Showing papers on "Energy (signal processing) published in 2012"

Relaying Protocols for Wireless Energy Harvesting and Information Processing

Abstract: An emerging solution for prolonging the lifetime of energy constrained relay nodes in wireless networks is to avail the ambient radio-frequency (RF) signal and to simultaneously harvest energy and process information. In this paper, an amplify-and-forward (AF) relaying network is considered, where an energy constrained relay node harvests energy from the received RF signal and uses that harvested energy to forward the source information to the destination. Based on the time switching and power splitting receiver architectures, two relaying protocols, namely, i) time switching-based relaying (TSR) protocol and ii) power splitting-based relaying (PSR) protocol are proposed to enable energy harvesting and information processing at the relay. In order to determine the throughput, analytical expressions for the outage probability and the ergodic capacity are derived for delay-limited and delay-tolerant transmission modes, respectively. The numerical analysis provides practical insights into the effect of various system parameters, such as energy harvesting time, power splitting ratio, source transmission rate, source to relay distance, noise power, and energy harvesting efficiency, on the performance of wireless energy harvesting and information processing using AF relay nodes. In particular, the TSR protocol outperforms the PSR protocol in terms of throughput at relatively low signal-to-noise-ratios and high transmission rate.

Optimal Energy Allocation for Wireless Communications With Energy Harvesting Constraints

Abstract: We consider the use of energy harvesters, in place of conventional batteries with fixed energy storage, for point-to-point wireless communications. In addition to the challenge of transmitting in a channel with time selective fading, energy harvesters provide a perpetual but unreliable energy source. In this paper, we consider the problem of energy allocation over a finite horizon, taking into account channel conditions and energy sources that are time varying, so as to maximize the throughput. Two types of side information (SI) on the channel conditions and harvested energy are assumed to be available: causal SI (of the past and present slots) or full SI (of the past, present and future slots). We obtain structural results for the optimal energy allocation, via the use of dynamic programming and convex optimization techniques. In particular, if unlimited energy can be stored in the battery with harvested energy and the full SI is available, we prove the optimality of a water-filling energy allocation solution where the so-called water levels follow a staircase function.

Dense electron-positron plasmas and ultraintense γ rays from laser-irradiated solids.

Abstract: In simulations of a 10 PW laser striking a solid, we demonstrate the possibility of producing a pure electron-positron plasma by the same processes as those thought to operate in high-energy astrophysical environments. A maximum positron density of ${10}^{26}\text{ }\text{ }{\mathrm{m}}^{\ensuremath{-}3}$ can be achieved, 7 orders of magnitude greater than achieved in previous experiments. Additionally, $35%$ of the laser energy is converted to a burst of $\ensuremath{\gamma}$ rays of intensity ${10}^{22}\text{ }\text{ }\mathrm{W}\text{ }{\mathrm{cm}}^{\ensuremath{-}2}$, potentially the most intense $\ensuremath{\gamma}$-ray source available in the laboratory. This absorption results in a strong feedback between both pair and $\ensuremath{\gamma}$-ray production and classical plasma physics in the new ``QED-plasma'' regime.

Chiral representation of the π N scattering amplitude and the pion-nucleon sigma term

Abstract: We present a novel analysis of the $\ensuremath{\pi}N$ scattering amplitude in Lorentz covariant baryon chiral perturbation theory renormalized in the extended-on-mass-shell scheme. This amplitude, valid up to $\mathcal{O}({p}^{3})$ in the chiral expansion, systematically includes the effects of the $\ensuremath{\Delta}(1232)$ in the $\ensuremath{\delta}$-counting, has the right analytic properties, and is renormalization-scale independent. This approach overcomes the limitations that previous chiral analyses of the $\ensuremath{\pi}N$ scattering amplitude had, providing an accurate description of the partial wave phase shifts of the Karlsruhe-Helsinki and George-Washington groups up to energies just below the resonance region. We also study the solution of the Matsinos group which focuses on the parameterization of the data at low energies. Once the values of the low-energy constants are determined by adjusting the center-of-mass energy dependence of the amplitude to the scattering data, we obtain predictions on different observables. In particular, we extract an accurate value for the pion-nucleon sigma term, ${\ensuremath{\sigma}}_{\ensuremath{\pi}N}$. This allows us to avoid the usual method of extrapolation to the unphysical region of the amplitude. Our study indicates that the inclusion of modern meson-factory and pionic-atom data favors relatively large values of the sigma term. We report the value ${\ensuremath{\sigma}}_{\ensuremath{\pi}N}=59(7)\text{ }\text{ }\mathrm{MeV}$ and comment on implications that this result may have.

