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Packaged, high-power, narrow-linewidth slab-coupled optical waveguide external cavity laser (SCOWECL)

Published in:
IEEE Photonics Technol. Lett., Vol. 23, No. 14, 15 July 2011.
Topic:

Summary

We report the demonstration of an InGaAlAs/InP quantum-well, high-power, low-noise packaged semiconductor external cavity laser (ECL) operating at 1550 nm. The laser comprises a double-pass, curved-channel slab-coupled optical waveguide amplifier (SCOWA) coupled to a narrow-bandwidth (2.5 GHz) fiber Bragg grating passive cavity using a lensedfiber. At a bias current of 4 A, the ECL produces 370 mW of fiber-coupled output power with a Voigt lineshape having Gaussian and Lorentzian linewidths of 35 kHz and 1 kHz, respectively, and relative intensity noise < -160 dB/Hz from 200 kHz to 10 GHz.
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Summary

We report the demonstration of an InGaAlAs/InP quantum-well, high-power, low-noise packaged semiconductor external cavity laser (ECL) operating at 1550 nm. The laser comprises a double-pass, curved-channel slab-coupled optical waveguide amplifier (SCOWA) coupled to a narrow-bandwidth (2.5 GHz) fiber Bragg grating passive cavity using a lensedfiber. At a bias current of...

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Eigenspace analysis for threat detection in social networks

Published in:
Int. Conf. on Information Fusion, 5 July 2011.

Summary

The problem of detecting a small, anomalous subgraph within a large background network is important and applicable to many fields. The non-Euclidean nature of graph data, however, complicates the application of classical detection theory in this context. A recent statistical framework for anomalous subgraph detection uses spectral properties of a graph's modularity matrix to determine the presence of an anomaly. In this paper, this detection framework and the related algorithms are applied to data focused on a specific application: detection of a threat subgraph embedded in a social network. The results presented use data created to simulate threat activity among noisy interactions. The detectability of the threat subgraph and its separability from the noise is analyzed under a variety of background conditions in both static and dynamic scenarios.
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Summary

The problem of detecting a small, anomalous subgraph within a large background network is important and applicable to many fields. The non-Euclidean nature of graph data, however, complicates the application of classical detection theory in this context. A recent statistical framework for anomalous subgraph detection uses spectral properties of a...

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Maximum directivity of a series-fed microstrip array antenna for wireless application

Published in:
AP-S/URSI 2011, IEEE Antennas and Propagation Society Int. Symp. and USNC/URSI National Radio Science Mtg., 3-8 July 2011, pp. 1327-1330.

Summary

An omnidirectional colinear microstrip array antenna is modeled as a ladder network. A formula is derived for the maximum directivity of a series-fed colinear antenna with an infinite number of ladder sections. It is shown that the maximum directivity is asymptotically limited and depends upon the product of the seriece impedance and shunt admittance of the equivalent ladder network. The result is verified by simulation and experiment.
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Summary

An omnidirectional colinear microstrip array antenna is modeled as a ladder network. A formula is derived for the maximum directivity of a series-fed colinear antenna with an infinite number of ladder sections. It is shown that the maximum directivity is asymptotically limited and depends upon the product of the seriece...

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Cryogenic Yb3+ -doped materials for pulsed solid-state laser applications

Published in:
Opt. Mat. Expr., Vol. 1, No. 3, 1 July 2011, pp. 434-450.

Summary

We review recent progress in pulsed lasers using cryogenically-cooled Yb3+ -doped gain media, with an emphasis on high average power. Recent measurements of thermo-optic properties for various host material at both room and cryogenic temperature are presented, including themral conductivity, coefficient of thermal expansion and refractive index. Host materials reviewed include Y2O3, Lu2O3, Sc2O3, YLF, YSO, GSAG, and YVO4. We report on performance of several cryogenic Yb lasers operating at 5-kHz pulse repetition frequency (PRF) a Q-switched Yb:YAG laser is shwon to operate at 114-W average power, with 16-ns pulse duration. A chirped pulse amplifier achieves 115-W output using a composite Yb:YAG/Yb:GSAG amplifier, with pulses that compress to 1.6 ps. Finally, a high-average-power femtosecond laser based on Yb:YLF is discussed, with results for a 10-W regenerative amplifier at 10-kHZ PRF.
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Summary

We review recent progress in pulsed lasers using cryogenically-cooled Yb3+ -doped gain media, with an emphasis on high average power. Recent measurements of thermo-optic properties for various host material at both room and cryogenic temperature are presented, including themral conductivity, coefficient of thermal expansion and refractive index. Host materials reviewed...

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Noise spectroscopy through dynamical decoupling with a superconducting flux qubit

Summary

Quantum coherence in natural and artificial spin systems is fundamental to applications ranging from quantum information science to magnetic-resonance imaging and identification. Several multipulse control sequences targeting generalized noise models have been developed to extend coherence by dynamically decoupling a spin system from its noisy environment. In any particular implementation, however, the efficacy of these methods is sensitive to the specific frequency distribution of the noise, suggesting that these same pulse sequences could also be used to probe the noise spectrum directly. Here we demonstrate noise spectroscopy by means of dynamical decoupling using a superconducting qubit with energy-relaxation time T1 D12 us. We first demonstrate that dynamical decoupling improves the coherence time T2 in this system up to the T2 D2 T1 limit (pure dephasing times exceeding 100 us), and then leverage its filtering properties to probe the environmental noise over a frequency (f) range 0.2-20 MHz, observing a 1=fa distribution with a < 1. The characterization of environmental noise has broad utility for spin-resonance applications, enabling the design of optimized coherent-control methods, promoting device and materials engineering, and generally improving coherence.
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Summary

Quantum coherence in natural and artificial spin systems is fundamental to applications ranging from quantum information science to magnetic-resonance imaging and identification. Several multipulse control sequences targeting generalized noise models have been developed to extend coherence by dynamically decoupling a spin system from its noisy environment. In any particular implementation...

