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doc: Describe Jacobi calculation in safegcd_implementation.md
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# The safegcd implementation in libsecp256k1 explained

This document explains the modular inverse implementation in the `src/modinv*.h` files. It is based
on the paper
This document explains the modular inverse and Jacobi symbol implementations in the `src/modinv*.h` files.
It is based on the paper
["Fast constant-time gcd computation and modular inversion"](https://gcd.cr.yp.to/papers.html#safegcd)
by Daniel J. Bernstein and Bo-Yin Yang. The references below are for the Date: 2019.04.13 version.

Expand Down Expand Up @@ -769,3 +769,51 @@ def modinv_var(M, Mi, x):
d, e = update_de(d, e, t, M, Mi)
return normalize(f, d, Mi)
```

## 8. From GCDs to Jacobi symbol

We can also use a similar approach to calculate Jacobi symbol *(x | M)* by keeping track of an
extra variable *j*, for which at every step *(x | M) = j (g | f)*. As we update *f* and *g*, we
make corresponding updates to *j* using
[properties of the Jacobi symbol](https://en.wikipedia.org/wiki/Jacobi_symbol#Properties):
* *((g/2) | f)* is either *(g | f)* or *-(g | f)*, depending on the value of *f mod 8* (negating if it's *3* or *5*).
* *(f | g)* is either *(g | f)* or *-(g | f)*, depending on *f mod 4* and *g mod 4* (negating if both are *3*).

These updates depend only on the values of *f* and *g* modulo *4* or *8*, and can thus be applied
very quickly, as long as we keep track of a few additional bits of *f* and *g*. Overall, this
calculation is slightly simpler than the one for the modular inverse because we no longer need to
keep track of *d* and *e*.

However, one difficulty of this approach is that the Jacobi symbol *(a | n)* is only defined for
positive odd integers *n*, whereas in the original safegcd algorithm, *f, g* can take negative
values. We resolve this by using the following modified steps:

```python
# Before
if delta > 0 and g & 1:
delta, f, g = 1 - delta, g, (g - f) // 2

# After
if delta > 0 and g & 1:
delta, f, g = 1 - delta, g, (g + f) // 2
```

The algorithm is still correct, since the changed divstep, called a "posdivstep" (see section 8.4
and E.5 in the paper) preserves *gcd(f, g)*. However, there's no proof that the modified algorithm
will converge. The justification for posdivsteps is completely empirical: in practice, it appears
that the vast majority of nonzero inputs converge to *f=g=gcd(f<sub>0</sub>, g<sub>0</sub>)* in a
number of steps proportional to their logarithm.

Note that:
- We require inputs to satisfy *gcd(x, M) = 1*, as otherwise *f=1* is not reached.
- We require inputs *x &neq; 0*, because applying posdivstep with *g=0* has no effect.
- We need to update the termination condition from *g=0* to *f=1*.

We account for the possibility of nonconvergence by only performing a bounded number of
posdivsteps, and then falling back to square-root based Jacobi calculation if a solution has not
yet been found.

The optimizations in sections 3-7 above are described in the context of the original divsteps, but
in the C implementation we also adapt most of them (not including "avoiding modulus operations",
since it's not necessary to track *d, e*, and "constant-time operation", since we never calculate
Jacobi symbols for secret data) to the posdivsteps version.

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