Unveiling the Effect of Magnetic Noise in the Coherence of Single-Molecule Quantum Processors

Quantum bits (qubits) constitute the most elementary building-blocks of any quantum technology, where information is stored and processed in the form of quantum superpositions between discrete energy levels. In particular, the fabrication of quantum processors is a key long-term goal that will allow us conducting specific tasks much more efficiently than the most powerful classical computers can do. Motivated by recent experiments in which three addressable spin qubits are defined on a potential single-molecule quantum processor, namely the [Gd(H2O)P5W30O110]12− polyoxometalate, we investigate the decohering effect of magnetic noise on the encoded quantum information. Our state-of-the-art model, which provides more accurate results than previous estimates, show a noticeable contribution of magnetic noise in limiting the survival timescale of the qubits. Yet, our results suggest that it might not be the only dephasing mechanism at play but other mechanisms, such as lattice vibrations and physical movement of magnetic nuclei, must be considered to understand the whole decoherence process

Spin Relaxation and Coherence in Molecular Nanomagnets and Molecular Spin Qubits

Uno de los bloques de construcción más prometedores para almacenamiento y procesamiento de información son los llamados nanoimanes moleculares y qubits de espín molecular. Estos sistemas moleculares cero-dimensionales exhiben fenómenos magnéticos interesantes, donde la información se codifica en sus niveles de energía de espín. Debido a la dificultad de aislar completamente un sistema mecano-cuántico, interacciones descontroladas con el entorno circundante pueden dañar la información ya sea guardada o bajo procesamiento en estos sistemas. Por tanto, con el fin de construir nanoimanes moleculares y qubits de espín molecular capaces de satisfacer las exigencias más desafiantes ya sean actuales o futuras, uno primero necesita desarrollar un marco de trabajo racional para saber cómo hay que diseñar un sistema dado tan desacoplado de los efectos perjudiciales de su entorno como sea posible. En esta tesis, llevamos a cabo una exploración teórica de algunos de los mecanismos más importantes que contribuyen a la relajación de espín, es decir, el colapso de la información guardada y procesada en los sistemas mencionados arriba. Pretendemos desarrollar métodos de primeros principios y eficientes ideados primero para cuantificar el daño de estos mecanismos, y luego para proporcionar reglas sintéticas para re-diseñar y mejorar un sistema dado en el laboratorio. Aplicaremos y testaremos nuestros novedosos métodos a un conjunto representativo de los nanoimanes moleculares y qubits de espín molecular más interesantes y prometedores. Con el propósito de facilitar un uso sistemático de estos métodos a cualquier investigador interesado, también desarrollamos y proporcionamos un marco de trabajo computacional que incorpora los modelos teóricos aquí desarrollados

Decoherence from dipolar interspin interactions in molecular spin qubits

The realization of spin-based logical gates crucially depends on magnetically coupled spin qubits. Thus, understanding decoherence when spin qubits are in close proximity will become a roadblock to overcome. Herein, we propose a method free of fitting parameters to evaluate the qubit phase memory time Tm in samples with high electron spin concentrations. The method is based on a model aimed to estimate magnetic nuclear decoherence [P. C. E. Stamp and I. S. Tupitsyn, Phys. Rev. B 69, 014401 (2004)]. It is applied to a ground-spin J=8 magnetic molecule 1 displaying atomic clock transitions, namely [HoIII(W5O18)2]9−, which remarkably increase Tm at unusually high electron-spin concentrations. Our approach unveils the causes that limit the coherence reached at the clock transitions in challenging systems such as 1, where recent models fail

Quantum Error Correction with magnetic molecules

Quantum algorithms often assume independent spin qubits to produce trivial $|\uparrow\rangle=|0\rangle$, $|\downarrow\rangle=|1\rangle$ mappings. This can be unrealistic in many solid-state implementations with sizeable magnetic interactions. Here we show that the lower part of the spectrum of a molecule containing three exchange-coupled metal ions with $S=1/2$ and $I=1/2$ is equivalent to nine electron-nuclear qubits. We derive the relation between spin states and qubit states in reasonable parameter ranges for the rare earth $^{159}$Tb$^{3+}$ and for the transition metal Cu$^{2+}$, and study the possibility to implement Shor's Quantum Error Correction code on such a molecule. We also discuss recently developed molecular systems that could be adequate from an experimental point of view.Comment: 5 pages, 3 figures, 2 table

