Magnetomechanical damping by polycrystalline TbDy

Vibration damping in polycrystalline TbDy alloys was studied at cryogenic temperatures. Mechanical hysteretic losses were measured at various strains, frequencies, and loading configurations at 77 K. Some textured TbDy materials demonstrated 22.6% energy dissipation in mechanical measurements at low frequency (0.01 Hz) and a mean logarithmic decrement of 0.23 at a higher frequency (25 kHz). Ultrasonic velocities of longitudinal and shear elastic waves were measured on single and polycrystalline TbDy; little variation in ultrasonic velocities was found even for samples with large variation in crystallographic texture and magnetomechanical properties

Magnetomechanical effects in textured polycrystalline Tb76Dy24

Uniaxial stress-strain measurements were performed on polycrystalline Tb76Dy24 alloys which exhibit "giant magnetostriction" at cryogenic temperatures. The Young's moduli were reduced by up to a factor of five at 77 K, in comparison to their values at 300 K. We attribute this reduction to a mechanical compliance from domain rotation. Large mechanical hysteresis is also found in nominally elastic stress-strain curves measured below the Curie temperature. Hysteretic curves from 0 to 25 MPa demonstrate up to 19% dissipation of the applied mechanical energy. The anisotropy of thermal expansion was also measured and used as a parameter for the degree of crystallographic texture. This anisotropy was correlated to bulk magnetostriction and to mechanical hysteresis

The Montage Image Mosaic Service: Custom Image Mosaics On-Demand

The Montage software suite has proven extremely useful as a general engine for reprojecting, background matching, and mosaicking astronomical image data from a wide variety of sources. The processing algorithms support all common World Coordinate System (WCS) projections and have been shown to be both astrometrically accurate and flux conserving. The background ‘matching’ algorithm does not remove background flux but rather finds the best compromise background based on all the input and matches the individual images to that. The Infrared Science Archive (IRSA), part of the Infrared Processing and Analysis Center (IPAC) at Caltech, has now wrapped the Montage software as a CGI service and provided a compute and request management infrastructure capable of producing approximately 2 TBytes / day of image mosaic output (e.g. from 2MASS and SDSS data). Besides the basic Montage engine, this service makes use of a 16-node LINUX cluster (dual processor, dual core) and the ROME request management software developed by the National Virtual Observatory (NVO). ROME uses EJB/database technology to manage user requests, queue processing and load balance between users, and managing job monitoring and user notification. The Montage service will be extended to process userdefined data collections, including private data uploads

A Cost-Benefit Study of Doing Astrophysics On The Cloud: Production of Image Mosaics

Utility grids such as the Amazon EC2 and Amazon S3 clouds offer computational and storage resources that can be used on-demand for a fee by compute- and data-intensive applications. The cost of running an application on such a cloud depends on the compute, storage and communication resources it will provision and consume. Different execution plans of the same application may result in significantly different costs. We studied via simulation the cost performance trade-offs of different execution and resource provisioning plans by creating, under the Amazon cloud fee structure, mosaics with the Montage image mosaic engine, a widely used data- and compute-intensive application. Specifically, we studied the cost of building mosaics of 2MASS data that have sizes of 1, 2 and 4 square degrees, and a 2MASS all-sky mosaic. These are examples of mosaics commonly generated by astronomers. We also study these trade-offs in the context of the storage and communication fees of Amazon S3 when used for long-term application data archiving. Our results show that by provisioning the right amount of storage and compute resources cost can be significantly reduced with no significant impact on application performance

Magnetostriction of single crystal and polycrystalline Tb0.60Dy0.40 at cryogenic temperatures

At cryogenic temperatures, single crystals of TbDy alloys exhibit giant magnetostrictions of nearly 9000 ppm, making these materials promising for engineering service in cryogenic actuators, valves, and positioners. The preparation of single crystals is difficult and costly. Preliminary results on the magnetostriction of textured polycrystalline materials are presented here. For instance, polycrystalline Tb0.60Dy0.40, plane-rolled (one direction of applied stress) to induce crystallographic texture, has shown magnetostrictions at 77 K of 3000 ppm for an applied field of 4.5 kOe and an applied load of 23 MPa, or 48% that of a single crystal under similar conditions. Comparisons are presented between the magnetostrictive response of plane- and form-rolled (two orthogonal directions of applied stress) polycrystalline Tb0.60Dy0.40 at 10 and 77 K. It is reported that at 10 K plane-rolled Tb0.60Dy0.40 exhibits 1600 ppm magnetostriction at an applied field of 4.4 kOe with a minimal applied load of 0.28 MPa. An observed restoration of the initial unstrained state may be a useful feature of polycrystalline materials for engineering service. Finally it is reported that thermal expansion measurements provide a measure of crystallographic texture for comparison with the magnetostriction

