5,342 research outputs found
Geometric phase and quantum phase transition in an inhomogeneous periodic XY spin-1/2 model
The notion of geometric phase has been recently introduced to analyze the
quantum phase transitions of many-body systems from the geometrical
perspective. In this work, we study the geometric phase of the ground state for
an inhomogeneous period-two anisotropic XY model in a transverse field. This
model encompasses a group of familiar spin models as its special cases and
shows a richer critical behavior. The exact solution is obtained by mapping on
a fermionic system through the Jordan-Wigner transformation and constructing
the relevant canonical transformation to realize the diagonalization of the
Hamiltonian coupled in the -space. The results show that there may exist
more than one quantum phase transition point at some parameter regions and
these transition points correspond to the divergence or extremum properties of
the Berry curvature.Comment: 6 pages, 3 figures. As a backup of a previous work and some typos in
the published version are fixe
Examining Chinese Postgraduate Students’ Academic Adjustment in the UK Higher Education Sector: a Process-Based Stage Model
The current theories relating to international student transition have largely tended to concentrate on what is to be adapted. This research contributes to the pedagogic literature examining how the transition is made by international postgraduate students. Using data from 20 qualitative in-depth interviews in conjunction with observations of teaching sessions and the researchers’ field notes, we discovered a process-based stage model which identifies a step-by-step approach at a micro-level of academic transition. Our findings extended the prior stage modes to incorporate students’ pre-arrival experience and claim that the pre-departure stage plays a crucial role on Chinese students’ later academic adjustment in the UK. The finding of our four-stage-model helps not only higher education institutions increasing sensitivity to the design of study programmes and induction provision but provides practical implications for recruitment agents that attempt to engage students’ pre-arrival preparations in terms of enhancing their marketing strategy in the long term
Judgment Sieve: Reducing Uncertainty in Group Judgments through Interventions Targeting Ambiguity versus Disagreement
When groups of people are tasked with making a judgment, the issue of
uncertainty often arises. Existing methods to reduce uncertainty typically
focus on iteratively improving specificity in the overall task instruction.
However, uncertainty can arise from multiple sources, such as ambiguity of the
item being judged due to limited context, or disagreements among the
participants due to different perspectives and an under-specified task. A
one-size-fits-all intervention may be ineffective if it is not targeted to the
right source of uncertainty. In this paper we introduce a new workflow,
Judgment Sieve, to reduce uncertainty in tasks involving group judgment in a
targeted manner. By utilizing measurements that separate different sources of
uncertainty during an initial round of judgment elicitation, we can then select
a targeted intervention adding context or deliberation to most effectively
reduce uncertainty on each item being judged. We test our approach on two
tasks: rating word pair similarity and toxicity of online comments, showing
that targeted interventions reduced uncertainty for the most uncertain cases.
In the top 10% of cases, we saw an ambiguity reduction of 21.4% and 25.7%, and
a disagreement reduction of 22.2% and 11.2% for the two tasks respectively. We
also found through a simulation that our targeted approach reduced the average
uncertainty scores for both sources of uncertainty as opposed to uniform
approaches where reductions in average uncertainty from one source came with an
increase for the other
Hahn echo and criticality in spin-chain systems
We establish a relation between Hahn spin-echo of a spin-
particle and quantum phase transition in a spin-chain, which couples to the
particle. The Hahn echo is calculated and discussed at zero as well as at
finite temperatures. On the example of XY model, we show that the critical
points of the chain are marked by the extremal values in the Hahn echo, and
influence the Hahn echo in surprising high temperature. An explanation for the
relation between the echo and criticality is also presented.Comment: 5 pages, 6 figure
Lightweight Face Relighting
In this paper we present a method to relight human faces in real time, using consumer-grade graphics cards even with limited 3D capabilities. We show how to render faces using a combination of a simple, hardware-accelerated parametric model simulating skin shading and a detail texture map, and provide robust procedures to estimate all the necessary parameters for a given face. Our model strikes a balance between the difficulty of realistic face rendering (given the very specific reflectance properties of skin) and the goal of real-time rendering with limited hardware capabilities. This is accomplished by automatically generating an optimal set of parameters for a simple rendering model. We offer a discussion of the issues in face rendering to discern the pros and cons of various rendering models and to generalize our approach to most of the current hardware constraints. We provide results demonstrating the usability of our approach and the improvements we introduce both in the performance and in the visual quality of the resulting faces
Constraints on Holographic Dark Energy from Latest Supernovae, Galaxy Clustering, and Cosmic Microwave Background Anisotropy Observations
The holographic dark energy model is proposed by Li as an attempt for probing
the nature of dark energy within the framework of quantum gravity. The main
characteristic of holographic dark energy is governed by a numerical parameter
in the model. The parameter can only be determined by observations.