Controlling Complex Networks: How Much Energy Is Needed?

Abstract: The outstanding problem of controlling complex networks is relevant to many areas of science and engineering, and has the potential to generate technological breakthroughs as well. We address the physically important issue of the energy required for achieving control by deriving and validating scaling laws for the lower and upper energy bounds. These bounds represent a reasonable estimate of the energy cost associated with control, and provide a step forward from the current research on controllability toward ultimate control of complex networked dynamical systems.

The energy–speed–accuracy trade-off in sensory adaptation

Abstract: Adaptation is the essential process by which an organism becomes better suited to its environment. The benefits of adaptation are well documented, but the cost it incurs remains poorly understood. Here, by analysing a stochastic model of a minimum feedback network underlying many sensory adaptation systems, we show that adaptive processes are necessarily dissipative, and continuous energy consumption is required to stabilize the adapted state. Our study reveals a general relation among energy dissipation rate, adaptation speed and the maximum adaptation accuracy. This energy-speed-accuracy relation is tested in the Escherichia coli chemosensory system, which exhibits near-perfect chemoreceptor adaptation. We identify key requirements for the underlying biochemical network to achieve accurate adaptation with a given energy budget. Moreover, direct measurements confirm the prediction that adaptation slows down as cells gradually de-energize in a nutrient-poor medium without compromising adaptation accuracy. Our work provides a general framework to study cost-performance tradeoffs for cellular regulatory functions and information processing.

Energy-Based Geometric Multi-model Fitting

Abstract: Geometric model fitting is a typical chicken-&-egg problem: data points should be clustered based on geometric proximity to models whose unknown parameters must be estimated at the same time. Most existing methods, including generalizations of RANSAC, greedily search for models with most inliers (within a threshold) ignoring overall classification of points. We formulate geometric multi-model fitting as an optimal labeling problem with a global energy function balancing geometric errors and regularity of inlier clusters. Regularization based on spatial coherence (on some near-neighbor graph) and/or label costs is NP hard. Standard combinatorial algorithms with guaranteed approximation bounds (e.g. ?-expansion) can minimize such regularization energies over a finite set of labels, but they are not directly applicable to a continuum of labels, e.g. ${\mathcal{R}}^{2}$ in line fitting. Our proposed approach (PEaRL) combines model sampling from data points as in RANSAC with iterative re-estimation of inliers and models' parameters based on a global regularization functional. This technique efficiently explores the continuum of labels in the context of energy minimization. In practice, PEaRL converges to a good quality local minimum of the energy automatically selecting a small number of models that best explain the whole data set. Our tests demonstrate that our energy-based approach significantly improves the current state of the art in geometric model fitting currently dominated by various greedy generalizations of RANSAC.

