10 resultados para inter-area oscillation frequency

em CaltechTHESIS


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Experimental demonstrations and theoretical analyses of a new electromechanical energy conversion process which is made feasible only by the unique properties of superconductors are presented in this dissertation. This energy conversion process is characterized by a highly efficient direct energy transformation from microwave energy into mechanical energy or vice versa and can be achieved at high power level. It is an application of a well established physical principle known as the adiabatic theorem (Boltzmann-Ehrenfest theorem) and in this case time dependent superconducting boundaries provide the necessary interface between the microwave energy on one hand and the mechanical work on the other. The mechanism which brings about the conversion is another known phenomenon - the Doppler effect. The resonant frequency of a superconducting resonator undergoes continuous infinitesimal shifts when the resonator boundaries are adiabatically changed in time by an external mechanical mechanism. These small frequency shifts can accumulate coherently over an extended period of time to produce a macroscopic shift when the resonator remains resonantly excited throughout this process. In addition, the electromagnetic energy in s ide the resonator which is proportional to the oscillation frequency is al so accordingly changed so that a direct conversion between electromagnetic and mechanical energies takes place. The intrinsically high efficiency of this process is due to the electromechanical interactions involved in the conversion rather than a process of thermodynamic nature and therefore is not limited by the thermodynamic value.

A highly reentrant superconducting resonator resonating in the range of 90 to 160 MHz was used for demonstrating this new conversion technique. The resonant frequency was mechanically modulated at a rate of two kilohertz. Experimental results showed that the time evolution of the electromagnetic energy inside this frequency modulated (FM) superconducting resonator indeed behaved as predicted and thus demonstrated the unique features of this process. A proposed usage of FM superconducting resonators as electromechanical energy conversion devices is given along with some practical design considerations. This device seems to be very promising in producing high power (~10W/cm^3) microwave energy at 10 - 30 GHz.

Weakly coupled FM resonator system is also analytically studied for its potential applications. This system shows an interesting switching characteristic with which the spatial distribution of microwave energies can be manipulated by external means. It was found that if the modulation was properly applied, a high degree (>95%) of unidirectional energy transfer from one resonator to the other could be accomplished. Applications of this characteristic to fabricate high efficiency energy switching devices and high power microwave pulse generators are also found feasible with present superconducting technology.

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Hair cells from the bull frog's sacculus, a vestibular organ responding to substrate-borne vibration, possess electrically resonant membrane properties which maximize the sensitivity of each cell to a particular frequency of mechanical input. The electrical resonance of these cells and its underlying ionic basis were studied by applying gigohm-seal recording techniques to solitary hair cells enzymatically dissociated from the sacculus. The contribution of electrical resonance to frequency selectivity was assessed from microelectrode recordings from hair cells in an excised preparation of the sacculus.

Electrical resonance in the hair cell is demonstrated by damped membrane-potential oscillations in response to extrinsic current pulses applied through the recording pipette. This response is analyzed as that of a damped harmonic oscillator. Oscillation frequency rises with membrane depolarization, from 80-160 Hz at resting potential to asymptotic values of 200-250 Hz. The sharpness of electrical tuning, denoted by the electrical quality factor, Qe, is a bell-shaped function of membrane voltage, reaching a maximum value around eight at a membrane potential slightly positive to the resting potential.

In whole cells, three time-variant ionic currents are activated at voltages more positive than -60 to -50 mV; these are identified as a voltage-dependent, non-inactivating Ca current (Ica), a voltage-dependent, transient K current (Ia), and a Ca-dependent K current (Ic). The C channel is identified in excised, inside-out membrane patches on the basis of its large conductance (130-200 pS), its selective permeability to Kover Na or Cl, and its activation by internal Ca ions and membrane depolarization. Analysis of open- and closed-lifetime distributions suggests that the C channel can assume at least two open and three closed kinetic states.

Exposing hair cells to external solutions that inhibit the Ca or C conductances degrades the electrical resonance properties measured under current-clamp conditions, while blocking the A conductance has no significant effect, providing evidence that only the Ca and C conductances participate in the resonance mechanism. To test the sufficiency of these two conductances to account for electrical resonance, a mathematical model is developed that describes Ica, Ic, and intracellular Ca concentration during voltage-clamp steps. Ica activation is approximated by a third-order Hodgkin-Huxley kinetic scheme. Ca entering the cell is assumed to be confined to a small submembrane compartment which contains an excess of Ca buffer; Ca leaves this space with first-order kinetics. The Ca- and voltage-dependent activation of C channels is described by a five-state kinetic scheme suggested by the results of single-channel observations. Parameter values in the model are adjusted to fit the waveforms of Ica and Ic evoked by a series of voltage-clamp steps in a single cell. Having been thus constrained, the model correctly predicts the character of voltage oscillations produced by current-clamp steps, including the dependencies of oscillation frequency and Qe on membrane voltage. The model shows quantitatively how the Ca and C conductances interact, via changes in intracellular Ca concentration, to produce electrical resonance in a vertebrate hair cell.

