# The Goldilocks Prime

In Ham15 Mike Hamburg introduced a class of primes of the form $p = φ^2 - φ - 1$ and named them Goldilocks primes. In those prime fields $φ$ satisfies the Golden ratio relation $φ² = φ + 1$. When $φ$ is a power of two this allows for very efficient implementation. Unfortunately, the $-1$ at the end means it will have very few power-of-two roots of unity. We'd like to have many so we can do big number theoretic transforms.

We will instead consider primes of the form $p = φ^2 - φ + 1$. Following the plonky2 project we keep the name Goldilocks prime. Now $φ$ satisfies a modified Golden ration relation $φ² = φ - 1$. More importantly, the $+1$ at the end guarantees we will have a $φ$-th root of unity.

The values of $φ$ and $p$ where $p$ is prime are the sequences A055494 and A002383 respectively:

$$ \begin{aligned} φ &= 2, 3, 4, 6, 7, 9, 13, 15, 16, 18, 21, 22, 25, 28, …, \\ p &= 3, 7, 13, 31, 43, 73, 157, 211, 241, 307, 421, … \end{aligned} $$

As mentioned, in the prime field $\F_p$ we have $φ^2 = φ - 1$. From this further useful relations on the powers of $φ$ follow:

$$ \begin{aligned} φ^3 &= - 1 &\hspace{2em} φ^4 &= - φ &\hspace{2em} φ^5 &= 1 - φ &\hspace{2em} φ^6 &= 1 \end{aligned} $$

And the pattern repeats. This shows hat $φ$ is a primitive 6th root of unity. These relations leads to a particularly efficient modular reduction algorithm. First we write the number $n$ in base $φ$:

$$ n = n_0 + n_1 ⋅ φ + n_2 ⋅ φ^2 + n_3 ⋅ φ^3 + n_4 ⋅ φ^4 + ⋯ $$

We get rid of all the terms $n_{>3}$ by folding them into $n_0$, $n_1$, $n_2$ using the relations on $φ^3$ and $φ^6$.

$$ \begin{aligned} n_0' &= n_0 - n_3 + n_6 - n_{9\phantom{0}} + ⋯ \\ n_1' &= n_1 - n_4 + n_7 - n_{10} + ⋯ \\ n_2' &= n_2 - n_5 + n_8 - n_{11} + ⋯ \\ \end{aligned} $$

To reduce this from three to two terms we use the relation on $φ^2$.

$$ \begin{aligned} n_0' = n_0 - n_2 \\ n_1' = n_1 + n_2 \end{aligned} $$

The reduced number is $n_0 + n_1 ⋅ φ$. All that remains is carry propagation and some conditional subtractions of the modulus. Note that the reduction requires no multiplication operations.

To multiply two numbers $a,b ∈ \F_p$ we can write them in base $φ$ and make use of Karatsuba multiplication:

$$ \begin{aligned} a⋅b &= (a_0 + a_1 ⋅ φ) ⋅ (b_0 + b_1 ⋅ φ) \\ &= a_0 ⋅ b_0 + (a_0⋅b_1 + a_1⋅b_0) ⋅ φ + a_1⋅b_1 ⋅ φ^2 \\ &= a_0 ⋅ b_0 - a_1⋅b_1 + (a_0⋅b_1 + a_1⋅b_0 + a_1⋅b_1) ⋅ φ \\ &= a_0 ⋅ b_0 - a_1⋅b_1 + ((a_0 + a_1) ⋅ (b_0 + b_1) - a_0⋅b_0) ⋅ φ \\ \end{aligned} $$

This requires three full multiplications in base $φ$ and results in three terms. We reduce this to two terms using the final step of the modular reduction procedure.

**Question.** What do Barrett and Montgomery reduction look like?

## A lucky binary base

To implement base $φ$ operations efficiently we'd like it to be a power of two, i.e. $φ = 2^k$. There are not many such primes, the only solutions with $k < 4000$ are $k = 1$, $4$, and $32$. The first to are too small to be practically useful which leaves us with $32$. $φ = 2^{32}$ makes an especially useful prime $p = 2^{64} - 2^{32} + 1$ or written in full

$$ p = 18446744069414584321 = \mathtt{0x\,ffff\,ffff\,0000\,0001} $$

This is a great size. It is small enough to fit in a 64-bit number, but large enough to do a lot of useful math in. For example, if we have three 32-bit numbers $a,b,c ∈ [0, 2^{32}-1]$ we can compute $a ⋅ b + c$ without overflowing:

$$ a⋅b + c \enspace ≤ \enspace (2^{32} - 1)^2 + (2^{32} - 1) \enspace=\enspace 2^{64} - 2^{32} \enspace<\enspace p $$

