What Do CFTs Tell Us About Anti-de Sitter Spacetimes?

The AdS/CFT conjecture relates quantum gravity on Anti-de Sitter (AdS) space to a conformal field theory (CFT) defined on the spacetime boundary. We interpret the CFT in terms of natural analogues of the bulk S-matrix. Our first approach finds the bulk S-matrix as a limit of scattering from an AdS bubble immersed in a space admitting asymptotic states. Next, we show how the periodicity of geodesics obstructs a standard LSZ prescription for scattering within global AdS. To avoid this subtlety we partition global AdS into patches within which CFT correlators reconstruct transition amplitudes of AdS states. Finally, we use the AdS/CFT duality to propose a large N collective field theory that describes local, perturbative supergravity. Failure of locality in quantum gravity should be related to the difference between the collective 1/N expansion and genuine finite N dynamics.Comment: 33 pages, 7 figures, uses harvmac, reference adde

A New Waveform Consistency Test for Gravitational Wave Inspiral Searches

Searches for binary inspiral signals in data collected by interferometric gravitational wave detectors utilize matched filtering techniques. Although matched filtering is optimal in the case of stationary Gaussian noise, data from real detectors often contains "glitches" and episodes of excess noise which cause filter outputs to ring strongly. We review the standard \chi^2 statistic which is used to test whether the filter output has appropriate contributions from several different frequency bands. We then propose a new type of waveform consistency test which is based on the time history of the filter output. We apply one such test to the data from the first LIGO science run and show that it cleanly distinguishes between true inspiral waveforms and large-amplitude false signals which managed to pass the standard \chi^2 test.Comment: 10 pages, 6 figures, submitted to Classical and Quantum Gravity for the proceedings of the Eighth Gravitational Wave Data Analysis Workshop (GWDAW-8

Employment, Income and Labour Supply Decision of Rural Households : An Economic Analysis of MGNREGS in Tamil Nadu

In India, Mahatma Gandhi National Rural Employment Guarantee Scheme (MGMGNREGS) is one of the major rural development programmes. It provides guaranteed employment to the rural households for 100 days in a year. This paper has attempted to find out the employment status, income and labour supply decision of the participants and non-participants of MGNREGS in Tamil Nadu. It has also studied the household nutritional security of these households. The study has revealed that the number of migrants in the family, number of livestock units owned, and number of person-days employed in agriculture, nonagriculture and MGNREGS are significantly influenced by the household income of the participants and non-participants of MGNREGS. The analysis of household food-security has shown that the expenditure for all commodities, viz. leisure, cereals, pulses, oils, fruits & vegetables, milk, chicken and fish are positive and significant in the case of MGNREGS participants, whereas the expenditure variable is significant only for two commodities, viz. cereals and oils in case of MGNREGS non-participants. It shows that the MGNREGS participants consume more high-value commodities like milk, chicken and fish, as compared to MGNREGS non-participants. The labour supply decision of sample respondents has shown that the elasticity of labour supply with respect to wage rate is more than one in both participants and non-participants of MGNREGS, indicating that an one per cent increase in wage rate increases labour supply by 1.92 per cent and 2.36 per cent, respectively. In addition, as the number of dependents increases, the household increases labour supply to derive additional income to meet the increased household expenditures. An interesting and encouraging observation is that the scheme has reduced the migration of people from rural to urban areas.MGNREGS, employment, income, labour supply, Agricultural and Food Policy, J21, J22, H23, I31,

What we don't know about time

String theory has transformed our understanding of geometry, topology and spacetime. Thus, for this special issue of Foundations of Physics commemorating "Forty Years of String Theory", it seems appropriate to step back and ask what we do not understand. As I will discuss, time remains the least understood concept in physical theory. While we have made significant progress in understanding space, our understanding of time has not progressed much beyond the level of a century ago when Einstein introduced the idea of space-time as a combined entity. Thus, I will raise a series of open questions about time, and will review some of the progress that has been made as a roadmap for the future.Comment: 15 pages; Essay for a special issue of Foundations of Physics commemorating "Forty years of string theory