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Two trends are emerging from modern electric power systems: the growth of renewable (e.g., solar and wind) generation, and the integration of information technologies and advanced power electronics. The former introduces large, rapid, and random fluctuations in power supply, demand, frequency, and voltage, which become a major challenge for real-time operation of power systems. The latter creates a tremendous number of controllable intelligent endpoints such as smart buildings and appliances, electric vehicles, energy storage devices, and power electronic devices that can sense, compute, communicate, and actuate. Most of these endpoints are distributed on the load side of power systems, in contrast to traditional control resources such as centralized bulk generators. This thesis focuses on controlling power systems in real time, using these load side resources. Specifically, it studies two problems.

(1) Distributed load-side frequency control: We establish a mathematical framework to design distributed frequency control algorithms for flexible electric loads. In this framework, we formulate a category of optimization problems, called optimal load control (OLC), to incorporate the goals of frequency control, such as balancing power supply and demand, restoring frequency to its nominal value, restoring inter-area power flows, etc., in a way that minimizes total disutility for the loads to participate in frequency control by deviating from their nominal power usage. By exploiting distributed algorithms to solve OLC and analyzing convergence of these algorithms, we design distributed load-side controllers and prove stability of closed-loop power systems governed by these controllers. This general framework is adapted and applied to different types of power systems described by different models, or to achieve different levels of control goals under different operation scenarios. We first consider a dynamically coherent power system which can be equivalently modeled with a single synchronous machine. We then extend our framework to a multi-machine power network, where we consider primary and secondary frequency controls, linear and nonlinear power flow models, and the interactions between generator dynamics and load control.

(2) Two-timescale voltage control: The voltage of a power distribution system must be maintained closely around its nominal value in real time, even in the presence of highly volatile power supply or demand. For this purpose, we jointly control two types of reactive power sources: a capacitor operating at a slow timescale, and a power electronic device, such as a smart inverter or a D-STATCOM, operating at a fast timescale. Their control actions are solved from optimal power flow problems at two timescales. Specifically, the slow-timescale problem is a chance-constrained optimization, which minimizes power loss and regulates the voltage at the current time instant while limiting the probability of future voltage violations due to stochastic changes in power supply or demand. This control framework forms the basis of an optimal sizing problem, which determines the installation capacities of the control devices by minimizing the sum of power loss and capital cost. We develop computationally efficient heuristics to solve the optimal sizing problem and implement real-time control. Numerical experiments show that the proposed sizing and control schemes significantly improve the reliability of voltage control with a moderate increase in cost.

