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Merge pull request #509 from AdaWorldAPI/claude/jirak-math-theorems-harvest-rfii13
perturbation-sim: resilience arc — meta-hop → buffer → exploration → fail-first scorecard
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crates/perturbation-sim/COUNTRY_STUDY.md

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crates/perturbation-sim/Cargo.toml

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@@ -60,3 +60,35 @@ path = "examples/reinforce.rs"
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[[example]]
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name = "hhtl_resident"
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path = "examples/hhtl_resident.rs"
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[[example]]
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name = "meta_hops"
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path = "examples/meta_hops.rs"
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[[example]]
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name = "validate_mediators"
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path = "examples/validate_mediators.rs"
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[[example]]
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name = "rolling_floor"
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path = "examples/rolling_floor.rs"
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[[example]]
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name = "modifier_validity"
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path = "examples/modifier_validity.rs"
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[[example]]
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name = "resilience"
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path = "examples/resilience.rs"
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[[example]]
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name = "buffer"
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path = "examples/buffer.rs"
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[[example]]
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name = "explore"
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path = "examples/explore.rs"
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[[example]]
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name = "scorecard"
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path = "examples/scorecard.rs"

crates/perturbation-sim/METHODS.md

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@@ -365,6 +365,52 @@ Reserve **electricity-specific** encoding for the **raw physical layer** (AC
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256-palette lossy, ±½ bucket — fine for a live screen/stream; compute exact
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stats on raw. `turbovec` is coarse — retrieval, not values.)
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## 11. Why the pyramid is a *computation* substrate: witness arc as a standing wave
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The perturbation pyramid is not only an outage model — it is the **computation
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kernel** for evaluating a Mailbox-SoA **witness arc** as a *standing wave* instead
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of by *pointer chasing*. This is the bridge the operator named ("use Mailbox SoA
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and witness > pointer chasing as a standing wave, but it needs the perturbation
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pyramid for computation"), and it lands on architecture that already exists in
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`lance-graph-contract`.
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**The two views of the same arc** (already documented in
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`contract::witness_table` and `contract::soa_view`):
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- **Particle view (pointer chasing).** The `CausalEdge64` W-slot → witness chain
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is a Markov #1 reference arc; walking it means dereferencing one witness per hop
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across the SPO store — `O(hops)` dependent loads, each a cache miss. This is the
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*discrete, addressable, exact* witness pointer (`witness_table.rs`: "the chain of
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W-references across edges forms a Markov chain … walked backwards without
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dereferencing the full SPO store on every hop"; `soa_view.rs`: "the *particle*").
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- **Wave view (standing wave).** The same arc, evaluated *all at once* as a bipolar
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**interference field** over the HHTL tiers — the windowed/resonance reading
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(`soa_view.rs`: "the windowed … *wave*"). No per-hop dereference: the field is a
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function of the address tree, not of a pointer walk.
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**The pyramid is what makes the wave computable** — and it is exactly
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`timing::meta_cascade_phase` (§4.7 of `PAPER.md`):
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| Standing-wave ingredient | Pyramid mechanism (this crate) | OGAR canon |
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|---|---|---|
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| phase (±1) composes between levels | `phase_{i+1} = phaseᵢ · sign` (XOR/multiply) | "sign side = `vsa_bind` = XOR" |
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| magnitude bundles into the field | `field_k = Σ phaseᵢ·magnitudeᵢ` (running sum) | "magnitude side = `vsa_bundle` = add" |
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| the field is the Walsh–Hadamard of the tree | `sketch::fwht` / `walsh_pyramid_energy` (`ndarray::simd::wht_f32`) | "Bipolar-phase pyramid — Walsh-Hadamard on VSA" |
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| tier = one meta-hop, `O(tiers)` not `O(hops)` | 4 HHTL tiers, `tier = level >> 2` | "perturbation pyramid for computation" |
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So the witness arc that the particle view walks in `O(hops)` dependent loads, the
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wave view reads in `O(tiers)` (≤ 4) tier lookups — *because the deterministic
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bipolar phase is generated from the address, never stored* (OGAR "DETERMINISTIC
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PHASE"). The standing wave is the witness arc; the perturbation pyramid is its
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evaluator; the SoA columns (`FingerprintColumns`/`EdgeColumn`) are its backing
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store. **Scope (honest):** the bridge is *structural*`perturbation-sim`
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demonstrates the pyramid/phase/inertia field on power grids; wiring it as the
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actual `witness`-arc evaluator in the contract is a separate, gated step (the
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witness/SoA types are the cognitive spine — additive only, behind the iron rules).
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It is recorded here as the computation-substrate connection, not yet as shipped
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contract code. CONJECTURE [H].
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## Anti-dilution table — the distinctions to never collapse
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| Do NOT conflate | Because |

