12,113 research outputs found
Observation of fractional quantum Hall effect in an InAs quantum well
The two-dimensional electron system in an InAs quantum well has emerged as a
prime candidate for hosting exotic quasi-particles with non-Abelian statistics
such as Majorana fermions and parafermions. To attain its full promise,
however, the electron system has to be clean enough to exhibit
electron-electron interaction phenomena. Here we report the observation of
fractional quantum Hall effect in a very low disorder InAs quantum well with a
well-width of 24 nm, containing a two-dimensional electron system with a
density cm and low-temperature mobility cm/Vs. At a temperature of mK and T, we
observe a deep minimum in the longitudinal resistance, accompanied by a nearly
quantized Hall plateau at Landau level filling factor
Idle Time Optimization for Target Assignment and Path Finding in Sortation Centers
In this paper, we study the one-shot and lifelong versions of the Target
Assignment and Path Finding problem in automated sortation centers, where each
agent needs to constantly assign itself a sorting station, move to its assigned
station without colliding with obstacles or other agents, wait in the queue of
that station to obtain a parcel for delivery, and then deliver the parcel to a
sorting bin. The throughput of such centers is largely determined by the total
idle time of all stations since their queues can frequently become empty. To
address this problem, we first formalize and study the one-shot version that
assigns stations to a set of agents and finds collision-free paths for the
agents to their assigned stations. We present efficient algorithms for this
task based on a novel min-cost max-flow formulation that minimizes the total
idle time of all stations in a fixed time window. We then demonstrate how our
algorithms for solving the one-shot problem can be applied to solving the
lifelong problem as well. Experimentally, we believe to be the first
researchers to consider real-world automated sortation centers using an
industrial simulator with realistic data and a kinodynamic model of real
robots. On this simulator, we showcase the benefits of our algorithms by
demonstrating their efficiency and effectiveness for up to 350 agents.Comment: AAAI 2020, to appea
Interface modification of clay and graphene platelets reinforced epoxy nanocomposites: a comparative study
The interface between the matrix phase and dispersed phase of a composite plays a critical role in influencing its properties. However, the intricate mecha-nisms of interface are not fully understood, and polymer nanocomposites are no exception. This study compares the fabrication, morphology, and mechanical and thermal properties of epoxy nanocomposites tuned by clay layers (denoted as m-clay) and graphene platelets (denoted as m-GP). It was found that a chemical modification, layer expansion and dispersion of filler within the epoxy matrix resulted in an improved interface between the filler mate-rial and epoxy matrix. This was confirmed by Fourier transform infrared spectroscopy and transmission electron microscope. The enhanced interface led to improved mechanical properties (i.e. stiffness modulus, fracture toughness) and higher glass transition temperatures (Tg) compared with neat epoxy. At 4 wt% m-GP, the critical strain energy release rate G1c of neat epoxy improved by 240 % from 179.1 to 608.6 J/m2 and Tg increased from 93.7 to 106.4 �C. In contrast to m-clay, which at 4 wt%, only improved the G1c by 45 % and Tg by 7.1 %. The higher level of improvement offered by m-GP is attributed to the strong interaction of graphene sheets with epoxy because the covalent bonds between the carbon atoms of graphene sheets are much stronger than silicon-based clay
and production at hadron colliders in nonrelativistic QCD
and (n=1,2,3) production at the LHC is studied at
next-to-leading order in in nonrelativistic QCD. Feeddown
contributions from higher and states are all considered for
lower cross sections and polarizations. The long distance matrix
elements (LDMEs) are extracted from the yield data, and then used to make
predictions for the polarizations, which are found to be
consistent with the measured polarization data within errors. In particular,
the polarization puzzle can be understood by a large feeddown
contribution from states. Our results may provide a good
description for both cross sections and polarizations of prompt
and production at the LHC.Comment: The text and abstract are substantially changed due to the change in
the fitting procedure: we now extract LDMEs of and
by fitting the yield data of the LHC (including cross sections
measured by ATLAS, CMS, and LHCb), and then make predictions for the
polarizations of $\Upsilon(nS)
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