Optical performance of the JWST MIRI flight model: characterization of the point spread function at high-resolution

The Mid Infra Red Instrument (MIRI) is one of the four instruments onboard the James Webb Space Telescope (JWST), providing imaging, coronagraphy and spectroscopy over the 5-28 microns band. To verify the optical performance of the instrument, extensive tests were performed at CEA on the flight model (FM) of the Mid-InfraRed IMager (MIRIM) at cryogenic temperatures and in the infrared. This paper reports on the point spread function (PSF) measurements at 5.6 microns, the shortest operating wavelength for imaging. At 5.6 microns the PSF is not Nyquist-sampled, so we use am original technique that combines a microscanning measurement strategy with a deconvolution algorithm to obtain an over-resolved MIRIM PSF. The microscanning consists in a sub-pixel scan of a point source on the focal plane. A data inversion method is used to reconstruct PSF images that are over-resolved by a factor of 7 compared to the native resolution of MIRI. We show that the FWHM of the high-resolution PSFs were 5-10% wider than that obtained with Zemax simulations. The main cause was identified as an out-of-specification tilt of the M4 mirror. After correction, two additional test campaigns were carried out, and we show that the shape of the PSF is conform to expectations. The FWHM of the PSFs are 0.18-0.20 arcsec, in agreement with simulations. 56.1-59.2% of the total encircled energy (normalized to a 5 arcsec radius) is contained within the first dark Airy ring, over the whole field of view. At longer wavelengths (7.7-25.5 microns), this percentage is 57-68%. MIRIM is thus compliant with the optical quality requirements. This characterization of the MIRIM PSF, as well as the deconvolution method presented here, are of particular importance, not only for the verification of the optical quality and the MIRI calibration, but also for scientific applications.Comment: 13 pages, submitted to SPIE Proceedings vol. 7731, Space Telescopes and Instrumentation 2010: Optical, Infrared, and Millimeter Wav

Do ResearchGate Scores create ghost academic reputations?

