Identifying a new particle with jet substructures

We investigate a potential of measuring properties of a heavy resonance X, exploiting jet substructure techniques. Motivated by heavy higgs boson searches, we focus on the decays of X into a pair of (massive) electroweak gauge bosons. More specifically, we consider a hadronic Z boson, which makes it possible to determine properties of X at an earlier stage. For $m_X$ of O(1) TeV, two quarks from a Z boson would be captured as a "merged jet" in a significant fraction of events. The use of the merged jet enables us to consider a Z-induced jet as a reconstructed object without any combinatorial ambiguity. We apply a conventional jet substructure method to extract four-momenta of subjets from a merged jet. We find that jet substructure procedures may enhance features in some kinematic observables formed with subjets. Subjet momenta are fed into the matrix element associated with a given hypothesis on the nature of X, which is further processed to construct a matrix element method (MEM)-based observable. For both moderately and highly boosted Z bosons, we demonstrate that the MEM with current jet substructure techniques can be a very powerful discriminator in identifying the physics nature of X. We also discuss effects from choosing different jet sizes for merged jets and jet-grooming parameters upon the MEM analyses.Comment: 36 pages, 11 figures, published in JHE

Multi-Screen Strategy for Selling Mobile Content to Customers

Our research aims to discover the role of multiple smart devices and their different screen sizes in paid content sales, thus building a multi-screen content sales strategy. Our econometric model adopts a difference-in-differences method to measure the impact of multi-screen devices on users’ content consumption through screen size effects. In a natural experiment setting, we sample 238 individual customers who registered a single smartphone with a 3- to 4-inch screen at the beginning and then added devices with a similar or larger screen. Our paper determines the parameters in existing theoretical frameworks of online consumer utility (product selection and digital content price) to determine paid content purchase behavior in a multi-screen environment. Our key findings are that the price sensitivity of content decreases as a user registers new smart devices and registering new devices with larger screens positively influences less popular content consumption more than a small screen device does

Decentralized system identification using stochastic subspace identification for wireless sensor networks

Wireless sensor networks (WSNs) facilitate a new paradigm to structural identification and monitoring for civil infrastructure. Conventional structural monitoring systems based on wired sensors and centralized data acquisition systems are costly for installation as well as maintenance. WSNs have emerged as a technology that can overcome such difficulties, making deployment of a dense array of sensors on large civil structures both feasible and economical. However, as opposed to wired sensor networks in which centralized data acquisition and processing is common practice, WSNs require decentralized computing algorithms to reduce data transmission due to the limitation associated with wireless communication. In this paper, the stochastic subspace identification (SSI) technique is selected for system identification, and SSI-based decentralized system identification (SDSI) is proposed to be implemented in a WSN composed of Imote2 wireless sensors that measure acceleration. The SDSI is tightly scheduled in the hierarchical WSN, and its performance is experimentally verified in a laboratory test using a 5-story shear building model. ??? 2015 by the authors; licensee MDPI, Basel, Switzerlandopen0