L1 ⚛ L1-167 ⊙ Testnet

Lucky Imaging Atmospheric Turbulence Recovery

Astronomy · Atmospheric compensation

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⬇ principle.md ⬇ principle.json

Fork L1-167

⬇ L1-167.md ⬇ L1-167.json

Prompt — copy into your LLM

You are helping me submit a MODIFICATION of L1-167 (Lucky Imaging Atmospheric Turbulence Recovery) to the PWM Protocol — a Principle (L1) artifact.

I will paste a Markdown template (or the current L1-167.md).
1. Rewrite the Markdown so the science is correct and clearly explained for my change.
2. Regenerate the sibling L1-167.json so EVERY field matches the Markdown.
3. Keep the schema in the "File Mapping" footer at the bottom of the MD.
4. Keep the parent reference unchanged unless I ask otherwise.
Rules: the Markdown is the source of truth; use SI units; do NOT invent benchmark scores.
Output each file in its own fenced code block tagged with the filename.

Here is my template:
[PASTE THE .md HERE]

⚙ Forward Model

y = `O.shift_add` `S.frame.selection` `K.psf.turbulence` x,    measurements ~ Poisson(αy)

world state x (2D intensity)

→

K · psf · turbulence `K.psf.turbulence`

→

S · frame · selection `S.frame.selection`

→

O · shift add `O.shift_add`

→

observation y (photon detector)

Noise: Poisson shot noise from quantum-limited detection

Markdown — human-readable source of truth

⚙ auto-generated

⬇ L1-167.md

# ⚛ L1 Principle — Lucky Imaging Atmospheric Turbulence Recovery **ID:** `L1-167` · **Status:** ⊙ Testnet (genesis catalog) > **🌐 Domain:** Astronomy — *Atmospheric compensation* > **🎯 Problem class:** linear inverse · **🧮 Solution space:** 2D intensity > **📡 Carrier:** photon · **🌫 Noise:** shot poisson > **⚖ Difficulty (δ):** 3 · **⛓ Block:** 41554243 --- ## 🧠 1. Introduction **Lucky Imaging Atmospheric Turbulence Recovery** is a **linear inverse problem** whose unknown lives in **2D intensity** space, within the **Atmospheric compensation** sub-domain of **Astronomy**. Measurements consist of photons collected by an optical detector via a **frame selection deconvolution** sensing mechanism. The forward operator applies, in order: K · psf · turbulence operator; S · frame · selection operator; O · shift add operator. Observations are corrupted by Poisson shot noise from quantum-limited detection. Existence of the recovered 2D_intensity 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 ~= 50); seeing_variation dominates the stability cliff; the remaining mismatch parameters contribute higher-order bias terms. Shot poisson sets the irreducible data-fidelity floor. ## ⚙ 2. Forward Model Physical chain: **x** → K · psf · turbulence → S · frame · selection → O · shift add → **y** (detector). ``` y = `O.shift_add` `S.frame.selection` `K.psf.turbulence` x, measurements ~ Poisson(αy) ``` **Measurement DAG:** | Primitive | What it does | |---|---| | `K.psf.turbulence` | K · psf · turbulence operator | | `S.frame.selection` | S · frame · selection operator | | `O.shift_add` | O · shift add operator | ## 🔬 3. Physics Fingerprint | Property | Value | |---|---| | Domain | Astronomy | | Sub domain | Atmospheric compensation | | Carrier | photon | | Problem class | linear_inverse | | Solution space | 2D_intensity | | Noise model | shot_poisson | | Integration axis | temporal | | Difficulty delta | 3 | | L dag | 2.5 | ## 📡 4. Measurement Model Existence of the recovered 2D_intensity 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 ~= 50); seeing_variation dominates the stability cliff; the remaining mismatch parameters contribute higher-order bias terms. Shot poisson sets the irreducible data-fidelity floor. | Metric | Value | |---|---| | Metric | Strehl_ratio | | Secondary | FWHM_lambda_over_D | ## 📏 5. Operating Range (Ω) **Center problem class:** `linear_inverse` · **Forward operator:** `frame_selection_deconvolution` **Center point:** | Parameter | Unit | Value | |---|---|---| | H | px | 256 | | W | px | 256 | | N frames | — | 500 | | Seeing r0 cm | — | 15 | | Selection fraction | — | 0.05 | **Allowed bounds:** | Parameter | Unit | Range | |---|---|---| | H | px | 64 – 1024 | | W | px | 64 – 1024 | | N frames | — | 100 – 5000 | | Seeing r0 cm | — | 5.0 – 30.0 | | Selection fraction | — | 0.001 – 0.2 | ## 🎯 6. Tolerance (ε) **Center tolerance:** 0.30 Strehl_ratio | Metric | Range | |---|---| | Strehl ratio | 0.05 – 0.8 | ## ⚖ 7. Hardness Function Hardness scales as **`epsilon_fn`** on **Strehl_ratio**, with κ = `3000` and δ = `3`. ## 💾 8. Reference Dataset - **primary** · weight 1.0 · IPFS _(not pinned yet)_ ## 9. On-chain Registration - **Chain hash:** `0xf5d129fd0e87d75a8e4f39bc50228553d271dba82358a71a0c1d9308c1d35e8a` - **Chain tx hash:** `0xe3eba1e4c05b3547a5d45028840008c66af1e0b01c2ce3c6c328a3fa98d877d1` - **Chain block:** `41554243` --- ## File Mapping This bundle consists of: `L1-167.md`, `L1-167.json`. | File | Role | How to regenerate | |------|------|-------------------| | `L1-167.md` | Source of truth — edit this | Human or LLM | | `L1-167.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 `L1-167`._ _Edit it, regenerate the JSON, and submit at [/submit](/submit) to claim the artifact._

