2,981 research outputs found
A Study on the Growth Policies and Profitability's of Select Mergers and Acquisitions in India
Information is Not Lost in the Evaporation of 2-dimensional Black Holes
We analyze Hawking evaporation of the Callen-Giddings-Harvey-Strominger
(CGHS) black holes from a quantum geometry perspective and show that
information is not lost, primarily because the quantum space-time is
sufficiently larger than the classical. Using suitable approximations to
extract physics from quantum space-times we establish that: i)future null
infinity of the quantum space-time is sufficiently long for the the past vacuum
to evolve to a pure state in the future; ii) this state has a finite norm in
the future Fock space; and iii) all the information comes out at future
infinity; there are no remnants.Comment: 4 pages, 2 figure
Classical and quantum geometrodynamics of 2d vacuum dilatonic black holes
We perform a canonical analysis of the system of 2d vacuum dilatonic black
holes. Our basic variables are closely tied to the spacetime geometry and we do
not make the field redefinitions which have been made by other authors. We
present a careful discssion of asymptotics in this canonical formalism.
Canonical transformations are made to variables which (on shell) have a clear
spacetime significance. We are able to deduce the location of the horizon on
the spatial slice (on shell) from the vanishing of a combination of canonical
data. The constraints dramatically simplify in terms of the new canonical
variables and quantization is easy. The physical interpretation of the variable
conjugate to the ADM mass is clarified. This work closely parallels that done
by Kucha{\v r} for the vacuum Schwarzschild black holes and is a starting point
for a similar analysis, now in progress, for the case of a massless scalar
field conformally coupled to a 2d dilatonic black hole.Comment: 21 pages, latex fil
Airborne mapping of complex obstacles using 2D Splinegon
This paper describes a recently proposed algorithm in mapping the unknown
obstacle in a stationary environment where the obstacles are represented as
curved in nature. The focus is to achieve a guaranteed performance of sensor
based navigation and mapping. The guaranteed performance is quantified by
explicit bounds of the position estimate of an autonomous aerial vehicle using
an extended Kalman filter and to track the obstacle so as to extract the map of
the obstacle. This Dubins path planning algorithm is used to provide a flyable
and safe path to the vehicle to fly from one location to another. This
description takes into account the fact that the vehicle is made to fly around
the obstacle and hence will map the shape of the obstacle using the 2D-Splinegon
technique. This splinegon technique, the most efficient and a robust way to
estimate the boundary of a curved nature obstacles, can provide mathematically
provable performance guarantees that are achievable in practice
The Price Impact of Order Book Events
We study the price impact of order book events - limit orders, market orders
and cancelations - using the NYSE TAQ data for 50 U.S. stocks. We show that,
over short time intervals, price changes are mainly driven by the order flow
imbalance, defined as the imbalance between supply and demand at the best bid
and ask prices. Our study reveals a linear relation between order flow
imbalance and price changes, with a slope inversely proportional to the market
depth. These results are shown to be robust to seasonality effects, and stable
across time scales and across stocks. We argue that this linear price impact
model, together with a scaling argument, implies the empirically observed
"square-root" relation between price changes and trading volume. However, the
relation between price changes and trade volume is found to be noisy and less
robust than the one based on order flow imbalance
Generic Schema Matching with Cupid
Schema matching is a critical step in many applications, such as XML message mapping, data warehouse loading, and schema integration. In this paper, we
investigate algorithms for generic schema matching, outside of any particular data model or application. We first present a taxonomy for past solutions, showing that a rich range of techniques is available. We then propose a new algorithm, Cupid, that discovers mappings between schema elements based on their names, data types, constraints, and schema structure, using a broader set of techniques than past approaches. Some of our innovations are the integrated use of linguistic and structural matching, context-dependent matching of shared types, and a bias toward leaf structure where much of the schema content resides. After describing our algorithm, we present experimental results that compare Cupid to two other schema matching systems
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