Demonstration of sub-3 ps temporal resolution with a superconducting nanowire single-photon detector

Improvements in temporal resolution of single-photon detectors enable increased data rates and transmission distances for both classical and quantum optical communication systems, higher spatial resolution in laser ranging, and observation of shorter-lived fluorophores in biomedical imaging. In recent years, superconducting nanowire single-photon detectors (SNSPDs) have emerged as the most efficient time-resolving single-photon-counting detectors available in the near-infrared, but understanding of the fundamental limits of timing resolution in these devices has been limited due to a lack of investigations into the timescales involved in the detection process. We introduce an experimental technique to probe the detection latency in SNSPDs and show that the key to achieving low timing jitter is the use of materials with low latency. By using a specialized niobium nitride SNSPD we demonstrate that the system temporal resolution can be as good as 2.6 ± 0.2 ps for visible wavelengths and 4.3 ± 0.2 ps at 1,550 nm

Demonstration of sub-3 ps temporal resolution with a superconducting nanowire single-photon detector

Improvements in temporal resolution of single-photon detectors enable increased data rates and transmission distances for both classical and quantum optical communication systems, higher spatial resolution in laser ranging, and observation of shorter-lived fluorophores in biomedical imaging. In recent years, superconducting nanowire single-photon detectors (SNSPDs) have emerged as the most efficient time-resolving single-photon-counting detectors available in the near-infrared, but understanding of the fundamental limits of timing resolution in these devices has been limited due to a lack of investigations into the timescales involved in the detection process. We introduce an experimental technique to probe the detection latency in SNSPDs and show that the key to achieving low timing jitter is the use of materials with low latency. By using a specialized niobium nitride SNSPD we demonstrate that the system temporal resolution can be as good as 2.6 ± 0.2 ps for visible wavelengths and 4.3 ± 0.2 ps at 1,550 nm

Multilevel Computational Analysis of Fluorocarbon Polyatomic Deposition on Diamond

Hyperthermal polyatomic fluorocarbon (FC) deposition upon the diamond (111) surface is simulated and analyzed at several levels of computational theory. Classical molecular dynamics simulations using the reactive empirical bond order (REBO) potential are used to categorize the surface reactions that occur during radical deposition. Molecular dynamics (MD) simulations, using density functional theory (DFT-MD) via the SIESTA method and program, are used to corroborate the findings from the classical simulations and to categorize reactions that occur during cation deposition. Finally, reaction enthalpies are calculated with higher level quantum mechanical methods using a cluster model to verify and refine the predictions from the MD simulations. The multilevel analysis predicts that FC radicals add directly to the diamond (111) surface with the simultaneous formation of HF. In contrast, FC cations preferentially dissociate H from the surface leaving behind a cationic carbon site. Cations and radical species are found to prefer different reaction pathways, which limits the applicability of REBO. Furthermore, the comparison reveals a difference in the predicted reaction probabilities between REBO and DFT which is attributable to the short cut off distance for interaction in the current REBO formulation

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