Quantum Artificial Life in an IBM Quantum Computer

We present the first experimental realization of a quantum artificial life algorithm in a quantum computer. The quantum biomimetic protocol encodes tailored quantum behaviors belonging to living systems, namely, self-replication, mutation, interaction between individuals, and death, into the cloud quantum computer IBM ibmqx4. In this experiment, entanglement spreads throughout generations of individuals, where genuine quantum information features are inherited through genealogical networks. As a pioneering proof-of-principle, experimental data fits the ideal model with accuracy. Thereafter, these and other models of quantum artificial life, for which no classical device may predict its quantum supremacy evolution, can be further explored in novel generations of quantum computers. Quantum biomimetics, quantum machine learning, and quantum artificial intelligence will move forward hand in hand through more elaborate levels of quantum complexity

Controlled nucleation of topological defects in the stripe domain patterns of Lateral multilayers with Perpendicular Magnetic Anisotropy: competition between magnetostatic, exchange and misfit interactions

Magnetic lateral multilayers have been fabricated on weak perpendicular magnetic anisotropy amorphous Nd-Co films in order to perform a systematic study on the conditions for controlled nucleation of topological defects within their magnetic stripe domain pattern. A lateral thickness modulation of period $w$ is defined on the nanostructured samples that, in turn, induces a lateral modulation of both magnetic stripe domain periods $\lambda$ and average in-plane magnetization component $M_{inplane}$. Depending on lateral multilayer period and in-plane applied field, thin and thick regions switch independently during in-plane magnetization reversal and domain walls are created within the in-plane magnetization configuration coupled to variable angle grain boundaries and disclinations within the magnetic stripe domain patterns. This process is mainly driven by the competition between rotatable anisotropy (that couples the magnetic stripe pattern to in-plane magnetization) and in-plane shape anisotropy induced by the periodic thickness modulation. However, as the structural period $w$ becomes comparable to magnetic stripe period $\lambda$, the nucleation of topological defects at the interfaces between thin and thick regions is hindered by a size effect and stripe domains in the different thickness regions become strongly coupled.Comment: 10 pages, 7 figures, submitted to Physical Review

Quantum autoencoders via quantum adders with genetic algorithms

The quantum autoencoder is a recent paradigm in the field of quantum machine learning, which may enable an enhanced use of resources in quantum technologies. To this end, quantum neural networks with less nodes in the inner than in the outer layers were considered. Here, we propose a useful connection between approximate quantum adders and quantum autoencoders. Specifically, this link allows us to employ optimized approximate quantum adders, obtained with genetic algorithms, for the implementation of quantum autoencoders for a variety of initial states. Furthermore, we can also directly optimize the quantum autoencoders via genetic algorithms. Our approach opens a different path for the design of quantum autoencoders in controllable quantum platforms

Exact solution of variable coefficient mixed hyperbolic partial differential problems

AbstractThis paper is concerned with the construction of exact series solution of mixed variable coefficient hyperbolic problems

Dental Treatment under General Anesthesia in Healthy and Medically Compromised/Developmentally Disabled Children: A Comparative Study

Aim: To compare the type, number of procedures and working time of dental treatment provided under dental general anesthesia (DGA) in healthy and medically compromised/developmentally disabled children (MCDD children). Design: This cross-sectional prospective study involved 80 children divided into two groups of 40 children each. Group 1 consisted of healthy and Group 2 consisted of MCDD children. Results: Healthy children needed more working time than MCDD children, the means being 161±7.9 and 84±5.7 minutes, respectively (P= 0.0001). Operative dentistry and endodontic treatments showed a significant statistical difference (P= 0.0001). The means of procedures were 17±5.0 for healthy children and 11±4.8 for MCDD children (P= 0.0001). Conclusions: Healthy children needed more extensive dental treatment than MCDD children under DGA. The information from this sample of Mexican children could be used as reference for determining trends both within a facility as well as in comparing facilities in cross-population studies