Starbursts triggered by cloud compression in interacting galaxies

We propose a physical mechanism for the triggering of starbursts in interacting spiral galaxies by shock compression of the pre-existing disk giant molecular clouds (GMCs). We show that as a disk GMC tumbles into the central region of a galaxy following a galactic tidal encounter, it undergoes a radiative shock compression by the pre-existing high pressure of the central molecular intercloud medium. The shocked outer shell of a GMC becomes gravitationally unstable, which results in a burst of star formation in the initially stable GMC. In the case of colliding galaxies with physical overlap such as Arp 244, the cloud compression is shown to occur due to the hot, high-pressure remnant gas resulting from the collisions of atomic hydrogen gas clouds from the two galaxies. The resulting values of infrared luminosity agree with observations. The main mode of triggered star formation is via clusters of stars, thus we can naturally explain the formation of young, luminous star clusters observed in starburst galaxies.

Aerosol radiative forcing over land: effect of surface and cloud reflection

It is now clearly understood that atmospheric aerosols have a significant impact on climate due to their important role in modifying the incoming solar and outgoing infrared radiation. The question of whether aerosol cools (negative forcing) or warms (positive forcing) the planet depends on the relative dominance of absorbing aerosols. Recent investigations over the tropical Indian Ocean have shown that, irrespective of the comparatively small percentage contribution in optical depth (similar to11%), soot has an important role in the overall radiative forcing. However, when the amount of absorbing aerosols such as soot are significant, aerosol optical depth and chemical composition are not the only determinants of aerosol climate effects, but the altitude of the aerosol layer and the altitude and type of clouds are also important. In this paper, the aerosol forcing in the presence of clouds and the effect of different surface types (ocean, soil, vegetation, and different combinations of soil and vegetation) are examined based on model simulations, demonstrating that aerosol forcing changes sign from negative (cooling) to positive (warming) when reflection from below (either due to land or clouds) is high.

Laboratory simulations show diabatic heating drives cumulus-cloud evolution and entrainment

Clouds are the largest source of uncertainty in climate science, and remain a weak link in modeling tropical circulation. A major challenge is to establish connections between particulate microphysics and macroscale turbulent dynamics in cumulus clouds. Here we address the issue from the latter standpoint. First we show how to create bench-scale flows that reproduce a variety of cumulus-cloud forms (including two genera and three species), and track complete cloud life cycles-e.g., from a ``cauliflower'' congestus to a dissipating fractus. The flow model used is a transient plume with volumetric diabatic heating scaled dynamically to simulate latent-heat release from phase changes in clouds. Laser-based diagnostics of steady plumes reveal Riehl-Malkus type protected cores. They also show that, unlike the constancy implied by early self-similar plume models, the diabatic heating raises the Taylor entrainment coefficient just above cloud base, depressing it at higher levels. This behavior is consistent with cloud-dilution rates found in recent numerical simulations of steady deep convection, and with aircraft-based observations of homogeneous mixing in clouds. In-cloud diabatic heating thus emerges as the key driver in cloud development, and could well provide a major link between microphysics and cloud- scale dynamics.

Efficient Algorithms for Computing All Low s-t Edge Connectivities and Related Problems

Given an undirected unweighted graph G = (V, E) and an integer k ≥ 1, we consider the problem of computing the edge connectivities of all those (s, t) vertex pairs, whose edge connectivity is at most k. We present an algorithm with expected running time Õ(m + nk3) for this problem, where |V| = n and |E| = m. Our output is a weighted tree T whose nodes are the sets V1, V2,..., V l of a partition of V, with the property that the edge connectivity in G between any two vertices s ε Vi and t ε Vj, for i ≠ j, is equal to the weight of the lightest edge on the path between Vi and Vj in T. Also, two vertices s and t belong to the same Vi for any i if and only if they have an edge connectivity greater than k. Currently, the best algorithm for this problem needs to compute all-pairs min-cuts in an O(nk) edge graph; this takes Õ(m + n5/2kmin{k1/2, n1/6}) time. Our algorithm is much faster for small values of k; in fact, it is faster whenever k is o(n5/6). Our algorithm yields the useful corollary that in Õ(m + nc3) time, where c is the size of the global min-cut, we can compute the edge connectivities of all those pairs of vertices whose edge connectivity is at most αc for some constant α. We also present an Õ(m + n) Monte Carlo algorithm for the approximate version of this problem. This algorithm is applicable to weighted graphs as well. Our algorithm, with some modifications, also solves another problem called the minimum T-cut problem. Given T ⊆ V of even cardinality, we present an Õ(m + nk3) algorithm to compute a minimum cut that splits T into two odd cardinality components, where k is the size of this cut.

