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Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.
Error code:   FeaturesError
Exception:    ArrowInvalid
Message:      JSON parse error: Invalid value. in row 0
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 324, in _generate_tables
                  df = pandas_read_json(f)
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 38, in pandas_read_json
                  return pd.read_json(path_or_buf, **kwargs)
                         ~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 815, in read_json
                  return json_reader.read()
                         ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1014, in read
                  obj = self._get_object_parser(self.data)
                File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1040, in _get_object_parser
                  obj = FrameParser(json, **kwargs).parse()
                File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1176, in parse
                  self._parse()
                  ~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1392, in _parse
                  ujson_loads(json, precise_float=self.precise_float), dtype=None
                  ~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
              ValueError: Expected object or value
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 244, in compute_first_rows_from_streaming_response
                  iterable_dataset = iterable_dataset._resolve_features()
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 4408, in _resolve_features
                  features = _infer_features_from_batch(self.with_format(None)._head())
                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2679, in _head
                  return next(iter(self.iter(batch_size=n)))
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2861, in iter
                  for key, pa_table in ex_iterable.iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2395, in _iter_arrow
                  yield from self.ex_iterable._iter_arrow()
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 327, in _generate_tables
                  raise e
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 290, in _generate_tables
                  pa_table = paj.read_json(
                      io.BytesIO(batch), read_options=paj.ReadOptions(block_size=block_size)
                  )
                File "pyarrow/_json.pyx", line 342, in pyarrow._json.read_json
                File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
                  raise convert_status(status)
              pyarrow.lib.ArrowInvalid: JSON parse error: Invalid value. in row 0

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GraphKind — Universes of color refinement

CI preprint verifications proof status

Español · Page (ES) · Page (EN) · Paper · Proof · Reproduce


Abstract

We classify the operators under which the color refinement (1-WL) profile of a graph is invariant, inside a parametric family of observation universes (f, ι)f compresses neighborhood counts and ι is an involution. The engine proposed and verified that the color refinement partition is complement-invariant (call it T4; the conjecture mechanism was human-built), verified it on 2,131,019 exhaustive graphs (n≤7, 100.0000%) plus 19,407 adversarial ones, and a written proof was produced (injectivity of the neighborhood-multiset subtraction). Parameterizing the universe, the data — not the authors — selected the count law T4 ⟺ f(1) ≠ f(2) (34/34 and 102/102), and further probing produced a characterization:

T4(ι,f) holds    ιSnKand(ι changes the pair    f(1)f(2)),K={id, comp_dir, transp, comp_transp}Z2×Z2. T4(\iota, f)\ \text{holds} \iff \iota \in S_n \cdot K \quad\text{and}\quad \bigl(\iota\ \text{changes the pair} \implies f(1) \neq f(2)\bigr), \qquad K = \{\mathrm{id},\ \mathrm{comp\_dir},\ \mathrm{transp},\ \mathrm{comp\_transp}\} \cong \mathbb{Z}_2 \times \mathbb{Z}_2 .

The forward direction is proved (count mechanism); the converse is verified exhaustively in n=4 (96 exact survivors, zero outside), targeted in n=5 (6,424 witnesses), and on real data (molecules 100/100, CST 94/94). Changing the type of the invariant — partition → orbit → distribution → observer — T4 dies in a deterministic Z₃ universe, dies under process randomness, survives under object randomness, and is inherited by the whole k-FWL hierarchy (≡ (k+1)-WL; 51/51). Every claim is reproducible with one command, each verification carrying an assert with the exact number. Limits are declared; five of our own bugs were caught by controls and are documented, not deleted.


Contributions

  1. T4, proposed and verified by the engine: CR_k(G) = CR_k(Ḡ) as partitions (not merely equal multisets of class sizes) — with a written proof.
  2. The count law f(1) ≠ f(2), selected by the data after two human hypotheses were refuted by the table.
  3. The characterization Sₙ·K with (⇐) proved and (⇒) verified; the missing piece — uniformity — identified by falsification.
  4. The type change: T4 across deterministic, dynamic, probabilistic and observer universes.
  5. Method: freeze-before-interpret, negative controls, and five own bugs caught and recorded.

1. The theorem (T4)

Let G = (V, E) be a finite simple graph, its complement, and CR_k(G) the partition of V induced by round k of color refinement with initial colors f(type, degree).

