# Gate Q, choose set: policy **net2** paired against Taylor's full plain policy, seeds 60000..61023

**Result: net2 minus full = +0.005367400 edge, se 0.016095032, n = 1024 (all 1,024 choose seeds completed).** The fixed-net 2-pass policy as shipped in net-1 is statistically indistinguishable from the full `pol_mid.json` tables on Taylor's replica: the difference is a third of its standard error, and net2 is ahead on 513 seeds and behind on 511. Mean edge: full 529.061693, net2 529.067061. Credit: Taylor (gtmcknight) for the solved policy, tables, filter and replica (amm-sim `4812a6382311624e1506aca131ca35c378f930d9`, `research/solved`). All numbers are replica measurements on the choose set; nothing here ran on the Rust engine, and no engine seed was consumed.

Supplementary (same seeds, same full arm, not the item's named policy): the port-2 filter approximation alone (**agg**, `PortReal` with the full tables) minus full = -0.045195795, se 0.013343417, n = 1024. Details in its own section.

## Gate P (before any scoring)

Unmodified `python3 -I gates.py` in `research/solved` at the pinned commit (`git status` clean, no tracked file changed), system `python3` 3.12.3, no third-party packages:

```text
seed   perfect-info      gaussian+plain    gaussian+qm       lattice+qm
10000  448.261189  443.455598  443.522608  443.663520
10001  576.779199  571.463409  571.623551  571.977293
10002  531.886497  525.168028  525.865859  526.411631
```

This equals the README's gate block digit for digit (gaussian+plain 443.455598 / 571.463409 / 525.168028).

## Policies

- **FULL arm.** `real.RealPolicy(real.load('pol_mid.json'), {'soft': 1})` driven by `replica2.run(seed, policy)`, edge = `['edge']`. Taylor's files, unmodified, run with `python3 -I` and the standard library only.
- **net2 arm (the item's policy).** net-1's `netref.Net2()`: `NetPolicy(mode=2)`, which subclasses port-3's `standalone.Coarse` (the Gaussian plain filter: per-silent-step truncation, cap 12, `soft=1` mixture) and replaces only `_fees`. For each callback it clamps w to [-800, 800] bps and R to [-30, 30] (phase 0) or [-800, 800] (phases 1, 2), rounds `16384*[w/100, R/100, phase]` to nearest-even integers, and evaluates the fixed-net 4-32-32-1 int16 MLP (shifts 12, 10, 12, floor via arithmetic shift, ReLU) once at (w, R, phase) for the ask offset and once at (-w, -R, phase) for the bid offset. Fees: `1-exp(-(a-w)e-4)` if `a>w` else 0, `1-exp(-(b+w)e-4)` if `b>-w` else 0, capped at 10 %. Weights come from `payload.bin` loaded by `netref.load_payload`. `netref.py`, `standalone.py` and the payload are used exactly as published; nothing in them was edited.
- **agg arm (supplementary).** port-2's `reference.PortReal(real.load('pol_mid.json'), {'soft': 1})`: Taylor's `RealPolicy` with the full tables, where `reference.py`'s module-level hook on `real.trunc` makes the silent-step loop accumulate `min(dt-1, 12)` variance increments and truncate once at the end instead of once per step. `reference.py` is used verbatim; to let it import, port-2's `Strategy.sol` was placed where it expects it and Taylor's `research/solved` was copied to `taylor/research/solved` beside it. `CompressedReal` and the TABLE lookup in that file are not used.

Each seed was run once per arm, each arm on its own trajectory (the policy's fees change the path), paired by seed. The full arm was computed inside each run; its 1,024 edges are byte-identical between the net2 run (where `reference.py` was never imported) and the agg run (where its `real.trunc` hook was installed), which confirms the hook is inert for `RealPolicy` and the replica is deterministic per seed.

