Showing papers on "Energy (signal processing) published in 2017"

Jet energy scale measurements and their systematic uncertainties in proton-proton collisions at √s=13 TeV with the ATLAS detector

Abstract: Jet energy scale measurements and their systematic uncertainties are reported for jets measured with the ATLAS detector using proton-proton collision data with a center-of-mass energy of $\sqrt{s} = 13$ TeV, corresponding to an integrated luminosity of 3.2 fb$^{-1}$ collected during 2015 at the LHC. Jets are reconstructed from energy deposits forming topological clusters of calorimeter cells, using the anti-$k_{t}$ algorithm with radius parameter $R = 0.4$. Jets are calibrated with a series of simulation-based corrections and in situ techniques. In situ techniques exploit the transverse momentum balance between a jet and a reference object such as a photon, $Z$ boson, or multijet system for jets with $20 0.8$) is derived from dijet $p_{T}$ balance measurements. For jets of $p_{T} = 80$ GeV, the additional uncertainty for the forward jet calibration reaches its largest value of about 2% in the range $|\eta| > 3.5$ and in a narrow slice of $2.2 < |\eta| < 2.4$.

Sterile Neutrino Search at the NEOS Experiment.

Abstract: An experiment to search for light sterile neutrinos is conducted at a reactor with a thermal power of 2.8 GW located at the Hanbit nuclear power complex. The search is done with a detector consisting of a ton of Gd-loaded liquid scintillator in a tendon gallery approximately 24 m from the reactor core. The measured antineutrino event rate is 1976 per day with a signal to background ratio of about 22. The shape of the antineutrino energy spectrum obtained from the eight-month data-taking period is compared with a hypothesis of oscillations due to active-sterile antineutrino mixing. No strong evidence of $3+1$ neutrino oscillation is found. An excess around the 5 MeV prompt energy range is observed as seen in existing longer-baseline experiments. The mixing parameter ${\mathrm{sin}}^{2}2{\ensuremath{\theta}}_{14}$ is limited up to less than 0.1 for $\mathrm{\ensuremath{\Delta}}{m}_{41}^{2}$ ranging from 0.2 to $2.3\text{ }{\mathrm{eV}}^{2}$ with a 90% confidence level.

Synchroextracting Transform

Abstract: In this paper, we introduce a new time-frequency (TF) analysis (TFA) method to study the trend and instantaneous frequency (IF) of nonlinear and nonstationary data. Our proposed method is termed the synchroextracting transform (SET), which belongs to a postprocessing procedure of the short-time Fourier transform (STFT). Compared with classical TFA methods, the proposed method can generate a more energy concentrated TF representation and allow for signal reconstruction. The proposed SET method is inspired by the recently proposed synchrosqueezing transform (SST) and the theory of the ideal TFA. To analyze a signal, it is important to obtain the time-varying information, such as the IF and instantaneous amplitude. The SST is to squeeze all TF coefficients into the IF trajectory. Differ from the squeezing manner of SST, the main idea of SET is to only retain the TF information of STFT results most related to time-varying features of the signal and to remove most smeared TF energy, such that the energy concentration of the novel TF representation can be enhanced greatly. Numerical and real-world signals are employed to validate the effectiveness of the SET method.

