$\sqrt{s}=7\,\mathrm{TeV}$. The central jet is defined to lie within the pseudo-rapidity interval $\left|\eta_{c}\right|<2.8$ while the forward has to lie within $4.9>\left|\eta_{f}\right|>3.2$. Both jets are high-$p_{T}$ jets with $p_{T}>35\,\mathrm{GeV}$. The jets were reconstructed using anti-$k_{T}$ algorithm with radius $R=0.5$. The data samples consist in jet $p_{T}$ spectra for forward and for central jets, $d\sigma_{S}/dp_{T}\Delta\eta_{S}$ with $S=f,c$. There are in total 12 data bins for both forward and central jets.

We have applied the following fitting procedure. For each existing experimental data bin $B$ we produce a 2-dimensional normalized histogram $\mathcal{H}^{B}$ with bins in $x$ and $k_{T}$, such that the cross section can be calculated as $$\sigma^{B}=\sum_{i,j}\mathcal{H}_{ij}^{B}\mathcal{F}\left(x\left(i\right),k_{T}\left(j\right)\right),\label{eq:Fit1}$$ where $i,j$ enumerate the bins in $\left(x,k_{T}\right)$. To make the histograms $\mathcal{H}^{B}$ we

1.  generate Monte Carlo events for the process under consideration with $\mathcal{F}=\mathcal{F}^{*}$, where $\mathcal{F}^{*}$ is a relatively “broad” trial UGD (evolving according to one of the scenarios \[enu:pure-BFKL-equation\]-\[enu:BFKLCDS\]),

2.  make histograms $\mathfrak{h}^{B}$ in $\left(x,k_{T}\right)$ of contributions to each data bin $B$,

3.  divide by $\mathcal{F}^{*}\left(x,k_{T}\right)$, i.e. $\mathcal{H}_{ij}^{B}=\mathfrak{h}_{ij}^{B}/\mathcal{F}^{*}\left(x\left(i\right),k_{T}\left(j\right)\right)$.

Hence, in principle $\mathcal{H}^{B}$ are independent of $\mathcal{F}^{*}$ used for their generation and are calculated only once. This is advantageous, as the hard cross section calculation is costly in CPU time. The latter is calculated 