0:00:04well can do all video abstract
0:00:09quantum effects are everywhere l
0:00:11from a solstice semiconductors to super conductors to chemistry and biology
0:00:17similarity the field of control is essential for most model technology for example regarding robotics
0:00:24died in systems micro controllers in chemical engineering
0:00:28naturally we would also like to extend controlled and then a scale systems and quantum
0:00:33dynamics in atoms molecules and quantum devices
0:00:36this can be done by engineering the hamiltonian that governs the evolution of the system
0:00:41my have the application of optimized extol of electromagnetic fields
0:00:47many applications of quantum control
0:00:49in this paper we focus on the implementation of robust quantum gates which ones realized
0:00:56with pave the way to full scale quantum computers
0:01:01and major obstacle for the realization of robust quantum gates uncontrollable interactions with the environment
0:01:07that lead to d coherence eliminating the system's not classical properties
0:01:13different types of environment in the markovian grapheme system back correlations tk fast so that
0:01:19the environment has effectively no memory of past interactions with the system
0:01:24many physical processes of this nature for example the spontaneous emission of falling tones and
0:01:30phone and what collusion of the facing atomic labels
0:01:33on the other hand it correlations between the system and that all significant on the
0:01:39times you know which the system impulse
0:01:41then the environment is non-markovian
0:01:44typically the case for small structured environments such as one almost is computed surrounded by
0:01:50weakly coupled noise q s found solid state systems
0:01:54both types of environment all important in practice leading us to the key question we
0:02:00study in this paper
0:02:03how to the differences between these environments affect our ability to coherently controls the dynamics
0:02:09specifically we address in the implementation of quantum gates in different environments using optimal control
0:02:15it's really filters finite time resolution they minimize kate errors using an iterative algorithm
0:02:21in each iteration the fields are updated four times at once as shell using a
0:02:25quasi newton message was extracted at gradient which is more efficient than the popular quote
0:02:30of method
0:02:32the performance of the algorithm is analyzed in terms of the minimum gate errors obtained
0:02:36in the convergence behavior
0:02:38a simple problems little variability is observed for more challenging task however frequent wrapping long
0:02:44tails a diminishing returns make sensible termination conditions and repeated runs essential
0:02:50to quantify the likelihood of success of a typical run and the time required on
0:02:54average to find a suitable field
0:02:57new notions of success rate and sixty four introduce
0:03:00density plots show then utilized to study the effects of parameters that risky operation times
0:03:06and initial field of these performance indicators
0:03:10we also consider how feels optimize in the closed system setting perform open systems
0:03:15in the non market in case of fields can be substantially improved by explicitly considering
0:03:20the environment
0:03:21well almost no improvement in the markovian case
0:03:25how does the controls work
0:03:27in the non-markovian case plots a trajectory plot shows that the improved performance controls
0:03:33is mainly due to suppression of indirect no skip the expectation that result from the
0:03:38closed system optimal the others are applied
0:03:41however certainly factors such as feel they could cause unwanted most cupid excitations that renders
0:03:47the controls completely ineffective
0:03:50i can be mitigated by explicitly considering leakage in the optimisation but at the expense
0:03:54of substantially increase kate operation time to control complexity
0:03:58as shown this demonstrated limited control robustness an underscore c important the system design and
0:04:04characterization for control