Adaptive Regret Minimization in Bounded-Memory Games

Online learning algorithms that minimize regret provide strong guarantees in situations that involve repeatedly making decisions in an uncertain environment, e.g. a driver deciding what route to drive to work every day. While regret minimization has been extensively studied in repeated games, we study regret minimization for a richer class of games called bounded memory games. In each round of a two-player bounded memory-m game, both players simultaneously play an action, observe an outcome and receive a reward. The reward may depend on the last m outcomes as well as the actions of the players in the current round. The standard notion of regret for repeated games is no longer suitable because actions and rewards can depend on the history of play. To account for this generality, we introduce the notion of k-adaptive regret, which compares the reward obtained by playing actions prescribed by the algorithm against a hypothetical k-adaptive adversary with the reward obtained by the best expert in hindsight against the same adversary. Roughly, a hypothetical k-adaptive adversary adapts her strategy to the defender's actions exactly as the real adversary would within each window of k rounds. Our definition is parametrized by a set of experts, which can include both fixed and adaptive defender strategies. We investigate the inherent complexity of and design algorithms for adaptive regret minimization in bounded memory games of perfect and imperfect information. We prove a hardness result showing that, with imperfect information, any k-adaptive regret minimizing algorithm (with fixed strategies as experts) must be inefficient unless NP=RP even when playing against an oblivious adversary. In contrast, for bounded memory games of perfect and imperfect information we present approximate 0-adaptive regret minimization algorithms against an oblivious adversary running in time n^{O(1)}.Comment: Full Version. GameSec 2013 (Invited Paper

How good are your fits? Unbinned multivariate goodness-of-fit tests in high energy physics

Multivariate analyses play an important role in high energy physics. Such analyses often involve performing an unbinned maximum likelihood fit of a probability density function (p.d.f.) to the data. This paper explores a variety of unbinned methods for determining the goodness of fit of the p.d.f. to the data. The application and performance of each method is discussed in the context of a real-life high energy physics analysis (a Dalitz-plot analysis). Several of the methods presented in this paper can also be used for the non-parametric determination of whether two samples originate from the same parent p.d.f. This can be used, e.g., to determine the quality of a detector Monte Carlo simulation without the need for a parametric expression of the efficiency.Comment: 32 pages, 12 figure

Learning from FITS: Limitations in use in modern astronomical research

The Flexible Image Transport System (FITS) standard has been a great boon to astronomy, allowing observatories, scientists and the public to exchange astronomical information easily. The FITS standard, however, is showing its age. Developed in the late 1970s, the FITS authors made a number of implementation choices that, while common at the time, are now seen to limit its utility with modern data. The authors of the FITS standard could not anticipate the challenges which we are facing today in astronomical computing. Difficulties we now face include, but are not limited to, addressing the need to handle an expanded range of specialized data product types (data models), being more conducive to the networked exchange and storage of data, handling very large datasets, and capturing significantly more complex metadata and data relationships. There are members of the community today who find some or all of these limitations unworkable, and have decided to move ahead with storing data in other formats. If this fragmentation continues, we risk abandoning the advantages of broad interoperability, and ready archivability, that the FITS format provides for astronomy. In this paper we detail some selected important problems which exist within the FITS standard today. These problems may provide insight into deeper underlying issues which reside in the format and we provide a discussion of some lessons learned. It is not our intention here to prescribe specific remedies to these issues; rather, it is to call attention of the FITS and greater astronomical computing communities to these problems in the hope that it will spur action to address them

The Next Generation of the Montage Image Mosaic Toolkit

The scientific computing landscape has evolved dramatically in the past few years, with new schemes for organizing and storing data that reflect the growth in size and complexity of astronomical data sets. In response to this changing landscape, we are, over the next two years, deploying the next generation of the Montage toolkit ([ascl:1010.036]). The first release (October 2015) supports multi-dimensional data sets ("data cubes"), and insertion of XMP/AVM tags that allows images to "drop-in" to the WWT. The same release offers a beta-version of web-based interactive visualization of images; this includes wrappers for visualization in Python. Subsequent releases will support HEALPix (now standard in cosmic background experiments); incorporation of Montage into package managers (which enable automated management of software builds), and support for a library that will enable Montage to be called directly from Python. This next generation toolkit will inherit the architectural benefits of the current engine - component based tools, ANSI-C portability across Unix platforms and scalability for distributed processing. With the expanded functionality under development, Montage can be viewed not simply as a mosaic engine, but as a scalable, portable toolkit for managing, organizing and processing images