[BUG] Complex vjps are wrong for arcsin/arccos/arctan/arcsinh/arccosh/arctanh (missing conjugate)

Describe the bug

The inverse trigonometric / hyperbolic ops return the wrong gradient for complex inputs: their vjp delegates to their jvp, so the conjugate is dropped. For a holomorphic f the vjp must be cotangent * conj(f'(z)).

Affected: arccos, arccosh, arcsin, arcsinh, arctan, arctanh.

This is the same issue fixed for square/sin/tanh/… in #3766.

To Reproduce

import mlx.core as mx
z = mx.array(0.3 + 0.2j, mx.complex64)
g = mx.array(1.0 + 1.0j, mx.complex64)
vjp = mx.vjp(mx.arctan, [z], [g])[1][0]
expected = g * mx.conj(1 / (1 + z**2))   # cotangent * conj(f'(z))
print(vjp, expected)   # differ

Expected behavior

vjp == cotangent * conj(f'(z)), consistent with mx.exp/mx.log and finite differences.

Desktop

• OS: macOS
• Version: main (0.32.0.dev)

Start with the mx.vjp and affected inverse trigonometric and hyperbolic operations described in the issue, then reproduce the complex arctan case from the example. Check the existing implementation and tests for mx.exp, mx.log, and the fix referenced in #3766. Done means all six listed operations produce the conjugated derivative for complex inputs and agree with finite differences.