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Alexander S. Petty  |  ©2009-2026
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collision

The Character Structure of the Collision Fluctuation

October 14, 202210 min read
Companion paper: The Character Structure of the Collision Fluctuation →
A bright beam passes through a triangular prism and spreads into colored rays against a dark field.
A single total conceals the differences between its residue streams. Character weights bring those differences into view.

I added up the collision deviations at the primes, giving each one a weight of 1/p1/p1/p. Through 100100100, the sum was about −0.851-0.851−0.851. Through 1,0001,0001,000, it was −1.149-1.149−1.149. Through 10,00010,00010,000, it was −1.393-1.393−1.393.

The sum was drifting downward. I wanted to know who was contributing.

In base ten, every prime in this calculation ends in 111, 333, 777, or 999. The total mixes those four streams together. A negative answer cannot tell us whether the streams are alike, whether one dominates, or whether differences between them disappear in the addition.

So I kept four running totals.

A reference level at each prime

First, the quantity being added.

Take the fractions 1/p,2/p,…,(p−1)/p1/p,2/p,\ldots,(p-1)/p1/p,2/p,…,(p−1)/p and look at their leading decimal digits. Each remainder belongs to the bin for the digit it produces. Multiply the remainder by ten, reduce modulo ppp, and look again. This is one step of long division. A collision occurs when the old remainder and the new remainder produce the same digit.

Count those collisions over all the nonzero remainders. At p=13p=13p=13, there are none. At p=17p=17p=17, there are two.

To give those counts a reference level, try all nonidentity multipliers. Some produce no collisions. The ones that do are called constructive. Average their positive counts. Bin Derangements and the Gate Width Theorem gives that mean exactly from the sizes of the digit bins.

At both 131313 and 171717, the constructive mean is 222. Subtract it from the count for multiplication by ten.

Prime Collisions for multiplication by ten Constructive mean Deviation
131313 000 222 −2-2−2
171717 222 222 000
191919 000 222 −2-2−2
232323 000 7/37/37/3 −7/3-7/3−7/3
292929 222 26/926/926/9 −8/9-8/9−8/9

That last column is the collision deviation, written Δp\Delta_pΔp​. It measures where multiplication by the base sits relative to the constructive mean at that prime. The reference level comes from the finite digit table itself.

Dividing by ppp makes each prime’s contribution smaller. The first terms of the sum are therefore −2/13-2/13−2/13, 0/170/170/17, −2/19-2/19−2/19, and −7/69-7/69−7/69. We include every prime greater than 111111. At 111111, the digit bins are singletons, no nonidentity multiplier is constructive, and there is no constructive mean to subtract.

This centering does not make the sum over primes zero. The mean was taken over multipliers at each individual prime. We then chose one multiplier and carried its deviation into a different sum.

Four running totals

Let F1F_1F1​ collect the weighted deviations at primes ending in 111. Let F3F_3F3​, F7F_7F7​, and F9F_9F9​ do the same for the other endings. All four stop at the same cutoff.

Two plots show the total weighted collision deviation and its four residue streams for primes from 13 through 10000 in base ten at lag one.
The lower curves add to the upper one. Keeping them separate reveals differences that the total cannot show.

Through 10,00010,00010,000, the four contributions are approximately

Last digit Weighted deviation sum
111 −0.418680-0.418680−0.418680
333 −0.556673-0.556673−0.556673
777 −0.314742-0.314742−0.314742
999 −0.102500-0.102500−0.102500

They are all negative at this cutoff, but they are far from equal. The stream ending in 333 contributes more than five times the negative amount of the stream ending in 999.

Keeping separate accounts already exposes that difference. There is also a way to combine the accounts that respects the arithmetic of their labels.

Weights that multiply correctly

Multiply two numbers ending in 333 and 777. Their product ends in 111. Multiply two ending in 333. Their product ends in 999.

A Dirichlet character assigns a weight to each of these four endings, with one requirement. Multiplying the weights must give the weight of the product’s ending.

Giving every ending the weight 111 works. A more useful recipe gives weight +1+1+1 to endings 111 and 999, and weight −1-1−1 to endings 333 and 777. Check the examples. For 333 times 777, the weights multiply to (−1)(−1)=1(-1)(-1)=1(−1)(−1)=1, the weight assigned to ending 111. For 333 times 333, they also give 111, the weight assigned to ending 999.

Two more recipes use iii, the square root of −1-1−1. It can be pictured as a quarter-turn. Four quarter-turns return to the start. The endings do the same under repeated multiplication by 333, passing through 3,9,7,13,9,7,13,9,7,1.

Assign those endings the weights i,−1,−i,1i,-1,-i,1i,−1,−i,1. Multiplication still works. In particular, the weights for 333 and 777 give i(−i)=1i(-i)=1i(−i)=1.

These are the four recipes. I have called the sums they produce A0,A1,A2,A3A_0,A_1,A_2,A_3A0​,A1​,A2​,A3​ to keep the notation short.

