Anisotropic excitation of surface plasmon polaritons on a metal film by a scattering-type scanning near-field microscope with a nonrotationally-symmetric probe tip

We investigated the excitation of surface plasmon polaritons on gold films with the metallized probe tip of a scattering-type scanning near-field optical microscope (s-SNOM). The emission of the polaritons from the tip, illuminated by near-infrared laser radiation, was found to be anisotropic and not circularly symmetric as expected on the basis of literature data. We furthermore identified an additional excitation channel via light that was reflected off the tip and excited the plasmon polaritons at the edge of the metal film. Our results, while obtained for a non-rotationally-symmetric type of probe tip and thus specific for this situation, indicate that when an s-SNOM is employed for the investigation of plasmonic structures, the unintentional excitation of surface waves and anisotropic surface wave propagation must be considered in order to correctly interpret the signatures of plasmon polariton generation and propagation

Anisotropic excitation of surface plasmon polaritons on a metal film by a scattering-type scanning near-field microscope with a non-rotationally-symmetric probe tip

We investigated the excitation of surface plasmon polaritons on gold films with the metallized probe tip of a scattering-type scanning near-field optical microscope (s-SNOM). The emission of the polaritons from the tip, illuminated by near-infrared laser radiation, was found to be anisotropic and not circularly symmetric as expected on the basis of literature data. We furthermore identified an additional excitation channel via light that was reflected off the tip and excited the plasmon polaritons at the edge of the metal film. Our results, while obtained for a non-rotationally-symmetric type of probe tip and thus specific for this situation, indicate that when an s-SNOM is employed for the investigation of plasmonic structures, the unintentional excitation of surface waves and anisotropic surface wave propagation must be considered in order to correctly interpret the signatures of plasmon polariton generation and propagation

Anisotropic excitation of surface plasmon polaritons on a metal film by a scattering-type scanning near-field microscope with a non-rotationally-symmetric probe tip

We investigated the excitation of surface plasmon polaritons on gold films with the metallized probe tip of a scattering-type scanning near-field optical microscope (s-SNOM). The emission of the polaritons from the tip, illuminated by near-infrared laser radiation, was found to be anisotropic and not circularly symmetric as expected on the basis of literature data. We furthermore identified an additional excitation channel via light that was reflected off the tip and excited the plasmon polaritons at the edge of the metal film. Our results, while obtained for a non-rotationally-symmetric type of probe tip and thus specific for this situation, indicate that when an s-SNOM is employed for the investigation of plasmonic structures, the unintentional excitation of surface waves and anisotropic surface wave propagation must be considered in order to correctly interpret the signatures of plasmon polariton generation and propagation

Registered Replication Report:Dijksterhuis and van Knippenberg (1998)

Dijksterhuis and van Knippenberg (1998) reported that participants primed with a category associated with intelligence (professor) subsequently performed 13% better on a trivia test than participants primed with a category associated with a lack of intelligence (soccer hooligans). In two unpublished replications of this study designed to verify the appropriate testing procedures, Dijksterhuis, van Knippenberg, and Holland observed a smaller difference between conditions (2%-3%) as well as a gender difference: Men showed the effect (9.3% and 7.6%), but women did not (0.3% and -0.3%). The procedure used in those replications served as the basis for this multilab Registered Replication Report. A total of 40 laboratories collected data for this project, and 23 of these laboratories met all inclusion criteria. Here we report the meta-analytic results for those 23 direct replications (total N = 4,493), which tested whether performance on a 30-item general-knowledge trivia task differed between these two priming conditions (results of supplementary analyses of the data from all 40 labs, N = 6,454, are also reported). We observed no overall difference in trivia performance between participants primed with the professor category and those primed with the hooligan category (0.14%) and no moderation by gender

Same data, different conclusions : radical dispersion in empirical results when independent analysts operationalize and test the same hypothesis

In this crowdsourced initiative, independent analysts used the same dataset to test two hypotheses regarding the effects of scientists’ gender and professional status on verbosity during group meetings. Not only the analytic approach but also the operationalizations of key variables were left unconstrained and up to individual analysts. For instance, analysts could choose to operationalize status as job title, institutional ranking, citation counts, or some combination. To maximize transparency regarding the process by which analytic choices are made, the analysts used a platform we developed called DataExplained to justify both preferred and rejected analytic paths in real time. Analyses lacking sufficient detail, reproducible code, or with statistical errors were excluded, resulting in 29 analyses in the final sample. Researchers reported radically different analyses and dispersed empirical outcomes, in a number of cases obtaining significant effects in opposite directions for the same research question. A Boba multiverse analysis demonstrates that decisions about how to operationalize variables explain variability in outcomes above and beyond statistical choices (e.g., covariates). Subjective researcher decisions play a critical role in driving the reported empirical results, underscoring the need for open data, systematic robustness checks, and transparency regarding both analytic paths taken and not taken. Implications for organizations and leaders, whose decision making relies in part on scientific findings, consulting reports, and internal analyses by data scientists, are discussed

Same data, different conclusions: Radical dispersion in empirical results when independent analysts operationalize and test the same hypothesis

In this crowdsourced initiative, independent analysts used the same dataset to test two hypotheses regarding the effects of scientists’ gender and professional status on verbosity during group meetings. Not only the analytic approach but also the operationalizations of key variables were left unconstrained and up to individual analysts. For instance, analysts could choose to operationalize status as job title, institutional ranking, citation counts, or some combination. To maximize transparency regarding the process by which analytic choices are made, the analysts used a platform we developed called DataExplained to justify both preferred and rejected analytic paths in real time. Analyses lacking sufficient detail, reproducible code, or with statistical errors were excluded, resulting in 29 analyses in the final sample. Researchers reported radically different analyses and dispersed empirical outcomes, in a number of cases obtaining significant effects in opposite directions for the same research question. A Boba multiverse analysis demonstrates that decisions about how to operationalize variables explain variability in outcomes above and beyond statistical choices (e.g., covariates). Subjective researcher decisions play a critical role in driving the reported empirical results, underscoring the need for open data, systematic robustness checks, and transparency regarding both analytic paths taken and not taken. Implications for organizations and leaders, whose decision making relies in part on scientific findings, consulting reports, and internal analyses by data scientists, are discussed