18,569 research outputs found
Distributed Adaptive Gradient Optimization Algorithm
In this paper, a distributed optimization problem with general differentiable
convex objective functions is studied for single-integrator and
double-integrator multi-agent systems. Two distributed adaptive optimization
algorithm is introduced which uses the relative information to construct the
gain of the interaction term. The analysis is performed based on the Lyapunov
functions, the analysis of the system solution and the convexity of the local
objective functions. It is shown that if the gradients of the convex objective
functions are continuous, the team convex objective function can be minimized
as time evolves for both single-integrator and double-integrator multi-agent
systems. Numerical examples are included to show the obtained theoretical
results.Comment: 12 pages, 3 figure
BFDA: A Matlab Toolbox for Bayesian Functional Data Analysis
We provide a MATLAB toolbox, BFDA, that implements a Bayesian hierarchical
model to smooth multiple functional data with the assumptions of the same
underlying Gaussian process distribution, a Gaussian process prior for the mean
function, and an Inverse-Wishart process prior for the covariance function.
This model-based approach can borrow strength from all functional data to
increase the smoothing accuracy, as well as estimate the mean-covariance
functions simultaneously. An option of approximating the Bayesian inference
process using cubic B-spline basis functions is integrated in BFDA, which
allows for efficiently dealing with high-dimensional functional data. Examples
of using BFDA in various scenarios and conducting follow-up functional
regression are provided. The advantages of BFDA include: (1) Simultaneously
smooths multiple functional data and estimates the mean-covariance functions in
a nonparametric way; (2) flexibly deals with sparse and high-dimensional
functional data with stationary and nonstationary covariance functions, and
without the requirement of common observation grids; (3) provides accurately
smoothed functional data for follow-up analysis.Comment: A tool paper submitted to the Journal of Statistical Softwar
Control of Spin-Exchange Interaction between Alkali-Earth Atoms via Confinement-Induced Resonances in a Quasi 1+0 Dimensional System
A nuclear-spin exchange interaction exists between two ultracold fermionic
alkali-earth (like) atoms in the electronic state (-state)
and state (-state), and is an essential ingredient for the
quantum simulation of Kondo effect. We study the control of this spin-exchange
interaction for two atoms simultaneously confined in a quasi-one-dimensional
(quasi-1D) tube, where the -atom is freely moving in the axial direction
while the -atom is further localized by an additional axial trap and behaves
as a quasi-zero-dimensional (quasi-0D) impurity. In this system, the two atoms
experience effective-1D spin-exchange interactions in both even and odd partial
wave channels, whose intensities can be controlled by the characteristic
lengths of the confinements via the confinement-induced-resonances (CIRs). In
current work, we go beyond that pure-1D approximation. We model the transverse
and axial confinements by harmonic traps with finite characteristic lengths
and , respectively, and exactly solve the "quasi-1D + quasi-0D"
scattering problem between these two atoms. Using the solutions we derive the
effective 1D spin-exchange interaction and investigate the locations and widths
of the even/odd wave CIRs for our system.
It is found that when the ratio is larger, the CIRs can be
induced by weaker confinements, which are easier to be realized experimentally.
The comparison between our results and the recent experiment shows that the
two experimentally observed resonance branches of the spin-exchange effect are
due to an even-wave CIR and an odd-wave CIR, respectively. Our results are
advantageous for the control and description of either the effective
spin-exchange interaction or other types of interactions between ultracold
atoms in quasi 1+0 dimensional systems.Comment: 14 pages, 3 figures. Compare to previous version, we did a major
revision in current versio
Distributed Subgradient-based Multi-agent Optimization with More General Step Sizes
A wider selection of step sizes is explored for the distributed subgradient
algorithm for multi-agent optimization problems, for both time-invariant and
time-varying communication topologies. The square summable requirement of the
step sizes commonly adopted in the literature is removed. The step sizes are
only required to be positive, vanishing and non-summable. It is proved that in
both unconstrained and constrained optimization problems, the agents' estimates
reach consensus and converge to the optimal solution with the more general
choice of step sizes. The idea is to show that a weighted average of the
agents' estimates approaches the optimal solution, but with different
approaches. In the unconstrained case, the optimal convergence of the weighted
average of the agents' estimates is proved by analyzing the distance change
from the weighted average to the optimal solution and showing that the weighted
average is arbitrarily close to the optimal solution. In the constrained case,
this is achieved by analyzing the distance change from the agents' estimates to
the optimal solution and utilizing the boundedness of the constraints. Then the
optimal convergence of the agents' estimates follows because consensus is
reached in both cases. These results are valid for both a strongly connected
time-invariant graph and time-varying balanced graphs that are jointly strongly
connected
A Novel Carrier Waveform Inter-Displacement Modulation Method in Underwater Communication Channel
As the main way of underwater wireless communication, underwater acoustic
communication is one of the focuses of ocean research. Compared with the free
space wireless communication channel, the underwater acoustic channel suffers
from more severe multipath effect, the less available bandwidth and the even
complex noise. The underwater acoustic channel is one of the most complicated
