Jaypee Institute of Information Technology

About: Jaypee Institute of Information Technology is a education organization based out in Noida, Uttar Pradesh, India. It is known for research contribution in the topics: Computer science & Cluster analysis. The organization has 2136 authors who have published 3435 publications receiving 31458 citations. The organization is also known as: JIIT Noida.

Quasiprobability distributions in open quantum systems: spin-qubit systems

Abstract: Quasiprobability distributions (QDs) in open quantum systems are investigated for $SU(2)$, spin like systems, having relevance to quantum optics and information. In this work, effect of both quantum non-demolition (QND) and dissipative open quantum systems, on the evolution of a number of spin QDs are investigated. Specifically, compact analytic expressions for the $W$, $P$, $Q$, and $F$ functions are obtained for some interesting single, two and three qubit states, undergoing general open system evolutions. Further, corresponding QDs are reported for an N qubit Dicke model and a spin-1 system. The existence of nonclassical characteristics are observed in all the systems investigated here. The study leads to a clear understanding of quantum to classical transition in a host of realistic physical scenarios. Variation of the amount of nonclassicality observed in the quantum systems, studied here,are also investigated using nonclassical volume.

Social Influence Maximization Using Genetic Algorithm with Dynamic Probabilities

Abstract: The previous decades have observed the exponential growth of online social networks, where billions of users exchange information with each other and generate tremendously large quantity of the content. This dominance of social networks in our daily life has encouraged more consideration of researcher in the field of information diffusion, where a small bit of information could widespread through “world of mouth” effect. One of the key research problems in information diffusion is influence maximization, which is a NP-hard problem. Influence Maximization (IM) is the problem to find k number of nodes that are most influential nodes of the network, which can maximize the information propagation in the network. Various heuristics available to find most influencing nodes of the network include random, high degree, single discount, general greedy and genetic algorithm with weighted cascade etc. In this paper, we proposed dynamic probability based genetic approach using topic affinity propagation (TAP) method to find the optimal set of influential nodes of the network. The efficiency of the proposed approach is analyzed on two large-scale networks. Results express that the proposed algorithm is able to improve the influence spread by 6% to 13% with respect to various influence maximization heuristics.

Effective asthma disease prediction using naive Bayes — Neural network fusion technique

Abstract: Asthma is a lung disease caused by the inflammation and narrowing of the airways that causes recurrent attacks of breathlessness and wheezing, and often can be life-threatening. Around 15–20 million people are suffering from asthma in India[1]. This paper aims at analyzing various data mining techniques for the prediction of asthma. The observations show that the fusion approach of naive bayes and neural network proved to be the best among classification algorithms in the diagnosis of asthma. This methodology is evaluated using 1024 raw data obtained from a city hospital. The proposed approach helps patients in their diagnosis of asthma.

Maximal entanglement concentration for a set of $$(n+1)$$(n+1)-qubit states

Abstract: We propose two schemes for concentration of $$(n+1)$$(n+1)-qubit entangled states that can be written in the form of $$\left( \alpha |\varphi _{0}\rangle |0\rangle +\beta |\varphi _{1}\rangle |1\rangle \right) _{n+1}$$?|?0?|0?+s|?1?|1?n+1 where $$|\varphi _{0}\rangle $$|?0? and $$|\varphi _{1}\rangle $$|?1? are mutually orthogonal n-qubit states. The importance of this general form is that the entangled states such as Bell, cat, GHZ, GHZ-like, $$|\varOmega \rangle $$|Ω?, $$|Q_{5}\rangle $$|Q5?, 4-qubit cluster states and specific states from the nine SLOCC-nonequivalent families of 4-qubit entangled states can be expressed in this form. The proposed entanglement concentration protocol is based on the local operations and classical communications (LOCC). It is shown that the maximum success probability for ECP using quantum nondemolition technique (QND) is $$2\beta ^{2}$$2s2 for $$(n+1)$$(n+1)-qubit states of the prescribed form. It is shown that the proposed schemes can be implemented optically. Further, it is also noted that the proposed schemes can be implemented using quantum dot and microcavity systems.