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Researchers have spent decades refining and improving their methods for fabricating smaller, finer-tuned, higher-quality nanoscale optical elements with the goal of making more sensitive and accurate measurements of the world around them using optics. Quantum optics has been a well-established tool of choice in making these increasingly sensitive measurements which have repeatedly pushed the limits on the accuracy of measurement set forth by quantum mechanics. A recent development in quantum optics has been a creative integration of robust, high-quality, and well-established macroscopic experimental systems with highly-engineerable on-chip nanoscale oscillators fabricated in cleanrooms. However, merging large systems with nanoscale oscillators often require them to have extremely high aspect-ratios, which make them extremely delicate and difficult to fabricate with an "experimentally reasonable" repeatability, yield and high quality. In this work we give an overview of our research, which focused on microscopic oscillators which are coupled with macroscopic optical cavities towards the goal of cooling them to their motional ground state in room temperature environments. The quality factor of a mechanical resonator is an important figure of merit for various sensing applications and observing quantum behavior. We demonstrated a technique for pushing the quality factor of a micromechanical resonator beyond conventional material and fabrication limits by using an optical field to stiffen and trap a particular motional mode of a nanoscale oscillator. Optical forces increase the oscillation frequency by storing most of the mechanical energy in a nearly loss-less optical potential, thereby strongly diluting the effects of material dissipation. By placing a 130 nm thick SiO2 pendulum in an optical standing wave, we achieve an increase in the pendulum center-of-mass frequency from 6.2 to 145 kHz. The corresponding quality factor increases 50-fold from its intrinsic value to a final value of Qm = 5.8(1.1) x 105, representing more than an order of magnitude improvement over the conventional limits of SiO2 for a pendulum geometry. Our technique may enable new opportunities for mechanical sensing and facilitate observations of quantum behavior in this class of mechanical systems. We then give a detailed overview of the techniques used to produce high-aspect-ratio nanostructures with applications in a wide range of quantum optics experiments. The ability to fabricate such nanodevices with high precision opens the door to a vast array of experiments which integrate macroscopic optical setups with lithographically engineered nanodevices. Coupled with atom-trapping experiments in the Kimble Lab, we use these techniques to realize a new waveguide chip designed to address ultra-cold atoms along lithographically patterned nanobeams which have large atom-photon coupling and near 4π Steradian optical access for cooling and trapping atoms. We describe a fully integrated and scalable design where cold atoms are spatially overlapped with the nanostring cavities in order to observe a resonant optical depth of d0 ≈ 0.15. The nanodevice illuminates new possibilities for integrating atoms into photonic circuits and engineering quantum states of atoms and light on a microscopic scale. We then describe our work with superconducting microwave resonators coupled to a phononic cavity towards the goal of building an integrated device for quantum-limited microwave-to-optical wavelength conversion. We give an overview of our characterizations of several types of substrates for fabricating a low-loss high-frequency electromechanical system. We describe our electromechanical system fabricated on a Si3N4 membrane which consists of a 12 GHz superconducting LC resonator coupled capacitively to the high frequency localized modes of a phononic nanobeam. Using our suspended membrane geometry we isolate our system from substrates with significant loss tangents, drastically reducing the parasitic capacitance of our superconducting circuit to ≈ 2.5$ fF. This opens up a number of possibilities in making a new class of low-loss high-frequency electromechanics with relatively large electromechanical coupling. We present our substrate studies, fabrication methods, and device characterization.

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The behavior of spheres in non-steady translational flow has been studied experimentally for values of Reynolds number from 0.2 to 3000. The aim of the work was to improve our qualitative understanding of particle transport in turbulent gaseous media, a process of extreme importance in power plants and energy transfer mechanisms.

Particles, subjected to sinusoidal oscillations parallel to the direction of steady translation, were found to have changes in average drag coefficient depending upon their translational Reynolds number, the density ratio, and the dimensionless frequency and amplitude of the oscillations. When the Reynolds number based on sphere diameter was less than 200, the oscillation had negligible effect on the average particle drag.

For Reynolds numbers exceeding 300, the coefficient of the mean drag was increased significantly in a particular frequency range. For example, at a Reynolds number of 3000, a 25 per cent increase in drag coefficient can be produced with an amplitude of oscillation of only 2 per cent of the sphere diameter, providing the frequency is near the frequency at which vortices would be shed in a steady flow at the mean speed. Flow visualization shows that over a wide range of frequencies, the vortex shedding frequency locks in to the oscillation frequency. Maximum effect at the natural frequency and lock-in show that a non-linear interaction between wake vortex shedding and the oscillation is responsible for the increase in drag.

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The temporal structure of neuronal spike trains in the visual cortex can provide detailed information about the stimulus and about the neuronal implementation of visual processing. Spike trains recorded from the macaque motion area MT in previous studies (Newsome et al., 1989a; Britten et al., 1992; Zohary et al., 1994) are analyzed here in the context of the dynamic random dot stimulus which was used to evoke them. If the stimulus is incoherent, the spike trains can be highly modulated and precisely locked in time to the stimulus. In contrast, the coherent motion stimulus creates little or no temporal modulation and allows us to study patterns in the spike train that may be intrinsic to the cortical circuitry in area MT. Long gaps in the spike train evoked by the preferred direction motion stimulus are found, and they appear to be symmetrical to bursts in the response to the anti-preferred direction of motion. A novel cross-correlation technique is used to establish that the gaps are correlated between pairs of neurons. Temporal modulation is also found in psychophysical experiments using a modified stimulus. A model is made that can account for the temporal modulation in terms of the computational theory of biological image motion processing. A frequency domain analysis of the stimulus reveals that it contains a repeated power spectrum that may account for psychophysical and electrophysiological observations.

Some neurons tend to fire bursts of action potentials while others avoid burst firing. Using numerical and analytical models of spike trains as Poisson processes with the addition of refractory periods and bursting, we are able to account for peaks in the power spectrum near 40 Hz without assuming the existence of an underlying oscillatory signal. A preliminary examination of the local field potential reveals that stimulus-locked oscillation appears briefly at the beginning of the trial.

