Evaluation of nitrogen- and silicon-vacancy defect centres as single photon sources in quantum key distribution

We demonstrate a quantum key distribution (QKD) testbed for room temperature single photon sources based on defect centres in diamond. A BB84 protocol over a short free-space transmission line is implemented. The performance of nitrogen-vacancy (NV) as well as silicon-vacancy defect (SiV) centres is evaluated and an extrapolation for next-generation sources with enhanced efficiency is discussed.Comment: 14 pages, 5 figure

Bright Room-Temperature Single Photon Emission from Defects in Gallium Nitride

Single photon emitters play a central role in many photonic quantum technologies. A promising class of single photon emitters consists of atomic color centers in wide-bandgap crystals, such as diamond silicon carbide and hexagonal boron nitride. However, it is currently not possible to grow these materials as sub-micron thick films on low-refractive index substrates, which is necessary for mature photonic integrated circuit technologies. Hence, there is great interest in identifying quantum emitters in technologically mature semiconductors that are compatible with suitable heteroepitaxies. Here, we demonstrate robust single photon emitters based on defects in gallium nitride (GaN), the most established and well understood semiconductor that can emit light over the entire visible spectrum. We show that the emitters have excellent photophysical properties including a brightness in excess of 500x10^3 counts/s. We further show that the emitters can be found in a variety of GaN wafers, thus offering reliable and scalable platform for further technological development. We propose a theoretical model to explain the origin of these emitters based on cubic inclusions in hexagonal gallium nitride. Our results constitute a feasible path to scalable, integrated on-chip quantum technologies based on GaN

Nanofabrication on unconventional substrates using transferred hard masks

A major challenge in nanofabrication is to pattern unconventional substrates that cannot be processed for a variety of reasons, such as incompatibility with spin coating, electron beam lithography, optical lithography, or wet chemical steps. Here, we present a versatile nanofabrication method based on re-usable silicon membrane hard masks, patterned using standard lithography and mature silicon processing technology. These masks, transferred precisely onto targeted regions, can be in the millimetre scale. They allow for fabrication on a wide range of substrates, including rough, soft, and non-conductive materials, enabling feature linewidths down to 10 nm. Plasma etching, lift-off, and ion implantation are realized without the need for scanning electron/ion beam processing, UV exposure, or wet etching on target substrates.United States. Dept. of Energy. Office of Basic Energy Sciences (Brookhaven National Laboratory. Contract DE-AC02-98CH10886)Alexander von Humboldt-Stiftun

Expression analysis of G Protein-coupled receptors in mouse macrophages

Background. Monocytes and macrophages express an extensive repertoire of G Protein-Coupled Receptors (GPCRs) that regulate inflammation and immunity. In this study we performed a systematic micro-array analysis of GPCR expression in primary mouse macrophages to identify family members that are either enriched in macrophages compared to a panel of other cell types, or are regulated by an inflammatory stimulus, the bacterial product lipopolysaccharide (LPS). Results. Several members of the P2RY family had striking expression patterns in macrophages; P2ry6 mRNA was essentially expressed in a macrophage-specific fashion, whilst P2ry1 and P2ry5 mRNA levels were strongly down-regulated by LPS. Expression of several other GPCRs was either restricted to macrophages (e.g. Gpr84) or to both macrophages and neural tissues (e.g. P2ry12, Gpr85). The GPCR repertoire expressed by bone marrow-derived macrophages and thioglycollate- elicited peritoneal macrophages had some commonality, but there were also several GPCRs preferentially expressed by either cell population. Conclusion. The constitutive or regulated expression in macrophages of several GPCRs identified in this study has not previously been described. Future studies on such GPCRs and their agonists are likely to provide important insights into macrophage biology, as well as novel inflammatory pathways that could be future targets for drug discovery

A machine learning enhanced mechanistic simulation framework for functional deficit prediction in TBI