Theorem (EXP-086). For every G and every k ≥ 0: $$CR_k(G) = CR_k(\bar G)$$ as partitions of the same vertex set V (color names differ; the classes are identical).

Corollary (T4). The multisets of class sizes of the stable partitions of CR(G) and CR(Ḡ) coincide, and they coincide at every round.

G and its complement share the same partition

Real data: Q3 and its complement, colored by WL class — the same partition
Real data: Q₃ and its complement, vertices colored by WL class — the partition is identical (T4).

T4 round by round: G and its complement, colored by WL class at k=0..3
Real data: the WL refinement round by round (k=0…3) — G and its complement keep the same classes at every level.

Proof (sketch). Base. In , deg_Ḡ(v) = n−1−deg_G(v); since d ↦ n−1−d is a bijection of degrees, the relation "same color" is the same in G and . Step. Assume CR_k(G) = CR_k(Ḡ) =: P_k. For v ∈ V, the closed neighborhood in is N_Ḡ[v] = V ∖ N_G(v), and its round-k color multiset is

Mk(v)=Tk(Mk(v)[colork(v)]),Tk:=total color multiset of Pk.M'_k(v) = T_k - \bigl(M_k(v) - [\mathrm{color}_k(v)]\bigr), \qquad T_k := \text{total color multiset of } P_k .

Since T_k is fixed, the map M_k(v) ↦ M'_k(v) is injective: u, v have the same closed-neighborhood multiset in G iff they do in . Because color_{k+1}(v) is a deterministic function of (color_k(v), M_k(v)), the relation "same color" is preserved, hence CR_{k+1}(G) = CR_{k+1}(Ḡ). ∎

Status: written proof (one page), verified on 2,131,019 exhaustive graphs (n≤7), 19,407 adversarial, and 688/688 compatibility pairs; external review pending. Full text: paper/PRUEBA-T4.md · cycle: paper/TEOREMA-UNIVERSOS.md.


2. The count law

In the standard universe with an involution that changes the connected pair:

T4 holds    f(1)f(2). T4\ \text{holds} \iff f(1) \neq f(2).

Mechanism. In the complement, a vertex with 1 neighbor in a class gets |c|−1 (which may be 2): if f collapses 1 and 2, the duality dies. What f does with 3, 4, 5… is irrelevant. Verified 34/34 (17 functions × 2 involutions, n≤6) and shielded 102/102 (formal definition of dual-global, 6 involutions × 17 functions).

The 34 universes of EXP-102: T4 holds iff f(1) != f(2)
Real data: the 34 universes (17 functions × 2 involutions) — T4 holds exactly when f(1) ≠ f(2).


3. The characterization

The Klein group: two halves, two conditions

Forward direction (proved). For ι = σ∘s∘c:

case mechanism condition
σ (relabel) WL is isomorphism-invariant; the coloring transports bijectively holds for every f
s (global in/out swap) counts swap: (in_D,out_D) → (out_D,in_D); the profile maps by (f(a),f(b)) → (f(b),f(a)) holds for every f
c (uniform complement) counts map `m → D

The non-obvious piece is uniformity: preserving the pair is not enough if the action is not uniform (flip_inc0 preserves the pair and dies 0/24). Outside Sₙ·K, everything dies.

Converse (verified).

camera result
n=4, induced space, exhaustive (528 iotas × 4096 digraphs) 96 exact survivors (= 24·4), zero outside
n=5, targeted (8,160 iotas) 7,680 with valid witness; the 480 without are uniform
outside the space (10,000 random affine) 10,000/10,000 with witness
witness existence (6,424 non-uniform) 6,424/6,424 valid witnesses
real data molecules 100/100 · CST 94/94

Real data: of the 528 induced iotas at n=4, exactly the 96 uniform ones survive
Real data: of the 528 induced iotas at n=4, exactly the 96 uniform ones survive (= 24·4).

Autonomous search. Given a language of 11 primitives + 3 combinators (~400 recipes) and a rate/MDL criterion, the engine found that the best valid witness is the cycle (99.63%, complexity 1) — better than the human construction (97.8%). No valid recipe reaches 100%.


