exploit symmetry in the hessian

[KristofferC]

Instead of relying on the Jacobian of gradient for the Hessian, explicitly seed dual numbers and only calculate the upper triangular part when chunking, gives ~2x speedup as input length becomes big

┌─────────────────────┬───────────────────┬───────────────────────┐
│      function       │         n         │        speedup        │
├─────────────────────┼───────────────────┼───────────────────────┤
│ rosenbrock / ackley │ 10 (single chunk) │ ~1.0x (no regression) │
├─────────────────────┼───────────────────┼───────────────────────┤
│ rosenbrock / ackley │ 30                │ 1.45x / 1.57x         │
├─────────────────────┼───────────────────┼───────────────────────┤
│ rosenbrock / ackley │ 100               │ 1.85x / 1.94x         │
└─────────────────────┴───────────────────┴───────────────────────┘

Fixes #836 cc @gdalle

Basically one-shotted by Claude and then decringified with gpt.

[codecov]

Codecov Report

❌ Patch coverage is 91.35802% with 7 lines in your changes missing coverage. Please review.
✅ Project coverage is 90.44%. Comparing base (569af35) to head (0091edd).

Files with missing lines	Patch %	Lines
src/hessian.jl	91.35%	7 Missing ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##           master     #837      +/-   ##
==========================================
- Coverage   90.68%   90.44%   -0.24%     
==========================================
  Files          11       11              
  Lines        1052     1120      +68     
==========================================
+ Hits          954     1013      +59     
- Misses         98      107       +9     

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