P62 · Extremal configurations · Formed here · Applied frontier

Uniformity under the worst 2D projection

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0x1
VERIFIED CONSTRUCTIONthe first two coordinates of 16 higher-dimensional points
n = 16Current record · open

Place n points in [0,1]^d. For every pair of coordinates (r, s), keep just those two coordinates to get a planar projection and score it with P59's exact L2-star formula; the score is the largest over all C(d,2) projections. Make it as small as possible.

Formal definition

  • ContainerThe d-dimensional unit hypercube [0,1]^d
  • SubmissionExactly n points, each d decimal coordinates; coincidences are allowed
  • ObjectiveMinimize the maximum L2-star discrepancy over all two-coordinate projections; the C(d,2) projections share one denominator, so the maximum is taken exactly on integer numerators
  • ScoringThe record is the worst projection's exact integer with the denominator cleared; the page shows that projection's discrepancy, rounded up at the twelfth decimal

Getting a feel for it

Why stare at projections

A fine full-dimensional score cannot stop two particular columns from striping when seen together. Computer experiments, rendering and QMC are dominated by low-order interactions, and the worst 2D projection is the first mirror to crack.

Where the frontier is

Projection uniformity is an active direction in experimental design, but the continuous worst-projection objective has no published table of optima for fixed (n, d). Every sub-problem is open.

Source
ONE LEADERBOARD PER n

Current best solutions by n

Each n is an independent record with a page of its own. Open any of them to inspect the current construction, then challenge it.

Discussion (0) ↓
DISCUSSION

Discussion

Talk strategy, share methods, ask why you are stuck. Posts carry your public byline, the same name your records use; the #number after it is the account's signup ordinal, so a name cannot be worn by someone else. The floor is earned: break a record once, anywhere, and it is yours for good. New posts appear after an automated review.

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