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Accounting for state uncertainty in collision avoidance

Published in:
J. Guidance, Control, and Dynamics, Vol. 34, No. 4, July-August 2011, pp. 951-960.

Summary

An important consideration in the development of aircraft collision avoidance systems is how to account for state uncertainty due to sensor limitations and noise. However, many collision avoidance systems simply use point estimates of the state instead of leveraging the full posterior state distribution. Recently, there has been work on applying decision-theoretic methods to collision avoidance, but the importance of accommodating state uncertainty has not yet been well studied. This paper presents a computationally efficient framework for accounting for state uncertainty based on dynamic programming. Examination of characteristic encounters and Monte Carlo simulations demonstrates that properly handling state uncertainty rather than simply using point estimates can significantly enhance safety and improve robustness to sensor error.
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Summary

An important consideration in the development of aircraft collision avoidance systems is how to account for state uncertainty due to sensor limitations and noise. However, many collision avoidance systems simply use point estimates of the state instead of leveraging the full posterior state distribution. Recently, there has been work on...

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Pre-discovery observations of disrupting asteroid P/2010 A2

Published in:
Astronom. J., Vol. 142, No. 29, July 2011.

Summary

Solar system object P/2010 A2 is the first-noticed example of the aftermath of a recently disrupted asteroid, probably resulting from a collision. Nearly a year elapsed between its inferred initiation in early 2009 and its eventual detection in early 2010. Here, we use new observations to assess the factors underlying the visibility, especially to understand the delayed discovery. We present pre-discovery observations from the LINEAR telescope and set limits to the early-time brightness from SOHO and STEREO satellite coronagraphic images. Consideration of the circumstances of discovery of P/2010 A2 suggests that similar objects must be common, and that future all-sky surveys will reveal them in large numbers.
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Summary

Solar system object P/2010 A2 is the first-noticed example of the aftermath of a recently disrupted asteroid, probably resulting from a collision. Nearly a year elapsed between its inferred initiation in early 2009 and its eventual detection in early 2010. Here, we use new observations to assess the factors underlying...

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Collision avoidance system optimization with probabilistic pilot response models

Published in:
2011 American Control Conf., 29 June-1 July 2011, pp. 2765-2770.

Summary

All large transport aircraft are required to be equipped with a collision avoidance system that instructs pilots how to maneuver to avoid collision with other aircraft. Uncertainty in the compliance of pilots to advisories makes designing collision avoidance logic challenging. Prior work has investigated formulating the problem as a Markov decision process and solving for the optimal collision avoidance strategy using dynamic programming. The logic was optimized to a pilot response model in which the pilot responds deterministically to all alerts. Deviation from this model during flight can degrade safety. This paper extends the methodology to include probabilistic pilot response models that capture the variability in pilot behavior in order to enhance robustness.
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Summary

All large transport aircraft are required to be equipped with a collision avoidance system that instructs pilots how to maneuver to avoid collision with other aircraft. Uncertainty in the compliance of pilots to advisories makes designing collision avoidance logic challenging. Prior work has investigated formulating the problem as a Markov...

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Anomalous subgraph detection via sparse principal component analysis

Published in:
Proc. 2011 IEEE Statistical Signal Processing Workshop (SSP), 28-30 June 2011, pp. 485-488.

Summary

Network datasets have become ubiquitous in many fields of study in recent years. In this paper we investigate a problem with applicability to a wide variety of domains - detecting small, anomalous subgraphs in a background graph. We characterize the anomaly in a subgraph via the well-known notion of network modularity, and we show that the optimization problem formulation resulting from our setup is very similar to a recently introduced technique in statistics called Sparse Principal Component Analysis (Sparse PCA), which is an extension of the classical PCA algorithm. The exact version of our problem formulation is a hard combinatorial optimization problem, so we consider a recently introduced semidefinite programming relaxation of the Sparse PCA problem. We show via results on simulated data that the technique is very promising.
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Summary

Network datasets have become ubiquitous in many fields of study in recent years. In this paper we investigate a problem with applicability to a wide variety of domains - detecting small, anomalous subgraphs in a background graph. We characterize the anomaly in a subgraph via the well-known notion of network...

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Efficient reconstruction of block-sparse signals

Published in:
IEEE Statistical Signal Processing Workshop, 28-30 June 2011.

Summary

In many sparse reconstruction problems, M observations are used to estimate K components in an N dimensional basis, where N > M ¿ K. The exact basis vectors, however, are not known a priori and must be chosen from an M x N matrix. Such underdetermined problems can be solved using an l2 optimization with an l1 penalty on the sparsity of the solution. There are practical applications in which multiple measurements can be grouped together, so that K x P data must be estimated from M x P observations, where the l1 sparsity penalty is taken with respect to the vector formed using the l2 norms of the rows of the data matrix. In this paper we develop a computationally efficient block partitioned homotopy method for reconstructing K x P data from M x P observations using a grouped sparsity constraint, and compare its performance to other block reconstruction algorithms.
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Summary

In many sparse reconstruction problems, M observations are used to estimate K components in an N dimensional basis, where N &gt; M ¿ K. The exact basis vectors, however, are not known a priori and must be chosen from an M x N matrix. Such underdetermined problems can be solved...

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