4. From conjecture to theorem candidate

From autonomous conjecture to theorem candidate


5. The type change

The invariant changes type

Observer cascade: 26 to 0

universe invariant T4 evidence
standard partition ✅ holds (proved) 2,131,019/2,131,019
deterministic Z₃ orbit (periods) ❌ dies max 52.4% (maj); 6 rules
random R1 (async WL) distribution ❌ dies 204/1096 = 18.6%
random R2 (G(n,p) vs G(n,1−p)) distribution ✅ holds exactly (complement bijects ensembles)
random R3 (random involutions) measure threshold = measure 0/5000 uniform vs 96/528 induced
k-FWL hierarchy (≡ (k+1)-WL) partition of k-tuples ✅ inherited 51/51 in k=1,2,3
observer cascade (n≤7) 26 → 0 (k=1 → k=2)
Rook vs Shrikhande k=1 no, k=2 no, k=3 yes

6. Method

  • Freeze before interpreting: every experiment freezes results_frozen.json first.
  • Negative controls: the check that caught the false "proof" (52/104 uniform failures) and the wrongly built Shrikhande (is_isomorphic = True).
  • Five own bugs caught and recorded (not deleted):
# bug fix
1 multiset of sizes (weak: C6 and 2·C3 share it) colors
2 comparing colors across graphs compare partitions
3 indices in the initial coloring degrees + adjacencies
4 separated multisets (weak k-WL) correlated pairs (= k-FWL)
5 wrongly built Shrikhande (it was the Rook twice) is_isomorphic

The method is part of the result.


7. Reproduce

git clone https://github.com/cripto-bot/graphkind-universos-v2
cd graphkind-universos-v2
python3 -m venv .venv && .venv/bin/pip install -r requirements.txt
bash reproduce.sh            # V1–V12 (~10-15 min)
bash reproduce.sh --rapido   # V1, V3, V5, V8, V10, V11 (~3 min)

Every verification carries an assert with the exact number from the paper: if anything does not match, it fails. CI runs the fast subset on every push and the full suite on demand.

# verification assert
V1 the law f(1)≠f(2) (17 f × 2 involutions, n≤6) 34/34
V2 characterization n=4 exhaustive 96 and 48
V3 T4_k complement-invariance (k-FWL) 51/51
V4 observer cascade n≤7 26 → 0
V5 Rook vs Shrikhande (k-FWL; 3-WL std does NOT) k*=3
V6 deterministic Z₃ does not hold
V7 random R1 204/1096
V8 R3 measure dependence 96/528
V9 autonomous search cycle 99.63%
V10 hash certificate (12-hex == 64-hex) no collisions
V11 convergence certificate (stable == n+2) OK
V12 classification constant across graphs (n=4) OK

7b. Corrections (2026-09-13)

Independent verification (EXP-159 of the lab) found a naming error and two certificates were added:

  1. k-FWL, not "k-WL" (D-005). The kernel implemented in codigo/wl.py is the correlated one (folklore, k-FWL), equivalent to (k+1)-WL. The plain name "k-WL" is the standard variant (position- separated multisets), which is strictly weaker: standard 3-WL does NOT separate Rook from Shrikhande; 3-FWL (≡ 4-WL) does. The code, docstrings and prints now say k-FWL (≡ (k+1)-WL). V3/V5 are unchanged numerically.
  2. V10 — hash certificate: the 12-hex hash does not alter any partition (12-hex partition == 64-hex partition over 74 graphs × 17 f).
  3. V11 — convergence certificate: the refinement reaches its stable partition within the n+2 cap (stable == fixed n+2 rounds over 1098 graphs × 17 f); wl_sym/wl_k_colors now stop at convergence.
  4. V12 — classification scope: clasificar_involucion classifies on one graph; V12 verifies that the class is constant across all graphs n=4 for the tested (ι, f). The universal statement remains the open direction of the paper.

The numerical results of the paper are unchanged; the naming and the certificates are the corrections.


