Tables sharing the same lde_size now reuse a single Arc<LdeTwiddles>
instead of each allocating their own copy. This avoids redundant twiddle
computation and allocation when multiple tables happen to have the same
trace length (e.g., all 2^19-row tables after the cap change).

Under the `parallel` feature, fold each conjugate pair concurrently
using `par_chunks(2).zip(inv_twiddles.par_iter())`, collecting into a
new Vec of half length. The sequential path (no `parallel` feature) is
unchanged. This avoids the index aliasing issue from an in-place
interleaved write.

Replace the per-row `Vec` allocation inside the iterator with a
thread-local buffer via Rayon's `map_init` (parallel path) or a single
buffer allocated outside the loop (sequential path). This avoids one
heap allocation per row during Merkle tree construction.