Search

Asteroseismic time series data have imprints of stellar oscillation modes, whose detection and characterization through time series analysis allows us to probe stellar interior physics. Such analyses usually occur in the Fourier domain by computing the Lomb–Scargle (LS) periodogram, an estimator of the power spectrum underlying unevenly sampled time series data. However, the LS periodogram suffers from the statistical problems of (1) inconsistency (or noise) and (2) bias due to high spectral leakage. Here, we develop a multitaper power spectrum estimator using the nonuniform fast Fourier transform ( mtNUFFT ) to tackle the inconsistency and bias problems of the LS periodogram. Using a simulated light curve, we show that the mtNUFFT power spectrum estimate of solar-like oscillations has lower variance and bias than the LS estimate. We also apply our method to the Kepler-91 red giant, and combine it with PBjam peakbagging to obtain mode parameters and a derived age estimate of 3.97 ± 0.52 Gyr. PBjam allows the improvement of age precision relative to the 4.27 ± 0.75 Gyr APOKASC-2 (uncorrected) estimate, whereas partnering mtNUFFT with PBjam speeds up peakbagging thrice as much as LS. This increase in efficiency has promising implications for Galactic archaeology, in addition to stellar structure and evolution studies. Our new method generally applies to time-domain astronomy and is implemented in the public Python package tapify , available at https://github.com/aaryapatil/tapify .

Purpose: Radiation therapy is a standard modality in the treatment for cancers of the head and neck, but is associated with significant short- and long-term side effects. Proton therapy, with its unique physical characteristics, can deliver less dose to normal tissues, resulting in fewer side effects. Proton therapy is currently being used for the treatment of head and neck cancer, with increasing clinical evidence supporting its use. However, barriers to wider adoption include access, cost, and the need for higher-level evidence. Methods: The clinical evidence for the use of proton therapy in the treatment of head and neck cancer are reviewed here, including indications, advantages, and challenges. Results: The Particle Therapy Cooperative Group Head and Neck Subcommittee task group provides consensus guidelines for the use of proton therapy for head and neck cancer. Conclusion: This report can be used as a guide for clinical use, to understand clinical trials, and to inform future research efforts.

As the silicon photonics field matures and a data-hungry future looms ahead, new technologies are required to keep up pace with the increase in capacity demand. In this paper, we review current developments in the near-IR and mid-IR group IV photonic modulators that show promising performance. We analyse recent trends in optical and electrical co-integration of modulators and drivers enabling modulation data rates of 112 GBaud in the near infrared. We then describe new developments in short wave infrared spectrum modulators such as employing more spectrally efficient PAM-4 coding schemes for modulations up to 40 GBaud. Finally, we review recent results at the mid infrared spectrum and application of the thermo-optic effect for modulation as well as the emergence of new platforms based on germanium to tackle the challenges of modulating light in the long wave infrared spectrum up to 10.7 μm with data rates of 225 MBaud.

In this paper we demonstrate that by breaking the left/right symmetry in a bi-planar double-silicon on insulator (SOI) photonic crystal (PhC) fin-waveguide, we can couple the conventionally used transverse-electric (TE) polarized mode to the transverse-magnetic (TM) polarization slot-mode. Finite difference time domain (FDTD) simulations indicate that the TE mode couples to the robust TM mode inside the Brillouin zone. Broadband transmission data shows propagation identified with horizontal-slot TM mode within the TE bandgap for fully mismatched fabricated devices. This simultaneously demonstrates TE to TM mode conversion, and the narrowest Si photonics SiO2 slot-mode propagation reported in the literature (10 nm wide slot), which both have many potential telecommunication applications.

Germanium (Ge) ion implantation into silicon waveguides will induce lattice defects in the silicon, which can eventually change the crystal silicon into amorphous silicon and increase the refractive index from 3.48 to 3.96. A subsequent annealing process, either by using an external laser or integrated thermal heaters can partially or completely remove those lattice defects and gradually change the amorphous silicon back into the crystalline form and, therefore, reduce the material’s refractive index. Utilising this change in optical properties, we successfully demonstrated various erasable photonic devices. Those devices can be used to implement a flexible and commercially viable wafer-scale testing method for a silicon photonics fabrication line, which is a key technology to reduce the cost and increase the yield in production. In addition, Ge ion implantation and annealing are also demonstrated to enable post-fabrication trimming of ring resonators and Mach–Zehnder interferometers and to implement nonvolatile programmable photonic circuits.