[EN] The academic social network site ResearchGate (RG) has its own indicator, RG Score, for its members. The high profile nature of the site means that the RG Score may be used for recruitment, promotion and other tasks for which researchers are evaluated. In response, this study investigates whether it is reasonable to employ the RG Score as evidence of scholarly reputation. For this, three different author samples were investigated. An outlier sample includes 104 authors with high values. A Nobel sample comprises 73 Nobel winners from Medicine and Physiology, Chemistry, Physics and Economics (from 1975 to 2015). A longitudinal sample includes weekly data on 4 authors with different RG Scores. The results suggest that high RG Scores are built primarily from activity related to asking and answering questions in the site. In particular, it seems impossible to get a high RG Score solely through publications. Within RG it is possible to distinguish between (passive) academics that interact little in the site and active platform users, who can get high RG Scores through engaging with others inside the site (questions, answers, social networks with influential researchers). Thus, RG Scores should not be mistaken for academic reputation indicators.Alberto Martin-Martin enjoys a four-year doctoral fellowship (FPU2013/05863) granted by the Ministerio de Educacion, Cultura, y Deporte (Spain). Enrique Orduna-Malea holds a postdoctoral fellowship (PAID-10-14), from the Polytechnic University of Valencia (Spain).Orduña Malea, E.; Martín-Martín, A.; Thelwall, M.; Delgado-López-Cózar, E. (2017). Do ResearchGate Scores create ghost academic reputations?. Scientometrics. 112(1):443-460. https://doi.org/10.1007/s11192-017-2396-9S4434601121Bosman, J. & Kramer, B. (2016). Innovations in scholarly communication—data of the global 2015–2016 survey. Available at: http://zenodo.org/record/49583 #. Accessed December 11, 2016.González-Díaz, C., Iglesias-García, M., & Codina, L. (2015). Presencia de las universidades españolas en las redes sociales digitales científicas: Caso de los estudios de comunicación. El profesional de la información, 24(5), 1699–2407.Goodwin, S., Jeng, W., & He, D. (2014). Changing communication on ResearchGate through interface updates. Proceedings of the American Society for Information Science and Technology, 51(1), 1–4.Hicks, D., Wouters, P., Waltman, L., de Rijcke, S., & Rafols, I. (2015). The Leiden Manifesto for research metrics. Nature, 520(7548), 429–431.Hoffmann, C. P., Lutz, C., & Meckel, M. (2015). A relational altmetric? Network centrality on ResearchGate as an indicator of scientific impact. Journal of the Association for Information Science and Technology, 67(4), 765–775.Jiménez-Contreras, E., de Moya Anegón, F., & Delgado López-Cózar, E. (2003). The evolution of research activity in Spain: The impact of the National Commission for the Evaluation of Research Activity (CNEAI). Research Policy, 32(1), 123–142.Jordan, K. (2014a). Academics’ awareness, perceptions and uses of social networking sites: Analysis of a social networking sites survey dataset (December 3, 2014). Available at: http://dx.doi.org/10.2139/ssrn.2507318 . Accessed December 11, 2016.Jordan, K. (2014b). Academics and their online networks: Exploring the role of academic social networking sites. First Monday, 19(11). Available at: http://dx.doi.org/10.5210/fm.v19i11.4937 . Accessed December 11, 2016.Jordan, K. (2015). Exploring the ResearchGate score as an academic metric: reflections and implications for practice. Quantifying and Analysing Scholarly Communication on the Web (ASCW’15), 30 June 2015, Oxford. Available at: http://ascw.know-center.tugraz.at/wp-content/uploads/2015/06/ASCW15_jordan_response_kraker-lex.pdf . Accessed December 11, 2016.Kadriu, A. (2013). Discovering value in academic social networks: A case study in ResearchGate. Proceedings of the ITI 2013—35th Int. Conf. on Information Technology Interfaces Information Technology Interfaces, pp. 57–62.Kraker, P. & Lex, E. (2015). A critical look at the ResearchGate score as a measure of scientific reputation. Proceedings of the Quantifying and Analysing Scholarly Communication on the Web workshop (ASCW’15), Web Science conference 2015. Available at: http://ascw.know-center.tugraz.at/wp-content/uploads/2016/02/ASCW15_kraker-lex-a-critical-look-at-the-researchgate-score_v1-1.pdf . Accessed December 11, 2016.Li, L., He, D., Jeng, W., Goodwin, S. & Zhang, C. (2015). Answer quality characteristics and prediction on an academic Q&A Site: A case study on ResearchGate. Proceedings of the 24th International Conference on World Wide Web Companion, pp. 1453–1458.Martín-Martín, A., Orduna-Malea, E., Ayllón, J. M. & Delgado López-Cózar, E. (2016). The counting house: measuring those who count. Presence of Bibliometrics, Scientometrics, Informetrics, Webometrics and Altmetrics in the Google Scholar Citations, ResearcherID, ResearchGate, Mendeley & Twitter. Available at: https://arxiv.org/abs/1602.02412 . Accessed December 11, 2016.Martín-Martín, A., Orduna-Malea, E. & Delgado López-Cózar, E. (2016). The role of ego in academic profile services: Comparing Google Scholar, ResearchGate, Mendeley, and ResearcherID. Researchgate, Mendeley, and Researcherid. The LSE Impact of Social Sciences blog. Available at: http://blogs.lse.ac.uk/impactofsocialsciences/2016/03/04/academic-profile-services-many-mirrors-and-faces-for-a-single-ego . Accessed December 11, 2016.Matthews, D. (2016). Do academic social networks share academics’ interests?. Times Higher Education. Available at: https://www.timeshighereducation.com/features/do-academic-social-networks-share-academics-interests . Accessed December 11, 2016.Memon, A. R. (2016). ResearchGate is no longer reliable: leniency towards ghost journals may decrease its impact on the scientific community. Journal of the Pakistan Medical Association, 66(12), 1643–1647.Mikki, S., Zygmuntowska, M., Gjesdal, Ø. L. & Al Ruwehy, H. A. (2015). Digital presence of norwegian scholars on academic network sites-where and who are they?. Plos One 10(11). Available at: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0142709 . Accessed December 11, 2016.Nicholas, D., Clark, D., & Herman, E. (2016). ResearchGate: Reputation uncovered. Learned Publishing, 29(3), 173–182.Orduna-Malea, E., Martín-Martín, A., & Delgado López-Cózar, E. (2016). The next bibliometrics: ALMetrics (Author Level Metrics) and the multiple faces of author impact. El profesional de la información, 25(3), 485–496.Ortega, Jose L. (2015). Relationship between altmetric and bibliometric indicators across academic social sites: The case of CSIC’s members. Journal of informetrics, 9(1), 39–49.Ortega, Jose L. (2016). Social network sites for scientists. Cambridge: Chandos.Ovadia, S. (2014). ResearchGate and Academia. edu: Academic social networks. Behavioral & Social Sciences Librarian, 33(3), 165–169.Thelwall, M., & Kousha, K. (2015). ResearchGate: Disseminating, communicating, and measuring Scholarship? Journal of the Association for Information Science and Technology, 66(5), 876–889.Thelwall, M. & Kousha, K. (2017). ResearchGate articles: Age, discipline, audience size and impact. Journal of the Association for Information Science and Technology, 68(2), 468–479.Van Noorden, R. (2014). Online collaboration: Scientists and the social network. Nature, 512(7513), 126–129.Wilsdon, J., Allen, L., Belfiore, E., Campbell, P., Curry, S., Hill, S. et al. (2015). The Metric Tide: Independent Review of the Role of Metrics in Research Assessment and Management. HEFCE. Available at: http://doi.org/10.13140/RG.2.1.4929.1363 . Accessed December 11, 2016

