Nonlinearity and Noise Effects in Multi-level Signal Millimeter-Wave over Fiber Transmission using Single- and Dual-Wavelength Modulation

We transmit multilevel quadrature amplitude modulation (QAM) data-IEEE 802.16 schemes-at 20 MSps and an orthogonal frequency-division multiplexing (OFDM) 802.11 g signal (54 Mbps) with a 25 GHz millimeter-wave over fiber system, which employs a dual wavelength source, over 20 km of single mode fiber. Downlink data transmission is successfully demonstrated over both optical and wireless (up to 12 m) paths with good error vector magnitude. An analysis of two different schemes, in which data is applied to one (single) and both (dual) of the wavelengths of a dual wavelength source, is carried out. The system performance is analyzed through simulation and a good match with experimental results is obtained. The analysis investigates the impact of Mach-Zehnder modulator (MZM) and RF amplifier nonlinearity and various noise sources, such as laser relative intensity noise, amplified spontaneous emission, thermal, and shot noise. A comparison of single carrier QAM IEEE 802.16 and OFDM in terms of their sensitivity to the distortions from MZM and RF amplifier nonlinearity is also presented

The Devil is in the Decoder: Classification, Regression and GANs

Many machine vision applications, such as semantic segmentation and depth prediction, require predictions for every pixel of the input image. Models for such problems usually consist of encoders which decrease spatial resolution while learning a high-dimensional representation, followed by decoders who recover the original input resolution and result in low-dimensional predictions. While encoders have been studied rigorously, relatively few studies address the decoder side. This paper presents an extensive comparison of a variety of decoders for a variety of pixel-wise tasks ranging from classification, regression to synthesis. Our contributions are: (1) Decoders matter: we observe significant variance in results between different types of decoders on various problems. (2) We introduce new residual-like connections for decoders. (3) We introduce a novel decoder: bilinear additive upsampling. (4) We explore prediction artifacts

Risk-Sensitive RL with Optimized Certainty Equivalents via Reduction to Standard RL

We study Risk-Sensitive Reinforcement Learning (RSRL) with the Optimized Certainty Equivalent (OCE) risk, which generalizes Conditional Value-at-risk (CVaR), entropic risk and Markowitz's mean-variance. Using an augmented Markov Decision Process (MDP), we propose two general meta-algorithms via reductions to standard RL: one based on optimistic algorithms and another based on policy optimization. Our optimistic meta-algorithm generalizes almost all prior RSRL theory with entropic risk or CVaR. Under discrete rewards, our optimistic theory also certifies the first RSRL regret bounds for MDPs with bounded coverability, e.g., exogenous block MDPs. Under discrete rewards, our policy optimization meta-algorithm enjoys both global convergence and local improvement guarantees in a novel metric that lower bounds the true OCE risk. Finally, we instantiate our framework with PPO, construct an MDP, and show that it learns the optimal risk-sensitive policy while prior algorithms provably fail

Dealing honestly with an honest mistake

A 70-year-old woman was admitted for a symptomatic left iliofemoral deep vein thrombosis. She underwent percutaneous mechanical thrombectomy, followed by overnight thrombolysis. The next day her clot had resolved, and a culprit left iliac vein stenosis was identified. After stent placement, a heparin infusion was initiated and the patient was taken back to the ward. At 11 the evening after the procedure, the resident on call was contacted to verify the written order. The resident stated that the heparin dose was to be 250 U/h; however, the nurse documented 2500 U/h and changed the infusion pump at the patient's bedside. At 5:30 the next morning, the resident was notified that the patient's partial thromboplastin time was >300 seconds and promptly shut off the heparin infusion. No noticeable adverse events occurred because of the high heparin dosing. The charge nurse was notified, as was risk management. What should the patient be told

THE STELLAR OBLIQUITY, PLANET MASS, AND VERY LOW ALBEDO OF QATAR-2 FROM K2 PHOTOMETRY

The Qatar-2 transiting exoplanet system was recently observed by the {\it Kepler} telescope as part of {\it K2} Campaign 6. The photometric time series has one-minute time sampling and a precision of about 690~ppm, after filtering out artifacts and spurious trends. We identify dozens of starspot-crossing events, when the planet eclipsed a relatively dark region of the stellar photosphere. The observed patterns in the sequence of these events demonstrate that the planet always transits over the same range of stellar latitudes, and therefore that the stellar obliquity is less than about 10$^\circ$. We support this conclusion with two different modeling approaches: one based on explicit identification and timing of the events, and the other based on fitting the light curves with a spotted-star model. We are also able to refine the usual transit parameters and measure the stellar rotation period ($18.5 \pm 1.9$~days), corresponding to a 'gyrochronological' age of $1.4 \pm 0.3$ Gyr. Coherent flux variations with the same period as the transits are seen throughout the entire light curve. These variations are well modeled as the combined effects of ellipsoidal light variations ($17.4 \pm 2.8$~ppm) and Doppler boosting ($11.9 \pm 2.5$~ppm). The magnitudes of these effects are both consistent with a planetary mass of $2.6 \pm 0.5~ M_{\text{Jup}}$, which is in turn consistent with the mass determined by the Doppler technique. No occultations are detected, giving a 2$\sigma$ upper limit of $0.013$ on the planet's visual geometric albedo. The measured transit times are consistent with a constant orbital period. In particular we find no evidence for orbital decay, although we are only able to place a weak lower bound on the relevant tidal quality factor: $Q'_\star > 1.5\times 10^4$~(95\% confidence).Comment: 13 pages, 8 figures, 6 tables. Accepted to A