Editorial optical computing circuits, devices and systems

Information forms the basis of modern technology. To meet the ever-increasing demand for information, means have to be devised for a more efficient and better-equipped technology to intelligibly process data. Advances in photonics have made their impact on each of the four key applications in information processing, i.e., acquisition, transmission, storage and processing of information. The inherent advantages of ultrahigh bandwidth, high speed and low-loss transmission has already established fiber-optics as the backbone of communication technology. However, the optics to electronics inter-conversion at the transmitter and receiver ends severely limits both the speed and bit rate of lightwave communication systems. As the trend towards still faster and higher capacity systems continues, it has become increasingly necessary to perform more and more signal-processing operations in the optical domain itself, i.e., with all-optical components and devices that possess a high bandwidth and can perform parallel processing functions to eliminate the electronic bottleneck.

On the role of cloud adjustment time scale in simulating precipitation with Relaxed Arakawa-Schubert convection scheme

The precipitation by Relaxed Arakawa-Schubert cumulus parameterization in a General Circulation Model (GCM) is sensitive to the choice of relaxation parameter or specified cloud adjustment time scale. In the present study, we examine sensitivity of simulated precipitation to the choice of cloud adjustment time scale (tau(adj)) over different parts of the tropics using National Center for Environmental Prediction (NCEP) Seasonal Forecast Model (SFM) during June-September. The results show that a single specified value of tau(adj) performs best only over a particular region and different values are preferred over different parts of the world. To find a relation between tau(adj) and cloud depth (convective activity) we choose six regions over the tropics. Based on the observed relation between outgoing long-wave radiation and tau(adj), we propose a linear cloud-type dependent relaxation parameter to be used in the model. The simulations over most parts of the tropics show improved results due to this newly formulated cloud-type dependent relaxation parameter.

Fragment Finder 2.0: a computing server to identify structurally similar fragments

Fragment Finder 2.0 is a web-based interactive computing server which can be used to retrieve structurally similar protein fragments from 25 and 90% nonredundant data sets. The computing server identifies structurally similar fragments using the protein backbone C alpha angles. In addition, the identified fragments can be superimposed using either of the two structural superposition programs, STAMP and PROFIT, provided in the server. The freely available Java plug-in Jmol has been interfaced with the server for the visualization of the query and superposed fragments. The server is the updated version of a previously developed search engine and employs an in-house-developed fast pattern matching algorithm. This server can be accessed freely over the World Wide Web through the URL http://cluster.physics.iisc.ernet.in/ff/.

Carbon Nanotube based Composite Fibers for Strain Sensing, Signal Processing and Computing

Carbon nanotubes dispersed in polymer matrix have been aligned in the form of fibers and interconnects and cured electrically and by UV light. Conductivity and effective semiconductor tunneling against reverse to forward bias field have been designed to have differentiable current-voltage response of each of the fiber/channel. The current-voltage response is a function of the strain applied to the fibers along axial direction. Biaxial and shear strains are correlated by differentiating signals from the aligned fibers/channels. Using a small doping of magnetic nanoparticles in these composite fibers, magneto-resistance properties are realized which are strong enough to use the resulting magnetostriction as a state variable for signal processing and computing. Various basic analog signal processing tasks such as addition, convolution and filtering etc. can be performed. These preliminary study shows promising application of the concept in combined analog-digital computation in carbon nanotube based fibers. Various dynamic effects such as relaxation, electric field dependent nonlinearities and hysteresis on the output signals are studied using experimental data and analytical model.

Resource Usage Monitoring in Clouds

Monitoring of infrastructural resources in clouds plays a crucial role in providing application guarantees like performance, availability, and security. Monitoring is crucial from two perspectives - the cloud-user and the service provider. The cloud user’s interest is in doing an analysis to arrive at appropriate Service-level agreement (SLA) demands and the cloud provider’s interest is to assess if the demand can be met. To support this, a monitoring framework is necessary particularly since cloud hosts are subject to varying load conditions. To illustrate the importance of such a framework, we choose the example of performance being the Quality of Service (QoS) requirement and show how inappropriate provisioning of resources may lead to unexpected performance bottlenecks. We evaluate existing monitoring frameworks to bring out the motivation for building much more powerful monitoring frameworks. We then propose a distributed monitoring framework, which enables fine grained monitoring for applications and demonstrate with a prototype system implementation for typical use cases.