Additional low-discrepancy sequences for (hyper)cubic integration

Following #241 (lattice rules) -- since that's already moving forward in #293 --
I wanted to propose a few complementary low-discrepancy constructions that
aren't covered by lattice rules alone:

• Sobol' sequences -- digital net construction, widely used, extensible in
  n (unlike lattice rules, which need n fixed in advance for a given
  generating vector).
• Halton sequences -- radical-inverse construction, also extensible,
  simpler to construct than Sobol' but with somewhat worse discrepancy in
  higher dimensions.
• (Randomized) Latin Hypercube Sampling -- not itself a low-discrepancy
  sequence in the classical sense, but a well-established variance-reduction
  alternative to plain Monte Carlo (Stein, 1987; McKay, Beckman & Conover,
  1979), often used alongside QMC methods for the same integration problems.
• Korobov lattice rules -- as far as I can tell, #293 implements the
  general CBC-constructed lattice rules (via the Kuo/UNSW tabulated vectors).
  Korobov lattices are a restricted special case (generating vector
  z(a) = (1, a, a^2, ..., a^{d-1}) mod n, a single integer parameter a),
  which trades a smaller search space for near-instant table lookup and much
  smaller storage -- a lighter-weight complement to the general CBC lattice
  rather than a duplicate of it.

I've implemented all four of these from scratch already: Halton, Korobov
lattice rules, and randomized LHS for QMCPy
(merged), and Halton and rank-1 lattice sequences for
torchquad (open PR).

To keep review manageable, I'd plan to open a separate PR per sequence
rather than one large PR.

Would this be of interest? Happy to start whenever convenient, and to adjust
scope/order based on what's most useful for the library.