Measurements of differential cross sections of Z/gamma*+jets+X events in proton anti-proton collisions at sqrt{s}=1.96 TeV

We present cross section measurements for Z/gamma*+jets+X production, differential in the transverse momenta of the three leading jets. The data sample was collected with the D0 detector at the Fermilab Tevatron proton anti-proton collider at a center-of-mass energy of 1.96 TeV and corresponds to an integrated luminosity of 1 fb-1. Leading and next-to-leading order perturbative QCD predictions are compared with the measurements, and agreement is found within the theoretical and experimental uncertainties. We also make comparisons with the predictions of four event generators. Two parton-shower-based generators show significant shape and normalization differences with respect to the data. In contrast, two generators combining tree-level matrix elements with a parton shower give a reasonable description of the the shapes observed in data, but the predicted normalizations show significant differences with respect to the data, reflecting large scale uncertainties. For specific choices of scales, the normalizations for either generator can be made to agree with the measurements.Comment: Published in PLB. 11 pages, 3 figure

Measurement of the t-channel single top quark production cross section

The D0 collaboration reports direct evidence for electroweak production of single top quarks through the t-channel exchange of a virtual W boson. This is the first analysis to isolate an individual single top quark production channel. We select events containing an isolated electron or muon, missing transverse energy, and two, three or four jets from 2.3 fb^-1 of ppbar collisions at the Fermilab Tevatron Collider. One or two of the jets are identified as containing a b hadron. We combine three multivariate techniques optimized for the t-channel process to measure the t- and s-channel cross sections simultaneously. We measure cross sections of 3.14 +0.94 -0.80 pb for the t-channel and 1.05 +-0.81 pb for the s-channel. The measured t-channel result is found to have a significance of 4.8 standard deviations and is consistent with the standard model prediction.Comment: 7 pages, 6 figure

