Heavy-Flavoured Jets at HERA

Heavy-flavoured jets have been studied in photoproduction at HERA. This includes the first measurement of dijet angular distributions in D* photoproduction and the ratio of the vector/(vector + pseudoscalar) production rate for charm mesons.Comment: Contribution to the Proceedings of the PHOTON 2001 Conference. 4 pages, 3 figure

Cavity Optomechanics with Ultra Cold Atoms in Synthetic Abelian and Non-Abelian Gauge Field

In this article we present a pedagogical discussion of some of the optomechanical properties of a high finesse cavity loaded with ultracold atoms in laser induced synthetic gauge fields of different types. Essentially, the subject matter of this article is an amalgam of two sub-fields of atomic molecular and optical (AMO) physics namely, the cavity optomechanics with ultracold atoms and ultracold atoms in synthetic gauge field. After providing a brief introduction to either of these fields we shall show how and what properties of these trapped ultracold atoms can be studied by looking at the cavity (optomechanical or transmission) spectrum. In presence of abelian synthetic gauge field we discuss the cold-atom analogue of Shubnikov de Haas oscillation and its detection through cavity spectrum. Then, in the presence of a non-abelian synthetic gauge field (spin-orbit coupling), we see when the electromagnetic field inside the cavity is quantized, it provides a quantum optical lattice for the atoms, leading to the formation of different quantum magnetic phases. We also discuss how these phases can be explored by studying the cavity transmission spectrum.Comment: Invited Review Article in the journal Ato

Estimation of soil water deficit in an irrigated cotton field with infrared thermography

Plant growth and soil water deficit can vary spatially and temporally in crop fields due to variation in soil properties and/or irrigation and crop management factors. We conducted field experiments with cotton (Gossypium hirsutum L.) over two seasons during 2007-2009 to test if infrared thermography can distinguish systematic variation in deficit irrigation applied to various parts of the field over time. Soil water content was measured with a neutron probe and thermal images of crop plants were taken with a thermal infrared camera. Leaf water potential and stomatal conductance were also measured on selected occasions. All measurements were made at fixed locations within three replicate plots of an irrigation experiment consisting of four soil-water deficit treatments. Canopy temperature related as well with soil water within the root zone of cotton as the stomatal conductance index derived from canopy temperature, but it neglected the effect of local and seasonal variation in environmental conditions. Similarities in the pattern of spatial variation in canopy temperature and soil water over the experimental field indicates that thermography can be used with stomatal conductance index to assess soil water deficit in cotton fields for scheduling of irrigation and to apply water in areas within the field where it is most needed to reduce water deficit stress to the crop. Further confidence with application of infrared thermography can be gained by testing our measurement approach and analysis with irrigation scheduling of other crops

Overfitting in Synthesis: Theory and Practice (Extended Version)

In syntax-guided synthesis (SyGuS), a synthesizer's goal is to automatically generate a program belonging to a grammar of possible implementations that meets a logical specification. We investigate a common limitation across state-of-the-art SyGuS tools that perform counterexample-guided inductive synthesis (CEGIS). We empirically observe that as the expressiveness of the provided grammar increases, the performance of these tools degrades significantly. We claim that this degradation is not only due to a larger search space, but also due to overfitting. We formally define this phenomenon and prove no-free-lunch theorems for SyGuS, which reveal a fundamental tradeoff between synthesizer performance and grammar expressiveness. A standard approach to mitigate overfitting in machine learning is to run multiple learners with varying expressiveness in parallel. We demonstrate that this insight can immediately benefit existing SyGuS tools. We also propose a novel single-threaded technique called hybrid enumeration that interleaves different grammars and outperforms the winner of the 2018 SyGuS competition (Inv track), solving more problems and achieving a $5\times$ mean speedup.Comment: 24 pages (5 pages of appendices), 7 figures, includes proofs of theorem