When computing on 32/64-bit computers we have some useful interactions with the binary rings:

$$ \begin{aligned} \mod{2^{n⋅32}}_p &= \mod{φ^n}_p &\quad \mod{2^{64}}_p &= \mod{-1}_{2^{32}} &\quad \mod{-p}_{2^{64}} &= \mod{-1}_{2^{32}} &\quad \mod{φ}_{2^{32}} &= 0 & \end{aligned} $$

The first identity gives us a very efficient way to implement bit-shifts. This in turn leads to an efficient inversion algorithm from the half-extended binary GCD:

```
def inverse(a):
(u, a) = (MODULUS, a)
(t0, t1) = (0, 1)
twos = trailing_zeros(v)
v >>= twos
twos += 96 # 2^96 = -1
while u != v:
u -= v
t0 += t1
count = trailing_zeros(u)
u >>= count
t1 <<= count
twos += count
if u < v:
(u, v) = (v, u)
(t0, t1) = (t1, t0)
twos += 96 # 2^96 = -1
return t0 << ((191 * twos) % 192) # 2^-1 = 2^191, 2^192 = 1
```

## Multiplicative group

The multiplicative group has order $p - 1$ and factors into a power of two and, interestingly, all five known Fermat primes.

$$ p - 1 = 2^{32} ⋅ 3 ⋅ 5 ⋅ 17 ⋅ 257 ⋅ 65537 $$

The factor $2^{32}$ means we can do efficient NTTs of power-of-two sizes using the Cooley-Tukey algorithm. The Fermat primes are not just curious, they allow us to use Rader's FFT algorithm to turn the Fermat prime sized NTTs into power-of-two NTTs. With efficient NTTs for all prime factors we can use the Good-Thomans algorithm to efficiently combine these without requirng twiddle factors. Overall this gives decent NTT performance for any divisor of $p-1$.

But what if we want a different size? The usual method is to pad the data until it is a power of two size. This is wasteful as can mean almost doubling the size. Instead we could go beyond powers of two and include the other small primes $3$, $5$ things improve quite a bit

For example if we do a $2^{32} ⋅ 3$ mixed radix, then in half of the cases it is 25% smaller than if we only use $2^{32}$. If we also add $5$ then in a quarter of the cases it is an extra 16% smaller. These two seem worthwhile. Adding $17$ still gives a visible improvement, but is probably not worth the implementation complexity. And $257$ and $65537$ do not contribute anything noticeable.

NTTs require lot's of multiplications by roots of unity. Goldilocks again helps us make this efficient. We already found that $φ=2^{32}$ is a $6$th root of unity, and multiplying by it is simply a left shift of 32 bits. But if $2^{32}$ is a $6$th root, then $2$ itself must be a $6 ⋅ 32 = 192$th root. Great! This means multiplying by $192$th roots is just cheap bit shift. And since $192 = 2^6 ⋅ 3$ has many divisors we can now create a whole set of $n$-th roots $ω_n$ that can be implemented using bit shifts:

$$ \begin{aligned} ω_2 &= 2^{96} & ω_{6\phantom{0}} &= 2^{32} & ω_{16} &= 2^{12} & ω_{48} &= 2^{4} & ω_{192} &= 2\\ ω_3 &= 2^{64} & ω_{8\phantom{0}} &= 2^{24} & ω_{24} &= 2^{8} & ω_{64} &= 2^{3} \\ ω_4 &= 2^{48} & ω_{12} &= 2^{16} & ω_{32} &= 2^{6} & ω_{96} &= 2^{2} \\ \end{aligned} $$

We can go even further and construct a $384$th root using two bit shifts, but for that we need a trick. Schönhage observed that given an $8$th root $ω_8$, the value $ω_8 + ω_8^7$ is a square root of $2$. Let's quickly check this

$$ (ω_8 + ω_8^7)^2 = ω_8^2 + ω_8^{7⋅2} + 2 ⋅ ω_8^{1+7} = ω_8^2 - ω_8^2 + 2 = 2 $$

