Control of Raman Lasing in the Nonimpulsive Regime

We explore coherent control of stimulated Raman scattering in the nonimpulsive regime. Optical pulse shaping of the coherent pump field leads to control over the stimulated Raman output. A model of the control mechanism is investigated.Comment: 4 pages, 5 figure

Extracting quantum dynamics from genetic learning algorithms through principal control analysis

Genetic learning algorithms are widely used to control ultrafast optical pulse shapes for photo-induced quantum control of atoms and molecules. An unresolved issue is how to use the solutions found by these algorithms to learn about the system's quantum dynamics. We propose a simple method based on covariance analysis of the control space, which can reveal the degrees of freedom in the effective control Hamiltonian. We have applied this technique to stimulated Raman scattering in liquid methanol. A simple model of two-mode stimulated Raman scattering is consistent with the results.Comment: 4 pages, 5 figures. Presented at coherent control Ringberg conference 200

Temperatures of Fragment Kinetic Energy Spectra

Multifragmentation reactions without large compression in the initial state (proton-induced reactions, reverse-kinematics, projectile fragmentation) are examined, and it is verified quantitatively that the high temperatures obtained from fragment kinetic energy spectra and lower temperatures obtained from observables such as level population or isotope ratios can be understood in a common framework.Comment: LaTeX, 7 pages, 2 figures available from autho

Comparison of Measured and Calculated Specific Resistances of Pd/Pt Interfaces

We compare specific resistances (AR equals area A times resistance R) of sputtered Pd/Pt interfaces measured in two different ways with no-free-parameter calculations. One way gives 2AR(Pd/Pt) of 0.29 (0.03) fohm-m(2) and the other 0.17 (0.13) fohm-m(2). From these we derive a best estimate of 2AR(Pd/Pt) of 0.28 (0.06) fohm-m(2), which overlaps with no-free-parameter calculations: 2AR(predicted) of 0.30 (0.04) fohm-m(2) for flat, perfect interfaces, or 0.33 (0.04) fohm-m(2) for interfaces composed of 2 monolayers of a 50percent-50percent PdPt alloy. These results support three prior examples of agreement between calculations and measurements for pairs of metals having the same crystal structure and the same lattice parameter to within 1 percent. We also estimate the spin-flipping probability at Pd/Pt interfaces as 0.13 (0.08).Comment: 3 pages, 3 figures, submitted for publication New version has corrected value of delta(Pd/Pt

Morphological analysis of the cm-wave continuum in the dark cloud LDN1622

The spectral energy distribution of the dark cloud LDN1622, as measured by Finkbeiner using WMAP data, drops above 30GHz and is suggestive of a Boltzmann cutoff in grain rotation frequencies, characteristic of spinning dust emission. LDN1622 is conspicuous in the 31 GHz image we obtained with the Cosmic Background Imager, which is the first cm-wave resolved image of a dark cloud. The 31GHz emission follows the emission traced by the four IRAS bands. The normalised cross-correlation of the 31 GHz image with the IRAS images is higher by 6.6sigma for the 12um and 25um bands than for the 60um and 100um bands: C(12+25) = 0.76+/-0.02 and C(60+100) = 0.64+/-0.01. The mid-IR -- cm-wave correlation in LDN 1622 is evidence for very small grain (VSG) or continuum emission at 26-36GHz from a hot molecular phase. In dark clouds and their photon-dominated regions (PDRs) the 12um and 25um emission is attributed to stochastic heating of the VSGs. The mid-IR and cm-wave dust emissions arise in a limb-brightened shell coincident with the PDR of LDN1622, where the incident UV radiation from the Ori OB1b association heats and charges the grains, as required for spinning dust.Comment: accepted for publication in ApJ - the complete article with uncompressed figures may be downloaded from http://www.das.uchile.cl/~simon/ftp/l1622.pd

Conformational Dependence of a Protein Kinase Phosphate Transfer Reaction

Atomic motions and energetics for a phosphate transfer reaction catalyzed by the cAMP-dependent protein kinase (PKA) are calculated by plane-wave density functional theory, starting from structures of proteins crystallized in both the reactant conformation (RC) and the transition-state conformation (TC). In the TC, we calculate that the reactants and products are nearly isoenergetic with a 0.2 eV barrier; while phosphate transfer is unfavorable by over 1.2 eV in the RC, with an even higher barrier. With the protein in the TC, the motions involved in reaction are small, with only P$_\gamma$ and the catalytic proton moving more than 0.5 \AA. Examination of the structures reveals that in the RC the active site cleft is not completely closed and there is insufficient space for the phosphorylated serine residue in the product state. Together, these observations imply that the phosphate transfer reaction occurs rapidly and reversibly in a particular conformation of the protein, and that the reaction can be gated by changes of a few tenths of an \AA in the catalytic site.Comment: revtex4, 7 pages, 4 figures, to be submitted to Scienc

Comments on Supersymmetry Algebra and Contact Term in Matrix String Theory

Following hep-th/0309238 relating the matrix string theory to the light-cone superstring field theory, we write down two supercharges in the matrix string theory explicitly. After checking the supersymmetry algebra at the leading order, we proceed to discuss higher-order contact terms.Comment: 17 pages, no figures, v2: eq. (5.1) and related appendices corrected, v3: final version to appear in JHE

Early Detection of Alzheimer\u27s Disease with Blood Plasma Proteins Using Support Vector Machines

\ua9 2013 IEEE. The successful development of amyloid-based biomarkers and tests for Alzheimer\u27s disease (AD) represents an important milestone in AD diagnosis. However, two major limitations remain. Amyloid-based diagnostic biomarkers and tests provide limited information about the disease process and they are unable to identify individuals with the disease before significant amyloid-beta accumulation in the brain develops. The objective in this study is to develop a method to identify potential blood-based non-amyloid biomarkers for early AD detection. The use of blood is attractive because it is accessible and relatively inexpensive. Our method is mainly based on machine learning (ML) techniques (support vector machines in particular) because of their ability to create multivariable models by learning patterns from complex data. Using novel feature selection and evaluation modalities, we identified 5 novel panels of non-amyloid proteins with the potential to serve as biomarkers of early AD. In particular, we found that the combination of A2M, ApoE, BNP, Eot3, RAGE and SGOT may be a key biomarker profile of early disease. Disease detection models based on the identified panels achieved sensitivity (SN) > 80%, specificity (SP) > 70%, and area under receiver operating curve (AUC) of at least 0.80 at prodromal stage (with higher performance at later stages) of the disease. Existing ML models performed poorly in comparison at this stage of the disease, suggesting that the underlying protein panels may not be suitable for early disease detection. Our results demonstrate the feasibility of early detection of AD using non-amyloid based biomarkers