Controlled delocalization of electronic states in a multi-strand quasiperiodic lattice

Finite strips, composed of a periodic stacking of infinite quasiperiodic Fibonacci chains, have been investigated in terms of their electronic properties. The system is described by a tight binding Hamiltonian. The eigenvalue spectrum of such a multi-strand quasiperiodic network is found to be sensitive on the mutual values of the intra-strand and inter-strand tunnel hoppings, whose distribution displays a unique three-subband self-similar pattern in a parameter subspace. In addition, it is observed that special numerical correlations between the nearest and the next-nearest neighbor hopping integrals can render a substantial part of the energy spectrum absolutely continuous. Extended, Bloch like functions populate the above continuous zones, signalling a complete delocalization of single particle states even in such a non-translationally invariant system, and more importantly, a phenomenon that can be engineered by tuning the relative strengths of the hopping parameters. A commutation relation between the potential and the hopping matrices enables us to work out the precise correlation which helps to engineer the extended eigenfunctions and determine the band positions at will.Comment: 8 pages, 6 figure

Implementation and characterization of BinaryWeave: A new search pipeline for continuous gravitational waves from Scorpius X-1

Scorpius X-1 (Sco X-1) has long been considered one of the most promising targets for detecting continuous gravitational waves with ground-based detectors. Observational searches for Sco X-1 have achieved substantial sensitivity improvements in recent years, to the point of starting to rule out emission at the torque-balance limit in the low-frequency range \sim 40--180 Hz. In order to further enhance the detection probability, however, there is still much ground to cover for the full range of plausible signal frequencies \sim 20--1500 Hz, as well as a wider range of uncertainties in binary orbital parameters. Motivated by this challenge, we have developed BinaryWeave, a new search pipeline for continuous waves from a neutron star in a known binary system such as Sco X-1. This pipeline employs a semi-coherent StackSlide F-statistic using efficient lattice-based metric template banks, which can cover wide ranges in frequency and unknown orbital parameters. We present a detailed timing model and extensive injection-and-recovery simulations that illustrate that the pipeline can achieve high detection sensitivities over a significant portion of the parameter space when assuming sufficiently large (but realistic) computing budgets. Our studies further underline the need for stricter constraints on the Sco X-1 orbital parameters from electromagnetic observations, in order to be able to push sensitivity below the torque-balance limit over the entire range of possible source parameters.Comment: 19 pages, 7 figures, 3 table

Flux driven and geometry controlled spin filtering for arbitrary spins in aperiodic quantum networks

We demonstrate that an aperiodic array of certain quantum networks comprising magnetic and non-magnetic atoms can act as perfect spin filters for particles with arbitrary spin state. This can be achieved by introducing minimal quasi-one dimensionality in the basic structural units building up the array, along with an appropriate tuning of the potential of the non-magnetic atoms, the tunnel hopping integral between the non-magnetic atoms and the backbone, and, in some cases, by tuning an external magnetic field. This latter result opens up the interesting possibility of designing a flux controlled spin demultiplexer using quantum networks. The proposed networks have close resemblance with a family of recently developed photonic lattices, and the scheme for spin filtering can thus be linked, in principle, to a possibility of suppressing any one of the two states of polarization of a single photon, almost at will. We use transfer matrices and a real space renormalization group scheme to unravel the conditions under which any aperiodic arrangement of such topologically different structures will filter out any given spin projection. Our results are analytically exact, and corroborated by extensive numerical calculations of the spin polarized transmission and the density of states of such systems

Application of artificial intelligence: benefits and limitations for human potential and labor-intensive economy – an empirical investigation into pandemic ridden Indian industry