crates/perturbation-sim/PAPER.md

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//! The buffer axis on the real ES core — impulse storage before yield, and the
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//! proof it is INDEPENDENT of the resistive (Kirchhoff) axis the modifier was
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//! confounded with.
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//!
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//! Per Cheeger compartment we read two resilience axes. STEADY / resistive: λ₂,
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//! Kf, mean pairwise resistance (topology) — §4.10. TRANSIENT / buffer: the
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//! sudden imbalance the compartment's inertia absorbs before a Ketchup yield
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//! (storage). Size-normalized, mean-buffer (per node = mean inertia,
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//! topology-FREE) and mean-resistance (per pair, topology) are independent by
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//! construction — the deconfound: `1/λ₂` was the dominant Kirchhoff term, the
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//! buffer is not.
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//!
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//! Then the Kugelstoßpendel demo: a sudden per-node impulse is metered against
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//! each compartment's buffer/node (mean inertia headroom); the thinnest-buffer
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//! compartment yields first (the Ketchup collapse) even when it is resistively
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//! healthy (high λ₂) — the low-inertia failure mode a resistance-only screen misses.
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//!
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//! Inertia `H` is NOT in the PyPSA topology, so it is an ILLUSTRATIVE per-node
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//! scenario field here (deterministic, topology-independent, a ~third of buses
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//! marked renewable-rich = low inertia). The *structure* (buffer ⊥ connectivity,
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//! low-buffer-yields-first) holds for any real `H`; feed measured inertia to calibrate.
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//!
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//! Run: cargo run --release --manifest-path crates/perturbation-sim/Cargo.toml \
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//! --example buffer -- /tmp/pypsa/buses.csv /tmp/pypsa/lines.csv ES
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use perturbation_sim::{
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cheeger_sweep, compartment_buffer, ketchup_yield, spearman, symmetric_eigen, Edge, Grid,
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Resilience,
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};
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use std::collections::HashMap;
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fn synthetic(rows: usize, cols: usize) -> Grid {
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let id = |r: usize, c: usize| r * cols + c;
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let mut e = Vec::new();
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for r in 0..rows {
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for c in 0..cols {
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if c + 1 < cols {
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e.push(Edge::new(id(r, c), id(r, c + 1), 1.0, 1.0));
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}
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if r + 1 < rows {
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e.push(Edge::new(id(r, c), id(r + 1, c), 1.0, 1.0));
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}
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}
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}
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Grid::new(rows * cols, e)
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}
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fn induced(grid: &Grid, members: &[usize]) -> Grid {
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let mut remap = HashMap::new();
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for (i, &m) in members.iter().enumerate() {
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remap.insert(m, i);
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}
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let edges = grid
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.edges
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.iter()
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.filter_map(|e| match (remap.get(&e.from), remap.get(&e.to)) {
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(Some(&a), Some(&b)) => Some(Edge::new(a, b, e.susceptance, e.limit)),
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_ => None,
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})
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.collect();
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Grid::new(members.len(), edges)
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}
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fn bisect(grid: &Grid, members: &[usize]) -> Option<(Vec<usize>, Vec<usize>)> {
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if members.len() < 6 {
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return None;
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}
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let sub = induced(grid, members);
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let c = cheeger_sweep(&sub, &vec![true; sub.edges.len()]);
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let (mut a, mut b) = (Vec::new(), Vec::new());
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for (i, &m) in members.iter().enumerate() {
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if c.partition[i] {
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a.push(m);
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} else {
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b.push(m);
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}
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}
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if a.is_empty() || b.is_empty() {
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None
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} else {
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Some((a, b))
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}
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}