Thus, in order to characterize the evolving feature of dark energy and to
predict the fate of the universe, it is of extraordinary importance to
constrain the parameter by using the currently available observational
data. In this paper, we derive constraints on the holographic dark energy model
from the latest observational data including the gold sample of 182 Type Ia
supernovae (SNIa), the shift parameter of the cosmic microwave background (CMB)
given by the three-year {\it Wilkinson Microwave Anisotropy Probe} ({\it WMAP})
observations, and the baryon acoustic oscillation (BAO) measurement from the
Sloan Digital Sky Survey (SDSS). The joint analysis gives the fit results in
1-: and . That
is to say, though the possibility of is more favored, the possibility of
can not be excluded in one-sigma error range, which is somewhat different
from the result derived from previous investigations using earlier data. So,
according to the new data, the evidence for the quintom feature in the
holographic dark energy model is not as strong as before.Comment: 22 pages, 8 figures; accepted for publication in Phys. Rev.
Landau-Zener transition of a two-level system driven by spin chains near their critical points
The Landau-Zener(LZ) transition of a two-level system coupling to spin chains
near their critical points is studied in this paper. Two kinds of spin chains,
the Ising spin chain and XY spin chain, are considered. We calculate and
analyze the effects of system-chain coupling on the LZ transition. A relation
between the LZ transition and the critical points of the spin chain is
established. These results suggest that LZ transitions may serve as the
witnesses of criticality of the spin chain. This may provide a new way to study
quantum phase transitions as well as LZ transitions.Comment: 5 pages, 4 figures. European Physical Journals D accepte
Abelian and Non-Abelian Quantum Geometric Tensor
We propose a generalized quantum geometric tenor to understand topological
quantum phase transitions, which can be defined on the parameter space with the
adiabatic evolution of a quantum many-body system. The generalized quantum
geometric tenor contains two different local measurements, the non-Abelian
Riemannian metric and the non-Abelian Berry curvature, which are recognized as
two natural geometric characterizations for the change of the ground-state
properties when the parameter of the Hamiltonian varies. Our results show the
symmetry-breaking and topological quantum phase transitions can be understood
as the singular behavior of the local and topological properties of the quantum
geometric tenor in the thermodynamic limit.Comment: 5 pages, 2 figure
Graphite Nanoeraser
We present here a method for cleaning intermediate-size (5~50nm)
contamination from highly oriented pyrolytic graphite. Electron beam deposition
causes a continuous increase of carbonaceous material on graphene and graphite
surfaces, which is difficult to remove by conventional techniques. Direct
mechanical wiping using a graphite nanoeraser is observed to drastically reduce
the amount of contamination. After the mechanical removal of contamination, the
graphite surfaces were able to self-retract after shearing, indicating that van
der Waals contact bonding is restored. Since contact bonding provides an
indication of a level of cleanliness normally only attainable in a high-quality
clean-room, we discuss potential applications in preparation of ultraclean
surfaces.Comment: 10 pages, two figure
Weak Signal Inclusion Under Dependence and Applications in Genome-wide Association Study
Motivated by the inquiries of weak signals in underpowered genome-wide
association studies (GWASs), we consider the problem of retaining true signals
that are not strong enough to be individually separable from a large amount of
noise. We address the challenge from the perspective of false negative control
and present false negative control (FNC) screening, a data-driven method to
efficiently regulate false negative proportion at a user-specified level. FNC
screening is developed in a realistic setting with arbitrary covariance
dependence between variables. We calibrate the overall dependence through a
parameter whose scale is compatible with the existing phase diagram in
high-dimensional sparse inference. Utilizing the new calibration, we
asymptotically explicate the joint effect of covariance dependence, signal
sparsity, and signal intensity on the proposed method. We interpret the results
using a new phase diagram, which shows that FNC screening can efficiently
select a set of candidate variables to retain a high proportion of signals even
when the signals are not individually separable from noise. Finite sample
performance of FNC screening is compared to those of several existing methods
in simulation studies. The proposed method outperforms the others in adapting
to a user-specified false negative control level. We implement FNC screening to
empower a two-stage GWAS procedure, which demonstrates substantial power gain
when working with limited sample sizes in real applications.Comment: arXiv admin note: text overlap with arXiv:2006.1566
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