Magnetic ordering of nitrogen-vacancy centers in diamond via resonator-mediated coupling

Nitrogen-vacancy centers in diamond, being a promising candidate for quantum information processing, may also be an ideal platform for simulating many-body physics. However, it is difficult to realize interactions between nitrogen-vacancy centers strong enough to form a macroscopically ordered phase under realistic temperatures. Here we propose a scheme to realize long-range ferromagnetic Ising interactions between distant nitrogen-vacancy centers by using a mechanical resonator as a medium. Since the critical temperature in the long-range Ising model is proportional to the number of spins, a ferromagnetic order can be formed at a temperature of tens of millikelvin for a sample with $\sim10^4$ nitrogen-vacancy centers. This method may provide a new platform for studying many-body physics using qubit systems.Comment: 5 pages, 4 figure

Empirical extinction coefficients for the GALEX, SDSS, 2MASS and WISE passbands

Using the "standard pair" technique of paring stars of almost nil and high extinction but otherwise of almost identical stellar parameters from the SDSS, and combing the SDSS, GALEX, 2MASS and WISE photometry ranging from the far UV to the mid-IR, we have measured dust reddening in the FUV-NUV, NUV-u, u-g, g-r, r-i, i-z, z-J, J-H, H-Ks, Ks-W1 and W1-W2 colors for thousands of Galactic stars. The measurements, together with the E(B-V) values given by Schlegel et al. (1998), allow us to derive the observed, model-free reddening coefficients for those colors. The results are compared with previous measurements and the predictions of a variety of Galactic reddening laws. We find that 1) The dust reddening map of Schlegel et al. (1998) over-estimates E(B-V) by about 14 per cent, consistent with the recent work of Schlafly et al. (2010) and Schlafly & Finkbeiner (2011); 2) All the new reddening coefficients, except those for NUV-u and u-g, prefer the R(V) = 3.1 Fitzpatrick reddening law rather than the R(V) = 3.1 CCM and O'Donnell (O'Donnell 1994) reddening laws. Using the Ks-band extinction coefficient predicted by the R(V) = 3.1 Fitzpatrick law and the observed reddening coefficients, we have deduced new extinction coefficients for the FUV, NUV, u, g, r, i, z, J, H, W1 and W2 passbands. We recommend that the new reddening and extinction coefficients should be used in the future and an update of the Fitzpatrick reddening law in the UV is probably necessary. We stress however that the FUV- and NUV-band coefficients should be used with caution given their relatively large measurement uncertainties. Finally, potential applications of the "standard pair" technique with the LAMOST Galactic surveys are discussed.Comment: 13 pages, 9 figures, accepted to MNRA

Outlook of Cognitive Neuroscience

Social science researches at present emphasize the construction of relations between multiple constructs. Psychological science is no exception. Before verifying whether their hypotheses are true with a questionnaire method or experimental method, scholars will check out the hot topics of recent years and construct multiple mediating and moderating relations first. They work on scattered topics that more or less overlap with many other disciplines. In previous years, the author focused on studying the youths with poor mental health in the new era of China, observing their moral choices in the corporate environment through game theory experiments. The conclusions are usually surprising- most new-generation youths choose to maximize their self-interests from between pro-social behaviors and risk aversion

Solving multiple-criteria R&D project selection problems with a data-driven evidential reasoning rule

In this paper, a likelihood based evidence acquisition approach is proposed to acquire evidence from experts'assessments as recorded in historical datasets. Then a data-driven evidential reasoning rule based model is introduced to R&D project selection process by combining multiple pieces of evidence with different weights and reliabilities. As a result, the total belief degrees and the overall performance can be generated for ranking and selecting projects. Finally, a case study on the R&D project selection for the National Science Foundation of China is conducted to show the effectiveness of the proposed model. The data-driven evidential reasoning rule based model for project evaluation and selection (1) utilizes experimental data to represent experts' assessments by using belief distributions over the set of final funding outcomes, and through this historic statistics it helps experts and applicants to understand the funding probability to a given assessment grade, (2) implies the mapping relationships between the evaluation grades and the final funding outcomes by using historical data, and (3) provides a way to make fair decisions by taking experts' reliabilities into account. In the data-driven evidential reasoning rule based model, experts play different roles in accordance with their reliabilities which are determined by their previous review track records, and the selection process is made interpretable and fairer. The newly proposed model reduces the time-consuming panel review work for both managers and experts, and significantly improves the efficiency and quality of project selection process. Although the model is demonstrated for project selection in the NSFC, it can be generalized to other funding agencies or industries.Comment: 20 pages, forthcoming in International Journal of Project Management (2019