Achieving AWGN Capacity Under Stochastic Energy Harvesting

Abstract: In energy harvesting communication systems, an exogenous recharge process supplies energy necessary for data transmission and the arriving energy can be buffered in a battery before consumption. We determine the information-theoretic capacity of the classical additive white Gaussian noise (AWGN) channel with an energy harvesting transmitter with an unlimited sized battery. As the energy arrives randomly and can be saved in the battery, codewords must obey cumulative stochastic energy constraints. We show that the capacity of the AWGN channel with such stochastic channel input constraints is equal to the capacity with an average power constraint equal to the average recharge rate. We provide two capacity achieving schemes: save-and-transmit and best-effort-transmit. In the save-and-transmit scheme, the transmitter collects energy in a saving phase of proper duration that guarantees that there will be no energy shortages during the transmission of code symbols. In the best-effort-transmit scheme, the transmission starts right away without an initial saving period, and the transmitter sends a code symbol if there is sufficient energy in the battery, and a zero symbol otherwise. Finally, we consider a system in which the average recharge rate is time varying in a larger time scale and derive the optimal offline power policy that maximizes the average throughput, by using majorization theory.

Second-order Convex Splitting Schemes for Gradient Flows with Ehrlich-Schwoebel Type Energy: Application to Thin Film Epitaxy

Abstract: We construct unconditionally stable, unconditionally uniquely solvable, and second-order accurate (in time) schemes for gradient flows with energy of the form $\int_\Omega ( F( abla\phi({\bf x})) + \frac{\epsilon^2}{2}|\Delta\phi({\bf x})|^2 ) d{\bf x}$. The construction of the schemes involves the appropriate combination and extension of two classical ideas: (i) appropriate convex-concave decomposition of the energy functional and (ii) the secant method. As an application, we derive schemes for epitaxial growth models with slope selection ($F({\bf y})= \frac14(|{\bf y}|^2-1)^2$) or without slope selection ($F({\bf y})=-\frac12\ln(1+|{\bf y}|^2)$). Two types of unconditionally stable uniquely solvable second-order schemes are presented. The first type inherits the variational structure of the original continuous-in-time gradient flow, while the second type does not preserve the variational structure. We present numerical simulations for the case with slope selection which verify well-known physical scaling laws for the long time coarsening process.

Event-by-event gluon multiplicity, energy density, and eccentricities in ultrarelativistic heavy-ion collisions

Abstract: The event-by-event multiplicity distribution, the energy densities and energy density weighted eccentricity moments ${\ensuremath{\epsilon}}_{n}$ (up to $n=6$) at early times in heavy-ion collisions at both the BNL Relativistic Heavy Ion Collider (RHIC) ($\sqrt{s}=200\phantom{\rule{0.16em}{0ex}}\mathrm{GeV}$) and the CERN Large Hardron Collider (LHC) ($\sqrt{s}=2.76\phantom{\rule{0.16em}{0ex}}\mathrm{TeV}$) are computed in the IP-Glasma model. This framework combines the impact parameter dependent saturation model (IP-Sat) for nucleon parton distributions (constrained by HERA deeply inelastic scattering data) with an event-by-event classical Yang-Mills description of early-time gluon fields in heavy-ion collisions. The model produces multiplicity distributions that are convolutions of negative binomial distributions without further assumptions or parameters. In the limit of large dense systems, the $n$-particle gluon distribution predicted by the Glasma-flux tube model is demonstrated to be nonperturbatively robust. In the general case, the effect of additional geometrical fluctuations is quantified. The eccentricity moments are compared to the MC-KLN model; a noteworthy feature is that fluctuation dominated odd moments are consistently larger than in the MC-KLN model.

Numerical studies of confined states in rotated bilayers of graphene

Abstract: Rotated graphene multilayers form a new class of graphene-related systems with electronic properties that drastically depend on the rotation angles. It has been shown that bilayers behave like two isolated graphene planes for large rotation angles. For smaller angles, states in the Dirac cones belonging to the two layers interact resulting in the appearance of two Van Hove singularities. States become localized as the rotation angle decreases and the two Van Hove singularities merge into one peak at the Dirac energy. Here we go further and consider bilayers with very small rotation angles. In this case, well-defined regions of AA stacking exist in the bilayer supercell and we show that states are confined in these regions for energies in the [$\ensuremath{-}{\ensuremath{\gamma}}_{t}$, $+{\ensuremath{\gamma}}_{t}$] range with ${\ensuremath{\gamma}}_{t}$ the interplane mean interaction. As a consequence, the local densities of states show discrete peaks for energies different from the Dirac energy.

