arXiv subjects

Tao Chen

Publications and source records attributed to Tao Chen.

At least 523 records · Page 29Linked to original sources

arXiv2018

Characterization of the stimulated excitation in a driven Bose-Einstein condensate

We apply the time-dependent generalized Hartree-Fock-Bogoliubov (td-GHFB) theory to describe the stimulated excitation driven by periodically modulating the interactions in a Bose-Einstein condensate (BEC). A comparison with the results calculated from the typical Bogoliubov approximation indicates that the additional interaction terms contributed by the excited modes play a significant role to explain the dynamics of the stimulating process. The td-GHFB model has not only painted a clear picture of the density wave propagation, but also partly explained the generation of the second order harmonic of the excited modes. The theoretical framework can be directly employed to study similar driven processes.

physics.atom-ph↗

arXiv2018

Fully anharmonic infrared cascade spectra of polycyclic aromatic hydrocarbons

The infrared (IR) emission of polycyclic aromatic hydrocarbons (PAHs) permeates our universe; astronomers have detected the IR signatures of PAHs around many interstellar objects. The IR emission of interstellar PAHs differs from their emission as seen under conditions on Earth, as they emit through a collisionless cascade down through their excited vibrational states from high internal energies. The difficulty in reproducing interstellar conditions in the laboratory results in a reliance on theoretical techniques. However, the size and complexity of PAHs requires careful consideration when producing the theoretical spectra. In this work we outline the theoretical methods necessary to lead to a fully theoretical IR cascade spectra of PAHs including: an anharmonic second order vibrational perturbation theory (VPT2) treatment; the inclusion of Fermi resonances through polyads; and the calculation of anharmonic temperature band shifts and broadenings (including resonances) through a Wang--Landau approach. We also suggest a simplified scheme to calculate vibrational emission spectra that retains the essential characteristics of the full IR cascade treatment and can directly transform low temperature absorption spectra in IR cascade spectra. Additionally we show that past astronomical models were in error in assuming a 15 cm$^{-1}$ correction was needed to account for anharmonic emission effects.

astro-ph.GA↗

arXiv2018

From planes to bowls: photodissociation of the bisanthenequinone cation

We present a combined experimental and theoretical study of the photodissociation of the bisanthenequinone (C28H12O2) cation, Bq+. The experiments show that, upon photolysis, the Bq+ cation does not dehydrogenate, but instead fragments through the sequential loss of the two neutral carbonyl groups, causing the formation of five-membered carbon cycles. Quantum chemical calculations confirm this Bq+ -> [Bq - CO]+ -> [Bq - 2CO]+ sequence as the energetically most favorable reaction pathway. For the first CO loss, a transition state with a barrier of ~3.2 eV is found, substantially lower than the lowest calculated H loss dissociation pathway (~ 4.9 eV). A similar situation applies for the second CO loss channel (~3.8 eV vs. ~4.7 eV), but where the first dissociation step does not strongly alter the planar PAH geometry, the second step transforms the molecule into a bowl-shaped one.

physics.atm-clus↗

arXiv2018

Anharmonicity and the infrared emission spectrum of highly excited PAHs

Aims. Infrared (IR) spectroscopy is a powerful tool to study molecules in space. A key issue in such analyses is understanding the effect that temperature and anharmonicity have on different vibrational bands, and thus interpreting the IR spectra for molecules under various conditions. Methods. We combined second order vibrational perturbation theory and the Wang-Landau random walk technique to produce accurate IR spectra of highly excited PAHs. We fully incorporated anharmonic effects, such as resonances, overtones, combination bands, and temperature effects. Results. The results are validated against experimental results for the pyrene molecule (C16H10). In terms of positions, widths, and relative intensities of the vibrational bands, our calculated spectra are in excellent agreement with gas-phase experimental data.

astro-ph.IM↗

arXiv2018

Laboratory photo-chemistry of pyrene clusters: an efficient way to form large PAHs

In this work, we study the photodissociation processes of small PAH clusters (e.g., pyrene clusters). The experiments are carried out using a quadrupole ion trap in combination with time-of-flight (QIT-TOF) mass spectrometry. The results show that pyrene clusters are converted into larger PAHs under the influence of a strong radiation field. Specifically, pyrene dimer cations (e.g., [C$_{16}$H$_{10}$$-$C$_{16}$H$_{9}$]$^+$ or C$_{32}$H$_{19}$$^+$), will photo-dehydrogenate and photo-isomerize to fully aromatic cations (PAHs) (e.g., C$_{32}$H$_{16}$$^+$) with laser irradiation. The structure of new formed PAHs and the dissociation energy for these reaction pathways are investigated with quantum chemical calculations. These studies provide a novel efficient evolution routes for the formation of large PAHs in the interstellar medium (ISM) in a bottom-up process that will counteract the top-down conversion of large PAHs into rings and chains, and provide a reservoir of large PAHs that can be converted into C$_{60}$ and other fullerenes and large carbon cages.

