Spectral characterization of the LANDSAT Thematic Mapper sensors

The spectral coverage characteristics of the two thematic mapper instruments were determined by analyses of spectral measurements of the optics, filters, and detectors. The following results are presented: (1) band 2 and 3 flatness was slightly below specification, and band 7 flatness was below specification; (2) band 5 upper-band edge was higher than specifications; (3) band 2 band edges were shifted upward about 9 nm relative to nominal; and (4) band 4, 5, and 7 lower band edges were 16 to 18 nm higher then nominal

Spectral characterization of the LANDSAT-D multispectral scanner subsystems

Relative spectral response data for the multispectral scanner subsystems (MSS) to be flown on LANDSAT-D and LANDSAT-D backup, the protoflight and flight models, respectively, are presented and compared to similar data for the Landsat 1,2, and 3 subsystems. Channel-bychannel (six channels per band) outputs for soil and soybean targets were simulated and compared within each band and between scanners. The two LANDSAT-D scanners proved to be nearly identical in mean spectral response, but they exhibited some differences from the previous MSS's. Principal differences between the spectral responses of the D-scanners and previous scanners were: (1) a mean upper-band edge in the green band of 606 nm compared to previous means of 593 to 598 nm; (2) an average upper-band edge of 697 nm in the red band compared to previous averages of 701 to 710 nm; and (3) an average bandpass for the first near-IR band of 702-814 nm compared to a range of 693-793 to 697-802 nm for previous scanners. These differences caused the simulated D-scanner outputs to be 3 to 10 percent lower in the red band and 3 to 11 percent higher in the first near-IR band than previous scanners for the soybeans target. Otherwise, outputs from soil and soybean targets were only slightly affected. The D-scanners were generally more uniform from channel to channel within bands than previous scanners

Introduction to Thematic Mapper investigations. Section 1: Radiometry. Section 2: Geometry

An overview of papers which deal with radiometric characterization of the TM sensor is presented. Spectral characteristics are summarized. The geometric accuracy of TM are also examined. Aspects of prelaunch and post launch sensor performance, ground processing techniques, and error correction are also investigated

Characterization of the LANDSAT sensors' spatial responses

The characteristics of the thematic mapper (TM) and multispectral scanner (MSS) sensors on LANDSATs 4 and 5 affecting their spatial responses are described, and functions defining the response of the system to an arbitrary input spatial pattern are derived, i.e., transfer functions (TF) and line spread functions (LSF). These design LSF's and TF's were modified based on prelaunch component and system measurements to provide improved estimates. Prelaunch estimates of LSF/FT's are compared to in-orbit estimates. For the MSS instruments, only limited prelaunch scan direction square-wave response (SWR) data were available. Design estimates were modified by convolving in Gaussian blur till the derived LSF/TF's produced SWR's comparable to the measurements. The two MSS instruments were comparable at their temperatures of best focus; separate calculations were performed for bands 1 and 3, band 2 and band 4. The pre-sample nadir effective instantaneous field's of view (EIFOV's) based on the .5 modulation transfer function (MTF) criteria vary from 70 to 75 meters in the track direction and 79 to 82 meters in the scan direction. For the TM instruments more extensive prelaunch measurements were available. Bands 1 to 4, 5 and 7, and 6 were handled separately as were the two instruments. Derived MTF's indicate nadir pre-sample EIFOV's of 32 to 33 meter track (bands 1 to 5, 7) and 36 meter scan (bands 1 to 5, 7) and 1245 meter track (band 6) and 141 meter scan (band 6) for both TM's

Remarks on Duality Transformations and Generalized Stabilizer States

We consider the transformation of Hamilton operators under various sets of quantum operations acting simultaneously on all adjacent pairs of particles. We find mappings between Hamilton operators analogous to duality transformations as well as exact characterizations of ground states employing non-Hermitean eigenvalue equations and use this to motivate a generalization of the stabilizer formalism to non-Hermitean operators. The resulting class of states is larger than that of standard stabilizer states and allows for example for continuous variation of local entropies rather than the discrete values taken on stabilizer states and the exact description of certain ground states of Hamilton operators.Comment: Contribution to Special Issue in Journal of Modern Optics celebrating the 60th birthday of Peter Knigh

GANVO: Unsupervised Deep Monocular Visual Odometry and Depth Estimation with Generative Adversarial Networks

In the last decade, supervised deep learning approaches have been extensively employed in visual odometry (VO) applications, which is not feasible in environments where labelled data is not abundant. On the other hand, unsupervised deep learning approaches for localization and mapping in unknown environments from unlabelled data have received comparatively less attention in VO research. In this study, we propose a generative unsupervised learning framework that predicts 6-DoF pose camera motion and monocular depth map of the scene from unlabelled RGB image sequences, using deep convolutional Generative Adversarial Networks (GANs). We create a supervisory signal by warping view sequences and assigning the re-projection minimization to the objective loss function that is adopted in multi-view pose estimation and single-view depth generation network. Detailed quantitative and qualitative evaluations of the proposed framework on the KITTI and Cityscapes datasets show that the proposed method outperforms both existing traditional and unsupervised deep VO methods providing better results for both pose estimation and depth recovery.Comment: ICRA 2019 - accepte

Documentation of Infanticide and Cannibalism in Bald Eagles

Non-kin infanticide, the killing of dependent young by unrelated conspecifics, occurs in a wide array of taxonomic groups including mammals, insects, fish, and birds (Hrdy 1979, Hrdy and Hausfater 1984). Several hypotheses have been proposed to explain this behavior including the removal of potential competitors to gain access to limited resources such as nesting territories and food (Hrdy 1979)..

Quantum secret sharing with qudit graph states

We present a unified formalism for threshold quantum secret sharing using graph states of systems with prime dimension. We construct protocols for three varieties of secret sharing: with classical and quantum secrets shared between parties over both classical and quantum channels.Comment: 13 pages, 12 figures. v2: Corrected to reflect imperfections of (n,n) QQ protocol. Also changed notation from $(n,m)$ to $(k,n)$, corrected typos, updated references, shortened introduction. v3: Updated acknowledgement

Experimental demonstration of a graph state quantum error-correction code

Scalable quantum computing and communication requires the protection of quantum information from the detrimental effects of decoherence and noise. Previous work tackling this problem has relied on the original circuit model for quantum computing. However, recently a family of entangled resources known as graph states has emerged as a versatile alternative for protecting quantum information. Depending on the graph's structure, errors can be detected and corrected in an efficient way using measurement-based techniques. In this article we report an experimental demonstration of error correction using a graph state code. We have used an all-optical setup to encode quantum information into photons representing a four-qubit graph state. We are able to reliably detect errors and correct against qubit loss. The graph we have realized is setup independent, thus it could be employed in other physical settings. Our results show that graph state codes are a promising approach for achieving scalable quantum information processing