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⌥ Hierarchy

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L2-167-001 Lucky Imaging Atmospheric Turbulence Recovery — Nominal + Mismatch Specs

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📋 JSON metadata

{
  "artifact_id": "L1-167",
  "chain_block": 41554243,
  "chain_hash": "0xf5d129fd0e87d75a8e4f39bc50228553d271dba82358a71a0c1d9308c1d35e8a",
  "chain_tx_hash": "0xe3eba1e4c05b3547a5d45028840008c66af1e0b01c2ce3c6c328a3fa98d877d1",
  "domain": "Astronomy",
  "hardness_fn": {
    "delta": 3,
    "kappa": 3000,
    "metric": "Strehl_ratio",
    "type": "epsilon_fn"
  },
  "initiator_dataset": [
    {
      "ipfs_cid": null,
      "license_hash": null,
      "name": "primary",
      "weight": 1.0
    }
  ],
  "layer": "L1",
  "observable_profile": {
    "metric": "Strehl_ratio",
    "regime": "Existence of the recovered 2D_intensity 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 ~= 50); seeing_variation dominates the stability cliff; the remaining mismatch parameters contribute higher-order bias terms. Shot poisson sets the irreducible data-fidelity floor.",
    "secondary": "FWHM_lambda_over_D"
  },
  "physics_fingerprint": {
    "L_DAG": 2.5,
    "carrier": "photon",
    "difficulty_delta": 3,
    "domain": "Astronomy",
    "integration_axis": "temporal",
    "noise_model": "shot_poisson",
    "primitives": [
      "K.psf.turbulence",
      "S.frame.selection",
      "O.shift_add"
    ],
    "problem_class": "linear_inverse",
    "sensing_mechanism": "frame_selection_deconvolution",
    "solution_space": "2D_intensity",
    "sub_domain": "Atmospheric compensation",
    "title": "Lucky Imaging Atmospheric Turbulence Recovery"
  },
  "size_tiers": {
    "allowed_forward_operators": [
      "frame_selection_deconvolution"
    ],
    "allowed_omega_dimensions": [
      "H",
      "W",
      "N_frames",
      "seeing_r0_cm",
      "selection_fraction"
    ],
    "allowed_problem_classes": [
      "linear_inverse"
    ],
    "center_spec": {
      "epsilon_fn_center": "0.30 Strehl_ratio",
      "forward_operator": "frame_selection_deconvolution",
      "input_format": "measurement_only",
      "omega": {
        "H": 256,
        "N_frames": 500,
        "W": 256,
        "seeing_r0_cm": 15.0,
        "selection_fraction": 0.05
      },
      "problem_class": "linear_inverse"
    },
    "epsilon_bounds": {
      "Strehl_ratio": [
        0.05,
        0.8
      ]
    },
    "omega_bounds": {
      "H": [
        64,
        1024
      ],
      "N_frames": [
        100,
        5000
      ],
      "W": [
        64,
        1024
      ],
      "seeing_r0_cm": [
        5.0,
        30.0
      ],
      "selection_fraction": [
        0.001,
        0.2
      ]
    }
  },
  "staked_pwm": 0.0,
  "status": "testnet",
  "sub_domain": "Atmospheric compensation",
  "title": "Lucky Imaging Atmospheric Turbulence Recovery"
}

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