Iterative Phase Optimization of Elementary Quantum Error Correcting Codes

Performing experiments on small-scale quantum computers is certainly a challenging endeavor. Many parameters need to be optimized to achieve high-fidelity operations. This can be done efficiently for operations acting on single qubits, as errors can be fully characterized. For multiqubit operations, though, this is no longer the case, as in the most general case, analyzing the effect of the operation on the system requires a full state tomography for which resources scale exponentially with the system size. Furthermore, in recent experiments, additional electronic levels beyond the two-level system encoding the qubit have been used to enhance the capabilities of quantum-information processors, which additionally increases the number of parameters that need to be controlled. For the optimization of the experimental system for a given task (e.g., a quantum algorithm), one has to find a satisfactory error model and also efficient observables to estimate the parameters of the model. In this manuscript, we demonstrate a method to optimize the encoding procedure for a small quantum error correction code in the presence of unknown but constant phase shifts. The method, which we implement here on a small-scale linear ion-trap quantum computer, is readily applicable to other AMO platforms for quantum-information processing.

Optimization of Enzymes Inactivation in High Pressure Processes

The demand of highest quality foods in terms of taste and their properties preservation without the use of additives is constantly increasing. Consequently, new approaches to food processing have been developed, as for example high-pressure technology which has proven to be very valuable because it allows to maintain good properties of food like some vitamins and, at the same time, to reduce some undesirable bacteria. This technology avoids the use of high temperatures during the process (not like Pasteurization), which may have adverse effect on some nutritional properties of the food, its flavour, etc. The models for some enzymatic inactivations, which depend on the pressure and temperature profiles are presented. This work deals with the optimization of the inactivation of certain enzymes when high pressure treatment on food processing is applied. The optimization algorithms will minimize the inactivation not only of a certain isolated enzyme but also to several enzymes that can be involved simultaneously in the high-pressure process.