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/// Deterministic topology-independent inertia field (ILLUSTRATIVE, see header):
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/// most buses synchronous H∈[3,7] s; ~⅓ marked renewable-rich at H=1 s.
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fn inertia_scenario(n: usize) -> Vec<f64> {
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(0..n)
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.map(|i| {
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let mut z = (i as u64).wrapping_mul(0x9E37_79B9_7F4A_7C15);
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z = (z ^ (z >> 30)).wrapping_mul(0xBF58_476D_1CE4_E5B9);
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let u = ((z ^ (z >> 31)) >> 11) as f64 / (1u64 << 53) as f64;
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if u < 0.33 {
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1.0 // renewable-rich: low inertia, thin buffer
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} else {
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3.0 + 4.0 * u // synchronous: H∈[3,7]
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}
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})
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.collect()
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}
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fn main() {
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let args: Vec<String> = std::env::args().collect();
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let grid = if args.len() >= 3 {
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let buses = std::fs::read_to_string(&args[1]).expect("buses.csv");
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let lines = std::fs::read_to_string(&args[2]).expect("lines.csv");
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let cc = args.get(3).map(|s| s.as_str()).unwrap_or("ES");
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let imp = perturbation_sim::from_pypsa_csv(&buses, &lines, Some(cc))
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.expect("import")
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.largest_component();
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println!(
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"grid: {cc} PyPSA core — {} buses, {} lines",
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imp.grid.n,
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imp.grid.edges.len()
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);
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imp.grid
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} else {
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let g = synthetic(10, 10);
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println!("grid: synthetic 10×10 — {} buses", g.n);
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g
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};
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let n = grid.n;
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let df_band = 0.2; // Hz protection band
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let inertia = inertia_scenario(n);
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// Depth-3 Cheeger compartments.
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let mut basins: Vec<Vec<usize>> = vec![(0..n).collect()];
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for _ in 0..3 {
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let mut next = Vec::new();
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for b in &basins {
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match bisect(&grid, b) {
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Some((x, y)) => {
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next.push(x);
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next.push(y);
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}
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None => next.push(b.clone()),
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}
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}
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basins = next;
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}
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let comps: Vec<&Vec<usize>> = basins
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.iter()
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.filter(|b| b.len() >= 4 && induced(&grid, b).edges.len() >= 3)
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.collect();
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// Per compartment: resistive axis (λ₂, mean R) + buffer axis (total & per-node).
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println!(
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"\n== Two resilience axes per compartment ({} compartments) ==",
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comps.len()
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);
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println!(
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" {:>4} {:>6} {:>12} {:>12} {:>12} {:>12}",
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"comp", "nodes", "λ₂ (steady)", "mean R", "buffer Σ", "buffer/node"
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);
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let (mut mean_r, mut mean_buf, mut lam2s): (Vec<f64>, Vec<f64>, Vec<f64>) =
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(Vec::new(), Vec::new(), Vec::new());
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for (ci, b) in comps.iter().enumerate() {
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let sub = induced(&grid, b);
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let cert = Resilience::from_eigenvalues(
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&symmetric_eigen(&sub.laplacian_of(&vec![true; sub.edges.len()]), sub.n).values,
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1e-9,
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);
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let h_local: Vec<f64> = b.iter().map(|&node| inertia[node]).collect();
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let buf = compartment_buffer(&h_local, df_band);
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let buf_per_node = buf / b.len() as f64;
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println!(
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" {:>4} {:>6} {:>12.3e} {:>12.3e} {:>12.3e} {:>12.4}",
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ci,
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b.len(),
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cert.lambda2,
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cert.mean_resistance(),
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buf,
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buf_per_node
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);
