Non-adaptive Heisenberg-limited metrology with multi-channel homodyne measurements

We show a protocol achieving the ultimate Heisenberg-scaling sensitivity in the estimation of a parameter encoded in a generic linear network, without employing any auxiliary networks, and without the need of any prior information on the parameter nor on the network structure. As a result, this protocol does not require a prior coarse estimation of the parameter, nor an adaptation of the network. The scheme we analyse consists of a single-mode squeezed state and homodyne detectors in each of the M output channels of the network encoding the parameter, making it feasible for experimental applications

SKiNFOLK: An American Experiment: The Role of Open Process and Collective Dramaturgy in Nonlinear Theater-making

What are the possibilities and limitations when introducing unconventional form and content into theatrical work? How does moving toward form and content labeled “non-linear” or otherwise non-traditional impact audience reception and engagement? Through several exercises and assignments in monologue-writing, score-building, and mixing media, I began creating a play that is the crux of this thesis: SKiNFOLK: An American Show. Without knowing it, I was building what I now call an open process--one in which (partly due to aspects of my own identity as the source material), audiences are invited to allow a more intimate and vulnerable theater experience. The direction of the personal was a partly conscious decision, but mostly it sprang from instinct, my own desire for healing, and the deep challenge it would present me as a writer and performer to blend and otherwise explore the limits of perceived dichotomies including but not limited to: poetry and fact, real and imagined, the theatrical and the mundane, individuality and collectivity. My theoretical and dramaturgical suspicion was that by intentionally pushing my personal boundaries as well as the boundaries of what is traditionally accepted as a play, the audience would have more freedom to participate, not through superficial means of placing their bodies or voices in the “right place” at the “right time,” but in a process of collective dramaturgy

Broken passivity and time-reversal-symmetry bounds in acoustics devices

We collect information about the world through our senses, two of which, hearing and touch, are attuned to the mechanical vibrations travelling around us. Scientists and engineers have learned to control these acoustic waves, and in so doing they have opened new possibilities in how we interact with each other and the natural world. One area of rapid progress is acoustic metamaterials, which are architected structures that can shape sound waves in ways that go beyond what is possible with natural materials. Given the potential of these new materials, it is important to consider their limits and identify the underlying physical principles responsible for them. In this dissertation we examine limitations in the response of acoustic materials and devices due to passivity and time-reversal symmetry. An important constraint that arises due to time-reversal symmetry is reciprocity. Reciprocity must be broken to create devices that allow sound through in only one direction. This work explores acoustic nonreciprocity with particular attention to applications in surface acoustic wave devices and topological acoustic demonstrations. One way to achieve acoustic nonreciprocity is with fluid flow. Based on this technique, we present an acoustic Mach-Zehnder isolator and nonreciprocal leaky-wave antenna. A different but equally fundamental and important constraint in acoustics technology is the trade-off between the size, efficiency, and bandwidth of a small resonator. By considering arbitrary stored and radiated sound fields surrounding a compact source, we derive a theoretical lower bound on the quality factor of a passive acoustic radiator. This work discusses opportunities to overcome this constraint by considering active resonators. We experimentally demonstrate a three-fold bandwidth improvement to the passive case by synthesizing a non-Foster circuit load for a piezoelectric sonar transducer. By using a Green’s function approach and by connecting the physics of a disordered array to the statistical theory of random walks, we also explore the physics of near-zero-index materials, and leverage their unusual sound-matter interactions to enable robust and highly directive acoustic sources. This work introduces an entirely new way to achieve highly directional sound beyond traditional techniques.Mechanical Engineerin

Extracellular electrical stimulation of retinal ganglion cells

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1994.Includes bibliographical references (p. 106-110).by Andrew Eli Grumet.M.S

Networked Dynamical Systems: Privacy, Control, and Cognition

Many natural and man-made systems, ranging from thenervous system to power and transportation grids to societies, exhibitdynamic behaviors that evolve over a sparse and complex network. This networked aspect raises significant challenges and opportunities for the identification, analysis, and control of such dynamic behaviors. While some of these challenges emanate from the networked aspect \emph{per se} (such as the sparsity of connections between system components and the interplay between nodal \emph{communication} and network dynamics), various challenges arise from the specific application areas (such as privacy concerns in cyber-physical systems or the need for \emph{scalable} algorithm designs due to the large size of various biological and engineered networks). On the other hand, networked systems provide significant opportunities and allow for performance and robustness levels that are far beyond reach for centralized systems, with examples ranging from the Internet (of Things) to the smart grid and the brain. This dissertation aims to address several of these challenges and harness these opportunities. The dissertation is divided into three parts. In the first part, we study privacy concerns whose resolution is vital for the utility of networked cyber-physical systems. We study the problems of average consensus and convex optimization as two principal distributed computations occurring over networks and design algorithm with rigorous privacy guarantees that provide a \emph{best achievable} tradeoff between network utility and privacy. In the second part, we analyze networks with resource constraints. More specifically, we study three problems of stabilization under communication (bandwidth and latency) limitations in sensing and actuation, optimal time-varying control scheduling problem under limited number of actuators and control energy, and the structure identification problem of under-sensed networks (i.e., networks with latent nodes). Finally in the last part, we focus on the intersection of networked dynamical systems and neuroscience and draw connections between brain network dynamics and two extensively studied but yet not fully understood neuro-cognitive phenomena: goal-driven selective attention and neural oscillations. Using a novel axiomatic approach, we establish these connections in the form of necessary and/or sufficient conditions on the network structure that match the network output trajectories with experimentally observed brain activity

Heisenberg scaling precision in multi-mode distributed quantum metrology

We propose an $N$-photon Gaussian measurement scheme which allows the estimation of a parameter $\varphi$ encoded into a multi-port interferometer with a Heisenberg scaling precision (i.e. of order $1/N$). In this protocol, no restrictions on the structure of the interferometer are imposed other than linearity and passivity, allowing the parameter $\varphi$ to be distributed over several components. In all previous proposals Heisenberg scaling has been obtained provided that both the input state and the measurement at the output are suitably adapted to the unknown parameter $\varphi$. This is a serious drawback which would require in practice the use of iterative procedures with a sequence of trial input states and measurements, which involve an unquantified use of additional resources. Remarkably, we find that only one stage has to be adapted, which leaves the choice of the other stage completely arbitrary. We also show that our scheme is robust against imperfections in the optimized stage. Moreover, we show that the adaptive procedure only requires a preliminary classical knowledge (i.e to a precision $1/\sqrt{N}$) on the parameter, and no further additional resources. As a consequence, the same adapted stage can be employed to monitor with Heisenberg-limited precision any variation of the parameter of the order of $1/\sqrt{N}$ without any further adaptation.Comment: 5 pages, 3 figure