Updated Global 3+1 Analysis of Short-BaseLine Neutrino Oscillations

Abstract: We present the results of an updated fit of short-baseline neutrino oscillation data in the framework of 3+1 active-sterile neutrino mixing. We first consider ν e and $$ {\overline{ u}}_e $$ disappearance in the light of the Gallium and reactor anomalies. We discuss the implications of the recent measurement of the reactor $$ {\overline{ u}}_e $$ spectrum in the NEOS experiment, which shifts the allowed regions of the parameter space towards smaller values of |U e4|2. The β-decay constraints of the Mainz and Troitsk experiments allow us to limit the oscillation length between about 2 cm and 7 m at 3σ for neutrinos with an energy of 1 MeV. The corresponding oscillations can be discovered in a model-independent way in ongoing reactor and source experiments by measuring ν e and $$ {\overline{ u}}_e $$ disappearance as a function of distance. We then consider the global fit of the data on short-baseline $$ {}_{ u_{\mu}}^{\left(-\right)}{\to}_{ u_e}^{\left(-\right)} $$ transitions in the light of the LSND anomaly, taking into account the constraints from $$ {}_{ u_e}^{\left(-\right)} $$ and $$ {}_{ u_{\mu}}^{\left(-\right)} $$ disappearance experiments, including the recent data of the MINOS and IceCube experiments. The combination of the NEOS constraints on |U e4|2 and the MINOS and IceCube constraints on |U μ4|2 lead to an unacceptable appearance-disappearance tension which becomes tolerable only in a pragmatic fit which neglects the MiniBooNE low-energy anomaly. The minimization of the global χ 2 in the space of the four mixing parameters Δm 41 2 , |U e4|2, |U μ4|2, and |U τ4|2 leads to three allowed regions with narrow Δm 41 2 widths at Δm 41 2 ≈ 1.7 (best-fit), 1.3 (at 2σ), 2.4 (at 3σ) eV2. The effective amplitude of short-baseline $$ {}_{ u_{\mu}}^{\left(-\right)}{\to}_{ u_e}^{\left(-\right)} $$ oscillations is limited by 0.00048 ≲ sin2 2ϑ eμ ≲ 0.0020 at 3σ. The restrictions of the allowed regions of the mixing parameters with respect to our previous global fits are mainly due to the NEOS constraints. We present a comparison of the allowed regions of the mixing parameters with the sensitivities of ongoing experiments, which show that it is likely that these experiments will determine in a definitive way if the reactor, Gallium and LSND anomalies are due to active-sterile neutrino oscillations or not.

Machine Learning of Accurate Energy-Conserving Molecular Force Fields

Abstract: The law of energy conservation is used to develop an efficient machine learning approach to construct accurate force fields. Using conservation of energy—a fundamental property of closed classical and quantum mechanical systems—we develop an efficient gradient-domain machine learning (GDML) approach to construct accurate molecular force fields using a restricted number of samples from ab initio molecular dynamics (AIMD) trajectories. The GDML implementation is able to reproduce global potential energy surfaces of intermediate-sized molecules with an accuracy of 0.3 kcal mol−1 for energies and 1 kcal mol−1 Å̊−1 for atomic forces using only 1000 conformational geometries for training. We demonstrate this accuracy for AIMD trajectories of molecules, including benzene, toluene, naphthalene, ethanol, uracil, and aspirin. The challenge of constructing conservative force fields is accomplished in our work by learning in a Hilbert space of vector-valued functions that obey the law of energy conservation. The GDML approach enables quantitative molecular dynamics simulations for molecules at a fraction of cost of explicit AIMD calculations, thereby allowing the construction of efficient force fields with the accuracy and transferability of high-level ab initio methods.

Analytical spectral density of the Sachdev-Ye-Kitaev model at finite N

Abstract: We derive an approximate analytical formula for the spectral density of the $q$-body Sachdev-Ye-Kitaev (SYK) model obtained by summing a class of diagrams representing leading intersecting contractions. This expression agrees with that of $Q$-Hermite polynomials, with $Q$ a nontrivial function of $q\ensuremath{\ge}2$ and the number of Majorana fermions $N$. Numerical results, obtained by exact diagonalization, are in excellent agreement with this approximate analytical spectral density even for relatively small $N\ensuremath{\sim}8$. For $N\ensuremath{\gg}1$ and not close to the edge of the spectrum, we find that the approximate analytical spectral density simplifies to ${\ensuremath{\rho}}_{\mathrm{asym}}(E)=\mathrm{exp}[2{\mathrm{arcsin}}^{2}(E/{E}_{0})/\mathrm{log}\ensuremath{\eta}]$, where $\ensuremath{\eta}(N,q)$ is the suppression factor of the contribution of intersecting Wick contractions relative to nested contractions and ${E}_{0}$ is the ground-state energy per particle. This spectral density reproduces the known result for the free energy in the large-$q$ and large-$N$ limit at arbitrary values of the temperature. In the infrared region, where the SYK model is believed to have a gravity dual, the analytical spectral density is given by $\ensuremath{\rho}(E)\ensuremath{\sim}\mathrm{sinh}[2\ensuremath{\pi}\sqrt{2}\sqrt{(1\ensuremath{-}E/{E}_{0})/(\ensuremath{-}\mathrm{log}\ensuremath{\eta})}]$. It therefore has a square-root edge, as in random matrix ensembles, followed by an exponential growth, a distinctive feature of black holes and also of low-energy nuclear excitations. Results for level statistics in this region confirm the agreement with random matrix theory. Physically this is a signature that, for sufficiently long times, the SYK model and its gravity dual evolve to a fully ergodic state whose dynamics only depends on the global symmetry of the system. Our results strongly suggest that random matrix correlations are a universal feature of quantum black holes and that the SYK model, combined with holography, may be relevant to modeling certain aspects of the nuclear dynamics.

