421 research outputs found
Necessity for quantum coherence of nondegeneracy in energy flow
In this work, we show that the quantum coherence among non-degenerate energy
subspaces (CANES) is essential for the energy flow in any quantum system. CANES
satisfies almost all of the requirements as a coherence measure, except that
the coherence within degenerate subspaces is explicitly eliminated.We show that
the energy of a system becomes frozen if and only if the corresponding CANES
vanishes, which is true regardless of the form of interaction with the
environment. However, CANES can remain zero even if the entanglement changes
over time. Furthermore, we show how the power of energy flow is bounded by the
value of CANES. An explicit relation connecting the variation of energy and
CANES is also presented. These results allow us to bound the generation of
system-environment correlation through the local measurement of the system's
energy flow
The Role of Semantic Parsing in Understanding Procedural Text
In this paper, we investigate whether symbolic semantic representations,
extracted from deep semantic parsers, can help reasoning over the states of
involved entities in a procedural text. We consider a deep semantic
parser~(TRIPS) and semantic role labeling as two sources of semantic parsing
knowledge. First, we propose PROPOLIS, a symbolic parsing-based procedural
reasoning framework. Second, we integrate semantic parsing information into
state-of-the-art neural models to conduct procedural reasoning. Our experiments
indicate that explicitly incorporating such semantic knowledge improves
procedural understanding. This paper presents new metrics for evaluating
procedural reasoning tasks that clarify the challenges and identify differences
among neural, symbolic, and integrated models.Comment: 9 pages, Appected in EACL202
Axisymmetric column collapses of bi-frictional granular mixtures
The behavior of granular column collapses is associated with the dynamics of
geohazards, such as debris flows, landslides, and pyroclastic flows, yet its
underlying physics is still not well understood. In this paper, we explore
granular column collapses using the spheropolyhedral discrete element method
(DEM), where the system contains two types of particles with different
frictional properties. We impose three different mixing ratios and multiple
different particle frictional coefficients, which lead to different run-out
distances and deposition heights. Based on our previous work and a simple
mixture theory, we propose a new effective initial aspect ratio for the
bi-frictional granular mixture, which helps unify the description of the
relative run-out distances. We analyze the kinematics of bi-frictional granular
column collapses and find that deviations from classical power-law scaling in
both the dimensionless terminal time and the dimensionless time when the system
reaches the maximum kinetic energy may result from differences in the initial
solid fraction and initial structures. To clarify the influence of initial
states, we further decrease the initial solid fraction of granular column
collapses, and propose a trial function to quantitatively describe its
influence. Due to the utilization of a simple mixture theory of contact
occurrence probability, this study can be associated with the
friction-dependent rheology of granular systems and friction-induced granular
segregations, and further generalized into applications with multiple species
of particles in various natural and engineering mixtures
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