Does the overflow twin's lead over ARX survive refitting on a real two-tank rig? A 0.13 V gap in 100% of refits with 87.5% of the training data, but 0.07 V and 84 to 90% of refits with 50 to 75%

What it found

Adds fit variance to free-tankci. Refits the 8-parameter overflow twin and linear ARX 4/4 on 100 random contiguous windows of the real Cascaded Tanks training trace (Schoukens et al. 2016) at three window lengths and scores each on the fixed test trace as in free-tanktwin. With 896 of 1024 samples the twin's test RMSE is 0.518 V (sd 0.012) against 0.651 V (sd 0.004) for ARX, a gap of 0.133 V in all 100 refits. With 768 samples the gap is 0.066 V (2.5 to 97.5%: −0.004 to 0.169) and the twin wins 90%; with 512 it is 0.070 V and 84%. The twin's advantage therefore depends on the training trace covering the operating range. Windows overlap and shrinking them confounds fit variance with less information, so only the longest window approximates the same data refitted; the optimiser start is fixed. All data are measured; no input is invented.

A figure from its own output

Paper, code and results

• README and method
• Experiments and results
• Tests

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Proper scoring & elicitation28Effort & peer prediction9Verification games & slashing19Detection & tolerances14Markets as routers13Prediction-market design9Paying contributors8Decentralised training systems23Digital twins & sim-to-real164LLM chip design loops40Robot manufacturing loops53Ambient AI assistant46Self-replicating manufacturing34Simulation-first design64Engineered clothing45Task-specific AI accelerators40Algorithmic chip-design loops42Open-source purpose-built robots44The software-engineering loop43Adversarial human imitation41Open-source residential construction41Autonomous multi-angle capture34Sensing, imaging and 3D31Energy supply and dense energy storage39Robot societies among people31Agentic co-design of low-cost robots27Laundry-hanging robots25Machine learning on qualitative data23Robots on the building site27Civilizations & group psychology1History & human sciences1

Produced with AI assistance (Claude). Results are from the code in this repository and are simulated or stylised unless the abstract says otherwise; nothing here implies affiliation with or endorsement by any lab, researcher or company cited. MIT licensed.