Robust 1-Bit Compressed Sensing via Hinge Loss Minimization

This work theoretically studies the problem of estimating a structured high-dimensional signal $x_0 \in \mathbb{R}^n$ from noisy $1$-bit Gaussian measurements. Our recovery approach is based on a simple convex program which uses the hinge loss function as data fidelity term. While such a risk minimization strategy is very natural to learn binary output models, such as in classification, its capacity to estimate a specific signal vector is largely unexplored. A major difficulty is that the hinge loss is just piecewise linear, so that its "curvature energy" is concentrated in a single point. This is substantially different from other popular loss functions considered in signal estimation, e.g., the square or logistic loss, which are at least locally strongly convex. It is therefore somewhat unexpected that we can still prove very similar types of recovery guarantees for the hinge loss estimator, even in the presence of strong noise. More specifically, our non-asymptotic error bounds show that stable and robust reconstruction of $x_0$ can be achieved with the optimal oversampling rate $O(m^{-1/2})$ in terms of the number of measurements $m$. Moreover, we permit a wide class of structural assumptions on the ground truth signal, in the sense that $x_0$ can belong to an arbitrary bounded convex set $K \subset \mathbb{R}^n$. The proofs of our main results rely on some recent advances in statistical learning theory due to Mendelson. In particular, we invoke an adapted version of Mendelson's small ball method that allows us to establish a quadratic lower bound on the error of the first order Taylor approximation of the empirical hinge loss function

Deducing effective light transport parameters in optically thin systems

We present an extensive Monte Carlo study on light transport in optically thin slabs, addressing both axial and transverse propagation. We completely characterize the so-called ballistic-to-diffusive transition, notably in terms of the spatial variance of the transmitted/reflected profile. We test the validity of the prediction cast by diffusion theory, that the spatial variance should grow independently of absorption and, to a first approximation, of the sample thickness and refractive index contrast. Based on a large set of simulated data, we build a freely available look-up table routine allowing reliable and precise determination of the microscopic transport parameters starting from robust observables which are independent of absolute intensity measurements. We also present the Monte Carlo software package that was developed for the purpose of this study

Robust 1-bit compressed sensing and sparse logistic regression: A convex programming approach

This paper develops theoretical results regarding noisy 1-bit compressed sensing and sparse binomial regression. We show that a single convex program gives an accurate estimate of the signal, or coefficient vector, for both of these models. We demonstrate that an s-sparse signal in R^n can be accurately estimated from m = O(slog(n/s)) single-bit measurements using a simple convex program. This remains true even if each measurement bit is flipped with probability nearly 1/2. Worst-case (adversarial) noise can also be accounted for, and uniform results that hold for all sparse inputs are derived as well. In the terminology of sparse logistic regression, we show that O(slog(n/s)) Bernoulli trials are sufficient to estimate a coefficient vector in R^n which is approximately s-sparse. Moreover, the same convex program works for virtually all generalized linear models, in which the link function may be unknown. To our knowledge, these are the first results that tie together the theory of sparse logistic regression to 1-bit compressed sensing. Our results apply to general signal structures aside from sparsity; one only needs to know the size of the set K where signals reside. The size is given by the mean width of K, a computable quantity whose square serves as a robust extension of the dimension.Comment: 25 pages, 1 figure, error fixed in Lemma 4.

Tunable superlattice p-i-n photodetectors: characteristics, theory, and application

Extended measurements and theory on the recently developed monolithic wavelength demultiplexer consisting of voltage-tunable superlattice p-i-n photodetectors in a waveguide confirmation are discussed. It is shown that the device is able to demultiplex and detect two optical signals with a wavelength separation of 20 nm directly into different electrical channels at a data rate of 1 Gb/s and with a crosstalk attenuation varying between 20 and 28 dB, depending on the polarization. The minimum acceptable crosstalk attenuation at a data rate of 100 Mb/s is determined to be 10 dB. The feasibility of using the device as a polarization angle sensor for linearly polarized light is also demonstrated. A theory for the emission of photogenerated carriers out of the quantum wells is included, since this is potentially a speed limiting mechanism in these detectors. It is shown that a theory of thermally assisted tunneling by polar optical phonon interaction is able to predict emission times consistent with the observed temporal response

Optimization of InP APDs for high-speed lightwave systems

Calculations based on a rigorous analytical model are carried out to optimize the width of the indium phosphide avalanche region in high-speed direct-detection avalanche photodiode-based optical receivers. The model includes the effects of intersymbol interference (ISI), tunneling current, avalanche noise, and its correlation with the stochastic avalanche duration, as well as dead space. A minimum receiver sensitivity of -28 dBm is predicted at an optimal width of 0.18 mu m and an optimal gain of approximately 13, for a 10 Gb/s communication system, assuming a Johnson noise level of 629 noise electrons per bit. The interplay among the factors controlling the optimum sensitivity is confirmed. Results show that for a given transmission speed, as the device width decreases below an optimum value, increased tunneling current outweighs avalanche noise reduction due to dead space, resulting in an increase in receiver sensitivity. As the device width increases above its optimum value, the receiver sensitivity increases as device bandwidth decreases, causing ISI to dominate avalanche noise and tunneling current shot noise

Enhancing capacity of coherent optical information storage and transfer in a Bose-Einstein condensate

Coherent optical information storage capacity of an atomic Bose-Einstein condensate is examined. Theory of slow light propagation in atomic clouds is generalized to short pulse regime by taking into account group velocity dispersion. It is shown that the number of stored pulses in the condensate can be optimized for a particular coupling laser power, temperature and interatomic interaction strength. Analytical results are derived for semi-ideal model of the condensate using effective uniform density zone approximation. Detailed numerical simulations are also performed. It is found that axial density profile of the condensate protects the pulse against the group velocity dispersion. Furthermore, taking into account finite radial size of the condensate, multi-mode light propagation in atomic Bose-Einstein condensate is investigated. The number of modes that can be supported by a condensate is found. Single mode condition is determined as a function of experimentally accessible parameters including trap size, temperature, condensate number density and scattering length. Quantum coherent atom-light interaction schemes are proposed for enhancing multi-mode light propagation effects.Comment: 12pages. Laser Physics, in pres