compute-methods
Environment-verified friction sheets for field-standard computational tools (Rydberg pair interactions, QEC circuits, qLDPC decoding, code distance, atom…
Verifier-in-the-loop CONSTRUCTION of quantum error-correcting codes with transversal non-Clifford gates (CCZ/T). Applies whenever the project goal is a new or better code/construction — INCLUDING search-phrased goals ("find codes beating X"), where the construct-loop (propose
$ npx -y skills add Muuuun/luxas --skill qec-construct --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/qec-constructContext preview
The summary Claude sees to decide when to auto-load this skill.
Verifier-in-the-loop CONSTRUCTION of quantum error-correcting codes with transversal non-Clifford gates (CCZ/T). Applies whenever the project goal is a new or better code/construction — INCLUDING search-phrased goals ("find codes beating X"), where the construct-loop (propose
name: qec-construct
description: Verifier-in-the-loop CONSTRUCTION of quantum error-correcting codes with transversal non-Clifford gates (CCZ/T). Applies whenever the project goal is a new or better code/construction — INCLUDING search-phrased goals ("find codes beating X"), where the construct-loop (propose algebraic rule → qverify → debug) is the REQUIRED mode, replacing blind random/grid sampling (empirically caps far below frontier). Gate certification is currently abelian/CCZ only, validated against the 11 Menon codes; CSS + distance checks are general. Brain, do not run this yourself — forward this SKILL.md path into every code-construction experiment spawn task; experiment/tool_impl run the loop.**Applies when** RESEARCH.md's goal is a new or improved QEC code / code family / transversal-gate construction — construct, invent, design, discover, improve distance/FOM, and search-phrased variants ("find codes beating X") equally.
**Does NOT apply** to magic-state cultivation, lattice surgery, decoder, or imaging projects: the gate check is abelian/CCZ-only and those are out of scope regardless of wiring.
**Brain's only two obligations** (do not run the loop yourself): 1. Read this file BEFORE writing notes/plan.md. 2. Every code-construction/code-search experiment spawn task MUST (a) include the literal path `skills/qec-construct/SKILL.md` with the instruction to read it in the Design phase and wrap `scripts/qverify` as a tool, and (b) frame the experiment as a construct-loop (propose a parametrized ALGEBRAIC construction → qverify → debug the failure), never as random/grid sampling over supports — sampling is the mode that capped at FOM ~10.4 vs frontier 45.5.
Broad/random/hill-climb search over code supports is a known dead end for this problem (empirically caps far below the frontier; the good codes are rare isolated optima). Your job is to **propose a parametrized ALGEBRAIC construction** — a group + a generating rule for the supports + (for a new gate) the cup-product / Leibniz conditions — and **debug it against the sound verifier**, not to sample points and hope.
If you find yourself enumerating random supports, stop: that is the wrong mode.
Call it at high frequency. Input a construction spec (JSON), get a SOUND verdict — including **which condition failed**, so you can fix it.
echo '{"family":"abelian","group_shape":[3,4,5],
"supp_a":[[0,1,3],[0,3,0],[2,1,3],[2,3,1]],
"supp_b":[[1,1,4],[1,2,2],[2,1,1],[2,2,4]],
"supp_c":[[0,0,4],[2,0,1]],
"frontier_fom":14.4}' | scripts/qverifyWhat it checks, cheapest first:
1. Propose a construction (group + support-generating rule + preorientation). 2. `qverify` it (cheap). If `css` or `gate` fails → read which condition failed → **fix the construction** (this is the Menon-style derivation-debug; e.g. the naive cup-product conditions force d=2 — find the offset/structure that escapes it). 3. Keep the cheap screen as your fitness: iterate the construction rule to push `FOM_upper` up while keeping the gate valid. 4. On a promoted candidate, run `"exact":true` to certify.
A code counts as a **new frontier code** ONLY if a single `qverify` run shows: `css_valid` ✓, `gate.preserves_codespace`/`stcp_conditions_hold` ✓, `K_CCZ ≥ 1`, and `distance_exact.status == "optimal"` with `fom_exact` strictly above the frontier. **Estimated / biased-sampled / timed-out distances never certify a win.** If you report a win on anything less, it is a hallucination, not a result.
The abelian families are heavily optimized (you will mostly re-find Menon). The upside is the **under-explored non-abelian region** (`"family":"general"`, `"group":{"kind":"dihedral","n":..}` or `{"kind":"perm","generators":[..]}`). The CSS + distance + cheap-screen verifiers ARE general and sound for non-abelian. But two honest caveats: (1) the **non-abelian CCZ gate check is NOT yet implemented in qverify** — so a non-abelian code is CSS/distance-verified but cannot be gate-CERTIFIED here yet; implementing a group-agnostic direct-circuit coboundary-invariance check (validated against `verify_stcp` before ship) is the open next step. (2) Non-abelian is a **high-risk** region, not virgin territory: Tiew2026 already *derived* non-abelian weight-4 cup-product gate conditions, yet experts (Tiew, Menon) converged on abelian for deep reasons — the cup product is graded-commutative (abelian-aligned), and abelian gives Fourier/character analysis, analytic distance bounds, and hardware locality. Betting on non-abelian bets that their choice was driven by "harder to analyze" (which this skill's verifiers bypass) rather than "structurally worse" (which they don't).
This skill gives you a sound, cheap, debuggable verifier and the construct-don't- search discipline. It does **not** guarantee a better code — proposing the right construction is still the hard part. But it is the mac
An autonomous research colleague — from a question to a compiled manuscript, while you sleep.
Repo: Muuuun/luxas
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