L1 ⚛ L1-120 ⊙ Testnet

Scanning Acoustic Microscopy (SAM)

Industrial Inspection · High-frequency ultrasonic microscopy for buried interfaces

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⬇ principle.md ⬇ principle.json

Fork L1-120

⬇ L1-120.md ⬇ L1-120.json

Prompt — copy into your LLM

You are helping me submit a MODIFICATION of L1-120 (Scanning Acoustic Microscopy (SAM)) to the PWM Protocol — a Principle (L1) artifact.

I will paste a Markdown template (or the current L1-120.md).
1. Rewrite the Markdown so the science is correct and clearly explained for my change.
2. Regenerate the sibling L1-120.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 = ∫_t dt `L.pulse_echo` S_raster `L.acoustic_lens` x + n,    n ~ 𝒩(0, σ²)

world state x (3D acoustic impedance)

→

L · acoustic lens `L.acoustic_lens`

→

Raster scan S_raster

→

L · pulse echo `L.pulse_echo`

→

Temporal integration ∫_t dt

→

observation y (acoustic detector)

Noise: additive Gaussian noise

Markdown — human-readable source of truth

⚙ auto-generated

⬇ L1-120.md

# ⚛ L1 Principle — Scanning Acoustic Microscopy (SAM) **ID:** `L1-120` · **Status:** ⊙ Testnet (genesis catalog) > **🌐 Domain:** Industrial Inspection — *High-frequency ultrasonic microscopy for buried interfaces* > **🎯 Problem class:** linear inverse · **🧮 Solution space:** 3D acoustic impedance > **📡 Carrier:** acoustic · **🌫 Noise:** gaussian > **⚖ Difficulty (δ):** 3 · **⛓ Block:** 41554212 --- ## 🧠 1. Introduction **Scanning Acoustic Microscopy (SAM)** is a **linear inverse problem** whose unknown lives in **3D acoustic impedance** space, within the **High-frequency ultrasonic microscopy for buried interfaces** sub-domain of **Industrial Inspection**. Measurements consist of acoustic pressure waves recorded by transducers via a **scanning acoustic microscopy** sensing mechanism. The forward operator applies, in order: L · acoustic lens operator; ordered pixel-by-pixel sampling; L · pulse echo operator; detector accumulates flux over the exposure window. Observations are corrupted by additive Gaussian noise. Existence of the recovered 3D acoustic impedance is guaranteed within the declared Omega bounds. Uniqueness holds on the measurement-supported subspace; out-of-support modes are controlled by the declared priors. Stability is moderately conditioned (kappa_eff ~= 10); coupling_fluid_variation dominates the stability cliff; surface_curvature and the remaining mismatch parameters contribute higher-order bias terms. Additive gaussian thermal/electronic noise sets the irreducible data-fidelity floor, while mild Tikhonov or analytic inversion is sufficient at the nominal Omega point. ## ⚙ 2. Forward Model Physical chain: **x** → L · acoustic lens → Raster scan → L · pulse echo → Temporal integration → **y** (detector). ``` y = ∫_t dt `L.pulse_echo` S_raster `L.acoustic_lens` x + n, n ~ 𝒩(0, σ²) ``` **Measurement DAG:** | Primitive | What it does | |---|---| | `L.acoustic_lens` | L · acoustic lens operator | | `S.scan.raster` | Ordered pixel-by-pixel sampling | | `L.pulse_echo` | L · pulse echo operator | | `int.temporal` | Detector accumulates flux over the exposure window | ## 🔬 3. Physics Fingerprint | Property | Value | |---|---| | Domain | Industrial Inspection | | Sub domain | High-frequency ultrasonic microscopy for buried interfaces | | Carrier | acoustic | | Problem class | linear_inverse | | Solution space | 3D_acoustic_impedance | | Noise model | gaussian | | Integration axis | temporal | | Difficulty delta | 3 | | L dag | 3.3 | ## 📡 4. Measurement Model Existence of the recovered 3D acoustic impedance is guaranteed within the declared Omega bounds. Uniqueness holds on the measurement-supported subspace; out-of-support modes are controlled by the declared priors. Stability is moderately conditioned (kappa_eff ~= 10); coupling_fluid_variation dominates the stability cliff; surface_curvature and the remaining mismatch parameters contribute higher-order bias terms. Additive gaussian thermal/electronic noise sets the irreducible data-fidelity floor, while mild Tikhonov or analytic inversion is sufficient at the nominal Omega point. | Metric | Value | |---|---| | Metric | PSNR_dB | | Secondary | SSIM | ## 📏 5. Operating Range (Ω) **Center problem class:** `sam` · **Forward operator:** `sam_forward` **Center point:** | Parameter | Unit | Value | |---|---|---| | H | px | 512 | | W | px | 512 | | Z | — | 64 | | F mhz | MHz | 100 | | Snr db | dB | 25 | | Pixel um | µm | 10 | | Surface curvature | — | 0 | | Multiple reflections | — | 0 | | Coupling fluid variation | — | 0 | **Allowed bounds:** | Parameter | Unit | Range | |---|---|---| | H | px | 64 – 2048 | | W | px | 64 – 2048 | | Z | — | 16 – 512 | | F mhz | MHz | 10 – 2000 | | Snr db | dB | 0.0 – 40.0 | | Pixel um | µm | 0.5 – 500 | | Surface curvature | — | 0.0 – 0.3 | | Multiple reflections | — | 0.0 – 0.3 | | Water path attenuation | — | 0.0 – 0.2 | | Coupling fluid variation | — | 0.0 – 0.2 | ## 🎯 6. Tolerance (ε) **Center tolerance:** 26.0 | Metric | Range | |---|---| | Psnr db | 5.0 – 40.0 | ## ⚖ 7. Hardness Function Hardness scales as **`epsilon_fn`** on **PSNR_dB**, with κ = `200` and δ = `3`. ## 💾 8. Reference Dataset - **primary** · weight 1.0 · IPFS _(not pinned yet)_ ## 9. On-chain Registration - **Chain hash:** `0xd3e211b87ec868c236c41128dc2020c1a2f0725d5c591d07f0f3260a5bd80a4e` - **Chain tx hash:** `0x59bedcf1bb380e6c2178d52f606383d252ca9a8532db92b3b2e26da13489f085` - **Chain block:** `41554212` --- ## File Mapping This bundle consists of: `L1-120.md`, `L1-120.json`. | File | Role | How to regenerate | |------|------|-------------------| | `L1-120.md` | Source of truth — edit this | Human or LLM | | `L1-120.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 `L1-120`._ _Edit it, regenerate the JSON, and submit at [/submit](/submit) to claim the artifact._