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Cells in the lateral intraparietal cortex (LIP) of rhesus macaques respond vigorously and in spatially-tuned fashion to briefly memorized visual stimuli. Responses to stimulus presentation, memory maintenance, and task completion are seen, in varying combination from neuron to neuron. To help elucidate this functional segmentation a new system for simultaneous recording from multiple neighboring neurons was developed. The two parts of this dissertation discuss the technical achievements and scientific discoveries, respectively.

Technology. Simultanous recordings from multiple neighboring neurons were made with four-wire bundle electrodes, or tetrodes, which were adapted to the awake behaving primate preparation. Signals from these electrodes were partitionable into a background process with a 1/f-like spectrum and foreground spiking activity spanning 300-6000 Hz. Continuous voltage recordings were sorted into spike trains using a state-of-the-art clustering algorithm, producing a mean of 3 cells per site. The algorithm classified 96% of spikes correctly when tetrode recordings were confirmed with simultaneous intracellular signals. Recording locations were verified with a new technique that creates electrolytic lesions visible in magnetic resonance imaging, eliminating the need for histological processing. In anticipation of future multi-tetrode work, the chronic chamber microdrive, a device for long-term tetrode delivery, was developed.

Science. Simultaneously recorded neighboring LIP neurons were found to have similar preferred targets in the memory saccade paradigm, but dissimilar peristimulus time histograms, PSTH). A majority of neighboring cell pairs had a difference in preferred directions of under 45° while the trial time of maximal response showed a broader distribution, suggesting homogeneity of tuning with het erogeneity of function. A continuum of response characteristics was present, rather than a set of specific response types; however, a mapping experiment suggests this may be because a given cell's PSTH changes shape as well as amplitude through the response field. Spike train autocovariance was tuned over target and changed through trial epoch, suggesting different mechanisms during memory versus background periods. Mean frequency-domain spike-to-spike coherence was concentrated below 50 Hz with a significant maximum of 0.08; mean time-domain coherence had a narrow peak in the range ±10 ms with a significant maximum of 0.03. Time-domain coherence was found to be untuned for short lags (10 ms), but significantly tuned at larger lags (50 ms).

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A fundamental question in neuroscience is how distributed networks of neurons communicate and coordinate dynamically and specifically. Several models propose that oscillating local networks can transiently couple to each other through phase-locked firing. Coherent local field potentials (LFP) between synaptically connected regions is often presented as evidence for such coupling. The physiological correlates of LFP signals depend on many anatomical and physiological factors, however, and how the underlying neural processes collectively generate features of different spatiotemporal scales is poorly understood. High frequency oscillations in the hippocampus, including gamma rhythms (30-100 Hz) that are organized by the theta oscillations (5-10 Hz) during active exploration and REM sleep, as well as sharp wave-ripples (SWRs, 140-200 Hz) during immobility or slow wave sleep, have each been associated with various aspects of learning and memory. Deciphering their physiology and functional consequences is crucial to understanding the operation of the hippocampal network.

We investigated the origins and coordination of high frequency LFPs in the hippocampo-entorhinal network using both biophysical models and analyses of large-scale recordings in behaving and sleeping rats. We found that the synchronization of pyramidal cell spikes substantially shapes, or even dominates, the electrical signature of SWRs in area CA1 of the hippocampus. The precise mechanisms coordinating this synchrony are still unresolved, but they appear to also affect CA1 activity during theta oscillations. The input to CA1, which often arrives in the form of gamma-frequency waves of activity from area CA3 and layer 3 of entorhinal cortex (EC3), did not strongly influence the timing of CA1 pyramidal cells. Rather, our data are more consistent with local network interactions governing pyramidal cells' spike timing during the integration of their inputs. Furthermore, the relative timing of input from EC3 and CA3 during the theta cycle matched that found in previous work to engage mechanisms for synapse modification and active dendritic processes. Our work demonstrates how local networks interact with upstream inputs to generate a coordinated hippocampal output during behavior and sleep, in the form of theta-gamma coupling and SWRs.

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The Madden-Julian Oscillation (MJO) is a pattern of intense rainfall and associated planetary-scale circulations in the tropical atmosphere, with a recurrence interval of 30-90 days. Although the MJO was first discovered 40 years ago, it is still a challenge to simulate the MJO in general circulation models (GCMs), and even with simple models it is difficult to agree on the basic mechanisms. This deficiency is mainly due to our poor understanding of moist convection—deep cumulus clouds and thunderstorms, which occur at scales that are smaller than the resolution elements of the GCMs. Moist convection is the most important mechanism for transporting energy from the ocean to the atmosphere. Success in simulating the MJO will improve our understanding of moist convection and thereby improve weather and climate forecasting.