Black hole superradiance signatures of ultralight vectors

Abstract: The process of superradiance can extract angular momentum and energy from astrophysical black holes (BHs) to populate gravitationally bound states with an exponentially large number of light bosons. We analytically calculate superradiant growth rates for vectors around rotating BHs in the regime where the vector Compton wavelength is much larger than the BH size. Spin-1 bound states have superradiance times as short as a second around stellar BHs, growing up to a thousand times faster than their spin-0 counterparts. The fast rates allow us to use measurements of rapidly spinning BHs in x-ray binaries to exclude a wide range of masses for weakly coupled spin-1 particles, $5\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}14}\ensuremath{-}2\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}11}\text{ }\text{ }\mathrm{eV}$; lighter masses in the range $6\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}20}\ensuremath{-}2\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}17}\text{ }\text{ }\mathrm{eV}$ start to be constrained by supermassive BH spin measurements at a lower level of confidence. We also explore routes to detection of new vector particles possible with the advent of gravitational wave (GW) astronomy. The LIGO-Virgo Collaboration could discover hints of a new light vector particle in statistical analyses of masses and spins of merging BHs. Vector annihilations source continuous monochromatic gravitational radiation which could be observed by current GW observatories. At design sensitivity, Advanced LIGO may measure up to thousands of annihilation signals from within the Milky Way, while hundreds of BHs born in binary mergers across the observable Universe may superradiate vector bound states and become new beacons of monochromatic gravitational waves.

Optimization of Energy Systems

Abstract: Optimization of Energy Systems comprehensively describes the thermodynamic modelling, analysis and optimization of numerous types of energy systems in various applications. It provides a new understanding of the system and the process of defining proper objective functions for determination of the most suitable design parameters for achieving enhanced efficiency, cost effectiveness and sustainability.

Optically-controlled long-term storage and release of thermal energy in phase-change materials

Abstract: Thermal energy storage offers enormous potential for a wide range of energy technologies. Phase-change materials offer state-of-the-art thermal storage due to high latent heat. However, spontaneous heat loss from thermally charged phase-change materials to cooler surroundings occurs due to the absence of a significant energy barrier for the liquid–solid transition. This prevents control over the thermal storage, and developing effective methods to address this problem has remained an elusive goal. Herein, we report a combination of photo-switching dopants and organic phase-change materials as a way to introduce an activation energy barrier for phase-change materials solidification and to conserve thermal energy in the materials, allowing them to be triggered optically to release their stored latent heat. This approach enables the retention of thermal energy (about 200 J g−1) in the materials for at least 10 h at temperatures lower than the original crystallization point, unlocking opportunities for portable thermal energy storage systems. Phase-change materials offer excellent thermal storage due to their high latent heat; however, they suffer from spontaneous heat loss. Han et al., use organic photo-switching dopants to introduce an activation energy barrier which enables controllable thermal energy release and retention.

Distributed Optimal Energy Management for Energy Internet

Abstract: In this paper, a novel energy management framework for energy Internet with many energy bodies is presented, which features multicoupling of different energy forms, diversified energy roles, and peer-to-peer energy supply/demand, etc. The energy body as an integrated energy unit, which may have various functionalities and play multiple roles at the same time, is formulated for the system model development. Forecasting errors, confidence intervals, and penalty factor are also taken into account to model renewable energy resources to provide tradeoff between optimality and possibility. Furthermore, a novel distributed-consensus alternating direction method of multipliers (ADMM) algorithm, which contains a dynamic average consensus algorithm and distributed ADMM algorithm, is presented to solve the optimal energy management problem of energy Internet. The proposed algorithm can effectively handle the problems of power-heat-gas-coupling, global constraint limits, and nonlinear objective function. With this effort, not only the optimal energy market clearing price but also the optimal energy outputs/demands can be obtained through only local communication and computation. Simulation results are presented to illustrate the effectiveness of the proposed distributed algorithm.

Spin-Wave Excitations Evidencing the Kitaev Interaction in Single Crystalline α-RuCl_{3}.

