Infinite randomness and quantum Griffiths effects in a classical system: the randomly layered Heisenberg magnet

We investigate the phase transition in a three-dimensional classical Heisenberg magnet with planar defects, i.e., disorder perfectly correlated in two dimensions. By applying a strong-disorder renormalization group, we show that the critical point has exotic infinite-randomness character. It is accompanied by strong power-law Griffiths singularities. We compute various thermodynamic observables paying particular attention to finite-size effects relevant for an experimental verification of our theory. We also study the critical dynamics within a Langevin equation approach and find it extremely slow. At the critical point, the autocorrelation function decays only logarithmically with time while it follows a nonuniversal power-law in the Griffiths phase.Comment: 10 pages, 2 eps figures included, final version as published

Pinning down neutrino oscillation parameters in the 2-3 sector with a mgnetised atmospheric neutrino detector: a new study

We determine the sensitivity to neutrino oscillation parameters from a study of atmospheric neutrinos in a magnetised detector such as the ICAL at the proposed India-based Neutrino Observatory. In such a detector that can {\em separately} count $\nu_\mu$ and $\overline{\nu}_\mu$-induced events, the relatively smaller (about 5\%) uncertainties on the neutrino--anti-neutrino flux ratios translate to a constraint in the $\chi^2$ analysis that results in a significant improvement in the precision with which neutrino oscillation parameters such as $\sin^2\theta_{23}$ can be determined. Such an effect is unique to all magnetisable detectors and constitutes a great advantage in determining neutrino oscillation parameters using such detectors. Such a study has been performed for the first time here. Along with an increase in the kinematic range compared to earlier analyses, this results in sensitivities to oscillation parameters in the 2--3 sector that are comparable to or better than those from accelerator experiments where the fluxes are significantly higher. For example, the $1\sigma$ precisions on $\sin^2\theta_{23}$ and $|\Delta{m^2_{32(31)}}|$ achievable for 500 kTon yr exposure of ICAL are $\sim9\%$ and $\sim2.5\%$ respectively for both normal and inverted hierarchies. The mass hierarchy sensitivity achievable with this combination when the true hierarchy is normal (inverted) for the same exposure is $\Delta\chi^2\approx8.5$ ($\Delta\chi^2\approx9.5$)

Jet substructure and probes of CP violation in Vh production

We analyse the hVV (V = W, Z) vertex in a model independent way using Vh production. To that end, we consider possible corrections to the Standard Model Higgs Lagrangian, in the form of higher dimensional operators which parametrise the effects of new physics. In our analysis, we pay special attention to linear observables that can be used to probe CP violation in the same. By considering the associated production of a Higgs boson with a vector boson (W or Z), we use jet substructure methods to define angular observables which are sensitive to new physics effects, including an asymmetry which is linearly sensitive to the presence of CP odd effects. We demonstrate how to use these observables to place bounds on the presence of higher dimensional operators, and quantify these statements using a log likelihood analysis. Our approach allows one to probe separately the hZZ and hWW vertices, involving arbitrary combinations of BSM operators, at the Large Hadron Collider.Comment: 37 pages, 17 figures; v3 matches published versio

Network Inference via the Time-Varying Graphical Lasso

Many important problems can be modeled as a system of interconnected entities, where each entity is recording time-dependent observations or measurements. In order to spot trends, detect anomalies, and interpret the temporal dynamics of such data, it is essential to understand the relationships between the different entities and how these relationships evolve over time. In this paper, we introduce the time-varying graphical lasso (TVGL), a method of inferring time-varying networks from raw time series data. We cast the problem in terms of estimating a sparse time-varying inverse covariance matrix, which reveals a dynamic network of interdependencies between the entities. Since dynamic network inference is a computationally expensive task, we derive a scalable message-passing algorithm based on the Alternating Direction Method of Multipliers (ADMM) to solve this problem in an efficient way. We also discuss several extensions, including a streaming algorithm to update the model and incorporate new observations in real time. Finally, we evaluate our TVGL algorithm on both real and synthetic datasets, obtaining interpretable results and outperforming state-of-the-art baselines in terms of both accuracy and scalability

