L1 ⚛ L1-101 ⊙ Testnet

Active Sonar — underwater acoustic imaging

Remote Sensing · Underwater acoustic imaging

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⬇ L1-101.md

# ⚛ L1 Principle — Active Sonar — underwater acoustic imaging **ID:** `L1-101` · **Status:** ⊙ Testnet (genesis catalog) > **🌐 Domain:** Remote Sensing — *Underwater acoustic imaging* > **🎯 Problem class:** linear inverse · **🧮 Solution space:** 2D acoustic reflectivity > **📡 Carrier:** acoustic · **🌫 Noise:** gaussian > **⚖ Difficulty (δ):** 3 · **⛓ Block:** 41554186 --- ## 🧠 1. Introduction **Active Sonar — underwater acoustic imaging** is a **linear inverse problem** whose unknown lives in **2D acoustic reflectivity** space, within the **Underwater acoustic imaging** sub-domain of **Remote Sensing**. Measurements consist of acoustic pressure waves recorded by transducers via a **active sonar pulse** sensing mechanism. The forward operator applies, in order: L · emit · acoustic pulse operator; S · scan · beam operator; L · beamform operator; detector accumulates flux over the exposure window. Observations are corrupted by additive Gaussian noise. Existence of the recovered 2D acoustic reflectivity 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 ~= 12); sound_speed_profile_error dominates the stability cliff; multipath 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 · emit · acoustic pulse → S · scan · beam → L · beamform → Temporal integration → **y** (detector). ``` y = ∫_t dt `L.beamform` `S.scan.beam` `L.emit.acoustic_pulse` x + n, n ~ 𝒩(0, σ²) ``` **Measurement DAG:** | Primitive | What it does | |---|---| | `L.emit.acoustic_pulse` | L · emit · acoustic pulse operator | | `S.scan.beam` | S · scan · beam operator | | `L.beamform` | L · beamform operator | | `int.temporal` | Detector accumulates flux over the exposure window | ## 🔬 3. Physics Fingerprint | Property | Value | |---|---| | Domain | Remote Sensing | | Sub domain | Underwater acoustic imaging | | Carrier | acoustic | | Problem class | linear_inverse | | Solution space | 2D_acoustic_reflectivity | | Noise model | gaussian | | Integration axis | temporal | | Difficulty delta | 3 | | L dag | 3.5 | ## 📡 4. Measurement Model Existence of the recovered 2D acoustic reflectivity 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 ~= 12); sound_speed_profile_error dominates the stability cliff; multipath 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:** `sonar_active` · **Forward operator:** `sonar_active_forward` **Center point:** | Parameter | Unit | Value | |---|---|---| | F khz | kHz | 100 | | Snr db | dB | 20 | | N beams | — | 128 | | Range m | m | 500 | | Multipath | — | 0 | | N range bins | — | 1024 | | Platform roll | — | 0 | | Sound speed profile error | — | 0 | **Allowed bounds:** | Parameter | Unit | Range | |---|---|---| | F khz | kHz | 10 – 1000 | | Snr db | dB | 0.0 – 30.0 | | N beams | — | 32 – 1024 | | Range m | m | 10 – 5000 | | Multipath | — | 0.0 – 0.5 | | N range bins | — | 256 – 8192 | | Platform roll | — | 0.0 – 0.1 | | Reverberation | — | 0.0 – 0.3 | | Sound speed profile error | — | 0.0 – 0.05 | ## 🎯 6. Tolerance (ε) **Center tolerance:** 22.0 | Metric | Range | |---|---| | Psnr db | 5.0 – 40.0 | ## ⚖ 7. Hardness Function Hardness scales as **`epsilon_fn`** on **PSNR_dB**, with κ = `240` and δ = `3`. ## 💾 8. Reference Dataset - **primary** · weight 1.0 · IPFS _(not pinned yet)_ ## 9. On-chain Registration - **Chain hash:** `0x3ef545f9bf1b1692e3134d803e6d16b44b3343acaae994598dfe8993079f40c1` - **Chain tx hash:** `0x689ccee2465e89857007da46d5e087cbcb3923f68876625a032e73f9abf66b6d` - **Chain block:** `41554186` --- ## File Mapping This bundle consists of: `L1-101.md`, `L1-101.json`. | File | Role | How to regenerate | |------|------|-------------------| | `L1-101.md` | Source of truth — edit this | Human or LLM | | `L1-101.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 `L1-101`._ _Edit it, regenerate the JSON, and submit at [/submit](/submit) to claim the artifact._

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Read the attached Markdown (L1-101.md).
Regenerate L1-101.json so every field matches the Markdown.
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L2-101-001 Active Sonar — underwater acoustic imaging Mismatch-Only Spec

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📋 JSON metadata

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  "domain": "Remote Sensing",
  "hardness_fn": {
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    "kappa": 240,
    "metric": "PSNR_dB",
    "type": "epsilon_fn"
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    "regime": "Existence of the recovered 2D acoustic reflectivity 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 ~= 12); sound_speed_profile_error dominates the stability cliff; multipath 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": 3.5,
    "carrier": "acoustic",
    "difficulty_delta": 3,
    "domain": "Remote Sensing",
    "integration_axis": "temporal",
    "noise_model": "gaussian",
    "primitives": [
      "L.emit.acoustic_pulse",
      "S.scan.beam",
      "L.beamform",
      "int.temporal"
    ],
    "problem_class": "linear_inverse",
    "sensing_mechanism": "active_sonar_pulse",
    "solution_space": "2D_acoustic_reflectivity",
    "sub_domain": "Underwater acoustic imaging",
    "title": "Active Sonar \u2014 underwater acoustic imaging"
  },
  "size_tiers": {
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      "sound_speed_profile_error",
      "multipath",
      "platform_roll",
      "sound_speed_profile_error",
      "multipath",
      "platform_roll",
      "reverberation"
    ],
    "allowed_problem_classes": [
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    "center_spec": {
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      "forward_operator": "sonar_active_forward",
      "input_format": "measurement_only",
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        "N_range_bins": 1024,
        "SNR_dB": 20.0,
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        "sound_speed_profile_error": 0.0
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    "epsilon_bounds": {
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        40.0
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        1024
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      "N_range_bins": [
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      "SNR_dB": [
        0.0,
        30.0
      ],
      "f_kHz": [
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        1000
      ],
      "multipath": [
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        0.5
      ],
      "platform_roll": [
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        0.1
      ],
      "range_m": [
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        5000
      ],
      "reverberation": [
        0.0,
        0.3
      ],
      "sound_speed_profile_error": [
        0.0,
        0.05
      ]
    }
  },
  "staked_pwm": 0.0,
  "status": "testnet",
  "sub_domain": "Underwater acoustic imaging",
  "title": "Active Sonar \u2014 underwater acoustic imaging"
}

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