Observation of String Breaking in QCD

We numerically investigate the transition of the static quark-antiquark string into a static-light meson-antimeson system. Improving noise reduction techniques, we are able to resolve the signature of string breaking dynamics for n_f=2 lattice QCD at zero temperature. This result can be related to properties of quarkonium systems. We also study short-distance interactions between two static-light mesons.Comment: 27 pages, 22 figures, changed decimal place of errors in 3 entries of Table, corrected reference

String breaking

We numerically investigate the transition of the static quark-antiquark string into a static-light meson-antimeson system. Improving noise reduction techniques, we are able to resolve the signature of string breaking dynamics for Nf=2 lattice QCD at zero temperature. We discuss the lattice techniques used and present results on energy levels and mixing angle of the static two-state system. We visualize the action density distribution in the region of string breaking as a function of the static colour source-antisource separation. The results can be related to properties of quarkonium systems.Comment: 8 pages, Talk given at the Workshop on Computational Hadron Physics, Nicosia, Cyprus, 14--17 September 200

Improving Noise Robustness in Subspace-based Joint Sparse Recovery

In a multiple measurement vector problem (MMV), where multiple signals share a common sparse support and are sampled by a common sensing matrix, we can expect joint sparsity to enable a further reduction in the number of required measurements. While a diversity gain from joint sparsity had been demonstrated earlier in the case of a convex relaxation method using an $l_1/l_2$ mixed norm penalty, only recently was it shown that similar diversity gain can be achieved by greedy algorithms if we combine greedy steps with a MUSIC-like subspace criterion. However, the main limitation of these hybrid algorithms is that they often require a large number of snapshots or a high signal-to-noise ratio (SNR) for an accurate subspace as well as partial support estimation. One of the main contributions of this work is to show that the noise robustness of these algorithms can be significantly improved by allowing sequential subspace estimation and support filtering, even when the number of snapshots is insufficient. Numerical simulations show that a novel sequential compressive MUSIC (sequential CS-MUSIC) that combines the sequential subspace estimation and support filtering steps significantly outperforms the existing greedy algorithms and is quite comparable with computationally expensive state-of-art algorithms

Learning to Extract Distributed Polarization Sensing Data from Noisy Jones Matrices

We consider the problem of recovering spatially resolved polarization information from receiver Jones matrices. We introduce a physics-based learning approach, improving noise resilience compared to previous inverse scattering methods, while highlighting challenges related to model overparameterization.Comment: Will be appeared in OFC 202

Design techniques for high performance optical wireless front-ends

Wireless optical networks usually have demanding specifications in terms of bandwidth, dynamic range and sensitivity. The front-end is a critical element for the fulfillment of these demands. This paper discusses several design aspects of front-ends for optical wireless communications, covering techniques for achieving high gains, high input dynamic ranges, improving noise performance, and reducing electromagnetic interference (EMI). The paper further presents some experimental results of many of the techniques here described. The cumulative usage of those techniques significantly increases system performance, in terms of sensitivity, power and bandwidth even with low cost, CMOS technologies