## Checks before scoring

- `payload.bin`: 2,730 bytes, sha256 `9727ecc8acf6d31732793d1836c60cd637133b800bbe61b19098bfee7d17e0f6`, equal to the hash fixed-net and net-1 state.
- `pol_mid.json`: sha256 `efbb5ee102db4d312f64565d9bf7232b6becbe02b624164f744a402bbbf2983b`, equal to the hash fixed-net states.
- fixed-net's `decode_fixed_net` (run under a scratch venv with numpy 2.5.4, used for this check only) decodes the payload to the canonical JSON sha256 `068ee67f3219df2aaf9ab9f8e93d29dc79ad313afa17771d818f062609a1cec6`, the value fixed-net publishes. Against it, `netref.net_grid(i, j, ph)` was compared on **every** cell of the six tables (35,631 A cells plus their B reflections): max difference 0.0. `netref.net_bps` at integer grid coordinates equals `net_grid` (max difference 0.0), and `net_bps(0,0,0)` = 28.74755859375 bps, as net-1 states. Output of the check:

```text
payload bytes 2730 sha256 9727ecc8acf6d31732793d1836c60cd637133b800bbe61b19098bfee7d17e0f6
decoder canonical json bytes 1134669 sha256 068ee67f3219df2aaf9ab9f8e93d29dc79ad313afa17771d818f062609a1cec6
W2L equal to netref.RG: True ; H 32 ; shifts [12, 10, 12]
all 35631 grid cells: max |netref.net_grid - decoder A| = 0.0; max |reflected net_grid - decoder B| = 0.0; 7s
max |net_bps(grid coords) - net_grid| = 0.0
net_bps(0,0,0) = 28.74755859375 bps (net-1 states 28.74755859375)
```

- Probe pairs: seeds 60000 and 60001 give full-net2 = 0.2058 and 0.5312, equal to the two pairs net-1 reported (0.2058 and 0.5312).

## Paired result: net2 minus full, seeds 60000..61023

| statistic | value |
|---|---:|
| n completed | 1024 of 1,024 (none missing, no seed twice) |
| mean_diff (net2 - full) | +0.005367400 |
| sample sd of the differences | 0.515041009 |
| se = sd / sqrt(n) | 0.016095032 |
| mean edge, full arm | 529.061693433 |
| mean edge, net2 arm | 529.067060833 |
| net2 ahead / behind / tied | 513 / 511 / 0 |
| worst5 (seed, diff) | (60750, -2.363654), (60809, -1.978941), (60304, -1.950315), (61012, -1.532004), (60365, -1.505508) |
| best5 (seed, diff) | (60653, +5.160671), (60036, +1.897821), (60023, +1.461283), (61021, +1.461130), (60376, +1.456479) |

Reading: on the choose set the continuous 2-pass evaluation loses nothing measurable against the full tables (95 % interval about -0.026 to +0.037). This is the figure net-1 left unmeasured. It is a choose-set number; the report set 10000..12047 is a separate item and was not run here.

## Supplementary: agg minus full, same seeds

| statistic | value |
|---|---:|
| n completed | 1024 of 1,024 |
| mean_diff (agg - full) | -0.045195795 |
| sample sd / se | 0.426989359 / 0.013343417 |
| mean edge, full / agg | 529.061693433 / 529.016497639 |
| agg ahead / behind | 482 / 542 |
| worst5 (seed, diff) | (60409, -1.587160), (60653, -1.518656), (60055, -1.430361), (60794, -1.332243), (60333, -1.274773) |
| best5 (seed, diff) | (60680, +2.174120), (60066, +2.108840), (61021, +1.537892), (60671, +1.121858), (60082, +1.048141) |

So the one-truncation filter change alone costs about 0.045 edge (about 3.4 se) on these seeds. Its per-seed CSV (sha256 in the table below) is not reproduced here because the result file would exceed 48,000 bytes with both; the net2 CSV, the item's policy, is reproduced in full.

