Throughput gains from adaptive transceivers in nonlinear elastic optical networks

In this paper, we link the throughput gains, due to transceiver adaptation, in a point-to-point transmission link to the expected gains in a mesh network. We calculate the maximum network throughput for a given topology as we vary the length scale. We show that the expected gain in the network throughput due to transceiver adaptation is equivalent to the gain in a point-to-point link with a length equal to the mean length of the optical paths across the minimum network cut. We also consider upper and lower bounds on the variation of the gain in the network throughput due to transceiver adaptation, where integer-constrained channel bandwidth assignment and quantized adaptations are considered. This bounds the variability of results that can be expected and indicates why some networks can give apparently optimistic or pessimistic results. We confirm the results of previous authors that show finer quantization steps in the adaptive control lead to an increase in the throughput since the mean loss of throughput per transceiver is reduced. Finally, we consider the likely network advantage of digital nonlinear mitigation and show that a significant tradeoff occurs between the increase in the signal-to-noise ratio for larger mitigation bandwidths and the loss of throughput when routing fewer large-bandwidth superchannels

Throughput gains from adaptive transceivers in nonlinear elastic optical networks

In this paper, we link the throughput gains, due to transceiver adaptation, in a point-to-point transmission link to the expected gains in a mesh network. We calculate the maximum network throughput for a given topology as we vary the length scale. We show that the expected gain in the network throughput due to transceiver adaptation is equivalent to the gain in a point-to-point link with a length equal to the mean length of the optical paths across the minimum network cut. We also consider upper and lower bounds on the variation of the gain in the network throughput due to transceiver adaptation, where integer-constrained channel bandwidth assignment and quantized adaptations are considered. This bounds the variability of results that can be expected and indicates why some networks can give apparently optimistic or pessimistic results. We confirm the results of previous authors that show finer quantization steps in the adaptive control lead to an increase in the throughput since the mean loss of throughput per transceiver is reduced. Finally, we consider the likely network advantage of digital nonlinear mitigation and show that a significant tradeoff occurs between the increase in the signal-to-noise ratio for larger mitigation bandwidths and the loss of throughput when routing fewer large-bandwidth superchannels

The benefit of split nonlinearity compensation for single-channel optical fiber communications

In this Letter we analyze the benefit of digital compensation of fiber nonlinearity, where the digital signal processing is divided between the transmitter and receiver. The application of the Gaussian noise model indicates that, where there are two or more spans, it is always beneficial to split the nonlinearity compensation. The theory is verified via numerical simulations, investigating transmission of single channel 50 GBd polarization division multiplexed 256-ary quadrature amplitude modulation over 100 km standard single mode fiber spans, using lumped amplification. For this case, the additional increase in mutual information achieved over transmitter- or receiver-side nonlinearity compensation is approximately 1 bit for distances greater than 2000 km. Further, it is shown, theoretically, that the SNR gain for long distances and high bandwidth transmission is 1.5 dB versus transmitter- or receiver-based nonlinearity compensation

Field Measurements of Terrestrial and Martian Dust Devils

Surface-based measurements of terrestrial and martian dust devils/convective vortices provided from mobile and stationary platforms are discussed. Imaging of terrestrial dust devils has quantified their rotational and vertical wind speeds, translation speeds, dimensions, dust load, and frequency of occurrence. Imaging of martian dust devils has provided translation speeds and constraints on dimensions, but only limited constraints on vertical motion within a vortex. The longer mission durations on Mars afforded by long operating robotic landers and rovers have provided statistical quantification of vortex occurrence (time-of-sol, and recently seasonal) that has until recently not been a primary outcome of more temporally limited terrestrial dust devil measurement campaigns. Terrestrial measurement campaigns have included a more extensive range of measured vortex parameters (pressure, wind, morphology, etc.) than have martian opportunities, with electric field and direct measure of dust abundance not yet obtained on Mars. No martian robotic mission has yet provided contemporaneous high frequency wind and pressure measurements. Comparison of measured terrestrial and martian dust devil characteristics suggests that martian dust devils are larger and possess faster maximum rotational wind speeds, that the absolute magnitude of the pressure deficit within a terrestrial dust devil is an order of magnitude greater than a martian dust devil, and that the time-of-day variation in vortex frequency is similar. Recent terrestrial investigations have demonstrated the presence of diagnostic dust devil signals within seismic and infrasound measurements; an upcoming Mars robotic mission will obtain similar measurement types

