Consistency checks

B0 lifetime, dm and chi_d - Measure tau and dm both floating and with one fixed to PDG(BaBar?) value.
Split MC sample into data size samples - Can't do this too much with generics, signal MC is quite large.
MC truth fits - test event selection bias.
Counting experiment - ensure the values of tau, dm and chi_d are consistent.
MC counting to determine mistag, delta_mistag - compare counting/fit to MCtruth/full fit
Fit for dm based just on Dt shape - remove requirement that tau and dm be consistent. You can fit for dm using: just mixed event, just unmixed events, bRec, bbarRec,bTag,bbarTag.
Do fit broken down by tagging category - actually we will always do this, just make sure the results are consistent.
B0 vs B0bar - ensure dm and tau are consistent.
Resolution model - check the sensitivity of dm, tau to resolution model. Do the fit with GExp, 3G and maybe 2G also.
Mistag vs per-event-error - I assume we will use a functional form to describe the kaon mistag rate as a function of per-event-error. Check extreme values of the slope parameter in the mistag relation for its effect on dm, tau.

Systematic studies

Dt range - see how sensitive dm and tau are to cutting on Dt range.
Per-event-error range - how sensitive to the per-event-error cut at 1.8 ps.
Resolution function - how much does our choice of resolution function affect the result. If we fix some parameters - how much does that affect the result.
B+/B0 lifetime fraction - how does fixing this fraction affect results.
B+/B0 mistag rate fraction - how does this affect results.
z scale - standard number common to many analysis.
z boost - determine the bias due to our boost approximation and associated systematic.
beamspot position
background Dt distribution - done for each background