In Goldilocks $2^{24}$ is an $8$th root and $2^{96} = -1$ so $n = 2^{24} - 2^{72}$ is a square root of two. Furthermore since $n^2 = 2$ and $2$ is a $192$th root, it follows that $n$ is a $384$th root $ω_{384}$. If we don't want that factor of $3$ we can compute

$$ ω_{128} = ω_{384}^3 = ω_{384}^2 ⋅ ω_{384} = 2⋅(2^{24} - 2^{72}) = 2^{25} - 2^{73} $$

This also shows that all even powers of $ω_{384}$ have one bit set and all odd powers two.

$$ ω_{384}^i = \begin{cases} 2^{k} & i = 2⋅k \\ 2^{k + 24} - 2^{k + 73} & i = 2⋅k + 1 \\ \end{cases} $$

This $\sqrt{2}$ trick is useful, let's understand it better and see if we can take it further.

## Schönhage's trick

To intuitively understand why this works, forget for the moment that we are working in a prime field and imagine the 8th roots of unity in the complex plane.

We can construct the sum $ω_8 + ω_8^7$ by adding vectors. Pythagoras theorem shows it is $\sqrt{2}$. This procedure generalizes this to $n$-roots with $ω_n + ω_n^{n-1}$, where the angles between roots are $\frac{2⋅π}{n}$. A bit of trigonometry shows the solutions

$$ ω_n + ω_n^{n-1} = 2 ⋅ \cos \frac{2⋅π}{n} $$

For certain values of $n$ there are simple exact values for $\cos$, see a table of exact trigonometric values. We indeed get $\sqrt{2}$ and a few more. Most look quite uninteresting, but these two I like

$$ \begin{aligned} % ω_{8\phantom{0}} + ω_{8\phantom{0}}^7 &= \sqrt{2} \\ ω_{12} + ω_{12}^{11} &= \sqrt{3} &\hspace{2em} ω_{10} + ω_{10}^9 &= \frac{1 + \sqrt{5}}{2} \end{aligned} $$

The last one is also known as the Golden ratio. It turns out these work in the Goldilocks field as well. Since $ω_{12} = 2^{16}$ we have $\sqrt{3} = 2^{16} - 2^{80}$. For $ω_{10}$ I don't know a multiplication free construction.

**Question.** It is possible to geometrically construct $\sqrt[4]{2}$ using the geometric mean theorem. Is there a construction that leads to an efficient (multiplication free) implementation?

Adam P. Goucher explains that it is not possible to construct $\sqrt[4]{2}$ as a rational function of roots of unity.

## Generators

So far we've cleverly constructed roots up to $ω_{384}$, but for our NTTs we need all the roots up to the $2^{32}$th. The standard way to do this is to find a generator of the multiplicative group. A generator is a field element $g$ such that all non-zero numbers can be written as powers $g^i$ for some $i$. There are many such numbers and the smallest generator in Goldilocks in $7$. By Fermat's little theorem we have $g^{p - 1} = 1$ and thus $g$ is a primitive $(p-1)$-th root of unity. Since this is the highest possible root of unity, we can derive all others from it using

$$ ω_n = g^{\frac{p - 1}{n}} $$

It is convention to use the smallest generator, but if we compute $ω_{192}$ with $g=7$ we get $35184372080640$ instead of $2$. This happens because $n$-th primitive roots are not unique and there are many choices that work. While this is still a power of two, $ω_{192} = 2^{77}$, it makes things more complicated than they need to be and we get a more complicated formula for $ω_{384}^i$.

A priory there is no reason to pick one choice of roots over the other. But we do need our choices to be consistent, meaning we want

$$ ω_n = ω_{k⋅n}^k $$

to hold where applicable. Using a generator full fills that requirement. We'd also like a choice where we have an easy formula for multiplication by $ω_{384}^i$ in terms of bit shifts. The smallest generator that satisfies this is $554$. But this one has $ω_{384} = -(ω_8 + ω_8^7)$, it takes the negative square root of two. The smallest generator that picks the positive root is $2717$.

**Question.** Are there larger values of $k$ for which $2^{2⋅k} - 2^k + 1$ is prime or is $32$ the largest?

## Further references

*Gou21*. Adam P. Goucher (2021). "An efficient prime for number-theoretic transforms".*Po22*. Thomas Pornin (2022).

https://github.com/mir-protocol/plonky2/issues/1#issuecomment-809323437