Municipal Solid Waste Management in Cities - Issues of Basic Rights of People Surrounding Village and Alternatives

The Study is based on the findings of a three weeklong field study conducted in Villappilsala, a village 14 kms away from Thriuvananthapuram City. The waste disposal plant for treating the Municipal Solid Waste generated in the Thiruvanathapuram City is located here. The study focuses on the health and environmental impacts of the functioning of the plant on the local community and addresses the larger question of necessity for scientific and cost effective alternative methods of waste disposal in the city itself. The disposal of Solid Waste has become a problem calling for more attention in the wake of urban development, which is the consequence of more people settling in the cities. The issue of decentralised and scientific disposal of Solid Waste at household level and at the level of small groups of households is emphasised. The central issue thrown up by this study is the poorer sections of the village folk bearing the brunt of the consequences of the profligate consumption and callous waste disposal habits of the upper classes in the citiesMUNICIPAL SOLID WASTE; BASIC RIGHTS; Villappilsala; health and environmental impacts

Evaluation of rice–legume–rice cropping system on grain yield, nutrient uptake, nitrogen fixation, and chemical, physical, and biological properties of soil

To achieve higher yields and better soil quality under rice–legume–rice (RLR) rotation in a rainfed production system, we formulated integrated nutrient management (INM) comprised of Azospirillum (Azo), Rhizobium (Rh), and phosphate-solubilizing bacteria (PSB) with phosphate rock (PR), compost, and muriate of potash (MOP). Performance of bacterial bioinoculants was evaluated by determining grain yield, nitrogenase activity, uptake and balance of N, P, and Zn, changes in water stability and distribution of soil aggregates, soil organic C and pH, fungal/bacterial biomass C ratio, casting activities of earthworms, and bacterial community composition using denaturing gradient gel electrophoresis (DGGE) fingerprinting. The performance comparison was made against the prevailing farmers’ nutrient management practices [N/P2O5/K2O at 40:20:20 kg ha−1 for rice and 20:30:20 kg ha−1 for legume as urea/single super-phosphate/MOP (urea/SSP/MOP)]. Cumulative grain yields of crops increased by 7–16% per RLR rotation and removal of N and P by six crops of 2 years rotation increased significantly (P < 0.05) in bacterial bioinoculants-based INM plots over that in compost alone or urea/SSP/MOP plots. Apparent loss of soil total N and P at 0–15 cm soil depth was minimum and apparent N gain at 15–30 cm depth was maximum in Azo/Rh plus PSB dual INM plots. Zinc uptake by rice crop and diethylenetriaminepentaacetate-extractable Zn content in soil increased significantly (P < 0.05) in bacterial bioinoculants-based INM plots compared to other nutrient management plots. Total organic C content in soil declined at 0–15 cm depth and increased at 15–30 cm depth in all nutrient management plots after a 2-year crop cycle; however, bacterial bioinoculants-based INM plots showed minimum loss and maximum gain of total organic C content in the corresponding soil depths. Water-stable aggregation and distribution of soil aggregates in 53–250- and 250–2,000 μm classes increased significantly (P < 0.05) in bacterial bioinoculants-based INM plots compared to other nutrient management plots. Fungal/bacterial biomass C ratio seems to be a more reliable indicator of C and N dynamics in acidic soils than total microbial biomass C. Compost alone or Azo/Rh plus PSB dual INM plots showed significantly (P < 0.05) higher numbers of earthworms’ casts compared to urea/SSP/MOP alone and bacterial bioinoculants with urea or SSP-applied plots. Hierarchical cluster analysis based on similarity matrix of DGGE profiles revealed changes in bacterial community composition in soils due to differences in nutrient management, and these changes were seen to occur according to the states of C and N dynamics in acidic soil under RLR rotation