7c. The universe arc (v2, EXP-162 → 169)

The v2 adds the universe arc (multilayer, matrix, hypergraphs, arities, dual), with its freezes in resultados/ and V13–V16 in codigo/verificaciones_v2.py:

# verification assert
V13 multilayer: total holds, per-layer dies in the canonical variant, channels hold 4160/4160 · failures > 0 · 8320/8320
V14 3-uniform hypergraphs: T4 holds 6042/6042 (n≤5 + n=6 sample)
V15 per-arity dual: partition + saving 1024/1024 · 5120→3392 edges
V16 mixed arities: per-arity holds (repair) 1024/1024
V17 complement quotient (T4's price) 52 graphs · 24 pairs (SG-01 n≤8: 6,168)
V18 IR: IR_1 does not separate Rook/Shri, IR_2 does i*=2
V19 SG-04 certificate: n=10 exhaustive, no failures 12,005,168 · 0 collisions

Multilayer law
The multilayer coherence law (EXP-162/163): total holds, per-layer dies in the canonical variant.

k* ladder
The k\*(L) ladder is flat and corrects EXP-162's k\*=2.

Results: (1) multilayer — the coherence law: total holds (1298/1298, 1404/1404), per-layer dies only in the canonical variant (6.9%/7.4%); the preserving group is exactly the uniform one; the k* ladder is flat (corrects EXP-162's k*=2); (⇐) proved, (⇒) open. (2) matrix — the frontier moves with the observer, not with typing. (3) hypergraphs — prediction registered and correct (1831/1831). (4) arities — the ladder holds; the per-arity transplant fails (the law is of channels). (5) per-arity dual — assimilated: partition 100%, saving 14.37% vs 10.26%.

Matrix
The frontier moves with the observer, not with typing.

Hypergraphs
Prediction correct (1831/1831) and the arity transplant that fails.

Dual
Per-arity dual: 14.37% saving with guaranteed partition.

Trajectory
The refinement trajectory: T4 and the multilayer divergence.

Arities
The arity ladder and the failing transplant.

7d. The Holy Grail (SG-01→03)

  • Completeness in the class: the minimal family is {WL, 2-WL, 3-WL} with C_8 = 0 over 76,205,685 pairs (n≤8); leave-one-out: k-WL 3 does the work; the n=16 frontier (Rook/Shri) is separated only by the full family. Freeze: resultados/SG-01_results_frozen.json.

Frontier C_n
The frontier curves per observer (SG-01/03, EXP-119).

  • The price of T4: the complete invariant is not complement-invariant; the quotient G~Ḡ merges 6,168 pairs.
  • Individualization: i*=1 at n≤8 (13,597 graphs); i*=2 at Rook/Shrikhande (IR_1 no, IR_2 yes). The IR↔k-WL lattice: at n≤9 the complete ones collapse (vacuous equivalence); anchors A/B, C not observed. Freezes: SG-02, SG-03.

Holy Grail
Completeness, T4's price and i\*.

  • The multilayer proof ships in paper/PRUEBA-MULTICAPA.md ((⇐) proved, (⇒) open) and the transversal patterns + DECISION_LOG (D-001→D-017) in paper/DECISION_LOG.md.

7e. SG-04: the door (n=10 exhaustive)

  • 0 collisions over 12,005,168 exhaustive n=10 graphs (KW3/IR1p, 11.1 h) → the first incompleteness is not at n=10.
  • Directed: 9 regular combos n=11–15 (cap 5,000) + 10 Cayley/Paley/Q4 pairs → 0 failures.
  • The first known failure remains at n=16 (Rook/Shri): separated by elementary descriptors (SNFL, AUT, CICLOS, LOCAL, HOM2) + KF3/IR2p. Freeze: resultados/SG-04_results_frozen.json (certificate V19).
  • Registered correction: geng -d 3 (separated) fails; it is -d3.

8. Repository structure

paper/PAPER.md                   the paper (bilingual abstract, method, results, §12 v2 arc)
paper/TEOREMA-UNIVERSOS.md       the full cycle EXP-099→119
paper/PRUEBA-CARACTERIZACION.md  the (⇐) proof and the status of (⇒)
codigo/universos.py              the law inside the engine (t4_garantizado, oracle)
codigo/wl.py                     symmetric WL + correlated k-FWL (≡ (k+1)-WL)
codigo/verificaciones.py         V1–V12 with asserts of the exact numbers
paper/PRUEBA-MULTICAPA.md        (⇐) proved, (⇒) open (EXP-162)
paper/DECISION_LOG.md            laboratory decisions D-001→D-017
resultados/*.json                original freezes (EXP-102..169 + SG-01..04)
resultados/atlas/*.json          the atlas: 15 universes (EXP-105)
assets/*.svg                     figures
index.html · index.en.html       presentation pages (ES/EN)