Reporting guideline for the early stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI

A growing number of artificial intelligence (AI)-based clinical decision support systems are showing promising performance in preclinical, in silico, evaluation, but few have yet demonstrated real benefit to patient care. Early stage clinical evaluation is important to assess an AI system’s actual clinical performance at small scale, ensure its safety, evaluate the human factors surrounding its use, and pave the way to further large scale trials. However, the reporting of these early studies remains inadequate. The present statement provides a multistakeholder, consensus-based reporting guideline for the Developmental and Exploratory Clinical Investigations of DEcision support systems driven by Artificial Intelligence (DECIDE-AI). We conducted a two round, modified Delphi process to collect and analyse expert opinion on the reporting of early clinical evaluation of AI systems. Experts were recruited from 20 predefined stakeholder categories. The final composition and wording of the guideline was determined at a virtual consensus meeting. The checklist and the Explanation & Elaboration (E&E) sections were refined based on feedback from a qualitative evaluation process. 123 experts participated in the first round of Delphi, 138 in the second, 16 in the consensus meeting, and 16 in the qualitative evaluation. The DECIDE-AI reporting guideline comprises 17 AI specific reporting items (made of 28 subitems) and 10 generic reporting items, with an E&E paragraph provided for each. Through consultation and consensus with a range of stakeholders, we have developed a guideline comprising key items that should be reported in early stage clinical studies of AI-based decision support systems in healthcare. By providing an actionable checklist of minimal reporting items, the DECIDE-AI guideline will facilitate the appraisal of these studies and replicability of their findings

Scintillator ageing of the T2K near detectors from 2010 to 2021

The T2K experiment widely uses plastic scintillator as a target for neutrino interactions and an active medium for the measurement of charged particles produced in neutrino interactions at its near detector complex. Over 10 years of operation the measured light yield recorded by the scintillator based subsystems has been observed to degrade by 0.9–2.2% per year. Extrapolation of the degradation rate through to 2040 indicates the recorded light yield should remain above the lower threshold used by the current reconstruction algorithms for all subsystems. This will allow the near detectors to continue contributing to important physics measurements during the T2K-II and Hyper-Kamiokande eras. Additionally, work to disentangle the degradation of the plastic scintillator and wavelength shifting fibres shows that the reduction in light yield can be attributed to the ageing of the plastic scintillator. The long component of the attenuation length of the wavelength shifting fibres was observed to degrade by 1.3–5.4% per year, while the short component of the attenuation length did not show any conclusive degradation

Throughput gains from adaptive transceivers in nonlinear elastic optical networks

In this paper, we link the throughput gains, due to transceiver adaptation, in a point-to-point transmission link to the expected gains in a mesh network. We calculate the maximum network throughput for a given topology as we vary the length scale. We show that the expected gain in the network throughput due to transceiver adaptation is equivalent to the gain in a point-to-point link with a length equal to the mean length of the optical paths across the minimum network cut. We also consider upper and lower bounds on the variation of the gain in the network throughput due to transceiver adaptation, where integer-constrained channel bandwidth assignment and quantized adaptations are considered. This bounds the variability of results that can be expected and indicates why some networks can give apparently optimistic or pessimistic results. We confirm the results of previous authors that show finer quantization steps in the adaptive control lead to an increase in the throughput since the mean loss of throughput per transceiver is reduced. Finally, we consider the likely network advantage of digital nonlinear mitigation and show that a significant tradeoff occurs between the increase in the signal-to-noise ratio for larger mitigation bandwidths and the loss of throughput when routing fewer large-bandwidth superchannels

Impact of amplifier noise figure on network throughput

The impact of the amplifier noise figure (NF) on the optical network throughput is quantified from an information viewpoint. For every dB of NF decrease, throughput gains between 4% and 7% are reported

On optimal modulation and FEC overhead for future optical networks

Transceivers employing square PM-QAM with up to two FEC overheads are optimized based on the SNR distribution. For NSFNET two FEC overheads with PM-16QAM give an 82% throughput increase compared with PM-QPSK with 7% overhead