Long-Range Interaction between Charge and Spin Qubits in Quantum Dots

We analyze and give estimates for the long-distance coupling via floating metallic gates between different types of spin qubits in quantum dots made of different commonly used materials. In particular, we consider the hybrid, the singlet-triplet, and the spin-$1/2$ qubits, and the pairwise coupling between each type of these qubits with another hybrid qubit in GaAs, InAs, Si, and $\mathrm{Si_{0.9}Ge_{0.1}}$. We show that hybrid qubits can be capacitively coupled strongly enough to implement two-qubit gates, as long as the distance of the dots from the metallic gates is small enough. Thus, hybrid qubits are good candidates for scalable implementations of quantum computing in semiconducting nanostructures

Performance specifications for a meteorological satellite lidar Final report

Cirrus cloud cover observation capability and performance specifications for meteorological satellite lida

Electric Boolean games : redistribution schemes for resource-bounded agents

In Boolean games, agents uniquely control a set of propositional variables, and aim at achieving a goal formula whose realisation might depend on the choices the other agents make with respect to the variables they control. We consider the case in which assigning a value to propositional variables incurs a cost, and moreover, we assume agents to be restricted in their choice of assignments by an initial endowment: they can only make choices with a lower cost than this endowment. We then consider the possibility that endowments can be redistributed among agents. Different redistributions may lead to Nash equilibrium outcomes with very different properties, and so certain redistributions may be considered more attractive than others. In this context we study centralised redistribution schemes, where a system designer is allowed to redistribute the initial energy endowment among the agents in order to achieve desirable systemic properties. We also show how to extend this basic model to a dynamic variant in which an electric Boolean game takes place over a series of rounds

Heterogeneity aware fault tolerance for extreme scale computing

Upcoming Extreme Scale, or Exascale, Computing Systems are expected to deliver a peak performance of at least 10^18 floating point operations per second (FLOPS), primarily through significant expansion in scale. A major concern for such large scale systems, however, is how to deal with failures in the system. This is because the impact of failures on system efficiency, while utilizing existing fault tolerance techniques, generally also increases with scale. Hence, current research effort in this area has been directed at optimizing various aspects of fault tolerance techniques to reduce their overhead at scale. One characteristic that has been overlooked so far, however, is heterogeneity, specifically in the rate at which individual components of the underlying system fail, and in the execution profile of a parallel application running on such a system. In this thesis, we investigate the implications of such types of heterogeneity for fault tolerance in large scale high performance computing (HPC) systems. To that end, we 1) study how knowledge of heterogeneity in system failure likelihoods can be utilized to make current fault tolerance schemes more efficient, 2) assess the feasibility of utilizing application imbalance for improved fault tolerance at scale, and 3) propose and evaluate changes to system level resource managers in order to achieve reliable job placement over resources with unequal failure likelihoods. The results in this thesis, taken together, demonstrate that heterogeneity in failure likelihoods significantly changes the landscape of fault tolerance for large scale HPC systems

Collaborative beamforming schemes for wireless sensor networks with energy harvesting capabilities

In recent years, wireless sensor networks have attracted considerable attention in the research community. Their development, induced by technological advances in microelectronics, wireless networking and battery fabrication, is mainly motivated by a large number of possible applications such as environmental monitoring, industrial process control, goods tracking, healthcare applications, to name a few. Due to the unattended nature of wireless sensor networks, battery replacement can be either too costly or simply not feasible. In order to cope with this problem and prolong the network lifetime, energy efficient data transmission protocols have to be designed. Motivated by this ultimate goal, this PhD dissertation focuses on the design of collaborative beamforming schemes for wireless sensor networks with energy harvesting capabilities. On the one hand, by resorting to collaborative beamforming, sensors are able to convey a common message to a distant base station, in an energy efficient fashion. On the other, sensor nodes with energy harvesting capabilities promise virtually infinite network lifetime. Nevertheless, in order to realize collaborative beamforming, it is necessary that sensors align their transmitted signals so that they are coherently combined at the destination. Moreover, sensor nodes have to adapt their transmissions according to the amounts of harvested energy over time. First, this dissertation addresses the scenario where two sensor nodes (one of them capable of harvesting ambient energy) collaboratively transmit a common message to a distant base station. In this setting, we show that the optimal power allocation policy at the energy harvesting sensor can be computed independently (i.e., without the knowledge of the optimal policy at the battery operated one). Furthermore, we propose an iterative algorithm that allows us to compute the optimal policy at the battery operated sensor, as well. The insights gained by the aforementioned scenario allow us to generalize the analysis to a system with multiple energy harvesting sensors. In particular, we develop an iterative algorithm which sequentially optimizes the policies for all the sensors until some convergence criterion is satisfied. For the previous scenarios, this PhD dissertation evaluates the impact of total energy harvested, number of sensors and limited energy storage capacity on the system performance. Finally, we consider some practical schemes for carrier synchronization, required in order to implement collaborative beamforming in wireless sensor networks. To that end, we analyze two algorithms for decentralized phase synchronization: (i) the one bit of feedback algorithm previously proposed in the literature; and (ii) a decentralized phase synchronization algorithm that we propose. As for the former, we analyze the impact of additive noise on the beamforming gain and algorithm’s convergence properties, and, subsequently, we propose a variation that performs sidelobe control. As for the latter, the sensors are allowed to choose their respective training timeslots randomly, relieving the base station of the burden associated with centralized coordination. In this context, this PhD dissertation addresses the impact of number of timeslots and additive noise on the achieved received signal strength and throughputEn los últimos años, las redes de sensores inalámbricas han atraído considerable atención en la comunidad investigadora. Su desarrollo, impulsado por recientes avances tecnológicos en microelectrónica y radio comunicaciones, está motivado principalmente por un gran abanico de aplicaciones, tales como: Monitorización ambiental, control de procesos industriales, seguimiento de mercancías, telemedicina, entre otras. En las redes de sensores inalámbricas, es primordial el diseño de protocolos de transmisión energéticamente eficientes ya que no se contempla el reemplazo de baterías debido a su coste y/o complejidad. Motivados por esta problemática, esta tesis doctoral se centra en el diseño de esquemas de conformación de haz distribuidos para redes de sensores, en el que los nodos son capaces de almacenar energía del entorno, lo que en inglés se denomina energy harvesting. En primer lugar, esta tesis doctoral aborda el escenario en el que dos sensores (uno de ellos capaz de almacenar energía del ambiente) transmiten conjuntamente un mensaje a una estación base. En este contexto, se demuestra que la política de asignación de potencia óptima en el sensor con energy harvesting puede ser calculada de forma independiente (es decir, sin el conocimiento de la política óptima del otro sensor). A continuación, se propone un algoritmo iterativo que permite calcular la política óptima en el sensor que funciona con baterías. Este esquema es posteriormente generalizado para el caso de múltiples sensores. En particular, se desarrolla un algoritmo iterativo que optimiza las políticas de todos los sensores secuencialmente. Para los escenarios anteriormente mencionados, esta tesis evalúa el impacto de la energía total cosechada, número de sensores y la capacidad de la batería. Por último, se aborda el problema de sincronización de fase en los sensores con el fin de poder realizar la conformación de haz de forma distribuida. Para ello, se analizan dos algoritmos para la sincronización de fase descentralizados: (i) el algoritmo "one bit of feedback" previamente propuesto en la literatura, y (ii) un algoritmo de sincronización de fase descentralizado que se propone en esta tesis. En el primer caso, se analiza el impacto del ruido aditivo en la ganancia y la convergencia del algoritmo. Además, se propone una variación que realiza el control de lóbulos secundarios. En el segundo esquema, los sensores eligen intervalos de tiempo de forma aleatoria para transmitir y posteriormente reciben información de la estación base para ajustar sus osciladores. En este escenario, esta tesis doctoral aborda el impacto del número de intervalos de tiempo y el ruido aditivo sobre la ganancia de conformación

