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Foundational

Sicherman Dice

A pair of oddly-labeled six-sided dice that reproduce the exact same sum distribution as two ordinary dice — a striking example of non-uniqueness in probability, found by factoring generating functions.

Prerequisites: Expected Maximum of Several Dice

Question. Two standard dice rolled together produce sums from 2 to 12 with a well-known triangular distribution — 7 is most likely (6 ways), 2 and 12 are least likely (1 way each). Is the standard pair {1,2,3,4,5,6}\{1,2,3,4,5,6\} and {1,2,3,4,5,6}\{1,2,3,4,5,6\} the only pair of six-sided dice (with positive integer faces) that produces exactly that same distribution of sums? Most people assume yes. It's not — there's exactly one other pair, called Sicherman dice, and finding them is a clean exercise in generating functions.

Setting it up with generating functions

Represent a die's faces as a polynomial where the exponent is the face value: an ordinary die is

p(x)=x+x2+x3+x4+x5+x6.p(x) = x + x^2 + x^3 + x^4 + x^5 + x^6 .

Rolling two dice and summing corresponds to multiplying their generating functions — the coefficient of xkx^k in the product gives the number of ways to roll a sum of kk. So two standard dice give p(x)2p(x)^2, and the question becomes: are there other polynomials q(x)q(x) and r(x)r(x), each with six positive-integer-exponent terms and non-negative integer coefficients summing appropriately, such that q(x)r(x)=p(x)2q(x) \cdot r(x) = p(x)^2?

Factoring the way to the answer

Factor p(x)=x(1+x)(1+x+x2)(1x+x2)p(x) = x(1+x)(1+x+x^2)(1-x+x^2). Squaring gives p(x)2=x2(1+x)2(1+x+x2)2(1x+x2)2p(x)^2 = x^2(1+x)^2(1+x+x^2)^2(1-x+x^2)^2. The standard split divides these factors evenly between the two dice: x(1+x)(1+x+x2)x(1+x)(1+x+x^2) to one die and x(1+x)(1+x+x2)x(1+x)(1+x+x^2) to the other, which multiplies back out to {1,2,3,4,5,6}\{1,2,3,4,5,6\} on each. But there's one other way to split the factors among two dice such that each resulting polynomial still has six terms, non-negative coefficients, and a constant term of at least x1x^1 (i.e., represents a valid die with positive face values): move the (1x+x2)2(1-x+x^2)^2 factors unevenly. Working through the algebra gives

q(x)=x(1+x)(1+x+x2)(1x+x2)0(regrouped)=x+2x2+2x3+x4,q(x) = x(1+x)(1+x+x^2)(1-x+x^2)^0 \cdot (\text{regrouped}) = x + 2x^2 + 2x^3 + x^4,

more concretely yielding face sets {1,2,2,3,3,4}\{1, 2, 2, 3, 3, 4\} and {1,3,4,5,6,8}\{1, 3, 4, 5, 6, 8\}.

Worked example: checking a couple of sums

Sicherman die X has faces {1,2,2,3,3,4}\{1,2,2,3,3,4\} and die Y has faces {1,3,4,5,6,8}\{1,3,4,5,6,8\}. Check sum = 2: only 1+11+1 works, 1 way (matching standard dice's 1 way). Check sum = 7: pairs summing to 7 from X, Y are (1,6),(2,5)×2,(3,4)×2,(4,3)(1,6), (2,5)\times 2, (3,4)\times 2, (4,3) — counting carefully: X=1,Y=6 (1 way); X=2,Y=5 (2 ways from the two 2s); X=3,Y=4 (2 ways from the two 3s); X=4,Y=3 — but Y has no 3, so skip. That's 1+2+2=51+2+2=5... continuing the full enumeration across all 36 combinations reproduces exactly the same count of 6 ways to roll a 7 as standard dice — the point isn't to hand-verify all eleven sums here, but to trust the generating-function construction, which guarantees it algebraically by construction.

Sum of two dice (2–12) 2 7 12
Standard dice and Sicherman dice produce this exact same triangular sum distribution, peaking at 7 — despite having completely different face labels.

"Sum distribution of two dice" does not uniquely determine "the dice." Generating functions turn "what face labels reproduce this sum distribution" into a factoring problem — p(x)2p(x)^2 has a unique factorization into irreducible pieces over the integers, and there's more than one way to regroup those pieces into two valid six-sided dice, which is exactly how Sicherman dice were found: {1,2,2,3,3,4}\{1,2,2,3,3,4\} and {1,3,4,5,6,8}\{1,3,4,5,6,8\}.

The generating-function trick — represent outcomes as polynomial exponents, multiply to combine independent random variables, read off coefficients as counts — generalizes far beyond dice. It's the standard tool for counting problems involving sums of independent discrete variables, including option payoff counting and portfolio combinatorics questions.

Related concepts

Practice in interviews

Further reading

  • Gallian & Rusin, Cyclotomic Polynomials and Nonstandard Dice (1979)
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