Purpose – This paper aims to study the extent of use of artificial intelligence (AI) in the modern organization; to comprehend the changing nature of future jobs in the context of application of AI; and to study the impact of AI on the economy of the country with special reference to the job market. Given the critical scenario of labor intensive Indian economy, the paper intends to show how AI shall affect rather coexist with human intelligence or labor. Design/methodology/approach – The research on implementation of AI in different industries and its effect on job market are at a nascent stage. There is a dearth of literature. Hence, this study followed a qualitative approach to have a better understanding of the research questions as Bhattacherjee (2012) confirms that employing an interpretive paradigm (qualitative analysis as the analysis of data, e.g. data from interview transcripts) is the more productive way to study social order and that it is achieved through “subjective interpretation of participants involved, such as by interviewing different participants and reconciling differences among their responses using their own subjective perspectives”. Sample selection: The selection technique utilized is purposive sampling. The respondents in this research are the general managers and HRs from different companies. A total of 14 senior professionals from various sectors were approached for the interview out of which seven people gave their consent to take interview. Seven senior HR professionals, mainly general managers and HRs from various sectors viz. oil and gas sector, manufacturing, healthcare, construction, media, power and energy and retail were interviewed to understand how they are using AI in their respective fields. Inclusion Criteria: (1) Generally, the people covered under the research are from the decision-making level of their companies so they are in a position to give strategic perspective as well as day to day implication of implementation of AI. (2) Respondents have adequate knowledge of the respective industry to which they belong. (3) Respondents have reasonable industry of dealing with Human Resource Management and national economy as a whole assessment tool and its administration procedures. A narrative approach was adopted to have a better understanding of the research questions and comprehend their views regarding implementation of AI in their respective companies. A semi structured open ended interview was administered to steer the discussion around the research questions. The respondents were interviewed over the phone and each respondent shared their stories. Analysis of data: The narrations were then transcribed by online transcriber website otter.ai.com. The common keywords as prescribed by the website are as: AI, strategy, learning and implementation. The extracts of the discussions are noted in the next segment of the paper. As and when required this research also used secondary data from the journals, literature available in the websites to understand the implementation of AI globally. Findings – A country where the government itself admits 90% of its workforce belongs to informal sector and conspicuously exits a multi-faceted stark digital divide (Huberman, 2001; DiMaggio et al., 2001; Guillen, 2006; Servon, 2002) wherein gap of digital divide is significant between the rural and urban India (Dasgupta et al., 2002; Nath, 2001; Singh, 2007; Mahajan, 2003; Dutta, 2003) talking of educating, applying and implementing AI seems to be “ a distant dream” but an “ambiguous ambition ” Research limitations/implications – Prior to implementation of AI that India has to ensure, the basic hygiene factors of informal sector labor force like social security, 2008, low wages and lack of legal protection, unpaid overtime and occupational health problems, poor bargaining power, working without leave under coercion, child care issues and health ailments(for which mere legislation or statutarization is just a formality executed than taking real action) to take the majority of Indian workforce to attain the motivational factor to acquire the knowledge and skill of AI and to implement it. Practical implications – The AI and its adoption are still at their embryonic stage in Indian companies. With the adoption of such sophisticated technology, in one side, the organizations are dreaming of efficiency, higher productivity and better organizational performance whereas on the other side requirement of changing skill sets and decreasing manpower, creating fear among the mass, which results in hard resistance against the implementation process of AI. On the other hand, lack of expertise and high cost of adoption is also hindering AI to implement in the organizations. The adoption and implementation stage of AI vary from organization to organizations, as well as functions to functions. While the marketing departments of several organizations are using advanced level of AI, there, the HR departments are using AI at the very initial stage. But it is evident from the above discussions that adoption of AI in business functions is inevitable and only it is a matter of time. With the COVID-19 pandemic this has become the utmost necessity for many organizations, particularly who works across the globe. HR partners of the businesses are also adopting AI at a fast pace to do away with the mundane works and deliver efficient services to the stakeholders. It is understood from the discourse that the prerequisite for a successful implementation of AI across the industries throughout the country, needs a concerted effort from industries, academia and government. Social implications – The answer lies in Keynesian economics. The central tenet of which is government intervention rather investment to stabilize and progress the economy by way of spreading Internet connectivity, basic literacy and computer literacy, then only truly AI can be effective in a greater scale. Originality/value – A study on application of artificial intelligence in the pandemic era from a wider perspective, this work is an empirical investigation into the benefits and limitations of artificial intelligence for human potential and labour -intensive pandemic ridden Indian economy