Molecular Energy Transfer and Spectroscopy

Contains research objectives and reports on one research project.National Science Foundation (Grant GP-6504)Petroleum Research Fund (Grant 2523-A5)Sloan Foundation for Basic Research (M.I.T. Grant

Exploiting Machine Learning to Subvert Your Spam Filter

Using statistical machine learning for making security decisions introduces new vulnerabilities in large scale systems. This paper shows how an adversary can exploit statistical machine learning, as used in the SpamBayes spam filter, to render it useless—even if the adversary’s access is limited to only 1 % of the training messages. We further demonstrate a new class of focused attacks that successfully prevent victims from receiving specific email messages. Finally, we introduce two new types of defenses against these attacks.

A Silurian ophiuroid with soft tissue preservation

Most Palaeozoic brittle stars lack the fused arm ossicles (vertebrae) that facilitate the remarkable mode of walking that characterizes living forms. Here we describe a stem ophiuroid from the Herefordshire Lagerstätte (Silurian, Wenlock Series) which is remarkable in preserving the body cavity uncompacted and long tube feet. We assign the specimen to the order Oegophiurida. The morphology of the arms and attitude of the specimen suggest that locomotion may have been achieved by arm propulsion combined with podial walking. This ophiuroid increases the diversity of echinoderm higher taxa with preserved soft parts represented in the Herefordshire Lagerstätte

Online Meta-learning by Parallel Algorithm Competition

The efficiency of reinforcement learning algorithms depends critically on a few meta-parameters that modulates the learning updates and the trade-off between exploration and exploitation. The adaptation of the meta-parameters is an open question in reinforcement learning, which arguably has become more of an issue recently with the success of deep reinforcement learning in high-dimensional state spaces. The long learning times in domains such as Atari 2600 video games makes it not feasible to perform comprehensive searches of appropriate meta-parameter values. We propose the Online Meta-learning by Parallel Algorithm Competition (OMPAC) method. In the OMPAC method, several instances of a reinforcement learning algorithm are run in parallel with small differences in the initial values of the meta-parameters. After a fixed number of episodes, the instances are selected based on their performance in the task at hand. Before continuing the learning, Gaussian noise is added to the meta-parameters with a predefined probability. We validate the OMPAC method by improving the state-of-the-art results in stochastic SZ-Tetris and in standard Tetris with a smaller, 10$\times$10, board, by 31% and 84%, respectively, and by improving the results for deep Sarsa($\lambda$) agents in three Atari 2600 games by 62% or more. The experiments also show the ability of the OMPAC method to adapt the meta-parameters according to the learning progress in different tasks.Comment: 15 pages, 10 figures. arXiv admin note: text overlap with arXiv:1702.0311

Temperature dependence of surface reconstructions of Au on Pd(110)

Surface reconstructions of Au film on Pd(110) substrate are studied using a local Einstein approximation to quasiharmonic theory with the Sutton-Chen interatomic potential. Temperature dependent surface free energies for different coverages and surface structures are calculated. Experimentally observed transformations from $(1\times1)$ to $(1 \times 2)$ and $(1 \times 3)$ structures can be explained in the framework of this model. Also conditions for Stranski-Krastanov growth mode are found to comply with experiments. The domain of validity of the model neglecting mixing entropy is analyzed.Comment: 7 pages, REVTeX two-column format, 3 postscript figures available on request from [email protected] To appear in Phys. Rev. Letter

From Random Matrices to Stochastic Operators

We propose that classical random matrix models are properly viewed as finite difference schemes for stochastic differential operators. Three particular stochastic operators commonly arise, each associated with a familiar class of local eigenvalue behavior. The stochastic Airy operator displays soft edge behavior, associated with the Airy kernel. The stochastic Bessel operator displays hard edge behavior, associated with the Bessel kernel. The article concludes with suggestions for a stochastic sine operator, which would display bulk behavior, associated with the sine kernel.Comment: 41 pages, 5 figures. Submitted to Journal of Statistical Physics. Changes in this revision: recomputed Monte Carlo simulations, added reference [19], fit into margins, performed minor editin

Non-Gaussian Radio-Wave Scattering in the Interstellar Medium

It was recently suggested by Boldyrev & Gwinn that the characteristics of radio scintillations from distant pulsars are best understood if the interstellar electron-density fluctuations that cause the time broadening of the radio pulses obey non-Gaussian statistics. In this picture the density fluctuations are inferred to be strong on very small scales ($\sim 10^8-10^{10} {cm}$). We argue that such density structures could correspond to the ionized boundaries of molecular regions (clouds) and demonstrate that the power-law distribution of scattering angles that is required to match the observations arises naturally from the expected intersections of our line of sight with randomly distributed, thin, approximately spherical ionized shells of this type. We show that the observed change in the time-broadening behavior for pulsar dispersion measures $\lesssim 30 {\rm pc} {\rm cm}^{-3}$ is consistent with the expected effect of the general ISM turbulence, which should dominate the scattering for nearby pulsars. We also point out that if the clouds are ionized by nearby stars, then their boundaries may become turbulent on account of an ionization front instability. This turbulence could be an alternative cause of the inferred density structures. An additional effect that might contribute to the strength of the small-scale fluctuations in this case is the expected flattening of the turbulent density spectrum when the eddy sizes approach the proton gyroscale.Comment: 15 pages, 3 figures, accepted to Ap

Masers and Outflows in the W3(OH)/W3(H2O) region

Methanol masers and molecular shock tracers were observed in the W3(OH)/W3(H$_2$O) region with the BIMA array and the Onsala 20m radiotelescope. Characteristics of the outflows in the region are discussed. A model of the W3(OH) methanol maser formation region is constructed.Comment: 4 pages, 2 figures, numerous journal misprints are correcte

Impurity effects on the melting of Ni clusters

We demonstrate that the addition of a single carbon impurity leads to significant changes in the thermodynamic properties of Ni clusters consisting of more than a hundred atoms. The magnitude of the change induced is dependent upon the parameters of the Ni-C interaction. Hence, thermodynamic properties of Ni clusters can be effectively tuned by the addition of an impurity of a particular type. We also show that the presence of a carbon impurity considerably changes the mobility and diffusion of atoms in the Ni cluster at temperatures close to its melting point. The calculated diffusion coefficients of the carbon impurity in the Ni cluster can be used for a reliable estimate of the growth rate of carbon nanotubes.Comment: 27 pages, 13 figure

Etching effects during the chemical vapor deposition of (100) diamond

Current theories of CVD growth on (100) diamond are unable to account for the numerous experimental observations of slow-growing, locally smooth (100)(2×1)(100)(2×1) films. In this paper we use quantum mechanical calculations of diamond surface thermochemistry and atomic-scale kinetic Monte Carlo simulations of deposition to investigate the efficacy of preferential etching as a mechanism that can help to reconcile this discrepancy. This etching mechanism allows for the removal of undercoordinated carbon atoms from the diamond surface. In the absence of etching, simulated growth on the (100)(2×1)(100)(2×1) surface is faster than growth on the (110) and (111) surfaces, and the (100) surface is atomically rough. When etching is included in the simulations, the (100) growth rates decrease to values near those observed experimentally, while the rates of growth on the other surfaces remain largely unaffected and similar to those observed experimentally. In addition, the etching mechanism promotes the growth of smooth (100) surface regions in agreement with numerous scanning probe studies. © 1999 American Institute of Physics.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/70606/2/JCPSA6-111-9-4291-1.pd