231 research outputs found

    Reduced calibration uncertainties for the global network of gravitational-wave observatories and the impact on sky localization of burst-like sources

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    The Advanced Laser Interferometer Gravitational-wave Observatory (LIGO) is a science facility in the United States devoted to the observation of gravitational waves (GWs). It comprises two kilometer-scale laser interferometers. It is a part of a global ground-based GW detector network that also includes Virgo in Italy and KAGRA in Japan. Calibration of the LIGO detectors is achieved using displacement fiducials generated by radiation pressure based systems called Photon Calibrators (Pcals). The first part of this research described here details the developments implemented during the third LIGO-Virgo-KAGRA (LVK) observation run, O3, in the propagation of laser power calibration via transfer standards to on-line power sensors. These developments have enabled generation of length fiducials with improved accuracy of 0.41%. This estimated uncertainty is almost a factor of two smaller than the lowest values previously reported. This result enabled reducing the uncertainty in overall calibration of the LIGO interferometers during the O3 observing run to the 2% level. GW source parameter estimation and localization rely on accurately calibrated strain data. The second part of the research reported here investigates the impact of overall, systematic detector calibration errors on the sky localization of burst-like GW sources, specifically core collapse supernovae (CCSN). This analysis is performed using simulated waveforms from different CCSN models and one of the standard LVK pipelines used to search for burst-like GW signals. Overall calibration errors as large as ± 10% are imposed on a single detector in the LIGO-Virgo network. Preliminary results indicate that this causes average changes in the area of 90% sky localization confidence regions as large as 18%. Associated average errors in estimated probabilities for these regions are as large as 5%. Furthermore, for sources located in some regions of the sky, source localization errors are as large as 90%, indicating that counterparts to GW signals would not be found within the 90% confidence regions in follow-up observations by electromagnetic observatories”--Abstract, page iii

    Toward Calibration of the Global Network of Gravitational Wave Detectors with Sub-Percent Absolute and Relative Accuracy

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    The detection of gravitational-wave signals by the LIGO and Virgo observatories during the past few years has ushered us into the era of gravitational-wave astronomy, shifting our focus from detection to source parameter estimation. This has imposed stringent requirements on calibration in order to maximize the astrophysical information extracted from these detected signals. Current detectors rely on photon radiation pressure from auxiliary lasers to achieve required calibration accuracy. These photon calibrators have made significant improvements over the last few years, realizing fiducials displacements with sub-percent accuracy. This achieved accuracy is directly dependent on the laser power calibration. For the next observing campaign, scheduled to begin at the end of 2022, a new scheme is being implemented to achieve improved laser power calibration accuracy for all of the GW detectors in the global network. It is expected to significantly improve absolute and relative calibration accuracy for the entire network

    LPWAN Performance Enhancement for IoT in the Smart Grid

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    With the proliferation of IoT devices across the globe, the adoption of IoT related technologies has been increasing rapidly. Newer technologies which fall in the category of Low Power Wide Area Network (LPWAN) have increased this adoption even further. A lot of research is being done in LPWAN licensed band as well as unlicensed band technologies to make them more efficient, such as in terms of power consumption and latency. In this thesis the author has focused on cellular IoT technologies (licensed spectrum LPWAN technologies), to improve the end-to-end behavior. The focus is to see and improve the effect of the device on the network behavior. We have done tests on different networks and went through the 3GPP Specification Release 14 to find possible areas of improvement. Keeping this in mind we have designed a solution to increase the number of pageable devices that can be maintained by the network compared to its original capacity (when not using our solution). This solution can be used to optimize as per the use case, whether to provide lower latency or save energy consumption of the device. To verify that the solution can be used in real life, we have tested it with Stedin critical application device in their substation.Electrical Engineering | Embedded System

    Understanding Interactions in Social Networks and Committees

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    While much of the literature on cross section dependence has fo?cused mainly on estimation of the regression coefficients in the under?lying model, estimation and inferences on the magnitude and strength of spill-overs and interactions has been largely ignored. At the same time, such inferences are important in many applications, not least because they have structural interpretations and provide useful inter?pretation and structural explanation for the strength of any interac?tions. In this paper we propose GMM methods designed to uncover underlying (hidden) interactions in social networks and committees. Special attention is paid to the interval censored regression model. Our methods are applied to a study of committee decision making within the Bank of England¡¯s monetary policy committee.Committee Decision Making, Social Networks, Cross Section and Spatial Interaction, Generalised Method of Moments, Censored Regression Model, Expectation-Maximisation Algorithm, Monetary Policy, Interest Rates.

