contents
§16

Open problems — frontiers of group theory

The "basic invariants" of the cube group (order, diameter, structure theorem) are completely settled. But step out by even one notch and several problems still resist the mathematical community after 50 years — spanning combinatorics, geometry, complexity, and quantum algorithms.

open problems at a glance
#problembest knowndifficulty
14×4 God's number[22, 36] HTMmedium (algorithmic)
2n×n asymptotic constantΘ(n²/log n)hard (theoretical)
3average optimal length17.97 HTMeasy (statistical)
4non-Abelian HSPno quantum speedupvery hard (quantum)
5mixing-time cutoff≈ 22 ± 3hard (probabilistic)

16.1 4×4×4's God's number

The 4×4×4's diameter is bounded only to [22, 36] HTM. With order , exhaustive enumeration is impossible — 27 orders of magnitude beyond the atom count of the observable universe. The strongest approaches use:

16.2 Asymptotics of n×n×n

For general n × n × n, Demaine, Demaine, Eisenstat, Lubiw, Winslow (2018) proved that finding the optimal alg is NP-complete for n ≥ 2. The same paper established asymptotic bounds:

The Θ-bracket is tight, but the exact constant inside is unknown. We have with , but the explicit values of are open. This is a flagship problem in "puzzle complexity."

16.3 Statistical properties of optimal solutions

The 3×3 HTM diameter = 20 is settled. But what is the average optimal solve length? Rokicki measured over all 4.3 × 10¹⁹ states an average HTM. So nearly 99% of states need 16–20 moves — the distance distribution is highly concentrated. The following sub-questions remain open:

16.4 Which solver is best?

Thistlethwaite (1981) and Kociemba's two-phase (1992) are subgroup-chain descent algorithms, slicing state space into lookup layers. But several entirely different approaches exist:

Which method is Pareto-optimal in "average optimal length × runtime"? Tied tightly to G's structure (generator symmetry, subgroup-chain decomposability), this remains a long-running research question.

16.5 Quantum algorithms?

Can a quantum computer solve the cube in subexponential time? This sits at the intersection of black-box group theory and quantum algorithms. Shor's algorithm handles Abelian groups (integer factorization, discrete log); the non-Abelian Hidden Subgroup Problem (HSP) — open:

For Abelian G there is an quantum algorithm; for general non-Abelian G, subexponential is known only for some classes (dihedral groups, certain solvable groups). The cube group is a perfect non-Abelian HSP testbed — any polynomial quantum algorithm on G would be a major breakthrough.

16.6 Random-walk cutoff threshold

Diaconis (1980s) introduced the cutoff phenomenon: for many natural random walks on groups, sits near 1 for a long time and then drops sharply within a narrow window (§24). The classic example: Bayer–Diaconis (1992) proved 52 cards need riffle shuffles to mix. For the cube:

Lower bound ~18, upper ~30, exact threshold unproven. WCA's 25-move scramble is no accident — above the estimated cutoff, above the proven God's number (20), without hitting known extremal positions.

"The cube's open problems are not 'too hard nobody knows'; they are 'too specific nobody has reduced'. Algorithms, geometry, representation theory all crash into G's concrete structure."
— Joyner & Frey, on group theory in the cube
cuberoot.me · Rubik's Cube as a Group · 2026