Performance versus `quadgk`

Hi, I made some benchmarks and noted that for 1-d integral `quadgk` is way more fast than `hquadrature`. Here is a simple example
```julia
julia> using HCubature, BenchmarkTools

julia> f() = hquadrature(t -> exp(-t)/t, 1, 100000)
f (generic function with 1 method)

julia> g() = HCubature.QuadGK.quadgk(t -> exp(-t)/t, 1, 100000)
g (generic function with 1 method)

julia> @btime f()
26.478 μs (1131 allocations: 31.97 KiB)
(0.21938393439552029, 1.3846093405775578e-9)

julia> @btime g()
10.078 μs (339 allocations: 8.02 KiB)
(0.2193839343955203, 1.3846093658126016e-9)
```
Is this difference on algorithm level or just because `quadgk` is internally optimized?

Thanks!

Start by reproducing the Julia benchmark in the issue and comparing hquadrature with HCubature.QuadGK.quadgk, including timings and allocations. Determine whether the difference comes from the algorithms or implementation overhead; the issue provides no files or tests to target.

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