Demonstration of Frequency Stability limited by Thermal Fluctuation Noise in Silicon Nitride Nanomechanical Resonators

The frequency stability of nanomechanical resonators (NMR) dictates the fundamental performance limit of sensors that relate physical perturbations to a resonance frequency shift. While the contribution of thermomechanical noise to frequency stability was understood recently, thermal fluctuation noise has attracted less attention despite being the ultimate performance limit of temperature sensing. We provide a model for the frequency stability of NMR considering both additive phase noise (i.e., thermomechanical and detection noises) and thermal fluctuation noise. We then experimentally demonstrate optimized NMR achieving frequency stability limited by thermal fluctuation noise. Our work shows that current models for NMR frequency stability can be incomplete. It also paves a way for NMR radiation detectors to reach the unattained fundamental detectivity limit of thermal-based radiation sensing

Objects that Sound

In this paper our objectives are, first, networks that can embed audio and visual inputs into a common space that is suitable for cross-modal retrieval; and second, a network that can localize the object that sounds in an image, given the audio signal. We achieve both these objectives by training from unlabelled video using only audio-visual correspondence (AVC) as the objective function. This is a form of cross-modal self-supervision from video. To this end, we design new network architectures that can be trained for cross-modal retrieval and localizing the sound source in an image, by using the AVC task. We make the following contributions: (i) show that audio and visual embeddings can be learnt that enable both within-mode (e.g. audio-to-audio) and between-mode retrieval; (ii) explore various architectures for the AVC task, including those for the visual stream that ingest a single image, or multiple images, or a single image and multi-frame optical flow; (iii) show that the semantic object that sounds within an image can be localized (using only the sound, no motion or flow information); and (iv) give a cautionary tale on how to avoid undesirable shortcuts in the data preparation.Comment: Appears in: European Conference on Computer Vision (ECCV) 201

Effects of protected areas on survival of threatened gibbons in China

Establishing protected areas (PAs) is an essential strategy to reduce biodiversity loss. However, many PAs do not provide adequate protection due to poor funding, inadequate staffing and equipment, and ineffective management. As part of China's recent economic growth, the Chinese government has significantly increased investment in nature reserves over the past 20 years, providing a unique opportunity to evaluate whether PAs can protect threatened species effectively. We compiled data from published literature on populations of gibbons (Hylobatidae), a threatened taxon with cultural significance, that occurred in Chinese reserves after 1980. We evaluated the ability of these PAs to maintain gibbon habitat and populations by comparing forest cover and human disturbance between reserves and their surrounding areas and modeling the impact of reserve characteristics on gibbon population trends. We also assessed the perspective of reserve staff concerning PA management effectiveness through an online survey. Reserves effectively protected gibbon habitat by reducing forest loss and human disturbance; however, half the reserves lost their gibbon populations since being established. Gibbons were more likely to survive in reserves established more recently, at higher elevation, with less forest loss and lower human impact, and that have been relatively well studied. A larger initial population size in the 1980s was positively associated with gibbon persistence. Although staff of all reserves reported increased investment and improved management over the past 20–30 years, no relationship was found between management effectiveness and gibbon population trends. We suggest early and emphatic intervention is critical to stop population decline and prevent extinction

Initial bound state studies in light-front QCD

We present the first numerical QCD bound state calculation based on a renormalization group-improved light-front Hamiltonian formalism. The QCD Hamiltonian is determined to second order in the coupling, and it includes two-body confining interactions. We make a momentum expansion, obtaining an equal-time-like Schrodinger equation. This is solved for quark-antiquark constituent states, and we obtain a set of self-consistent parameters by fitting B meson spectra.Comment: 38 pages, latex, 5 latex figures include

Firm valuation from customer equity:When does itwork andwhen does it fail?

Is customer equity a good proxy for a firm's market value? Using data from Netflix over 10 years, I provide evidence that a CLV-based customer equity model tracks market capitalization remarkably well under versatile conditions of stable growth, profit volatility, and even a broad market crash. However, if a firm shifts business model through radical innovation, the customer equity model requires recalibration to continue tracking market capitalization

A quantum search for zeros of polynomials

A quantum mechanical search procedure to determine the real zeros of a polynomial is introduced. It is based on the construction of a spin observable whose eigenvalues coincide with the zeros of the polynomial. Subsequent quantum mechanical measurements of the observable output directly the numerical values of the zeros. Performing the measurements is the only computational resource involved

Background modeling by shifted tilings of stacked denoising autoencoders

The effective processing of visual data without interruption is currently of supreme importance. For that purpose, the analysis system must adapt to events that may affect the data quality and maintain its performance level over time. A methodology for background modeling and foreground detection, whose main characteristic is its robustness against stationary noise, is presented in the paper. The system is based on a stacked denoising autoencoder which extracts a set of significant features for each patch of several shifted tilings of the video frame. A probabilistic model for each patch is learned. The distinct patches which include a particular pixel are considered for that pixel classification. The experiments show that classical methods existing in the literature experience drastic performance drops when noise is present in the video sequences, whereas the proposed one seems to be slightly affected. This fact corroborates the idea of robustness of our proposal, in addition to its usefulness for the processing and analysis of continuous data during uninterrupted periods of time.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Systematic Renormalization in Hamiltonian Light-Front Field Theory: The Massive Generalization

Hamiltonian light-front field theory can be used to solve for hadron states in QCD. To this end, a method has been developed for systematic renormalization of Hamiltonian light-front field theories, with the hope of applying the method to QCD. It assumed massless particles, so its immediate application to QCD is limited to gluon states or states where quark masses can be neglected. This paper builds on the previous work by including particle masses non-perturbatively, which is necessary for a full treatment of QCD. We show that several subtle new issues are encountered when including masses non-perturbatively. The method with masses is algebraically and conceptually more difficult; however, we focus on how the methods differ. We demonstrate the method using massive phi^3 theory in 5+1 dimensions, which has important similarities to QCD.Comment: 7 pages, 2 figures. Corrected error in Eq. (11), v3: Added extra disclaimer after Eq. (2), and some clarification at end of Sec. 3.3. Final published versio