Abstract: Kitaev interactions underlying a quantum spin liquid have long been sought, but experimental data from which their strengths can be determined directly, are still lacking. Here, by carrying out inelastic neutron scattering measurements on high-quality single crystals of $\ensuremath{\alpha}\text{\ensuremath{-}}{\mathrm{RuCl}}_{3}$, we observe spin-wave spectra with a gap of $\ensuremath{\sim}2\text{ }\text{ }\mathrm{meV}$ around the $M$ point of the two-dimensional Brillouin zone. We derive an effective-spin model in the strong-coupling limit based on energy bands obtained from first-principles calculations, and find that the anisotropic Kitaev interaction $K$ term and the isotropic antiferromagnetic off-diagonal exchange interaction $\mathrm{\ensuremath{\Gamma}}$ term are significantly larger than the Heisenberg exchange coupling $J$ term. Our experimental data can be well fit using an effective-spin model with $K=\ensuremath{-}6.8\text{ }\text{ }\mathrm{meV}$ and $\mathrm{\ensuremath{\Gamma}}=9.5\text{ }\text{ }\mathrm{meV}$. These results demonstrate explicitly that Kitaev physics is realized in real materials.

Line-to-Line Fault Detection for Photovoltaic Arrays Based on Multiresolution Signal Decomposition and Two-Stage Support Vector Machine

Abstract: Fault detection in photovoltaic (PV) arrays becomes difficult as the number of PV panels increases Particularly, under low irradiance conditions with an active maximum power point tracking algorithm, line-to-line (L-L) faults may remain undetected because of low fault currents, resulting in loss of energy and potential fire hazards This paper proposes a fault detection algorithm based on multiresolution signal decomposition for feature extraction, and two-stage support vector machine (SVM) classifiers for decision making This detection method only requires data of the total voltage and current from a PV array and a limited amount of labeled data for training the SVM Both simulation and experimental case studies verify the accuracy of the proposed method

Dark forces coupled to nonconserved currents

Abstract: New light vectors with dimension-4 couplings to Standard Model states have ${\text{(energy/vector mass)}}^{2}$-enhanced production rates unless the current they couple to is conserved. These processes allow us to derive new constraints on the couplings of such vectors, that are significantly stronger than the previous literature for a wide variety of models. Examples include vectors with axial couplings to quarks and vectors coupled to currents (such as baryon number) that are only broken by the chiral anomaly. Our new limits arise from a range of processes, including rare $Z$ decays and flavor-changing meson decays, and rule out a number of phenomenologically motivated proposals.

Energy-Aware Approaches for Energy Harvesting Powered Wireless Sensor Nodes

Abstract: Intensive research on energy harvesting powered wireless sensor nodes (WSNs) has been driven by the needs of reducing the power consumption by the WSNs and increasing the power generated by energy harvesters. The mismatch between the energy generated by the harvesters and the energy demanded by the WSNs is always a bottleneck as the ambient environmental energy is limited and time varying. This paper introduces a combined energy-aware interface with an energy-aware program to deal with the mismatch through managing the energy flow from the energy storage capacitor to the WSNs. These two energy-aware approaches were implemented in a custom developed vibration energy harvesting powered WSN. The experimental results show that, with the 3.2-mW power generated by a piezoelectric energy harvester under an emulated aircraft wing strain loading of $600~\mu \varepsilon $ at 10 Hz, the combined energy-aware approaches enable the WSN to have a significantly reduced sleep current from $28.3~\mu \text{A}$ of a commercial WSN to $0.95~\mu \text{A}$ and enable the WSN operations for a long active time of about 1.15 s in every 7.79 s to sample and transmit a large number of data (388 B), rather than a few ten milliseconds and a few bytes, as demanded by vibration measurement. When the approach was not used, the same amount of energy harvested was not able to power the WSN to start, not mentioning to enabling the WSN operation, which highlighted the importance and the value of the energy-aware approaches in enabling energy harvesting powered WSN operation successfully.