A general framework for the optimization of energy harvesting communication systems with battery imperfections

Abstract: Energy harvesting has emerged as a powerful technology for complementing current battery-powered communication systems in order to extend their lifetime. In this paper a general framework is introduced for the optimization of communication systems in which the transmitter is able to harvest energy from its environment. Assuming that the energy arrival process is known non-causally at the transmitter, the structure of the optimal transmission scheme, which maximizes the amount of transmitted data by a given deadline, is identified. Our framework includes models with continuous energy arrival as well as battery constraints. A battery that suffers from energy leakage is studied further, and the optimal transmission scheme is characterized for a constant leakage rate.

Mapping the hydrodynamic response to the initial geometry in heavy-ion collisions

Abstract: We investigate how the initial geometry of a heavy-ion collision is transformed into final flow observables by solving event-by-event ideal hydrodynamics with realistic fluctuating initial conditions. We study quantitatively to what extent anisotropic flow (${v}_{n}$) is determined by the initial eccentricity ${\ensuremath{\varepsilon}}_{n}$ for a set of realistic simulations, and we discuss which definition of ${\ensuremath{\varepsilon}}_{n}$ gives the best estimator of ${v}_{n}$. We find that the common practice of using an ${r}^{2}$ weight in the definition of ${\ensuremath{\varepsilon}}_{n}$ in general results in a poorer predictor of ${v}_{n}$ than when using ${r}^{n}$ weight, for $ng2$. We similarly study the importance of additional properties of the initial state. For example, we show that in order to correctly predict ${v}_{4}$ and ${v}_{5}$ for noncentral collisions, one must take into account nonlinear terms proportional to ${\ensuremath{\varepsilon}}_{2}^{2}$ and ${\ensuremath{\varepsilon}}_{2}{\ensuremath{\varepsilon}}_{3}$, respectively. We find that it makes no difference whether one calculates the eccentricities over a range of rapidity or in a single slice at $z=0$, nor is it important whether one uses an energy or entropy density weight. This knowledge will be important for making a more direct link between experimental observables and hydrodynamic initial conditions, the latter being poorly constrained at present.

Bakry-\'Emery curvature-dimension condition and Riemannian Ricci curvature bounds

Abstract: The aim of the present paper is to bridge the gap between the Bakry-\'{E}mery and the Lott-Sturm-Villani approaches to provide synthetic and abstract notions of lower Ricci curvature bounds. We start from a strongly local Dirichlet form ${{\mathcal{E}}}$ admitting a Carr\'{e} du champ $\Gamma$ in a Polish measure space $(X,\mathfrak{m})$ and a canonical distance ${\mathsf{d}}_{{{\mathcal{E}}}}$ that induces the original topology of $X$. We first characterize the distinguished class of Riemannian Energy measure spaces, where ${\mathcal{E}}$ coincides with the Cheeger energy induced by ${\mathsf{d}}_{{\mathcal{E}}}$ and where every function $f$ with $\Gamma(f)\le1$ admits a continuous representative. In such a class, we show that if ${{\mathcal{E}}}$ satisfies a suitable weak form of the Bakry-\'{E}mery curvature dimension condition $\mathrm {BE}(K,\infty)$ then the metric measure space $(X,{\mathsf{d}},\mathfrak{m})$ satisfies the Riemannian Ricci curvature bound $\mathrm {RCD}(K,\infty)$ according to [Duke Math. J. 163 (2014) 1405-1490], thus showing the equivalence of the two notions. Two applications are then proved: the tensorization property for Riemannian Energy spaces satisfying the Bakry-\'{E}mery $\mathrm {BE}(K,N)$ condition (and thus the corresponding one for $\mathrm {RCD}(K,\infty)$ spaces without assuming nonbranching) and the stability of $\mathrm {BE}(K,N)$ with respect to Sturm-Gromov-Hausdorff convergence.