Resting state functional magnetic resonance imaging (rsfMRI), and the underlying brain networks identified with it, have recently appeared as a promising avenue for the evaluation of functional deficits without the need for active patient participation. We hypothesize here that such alteration can be inferred from tissue damage within the network. From an engineering perspective, the numerical prediction of tissue mechanical damage following an impact remains computationally expensive. To this end, we propose a numerical framework aimed at predicting resting state network disruption for an arbitrary head impact, as described by the head velocity, location and angle of impact, and impactor shape. The proposed method uses a library of precalculated cases leveraged by a machine learning layer for efficient and quick prediction. The accuracy of the machine learning layer is illustrated with a dummy fall case, where the machine learning prediction is shown to closely match the full simulation results. The resulting framework is finally tested against the rsfMRI data of nine TBI patients scanned within 24 h of injury, for which paramedical information was used to reconstruct in silico the accident. While more clinical data are required for full validation, this approach opens the door to (i) on-the-fly prediction of rsfMRI alterations, readily measurable on clinical premises from paramedical data, and (ii) reverse-engineered accident reconstruction through rsfMRI measurements

Response of the Aerodyne Aerosol Mass Spectrometer to Inorganic Sulfates and Organosulfur Compounds: Applications in Field and Laboratory Measurements

Organosulfur compounds are important components of secondary organic aerosols (SOA). While the Aerodyne high-resolution time-of-flight aerosol mass spectrometer (AMS) has been extensively used in aerosol studies, the response of the AMS to organosulfur compounds is not well-understood. Here, we investigated the fragmentation patterns of organosulfurs and inorganic sulfates in the AMS, developed a method to deconvolve total sulfate into components of inorganic and organic origins, and applied this method in both laboratory and field measurements. Apportionment results from laboratory isoprene photooxidation experiment showed that with inorganic sulfate seed, sulfate functionality of organic origins can contribute ∼7% of SOA mass at peak growth. Results from measurements in the Southeastern U.S. showed that 4% of measured sulfate is from organosulfur compounds. Methanesulfonic acid was estimated for measurements in the coastal and remote marine boundary layer. We explored the application of this method to unit mass-resolution data, where it performed less well due to interferences. Our apportionment results demonstrate that organosulfur compounds could be a non-negligible source of sulfate fragments in AMS laboratory and field data sets. A reevaluation of previous AMS measurements over the full range of atmospheric conditions using this method could provide a global estimate/constraint on the contribution of organosulfur compounds

Low-jitter single-photon detector arrays integrated with silicon and aluminum nitride photonic chips

We present progress on a scalable scheme for integration of single-photon detectors with silicon and aluminum nitride photonic circuits. We assemble arrays of low-jitter waveguide-integrated single-photon detectors and show up to 24% system detection efficiency

Response of the Aerodyne Aerosol Mass Spectrometer to Inorganic Sulfates and Organosulfur Compounds: Applications in Field and Laboratory Measurements

Organosulfur compounds are important components of secondary organic aerosols (SOA). While the Aerodyne high-resolution time-of-flight aerosol mass spectrometer (AMS) has been extensively used in aerosol studies, the response of the AMS to organosulfur compounds is not well-understood. Here, we investigated the fragmentation patterns of organosulfurs and inorganic sulfates in the AMS, developed a method to deconvolve total sulfate into components of inorganic and organic origins, and applied this method in both laboratory and field measurements. Apportionment results from laboratory isoprene photooxidation experiment showed that with inorganic sulfate seed, sulfate functionality of organic origins can contribute ∼7% of SOA mass at peak growth. Results from measurements in the Southeastern U.S. showed that 4% of measured sulfate is from organosulfur compounds. Methanesulfonic acid was estimated for measurements in the coastal and remote marine boundary layer. We explored the application of this method to unit mass-resolution data, where it performed less well due to interferences. Our apportionment results demonstrate that organosulfur compounds could be a non-negligible source of sulfate fragments in AMS laboratory and field data sets. A reevaluation of previous AMS measurements over the full range of atmospheric conditions using this method could provide a global estimate/constraint on the contribution of organosulfur compounds

Scalable Integration of Solid State Quantum Memories into a Photonic Network

Single nitrogen vacancy centers in nanostructured diamond form high quality nodes integrated into low-loss photonic circuitry, enabling on-chip detection and signal manipulation. Pre-selection provides near-unity yield. Long coherence times are demonstrated in integrated nodes