Magnetometry of random AC magnetic fields using a single Nitrogen-Vacancy center

We report on the use of a single NV center to probe fluctuating AC magnetic fields. Using engineered currents to induce random changes in the field amplitude and phase, we show that stochastic fluctuations reduce the NV center sensitivity and, in general, make the NV response field-dependent. We also introduce two modalities to determine the field spectral composition, unknown a priori in a practical application. One strategy capitalizes on the generation of AC-field-induced coherence 'revivals', while the other approach uses the time-tagged fluorescence intensity record from successive NV observations to reconstruct the AC field spectral density. These studies are relevant for magnetic sensing in scenarios where the field of interest has a non-trivial, stochastic behavior, such as sensing unpolarized nuclear spin ensembles at low static magnetic fields.Comment: 11 pages, 3 figure

In-flight determination of spacecraft magnetic bias independent of attitude

A simple algorithm for the in-flight determination of the magnetic bias of a spacecraft is presented. The algorithm, developed for use during the Hubble Space Telescope mission, determines this bias independently of any attitude estimates and requires no spacecraft sensor data other than that from the spacecraft magnetometer(s). Estimates of the algorithm's accuracy and results from a number of numerical studies on the use of this algorithm are also presented

The Proposed Biological Station at the Tortugas

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Big data-savvy teams’ skills, big data-driven actions and business performance

Prior studies on big data analytics have emphasized the importance of specific big data skills and capabilities for organizational success; however, they have largely neglected to investigate the use of cross-functional teams’ skills and its links to the role played by relevant data-driven actions and business performance. Drawing on the resource-based view (RBV) of the firm and on the data collected from big data experts working in global agrifood networks, we examine the links between the use of big data-savvy (BDS) teams’ skills, big data-driven (BDD) actions and business performance. BDS teams depend on multidisciplinary skills (e.g., computing, mathematics, statistics, machine learning, and business domain knowledge) that help them to turn their traditional business operations into modern data-driven insights (e.g., knowing real time price changes and customer preferences), leading to BDD actions that enhance business performance. Our results, raised from structural equation modelling, indicate that BDS teams' skills that produce valuable insights are the key determinants for BDD actions, which ultimately contribute to business performance. We further demonstrate that those organisations that emphasise BDD actions perform better compared to those that do not focus on such applications and relevant insights

Noise resistance of adiabatic quantum computation using random matrix theory

Besides the traditional circuit-based model of quantum computation, several quantum algorithms based on a continuous-time Hamiltonian evolution have recently been introduced, including for instance continuous-time quantum walk algorithms as well as adiabatic quantum algorithms. Unfortunately, very little is known today on the behavior of these Hamiltonian algorithms in the presence of noise. Here, we perform a fully analytical study of the resistance to noise of these algorithms using perturbation theory combined with a theoretical noise model based on random matrices drawn from the Gaussian Orthogonal Ensemble, whose elements vary in time and form a stationary random process.Comment: 9 pages, 3 figure

Thermal noise limitations to force measurements with torsion pendulums: Applications to the measurement of the Casimir force and its thermal correction

A general analysis of thermal noise in torsion pendulums is presented. The specific case where the torsion angle is kept fixed by electronic feedback is analyzed. This analysis is applied to a recent experiment that employed a torsion pendulum to measure the Casimir force. The ultimate limit to the distance at which the Casimir force can be measured to high accuracy is discussed, and in particular the prospects for measuring the thermal correction are elaborated upon.Comment: one figure, five pages, to be submitted to Phys Rev

A Factorization Algorithm for G-Algebras and Applications

It has been recently discovered by Bell, Heinle and Levandovskyy that a large class of algebras, including the ubiquitous $G$-algebras, are finite factorization domains (FFD for short). Utilizing this result, we contribute an algorithm to find all distinct factorizations of a given element $f \in \mathcal{G}$, where $\mathcal{G}$ is any $G$-algebra, with minor assumptions on the underlying field. Moreover, the property of being an FFD, in combination with the factorization algorithm, enables us to propose an analogous description of the factorized Gr\"obner basis algorithm for $G$-algebras. This algorithm is useful for various applications, e.g. in analysis of solution spaces of systems of linear partial functional equations with polynomial coefficients, coming from $\mathcal{G}$. Additionally, it is possible to include inequality constraints for ideals in the input

On Kaluza's sign criterion for reciprocal power series

T. Kaluza has given a criterion for the signs of the power series of a function that is the reciprocal of another power series. In this note the sharpness of this condition is explored and various examples in terms of the Gaussian hypergeometric series are given. A criterion for the monotonicity of the quotient of two power series due to M. Biernacki and J. Krzy\.z is applied.Comment: 13 page

A Method to Tackle First Order Differential Equations with Liouvillian Functions in the Solution - II

We present a semi-decision procedure to tackle first order differential equations, with Liouvillian functions in the solution (LFOODEs). As in the case of the Prelle-Singer procedure, this method is based on the knowledge of the integrating factor structure.Comment: 11 pages, late