Mass function and particle creation in Schwarzschild-de Sitter spacetime

We construct a mass or energy function for the non-Nariai class Schwarzschild-de Sitter black hole spacetime in the region between the black hole and the cosmological event horizons. The mass function is local, positive definite, continuous and increases monotonically with the radial distance from the black hole event horizon. We derive the Smarr formula using this mass function, and demonstrate that the mass function reproduces the two-temperature Schwarzschild-de Sitter black hole thermodynamics, along with a term corresponding to the negative pressure due to positive cosmological constant. We further give a field theoretic derivation of the particle creation by both the horizons and discuss its connection with the mass function.Comment: v3, 16pp; added references and discussions, typo corrected; accepted in Eur. Phys. J.

Cosmic strings with positive Λ\Lambda

We discuss cosmic Nielsen-Olesen strings in space-times endowed with a positive cosmological constant. For the cylindrically symmetric, static free cosmic string, we discuss the contribution of the cosmological constant to the angle deficit, and to the motion of the null/timelike geodesics. For a non-gravitating cosmic string in a Schwarzschild-de Sitter space-time, we discuss how a thin string can pierce the two horizons. We also present a metric which describes the exterior of a self gravitating thin string present in the Schwarzschild-de Sitter space-time.Comment: 3 pages; based on a talk given in the 12th Marcel Grossmann Meeting, Paris by S. Bhattacharya; MG12 proceedings styl

No hair theorems for positive \Lambda

We extend all known black hole no-hair theorems to space-times endowed with a positive cosmological constant $\Lambda.$ Specifically, we prove that static spherical black holes with $\Lambda>0$ cannot support scalar fields in convex potentials and Proca-massive vector fields in the region between black hole and cosmic horizons. We also demonstrate the existence of at least one type of quantum hair, and of exactly one charged solution for the Abelian Higgs model. Our method of proof can be applied to investigate other types of quantum or topological hair on black holes in the presence of a positive $\Lambda.$Comment: 8pp. v2: added references; comment regarding phantom field, comment that spherical symmetry is not crucial for most of the proof; version published in PRL(name changed in journal

Lightweight Modules for Efficient Deep Learning based Image Restoration

Low level image restoration is an integral component of modern artificial intelligence (AI) driven camera pipelines. Most of these frameworks are based on deep neural networks which present a massive computational overhead on resource constrained platform like a mobile phone. In this paper, we propose several lightweight low-level modules which can be used to create a computationally low cost variant of a given baseline model. Recent works for efficient neural networks design have mainly focused on classification. However, low-level image processing falls under the image-to-image' translation genre which requires some additional computational modules not present in classification. This paper seeks to bridge this gap by designing generic efficient modules which can replace essential components used in contemporary deep learning based image restoration networks. We also present and analyse our results highlighting the drawbacks of applying depthwise separable convolutional kernel (a popular method for efficient classification network) for sub-pixel convolution based upsampling (a popular upsampling strategy for low-level vision applications). This shows that concepts from domain of classification cannot always be seamlessly integrated into image-to-image translation tasks. We extensively validate our findings on three popular tasks of image inpainting, denoising and super-resolution. Our results show that proposed networks consistently output visually similar reconstructions compared to full capacity baselines with significant reduction of parameters, memory footprint and execution speeds on contemporary mobile devices.Comment: Accepted at: IEEE Transactions on Circuits and Systems for Video Technology (Early Access Print) | |Codes Available at: https://github.com/avisekiit/TCSVT-LightWeight-CNNs | Supplementary Document at: https://drive.google.com/file/d/1BQhkh33Sen-d0qOrjq5h8ahw2VCUIVLg/view?usp=sharin

Optimum VM Placement for NFV Infrastructures

This paper shows how to use a Linux-based operating system as a real-time processing platform for low-latency and predictable packet processing in cloudified radio-access network (cRAN) scenarios. This use-case exhibits challenging end-to-end processing latencies, in the order of milliseconds for the most time-critical layers of the stack. A significant portion of the variability and instability in the observed end-to-end performance in this domain is due to the power saving capabilities of modern CPUs, often in contrast with the low-latency and high-performance requirements of this type of applications. We discuss how to properly configure the system for this scenario, and evaluate the proposed configuration on a synthetic application designed to mimic the behavior and computational requirements of typical software components implementing baseband processing in production environments

Effect of a positive cosmological constant on cosmic strings

We study cosmic Nielsen-Olesen strings in space-times with a positive cosmological constant. For the free cosmic string in a cylindrically symmetric space-time, we calculate the contribution of the cosmological constant to the angle deficit, and to the bending of null geodesics. For a cosmic string in a Schwarzschild-de Sitter space-time, we use Kruskal patches around the inner and outer horizons to show that a thin string can pierce them.Comment: v3:15pp. References and some explanations added; version accepted for publication in Phys. Rev.

Near Real-Time Anomaly Detection in NFV Infrastructures

This paper presents a scalable cloud-based archi-tecture for near real-time anomaly detection in the Vodafone NFV infrastructure, spanning across multiple data centers in 11 European countries. Our solution aims at processing in real-time system-level data coming from the monitoring subsystem of the infrastructure, raising alerts to operators as soon as the incoming data presents anomalous patterns. A number of different anomaly detection techniques have been implemented for the proposed architecture, and results from their comparative evaluation are reported, based on real monitoring data coming from one of the monitored data centers, where a number of interesting anomalies have been manually identified. Part of this labelled data-set is also released under an open data license, for possible reuse by other researchers