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At least 559 records · Page 31

A Survey of Massive Planets by Direct Imaging with Advanced Adaptive Optics

The observations are completed. The observing that has been done essentially on the Canada-France-Hawaii Telescope with the PUEO adaptive optics system, is sufficient to identify approximately 10 Jupiter masses objects around the selected targets. A small amount of data was also collected on the Gemini Telescope with the Hokupa'a adaptive optics system. For most of the stars of the sample, about 30mn of exposure time was collected per epoch, with at least 2 epochs. About 15% of the stars of the sample did not meet these requirements, due to observing difficulties listed below: (1) Guide star is too faint for the AO system; (2) The guide star is a close double (about 0.5 to 1 inch separation), which makes it unsuitable for AO guiding; (3) For a few stars, weather and observing constraints could not allow observations.

Owen, Tobias C.↗

Vector adaptive predictive coder for speech and audio

A real-time vector adaptive predictive coder which approximates each vector of K speech samples by using each of M fixed vectors in a first codebook to excite a time-varying synthesis filter and picking the vector that minimizes distortion. Predictive analysis for each frame determines parameters used for computing from vectors in the first codebook zero-state response vectors that are stored at the same address (index) in a second codebook. Encoding of input speech vectors s.sub.n is then carried out using the second codebook. When the vector that minimizes distortion is found, its index is transmitted to a decoder which has a codebook identical to the first codebook of the decoder. There the index is used to read out a vector that is used to synthesize an output speech vector s.sub.n. The parameters used in the encoder are quantized, for example by using a table, and the indices are transmitted to the decoder where they are decoded to specify transfer characteristics of filters used in producing the vector s.sub.n from the receiver codebook vector selected by the vector index transmitted.

Chen, Juin-Hwey↗

A Numerical Investigation of Parachute Deployment in Supersonic Flow

A validated computational fluid-structure interaction method applied to supersonic parachute inflation is extended to consider a unique, parallel self-contact algorithm, porosity interface conditions on the canopy, improved flow field sampling procedures for obtaining quality loading on the parachute canopy, adaptive mesh refinement, and improved treatment of thin geometries in an immersed boundary framework. These extensions are discussed in detail and demonstrated individually on test problems. Finally, the developments are brought together for demonstration on a sub-scale MSL parachute geometry.

Boustani, Jonathan↗

Multi-Channel Correlator Array-Fed Microwave Radiometer

Multiband passive microwave imagery in X to W Bands has a nearly 40-year history of utilization for measurement of multiple geophysical parameters (e.g., precipitation rate, ocean surface wind speed, sea ice concentration, and land surface temperature). Spatial resolution is limited by aperture size, and although aperture sizes have grown to 1-2 meters, current capability will not meet future spatial resolution needs. As aperture size increases, new antenna feed techniques are needed to maintain contiguous coverage and obtain Nyquist sampling. Here we apply the correlator array fed radiometer architecture adapted from radio astronomy and show how it can meet emerging needs. Simulation results of a 0.8-m, 36.5-GHz, array-fed reflector (equivalent to 20 meters at 1.41 GHz) show the feasibility of creating multiple over-lapping beams.

Microwave radiometer↗

Contextual Active Online Model Selection with Expert Advice

How can we collect the most useful labels to learn a model selection policy, when presented with arbitrary heterogeneous data streams? In this paper, we formulate this task as a contextual active model selection problem, where at each round the learner receives an unlabeled data point along with a context. The goal is to output the best model for any given context without obtaining an excessive amount of labels. In particular, we focus on the task of selecting pre-trained classifiers, and propose a contextual active model selection algorithm (CAMS), which relies on a novel uncertainty sampling query criterion defined on a given policy class for adaptive model selection. In comparison to prior art, our algorithm does not assume a globally optimal model. We provide rigorous theoretical analysis for the regret and query complexity under both adversarial and stochastic settings. Our experiments on several benchmark classification datasets demonstrate the algorithm’s effectiveness in terms of both regret and query complexity. Notably, to achieve the same accuracy, CAMS incurs less than 10% of the label cost when compared to the best online model selection baselines on CIFAR10.

