Interferometry based on quantum Kibble-Zurek mechanism

We propose an interferometry within quantum Kibble-Zurek mechanism, which is exemplified by two prototypical quench schemes, namely the round-trip and quarter-turn ones, in the transverse Ising and quantum $XY$ chains. Each scheme contains two linear quenches that drive the system across the quantum critical point twice. The two linear quenches arouse two respective critical dynamics that are well described by the quantum Kibble-Zurek mechanism. However, in combination, the two critical dynamics can interfere with each other deeply. As an effect of the interference, the dynamical phase is exposed in the final excitation probability, which leads to a quantum coherent many-body oscillation in the density of defects with predictable characteristic period. Thus such an interference is available for direct experimental observations. In the quantum $XY$ model, we show that an interference can also arise from the interplay between two different critical dynamics derived from a critical point and a tricritical point. Furthermore, we demonstrate that the interference influences the dephasing of the excited quasiparticle modes intricately by disclosing a remarkable phenomenon of multiple length scales, diagonal and off-diagonal ones, in the defect-defect correlators. It turns out that the dephased result relies on how the diagonal and off-diagonal lengths are modulated by the controllable parameter in a quench scheme.Comment: 19 pages, 12 figures, with table of content

Varying quench dynamics: the Kibble-Zurek, saturated, and pre-saturated regimes

According to the Kibble-Zurek mechanism, there is a universal power-law relationship between the defect density and the quench rate during a slow linear quench through a critical point. It is generally accepted that a fast quench results in a deviation from the Kibble-Zurek scaling law and leads to the formation of a saturated plateau in the defect density. Our focus is on the transitions of quench dynamics as quench rates vary from slow to very fast limits. We identify a pre-saturated regime that lies between the saturated and Kibble-Zurek regimes. This conclusion is elucidated through the adiabatic-impulse approximation and verified by a rigorous analysis on the transverse Ising chain. As we approach the transition point from the saturated to pre-saturated regimes, we notice a change in scaling laws and, with an increase in the initial transverse field, a shrinking of the saturated regime until it disappears. During another transition from the Kibble-Zurek to pre-saturated regimes, we observe an attenuation of the dephasing effect and a change in the behavior of the kink-kink correlation function from a Gaussian decay to an exponential decay. Finally, the coherent many-body oscillation after quench is investigated, which shows different behaviors in the three regimes and demonstrates a significant transition of scaling behavior between the S and PS regimes.Comment: 11 pages, 7 figure

A multi-wavelength observation and investigation of six infrared dark clouds

Context. Infrared dark clouds (IRDCs) are ubiquitous in the Milky Way, yet they play a crucial role in breeding newly-formed stars. Aims. With the aim of further understanding the dynamics, chemistry, and evolution of IRDCs, we carried out multi-wavelength observations on a small sample. Methods. We performed new observations with the IRAM 30 m and CSO 10.4 m telescopes, with tracers ${\rm HCO^+}$, HCN, ${\rm N_2H^+}$, ${\rm C^{18}O}$, DCO$^+$, SiO, and DCN toward six IRDCs G031.97+00.07, G033.69-00.01, G034.43+00.24, G035.39-00.33, G038.95-00.47, and G053.11+00.05. Results. We investigated 44 cores including 37 cores reported in previous work and seven newly-identified cores. Toward the dense cores, we detected 6 DCO$^+$, and 5 DCN lines. Using pixel-by-pixel spectral energy distribution (SED) fits of the $\textit{Herschel}$ 70 to 500 $\mu$m, we obtained dust temperature and column density distributions of the IRDCs. We found that ${\rm N_2H^+}$ emission has a strong correlation with the dust temperature and column density distributions, while ${\rm C^{18}O}$ showed the weakest correlation. It is suggested that ${\rm N_2H^+}$ is indeed a good tracer in very dense conditions, but ${\rm C^{18}O}$ is an unreliable one, as it has a relatively low critical density and is vulnerable to freezing-out onto the surface of cold dust grains. The dynamics within IRDCs are active, with infall, outflow, and collapse; the spectra are abundant especially in deuterium species. Conclusions. We observe many blueshifted and redshifted profiles, respectively, with ${\rm HCO^+}$ and ${\rm C^{18}O}$ toward the same core. This case can be well explained by model "envelope expansion with core collapse (EECC)".Comment: 24 pages, 11 figures, 4 tables. To be published in A&A. The resolutions of the pictures are cut dow

Online Job Scheduling in Distributed Machine Learning Clusters

Nowadays large-scale distributed machine learning systems have been deployed to support various analytics and intelligence services in IT firms. To train a large dataset and derive the prediction/inference model, e.g., a deep neural network, multiple workers are run in parallel to train partitions of the input dataset, and update shared model parameters. In a shared cluster handling multiple training jobs, a fundamental issue is how to efficiently schedule jobs and set the number of concurrent workers to run for each job, such that server resources are maximally utilized and model training can be completed in time. Targeting a distributed machine learning system using the parameter server framework, we design an online algorithm for scheduling the arriving jobs and deciding the adjusted numbers of concurrent workers and parameter servers for each job over its course, to maximize overall utility of all jobs, contingent on their completion times. Our online algorithm design utilizes a primal-dual framework coupled with efficient dual subroutines, achieving good long-term performance guarantees with polynomial time complexity. Practical effectiveness of the online algorithm is evaluated using trace-driven simulation and testbed experiments, which demonstrate its outperformance as compared to commonly adopted scheduling algorithms in today's cloud systems

Composite Differential Evolution for Constrained Evolutionary Optimization

When solving constrained optimization problems (COPs) by evolutionary algorithms, the search algorithm plays a crucial role. In general, we expect that the search algorithm has the capability to balance not only diversity and convergence but also constraints and objective function during the evolution. For this purpose, this paper proposes a composite differential evolution (DE) for constrained optimization, which includes three different trial vector generation strategies with distinct advantages. In order to strike a balance between diversity and convergence, one of these three trial vector generation strategies is able to increase diversity, and the other two exhibit the property of convergence. In addition, to accomplish the tradeoff between constraints and objective function, one of the two trial vector generation strategies for convergence is guided by the individual with the least degree of constraint violation in the population, and the other is guided by the individual with the best objective function value in the population. After producing offspring by the proposed composite DE, the feasibility rule and the ϵ constrained method are combined elaborately for selection in this paper. Moreover, a restart scheme is proposed to help the population jump out of a local optimum in the infeasible region for some extremely complicated COPs. By assembling the above techniques together, a constrained composite DE is proposed. The experiments on two sets of benchmark test functions with various features, i.e., 24 test functions from IEEE CEC2006 and 18 test functions with 10 dimensions and 30 dimensions from IEEE CEC2010, have demonstrated that the proposed method shows better or at least competitive performance against other state-of-the-art methods