Direct frequency-comb spectroscopy of 6S1/26S_{1/2}-8S1/28S_{1/2} transitions of atomic cesium

Direct frequency-comb spectroscopy is used to probe the absolute frequencies of $6S_{1/2}$-$8S_{1/2}$ two-photon transitions of atomic cesium in hot vapor environment. By utilizing the coherent control method of temporally splitting the laser spectrum above and below the two-photon resonance frequency, Doppler-free absorption is built in two spatially distinct locations and imaged for high-precision spectroscopy. Theoretical analysis finds that these transition lines are measured with uncertainty below $5\times10^{-10}$, mainly contributed from laser-induced AC Stark shift.Comment: 4 pages, 3 figure

Defect-free atomic array formation using Hungarian matching algorithm

Deterministic loading of single atoms onto arbitrary two-dimensional lattice points has recently been demonstrated, where by dynamically controlling the optical-dipole potential, atoms from a probabilistically loaded lattice were relocated to target lattice points to form a zero-entropy atomic lattice. In this atom rearrangement, how to pair atoms with the target sites is a combinatorial optimization problem: brute-force methods search all possible combinations so the process is slow, while heuristic methods are time-efficient but optimal solutions are not guaranteed. Here, we use the Hungarian matching algorithm as a fast and rigorous alternative to this problem of defect-free atomic lattice formation. Our approach utilizes an optimization cost function that restricts collision-free guiding paths so that atom loss due to collision is minimized during rearrangement. Experiments were performed with cold rubidium atoms that were trapped and guided with holographically controlled optical-dipole traps. The result of atom relocation from a partially filled 7-by-7 lattice to a 3-by-3 target lattice strongly agrees with the theoretical analysis: using the Hungarian algorithm minimizes the collisional and trespassing paths and results in improved performance, with over 50\% higher success probability than the heuristic shortest-move method.Comment: 7 pages, 6 figure

Coherent Control of Resonant Two-Photon Transitions by Counter-Propagating Ultrashort Pulse Pairs

We describe optimized coherent control methods for two-photon transitions in atoms of a ladder-type three-state energy configuration. Our approach is based on the spatial coherent control scheme which utilizes counter-propagating ultrashort laser pulses to produce complex excitation patterns in an extended space. Since coherent control requires constructive interference of constituent transition pathways, applying it to an atomic transition with a specific energy configuration requires specially designed laser pulses. Here, we show, in an experimental demonstration, that the two-photon transition with an intermediate resonant energy state can be coherently controlled and retrieved out from the resonance-induced background, when phase-flipping of the laser spectrum near the resonant intermediate transition is used. A simple reason for this behavior is the fact that the transition amplitude function (to be added to give an overall two-photon transition) changes its sign at the intermediate resonant frequency, thus, by a proper spectral-phase programming, the excitation patterns (or the position-dependent interference of the transition given as a consequence of the spatial coherent control) are well isolated in space along the focal region of the counter-propagating pulses.Comment: 6 pages, 5 figure

Fast Signal Separation of 2D Sparse Mixture via Approximate Message-Passing

Approximate message-passing (AMP) method is a simple and efficient framework for the linear inverse problems. In this letter, we propose a faster AMP to solve the \emph{$L_1$-Split-Analysis} for the 2D sparsity separation, which is referred to as \emph{MixAMP}. We develop the MixAMP based on the factor graphical modeling and the min-sum message-passing. Then, we examine MixAMP for two types of the sparsity separation: separation of the direct-and-group sparsity, and that of the direct-and-finite-difference sparsity. This case study shows that the MixAMP method offers computational advantages over the conventional first-order method, TFOCS.Comment: five figure

Building a Dynamic Model of Entrepreneurial Intention Formation in Sharing Economy Platform: The Resource-Based Theory Approach

