Universal quantum gates between nitrogen-vacancy centers in a levitated nanodiamond

We propose a scheme to realize universal quantum gates between nitrogen-vacancy (NV) centers in an optically trapped nanodiamond, through uniform magnetic field induced coupling between the NV centers and the torsional mode of the levitated nanodiamond. The gates are tolerant to the thermal noise of the torsional mode. By combining the scheme with dynamical decoupling technology, it is found that the high fidelity quantum gates are possible for the present experimental conditions. The proposed scheme is useful for NV-center-based quantum network and distributed quantum computationComment: 7 pages, 6 figure

Leveraging Interactions for Stationary and Dynamic Financial Distress Prediction: A Spatio-Temporal Financial Graph Attention Network

Financial distress prediction is a prominent research topic in information systems, with two primary modelling categories: stationary and dynamic modelling. Recent stationary modelling works have leveraged company interactions to improve prediction performance, considering the heterogeneity of interactions while ignoring the dynamicity. However, few dynamic modelling works utilized interactions. To address the inconsistency and limitation of stationary and dynamic modelling works in leveraging interactions, we propose the Spatio-Temporal Financial Graph Attention Network with Meta-learning (STFGAN-Meta). STFGAN-Meta leverages interactions\u27 spatial heterogeneity via the Spatial Aggregation module and temporal dynamicity via the Temporal Aggregation module. STFGAN-Meta introduces the Meta-learning Optimization module to unify stationary and dynamic modelling. Our experimental evaluation demonstrates that leveraging dynamicity and heterogeneity of interactions outperforms leveraging dynamicity or heterogeneity alone. Meta-learning succeeds in providing a generalized approach between stationary and dynamic modelling. STFGAN-Meta can be a promising risk assessment and decision-making tool in the financial industry

Properties of the scalar mesons f0(1370)f_0(1370), f0(1500)f_0(1500) and f0(1710)f_0(1710)

In the three-state mixing framework, considering the possible glueball components of $\eta$ and $\eta^\prime$, we investigate the hadronic decays of $f_0(1370)$, $f_0(1500)$ and $f_0(1710)$ into two pseudoscalar mesons. The quarkonia-glueball content of the three states is determined from the fit to the new data presented by the WA102 Collaboration. We find that these data are insensitive to the possible glueball components of $\eta$ and $\eta^\prime$. Furthermore, we discuss some properties of the mass matrix describing the mixing of the isoscalar scalar mesons.Comment: Latex 14 pages including 1 eps figur

Building a Data Infrastructure to Study Local Availability in Childcare for Children of Immigrant and U.S.-Born Parents: A Conditional Logit Model Analysis

In the United States, children of immigrants are more likely to start school at an academic disadvantage when compared to their peers with U.S.-born parents (Crosnoe, 2007; Han, 2008; Magnuson, Lahaie, & Waldfogel, 2006). It is possible that the disadvantage may be at least in part explained by differences in access to and use of high-quality childcare opportunities prior to the Kindergarten year. Indeed, while research has pointed to the benefits associated with high-quality early childhood education and public investments in expanding preschool enrollment, the children of immigrants continue to enroll in center-based care at lower rates compared to the children of U.S.-born parents (Brandon, 2004; Kahn & Greenberg, 2010; Karoly & Gonzalez, 2011; Takanishi, 2004). This study seeks to understand whether and how the supply of childcare services available in a neighborhood and other contextual factors contribute to differences in early education experiences by parental immigration status. Building a first of its kind dataset, I combined data from the Early Childhood Longitudinal Study, the Common Core of Data, the Early Childhood Learning and Knowledge Center Head Start Data Project, the Homeland Infrastructure Foundation-Level Data, and the U.S. Census Bureau to examine whether and how childcare supply affects childcare use between immigrant and U.S.-born parents. Using a conditional logit model, I find that the supply of childcare centers, Head Start, and state pre-K programs differs between children of immigrant and U.S.-born parents, and the supply of childcare centers, in particular, had differential effects on center enrollment by parental immigration status. Having at least one immigrant parent negatively impacted the odds of center participation, and, even having more access to childcare centers could not offset its negative effect. Implications of these findings and recommendations to improve the overall data quality are discussed.Doctor of Philosoph

Nonadiabatic dynamics and geometric phase of an ultrafast rotating electron spin

The spin in a rotating frame has attracted a lot of attentions recently, as it deeply relates to both fundamental physics such as pseudo-magnetic field and geometric phase, and applications such as gyroscopic sensors. However, previous studies only focused on adiabatic limit, where the rotating frequency is much smaller than the spin frequency. Here we propose to use a levitated nano-diamond with a built-in nitrogen-vacancy (NV) center to study the dynamics and the geometric phase of a rotating electron spin without adiabatic approximation. We find that the transition between the spin levels appears when the rotating frequency is comparable to the spin frequency at zero magnetic field. Then we use Floquet theory to numerically solve the spin energy spectrum, study the spin dynamics and calculate the geometric phase under a finite magnetic field, where the rotating frequency to fulfill the resonant transition condition could be greatly reduced.Comment: 6+2 pages, 3+1 figure

Improving Image Restoration with Soft-Rounding

Several important classes of images such as text, barcode and pattern images have the property that pixels can only take a distinct subset of values. This knowledge can benefit the restoration of such images, but it has not been widely considered in current restoration methods. In this work, we describe an effective and efficient approach to incorporate the knowledge of distinct pixel values of the pristine images into the general regularized least squares restoration framework. We introduce a new regularizer that attains zero at the designated pixel values and becomes a quadratic penalty function in the intervals between them. When incorporated into the regularized least squares restoration framework, this regularizer leads to a simple and efficient step that resembles and extends the rounding operation, which we term as soft-rounding. We apply the soft-rounding enhanced solution to the restoration of binary text/barcode images and pattern images with multiple distinct pixel values. Experimental results show that soft-rounding enhanced restoration methods achieve significant improvement in both visual quality and quantitative measures (PSNR and SSIM). Furthermore, we show that this regularizer can also benefit the restoration of general natural images.Comment: 9 pages, 6 figure