Feature Request: mix arguments of different-sized arrays (& floats)? about iminuit HOT 3 OPEN

Hi, I considered a similar feature every now and again, but there didn't seem to be a good enough use case for putting in the time.

evermore sounds like an interesting library, I considered writing something like that myself (as I am also a fan of JAX).

If you have differentiable likelihoods in JAX, I don't see why you would need iminuit. You can use the optax minimizers and you can compute uncertainties as well, at least the analog to the HESSE algorithm in MINUIT. You need to compute the hessian at the minimum with JAX and invert it. If your original function has a negative log-likelihood, then this produces the covariance matrix of the parameters.

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Hi @HDembinski,

thank you very much for your reply :)

Indeed it is possible to just use first order minimizer and to compute the hessian at the minimum with JAX and invert it. However, I am currently in the process of comparing evermore's features with similar tools. These tools always/only use Minuit for minimization, so a fair comparison of e.g. a likelihood profile between evermore and these tools would be to use the same minimizer.
Apart from that I received general feedback that people like to use Minuit because of its robustness and its potential to reach the minimum faster than 1st order minimizer.

These two points are my main motivation to use iminuit with evermore.

Best, Peter

PS: But I agree fully with you... I personally had a pretty robust and fast experience with optax.sgd so far - even for HEP-like fitting problems.

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Regarding BarlowBeeston, I recommend to have a look at our new method if you are not already aware of it. It is implemented as the default in the class Template and we also published a paper about it.

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