SPITZER OBSERVATIONS OF A1763. II. CONSTRAINING THE NATURE OF ACTIVITY IN THE CLUSTER-FEEDING FILAMENT WITH VLA AND XMM-NEWTON DATA

The A1763 superstructure at z = 0.23 contains the first galaxy filament to be directly detected using mid-infrared observations. Our previous work has shown that the frequency of starbursting galaxies, as characterized by 24 mu m emission is much higher within the filament than at either the center of the rich galaxy cluster, or the field surrounding the system. New Very Large Array and XMM-Newton data are presented here. We use the radio and X-ray data to examine the fraction and location of active galaxies, both active galactic nuclei (AGNs) and starbursts (SBs). The radio far-infrared correlation, X-ray point source location, IRAC colors, and quasar positions are all used to gain an understanding of the presence of dominant AGNs. We find very few MIPS-selected galaxies that are clearly dominated by AGN activity. Most radio-selected members within the filament are SBs. Within the supercluster, three of eight spectroscopic members detected both in the radio and in the mid-infrared are radio-bright AGNs. They are found at or near the core of A1763. The five SBs are located further along the filament. We calculate the physical properties of the known wide angle tail (WAT) source which is the brightest cluster galaxy of A1763. A second double lobe source is found along the filament well outside of the virial radius of either cluster. The velocity offset of the WAT from the X-ray centroid and the bend of the WAT in the intracluster medium are both consistent with ram pressure stripping, indicative of streaming motions along the direction of the filament. We consider this as further evidence of the cluster-feeding nature of the galaxy filament.

Subspace wavepacket evolution with Newton polynomials

Time-dependent wavepacket evolution techniques demand the action of the propagator, exp(-iHt/(h)over-bar), on a suitable initial wavepacket. When a complex absorbing potential is added to the Hamiltonian for combating unwanted reflection effects, polynomial expansions of the propagator are selected on their ability to cope with non-Hermiticity. An efficient subspace implementation of the Newton polynomial expansion scheme that requires fewer dense matrix-vector multiplications than its grid-based counterpart has been devised. Performance improvements are illustrated with some benchmark one and two-dimensional examples. (C) 2001 Elsevier Science B.V. All rights reserved.

World catalog of the genera of Pselaphidae (Coleoptera) / Alfred F. Newton, Jr., Donald S. Chandler.

n.s. no.53(1989)

Contributions to the paleontology of the upper cretaceous series / by William Newton Logan, A.M. ; Oliver Cummings Farrington, Ph.D. Curator, Dept. of Geology.

v.1:no.6(1899)

Current classification and family-group names in Staphyliniformia (Coleoptera) / Alfred F. Newton, Jr., Margaret K. Thayer.

n.s. no.67(1992)

S-system parameter estimation for noisy metabolic profiles using newton-flow analysis.

Biochemical systems are commonly modelled by systems of ordinary differential equations (ODEs). A particular class of such models called S-systems have recently gained popularity in biochemical system modelling. The parameters of an S-system are usually estimated from time-course profiles. However, finding these estimates is a difficult computational problem. Moreover, although several methods have been recently proposed to solve this problem for ideal profiles, relatively little progress has been reported for noisy profiles. We describe a special feature of a Newton-flow optimisation problem associated with S-system parameter estimation. This enables us to significantly reduce the search space, and also lends itself to parameter estimation for noisy data. We illustrate the applicability of our method by applying it to noisy time-course data synthetically produced from previously published 4- and 30-dimensional S-systems. In addition, we propose an extension of our method that allows the detection of network topologies for small S-systems. We introduce a new method for estimating S-system parameters from time-course profiles. We show that the performance of this method compares favorably with competing methods for ideal profiles, and that it also allows the determination of parameters for noisy profiles.

Department of Commerce, Newton Correctional Facility, FY 2007

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