Although traditional entrepreneurship has long been acknowledged as a driving force of economic development and employment, the emergence of the Internet and the development of mobile devices provide a new paradigm of business economy called sharing economy. Peer-to-peer sharing economy platform contributes to the generation of a new form of entrepreneurship, which allows entrepreneurs to supply and exchange resources, products, and services with customers for profit. Despite such contributions, few researchers investigate entrepreneurship in sharing economy and identify the difference between entrepreneurship in traditional businesses and on the sharing economy platform. This study primarily aims to explore the context of entrepreneurial intention on the sharing economy platform. The resource-based approach (Connor, 1991; Rumelt, 1987) is employed to demonstrate how different capital resources influence the self-perception of future entrepreneurs and their attitude toward an entrepreneurial venture on the sharing economy platform. To realize the main aim of this study, a new scale is developed to precisely reflect the essential resources in an entrepreneurial venture on the sharing economy platform. In study I, a new scale of entrepreneurial capital is developed from a qualitative approach of item generation. A 24-item entrepreneurial capital scale with four dimensions (financial, social, intellectual, and human capital) is produced. For the subsequent scale purification, a quantitative approach is employed, and 150 responses are analyzed using exploratory factor analysis and confirmatory factor analysis. Four capital resources are classified under the second-order factor model with one second-order factor (entrepreneurial capitals) and four capital sub-constructs. Study II aims to validate the scale developed in study I and generate a structural model describing the relationships between (1) entrepreneurial capital and perception and (2) perception and intention. To validate the scale of entrepreneurial capital on the sharing economy platform, 308 responses are analyzed to acquire the best measurement model of perception and test the research hypotheses using structural equation modeling. Seventeen items of entrepreneurial capital are validated. Eleven items loaded on to three first-order factors (feasibility, desirability, and propensity) that contributed to one second-order factor (perception) are also supported. Finally, two hypotheses regarding the relationship among entrepreneurial capital, perception, and entrepreneurship intention are tested and supported. Entrepreneurial capital resources significantly affect the perception of individuals toward an entrepreneurial venture on the sharing economy platform. Perception also leads to overall entrepreneurship intention. This study develops a new scale of entrepreneurial capital and an original measurement model of perception toward an entrepreneurial venture on the sharing economy platform. Comprehensive understanding enables this research to confirm the holistic model of entrepreneurship intention formation on the sharing economy platform. This study contributes to the body of literature regarding entrepreneurship, sharing economy, and the hospitality industry by significantly elaborating entrepreneurial intention in the context of the new economic platform. This study also benefits practitioners and educators by assessing and guiding capital resources in a business venture on the sharing economy platform

In vitro single vesicle fusion study of Ca2+-triggered SNARE-mediated membrane fusion

SNARE-mediated Ca2+ triggered membrane fusion is essential for neuronal communication. The speed at which this process is orchestrated is further emphasized because it serves as a temporal limit for cognitive and physical activities. However, attempts to recapitulate SNARE-mediated membrane fusion with SNAREs and synaptotagmin 1 (Syt1) between two single proteoliposomes came short in respect to Ca2+ sensitivity, speed and fusion efficiency compared to in vivo observations. This discrepancy raises concerns if there are some critical protein machinery that are missing or if the topology of the proteoliposome fusion assay does not faithfully represent synaptic vesicle and plasma membrane. Some suspect that the discrepancy might be due to the tight membrane curvature of proteoliposomes which may not mimic the relaxed curvature of the plasma membrane well. Others wonder if our long-standing dogma that SNAREs are the core membrane fusion machinery is valid. In this study we investigate the role of complexin (Cpx) in a well-defined in vitro environment. Specifically, we observed Ca2+-triggered SNARE-mediated content-mixing between two proteoliposome pairs with total internal reflection (TIR) microscopy. We find that Cpx enhances Ca2+-triggered vesicle fusion with the yield changing from approximately 10% to 70% upon increasing Cpx from 0 to 100 nM. Unexpectedly, however, the fusion efficiency becomes reduced when Cpx is increased further, dropping to 20% in the µM range, revealing a bell-shaped dose-response curve. With our Cpx assisted in vitro single vesicle-to-vesicle fusion assay which has high efficiency and physiologically relevant Ca2+ sensitivity, we investigated the inhibitory of effects botulinum toxins (BoNT) A and E. BoNT A and E both block neurotransmitter release by specifically cleaving the C-terminal ends of SNAP-25, a plasma membrane SNARE protein. Here, we find that SNAP-25A and E, the cleavage products of BoNT A and E respectively, terminate membrane fusion via completely different mechanisms. Specifically, SNAP-25E halts membrane fusion prior to the docking stage due to its incapability to support SNARE pairing. In contrast, SNAP-25A leads the fusion pathway faithfully prior to the fusion pore opening. The EPR results show that the discrepancy between SNAP-25A and E might stem from the extent of the dynamic destabilization of the t-SNARE core at the N-terminal half which plays a pivotal role in nucleating SNARE complex formation. Thus, the results provide insights into the structure and dynamics-based mechanism whereby BoNT A and E impairs membrane fusion. While we observed the increase of Ca2+ sensitivity and fusion probability by incorporating Cpx into the in vitro single vesicle-to-vesicle fusion assay, we still were not able to observe fast synchronous fusion. Thus, we expand our investigation and probe the proteoliposome-to-supported bilayer fusion assay. We find that SNAREs, Syt1 and Ca2+ together can elicit more than a 50-fold increase in the number of membrane fusion events. What is more remarkable is that the docking-to-fusion delay of ~55% of all vesicle fusion occurs resides within 20 msec. Furthermore, Syt1 binding to t-SNAREs prior to Ca2+ inhibits spontaneous fusion leading to a loss of subsequent Ca2+ response. Thus, we propose a productive and non-productive pathway for Syt1 in which pre-binding of Ca2+ may be required for the productive pathway. We believe that the improved membrane fusion assay provides unprecedented opportunities to test the mechanistic models for Ca2+-triggered exocytosis in a time scale ever closer to the natural one

