Nature does not rely on long-lived electronic quantum coherence for photosynthetic energy transfer

During the first steps of photosynthesis, the energy of impinging solar photons is transformed into electronic excitation energy of the light-harvesting biomolecular complexes. The subsequent energy transfer to the reaction center is commonly rationalized in terms of excitons moving on a grid of biomolecular chromophores on typical timescales [Formula: see text]100 fs. Today's understanding of the energy transfer includes the fact that the excitons are delocalized over a few neighboring sites, but the role of quantum coherence is considered as irrelevant for the transfer dynamics because it typically decays within a few tens of femtoseconds. This orthodox picture of incoherent energy transfer between clusters of a few pigments sharing delocalized excitons has been challenged by ultrafast optical spectroscopy experiments with the Fenna-Matthews-Olson protein, in which interference oscillatory signals up to 1.5 ps were reported and interpreted as direct evidence of exceptionally long-lived electronic quantum coherence. Here, we show that the optical 2D photon echo spectra of this complex at ambient temperature in aqueous solution do not provide evidence of any long-lived electronic quantum coherence, but confirm the orthodox view of rapidly decaying electronic quantum coherence on a timescale of 60 fs. Our results can be considered as generic and give no hint that electronic quantum coherence plays any biofunctional role in real photoactive biomolecular complexes. Because in this structurally well-defined protein the distances between bacteriochlorophylls are comparable to those of other light-harvesting complexes, we anticipate that this finding is general and directly applies to even larger photoactive biomolecular complexes

Global Routing Protocols for Wireless Body Area Networks

This work primarily consists of two parts. The first part deals with a wireless body area network with battery operated nodes. Global routing protocols are considered. The Dijkstra`s algorithm was modified using a novel link cost function in order to perform energy balancing across the network. The proposed protocol makes optimal use of the network energy and increases the network lifetime. Hardware experiments involving multiple nodes and an access point are performed to gather wireless channel information. Performance of two different types of network architectures is evaluated viz. on-body access point and off-body access point architectures. Results show up to 40% increase in average network lifetime with modest average increase of 0.4 dB in energy per bit. Proposed protocol lessens the need to recharge batteries frequently and as all the nodes deplete their energy source at the same time due to energy balancing, recharging can be done for all the batteries at the same time instead of recharging them one at a time. Network connectivity is evaluated using outage as a metric. Results show the cut-off effect which signifies the minimum amount of transmission power required to achieve reliable communication. The advantages of an off-body access point are demonstrated. The second part presents a global routing protocol based on Dijkstra`s algorithm for wireless body area networks with energy harvesting constraints. The protocol dynamically modifies routing trees based on available energy accumulated through energy harvesting. Various harvesting methods are considered. The results show that low data-rate applications are achievable using existing energy harvesting techniques while high data-rate applications call for advancements in these methods

Dinámica estocástica en física y biología

Tesis de la Universidad Complutense de Madrid, Facultad de Ciencias Físicas, Departamento de Estructura de la Materia, Física Térmica y Electrónica, leída el 26-10-2018Stochastic processes are present in virtually any field of science. Actually, in general deterministic processes are no more than an approximation of more complex stochastic processes in some regime of validity. In the present thesis, we will study some systems that appear in Physics and Biology where the presence of these stochastic processes plays a major role. First, we will study the Brownian ratchet systems, which are able to generate a directed motion simply by rectifying the thermal fluctuations to which Brownian particles are subjected. These Brownian ratchets began to be studied in the field of Statistical Physics as a Gedanken experiment that apparently broke the Second Law of Thermodynamics. Later they were applied to study the operation of some molecular motors. In this thesis we will study different types of Brownian ratchets, characterizing the average flux, the efficiency, and the quality of the transport of particles they produce..En prácticamente cualquier rama de la ciencia están presentes los procesos estocásticos. De hecho, en general los procesos deterministas no son más que una aproximación de procesos estocásticos más complejos en algún régimen de validez. En la presente tesis, estudiaremos algunos sistemas que aparecen en Física y Biología donde la presencia de dichos procesos es crucial.Primero, estudiaremos los conocidos como trinquetes brownianos, que son capaces de generar movimiento dirigido simplemente a través de la rectificación de las fluctuaciones térmicas a las que se ven sometidas las partículas Brownianas. Estos trinquetes Brownianos se empezaron a estudiar en el campo de la Física Estadística como un experimento mental que aparentemente rompía la Segunda Ley de la Termodinámica. Sin embargo, más adelante se ha visto que pueden ser aplicados para estudiar el funcionamiento de algunos motores moleculares. En esta tesis estudiaremos distintos tipos de trinquetes Brownianos, caracterizando el flujo medio, la eficiencia, y la calidad del transporte de partículas que producen...Depto. de Estructura de la Materia, Física Térmica y ElectrónicaFac. de Ciencias FísicasTRUEunpu

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig