40,041 research outputs found
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
that has been recently proposed in [PRL, {\bf 96}, 060502 (2006)]. The
Bell inequality is optimally violated by but not violated by the GHZ
state. The cluster state also violates the Bell inequality though not
optimally. The state 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 to . We performed Monte Carlo studies on the
overlap between "identical twins" raised in independent dynamical environments,
up to size . Our results suggest an overlap decaying with time as
with ; 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
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