Liu, Xuefeng↗

Development of Fusion Neutronics Methodology, Software, and Testing Facility in FDS Team

Fusion neutronics including methodology, software, experiments, etc. is studied concerning the generation, utilizing and protection of neutrons in fusion facilities. Achievements have been made in the past decades to solve the new problems fusion neutronics. However there is still some way to go such as following. Automatic modeling method based on CAD has been developed to avoid the heavy burden of manual geometry description. The pre-processing costs much time to simplify the CAD model for converting to Constructive Solid Geometry (CSG), 2D or 3D mesh based geometry. This problem has become a new focus. Deep penetration of radiation shielding is notable problem for fusion. Adaptive variance reduction methods such as Consistent Adjoint Driven Importance Sampling (CADIS) were developed to accelerate convergence. However the gap still exists between engineering requirements and current methodology. The geometry simplification, homogenizing based tally, error in nuclear data and error propagation in coupled calculation, etc., causes considerable uncertainty, which leads to 'safety factor' applied in simulation results to achieve required safety margin. It can significantly raise the cost and even makes it impractical to initiate the fusion facilities. Uncertainty qualification, error analysis and error propagation problem should be studied. New methodology and software should be validated. For example the (n,p), (n,a), (n,t) cross section of Cu, Fe, W, Ni which is important for evaluation of material radiation damage is absent. The validation of neutronics properties of special components such as first wall, blanket and coil are needed. The D-T fusion neutron generator can directly represent the neutron environment in fusion reactors. However the neutron yield is several orders of magnitudes lower than requirements. To resolve obstacles in fusion neutronics, broad improvements of methodology, software and testing facility have been achieved by FDS Team in recent years and the main progress was introduced in this paper.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Multiclass Continuous Correspondence Learning

We extend the Structural Correspondence Learning (SCL) domain adaptation algorithm of Blitzer er al. to the realm of continuous signals. Given a set of labeled examples belonging to a 'source' domain, we select a set of unlabeled examples in a related 'target' domain that play similar roles in both domains. Using these 'pivot samples, we map both domains into a common feature space, allowing us to adapt a classifier trained on source examples to classify target examples. We show that when between-class distances are relatively preserved across domains, we can automatically select target pivots to bring the domains into correspondence.

correspondence learning↗

CV4Quantum: Reducing the Sampling Overhead in Probabilistic Error Cancellation Using Control Variates

Quasiprobabilistic decompositions (QPDs) play a key role in maximizing the utility of near-term quantum hardware. For example, Probabilistic Error Cancellation (PEC) (an error mitigation technique) and circuit cutting (which enables large quantum computations to be performed on quantum hardware with a limited number of qubits) both involve QPDs. Computations based on QPDs typically incur large sampling overheads that grow exponentially with the number of error-terms mitigated or number of circuit-cuts employed, limiting their practical feasibility. In this work, we adapt the control variates variance reduction technique from the statistics literature in order to reduce the sampling overhead in QPD-based computations. We demonstrate our method using simulation experiments that mimic a realistic PEC scenario. In our experiments, we observed a more than 50% reduction in the number of samples needed to achieve a given precision, in more than 50% of the PEC-based estimations performed in the study when using our approach. We discuss how future research on constructing good control variates can lead to even stronger sampling overhead reduction.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Enumeration and Fluorescence In Situ Hybridization of Microbial Bioburden on Cleanroom Surfaces

