Add A=1 boundary conditions

[Radonirinaunimi]

A constraint that we should impose at the level of the fit is the boundary condition $F_i(x, Q^2, A=1)=F_i^p(x, Q^2)$ which can be implemented as follows (adding this here in order to not forget once the matching is done):

$$ \chi^2 \longleftarrow \chi^2 + \lambda{\mathrm{BC}} \sum{i} \sum_{j}^{nx} \sum{k}^{n_Q} \left( F_i(x_j, Q_k^2, A=1) - F_i^p(x_j, Q_k^2) \right)^2 $$

[RoyStegeman]

We should be able to get a covmat using the theory predictions and calculating correlations by summing over replicas. Perhaps we should also include the MHOU.

Anyway, my point is that we don't need lambda but can just calculate the chi2 also for the matching with yadism, so no need to make adjustments to the code.

[Radonirinaunimi]

We should be able to get a covmat using the theory predictions and calculating correlations by summing over replicas. Perhaps we should also include the MHOU.

Anyway, my point is that we don't need lambda but can just calculate the chi2 also for the matching with yadism, so no need to make adjustments to the code.

Yep, this way of doing it I do agree (as mentioned in the chat).

[RoyStegeman]

Ah okay, sorry, hadn't understood you were talking about generating covmats. But good, then we agree on what to do!