## Timing

| run | procs | chunks | total wall | wall per seed pair | cpu per seed pair (full + policy) | slowest pair |
|---|---:|---:|---:|---:|---:|---:|
| net2 vs full | 8 | 16 x 64 seeds | 459.2 s | 0.448 s | 3.449 s (0.146 + 3.303) | 6.76 s |
| agg vs full | 2 | 16 x 64 seeds | 110.3 s | 0.108 s | 0.212 s (0.103 + 0.109) | 0.37 s |

Longest single command: 33.4 s (one 64-seed chunk). The pure-Python MLP (two forward passes per callback, about 10,000 callbacks a run) is the whole cost of the net2 arm. 8 CPUs, system Python 3.12.3.

## Files used (sha256)

| file | sha256 |
|---|---|
| `research/solved/gates.py` (Taylor, unmodified) | `603280c1f595ca163ffaf2ba1ebdc7945fdb08dabae67fc53c922d39e1cce604` |
| `research/solved/replica2.py` (Taylor, unmodified) | `6e37b4e61e1ffa5ffb1e43912ddb8659105989aa986eb48fcd1d7608f8dca685` |
| `research/solved/real.py` (Taylor, unmodified; FULL arm policy) | `1305b5333731c046c3e6736cc2578eff4635c88132a39c22f5780d78aef2c81e` |
| `research/solved/evalpol.py` (Taylor, unmodified; `load`, `DPPolicy`) | `6e67667bfed7798bdd3384652a6efc6ba0b1fce653740d0f9af2bcbcb8e6a27c` |
| `research/solved/pol_mid.json` (Taylor, full plain tables) | `efbb5ee102db4d312f64565d9bf7232b6becbe02b624164f744a402bbbf2983b` |
| `netref.py` (net-1 artifact, verbatim; class `Net2`, mode 2) | `4925929cda219f729eb3f7baa7a42fee5cd89da02976f29845c18e9fcd9c111e` |
| `payload.bin` (fixed-net Data block, base64-decoded; 2,730 bytes) | `9727ecc8acf6d31732793d1836c60cd637133b800bbe61b19098bfee7d17e0f6` |
| `standalone.py` (port-3 artifact, verbatim; class `Coarse` filter) | `7d6d59855b4f2b88930d7e883be68999b424f5f48929ec867977968df04a30b7` |
| `reference.py` (port-2 artifact, verbatim; class `PortReal`, supplementary agg arm) | `6e617a1700fac6214005277e21fc709fff1418b50f51b88a2caff3876311699c` |
| port-2 `Strategy.sol` (port-2 artifact, verbatim; only read by `reference.py` at import) | `7e2d9c157a7725c2875eea31e5741938fb9eafef5a3442710573f1b1a87faf17` |
| `decoder.py` (fixed-net artifact `decode_fixed_net`, verbatim; cross-check only) | `079a0a8d125113fa3def17889d64bed56c6b7db729b5bb72be391eb4db8d3be9` |
| `pair.py` (my driver, below) | `ad60d7f12919df0c1cf014800835d055966b22899bd244705924c29dd8ee9838` |
| `stats.py` (my statistics script) | `d18ca7c9b06d4d718526c32167c9830638e4955e3eb3e93fda56b2d5b9778c2c` |
| `check_decoder.py` (my decoder cross-check) | `b48dfa6d3d717bab896d114b4cd384152357d6aa6bef88e12b4bef491a7496a7` |
| `net2_choose.csv` (per-seed output, full precision; reproduced below rounded to 6 decimals) | `328c3fc026e3b38f995a44a9cbfbeab50c8c0c537310bcaecdc64bc8fdfdb58b` |
| `agg_choose.csv` (per-seed output of the supplementary agg arm, full precision; not reproduced, size) | `cc848c8747a4c10a9938f7daaa4f1a4f51b08a88834e129b17fec15140b6f6bb` |

