Andre R. R. Carvalho

Identifying and calibrating quantitative dynamical models for physical quantum systems is important for a variety of applications. Here we present a closed-loop Bayesian learning algorithm for estimating multiple unknown parameters in a dynamical model, using optimised experimental "probe" controls and measurement. The estimation algorithm is based on a Bayesian particle filter, and is designed to autonomously choose informationally-optimised probe experiments with which to compare to model predictions. We demonstrate the performance of the algorithm in both simulated calibration tasks and in an experimental single-qubit ion-trap system. Experimentally, we find that with 60x fewer samples, we exceed the precision of conventional calibration methods, delivering an approximately 93x improvement in efficiency (as quantified by the reduction of measurements required to achieve a target residual uncertainty and multiplied by the increase in accuracy). In simulated and experimental demonstrations, we see that successively longer pulses are selected as the posterior uncertainty iteratively decreases, leading to an exponential improvement in the accuracy of model parameters with the number of experimental queries.

We study a class of entangling gates for trapped atomic ions and demonstrate the use of numeric optimization techniques to create a wide range of fast, error-robust gate constructions. Our approach introduces a framework for numeric optimization using individually addressed, amplitude and phase modulated controls targeting maximally and partially entangling operations on ion pairs, complete multi-ion registers, multi-ion subsets of large registers, and parallel operations within a single register. Our calculations and simulations demonstrate that the inclusion of modulation of the difference phase for the bichromatic drive used in the Mølmer-Sørensen gate permits approximately time-optimal control across a range of gate configurations, and when suitably combined with analytic constraints can also provide robustness against key experimental sources of error. We further demonstrate the impact of experimental constraints such as bounds on coupling rates or modulation band-limits on achievable performance. Using a custom optimization engine based on TensorFlow we also demonstrate time-to-solution for optimizations on ion registers up to 20 ions of order tens of minutes using a local-instance laptop, allowing computational access to system-scales relevant to near-term trapped-ion devices.

Trapped ions are one of the most promising approaches for the realization of a universal quantum computer. Faster quantum logic gates could dramatically improve the performance of trapped-ion quantum computers, and require the development of suitable high repetition rate pulsed lasers. Here we report on a robust frequency upconverted fiber laser based source, able to deliver 2.5 ps ultraviolet (UV) pulses at a stabilized repetition rate of 300.00000 MHz with an average power of 190 mW. The laser wavelength is resonant with the strong transition in Ytterbium (Yb+) at 369.53 nm and its repetition rate can be scaled up using high harmonic mode locking. We show that our source can produce arbitrary pulse patterns using a programmable pulse pattern generator and fast modulating components. Finally, simulations demonstrate that our laser is capable of performing resonant, temperature-insensitive, two-qubit quantum logic gates on trapped Yb$^+$ ions faster than the trap period and with fidelity above 99%.

In composed quantum systems, the presence of local dissipative channels causes loss of coherence and entanglement at a rate that grows with the temperature of the reservoirs. However, here we show that if temperature is artificially added to the system, entanglement decay can be significantly slowed down or even suppressed conditioned on suitable local monitoring of the reservoirs. We propose a scheme to implement the joint reservoir monitoring applicable in different experimental setups like trapped ions, circuit and cavity QED or quantum dots coupled to nanowires and we analyze its general robustness against detection inefficiencies and non-zero temperature of the natural reservoir.