16,672 research outputs found
Quantum mechanics in the general quantum systems (V): Hamiltonian eigenvalues
We derive out a complete series expression of Hamiltonian eigenvalues without
any approximation and cut in the general quantum systems based on Wang's formal
framework \cite{wang1}. In particular, we then propose a calculating approach
of eigenvalues of arbitrary Hamiltonian via solving an algebra equation
satisfied by a kernal function, which involves the contributions from all order
perturbations. In order to verify the validity of our expressions and reveal
the power of our approach, we calculate the ground state energy of a quartic
anharmonic oscillator and have obtained good enough results comparing with the
known one.Comment: 18 pages, No figure. This is the fifth manuscript. Previous
manuscripts see arXiv:quant-ph/0611216, arXiv:quant-ph/0611217,
arXiv:quant-ph/0601051 and arXiv:quant-ph/061206
On the nature of the $\pi_2(1880)
The strong decays of the as the quark-antiquark state
are investigated in the model and the flux-tube model, respectively.
The results are similar in the two models. It is found that the decay patterns
of the conventional meson and the light hybrid are very
different, and the experimental evidence for the is consistent
with it being the conventional meson rather than the light
hybrid. The possibility of the being a mixture of the
conventional and the hybrid is discussed.Comment: 11 pages, 3 figures, version accepted for publication in Phys. Rev.
Study of the elastocaloric effect and mechanical behavior for the NiTi shape memory alloys
The NiTi shape memory alloy exhibited excellent superelastic property and
elastocaloric effect. Large temperature changes of 30 K upon loading and -19 K
upon unloading were obtained at room temperature, which were higher than those
of the other NiTi-based materials and among the highest values reported in the
elastocaloric materials. The asymmetry of the measured temperature changes
between loading and unloading process was ascribed to the friction dissipation.
The large temperature changes originated from the large entropy change during
the stress-induced martensite transformation (MT) and the reverse MT. A large
coefficient-of-performance of the material (COPmater) of 11.7 was obtained,
which decreased with increasing the applied strain. These results are very
attractive in the present solid-state cooling which is potential to replace the
vapor compression refrigeration technologies
Short-term load forecasting using optimized LSTM networks based on EMD
Short-term load forecasting is one of the crucial sections in smart grid.
Precise forecasting enables system operators to make reliable unit commitment
and power dispatching decisions. With the advent of big data, a number of
artificial intelligence techniques such as back propagation, support vector
machine have been used to predict the load of the next day. Nevertheless, due
to the noise of raw data and the randomness of power load, forecasting errors
of existing approaches are relatively large. In this study, a short-term load
forecasting method is proposed on the basis of empirical mode decomposition and
long short-term memory networks, the parameters of which are optimized by a
particle swarm optimization algorithm. Essentially, empirical mode
decomposition can decompose the original time series of historical data into
relatively stationary components and long short-term memory network is able to
emphasize as well as model the timing of data, the joint use of which is
expected to effectively apply the characteristics of data itself, so as to
improve the predictive accuracy. The effectiveness of this research is
exemplified on a realistic data set, the experimental results of which show
that the proposed method has higher forecasting accuracy and applicability, as
compared with existing methods.Comment: 16 pages,11 figure
Almost Optimal Channel Access in Multi-Hop Networks With Unknown Channel Variables
We consider distributed channel access in multi-hop cognitive radio networks.
Previous works on opportunistic channel access using multi-armed bandits (MAB)
mainly focus on single-hop networks that assume complete conflicts among all
secondary users. In the multi-hop multi-channel network settings studied here,
there is more general competition among different communication pairs. We
formulate the problem as a linearly combinatorial MAB problem that involves a
maximum weighted independent set (MWIS) problem with unknown weights which need
to learn. Existing methods for MAB where each of nodes chooses from
channels have exponential time and space complexity , and poor
theoretical guarantee on throughput performance. We propose a distributed
channel access algorithm that can achieve of the optimum averaged
throughput where each node has communication complexity and space
complexity in the learning process, and time complexity in strategy decision process for an arbitrary wireless network.