We address this fundamental subject by analyzing observational datasets, constructing a hierarchy of numerical models, and developing theories. Parameters of the models are taken from observation, and the simulated MJO fits the data without further adjustments. The major findings include: 1) the MJO may be an ensemble of convection events linked together by small-scale high-frequency inertia-gravity waves; 2) the eastward propagation of the MJO is determined by the difference between the eastward and westward phase speeds of the waves; 3) the planetary scale of the MJO is the length over which temperature anomalies can be effectively smoothed by gravity waves; 4) the strength of the MJO increases with the typical strength of convection, which increases in a warming climate; 5) the horizontal scale of the MJO increases with the spatial frequency of convection; and 6) triggered convection, where potential energy accumulates until a threshold is reached, is important in simulating the MJO. Our findings challenge previous paradigms, which consider the MJO as a large-scale mode, and point to ways for improving the climate models.

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How animals use sensory information to weigh the risks vs. benefits of behavioral decisions remains poorly understood. Inter-male aggression is triggered when animals perceive both the presence of an appetitive resource, such as food or females, and of competing conspecific males. How such signals are detected and integrated to control the decision to fight is not clear. Here we use the vinegar fly, Drosophila melanogaster, to investigate the manner in which food and females promotes aggression.

In the first chapter, we explore how food controls aggression. As in many other species, food promotes aggression in flies, but it is not clear whether food increases aggression per se, or whether aggression is a secondary consequence of increased social interactions caused by aggregation of flies on food. Furthermore, nothing is known about how animals evaluate the quality and quantity of food in the context of competition. We show that food promotes aggression independently of any effect to increase the frequency of contact between males. Food increases aggression but not courtship between males, suggesting that the effect of food on aggression is specific. Next, we show that flies tune the level of aggression according to absolute amount of food rather than other parameters, such as area or concentration of food. Sucrose, a sugar molecule present in many fruits, is sufficient to promote aggression, and detection of sugar via gustatory receptor neurons is necessary for food-promoted aggression. Furthermore, we show that while food is necessary for aggression, too much food decreases aggression. Finally, we show that flies exhibit strategies consistent with a territorial strategy. These data suggest that flies use sweet-sensing gustatory information to guide their decision to fight over a limited quantity of a food resource.

Following up on the findings of the first chapter, we asked how the presence of a conspecific female resource promotes male-male aggression. In the absence of food, group-housed male flies, who normally do not fight even in the presence of food, fight in the presence of females. Unlike food, the presence of females strongly influences proximity between flies. Nevertheless, as group-housed flies do not fight even when they are in small chambers, it is unlikely that the presence of female indirectly increases aggression by first increasing proximity. Unlike food, the presence of females also leads to large increases in locomotion and in male-female courtship behaviors, suggesting that females may influence aggression as well as general arousal. Female cuticular hydrocarbons are required for this effect, as females that do not produce CH pheromones are unable to promote male-male aggression. In particular, 7,11-HD––a female-specific cuticular hydrocarbon pheromone critical for male-female courtship––is sufficient to mediate this effect when it is perfumed onto pheromone-deficient females or males. Recent studies showed that ppk23+ GRNs label two population of GRNs, one of which detects male cuticular hydrocarbons and another labeled by ppk23 and ppk25, which detects female cuticular hydrocarbons. I show that in particular, both of these GRNs control aggression, presumably via detection of female or male pheromones. To further investigate the ways in which these two classes of GRNs control aggression, I developed new genetic tools to independently test the male- and female-sensing GRNs. I show that ppk25-LexA and ppk25-GAL80 faithfully recapitulate the expression pattern of ppk25-GAL4 and label a subset of ppk23+ GRNs. These tools can be used in future studies to dissect the respective functions of male-sensing and female-sensing GRNs in male social behaviors.

Finally, in the last chapter, I discuss quantitative approaches to describe how varying quantities of food and females could control the level of aggression. Flies show an inverse-U shaped aggressive response to varying quantities of food and a flat aggressive response to varying quantities of females. I show how two simple game theoretic models, “prisoner’s dilemma” and “coordination game” could be used to describe the level of aggression we observe. These results suggest that flies may use strategic decision-making, using simple comparisons of costs and benefits.

In conclusion, male-male aggression in Drosophila is controlled by simple gustatory cues from food and females, which are detected by gustatory receptor neurons. Different quantities of resource cues lead to different levels of aggression, and flies show putative territorial behavior, suggesting that fly aggression is a highly strategic adaptive behavior. How these resource cues are integrated with male pheromone cues and give rise to this complex behavior is an interesting subject, which should keep researchers busy in the coming years.