Improved energy detection spectrum sensing for cognitive radio

Abstract: Energy detection constitutes a preferred approach for spectrum sensing in cognitive radio owing to its simplicity and applicability (it works irrespective of the signal format to be detected) as well as its low computational and implementation costs. The main drawback, however, is its well-known detection performance limitations. Various alternative detection methods have been shown to outperform energy detection, but at the expense of increased complexity and confined field of applicability. In this context, this work proposes and evaluates an improved version of the energy detection algorithm that is able to outperform the classical energy detection scheme while preserving a similar level of algorithm complexity as well as its general applicability regardless of the particular signal format or structure to be detected. The performance improvement is evaluated analytically and corroborated with the experimental results.

Time-dependent density functional theory for strong electromagnetic fields in crystalline solids

Abstract: We apply the coupled dynamics of time-dependent density functional theory and Maxwell equations to the interaction of intense laser pulses with crystalline silicon. As a function of electromagnetic field intensity, we see several regions in the response. At the lowest intensities, the pulse is reflected and transmitted in accord with the dielectric response, and the characteristics of the energy deposition are consistent with two-photon absorption. The absorption process begins to deviate from that at laser intensities of $\ensuremath{\sim}$${10}^{13}$ W/cm${}^{2}$, where the energy deposited is of the order of 1 eV per atom. Changes in the reflectivity are seen as a function of intensity. When it passes a threshold of about $3\ifmmode\times\else\texttimes\fi{}{10}^{12}$ W/cm${}^{2}$, there is a small decrease. At higher intensities, above $2\ifmmode\times\else\texttimes\fi{}{10}^{13}$ W/cm${}^{2}$, the reflectivity increases strongly. This behavior can be understood qualitatively in a model treating the excited electron-hole pairs as a plasma.

Pro-Energy: A novel energy prediction model for solar and wind energy-harvesting wireless sensor networks

Abstract: Energy harvesting is one of the most promising technologies towards the goal of perpetual operation of wireless sensor networks (WSNs). Environmentally-powered systems, however, have to deal with the variable behavior of ambient energy sources, which results in different amounts and rates of energy available over time. To alleviate the problem of the harvested power being neither constant nor continuous, energy prediction methods can be employed. Such models forecast the source availability and estimate the expected energy intake, allowing the system to take critical decisions about the utilization of the available energy. In this work, we present a novel energy prediction model, named Pro-Energy (PROfile energy prediction model), for multi-source energy harvesting WSNs, which is able to leverage past energy observations to provide accurate estimations of future energy availability. To assess the performance of our proposed solution, we use real-life solar and wind traces that we collected by interfacing TelosB nodes with solar cells and wind micro-turbines, as well as public available traces of solar and wind obtained from weather monitoring stations in the US. A comparative performance evaluation between Pro-Energy and energy predictors previously proposed in the literature, such as EWMA and WCMA, has shown that our solution significantly outperforms existing algorithms for both short and medium term prediction horizons, improving the prediction accuracy up to 60%.

The molecular gas in Luminous Infrared Galaxies II: extreme physical conditions, and their effects on the X_{co} factor

Abstract: In this work we conclude the analysis of our CO line survey of Luminous Infrared Galaxies (LIRGs: L_{IR}>=10^{11}L_{sol}) in the local Universe (Paper\,I), by focusing on the influence of their average ISM properties on the total molecular gas mass estimates via the so-called X_{co}=M(H_2)/L_{co,1-0} factor. One-phase radiative transfer models of the global CO Spectral Line Energy Distributions (SLEDs) yield an X_{co} distribution with: \sim(0.6+/-0.2) M_{sol}(K km s^{-1} pc^2)^{-1} over a significant range of average gas densities, temperatures and dynamical states. The latter emerges as the most important parameter in determining X_{co}, with unbound states yielding low values and self-gravitating states the highest ones. Nevertheless in many (U)LIRGs where available higher-J CO lines (J=3--2, 4--3, and/or J=6--5) or HCN line data from the literature allow a separate assessment of the gas mass at high densities (>=10^{4} cm^{-3}) rather than a simple one-phase analysis we find that {\it near-Galactic X_{co} (3-6)\, M_sol\,(K\,km^{-1}\,pc^2)^{-1} values become possible.} We further show that in the highly turbulent molecular gas in ULIRGs a high-density component will be common and can be massive enough for its high X_{co} to dominate the average value for the entire galaxy. ......... ...this may have thus resulted to systematic underestimates of molecular gas mass in ULIRGs.