    COVID-19 and persistence in the stock market: a study on a leading emerging market

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    Data availability: The data that support the findings of this study are available from the corresponding author upon reasonable request.In this study, we examine how sectors of the National Stock Exchange from India respond to the uncertainties introduced by the COVID-19 pandemic. By examining the synchronization between the sector-specific and overall market index (NIFTY 50) reaction to COVID-19, we contribute to the inconclusive ongoing academic literature regarding the impact of COVID-19 on the stock market, especially in the context of persistence in an emerging market. To analyze the persistence of sectoral indices, we apply multifractal detrended fluctuation analysis (MFDFA). We use the generalized Hurst exponent and singularity spectrum as indicators for persistence and spectral width as a measure of volatility. Our analysis shows that the sample sectoral indices are persistent before and after the announcement of COVID-19; however, volatility in some sectors reduces post-announcement of COVID-19. The findings will enrich the academic literature on the relationship between sector-specific and overall market indexes. In practice, the paper will guide investors to organize their portfolios, especially during future economic uncertainty

    Architectural Support for Address Translation on GPUs

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    The proliferation of heterogeneous compute platforms, of which CPU/GPU is a prevalent example, necessitates a manageable programming model to ensure widespread adoption. A key component of this is a shared unified address space between the heterogeneous units to obtain the programmability benefits of virtual memory. Indeed, processor vendors have already begun embracing heterogeneous systems with unified address spaces (e.g., Intel’s Haswell, AMD’s Berlin processor, and ARM’s Mali and Cortex cores). We are the first to explore GPU Translation Lookaside Buffers (TLBs) and page table walkers for address translation in the context of shared virtual memory for heterogeneous systems. To exploit the programmability benefits of shared virtual memory, it is natural to consider mirroring CPUs and placing TLBs prior (or parallel) to cache accesses, making caches physically addressed. We show the performance challenges of such an approach and propose modest hardware augmentations to recover much of this lost performance.We then consider the impact of this approach on the design of general purpose GPU performance improvement schemes. We look at: (1) warp scheduling to increase cache hit rates; and (2) dynamic warp formation to mitigate control flow divergence overheads. We show that introducing cache-parallel address translation does pose challenges, but that modest optimizations can buy back much of this lost performance. Overall, this paper explores address translation mechanisms on GPUs. While cache-parallel address translation does introduce non-trivial performance overheads, modestly TLB-aware designs can move overheads into a range deemed acceptable in the CPU world (5-15% of runtime). We presume this initial design leaves room for improvement but hope the larger result, that a little TLB-awareness goes a long way in GPUs, spurs future work in this fruitful area.Technical report DCS-TR-70

    Author Experiences with the IS Journal Review Process

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    Research publication in peer-reviewed journals is an important avenue for knowledge dissemination. However, information on journal review process metrics are often not available to prospective authors, which may preclude effective targeting of their research work to appropriate outlets. We study these metrics for information systems (IS) researchers through a survey of actual author experiences of the IS journal review process. Our results provide a knowledge base of the length and quality of the review process in various journals; responsiveness of the journal office and publication delay; and correlations of metrics with published studies of journal rankings. The data should enable authors to make effective submission decisions, as well as help to benchmark journal review processes among competing journals

    Quantifying and Improving I/O Predictability in Virtualized Systems

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    Virtualization enables the consolidation of virtual machines (VMs) to increase the utilization of physical servers in Infrastructure-as-a-Service (IaaS) cloud providers. Unfortunately, our quantification of storage I/O performance across a range of workloads, virtual machine monitor (VMM) architectures, approaches to storage virtualization, and storage devices shows widespread performance unpredictability in the face of consolidation. Surprisingly, the use of solid-state drives (SSDs) can exacerbate the problem. Since many users may desire consistent performance, we argue that IaaS cloud providers should provide a class of predictable-performance service in addition to their existing (predictability-oblivious) services. Thus, we propose and evaluate VirtualFence, a storage system that provides predictable performance for this new class of service. VirtualFence uses three main techniques: (1) non-work-conserving time-division I/O scheduling, (2) a small SSD cache in front of a much larger hard disk drive (HDD), and (3) space-partitioning of both the SSD cache and the HDD. Our evaluation of a prototype VirtualFence implemented in the Xen VMM shows that VirtualFence improves predictability significantly. More fundamentally, our evaluation illustrates the tradeoff between predictability and performance. We conclude that current VMMs are far from providing predictability. Systems like VirtualFence can remedy this problem, while allowing the cloud provider to select an appropriate compromise between performance and predictability.Technical report DCS-TR-69

    Education, Essentialism and the Epistemic Vices of Intolerance

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    This essay focuses on one of the core problems that pervade contemporary debates about democratic education in general and education for tolerance in particular: What is the specific relation between epistemic virtues and vices and political toleration as a democratic virtue and as an aim of education? In this chapter, the author argues to show that political intolerance usually is accompanied by (and arguably also at least partly caused by) epistemic vices, which can and should be counteracted by education for tolerance
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