should compute the discrete logarithm of

). Right now, there are parameters only for primes p of around 30, 60, or 155 digits (to be checked in params_dl/ subdirectory). If no target is given, then the output is a file containing the virtual logarithms of all the factor base elements. More flexibility is possible. An example of parameter file is given in parameters/dlp/param.p60. The main difference is that the lines related to characters and sqrt disappear and that there is an additional block of parameters related to individual logarithms. After the computation is finished, it is possible to run again the cado-nfs.py script, with a different target: only the last step will be run. For ensuring that the precomputed data is really used, copy-paste the command-line indicated in the output of the first computation that contains "If you want to compute a new targetâ€¦", and set the new target at the end. Note: the logarithms are given in an arbitrary base. If you want to define them with respect to a specific generator g, then you'll have to compute the logarithm of g and then divide all the logs by this value. **** Using non-linear polynomials Just like for factorization, it is possible to use two non-linear polynomials for DLP. However, the polynomial selection is not automatic in that case: the user must provide the polynomial file. Also, the current descent script will not work. See README.nonlinear for an example of importing a polynomial file with 2 non-linear polynomials. An important issue is that since the descent is not yet functional for this case, the script has no way to check the results if there is no linear polynomial. A good idea is to set tasks.reconstructlog.partial = false so that many consistency checks are performed while using all the relations that were deleted during the filter. **** Discrete logarithms in GF(p^k) for small k The algorithm works "mutatis mutandis" for discrete logarithm computations in GF(p^k). The only difference is that the two polynomials must have a common irreducible factor of degree k over GF(p). Polynomial selection for this case is not yet included, so you must build them by yourself, based on constructions available in the literature. Also the individual logarithm has to be implemented for that case. For DLP in GF(p^2), things are sligthly more integrated: ./cado-nfs.py

-dlp -ell