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L2-120-001 Scanning Acoustic Microscopy (SAM) Mismatch-Only Spec

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📋 JSON metadata

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  "artifact_id": "L1-120",
  "chain_block": 41554212,
  "chain_hash": "0xd3e211b87ec868c236c41128dc2020c1a2f0725d5c591d07f0f3260a5bd80a4e",
  "chain_tx_hash": "0x59bedcf1bb380e6c2178d52f606383d252ca9a8532db92b3b2e26da13489f085",
  "domain": "Industrial Inspection",
  "hardness_fn": {
    "delta": 3,
    "kappa": 200,
    "metric": "PSNR_dB",
    "type": "epsilon_fn"
  },
  "initiator_dataset": [
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      "license_hash": null,
      "name": "primary",
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  "layer": "L1",
  "observable_profile": {
    "metric": "PSNR_dB",
    "regime": "Existence of the recovered 3D acoustic impedance is guaranteed within the declared Omega bounds. Uniqueness holds on the measurement-supported subspace; out-of-support modes are controlled by the declared priors. Stability is moderately conditioned (kappa_eff ~= 10); coupling_fluid_variation dominates the stability cliff; surface_curvature and the remaining mismatch parameters contribute higher-order bias terms. Additive gaussian thermal/electronic noise sets the irreducible data-fidelity floor, while mild Tikhonov or analytic inversion is sufficient at the nominal Omega point.",
    "secondary": "SSIM"
  },
  "physics_fingerprint": {
    "L_DAG": 3.3,
    "carrier": "acoustic",
    "difficulty_delta": 3,
    "domain": "Industrial Inspection",
    "integration_axis": "temporal",
    "noise_model": "gaussian",
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    ],
    "problem_class": "linear_inverse",
    "sensing_mechanism": "scanning_acoustic_microscopy",
    "solution_space": "3D_acoustic_impedance",
    "sub_domain": "High-frequency ultrasonic microscopy for buried interfaces",
    "title": "Scanning Acoustic Microscopy (SAM)"
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    "allowed_problem_classes": [
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      "water_path_attenuation": [
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        0.2
      ]
    }
  },
  "staked_pwm": 0.0,
  "status": "testnet",
  "sub_domain": "High-frequency ultrasonic microscopy for buried interfaces",
  "title": "Scanning Acoustic Microscopy (SAM)"
}

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