Effective generation of Ising interaction and cluster states in coupled microcavities

We propose a scheme for realizing the Ising spin-spin interaction and atomic cluster states utilizing trapped atoms in coupled microcavities. It is shown that the atoms can interact with each other via the exchange of virtual photons of the cavities. Through suitably tuning the parameters, an effective Ising spin-spin interaction can be generated in this optical system, which is used to produce the cluster states. This scheme does not need the preparation of initial states of atoms and cavity modes, and is insensitive to cavity decay.Comment: 11pages, 2 figures, Revtex

On Mitigation of Side-Channel Attacks in 3D ICs: Decorrelating Thermal Patterns from Power and Activity

Various side-channel attacks (SCAs) on ICs have been successfully demonstrated and also mitigated to some degree. In the context of 3D ICs, however, prior art has mainly focused on efficient implementations of classical SCA countermeasures. That is, SCAs tailored for up-and-coming 3D ICs have been overlooked so far. In this paper, we conduct such a novel study and focus on one of the most accessible and critical side channels: thermal leakage of activity and power patterns. We address the thermal leakage in 3D ICs early on during floorplanning, along with tailored extensions for power and thermal management. Our key idea is to carefully exploit the specifics of material and structural properties in 3D ICs, thereby decorrelating the thermal behaviour from underlying power and activity patterns. Most importantly, we discuss powerful SCAs and demonstrate how our open-source tool helps to mitigate them.Comment: Published in Proc. Design Automation Conference, 201

Graphene-polyelectrolyte multilayer membranes with tunable structure and internal charge

One great advantage of graphene-polyelectrolyte multilayer (GPM) membranes is their tunable structure and internal charge for improved separation performance. In this study, we synthesized GO-dominant GPM membrane with internal negatively-charged domains, polyethyleneimine (PEI)-dominant GPM membrane with internal positively-charged domains and charge-balanced dense/loose GPM membranes by simply adjusting the ionic strength and pH of the GO and PEI solutions used in layer-by-layer membrane synthesis. A combined system of quartz crystal microbalance with dissipation (QCM-D) and ellipsometry was used to analyze the mass deposition, film thickness, and layer density of the GPM membranes. The performance of the GPM membranes were compared in terms of both permeability and selectivity to determine the optimal membrane structure and synthesis strategy. One effective strategy to improve the GPM membrane permeability-selectivity tradeoff is to assemble charge-balanced dense membranes under weak electrostatic interactions. This balanced membrane exhibits the highest MgCl2 selectivity (∼86%). Another effective strategy for improved cation removal is to create PEI-dominant membranes that provide internal positively-charged barrier to enhance cation selectivity without sacrificing water permeability. These findings shine lights on the development of a systematic approach to push the boundary of permeability-selectivity tradeoff for GPM membranes

Earth matter density uncertainty in atmospheric neutrino oscillations

That muon neutrinos $\nu_{\mu}$ oscillating into the mixture of tau neutrinos $\nu_{\tau}$ and sterile neutrinos $\nu_{s}$ has been studied to explain the atmospheric $\nu_{\mu}$ disappearance. In this scenario, the effect of Earth matter is a key to determine the fraction of $\nu_{s}$. Considering that the Earth matter density has uncertainty and this uncertainty has significant effects in some neutrino oscillation cases, such as the CP violation in very long baseline neutrino oscillations and the day-night asymmetry for solar neutrinos, we study the effects caused by this uncertainty in the above atmospheric $\nu_{\mu}$ oscillation scenario. We find that this uncertainty seems to have no significant effects and that the previous fitting results need not to be modified fortunately.Comment: 7 pages, 1 figure, to appear in Phys. Rev.

Fast Monte Carlo Simulation for Patient-specific CT/CBCT Imaging Dose Calculation

Recently, X-ray imaging dose from computed tomography (CT) or cone beam CT (CBCT) scans has become a serious concern. Patient-specific imaging dose calculation has been proposed for the purpose of dose management. While Monte Carlo (MC) dose calculation can be quite accurate for this purpose, it suffers from low computational efficiency. In response to this problem, we have successfully developed a MC dose calculation package, gCTD, on GPU architecture under the NVIDIA CUDA platform for fast and accurate estimation of the x-ray imaging dose received by a patient during a CT or CBCT scan. Techniques have been developed particularly for the GPU architecture to achieve high computational efficiency. Dose calculations using CBCT scanning geometry in a homogeneous water phantom and a heterogeneous Zubal head phantom have shown good agreement between gCTD and EGSnrc, indicating the accuracy of our code. In terms of improved efficiency, it is found that gCTD attains a speed-up of ~400 times in the homogeneous water phantom and ~76.6 times in the Zubal phantom compared to EGSnrc. As for absolute computation time, imaging dose calculation for the Zubal phantom can be accomplished in ~17 sec with the average relative standard deviation of 0.4%. Though our gCTD code has been developed and tested in the context of CBCT scans, with simple modification of geometry it can be used for assessing imaging dose in CT scans as well.Comment: 18 pages, 7 figures, and 1 tabl