wireless communication channels. To achieve a reliable underwater acoustic
communication, Phase Shift Keying (PSK) modulation and Passive Time Reversal
Mirror (PTRM) equalization are considered to be a suitable scheme. However, due
to the serious distortion of the received signal caused by the channel, this
scheme suffers from a high Bit Error Rate (BER) under the condition of the low
Signal to Noise Ratio (SNR). To solve this problem, we proposes a Carrier
Waveform Inter-Displacement (CWID) modulation method based on the Linear
Frequency Modulation (LFM) PSK and PTRM scheme. The new communication scheme
reduces BER by increasing the difference from the carrier waveform for
different symbols. Simulation results show the effectiveness and superiority of
the proposed method.Comment: 8 pages, 11 figure
Quantum Defect Theory for Orbital Feshbach Resonance
In the ultracold gases of alkali-earth (like) atoms, a new type of Feshbach
resonance, i.e., the orbital Feshbach resonance (OFR), has been proposed and
experimentally observed in ultracold Yb atoms. When the OFR of the
Yb atoms occurs, the energy gap between the open and closed channels is
smaller by two orders of magnitudes than the van der Waals energy. As a result,
quantitative accurate results for the low-energy two-body problems can be
obtained via multi-channel quantum defect theory (MQDT), which is based on the
exact solution of the Schrdinger equation with the van der
Waals potential. In this paper we use the MQDT to calculate the two-atom
scattering length, effective range, and the binding energy of two-body bound
states for the systems with OFR. With these results we further study the
clock-transition spectrum for the two-body bound states, which can be used to
experimentally measure the binding energy. Our results are helpful for the
quantitative theoretical and experimental researches for the ultracold gases of
alkali-earth (like) atoms with OFR.Comment: 11 pages, 6 figuer
Realized volatility and parametric estimation of Heston SDEs
We present a detailed analysis of \emph{observable} moments based parameter
estimators for the Heston SDEs jointly driving the rate of returns and
the squared volatilities . Since volatilities are not directly observable,
our parameter estimators are constructed from empirical moments of realized
volatilities , which are of course observable. Realized volatilities are
computed over sliding windows of size , partitioned into
intervals. We establish criteria for the joint selection of
and of the sub-sampling frequency of return rates data.
We obtain explicit bounds for the speed of convergence of realized
volatilities to true volatilities as . In turn, these bounds
provide also speeds of convergence of our observable estimators for the
parameters of the Heston volatility SDE.
Our theoretical analysis is supplemented by extensive numerical simulations
of joint Heston SDEs to investigate the actual performances of our moments
based parameter estimators. Our results provide practical guidelines for
adequately fitting Heston SDEs parameters to observed stock prices series
Parametric Estimation from Approximate Data: Non-Gaussian Diffusions
We study the problem of parameters estimation in Indirect Observability
contexts, where is an unobservable stationary process
parametrized by a vector of unknown parameters and all observable data are
generated by an approximating process which is close to
in norm. We construct consistent parameter estimators which are
smooth functions of the sub-sampled empirical mean and empirical lagged
covariance matrices computed from the observable data. We derive explicit
optimal sub-sampling schemes specifying the best paired choices of sub-sampling
time-step and number of observations. We show that these choices ensure that
our parameter estimators reach optimized asymptotic -convergence rates,
which are constant multiples of the norm
Orbital Feshbach Resonance with Small Energy Gap between Open and Closed Channels
Recently a new type of Feshbach resonance, i.e., orbital Feshbach resonance
(OFR) was proposed for the ultracold alkali-earth (like) atoms, and
experimentally observed in the ultracold gases of Yb atoms.
Unlike most of the magnetic Feshbach resonances of ultracold alkali atoms, when
the OFR of Yb atoms appears, the energy gap between the
thresholds of the open channel (OC) and the closed channel (CC) is much smaller
than the characteristic energy of the inter-atomic interaction, i.e., the van
der Waals energy. In this paper we study the OFR in the systems with small
CC-OC threshold gap. We show that in these systems the OFR can be induced by
the coupling between the OC and either an isolated bound state of the CC or the
scattering states of the CC. Moreover, we also show that in each case the
two-channel Huang-Yang pesudopoential is always applicable for the approximate
calculation of the low-energy scattering amplitude. Our results imply that in
the theoretical calculations for these systems it is appropriate to take into
account the contributions from the scattering states of the CC
Effect of different filling tendencies on the spatial quantum Zeno effect
The quantum Zeno effect is deeply related to the quantum measurement process
and thus studies of it may help shed light on the hitherto mysterious
measurement process in quantum mechanics. Recently, the spatial quantum Zeno
effect is observed in a Bose-Einstein condensate depleted by an electron beam.
We theoretically investigate how different intrinsic tendencies of filling
affect the quantum Zeno effect in this system by changing the impinging point
of the electron beam along the inhomogeneous condensate. Surprisingly, we find
no visible effect on the critical dissipation intensity at which the quantum
Zeno effect appear. Our finding shows the recent capability of combining the
Bose-Einstein condensate with an electron beam offers a great opportunity for
studying the spatial quantum Zeno effect, and more generally the dynamics of a
quantum many-body system out of equilibrium
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