Noise-Activated Escape from a Sloshing Potential Well

We treat the noise-activated escape from a one-dimensional potential well of an overdamped particle, to which a periodic force of fixed frequency is applied. We determine the boundary layer behavior, and the physically relevant length scales, near the oscillating well top. We show how stochastic behavior near the well top generalizes the behavior first determined by Kramers, in the case without forcing. Both the case when the forcing dies away in the weak noise limit, and the case when it does not, are examined. We also discuss the relevance of various scaling regimes to recent optical trap experiments.Comment: 9 pages, no figures, REVTeX, expanded versio

Alternative Buffer-Layers for the Growth of SrBi2Ta2O9 on Silicon

In this work we investigate the influence of the use of YSZ and CeO2/YSZ as insulators for Metal- Ferroelectric-Insulator-Semiconductor (MFIS) structures made with SrBi2Ta2O9 (SBT). We show that by using YSZ only the a-axis oriented Pyrochlore phase could be obtained. On the other hand the use of a CeO2/YSZ double-buffer layer gave a c-axis oriented SBT with no amorphous SiO2 inter- diffusion layer. The characteristics of MFIS diodes were greatly improved by the use of the double buffer. Using the same deposition conditions the memory window could be increased from 0.3 V to 0.9 V. From the piezoelectric response, nano-meter scale ferroelectric domains could be clearly identified in SBT thin films.Comment: 5 pages, 9 figures, 13 refernece

Chains of large gaps between primes

Let $p_n$ denote the $n$-th prime, and for any $k \geq 1$ and sufficiently large $X$, define the quantity $$G_k(X) := \max_{p_{n+k} \leq X} \min( p_{n+1}-p_n, \dots, p_{n+k}-p_{n+k-1} ),$$ which measures the occurrence of chains of $k$ consecutive large gaps of primes. Recently, with Green and Konyagin, the authors showed that $$G_1(X) \gg \frac{\log X \log \log X\log\log\log\log X}{\log \log \log X}$$ for sufficiently large $X$. In this note, we combine the arguments in that paper with the Maier matrix method to show that $$G_k(X) \gg \frac{1}{k^2} \frac{\log X \log \log X\log\log\log\log X}{\log \log \log X}$$ for any fixed $k$ and sufficiently large $X$. The implied constant is effective and independent of $k$.Comment: 16 pages, no figure

Experimental Test of Momentum Cooling Model Predictions at COSY and Conclusions for WASA and HESR

The High-Energy Storage Ring (HESR) of the future International Facility for Antiproton and Ion Research (FAIR) at GSI in Darmstadt is planned as an anti-proton cooler ring in the momentum range from 1.5 to 15 GeV/c. An important and challenging feature of the new facility is the combination of highly dense phase space cooled beams with internal targets. A detailed numerical and analytical approach to the Fokker-Planck equation for longitudinal filter cooling including the beam - target interaction has been carried out to demonstrate the stochastic cooling capability. To gain confidence in the model predictions a series of experimental stochastic cooling studies with the internal target ANKE at COSY have been carried out. A remarkable agreement between model and experiment was achieved. On this basis longitudinal stochastic cooling simulations were performed to predict the possibilities and limits of cooling when the newly installed WASA Pellet-target is operated.Comment: 17 pages, 11 figures, Talk given at Symposium on Meson Physics at COSY-11 and WASA-at-COSY, Cracow, Poland, 17-22 Jun 200

d-wave Superconductivity in the Hubbard Model

The superconducting instabilities of the doped repulsive 2D Hubbard model are studied in the intermediate to strong coupling regime with help of the Dynamical Cluster Approximation (DCA). To solve the effective cluster problem we employ an extended Non Crossing Approximation (NCA), which allows for a transition to the broken symmetry state. At sufficiently low temperatures we find stable d-wave solutions with off-diagonal long range order. The maximal $T_c\approx 150K$ occurs for a doping $\delta\approx 20$ and the doping dependence of the transition temperatures agrees well with the generic high-$T_c$ phase diagram.Comment: 5 pages, 5 figure

Critical values of a kernel density-based mutual information estimator

Copyright © 2006 IEEERecently, mutual information (MI) has become widely recognized as a statistical measure of dependence that is suitable for applications where data are non-Gaussian, or where the dependency between variables is non-linear. However, a significant disadvantage of this measure is the inability to define an analytical expression for the distribution of MI estimators, which are based upon a finite dataset. This paper deals specifically with a popular kernel density based estimator, for which the distribution is determined empirically using Monte Carlo simulation. The application of the critical values of MI derived from this distribution to a test for independence is demonstrated within the context of a benchmark input variable selection problem.http://www.okstate.edu/elec-engr/faculty/yen/wcci/WCCI-Web_ProgramList_F.htm

Expected exponential loss for gaze-based video and volume ground truth annotation

Many recent machine learning approaches used in medical imaging are highly reliant on large amounts of image and ground truth data. In the context of object segmentation, pixel-wise annotations are extremely expensive to collect, especially in video and 3D volumes. To reduce this annotation burden, we propose a novel framework to allow annotators to simply observe the object to segment and record where they have looked at with a \$200 eye gaze tracker. Our method then estimates pixel-wise probabilities for the presence of the object throughout the sequence from which we train a classifier in semi-supervised setting using a novel Expected Exponential loss function. We show that our framework provides superior performances on a wide range of medical image settings compared to existing strategies and that our method can be combined with current crowd-sourcing paradigms as well.Comment: 9 pages, 5 figues, MICCAI 2017 - LABELS Worksho