Here is the approximation ratio to MWIS for a local -hop
network with nodes,and is the number of mini-rounds inside each round
of strategy decision. For randomly located networks with an average degree ,
the time complexity is .Comment: 9 page
An accurate front capturing scheme for tumor growth models with a free boundary limit
We consider a class of tumor growth models under the combined effects of
density-dependent pressure and cell multiplication, with a free boundary model
as its singular limit when the pressure-density relationship becomes highly
nonlinear. In particular, the constitutive law connecting pressure and
density is , and when , the
cell density may evolve its support due to a pressure-driven geometric
motion with sharp interface along the boundary of its support. The nonlinearity
and degeneracy in the diffusion bring great challenges in numerical
simulations, let alone the capturing of the singular free boundary limit. Prior
to the present paper, there is lack of standard mechanism to numerically
capture the front propagation speed as . In this paper, we develope a
numerical scheme based on a novel prediction-correction reformulation that can
accurately approximate the front propagation even when the nonlinearity is
extremely strong. We show that the semi-discrete scheme naturally connects to
the free boundary limit equation as , and with proper
spacial discretization, the fully discrete scheme has improved stability,
preserves positivity, and implements without nonlinear solvers. Finally,
extensive numerical examples in both one and two dimensions are provided to
verify the claimed properties and showcase good performance in various
applications
Energy landscape and conical intersection points of the driven Rabi model
We examine the energy surfaces of the driven Rabi model, also known as the
biased or generalised Rabi model, as a function of the coupling strength and
the driving term. The energy surfaces are plotted numerically from the known
analytic solution. The resulting energy landscape consists of an infinite stack
of sheets connected by conical intersection points located at the degenerate
Juddian points in the eigenspectrum. Trajectories encircling these points are
expected to exhibit a nonzero geometric phase.Comment: 6 pages, 4 figures, minor correction
Analysis and computation of some tumor growth models with nutrient: from cell density models to free boundary dynamics
In this paper, we study the tumor growth equation along with various models
for the nutrient component, including the \emph{in vitro} model and the
\emph{in vivo} model. At the cell density level, the spatial availability of
the tumor density is governed by the Darcy law via the pressure
. For finite , we prove some a priori estimates of the
tumor growth model, such as boundedness of the nutrient density, and
non-negativity and growth estimate of the tumor density. As , the cell density models formally converge to Hele-Shaw flow models,
which determine the free boundary dynamics of the tumor tissue in the
incompressible limit. We derive several analytical solutions to the Hele-Shaw
flow models, which serve as benchmark solutions to the geometric motion of
tumor front propagation. Finally, we apply a conservative and positivity
preserving numerical scheme to the cell density models, with numerical results
verifying the link between cell density models and the free boundary dynamical
models
Throughput Optimizing Localized Link Scheduling for Multihop Wireless Networks Under Physical Interference Model
We study throughput-optimum localized link scheduling in wireless networks.
The majority of results on link scheduling assume binary interference models
that simplify interference constraints in actual wireless communication. While
the physical interference model reflects the physical reality more precisely,
the problem becomes notoriously harder under the physical interference model.
There have been just a few existing results on link scheduling under the
physical interference model, and even fewer on more practical distributed or
localized scheduling. In this paper, we tackle the challenges of localized link
scheduling posed by the complex physical interference constraints. By
cooperating the partition and shifting strategies into the pick-and-compare
scheme, we present a class of localized scheduling algorithms with provable
throughput guarantee subject to physical interference constraints. The
algorithm in the linear power setting is the first localized algorithm that
achieves at least a constant fraction of the optimal capacity region subject to
physical interference constraints. The algorithm in the uniform power setting
is the first localized algorithm with a logarithmic approximation ratio to the
optimal solution. Our extensive simulation results demonstrate correctness and
performance efficiency of our algorithms.Comment: A earlier work "Distributed Link Scheduling for Throughput
Maximization under Physical Interference Model" is presented in Proc. IEEE
Infocom 201
Molecular dynamics simulations with many-body potentials on multiple GPUs - the implementation, package and performance
Molecular dynamics (MD) is an important research tool extensively applied in
materials science. Running MD on a graphics processing unit (GPU) is an
attractive new approach for accelerating MD simulations. Currently, GPU
implementations of MD usually run in a one-host-process-one-GPU (OHPOG) scheme.
This scheme may pose a limitation on the system size that an implementation can
handle due to the small device memory relative to the host memory. In this
paper, we present a one-host-process-multiple-GPU (OHPMG) implementation of MD
with embedded-atom-model or semi-empirical tight-binding many-body potentials.
Because more device memory is available in an OHPMG process, the system size
that can be handled is increased to a few million or more atoms. In comparison
with the CPU implementation, in which Newton's third law is applied to improve
the computational efficiency, our OHPMG implementation has achieved a
28.9x~86.0x speedup in double precision, depending on the system size, the
cut-off ranges and the number of GPUs. The implementation can also handle a
group of small boxes in one run by combining the small boxes into a large box.
This approach greatly improves the GPU computing efficiency when a large number
of MD simulations for small boxes are needed for statistical purposes.Comment: 48 pages, 10 figure
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