Artifacts read, by sha256 id, all fetched from `https://api.imdnotdead.fun/artifacts/<id>` and verified to hash to their id: net-1 `66ed32a0fd17a43295542d22510b004a5323688a74b4321629ae875bb4592e55` (netref.py; Gate Q note), fixed-net `cc8778a3d8f1f86ffbfc77e971b5ed598b27fee68d61c338e8f3cb2057a363d0` (payload base64, decoder), port-3 `0dbcc10af41b3c3467ff0d9b9cb64c81328fcf18295f9be06b2d81bb98874067` (standalone.py), port-2 `e8c967d6358da0fd53117891357f19a1d684225bd71a5e302b6e299c85f1286c` (reference.py, Strategy.sol).

## Procedure

Layout under the scratch directory (deleted before submission, nothing in it is a deliverable): `repo/` = amm-sim clone at the pinned commit; `n1/netref.py`, `n1/payload.bin`; `p3/standalone.py` (netref imports it from `../p3`); `p2/reference.py` plus the two paths it needs; `fn/decoder.py`, `fn/check_decoder.py`; `gateq/pair.py`, `gateq/stats.py`. Commands, each under 8 minutes:

```sh
python3 -I gates.py                                   # in repo/research/solved: Gate P
venv/bin/python -I fn/check_decoder.py                # decoder cross-check (numpy only here)
python3 -I gateq/pair.py net2 <start> 64 gateq/net2_choose.csv 8   # 16 chunks, start = 60000, 60064, ... 60960
python3 -I gateq/pair.py agg  <start> 64 gateq/agg_choose.csv 2    # same 16 chunks
python3 -I gateq/stats.py gateq/net2_choose.csv 60000 1024
```

`pair.py` (driver): a `multiprocessing.Pool` whose initializer loads `pol_mid.json` and imports the policy module; each task runs the FULL arm and then the policy arm for one seed and returns `(seed, full, policy, t_full, t_policy)`; rows are appended to the CSV sorted by seed, seeds already in the CSV are skipped (resume), per-seed times go to `<csv>.times`. `stats.py` computes the paired statistics above from the CSV. Both were written for this item; their hashes are in the table.

```python
"""Gate Q driver: per-seed paired edges, FULL arm vs POLICY arm, on Taylor's (gtmcknight) replica.

usage: python3 -I pair.py <net2|agg> <start> <count> <csv> [nproc]

FULL arm:  real.RealPolicy(real.load('pol_mid.json'), {'soft': 1}) through replica2.run(seed, policy)
net2 arm:  net-1's netref.Net2() (fixed-net 2-pass MLP over port-3's standalone.Coarse filter)
agg arm:   port-2's reference.PortReal(real.load('pol_mid.json'), {'soft': 1}) (aggregated silent-step truncation)
Each seed is run once per arm, each arm on its own trajectory, paired by seed.
Rows (seed, full, policy) are appended to the CSV; seeds already present are skipped (resume).
Timing per seed is appended to <csv>.times (seed, t_full_s, t_policy_s).
"""
import sys, os, csv, time
from multiprocessing import Pool

B = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))          # scratch/
SOLVED = os.path.join(B, 'repo', 'research', 'solved')
sys.path.insert(0, SOLVED)
import replica2, real
POL = os.path.join(SOLVED, 'pol_mid.json')

KIND = None
T = None


def _init(kind):
    global KIND, T
    KIND = kind
    T = real.load(POL)
    if kind == 'net2':
        sys.path.insert(0, os.path.join(B, 'n1'))
        import netref  # noqa: F401  (imports port-3's standalone.Coarse from ../p3)
    elif kind == 'agg':
        sys.path.insert(0, os.path.join(B, 'p2'))
        import reference  # noqa: F401  (installs its real.trunc hook; inert unless PortReal is running)


def _policy():
    if KIND == 'net2':
        import netref
        return netref.Net2()
    if KIND == 'agg':
        import reference
        return reference.PortReal(T, {'soft': 1})
    raise SystemExit('unknown policy ' + str(KIND))


def work(seed):
    t0 = time.time()
    full = replica2.run(seed, real.RealPolicy(T, {'soft': 1}))['edge']
    t1 = time.time()
    pol = replica2.run(seed, _policy())['edge']
    t2 = time.time()
    return seed, full, pol, t1 - t0, t2 - t1


def done_seeds(path):
    if not os.path.exists(path):
        return set()
    with open(path) as f:
        return {int(r['seed']) for r in csv.DictReader(f)}


if __name__ == '__main__':
    kind, start, count, path = sys.argv[1], int(sys.argv[2]), int(sys.argv[3]), sys.argv[4]
    nproc = int(sys.argv[5]) if len(sys.argv) > 5 else 8
    have = done_seeds(path)
    todo = [s for s in range(start, start + count) if s not in have]
    new = not os.path.exists(path)
    t0 = time.time()
    with open(path, 'a', newline='') as f, open(path + '.times', 'a', newline='') as ft, Pool(nproc, _init, (kind,)) as pool:
        w = csv.writer(f); wt = csv.writer(ft)
        if new:
            w.writerow(['seed', 'full', kind]); f.flush()
        rows = []
        for seed, full, pol, tf, tp in pool.imap_unordered(work, todo, chunksize=1):
            rows.append((seed, full, pol, tf, tp))
        rows.sort()
        for seed, full, pol, tf, tp in rows:
            w.writerow([seed, repr(full), repr(pol)]); wt.writerow([seed, '%.3f' % tf, '%.3f' % tp])
    dt = time.time() - t0
    print(f'{kind}: {len(todo)} seeds {start}..{start+count-1} (skipped {count-len(todo)} already done) in {dt:.1f}s wall '
          f'= {dt/max(1,len(todo)):.2f}s/seed-pair wall with {nproc} procs; '
          f'cpu per pair {sum(r[3]+r[4] for r in rows)/max(1,len(rows)):.2f}s (full {sum(r[3] for r in rows)/max(1,len(rows)):.2f}, {kind} {sum(r[4] for r in rows)/max(1,len(rows)):.2f})', flush=True)
```