Understanding the apparent fractional charge of protons in the aqueous electrochemical double layer

A detailed atomic-scale description of the electrochemical interface is essential to the understanding of electrochemical energy transformations. In this work, we investigate the charge of solvated protons at the Pt(111) | H_2O and Al(111) | H_2O interfaces. Using semi-local density-functional theory as well as hybrid functionals and embedded correlated wavefunction methods as higher-level benchmarks, we show that the effective charge of a solvated proton in the electrochemical double layer or outer Helmholtz plane at all levels of theory is fractional, when the solvated proton and solvent band edges are aligned correctly with the Fermi level of the metal (E_F). The observed fractional charge in the absence of frontier band misalignment arises from a significant overlap between the proton and the electron density from the metal surface, and results in an energetic difference between protons in bulk solution and those in the outer Helmholtz plane

High Energy Physics Advisory Panel (HEPAP) - High Energy Physics Program informal long-range projections FY 1971-FY 1976, 1969 December

For more information about this item, visit https://archivesspace.mit.edu/repositories/2/archival_objects/25317

Modeling energy supply unit of ultra-low power devices with indoor photovoltaic harvesting

Challenges in the field of logistics have pushed development and integration of cyber-physical systems in these applications. PhyNode as one of these systems has shown promising results for enabling a transportation box with intelligence. However, engineering shortcomings during its development and implementation have shown potential for further research topics. Among them, balancing the Energy Supply Unit (ESU) to avoid periodic battery recharge is the main motivation of this work addressed by its modeling. For a systematic analysis of PhyNode's ESU, two types of models are developed for each of its three modules, including: Indoor photovoltaic harvesting (IPV), power management device and the battery. First type of models are computationally lightweight for on-board monitoring implementation. In contrary, system level detailed models are more advanced and computationally intensive. They are used to properly dimension the hardware or optimize the operational process during system design phase. At first IPV devices are analyzed extensively to highlight their differences from solar applications. In addition to the development of a high precision measurement platform for measurement of IPV behavior, collected data is used for model development. Due to wide range of signals, a normalized space is introduced in addition to guidelines for model's parameters estimation. Moreover, a new evaluation criteria is suggested enabling comparison of model's performance in different environmental situations. A battery measurement setup is introduced for analyzing battery with ultra-low power loads. In addition to the comparison of different battery identification methods, effect of aging on the battery performance has been analyzed. By measurement of PhyNode's load, both developed models are evaluated showing error less than 0.5% on estimation of the models' output. Furthermore, internal structure of power management device designed for ultra-low power applications is analyzed. Converter and maximum power point tracking as two main parts of this system are modeled separately. Despite suggestion of a partial model based on physical principles of converter, lack of design information leads to a black-box modeling approach. Therefore, two machine learning based models are developed for these parts. Combined model of them is tested on an evaluation data-set, showing a performance with a RMSE of 1.2%. Finally, a holistic model including all modules builds the overall structure of PhyNode's ESU. This model is tested with real data from different hardware combinations of PhyNode in action for long time periods showing a MAPE less than 1%. Due to the high accuracy of developed model, it is used for simulation of PhyNode in a real world scenarios. In addition, potentials of holistic model are shown by simulating energy balancing after different changes in either hardware or operational process of PhyNode

LIPIcs, Volume 251, ITCS 2023, Complete Volume

LIPIcs, Volume 251, ITCS 2023, Complete Volum