astro-ph.IM↗

arXiv2018

Single-loop realization of arbitrary non-adiabatic holonomic single-qubit quantum gates in a superconducting circuit

Geometric phases are noise-resilient, and thus provide a robust way towards high fidelity quantum manipulation. Here we experimentally demonstrate arbitrary non-adiabatic holonomic single-qubit quantum gates for both a superconducting transmon qubit and a microwave cavity in a single-loop way. In both cases, an auxiliary state is utilized, and two resonant microwave drives are simultaneously applied with well-controlled but varying amplitudes and phases for the arbitrariness of the gate. The resulting gates on the transmon qubit achieve a fidelity of 0.996 characterized by randomized benchmarking and the ones on the cavity show an averaged fidelity of 0.978 based on a full quantum process tomography. In principle, a nontrivial two-qubit holonomic gate between the qubit and the cavity can also be realized based on our presented experimental scheme. Our experiment thus paves the way towards practical non-adiabatic holonomic quantum manipulation with both qubits and cavities in a superconducting circuit.

quant-ph↗

arXiv2018

Cycle Doubling, Merging And Renormalization in the Tangent Family

In this paper we study the transition to chaos for the restriction to the real and imaginary axes of the tangent family $\{ T_t(z)=i t\tan z\}_{0< t\leq π}$. Because tangent maps have no critical points but have an essential singularity at infinity and two symmetric asymptotic values, there are new phenomena: as $t$ increases we find single instances of "period quadrupling", "period splitting" and standard "period doubling"; there follows a general pattern of "period merging" where two attracting cycles of period $2^n$ "merge" into one attracting cycle of period $2^{n+1}$, and "cycle doubling" where an attracting cycle of period $2^{n+1}$ "becomes" two attracting cycles of the same period. We use renormalization to prove the existence of these bifurcation parameters. The uniqueness of the cycle doubling and cycle merging parameters is quite subtle and requires a new approach. To prove the cycle doubling and merging parameters are, indeed, unique, we apply the concept of "holomorphic motions" to our context. In addition, we prove that there is an "infinitely renormalizable" tangent map $T_{t_\infty}$. It has no attracting or parabolic cycles. Instead, it has a strange attractor contained in the real and imaginary axes which is forward invariant and minimal under $T^2_{t_\infty}$. The intersection of this strange attractor with the real line consists of two binary Cantor sets and the intersection with the imaginary line is totally disconnected, perfect and unbounded.

math.DS↗

arXiv2018

Dynamics of Generalized Nevanlinna Functions

In the early 1980's, computers made it possible to observe that in complex dynamics, one often sees dynamical behavior reflected in parameter space and vice versa. This duality was first exploited by Douady, Hubbard and their students in early work on rational maps. See \cite{DH,BH} for example. Here, we continue to study these ideas in the realm of transcendental functions. In \cite{KK1}, it was shown that for the tangent family, $λ\tan z$, the way the hyperbolic components meet at a point where the asymptotic value eventually lands on infinity reflects the dynamic behavior of the functions at infinity. In the first part of this paper we show that this duality extends to a much more general class of transcendental meromorphic functions that we call {\em generalized Nevanlinna functions} with the additional property that infinity is not an asymptotic value. In particular, we show that in "dynamically natural" one dimensional slices of parameter space, there are "hyperbolic-like" components with a unique distinguished boundary point whose dynamics reflect the behavior inside an asymptotic tract at infinity. Our main result is that {\em every} parameter point in such a slice for which the asymptotic value eventually lands on a pole is such a distinguished boundary point. In the second part of the paper, we apply this result to the families $λ\tan^p z^q$, $p,q \in \mathbb Z^+$, to prove that all hyperbolic components of period greater than $1$ are bounded.