Phonon-induced linewidths of graphene electronic states

The linewidths of the electronic bands originating from the electron-phonon coupling in graphene are analyzed based on model tight-binding calculations and experimental angle-resolved photoemission spectroscopy (ARPES) data. Our calculations confirm the prediction that the high-energy optical phonons provide the most essential contribution to the phonon-induced linewidth of the two upper occupied $\sigma$ bands near the $\bar{\Gamma}$-point. For larger binding energies of these bands, as well as for the $\pi$ band, we find evidence for a substantial lifetime broadening from interband scattering $\pi \rightarrow \sigma$ and $\sigma \rightarrow \pi$, respectively, driven by the out-of-plane ZA acoustic phonons. The essential features of the calculated $\sigma$ band linewidths are in agreement with recent published ARPES data [F. Mazzola et al., Phys.~Rev.~B. 95, 075430 (2017)] and of the $\pi$ band linewidth with ARPES data presented here.Comment: 7 pages, 4 figure

Implementation of Distributed Time Exchange Based Cooperative Forwarding

In this paper, we design and implement time exchange (TE) based cooperative forwarding where nodes use transmission time slots as incentives for relaying. We focus on distributed joint time slot exchange and relay selection in the sum goodput maximization of the overall network. We formulate the design objective as a mixed integer nonlinear programming (MINLP) problem and provide a polynomial time distributed solution of the MINLP. We implement the designed algorithm in the software defined radio enabled USRP nodes of the ORBIT indoor wireless testbed. The ORBIT grid is used as a global control plane for exchange of control information between the USRP nodes. Experimental results suggest that TE can significantly increase the sum goodput of the network. We also demonstrate the performance of a goodput optimization algorithm that is proportionally fair.Comment: Accepted in 2012 Military Communications Conferenc

On the existence of supergravity duals to D1--D5 CFT states

We define a metric operator in the 1/2-BPS sector of the D1-D5 CFT, the eigenstates of which have a good semi-classical supergravity dual; the non-eigenstates cannot be mapped to semi-classical gravity duals. We also analyse how the data defining a CFT state manifests itself in the gravity side, and show that it is arranged into a set of multipoles. Interestingly, we find that quantum mechanical interference in the CFT can have observable manifestations in the semi-classical gravity dual. We also point out that the multipoles associated to the normal statistical ensemble fluctuate wildly, indicating that the mixed thermal state should not be associated to a semi-classical geometry.Comment: 22 pages, 2 figures. v2 : references added, typos correcte

System dynamics-based modelling and analysis of greening the construction industry supply chain

Increasing concern on global warming and corporate social responsibility have made environmental issues an area of importance to address for governments and businesses across the world. Among the Middle East countries, the United Arab Emirates (UAE) tops the list in terms of per capita energy spending and per capita carbon footprints. The construction industry is the major contributor to environmental pollution due to its size and nature of activity. The rapid growth of construction sector has a significant environmental impact with increase in carbon footprints. This paper analyses the environmental implications of the rapidly growing construction industry in UAE using system dynamics approach. Quantitative modelling of the construction industry supply chain helps to measure the dynamic interaction between its various factors under multiple realistic scenarios. The potential carbon savings and the impact of each factor are calculated using scenario development analysis. The paper has addressed in detail the various drivers and inhibitors of carbon emission in the construction industry supply chain and ways to evaluate the carbon savings. The paper provides an analytical decision framework to assess emissions of all stages applicable to the construction industry supply chain

Deep Model Compression: Distilling Knowledge from Noisy Teachers

The remarkable successes of deep learning models across various applications have resulted in the design of deeper networks that can solve complex problems. How- ever, the increasing depth of such models also results in a higher storage and runtime complexity, which restricts the deployability of such very deep models on mobile and portable devices, which have limited storage and battery capacity. While many methods have been proposed for deep model compression in recent years, almost all of them have focused on reducing storage complexity. In this work, we extend the teacher-student framework for deep model com- pression, since it has the potential to address runtime and train time complexity too. We propose a simple method- ology to include a noise-based regularizer while training the student from the teacher, which provides a healthy im- provement in the performance of the student network. Our experiments on the CIFAR-10, SVHN and MNIST datasets show promising improvement, with the best performance on the CIFAR-10 dataset. We also conduct a comprehensive empirical evaluation of the proposed method under related settings on the CIFAR-10 dataset to show the promise of the proposed approach