9. Limits and open problems

  • (⇒) for all n: open. Verified in n≤4 exhaustive, n=5 targeted, and real data; the ∀n argument is the remaining step.
  • Sufficiency of f(1)≠f(2) for arbitrary f: verified in the catalogs; general proof open.
  • The full affine space n≥5 is intractable (involutions of S₂₀); the tested space is the induced one plus random affine.
  • T4: written proof, external review pending; Lean formalization not available in the environment.
  • Universes: our own definitions, declared; the space is open.
  • Data: ChEMBL (CC-BY 4.0), CodeSearchNet, UniProt, Pfam — cited; fixed samples by seed.

10. References (selection)

  • Weisfeiler, Leman (1968). A reduction of a graph to a canonical form…
  • Morgan (1965); Rogers, Hahn (2010). Extended-connectivity fingerprints.
  • Dvořák (2010); Dell, Arvind, Larsson (2018). Homomorphisms and 1-WL.
  • Babai (2016). Graph isomorphism in quasipolynomial time.
  • Xu et al. (2019). How powerful are graph neural networks?
  • Morris et al. (2019). Weisfeiler and Leman go neural.
  • Zamfirescu (1980). Non-traceable 3-connected planar cubic graphs.
  • Lovász (1970). Problem on vertex-transitive graphs.


11. The laboratory behind this result

This paper is one thread of a 120-experiment laboratory (EXP-000 → EXP-120; 26,384 lines of run.py; 321 KB of frozen results) spanning six arcs. Every number here is anchored to a frozen artifact, and a meta-experiment (EXP-120) verifies the laboratory's key claims: 26/26 hits.

arc range what it built
Foundational 000–010 taxonomy collapse 0.5876; molecules 3.00×; parity with Morgan 1.0000 vs 0.9973; granularity k*=21→24
Riemann 011–019 2,001,052 zeros; JS 0.1350 vs 0.0161; Euler bridge 0.16110 ⊃ 1/2π; critical line σ*=0.50000; clean negatives
Arithmetic/Algebra/Physics 020–046 r* emerged (0.8934); discrete WL = Morgan (0.8877 vs 0.8864); structural calculus with no rules; NS-3D verified
Discovery/Ontology 047–079 real code (129 chains / 119 rings / 152 stars); 6/6 protein hypotheses rejected by controls; emergent math (λ=νn², ABC 6/6, cascade √5, Euler limit ~1.2); the tribunal
T4 080–098 68/68 → 19,407 → 2,131,019/2,131,019; written proof; refine_dual 10.3× / 40.5%; conjecture bank
Universes 099–120 this paper: law, characterization, witnesses, autonomous search, Z₃, random, k-FWL
Universes v2 162–169 multilayer (uniform law, group, k* ladder), universe×observer matrix, hypergraphs (prediction), arities, arity dual

Transversal patterns: freeze before interpreting · negative controls (single-pass shuffle is not evidence: it varies 0.05–0.84) · five of our own bugs caught and recorded, not deleted · four types of result: kinds → laws → theorems → universes.

Full map: paper/MAPA-DEL-LABORATORIO.md.

12. The engine: how it works and its measured power

How it works: iterative 1-WL refinement on a real 8-node example
The engine pipeline: data → graph → label₀ → round → STOP → kinds; the example shows rounds 3 → 5 → 5 → 5 up to the stable partition.

The engine's power, in real numbers
Measured power: parity with Morgan (AUC 0.9608 vs 0.9541), compression 3.00× (molecules) and 187.5× (code), refine_dual 10.3×, dual-normalization saving 40.5%, universe oracle 87/87, engine tests 104/104, T4 bank 2.13M.

© 2026 Juri (cripto-bot) · preprint · CC-BY-4.0 license (attribution required).
This document claims no priority over open problems: it reports a verified characterization in a bounded domain.
Cite as: Argaña Silguero, J. (2026). GraphKind — Universes v2 [software and data]. Zenodo. 10.5281/zenodo.22747350 (concept DOI; v2.0.0: 10.5281/zenodo.22747351) · see CITATION.cff.

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