New Constraints on Light Vectors Coupled to Anomalous Currents

Abstract: We derive new constraints on light vectors coupled to standard model (SM) fermions, when the corresponding SM current is broken by the chiral anomaly The cancellation of the anomaly by heavy fermions results, in the low-energy theory, in Wess-Zumino--type interactions between the new vector and the SM gauge bosons These interactions are determined by the requirement that the heavy sector preserves the SM gauge groups and lead to $(\mathrm{energy}/\mathrm{vector}\text{ }\mathrm{mass}{)}^{2}$ enhanced rates for processes involving the longitudinal mode of the new vector Taking the example of a vector coupled to a vector coupled to SM baryon number, $Z$ decays and flavor-changing neutral current meson decays via the new vector can occur with $(\mathrm{weak}\text{ }\mathrm{scale}/\mathrm{vector}\text{ }\mathrm{mass}{)}^{2}$ enhanced rates These processes place significantly stronger coupling bounds than others considered in the literature, over a wide range of vector masses

Anomalous Hall Effect and Topological Defects in Antiferromagnetic Weyl Semimetals: Mn 3 Sn / Ge

Abstract: We theoretically study the interplay between bulk Weyl electrons and magnetic topological defects, including magnetic domains, domain walls, and ${\mathbb{Z}}_{6}$ vortex lines, in the antiferromagnetic Weyl semimetals ${\mathrm{Mn}}_{3}\mathrm{Sn}$ and ${\mathrm{Mn}}_{3}\mathrm{Ge}$ with negative vector chirality. We argue that these materials possess a hierarchy of energy scales, which allows a description of the spin structure and spin dynamics using an $XY$ model with ${\mathbb{Z}}_{6}$ anisotropy. We propose a dynamical equation of motion for the $XY$ order parameter, which implies the presence of ${\mathbb{Z}}_{6}$ vortex lines, the double-domain pattern in the presence of magnetic fields, and the ability to control domains with current. We also introduce a minimal electronic model that allows efficient calculation of the electronic structure in the antiferromagnetic configuration, unveiling Fermi arcs at domain walls, and sharp quasibound states at ${\mathbb{Z}}_{6}$ vortices. Moreover, we have shown how these materials may allow electronic-based imaging of antiferromagnetic microstructure, and propose a possible device based on the domain-dependent anomalous Hall effect.

Optimal Resource Allocation in Simultaneous Cooperative Spectrum Sensing and Energy Harvesting for Multichannel Cognitive Radio

Abstract: In this paper, a simultaneous cooperative spectrum sensing and energy harvesting model is proposed to improve the transmission performance of the multichannel cognitive radio. The frame structure is divided into sensing slot and transmission slot. In the sensing slot, the secondary user (SU) splits the subchannels into two subchannel sets, one for sensing the primary user (PU) by multichannel cooperative spectrum sensing and the other one for collecting the radio frequency energy of the PU signal and noise by multichannel energy harvesting. In the transmission slot, the harvested energy is supplied to compensate the sensing energy loss in order to guarantee the throughput. We have formulated the resource allocation of the proposed model as a class of optimization problems, which maximize aggregate throughput, harvested energy, and energy efficiency of the SU over all the subchannels through jointly optimizing subchannel set, sensing time, and transmission power, respectively. To achieve the sub-optimal solutions to the optimization problems, we have proposed the subchannel allocation algorithm and the joint optimization algorithm of sensing time and transmission power based on the Greedy algorithm and the alternating direction optimization. The stopping criteria of SU is described, when the PU is not present but the harvested energy is not enough. The simulation results are presented to demonstrate the validity and predominance of our proposed algorithms.

Adaptive Mode Decomposition Methods and Their Applications in Signal Analysis for Machinery Fault Diagnosis: A Review With Examples

Abstract: Effective signal processing methods are essential for machinery fault diagnosis. Most conventional signal processing methods lack adaptability, thus being unable to well extract the embedded meaningful information. Adaptive mode decomposition methods have excellent adaptability and high flexibility in describing arbitrary complicated signals, and are free from the limitations imposed by conventional basis expansion, thus being able to adapt to the signal characteristics, extract rich characteristic information, and therefore reveal the underlying physical nature. This paper presents a systematic and up-to-date review on adaptive mode decomposition in two major topics, i.e., mono-component decomposition algorithms (such as empirical mode composition, local mean decomposition, intrinsic time-scale decomposition, local characteristic scale decomposition, Hilbert vibration decomposition, empirical wavelet transform, variational mode decomposition, nonlinear mode decomposition, and adaptive local iterative filtering) and instantaneous frequency estimation approaches (including Hilbert-transform-based analytic signal, direct quadrature, and normalized Hilbert transform based on empirical AM-FM decomposition, as well as generalized zero-crossing and energy separation) reported in more than 80 representative articles published since 1998. Their fundamental principles, advantages and disadvantages, and applications to signal analysis in machinery fault diagnosis, are examined. Examples are provided to illustrate their performance.