System and method for power control in a physical layer device

Abstract: A system and method for power control in a physical layer device. Energy savings during an active state can be produced through the monitoring of a received signal level by a receiver in a physical layer device. In one embodiment, based on an indication of the received signal level or other communication characteristic of the transmission medium, a control module can adjust the signal level or amplitude and/or adjust the voltage supply.

High-resolution supernova neutrino spectra represented by a simple fit

Abstract: To study the capabilities of supernova neutrino detectors, the instantaneous spectra are often represented by a quasithermal distribution of the form ${f}_{\ensuremath{ u}}(E)\ensuremath{\propto}{E}^{\ensuremath{\alpha}}{e}^{\ensuremath{-}(\ensuremath{\alpha}+1)E/{E}_{\mathrm{av}}}$, where ${E}_{\mathrm{av}}$ is the average energy and $\ensuremath{\alpha}$ a numerical parameter. Based on a spherically symmetric supernova model with full Boltzmann neutrino transport we have, at a few representative postbounce times, reconverged the models with vastly increased energy resolution to test the fit quality. For our examples, the spectra are well represented by such a fit in the sense that the counting rates for a broad range of target nuclei, sensitive to different parts of the spectrum, are reproduced very well. Therefore, the mean energy and root-mean-square energy of numerical spectra hold enough information to provide the correct $\ensuremath{\alpha}$ and to forecast the response of multichannel supernova neutrino detection.

Millikelvin reactive collisions between sympathetically cooled molecular ions and laser-cooled atoms in an ion-atom hybrid trap.

Abstract: We report on a study of cold reactive collisions between sympathetically cooled molecular ions and laser-cooled atoms in an ion-atom hybrid trap. Chemical reactions were studied at average collision energies $⟨{E}_{\mathrm{coll}}⟩/{k}_{\mathrm{B}}\ensuremath{\gtrsim}20\text{ }\text{ }\mathrm{mK}$, about 2 orders of magnitude lower than has been achieved in previous experiments with molecular ions. Choosing ${\mathrm{N}}_{2}^{+}+\mathrm{Rb}$ as a prototypical system, we find that the reaction rate is independent of the collision energy within the range studied, but strongly dependent on the internal state of Rb. Highly efficient charge exchange four times faster than the Langevin rate was observed with Rb in the excited ($5p$) $^{2}P_{3/2}$ state. This observation is rationalized by a capture process dominated by the charge-quadrupole interaction and a near resonance between the entrance and exit channels of the system. Our results provide a test of classical models for reactions of molecular ions at the lowest energies reached thus far.

Free-space nitrogen gas laser driven by a femtosecond filament

Abstract: We report an experimental proof and full characterization of laser generation in molecular nitrogen in an argon-nitrogen gas mixture remotely excited at a distance above 2 m in a femtosecond laser filament. Filamentation experiments performed with near-infrared, 1-\ensuremath{\mu}m-wavelength and midinfrared, 4-\ensuremath{\mu}m-wavelength short-pulse laser sources show that mid-IR laser pulses enable radical enhancement of filamentation-assisted lasing by N${}_{2}$ molecules. Energies as high as 3.5 \ensuremath{\mu}J are achieved for the 337- and 357-nm laser pulses generated through the second-positive-band transitions of N${}_{2}$, corresponding to a 0.5$%$ total conversion efficiency from midinfrared laser energy to the energy of UV lasing.