math.DS↗

arXiv2018

Fine-Grained Facial Expression Analysis Using Dimensional Emotion Model

Automated facial expression analysis has a variety of applications in human-computer interaction. Traditional methods mainly analyze prototypical facial expressions of no more than eight discrete emotions as a classification task. However, in practice, spontaneous facial expressions in naturalistic environment can represent not only a wide range of emotions, but also different intensities within an emotion family. In such situation, these methods are not reliable or adequate. In this paper, we propose to train deep convolutional neural networks (CNNs) to analyze facial expressions explainable in a dimensional emotion model. The proposed method accommodates not only a set of basic emotion expressions, but also a full range of other emotions and subtle emotion intensities that we both feel in ourselves and perceive in others in our daily life. Specifically, we first mapped facial expressions into dimensional measures so that we transformed facial expression analysis from a classification problem to a regression one. We then tested our CNN-based methods for facial expression regression and these methods demonstrated promising performance. Moreover, we improved our method by a bilinear pooling which encodes second-order statistics of features. We showed such bilinear-CNN models significantly outperformed their respective baselines.

cs.CV↗

arXiv2018

A Survey and Taxonomy of Self-Aware and Self-Adaptive Cloud Autoscaling Systems

Autoscaling system can reconfigure cloud-based services and applications, through various configurations of cloud software and provisions of hardware resources, to adapt to the changing environment at runtime. Such a behavior offers the foundation for achieving elasticity in modern cloud computing paradigm. Given the dynamic and uncertain nature of the shared cloud infrastructure, cloud autoscaling system has been engineered as one of the most complex, sophisticated and intelligent artifacts created by human, aiming to achieve self-aware, self-adaptive and dependable runtime scaling. Yet, existing Self-aware and Self-adaptive Cloud Autoscaling System (SSCAS) is not mature to a state that it can be reliably exploited in the cloud. In this article, we survey the state-of-the-art research studies on SSCAS and provide a comprehensive taxonomy for this field. We present detailed analysis of the results and provide insights on open challenges, as well as the promising directions that are worth investigated in the future work of this area of research. Our survey and taxonomy contribute to the fundamentals of engineering more intelligent autoscaling systems in the cloud.

cs.SE↗

arXiv2018

FEMOSAA: Feature Guided and Knee Driven Multi-Objective Optimization for Self-Adaptive Software

Self-adaptive software (SAS) can reconfigure itself to adapt to the changing environment at runtime, aiming for continually optimizing conflicted non-functional objectives, e.g., response time, energy consumption, throughput and cost etc. In this paper, we present Feature guided and knEe driven Multi-Objective optimization for Self-Adaptive softwAre (FEMOSAA), a novel framework that automatically synergizes the feature model and Multi-Objective Evolutionary Algorithm (MOEA), to optimize SAS at runtime. FEMOSAA operates in two phases: at design time, FEMOSAA automatically transposes the engineers' design of SAS, expressed as a feature model, to fit the MOEA, creating new chromosome representation and reproduction operators. At runtime, FEMOSAA utilizes the feature model as domain knowledge to guide the search and further extend the MOEA, providing a larger chance for finding better solutions. In addition, we have designed a new method to search for the knee solutions, which can achieve a balanced trade-off. We comprehensively evaluated FEMOSAA on two running SAS: one is a highly complex SAS with various adaptable real-world software under the realistic workload trace, another is a service-oriented SAS that can be dynamically composed from services. In particular, we compared the effectiveness and overhead of FEMOSAA against four of its variants and three other search-based frameworks for SAS under various scenarios, including three commonly applied MOEAs, two workload patterns and diverse conflicting quality objectives. The results reveal the effectiveness of FEMOSAA and its superiority over the others with high statistical significance and non-trivial effect sizes.

cs.SE↗

arXiv2018

Graph based Platform for Electricity Market Study, Education and Training

With the further development of deregulated electricity market in many other countries around the world, a lot of challenges have been identified for market data management, network topology processing and fast market-clearance mechanism design. In this paper, a graph computing framework based on TigerGraph database is proposed to solve a security constrained unit commitment (SCUC) and security constrained economic dispatch (SCED) problem, with parallelized graph power flow (PGPF) and innovative LU decomposition techniques, for electricity market-clearance. It also provides a comprehensive visualization platform to demonstrate the market clearing results vividly, such as locational marginal price (LMP), and is able to be utilized for electricity market operators' education and training purpose.

eess.SP↗

arXiv2018

NMR Evidence of Charge Fluctuations in Multiferroic CuBr2

We report combined magnetic susceptibility, dielectric constant, nuclear quadruple resonance (NQR) and zero-field nuclear magnetic resonance (NMR) measurements on single crystals of multiferroics CuBr$_2$. High quality of the sample is demonstrated by the sharp magnetic and magnetic-driven ferroelectric transition at $T_N=T_C\approx$ 74~K. The zero-field $^{79}$Br and $^{81}$Br NMR are resolved below $T_N$. The spin-lattice relaxation rates reveal charge fluctuations when cooled below 60~K. Evidences of an increase of NMR linewidth, a reduction of dielectric constant, and an increase of magnetic susceptibility are also seen at low temperatures. These data suggest an emergent instability which competes with the spiral magnetic ordering and the ferroelectricity. Candidate mechanisms are discussed based on the quasi-one-dimensional (1D) nature of the magnetic system.

