Quantum nonlocality of four-qubit entangled states

Quantum nonlocality of several four-qubit states is investigated by constructing a new Bell inequality. These include the Greenberger-Zeilinger-Horne (GHZ) state, W state, cluster state, and the state $|\chi>$ that has been recently proposed in [PRL, {\bf 96}, 060502 (2006)]. The Bell inequality is optimally violated by $|\chi>$ but not violated by the GHZ state. The cluster state also violates the Bell inequality though not optimally. The state $|\chi>$ can thus be discriminated from the cluster state by using the inequality. Different aspects of four-partite entanglement are also studied by considering the usefulness of a family of four-qubit mixed states as resources for two-qubit teleportation. Our results generalize those in [PRL, {\bf 72}, 797 (1994)].Comment: 13 pages, 1 figur

Nature vs. Nurture: Predictability in Low-Temperature Ising Dynamics

Consider a dynamical many-body system with a random initial state subsequently evolving through stochastic dynamics. What is the relative importance of the initial state ("nature") vs. the realization of the stochastic dynamics ("nurture") in predicting the final state? We examined this question for the two-dimensional Ising ferromagnet following an initial deep quench from $T=\infty$ to $T=0$. We performed Monte Carlo studies on the overlap between "identical twins" raised in independent dynamical environments, up to size $L=500$. Our results suggest an overlap decaying with time as $t^{-\theta_h}$ with $\theta_h = 0.22 \pm 0.02$; the same exponent holds for a quench to low but nonzero temperature. This "heritability exponent" may equal the persistence exponent for the 2D Ising ferromagnet, but the two differ more generally.Comment: 5 pages, 3 figures; new version includes results for nonzero temperatur

OH(A-X) fluorescence from photodissociative excitation of HO2 at 157.5 nm

The OH(A-X) fluorescence from photodissociative excitation of HO2 by F2 laser photons (157.5 nm) was observed and compared with the OH fluorescence spectra of H2O2 and the O2+CH3OH mixture. The rotational population distributions of OH(A) were obtained from the fluorescence spectra. The most populated levels are J = 4 for photodissociative excitation of HO2, J = 20 for H2O2, and J = 21 for the O2+CH3OH mixture. The fluorescence from the gas mixture is attributed to the O + H recombination for which the atoms are produced from photodissociation of parent molecules

Topological Quantum Phase Transition in Synthetic Non-Abelian Gauge Potential

The method of synthetic gauge potentials opens up a new avenue for our understanding and discovering novel quantum states of matter. We investigate the topological quantum phase transition of Fermi gases trapped in a honeycomb lattice in the presence of a synthetic non- Abelian gauge potential. We develop a systematic fermionic effective field theory to describe a topological quantum phase transition tuned by the non-Abelian gauge potential and ex- plore its various important experimental consequences. Numerical calculations on lattice scales are performed to compare with the results achieved by the fermionic effective field theory. Several possible experimental detection methods of topological quantum phase tran- sition are proposed. In contrast to condensed matter experiments where only gauge invariant quantities can be measured, both gauge invariant and non-gauge invariant quantities can be measured by experimentally generating various non-Abelian gauges corresponding to the same set of Wilson loops

Proper Scaling of the Anomalous Hall Effect

Working with epitaxial films of Fe, we succeeded in independent control of different scattering processes in the anomalous Hall effect. The result appropriately accounted for the role of phonons, thereby clearly exposing the fundamental flaws of the standard plot of the anomalous Hall resistivity versus longitudinal resistivity. A new scaling has been thus established that allows an unambiguous identification of the intrinsic Berry curvature mechanism as well as the extrinsic skew scattering and side-jump mechanisms of the anomalous Hall effect.Comment: 5 pages, 4 figure

Growth of aligned carbon nanotubes on carbon microfibers by dc plasma-enhanced chemical vapor deposition

It is shown that unidirectionally aligned carbon nanotubes can be grown on electrically conductive network of carbon microfibers via control of buffer layer material and applied electric field during dc plasma chemical vapor deposition growth. Ni catalyst deposition on carbon microfiber produces relatively poorly aligned nanotubes with significantly varying diameters and lengths obtained. The insertion of Ti 5 nm thick underlayer between Ni catalyst layer and C microfiber substrate significantly alters the morphology of nanotubes, resulting in much better aligned, finer diameter, and longer array of nanotubes. This beneficial effect is attributed to the reduced reaction between Ni and carbon paper, as well as prevention of plasma etching of carbon paper by inserting a Ti buffer layer. Such a unidirectionally aligned nanotube structure on an open-pore conductive substrate structure may conveniently be utilized as a high-surface-area base electrodes for fuel cells, batteries, and other electrochemical and catalytic reactions

Can Machine Learning, as a RegTech Compliance Tool, lighten the Regulatory Burden for Charitable Organisations in the United Kingdom?

Purpose: The purpose of this article is to explore the extent to which machine learning can be used as solution to lighten the compliance and regulatory burden on charitable organisations in the United Kingdom. Design/methodology/approach: The subject is approached through the analysis of data, literature, and domestic and international regulation. The first part of the article summarises the extent of current regulatory obligations faced by charities, these are then, in the second part, set against the potential technological solutions provided by machine learning as at July 2021. Findings: It is suggested that charities can utilise machine learning as a smart technological solution to ease the regulatory burden they face in a growing and impactful sector. Originality: The work is original because it is the first to specifically explore how machine learning as a technological advance can assist charities in meeting the regulatory compliance challenge