  Long global gyrokinetic turbulence simulations are particularly challenging
in situations where the system deviates strongly from its initial state and
when fluctuation level are high e.g. in strong gradient regions. For
Particle-in-Cell simulations, statistical sampling noise accumulation from
large marker weights due to large deviations from the control variate of a
delta-f scheme make such simulations often impractical. An adaptive control
variate in the form of a flux-surface-averaged Maxwellian with a time-dependent
temperature profile is introduced in an attempt to alleviate the former
problem. Under simplified collisionless physics, this adaptive delta-f scheme
is shown to reduce noise accumulation in the zonal flows and the simulated heat
flux in a quasi-steady turbulent state. The method also avoids the collapse of
the signal-to-noise ratio which occurs in the standard non-adaptive scheme, and
therefore, allows one to reach numerically converged results even with lower
marker numbers.