Advanced photonic probes are important for the development of non-contact wafer-scale testing of photonic chips. Here, Vynck et al. develop a quantitative technique based on mapping of transmittance variations by ultrafast perturbations to analyze arbitrary linear multi-port photonic devices.

We present a Bayesian inversion method for estimating volcanic ash emissions using satellite retrievals of ash column load and an atmospheric dispersion model. An a priori description of the emissions is used based on observations of the rise height of the volcanic plume and a stochastic model of the possible emissions. Satellite data are processed to give column loads where ash is detected and to give information on where we have high confidence that there is negligible ash. An atmospheric dispersion model is used to relate emissions and column loads. Gaussian distributions are assumed for the a priori emissions and for the errors in the satellite retrievals. The optimal emissions estimate is obtained by finding the peak of the a posteriori probability density under the constraint that the emissions are non-negative. We apply this inversion method within a framework designed for use during an eruption with the emission estimates (for any given emission time) being revised over time as more information becomes available. We demonstrate the approach for the 2010 Eyjafjallajökull and 2011 Grímsvötn eruptions. We apply the approach in two ways, using only the ash retrievals and using both the ash and clear sky retrievals. For Eyjafjallajökull we have compared with an independent dataset not used in the inversion and have found that the inversion-derived emissions lead to improved predictions.

Integrated optical circuits today are typically designed for a few special functionalities and require complex design and development procedures. Here, the authors demonstrate a reconfigurable but simple silicon waveguide mesh with different functionalities.

In 2016, Thach et al. reported figures of merit of the GeSn photodiodes with large mesa sizes of 500 and 250 μm to show the potential of the GeSn materials in short-wave infrared photonics23. However, there are only a few discussions about high frequency capabilities of GeSn photodetectors. It is needed to understand the potential of GeSn detectors as high frequency devices. This paper discusses comprehensively about the performance of GeSn photodiodes with 6.44 and 9.24% Sn for high frequency applications including high speed measurements and simulations. With high Sn incorporation, the cutoff wavelength is extended up to 2.2 and 2.5 μm wavelengths for 6.44 and 9.24% Sn devices, respectively. The photodiodes' bandwidth is 1.78 GHz, and the simulation shows excellent agreement with measurement results. The reported GeSn photodetectors together with recently reported GeSn lasers and other GeSn microwave photonic components will be a potential candidate for integrated microwave photonics.

The field of silicon photonics has experienced widespread adoption in the datacoms industry over the past decade, with a plethora of other applications emerging more recently such as light detection and ranging (LIDAR), sensing, quantum photonics, programmable photonics and artificial intelligence. As a result of this, many commercial complementary metal oxide semiconductor (CMOS) foundries have developed open access silicon photonics process lines, enabling the mass production of silicon photonics systems. On the other side of the spectrum, several research labs, typically within universities, have opened up their facilities for small scale prototyping, commonly exploiting e-beam lithography for wafer patterning. Within this ecosystem, there remains a challenge for early stage researchers to progress their novel and innovate designs from the research lab to the commercial foundries because of the lack of compatibility of the processing technologies (e-beam lithography is not an industry tool). The CORNERSTONE rapid-prototyping capability bridges this gap between research and industry by providing a rapid prototyping fabrication line based on deep-UV lithography to enable seamless scaling up of production volumes, whilst also retaining the ability for device level innovation, crucial for researchers, by offering flexibility in its process flows. This review article presents a summary of the current CORNERSTONE capabilities and an outlook for the future.

