Same strategy as for D⁺ :

1. study the track significance S_t = DCA/σ_DCA for background (hijing files used for mixing) and for signal; (single Λ_c per event, power-law pt, 50k)
2. once a possible cut is found, run the analysis code with this cut and study the distance of daughters to secondary vertex (dca_1V)
3. once a possible cut is found, rerun over the whole sample

1. track significance S_t = DCA/σ_DCA

Fig. 1 : S_t distribution for various cuts

[all the plots below are done for the kaon daughter]

Fig. 2 : same as Fig.1 but zoomed.

A possible cut (right panel) is S_t > 1.5 

note : it's lower than for the D⁺ cut.

I also check that the pt distribution of tracks is the same , otherwise the cut could be biased

Fig. 3 : P_t distribution of kaon daughter

2. DCA of daughters to the secondary vertex

Fig. 4 : DCA of daughters to secondary vertex for background and signal

Fig. 5 : DCA of daughters to secondary vertex for background and signal with same cuts when running the analysis code

Fig. 5 is integrated over all P_t but a possible cut would be DCA_SV < 40 μm

3. Preliminary plots for Λ_c

As mentioned previously, I've run with the following cuts :

• signs of tracks fixed 
• S_t = DCA/σ > 1.5
• dca_SV < 50 μm (I kept it loose for a first pass)
• not all data (~7.5k over 10k events)

 Fig. 6 : invariant mass for several cuts combinations [see text below]

From left to right , top to bottom :

1. |nσ|< 2
2. |nσ|< 2 && DecayLength >  100 μm
3. |nσ|< 2 && DecayLength >  200 μm
4. |nσ|< 2 && DecayLength/σ_DecayLength >0
5. |nσ|< 2 && DecayLength/σ_DecayLength >5
6. |nσ|< 2 && DecayLength/σ_DecayLength >7

Fig. 7 : same as Fig. 6 but with the constraint DCASV [of daughters] < 40 μm [was < 50 μm for Fig. 6]