Non-Intrusive Demand Monitoring and Load Identification for Energy Management Systems Based on Transient Feature Analyses

Abstract: Energy management systems strive to use energy resources efficiently, save energy, and reduce carbon output. This study proposes transient feature analyses of the transient response time and transient energy on the power signatures of non-intrusive demand monitoring and load identification to detect the power demand and load operation. This study uses the wavelet transform (WT) of the time-frequency domain to analyze and detect the transient physical behavior of loads during the load identification. The experimental results show the transient response time and transient energy are better than the steady-state features to improve the recognition accuracy and reduces computation requirements in non-intrusive load monitoring (NILM) systems. The discrete wavelet transform (DWT) is more suitable than short-time Fourier transform (STFT) for transient load analyses.

A Linear Energy Stable Scheme for a Thin Film Model Without Slope Selection

Abstract: We present a linear numerical scheme for a model of epitaxial thin film growth without slope selection. The PDE, which is a nonlinear, fourth-order parabolic equation, is the L2 gradient flow of the energy \(\int_{\Omega}( - \frac{1}{2} \ln(1 + | abla\phi|^{2} ) + \frac{\epsilon^{2}}{2}|\Delta\phi(\mathbf{x})|^{2})\,\mathrm{d}\mathbf{x}\). The idea of convex-concave decomposition of the energy functional is applied, which results in a numerical scheme that is unconditionally energy stable, i.e., energy dissipative. The particular decomposition used here places the nonlinear term in the concave part of the energy, in contrast to a previous convexity splitting scheme. As a result, the numerical scheme is fully linear at each time step and unconditionally solvable. Collocation Fourier spectral differentiation is used in the spatial discretization, and the unconditional energy stability is established in the fully discrete setting using a detailed energy estimate. We present numerical simulation results for a sequence of ϵ values ranging from 0.02 to 0.1. In particular, the long time simulations show the −log(t) decay law for the energy and the t1/2 growth law for the surface roughness, in agreement with theoretical analysis and experimental/numerical observations in earlier works.

Stop the Top Background of the Stop Search

Abstract: The main background for the supersymmetric stop direct production search comes from Standard Model $ t\overline t $ events. For the single-lepton search channel, we introduce a few kinematic variables to further suppress this background by focusing on its dileptonic and semileptonic topologies. All are defined to have end points in the background, but not signal distributions. They can substantially improve the stop signal significance and mass reach when combined with traditional kinematic variables such as the total missing transverse energy. Among them, our variable $ M_{{T2}}^W $ hasthebestoverallperformancebecause it uses all available kinematic information, including the on-shell mass of both W’s. We see 20 %-30 % improvement on the discovery significance and estimate that the 8 TeV LHC run with 20 fb−1 of data would be able to reach an exclusion limit of 650-700 GeV for direct stop production, as long as the stop decays dominantly to the top quark and a light stable neutralino. Most of the mass range required for the supersymmetric solution of the naturalness problem in the standard scenario can be covered.

Electric field control of nonvolatile four-state magnetization at room temperature.

Abstract: We find the realization of large converse magnetoelectric (ME) effects at room temperature in a magnetoelectric hexaferrite ${\mathrm{Ba}}_{0.52}{\mathrm{Sr}}_{2.48}{\mathrm{Co}}_{2}{\mathrm{Fe}}_{24}{\mathrm{O}}_{41}$ single crystal, in which rapid change of electric polarization in low magnetic fields (about 5 mT) is coined to a large ME susceptibility of $3200\text{ }\text{ }\mathrm{ps}/\mathrm{m}$. The modulation of magnetization then reaches up to $0.62{\ensuremath{\mu}}_{B}/\mathrm{f}.\mathrm{u}$. in an electric field of $1.14\text{ }\text{ }\mathrm{MV}/\mathrm{m}$. We find further that four ME states induced by different ME poling exhibit unique, nonvolatile magnetization versus electric field curves, which can be approximately described by an effective free energy with a distinct set of ME coefficients.