## Not done, and caveats

- The report set 10000..12047 was not scored; this item is the choose set only.
- Nothing ran on the Rust engine; no engine seed was used.
- The agg arm is supplementary. The item names net2 as its policy; agg was scored because the brief defines it alongside net2 and it costs about two minutes.
- The embedded CSV is rounded to 6 decimals; every statistic above was computed from the full-precision CSV (sha256 in the table). Recomputing from the rounded rows changes the mean by less than 1e-6.
- Only one candidate was scored for the item's policy, so nothing was "chosen" among alternatives; the choose-set figure is the deliverable.

## Per-seed CSV: net2 vs full (seed, full, net2), edges rounded to 6 decimals

```csv
seed,full,net2
60000,485.997849,485.792081
60001,489.639993,489.108791
60002,590.788660,590.480363
60003,589.328106,589.509943
60004,552.026454,553.387454
60005,622.074780,622.502941
60006,538.585011,537.963966
60007,447.561819,447.750733
60008,383.514185,383.928875
60009,467.754269,467.948509
60010,591.478434,591.390190
60011,448.402852,448.445738
60012,451.855763,452.360002
60013,483.946042,484.580165
60014,564.062673,563.834043
60015,491.348105,491.663185
60016,408.361946,408.333391
60017,592.114162,592.387170
60018,618.396030,617.451720
60019,512.729250,512.666003
60020,582.588794,582.976684
60021,367.385445,367.340880
60022,544.639100,544.522460
60023,706.281130,707.742414
60024,522.699975,522.964539
60025,705.045540,704.806943
60026,653.868483,653.844882
60027,608.409404,608.334603
60028,553.430717,552.786894
60029,623.253497,623.755252
60030,392.510156,392.363093
60031,668.576266,668.029389
60032,550.854749,550.885557
60033,670.569388,671.341397
60034,473.898130,474.431773
60035,617.127525,617.147303
60036,684.926411,686.824232
60037,549.332514,549.769088
60038,539.732764,539.503603
60039,538.008744,538.391989
60040,583.751737,583.591274
60041,531.467945,532.685482
60042,401.820117,401.437603
60043,541.794517,540.685307
60044,435.234851,435.192162
60045,598.562171,598.577743
60046,529.377009,528.776713
60047,487.372845,487.384594
60048,526.331825,526.162601
60049,446.961529,446.927850
60050,415.608561,415.384084
60051,411.981399,411.357103
60052,601.085709,600.951831
60053,463.117731,463.760639
60054,436.302818,436.986579
60055,538.817129,538.637563
60056,539.562679,539.220298
60057,578.019494,577.997862
60058,617.158756,617.780674
60059,417.974545,418.280350
60060,465.868324,465.249719
60061,372.383541,372.720860
60062,533.276668,533.301669
60063,393.670900,393.661806
60064,452.591409,452.573731
60065,559.244053,559.270305
60066,513.137719,513.610524
60067,579.825905,580.955026
60068,482.311901,483.442815
60069,522.734613,522.551780
60070,578.358370,578.900608
60071,488.399985,488.415820
60072,603.046674,603.474598
60073,570.280930,570.077567
60074,375.229345,374.822617
60075,497.598727,497.944405
60076,548.336389,548.832208
60077,426.684574,426.019056
60078,497.340413,496.829942
60079,481.320995,481.395194
60080,427.048410,426.780204
60081,599.935960,600.285833
60082,515.996295,516.098140
60083,570.177251,569.521460
60084,584.034371,583.052882
60085,533.459212,533.222999
60086,565.340042,565.767393
60087,706.353695,706.586525
60088,498.536546,499.345402
60089,503.673480,502.773867
60090,429.158546,429.494906
60091,591.459189,592.213376
60092,565.698699,565.989490
60093,452.616492,453.404678
60094,395.881136,396.451838
60095,603.170262,603.474906
60096,426.810589,427.506221
60097,473.938985,474.689085
60098,466.462871,466.339832
60099,433.031235,433.330153
60100,499.862323,499.109677
60101,580.986083,580.660344
60102,500.234794,500.249549
60103,591.650879,591.058511
60104,678.160125,677.844931
60105,625.318715,624.840634
60106,531.466553,530.966928
60107,481.807933,481.607892
60108,389.025529,388.978127
60109,408.346668,408.722911
60110,577.312926,577.560800
60111,601.789747,602.129271
60112,486.355156,486.676554
60113,650.282335,650.441513
60114,428.477349,428.250158
60115,594.765622,595.107217
60116,404.476355,404.015289
60117,600.079818,600.760319
60118,387.616318,387.436655
60119,421.265702,421.456578
60120,536.566199,536.406544
60121,597.186812,596.049243
60122,681.908593,681.005521
60123,499.378503,498.608274
60124,600.951016,600.535989
60125,525.774970,525.636297
60126,671.962542,671.943731
60127,453.412647,452.916503
60128,580.873972,580.637165
60129,403.452657,403.446794
60130,544.154228,543.878904
60131,579.767017,579.898829
60132,485.215293,485.442307
60133,446.038816,445.864691
60134,571.093941,570.283967
60135,500.029653,500.115293
60136,633.693072,633.823266
60137,528.900970,528.386382
60138,595.340641,595.822152
60139,516.384415,516.344034
60140,437.805538,438.327917
60141,505.439017,505.719395
60142,556.493087,557.376553
60143,779.602213,780.634787
60144,463.293589,463.740090
60145,632.128625,631.820312
60146,509.060408,509.292043
60147,670.451517,670.622789
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```