2026-05-23 Perfect Machine Study Index

Purpose

This directory is the deeper study pass that sits beside the source map. Use it when the next implementation pass needs more than “where is the file?” and needs the reason a cut exists.

Documents

FileUse It For
Architecture RuminationSystem ownership, current machine critique, coherent next cuts.
Optimization LedgerHot loop risks, low-level implementation options, micro-optimization candidates.
ReferencesResearch links for chirplets, CSS/LoRa, GCC-PHAT, D3D12/FFT/GPU compute.
Current Hotspot AuditStatic audit of likely runtime allocation/scan/driver-pressure hotspots.
Implementation RoadmapPhase plan, invariants, proofs, and benchmark harnesses.
Questions And HypothesesOpen questions and falsifiable hypotheses by domain.
Reading GuideTask-oriented route through the study docs and samples.
Data DictionaryData object definitions for streams, samples, chirp anchors, clock fits, calibration paths, reports, and Fensalir constraints.
Volumetric Audio FieldSound-field reconstruction decomposition and first practical audio target.
Acoustic Field ModelsField reconstruction models and the first honest acoustic source proof.
Chirplet Transform Deep DiveControlled chirp receiver versus generic chirplet transform.
Decoder Architecture OptionsActive receiver implementation options and promotion criteria.
Distributed Receiver SpecRaven/phone receiver shape for self-locating remote sensors using codebook and schedule state.
Visual Fusion 4DGS StudySensor fusion and realtime Gaussian splatting architecture study.
Open Implementation CatalogImplementation families to study before inventing local machinery.
Prior Research SynthesisDistillation of the older chirplet, adaptive sync, ambisonic, splatting, calibration, and visual archives.
Research Claims DigestClaim-level digest of external literature and how it steers Mimir.
Fensalir Integration MapContract-level cut between Mimir runtime truth and Fensalir GPU/render ownership.
Native Boundary MapNative/managed/Fensalir ownership boundaries for ASIO, cameras, reservoir, and GPU payloads.
Option MatrixImplementation alternatives, failure modes, and deciding proofs for the major subsystems.
Benchmark PlanMeasurement plan for audio sync, acoustic field, camera capture, Fensalir lowering, and splat fusion.
Calibration Session SpecCommand/session shape for learning and validating real output/mic path models.
Low-Level Implementation NotesConcrete memory layout, SIMD/GPU, ASIO, camera, and instrumentation notes.
Microsecond Sync MathTiming math for sample period, bandwidth, SNR, subsample delay, and acoustic distance.
State Machine InvariantsOwnership limits for runtime, hub, buffers, decoders, calibration, DSP, capture, Fensalir, network, and OBS.
Failure Mode LedgerFailure modes and coherent fixes across active witness, passive sync, actuator, camera, fusion, and network paths.
Hot Path PseudocodeCode-shaped intended hot paths for streaming decode, calibration weighting, actuator, native rings, camera rings, and Fensalir lowering.
GlossaryShort definitions for the synchronization, acoustic, visual, and reservoir terms used across the study.
sample-code-index.jsonMachine-readable index for sample sketches.
Sample Implementation SketchesIndex of sample implementation sketches.

Sample Code

SampleFuture Production TargetQuestion It Answers
samples/StreamingChirpBinDecoderSketch.csMimirChirpBinStreamingDecoder or equivalent runtime classWhat state removes full-window rescans?
samples/Avx2DechirpGoertzelSketch.cppNative CPU scorer for chirp-bin candidatesWhat does SIMD dechirp/bin scoring look like?
samples/BatchedChirpScoreAbiSketch.hNative scorer ABIWhat batch boundary avoids per-candidate managed/native overhead?
samples/ChirpBinScore.compute.hlslFensalir/D3D12 compute scorerHow would batched candidate/bin scoring map to GPU?
samples/FarrowFractionalDelaySketch.cppFaust/native DSP actuatorWhat is the smallest fractional delay proof?
samples/SpscAudioBlockRingSketch.cppNative capture worker handoffWhat shape should low-jitter audio block transfer take?
samples/CalibrationWeightedChirpLikelihoodSketch.csPhysical-path active decoderWhere does calibration enter symbol likelihood?
samples/SroPllAsrcControllerSketch.cppDSP actuator controlHow does delay/SRO state become a resampler command?
samples/GaussianSplatClaimUpdate.compute.hlslFensalir visual fusionWhat is the smallest live splat-claim compute shape?
samples/AquariumGpuSensorFrameBridgeSketch.csMimir-to-Fensalir visual loweringHow should runtime video observations become Fensalir sensor frames?
samples/AcousticConstraintLoweringSketch.csMimir-to-Fensalir acoustic loweringHow should decoded anchors/geometry become acoustic constraints?
samples/TemporalEvidenceCandidateSketch.csShared temporal evidence candidatesHow can Mimir lower candidates without owning Fensalir tracks?
samples/SrpPhatGridSketch.cppAcoustic source localizationWhat is the smallest TDOA/SRP-PHAT-style grid scoring proof?

Best Next Implementation Sequence

  1. Build a streaming chirp-bin decoder state object beside the current analyzer, but keep the old analyzer as proof oracle until outputs match.
  2. Load a real physical mic calibration model and compare weighted versus unweighted symbol likelihood on stored Scarlett captures.
  3. Emit reduced reliable-bin codebook from the physical model and measure meatspace anchor rate.
  4. Add native/Faust actuator proof using logged MimirAudioSynchronizationState before touching live program output.
  5. Port one direct camera path into IMimirVideoCaptureDriverSource; Leap first if timing/depth value wins, PS3 Eye first if raw driver throughput is the faster proof.

Index Terms

  • active sync
  • ASIO
  • AVX2
  • chirp-bin
  • chirplet
  • codebook adaptation
  • dechirp
  • D3D12 compute
  • Farrow fractional delay
  • Faust actuator
  • GCC-PHAT
  • group delay
  • LoRa CSS
  • native reservoir
  • Fensalir
  • Gaussian splatting
  • passive sync
  • Raven
  • response/confusion matrix
  • sample-rate offset
  • SPSC ring
  • Starfire
  • streaming decoder
  • volumetric audio
  • volumetric visual fusion