On Detection-Directed Estimation Approach for Noisy Compressive Sensing

In this paper, we investigate a Bayesian sparse reconstruction algorithm called compressive sensing via Bayesian support detection (CS-BSD). This algorithm is quite robust against measurement noise and achieves the performance of a minimum mean square error (MMSE) estimator that has support knowledge beyond a certain SNR threshold. The key idea behind CS-BSD is that reconstruction takes a detection-directed estimation structure consisting of two parts: support detection and signal value estimation. Belief propagation (BP) and a Bayesian hypothesis test perform support detection, and an MMSE estimator finds the signal values belonging to the support set. CS-BSD converges faster than other BP-based algorithms, and it can be converted to a parallel architecture to become much faster. Numerical results are provided to verify the superiority of CS-BSD compared to recent algorithms.Comment: 22 pages, 7 figures, 1 table, 1 algorithm tabl

Ultrafast Rabi oscillation of a Gaussian atom ensemble

We investigate Rabi oscillation of an atom ensemble in Gaussian spatial distribution. By using the ultrafast laser interaction with the cold atomic rubidium vapor spatially confined in a magneto-optical trap, the oscillatory behavior of the atom excitation is probed as a function of the laser pulse power. Theoretical model calculation predicts that the oscillation peaks of the ensemble-atom Rabi flopping fall on the simple Rabi oscillation curve of a single atom and the experimental result shows good agreement with the prediction. We also test the the three-pulse composite interaction $R_x(\pi/2)R_y(\pi)R_x(\pi/2)$ to develop a robust method to achieve a higher fidelity population inversion of the atom ensemble.Comment: 5 pages, 4 figure

Detection-Directed Sparse Estimation using Bayesian Hypothesis Test and Belief Propagation

In this paper, we propose a sparse recovery algorithm called detection-directed (DD) sparse estimation using Bayesian hypothesis test (BHT) and belief propagation (BP). In this framework, we consider the use of sparse-binary sensing matrices which has the tree-like property and the sampled-message approach for the implementation of BP. The key idea behind the proposed algorithm is that the recovery takes DD-estimation structure consisting of two parts: support detection and signal value estimation. BP and BHT perform the support detection, and an MMSE estimator finds the signal values using the detected support set. The proposed algorithm provides noise-robustness against measurement noise beyond the conventional MAP approach, as well as a solution to remove quantization effect by the sampled-message based BP independently of memory size for the message sampling. We explain how the proposed algorithm can have the aforementioned characteristics via exemplary discussion. In addition, our experiments validate such superiority of the proposed algorithm, compared to recent algorithms under noisy setup. Interestingly the experimental results show that performance of the proposed algorithm approaches that of the oracle estimator as SNR becomes higher

An iALM-ICA-based Anti-Jamming DS-CDMA Receiver for LMS Systems

We consider a land mobile satellite communication system using spread spectrum techniques where the uplink is exposed to MT jamming attacks, and the downlink is corrupted by multi-path fading channels. We proposes an anti-jamming receiver, which exploits inherent low-dimensionality of the received signal model, by formulating a robust principal component analysis (Robust PCA)-based recovery problem. Simulation results verify that the proposed receiver outperforms the conventional receiver for a reasonable rank of the jamming signal.Comment: IEEE Transactions on Aerospace and Electric Systems, "accepted