Trajectory analysis of high-order-harmonic generation from periodic crystals

Abstract: We theoretically study high-order-harmonic generation (HHG) from solids driven by intense laser pulses using a one-dimensional model periodic crystal. By numerically solving the time-dependent Schr\"odinger equation directly on a real-space grid, we successfully reproduce experimentally observed unique features of solid-state HHG such as the linear cutoff-energy scaling and the sudden transition from a single- to multiple-plateau structure. Based on the simulation results, we propose a simple model that incorporates vector-potential-induced intraband displacement, interband tunneling, and recombination with the valence-band hole. One key parameter is the peak-to-valley amplitude of the pulse vector potential, which determines the crystal momentum displacement during the half cycle. When the maximum peak-to-valley amplitude ${A}_{\mathrm{peak}}$ reaches the half width $\frac{\ensuremath{\pi}}{a}$ of the Brillouin zone with $a$ being the lattice constant, the HHG spectrum exhibits a transition from a single- to multiple-plateau structure, and even further plateaus appear at ${A}_{\mathrm{peak}}=\frac{2\ensuremath{\pi}}{a},\frac{3\ensuremath{\pi}}{a},\ensuremath{\cdots}$. The multiple cutoff positions are given as functions of ${A}_{\mathrm{peak}}$ and the second maximum ${A}_{\mathrm{peak}}^{\ensuremath{'}}$, in terms of the energy difference between different bands. Using our recipe, one can draw electron trajectories in the momentum space, from which one can deduce, for example, the time-frequency structure of HHG without elaborate quantum-mechanical calculations. Finally, we reveal that the cutoff positions depend on not only the intensity and wavelength of the pulse, but also its duration, in marked contrast to the gas-phase case. Our model can be viewed as a solid-state and momentum-space counterpart of the familiar three-step model, highly successful for gas-phase HHG, and provide a unified basis to understand HHG from solid-state materials and gaseous media.

The Large Enriched Germanium Experiment for Neutrinoless Double Beta Decay (LEGEND)

Abstract: The observation of neutrinoless double-beta decay (0${ u}{\beta}{\beta}$) would show that lepton number is violated, reveal that neutrinos are Majorana particles, and provide information on neutrino mass. A discovery-capable experiment covering the inverted ordering region, with effective Majorana neutrino masses of 15 - 50 meV, will require a tonne-scale experiment with excellent energy resolution and extremely low backgrounds, at the level of $\sim$0.1 count /(FWHM$\cdot$t$\cdot$yr) in the region of the signal. The current generation $^{76}$Ge experiments GERDA and the MAJORANA DEMONSTRATOR utilizing high purity Germanium detectors with an intrinsic energy resolution of 0.12%, have achieved the lowest backgrounds by over an order of magnitude in the 0${ u}{\beta}{\beta}$ signal region of all 0${ u}{\beta}{\beta}$ experiments. Building on this success, the LEGEND collaboration has been formed to pursue a tonne-scale $^{76}$Ge experiment. The collaboration aims to develop a phased 0${ u}{\beta}{\beta}$ experimental program with discovery potential at a half-life approaching or at $10^{28}$ years, using existing resources as appropriate to expedite physics results.

Curvature Filters Efficiently Reduce Certain Variational Energies

Abstract: In image processing, the rapid approximate solution of variational problems involving generic data-fitting terms is often of practical relevance, for example in real-time applications. Variational solvers based on diffusion schemes or the Euler-Lagrange equations are too slow and restricted in the types of data-fitting terms. Here, we present a filter-based approach to reduce variational energies that contain generic data-fitting terms, but are restricted to specific regularizations. Our approach is based on reducing the regularization part of the variational energy, while guaranteeing non-increasing total energy. This is applicable to regularization-dominated models, where the data-fitting energy initially increases, while the regularization energy initially decreases. We present fast discrete filters for regularizers based on Gaussian curvature, mean curvature, and total variation. These pixel-local filters can be used to rapidly reduce the energy of the full model. We prove the convergence of the resulting iterative scheme in a greedy sense, and we show several experiments to demonstrate applications in image-processing problems involving regularization-dominated variational models.

