18,916 research outputs found
Experimentally Attainable Optimal Pulse Shapes Obtained with the Aid of Genetic Algorithms
We propose a methodology to design optimal pulses for achieving quantum
optimal control on molecular systems. Our approach constrains pulse shapes to
linear combinations of a fixed number of experimentally relevant pulse
functions. Quantum optimal control is obtained by maximizing a multi-target
fitness function with genetic algorithms. As a first application of the
methodology we generated an optimal pulse that successfully maximized the yield
on a selected dissociation channel of a diatomic molecule. Our pulse is
obtained as a linear combination of linearly chirped pulse functions. Data
recorded along the evolution of the genetic algorithm contained important
information regarding the interplay between radiative and diabatic processes.
We performed a principal component analysis on these data to retrieve the most
relevant processes along the optimal path. Our proposed methodology could be
useful for performing quantum optimal control on more complex systems by
employing a wider variety of pulse shape functions.Comment: 7 pages, 6 figure
Magnetic hallmarks of viscous electron flow in graphene
We propose a protocol to identify spatial hallmarks of viscous electron flow
in graphene and other two-dimensional viscous electron fluids. We predict that
the profile of the magnetic field generated by hydrodynamic electron currents
flowing in confined geometries displays unambiguous features linked to
whirlpools and backflow near current injectors. We also show that the same
profile sheds light on the nature of the boundary conditions describing
friction exerted on the electron fluid by the edges of the sample. Our
predictions are within reach of vector magnetometry based on nitrogen-vacancy
centers embedded in a diamond slab mounted onto a graphene layer.Comment: 5 pages, 6 figure
Self-similar transmission properties of aperiodic Cantor potentials in gapped graphene
We investigate the transmission properties of quasiperiodic or aperiodic
structures based on graphene arranged according to the Cantor sequence. In
particular, we have found self-similar behaviour in the transmission spectra,
and most importantly, we have calculated the scalability of the spectra. To do
this, we implement and propose scaling rules for each one of the fundamental
parameters: generation number, height of the barriers and length of the system.
With this in mind we have been able to reproduce the reference transmission
spectrum, applying the appropriate scaling rule, by means of the scaled
transmission spectrum. These scaling rules are valid for both normal and
oblique incidence, and as far as we can see the basic ingredients to obtain
self-similar characteristics are: relativistic Dirac electrons, a self-similar
structure and the non-conservation of the pseudo-spin. This constitutes a
reduction of the number of conditions needed to observe self-similarity in
graphene-based structures, see D\'iaz-Guerrero et al. [D. S. D\'iaz-Guerrero,
L. M. Gaggero-Sager, I. Rodr\'iguez-Vargas, and G. G. Naumis,
arXiv:1503.03412v1, 2015]
Revisiting the optical -symmetric dimer
Optics has proved a fertile ground for the experimental simulation of quantum
mechanics. Most recently, optical realizations of -symmetric
quantum mechanics have been shown, both theoretically and experimentally,
opening the door to international efforts aiming at the design of practical
optical devices exploiting this symmetry. Here, we focus on the optical
-symmetric dimer, a two-waveguide coupler were the materials show
symmetric effective gain and loss, and provide a review of the linear and
nonlinear optical realizations from a symmetry based point of view. We go
beyond a simple review of the literature and show that the dimer is just the
smallest of a class of planar -waveguide couplers that are the optical
realization of Lorentz group in 2+1 dimensions. Furthermore, we provide a
formulation to describe light propagation through waveguide couplers described
by non-Hermitian mode coupling matrices based on a non-Hermitian generalization
of Ehrenfest theorem.Comment: 25 pages, 12 figure
Supervised Quantum Learning without Measurements
We propose a quantum machine learning algorithm for efficiently solving a
class of problems encoded in quantum controlled unitary operations. The central
physical mechanism of the protocol is the iteration of a quantum time-delayed
equation that introduces feedback in the dynamics and eliminates the necessity
of intermediate measurements. The performance of the quantum algorithm is
analyzed by comparing the results obtained in numerical simulations with the
outcome of classical machine learning methods for the same problem. The use of
time-delayed equations enhances the toolbox of the field of quantum machine
learning, which may enable unprecedented applications in quantum technologies
Stratified decision forests for accurate anatomical landmark localization in cardiac images
Accurate localization of anatomical landmarks is an important step in medical imaging, as it provides useful prior information for subsequent image analysis and acquisition methods. It is particularly useful for initialization of automatic image analysis tools (e.g. segmentation and registration) and detection of scan planes for automated image acquisition. Landmark localization has been commonly performed using learning based approaches, such as classifier and/or regressor models. However, trained models may not generalize well in heterogeneous datasets when the images contain large differences due to size, pose and shape variations of organs. To learn more data-adaptive and patient specific models, we propose a novel stratification based training model, and demonstrate its use in a decision forest. The proposed approach does not require any additional training information compared to the standard model training procedure and can be easily integrated into any decision tree framework. The proposed method is evaluated on 1080 3D highresolution and 90 multi-stack 2D cardiac cine MR images. The experiments show that the proposed method achieves state-of-theart landmark localization accuracy and outperforms standard regression and classification based approaches. Additionally, the proposed method is used in a multi-atlas segmentation to create a fully automatic segmentation pipeline, and the results show that it achieves state-of-the-art segmentation accuracy
Hermite Coherent States for Quadratic Refractive Index Optical Media
Producción CientíficaLadder and shift operators are determined for the set of Hermite–Gaussian modes associated with an optical medium with quadratic refractive index profile. These operators allow to establish irreducible representations of the su(1, 1) and su(2) algebras. Glauber coherent states, as well as su(1, 1) and su(2) generalized coherent states, were constructed as solutions of differential equations admitting separation of variables. The dynamics of these coherent states along the optical axis is also evaluated.MINECO grant MTM2014-57129-C2-1-P and Junta de Castilla y Leon grant VA057U16
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