Precise measurement of the top quark mass in the dilepton channel at D0

We measure the top quark mass (mt) in ppbar collisions at a center of mass energy of 1.96 TeV using dilepton ttbar->W+bW-bbar->l+nubl-nubarbbar events, where l denotes an electron, a muon, or a tau that decays leptonically. The data correspond to an integrated luminosity of 5.4 fb-1 collected with the D0 detector at the Fermilab Tevatron Collider. We obtain mt = 174.0 +- 1.8(stat) +- 2.4(syst) GeV, which is in agreement with the current world average mt = 173.3 +- 1.1 GeV. This is currently the most precise measurement of mt in the dilepton channel.Comment: 7 pages, 4 figure

Direct measurement of the mass difference between top and antitop quarks

We present a direct measurement of the mass difference between top and antitop quarks (dm) in lepton+jets top-antitop final states using the "matrix element" method. The purity of the lepton+jets sample is enhanced for top-antitop events by identifying at least one of the jet as originating from a b quark. The analyzed data correspond to 3.6 fb-1 of proton-antiproton collisions at 1.96 TeV acquired by D0 in Run II of the Fermilab Tevatron Collider. The combination of the e+jets and mu+jets channels yields dm = 0.8 +/- 1.8 (stat) +/- 0.5 (syst) GeV, which is in agreement with the standard model expectation of no mass difference.Comment: submitted to Phys. Rev.

Double parton interactions in photon+3 jet events in ppbar collisions sqrt{s}=1.96 TeV

We have used a sample of photon+3 jets events collected by the D0 experiment with an integrated luminosity of about 1 fb^-1 to determine the fraction of events with double parton scattering (f_DP) in a single ppbar collision at sqrt{s}=1.96 TeV. The DP fraction and effective cross section (sigma_eff), a process-independent scale parameter related to the parton density inside the nucleon, are measured in three intervals of the second (ordered in pT) jet transverse momentum pT_jet2 within the range 15 < pT_jet2 < 30 GeV. In this range, f_DP varies between 0.23 < f_DP < 0.47, while sigma_eff has the average value sigma_eff_ave = 16.4 +- 0.3(stat) +- 2.3(syst) mb.Comment: 15 pages, 13 figure

Measurement of trilinear gauge boson couplings from WW + WZ to lnu jj events in pp-bar collisions at sqrt{s}=1.96 TeV

We present a direct measurement of trilinear gauge boson couplings at gammaWW and ZWW vertices in WW and WZ events produced in pp-bar collisions at sqrt{s}=1.96 TeV. We consider events with one electron or muon, missing transverse energy, and at least two jets. The data were collected using the D0 detector and correspond to 1.1/fb of integrated luminosity. Considering two different relations between the couplings at the gammaWW and ZWW vertices, we measure these couplings at 68% C.L. to be kappa_{gamma}=1.07^{+0.26}_{-0.29}, lambda =0.00^{+0.06}_{-0.06} and g_{1}^{Z}=1.04^{+0.09}_{-0.09} in a scenario respecting SU(2)_L x U(1)_Y gauge symmetry and kappa =1.04^{+0.11}_{-0.11} and lambda=0.00^{+0.06}_{-0.06} in an "equal couplings" scenario.Comment: 14 pages, 7 figures, published in Phys. Rev. D, updated to published versio

Evidence for an anomalous like-sign dimuon charge asymmetry

We measure the charge asymmetry A of like-sign dimuon events in 6.1 fb(-1) of p (p) over bar collisions recorded with the D0 detector at a center-of-mass energy root s = 1.96 TeV at the Fermilab Tevatron collider. From A, we extract the like-sign dimuon charge asymmetry in semileptonic b-hadron decays: A(sl)(b) = -0.00957 +/- 0.00251 (stat) +/- 0.00146 (syst). This result differs by 3.2 standard deviations from the standard model prediction A(sl)(b)(SM) = (-2.3(0.6)(+0.5)) x 10(-4) and provides first evidence of anomalous CP violation in the mixing of neutral B mesons