2,118 research outputs found
Tuning Jeff = 1/2 Insulating State via Electron Doping and Pressure in Double-Layered Iridate Sr3Ir2O7
Sr3Ir2O7 exhibits a novel Jeff=1/2 insulating state that features a splitting
between Jeff=1/2 and 3/2 bands due to spin-orbit interaction. We report a
metal-insulator transition in Sr3Ir2O7 via either dilute electron doping (La3+
for Sr2+) or application of high pressure up to 35 GPa. Our study of
single-crystal Sr3Ir2O7 and (Sr1-xLax)3Ir2O7 reveals that application of high
hydrostatic pressure P leads to a drastic reduction in the electrical
resistivity by as much as six orders of magnitude at a critical pressure, PC =
13.2 GPa, manifesting a closing of the gap; but further increasing P up to 35
GPa produces no fully metallic state at low temperatures, possibly as a
consequence of localization due to a narrow distribution of bonding angles
{\theta}. In contrast, slight doping of La3+ ions for Sr2+ ions in Sr3Ir2O7
readily induces a robust metallic state in the resistivity at low temperatures;
the magnetic ordering temperature is significantly suppressed but remains
finite for (Sr0.95La0.05)3Ir2O7 where the metallic state occurs. The results
are discussed along with comparisons drawn with Sr2IrO4, a prototype of the
Jeff = 1/2 insulator.Comment: five figure
Multi-utility Learning: Structured-output Learning with Multiple Annotation-specific Loss Functions
Structured-output learning is a challenging problem; particularly so because
of the difficulty in obtaining large datasets of fully labelled instances for
training. In this paper we try to overcome this difficulty by presenting a
multi-utility learning framework for structured prediction that can learn from
training instances with different forms of supervision. We propose a unified
technique for inferring the loss functions most suitable for quantifying the
consistency of solutions with the given weak annotation. We demonstrate the
effectiveness of our framework on the challenging semantic image segmentation
problem for which a wide variety of annotations can be used. For instance, the
popular training datasets for semantic segmentation are composed of images with
hard-to-generate full pixel labellings, as well as images with easy-to-obtain
weak annotations, such as bounding boxes around objects, or image-level labels
that specify which object categories are present in an image. Experimental
evaluation shows that the use of annotation-specific loss functions
dramatically improves segmentation accuracy compared to the baseline system
where only one type of weak annotation is used
Potential for cost savings in high cost coronary bypass surgery patients: A New York State analysis
Impact of Investor's Varying Risk Aversion on the Dynamics of Asset Price Fluctuations
While the investors' responses to price changes and their price forecasts are
well accepted major factors contributing to large price fluctuations in
financial markets, our study shows that investors' heterogeneous and dynamic
risk aversion (DRA) preferences may play a more critical role in the dynamics
of asset price fluctuations. We propose and study a model of an artificial
stock market consisting of heterogeneous agents with DRA, and we find that DRA
is the main driving force for excess price fluctuations and the associated
volatility clustering. We employ a popular power utility function,
with agent specific and
time-dependent risk aversion index, , and we derive an approximate
formula for the demand function and aggregate price setting equation. The
dynamics of each agent's risk aversion index, (i=1,2,...,N), is
modeled by a bounded random walk with a constant variance . We show
numerically that our model reproduces most of the ``stylized'' facts observed
in the real data, suggesting that dynamic risk aversion is a key mechanism for
the emergence of these stylized facts.Comment: 17 pages, 7 figure
Unusual behaviors in the transport properties of REFeP (RE: La, Ce, Pr, and Nd)
We have investigated the resistivity (), thermoelectric power (TEP) and
Hall coefficient () on high quality single crystals of
REFeP. TEP in CeFeP is extremely large (
0.5mV/K at 290K) with a peak of 0.75mV/K at around 65K. The Hall
mobility also shows a peak at 65K, suggesting carriers with heavy masses
developed at lower temperatures related with the f-hybridized band. Both Pr-
and Nd- systems exhibit an apparent increase of with decreasing
temperature far above their magnetic transition temperatures. In the same
temperature ranges, TEP exhibits unusually large absolute values of -50V/K
for PrFeP and -15V/K for NdFeP, respectively.
For PrFeP, such anomalous transport properties suggest an unusual
ground state, possibly related with the Quadrupolar Kondo effect.Comment: 5 pages, 8 figure
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