It has been 10 years since the ash cloud from the eruption of Eyjafjallajökull caused unprecedented disruption to air traffic across Europe. During this event, the London Volcanic Ash Advisory Centre (VAAC) provided advice and guidance on the expected location of volcanic ash in the atmosphere using observations and the atmospheric dispersion model NAME (Numerical Atmospheric-Dispersion Modelling Environment). Rapid changes in regulatory response and procedures during the eruption introduced the requirement to also provide forecasts of ash concentrations, representing a step-change in the level of interrogation of the dispersion model output. Although disruptive, the longevity of the event afforded the scientific community the opportunity to observe and extensively study the transport and dispersion of a volcanic ash cloud. We present the development of the NAME atmospheric dispersion model and modifications to its application in the London VAAC forecasting system since 2010, based on the lessons learned. Our ability to represent both the vertical and horizontal transport of ash in the atmosphere and its removal have been improved through the introduction of new schemes to represent the sedimentation and wet deposition of volcanic ash, and updated schemes to represent deep moist atmospheric convection and parametrizations for plume spread due to unresolved mesoscale motions. A good simulation of the transport and dispersion of a volcanic ash cloud requires an accurate representation of the source and we have introduced more sophisticated approaches to representing the eruption source parameters, and their uncertainties, used to initialize NAME. Finally, upper air wind field data used by the dispersion model is now more accurate than it was in 2010. These developments have resulted in a more robust modelling system at the London VAAC, ready to provide forecasts and guidance during the next volcanic ash event.

Large explosive eruptions can result in the formation of an umbrella cloud which rapidly expands, spreading ash out radially from the volcano. The lateral spread by the intrusive gravity current dominates the transport of the ash cloud. Hence, to accurately forecast the transport of ash from large eruptions, lateral spread of umbrella clouds needs to be represented within volcanic ash transport and dispersion models. Here, we describe an umbrella cloud parameterisation which has been implemented into an operational Lagrangian model and consider how it may be used during an eruption when information concerning the eruption is limited and model runtime is key. We examine different relations for the volume flow rate into the umbrella, and the rate of spreading within the cloud. The scheme is validated against historic eruptions of differing scales (Pinatubo 1991, Kelud 2014, Calbuco 2015 and Eyjafjallajökull 2010) by comparing model predictions with satellite observations. Reasonable predictions of umbrella cloud spread are achieved using an estimated volume flow rate from the empirical equation by Bursik et al. and the observed eruption height. We show how model predictions can be refined during an ongoing eruption as further information and observations become available.

The integration of nanophotonics components with advanced complementary metal-oxide-semiconductor (CMOS) electronics requires drive voltages as low as 1 V for enabling next-generation CMOS electrophotonics transceivers. Slow-light propagation has been recently demonstrated as an effective mechanism to enhance the modulation efficiency in free-carrier-based electrooptical silicon modulators. Here, we exploit the use of slow light to reduce the driving voltage of carrier-depletion-based Mach-Zehnder modulators. The slow-light phase shifter consists of a p-n junction positioned in the middle of a corrugated waveguide. A modulation efficiency as high as VπLπ ~ 0.6 V·cm is achieved, thus allowing data transmission rates up to 10 Gb/s with a 1.5-Vpp drive voltage and an insertion loss of ~12 dB. The influence of the drive voltage on the modulation speed as well as the variation of the insertion losses with a group index is also analyzed and discussed.

During the eruption of Eyjafjallajökull in April and May 2010, the London Volcanic Ash Advisory Centre demonstrated the importance of infrared (IR) satellite imagery for monitoring volcanic ash and validating the Met Office operational model, NAME. This model is used to forecast ash dispersion and forms much of the basis of the advice given to civil aviation. NAME requires a source term describing the properties of the eruption plume at the volcanic source. Elements of the source term are often highly uncertain and significant effort has therefore been invested into the use of satellite observations of ash clouds to constrain them. This paper presents a data insertion method, where satellite observations of downwind ash clouds are used to create effective ‘virtual sources’ far from the vent. Uncertainty in the model output is known to increase over the duration of a model run, as inaccuracies in the source term, meteorological data and the parameterizations of the modelled processes accumulate. This new technique, where the dis- persion model (DM) is ‘reinitialized’ part-way through a run, could go some way to addressing this.

Change History: A correction to this article has been published and is linked from the HTML version of this article.