cond-mat.str-el↗

arXiv2017

A Novel Consensus-based Distributed Algorithm for Economic Dispatch Based on Local Estimation of Power Mismatch

This paper proposes a novel consensus-based distributed control algorithm for solving the economic dispatch problem of distributed generators. A legacy central controller can be eliminated in order to avoid a single point of failure, relieve computational burden, maintain data privacy, and support plug-and-play functionalities. The optimal economic dispatch is achieved by allowing the iterative coordination of local agents (consumers and distributed generators). As coordination information, the local estimation of power mismatch is shared among distributed generators through communication networks and does not contain any private information, ultimately contributing to a fair electricity market. Additionally, the proposed distributed algorithm is particularly designed for easy implementation and configuration of a large number of agents in which the distributed decision making can be implemented in a simple proportional-integral (PI) or integral (I) controller. In MATLAB/Simulink simulation, the accuracy of the proposed distributed algorithm is demonstrated in a 29-node system in comparison with the centralized algorithm. Scalability and a fast convergence rate are also demonstrated in a 1400-node case study. Further, the experimental test demonstrates the practical performance of the proposed distributed algorithm using the VOLTTRON platform and a cluster of low-cost credit-card-size single-board PCs.

math.OC↗

arXiv2017

Radiative deflection of a BaF molecular beam from the optical cycling

We demonstrate a quasi optical cycling for the $X(v=0)\to A(v'=0)$ transition and a radiative force induced deflection on the buffer-gas cooled BaF molecular beam. The laser induced fluorescence enhancement with additional sidebands and a polarization modulation scheme indicates that the hyperfine states and the Zeeman sublevels are closed. The quasi optical cycling by repumping the $X(v=1)\to A(v'=0)$ leads to a $\sim$ 0.8 mm deflection of the beam via scattering $\sim$ 150 photons per molecule, in good agreement with the predictions from our multi-level rate equation model. Further improvement by closing the leakage $X(v=2)$ and $Δ$ state allows scattering thousands of photons, and laser cooling and slowing of BaF.

physics.atom-ph↗

arXiv2017

Recursive Construction of Confidence Regions

Assuming that one-step transition kernel of a discrete time, time-homogenous Markov chain model is parameterized by a parameter $θ\in \boldsymbol Θ$, we derive a recursive (in time) construction of confidence regions for the unknown parameter of interest, say $θ^*\in \boldsymbol Θ$. It is supposed that the observed data used in construction of the confidence regions is generated by a Markov chain whose transition kernel corresponds to $θ^*$ . The key step in our construction is derivation of a recursive scheme for an appropriate point estimator of $θ^*$. To achieve this, we start by what we call the base recursive point estimator, using which we design a quasi-asymptotically linear recursive point estimator (a concept introduced in this paper). For the latter estimator we prove its weak consistency and asymptotic normality. The recursive construction of confidence regions is needed not only for the purpose of speeding up the computation of the successive confidence regions, but, primarily, for the ability to apply the dynamic programming principle in the context of robust adaptive stochastic control methodology.

math.ST↗

arXiv2017

Adaptive Robust Control Under Model Uncertainty

In this paper we propose a new methodology for solving an uncertain stochastic Markovian control problem in discrete time. We call the proposed methodology the adaptive robust control. We demonstrate that the uncertain control problem under consideration can be solved in terms of associated adaptive robust Bellman equation. The success of our approach is to the great extend owed to the recursive methodology for construction of relevant confidence regions. We illustrate our methodology by considering an optimal portfolio allocation problem, and we compare results obtained using the adaptive robust control method with some other existing methods.

math.OC↗

arXiv2017

Control and Energy Management System in Microgrids

As a cutting-edge technology, microgrids feature intelligent EMSs and sophisticated control, which will dramatically change our energy infrastructure. The modern microgrids are a relatively recent development with high potential to bring distributed generation, DES devices, controllable loads, communication infrastructure, and many new technologies into the mainstream. As a more controllable and intelligent entity, a microgrid has more growth potential than ever before. However, there are still many open questions, such as the future business models and economics. What is the cost-benefit to the end-user? How should we systematically evaluate the potential benefits and costs of control and energy management in a microgrid?

eess.SY↗