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mean_r.push(cert.mean_resistance());
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mean_buf.push(buf_per_node);
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lam2s.push(cert.lambda2);
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}
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// Deconfound: size-normalized buffer (= mean inertia, topology-free) vs mean
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// resistance (topology). Report with Jirak |ρ|√n — at n compartments these are
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// not significant, consistent with the structural independence.
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if comps.len() >= 3 {
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let nn = comps.len() as f64;
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let rho_rb = spearman(&mean_r, &mean_buf);
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let rho_lb = spearman(&lam2s, &mean_buf);
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println!("\n== Deconfound: is the buffer independent of the resistive axis? ==");
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println!(
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" Spearman(mean resistance, buffer/node) = {rho_rb:+.3} (|ρ|√n = {:.2})",
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rho_rb.abs() * nn.sqrt()
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);
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println!(
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" Spearman(λ₂, buffer/node) = {rho_lb:+.3} (|ρ|√n = {:.2})",
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rho_lb.abs() * nn.sqrt()
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);
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println!(
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" → both below the ~2 Jirak floor ⇒ no significant coupling: buffer (storage,\n \
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set by inertia) is a SEPARATE axis from connectivity (λ₂/Kirchhoff). Contrast\n \
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the `1/λ₂`↔Kirchhoff confound, which was near +1.0 (definitional). buffer/node\n \
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is mean inertia — topology-free by construction; any residual ρ is n={} noise.",
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comps.len()
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);
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}
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// Kugelstoßpendel: a sudden impulse hits each node of a compartment; the
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// compartment yields where its PER-NODE buffer (mean inertia headroom) is
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// thinnest. Per-node buffer varies independently of λ₂, so the compartment
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// that yields need not be the resistively-weakest — that is the point.
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let impulse = 0.032; // per-node strike, fraction of nominal (illustrative)
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println!(
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"\n== Kugelstoßpendel: per-node impulse {impulse} vs each compartment's buffer/node =="
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);
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// (compartment, per-node buffer, that compartment's λ₂), sorted thinnest first.
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let mut weakest: Vec<(usize, f64, f64)> = (0..comps.len())
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.map(|ci| (ci, mean_buf[ci], lam2s[ci]))
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.collect();
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weakest.sort_by(|a, b| a.1.partial_cmp(&b.1).unwrap());
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let mut first_yield = None;
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for (ci, buf, l2) in &weakest {
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let y = ketchup_yield(impulse, *buf);
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if y.yielded && first_yield.is_none() {
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first_yield = Some((*ci, *l2));
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}
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println!(
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" comp {ci:>2}: buffer/node={buf:.4} λ₂={l2:.2e} headroom={:+.0}% {}",
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100.0 * y.headroom,
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if y.yielded {
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"YIELDS → Ketchup seed"
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} else {
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"holds (elastic)"
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}
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);
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}
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match first_yield {
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Some((ci, l2)) => {
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let resistively_healthy = lam2s.iter().filter(|&&x| x < l2).count();
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println!(
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"\n → compartment {ci} yields FIRST (thinnest local buffer) at λ₂={l2:.2e},\n \
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which is MORE connected than {resistively_healthy}/{} compartments — a\n \
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resistance-only screen ranks it safe, the buffer axis flags it. That is the\n \
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low-inertia failure mode (renewable-rich node, 28 Apr 2025).",
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comps.len()
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);
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}
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None => println!("\n → all weakest nodes hold this impulse elastically (raise the strike to find the yield)."),
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}
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println!(
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"\n buffer = transient storage (inertia·band/f₀, the swing buffer); the yield is\n \
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the sharp non-Newtonian threshold. Inertia field ILLUSTRATIVE — feed real per-bus\n \
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H to calibrate; impulse magnitude should come from the flow redistribution (LODF)."
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);
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}

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