Novel method for vehicle and pedestrian detection based on information fusion

A novel approach for vehicle and pedestrian detection based on data fusion techniques is presented. The work fuses information from a 2D laser scanner and a computer camera, to provide detection and classification of vehicles and pedestrians in road environments. Thanks to the data fusion approach, the limitations of each sensor are overcome. Thus reliable system is provided, fulfilling the demands of road safety applications. Classification is performed using each sensor independently. Laser scanner approach is based in pattern matching and vision approach is based in the classical Histogram of Oriented Gradients features approach. A higher stage performs data fusion using Kalman Filter and Global Nearest Neighbors.This work was supported by the Spanish Government through the Cicyt projects (GRANT TRA2010-20225-C03-01) and (GRANT TRA 2011-29454-C03-02). CAM through SEGAUTO-II (S2009/DPI-1509)

Discrete features for rapid pedestrian detection in infrared images

Proceeding of: 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems October 7-12, 2012. Vilamoura, Algarve, Portugal.In this paper the authors propose a pedestrian detection system based on discrete features in infrared images. Unique keypoints are searched for in the images around which a descriptor, based on the histogram of the phase congruency orientation, is extracted. These descriptors are matched with defined regions of the body of a pedestrian. In case of a match, it creates a region of interest in the image, which is classified as a pedestrian / non-pedestrian by an SVM classifier. The pedestrian detection system has been tested in an advanced driver assistance system for urban driving.This work was supported by the Spanish Government through the Cicyt projects FEDORA (GRANT TRA2010-20225-C03- 01) and Driver Distraction Detector System (GRANT TRA2011-29454-C03-02), and by the Comunidad de Madrid through the project SEGVAUTO (S2009/DPI- 1509).Publicad

Contrast invariant features for human detection in far infrared images

Proceeding of: 2012 IEEE Intelligent Vehicles Symposium (IV), Alcalá de Henares, Spain, June 3-7, 2012In this paper a new contrast invariant descriptor for human detection in long-wave infrared images is proposed. It exploits local information histogram of orientations of phase coherence. Contrast in infrared images depends on the temperature of the object and the background, which makes gradient based descriptors less robust, especially in daylight conditions. The objective is to obtain a scale, brightness and contrast invariant descriptor that can successfully detect pedestrians in images taken with a cheap, temperature-sensitive, uncooled microbolometer. The descriptor, packed into grids is feed to a Support Vector Machine classifier. The algorithm has been tested in night and day sequences and its performance is compared with a day only descriptor: the histogram of oriented features (HOG).This work was supported by the Spanish Government through the Cicyt projects FEDORA (GRANT TRA2010- 20225-C03-01) and VIDAS-Driver (GRANT TRA2010- 21371-C03-02), and the Comunidad de Madrid through the project SEGVAUTO (S2009/DPI-1509).Publicad

Detección y localización de obstáculos mediante U-V Disparity con CUDA

Tradicionalmente la detección de obstáculos es un tema de investigación de gran interés en visión por computador aplicada tanto a la navegación de robots, como a los sistemas avanzados de ayuda a la conducción (ADAS). Aunque otras tecnologías como por ejemplo el láser, presentan buenos resultados para detectar obstáculos en entornos urbanos, la visión por computador proporciona información 2D &- ó 3D con visión estéreo &- que mejora la interpretación del entorno en exteriores. En este artículo se presenta una implementación en tiempo real de la construcción del mapa denso de disparidad y del U-V disparity, que son utilizados para la detección y localización de obstáculos. Para minimizar los efectos sobre el tiempo de cómputo que ocasionan tanto la construcción del mapa denso de disparidad, como la del U-V disparity, se han implementado ambos mediante el uso de GPUs (Unidades de Procesamiento Gráfico) por su alto rendimiento con algoritmos paralelizables.Publicad