Physics Fingerprint | Property | Value | |---|---| | Domain | Astrophysics | | Sub domain | Cosmic shear | | Carrier | photon | | Problem class | statistical_inverse | | Solution space | 2D_convergence_map | | Noise model | shape_noise_gaussian | | Integration axis | angular_correlation | | Difficulty delta | 5 | | L dag | 3.2 | ## 📡 4. Measurement Model Existence of the recovered 2D_convergence_map is guaranteed within the declared Omega bounds. Uniqueness holds on the measurement-supported subspace; out-of-support modes are controlled by declared priors. Stability is conditionally stable (kappa_eff ~= 20); PSF_leakage dominates the stability cliff; the remaining mismatch parameters contribute higher-order bias terms. Shape noise gaussian sets the irreducible data-fidelity floor. | Metric | Value | |---|---| | Metric | sigma_8_Omega_m_constraint_area | | Secondary | shear_calibration_bias | ## 📏 5. Operating Range (Ω) **Center problem class:** `statistical_inverse` · **Forward operator:** `ellipticity_shear_correlation` **Center point:** | Parameter | Unit | Value | |---|---|---| | A ia | — | 0.5 | | N gal million | — | 100 | | N gal arcmin2 | — | 10 | | Survey area deg2 | — | 1000 | **Allowed bounds:** | Parameter | Unit | Range | |---|---|---| | A ia | — | 0.0 – 2.0 | | N gal million | — | 1 – 3000 | | N gal arcmin2 | — | 5 – 100 | | Survey area deg2 | — | 100 – 20000 | ## 🎯 6. Tolerance (ε) **Center tolerance:** 0.015 sigma_8_Omega_m_constraint_area | Metric | Range | |---|---| | Sigma 8 omega m constraint area | 0.005 – 0.05 | ## ⚖ 7. Hardness Function Hardness scales as **`epsilon_fn`** on **sigma_8_Omega_m_constraint_area**, with κ = `500` and δ = `5`. ## 💾 8. Reference Dataset - **primary** · weight 1.0 · IPFS _(not pinned yet)_ ## 9. On-chain Registration - **Chain hash:** `0xb4bd353c63a743d3c416c5bd2a76462fa120577f7286904cea366a45656bb6ba` - **Chain tx hash:** `0xd83926770fc864b456937b83229b4a6a91d455b0b2a6030037300f98f1570e83` - **Chain block:** `41555177` --- ## File Mapping This bundle consists of: `L1-369.md`, `L1-369.json`. | File | Role | How to regenerate | |------|------|-------------------| | `L1-369.md` | Source of truth — edit this | Human or LLM | | `L1-369.json` | Structured metadata for the registry | LLM regenerates from the sections above | **Prompt for your LLM after editing this Markdown:** > Read the attached Markdown. Regenerate the sibling `.json` so every field matches. > Preserve the schema documented in the rows above. > Output each file in its own fenced code block tagged with the filename. > Output only the JSON object. _This Markdown was auto-synthesized from the catalog row for `L1-369`._ _Edit it, regenerate the JSON, and submit at [/submit](/submit) to claim the artifact._

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Read the attached Markdown (L1-369.md).
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L2-369-001 Weak Gravitational Lensing Shear Estimation — Nominal + Mismatch Specs

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📋 JSON metadata

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  "domain": "Astrophysics",
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    "integration_axis": "angular_correlation",
    "noise_model": "shape_noise_gaussian",
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    "sub_domain": "Cosmic shear",
    "title": "Weak Gravitational Lensing Shear Estimation"
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      "survey_area_deg2": [
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  "staked_pwm": 0.0,
  "status": "testnet",
  "sub_domain": "Cosmic shear",
  "title": "Weak Gravitational Lensing Shear Estimation"
}

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