A four by four table gives the character weights on decimal endings 1, 3, 7, and 9, with a multiplication check using 3 times 7.
Each row is a consistent weighting of the four endings. The first keeps the total. The other rows measure differences between the streams.

The all-ones recipe gives

A0=F1+F3+F7+F9.A_0=F_1+F_3+F_7+F_9.A0​=F1​+F3​+F7​+F9​.

This is the principal character component. With this normalization, it is the total, not the average.

The real signed recipe gives

A2=F1−F3−F7+F9.A_2=F_1-F_3-F_7+F_9.A2​=F1​−F3​−F7​+F9​.

It compares the combined contributions of endings 111 and 999 with those of endings 333 and 777.

The complex recipe collects two other differences into one number,

A1=(F1−F9)+i(F3−F7).A_1=(F_1-F_9)+i(F_3-F_7).A1​=(F1​−F9​)+i(F3​−F7​).

Its real part compares 111 with 999. Its imaginary part compares 333 with 777. The fourth recipe reverses that imaginary part. Thus A3A_3A3​ is the complex conjugate of A1A_1A1​. These two components always have the same magnitude in this calculation. Their agreement is built into the weights.

The difference hidden in the total

Now apply the signed recipe to the four values at 10,00010,00010,000.

Five bars show F1, minus F3, minus F7, F9, and their sum A2 at cutoff 10000. The sum is positive 0.350235 while the principal component is negative 1.392595.
Reversing the signs of the streams ending in 3 and 7 exposes a positive contrast. A downward total can contain this difference without revealing it.

The total is about −1.393-1.393−1.393. The contrast is about +0.350+0.350+0.350.

Endings 333 and 777 contribute the larger combined negative amount, so subtracting their contribution leaves a positive difference. This is a statement about the distribution of the deviation among the four classes. It is invisible in the total alone.

The full character calculation gives

Prime cutoff A0A_0A0​ Real part of A1A_1A1​ Imaginary part of A1A_1A1​ A2A_2A2​
100100100 −0.851414-0.851414−0.851414 −0.012410-0.012410−0.012410 −0.168966-0.168966−0.168966 0.3006200.3006200.300620
1,0001,0001,000 −1.149104-1.149104−1.149104 −0.208657-0.208657−0.208657 −0.217315-0.217315−0.217315 0.3296300.3296300.329630
5,0005,0005,000 −1.318994-1.318994−1.318994 −0.288890-0.288890−0.288890 −0.234378-0.234378−0.234378 0.3540140.3540140.354014
10,00010,00010,000 −1.392595-1.392595−1.392595 −0.316180-0.316180−0.316180 −0.241931-0.241931−0.241931 0.3502350.3502350.350235

The total becomes more negative across these cutoffs. The signed contrast first rises, then falls a little. Even this small table resists the idea that all the components simply grow together.

Every stream comes back

Dirichlet characters are classical coordinates for multiplication on residue classes. Their usefulness here is exact. The four components retain all four running totals.

For example, the stream ending in 111 comes back through

F1=A0+A2+2Re⁡A14.F_1=\frac{A_0+A_2+2\operatorname{Re}A_1}{4}.F1​=4A0​+A2​+2ReA1​​.

Adding A0A_0A0​ and A2A_2A2​ cancels the streams ending in 333 and 777. Adding twice the real part of A1A_1A1​ then cancels the stream ending in 999. Four copies of F1F_1F1​ remain. Division by four finishes the reconstruction.

The other streams return in the same way. This is finite Fourier inversion. It works at every cutoff. Parseval’s identity also says that the total squared size of the character components is four times that of the residue streams. The scale factor comes from the normalization of the transform.

There are four real quantities to recover. The two real components supply two of them. The real and imaginary parts of the conjugate pair supply the other two.

In another base, the admissible endings are the residue classes coprime to that base. There are φ(b)\varphi(b)φ(b) of them, and exactly as many characters. We can also compare remainders several digit steps apart, or replace 1/p1/p1/p by 1/ps1/p^s1/ps to change the weight given to larger primes. The same finite reconstruction holds. The digit calculation supplies the coefficients. Character orthogonality supplies the change of coordinates.

Beyond the cutoff

The difficult question is still ahead of the calculation. As more primes enter, does a component settle, keep oscillating, or grow without bound?

A downward graph through 10,00010,00010,000 cannot answer that. Neither can a positive contrast at four cutoffs. The finite theorem tells us exactly how to separate and recover the streams. It does not give their behavior at infinity.

But it gives the question a more precise form. At each prime, long division produces an exact deviation. Across primes, those deviations form a signal with a total, a signed contrast, and two further differences. We can follow each one without losing the ability to put the original streams back together.

I began with a sum that drifted downward. The calculation now preserves what that single number concealed. The primes ending in 333 and 777 pull more strongly in this range than those ending in 111 and 999. Whether that imbalance persists is a question I can finally ask on its own.

Companion paper: The Character Structure of the Collision Fluctuation →
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