Thermodynamic Machine Learning through Maximum Work Production

Adaptive systems -- such as a biological organism gaining survival advantage, an autonomous robot executing a functional task, or a motor protein transporting intracellular nutrients -- must model the regularities and stochasticity in their environments to take full advantage of thermodynamic resources. Analogously, but in a purely computational realm, machine learning algorithms estimate models to capture predictable structure and identify irrelevant noise in training data. This happens through optimization of performance metrics, such as model likelihood. If physically implemented, is there a sense in which computational models estimated through machine learning are physically preferred? We introduce the thermodynamic principle that work production is the most relevant performance metric for an adaptive physical agent and compare the results to the maximum-likelihood principle that guides machine learning. Within the class of physical agents that most efficiently harvest energy from their environment, we demonstrate that an efficient agent's model explicitly determines its architecture and how much useful work it harvests from the environment. We then show that selecting the maximum-work agent for given environmental data corresponds to finding the maximum-likelihood model. This establishes an equivalence between nonequilibrium thermodynamics and dynamic learning. In this way, work maximization emerges as an organizing principle that underlies learning in adaptive thermodynamic systems.Comment: 29 pages, 10 figures, 6 appendices; http://csc.ucdavis.edu/~cmg/compmech/pubs/tml.ht

Detrended fluctuation analysis for fractals and multifractals in higher dimensions

One-dimensional detrended fluctuation analysis (1D DFA) and multifractal detrended fluctuation analysis (1D MF-DFA) are widely used in the scaling analysis of fractal and multifractal time series because of being accurate and easy to implement. In this paper we generalize the one-dimensional DFA and MF-DFA to higher-dimensional versions. The generalization works well when tested with synthetic surfaces including fractional Brownian surfaces and multifractal surfaces. The two-dimensional MF-DFA is also adopted to analyze two images from nature and experiment and nice scaling laws are unraveled.Comment: 7 Revtex pages inluding 11 eps figure

Terahertz Hall Measurements On Optimally Doped Single Crystal Bi-2212

The infrared Hall angle in optimally doped single crystal $\rm Bi_2 Sr_2 Ca Cu_2 O_{8+x}$ was measured from 3.05 to 21.75 meV as a continuous function of temperature from 25 to 300\,K. In the normal state, the temperature dependence of the real part of the cotangent of the infrared Hall angle obeys the same power law as dc measurements. The measured Hall frequency $\rm \omega_H$ is significantly larger than the expected value based upon ARPES data analyzed in terms of the relaxation time approximation. This discrepancy as well as the temperature dependence of $\rm Re(\cot{\theta_H})$ and $\omega_H$ is well described by a Fermi liquid theory in which current vertex corrections produced by electron-magnon scattering are included.Comment: 10 pages, 2 figure

Charge dynamics in the phase string model for high-Tc superconductors

An understanding of the anomalous charge dynamics in the high-Tc cuprates is obtained based on a model study of doped Mott insulators. The high-temperature optical conductivity is found to generally have a two-component structure: a Drude like part followed by a mid-infrared band. The scattering rate associated with the Drude part exhibits a linear-temperature dependence over a wide range of high temperature, while the Drude term gets progressively suppressed below a characteristic energy of magnetic origin as the system enters the pseudogap phase. The high-energy optical conductivity shows a resonancelike feature in an underdoped case and continuously evolves into a 1/\omega tail at higher doping, indicating that they share the same physical origin. In particular, such a high-energy component is closely correlated with the \omega-peak structure of the density-density correlation function at different momenta, in systematic consistency with exact diagonalization results based on the t-J model. The underlying physics is attributed to the high-energy spin-charge separation in the model, in which the "mode coupling" responsible for the anomalous charge properties is not between the electrons and some collective mode but rather between new charge carriers, holons, and a novel topological gauge field controlled by spin dynamics, as the consequence of the strong short-range electron-electron Coulomb repulsion in the doped Mott insulator.Comment: 19 pages, 13 figures; final version to appear in Phys. Rev.