Non-Intrusive Energy Disaggregation Using Non-Negative Matrix Factorization With Sum-to-k Constraint

Abstract: Energy disaggregation or non-intrusive load monitoring addresses the issue of extracting device-level energy consumption information by monitoring the aggregated signal at one single measurement point without installing meters on each individual device. Energy disaggregation can be formulated as a source separation problem, where the aggregated signal is expressed as linear combination of basis vectors in a matrix factorization framework. In this paper, an approach based on Sum-to-k constrained non-negative matrix factorization (S2K-NMF) is proposed. By imposing the sum-to- k constraint and the non-negative constraint, S2K-NMF is able to effectively extract perceptually meaningful sources from complex mixtures. The strength of the proposed algorithm is demonstrated through two sets of experiments: Energy disaggregation in a residential smart home; and heating, ventilating, and air conditioning components energy monitoring in an industrial building testbed maintained at the Oak Ridge National Laboratory. Extensive experimental results demonstrate the superior performance of S2K-NMF as compared to state-of-the-art decomposition-based disaggregation algorithms.

A Novel Energy Function-Based Stability Evaluation and Nonlinear Control Approach for Energy Internet

Abstract: Unlike conventional interconnected power systems, energy Internet presents an unsolved and more challenging problem for the society including transfer impedance, damping, large penetration of distributed generation, and numerous hybrid integration of generators and converters. In this paper, a novel energy function designed for energy internet router is proposed to accurately evaluate its transfer stability. The reliability of the proposed energy function is confirmed through both theoretical analysis and empirical simulations. Furthermore, generalized methods to determine critical stable energy, stable domain, and critical clearing time are proposed. By updating stability criterion and evaluating system energy of post-disturbance system, fault energy-based impulsive feedback control method is specifically designed for energy Internet to stabilize the system. Simulation and experimental results are provided to validate the effectiveness of the proposed energy function and nonlinear control method.

Acoustic Focusing and Energy Confinement Based on Multilateral Metasurfaces

Abstract: The authors describe a $c\phantom{\rule{0}{0ex}}o\phantom{\rule{0}{0ex}}i\phantom{\rule{0}{0ex}}l\phantom{\rule{0}{0ex}}i\phantom{\rule{0}{0ex}}n\phantom{\rule{0}{0ex}}g-u\phantom{\rule{0}{0ex}}p-s\phantom{\rule{0}{0ex}}p\phantom{\rule{0}{0ex}}a\phantom{\rule{0}{0ex}}c\phantom{\rule{0}{0ex}}e$ approach to harvesting energy from ubiquitous, ambient low-frequency sound. They design multilateral metasurfaces composed of a labyrinthine series, for acoustic focusing and energy confinement. Control of the first reflection, coupling effects, and multiple reflections between and among the metasurfaces are discussed.

Energy diffusion and the butterfly effect in inhomogeneous Sachdev-Ye-Kitaev chains

Abstract: We compute the energy diffusion constant $D$, Lyapunov time $\tau_{\text{L}}$ and butterfly velocity $v_{\text{B}}$ in an inhomogeneous chain of coupled Majorana Sachdev-Ye-Kitaev (SYK) models in the large $N$ and strong coupling limit. We find $D\le v_{\text{B}}^2 \tau_{\text{L}}$ from a combination of analytical and numerical approaches. Our example necessitates the sharpening of postulated transport bounds based on quantum chaos.

Riding on the primary: A new spectrum sharing paradigm for wireless-powered IoT devices

Abstract: In this paper, a new spectrum sharing model referred to as riding on the primary (RoP) is proposed for wireless- powered IoT devices with ambient backscatter communication capabilities. The key idea of RoP is that the secondary transmitter harvests energy from the primary signal, then modulates its information bits to the primary signal, and reflects the modulated signal to the secondary receiver without violating the primary system's interference requirement. Compared with the conventional spectrum sharing model, the secondary system in the proposed RoP not only utilizes the spectrum of the primary system but also takes advantage of the primary signal to harvest energy and to carry its information. In this paper, we investigate the performance of such a spectrum sharing system under fading channels. To be specific, we maximize the ergodic capacity of the secondary system by jointly optimizing the transmit power of the primary signal and the reflection coefficient of the secondary ambient backscatter. Different (ideal/practical) energy consumption models, different (peak/average) transmit power constraints, different types (fixed/dynamically adjustable) reflection coefficient are considered. Optimal power allocation and reflection coefficient are obtained for each scenario.