Introduction: Microorganisms are everywhere on Earth, even in the cleanest of places. Spacecraft assembly cleanrooms can harbor low levels of living and dead microbial cells (e.g., [1,2]), and cleanroom bioburden can also include organic molecules from industrial sources and in situ biomass. Life detection missions require careful attention to avoid contaminants that can be easily convoluted with analytical targets. We are evaluating epifluorescent microscopy and fluorescence in situ hybridization (FISH) as methods to complement organic contamination detection techniques. Epifluorescent cell counting offers an accurate and cost-effective way to quantify low levels of surface biomass. FISH could allow for the identification of residual organisms, and can be targeted to detect active populations of specific organisms such as bacteria known to resist cleaning procedures. This effort is part of a larger study that is concentrated on characterizing the surface and airborne molecular organic contamination background in Johnson Space Center (JSC) Astromaterials curation laboratories and Goddard Space Flight Center (GSFC) spacecraft assembly rooms, and understanding contaminants in the context of cleaning procedures and residual bioburden. Methods: Samples were collected by swabbing surfaces in ISO 5 and ISO 7 equivalent cleanrooms at JSC. Swabs for FISH were fixed in 4% paraformaldehyde (PFA) for 3 hours and then stored in 1:1 ethanol:PBS, while swabs for cell counting were stored in 4% PFA until analysis to avoid any cell loss during centrifugation that could impact quantification of very low biomass samples. Cell counting was performed with SYBR Gold as in [3], but adapted for very low biomass. FISH was performed as in [4], using DAPI as a counterstain for all DNA-containing cells. Negative controls included wells with no probe applied, to test for natural fluorescence, as well as the nonsense probe NONEUB (reverse complement of EUB338) to evaluate non-specific probe binding. Results and Discussion: Cleanroom surfaces had 102-103 cells cm-2. The extremely low biomass of these samples was challenging for enumeration, and required careful and routine use of “field” and laboratory blanks. FISH was performed with the general archaeal and bacterial probes ARCH915 and EUB338 (EUBMIX, [4]), probe GAMBET ([4]), and PSE227, which targets the genus Pseudomonas [5]). The latter two probes were selected because Pseudomonas spp. and other Gammaproteobacteria have not been isolated from cleanroom surfaces but do appear frequently in rRNA gene libraries from these surfaces. While some active bacteria were identified (Fig. 1c), most cells detectable by DAPI did not have a strong or any fluorescent signal (e.g., Fig. 1d), indicating that the vast majority of cells are dead or inactive. This suggests that cleaning protocols are effective at inactivating microbial contaminants, but that dead or inactive cells can remain on surfaces. Cells were often clumped in a weakly autofluorescent matrix, possibly biofilm material (Fig. 1c,d). We also observed other particulate material that was collected by the swabs, including apparent textile fibers (Fig. 1b). Our results are consistent with other studies that show that the bioburden present in clean rooms includes active, dormant, and dead cells. We will discuss how FISH and epifluorescent cell counting could be applied in planetary protection protocols, including the advantages and disadvantages of FISH and cell counting for routine use, as well as different possible applications for more specialized FISH procedures. References: [1] Moissl-Eichinger et al. (2015) Sci Rep, 5, 9156 [2] Hendrickson et al. (2021) Microbiome, 9, 238 [3] Jones et al. (2017) Appl Environ Microbiol, 83, e00909-17 [4] Jones et al. (2015) Appl Environ Microbiol, 81, 1242-1250. [5] Watt et al. (2006) Environ Microbiol, 8, 871-884

C J Huff↗

MPLEx: a Robust and Universal Protocol for Single-Sample Integrative Proteomic, Metabolomic, and Lipidomic Analyses

In systems biology studies, the integration of multiple omics measurements (i.e., genomics, transcriptomics, proteomics, metabolomics, and lipidomics) has been shown to provide a more complete and informative view of biological pathways. Thus, the prospect of extracting different types of molecules (e.g., DNAs, RNAs, proteins, and metabolites) and performing multiple omics measurements on single samples is very attractive, but such studies are challenging due to the fact that the extraction conditions differ according to the molecule type. Here, we adapted an organic solvent-based extraction method that demonstrated broad applicability and robustness, which enabled comprehensive proteomics, metabolomics, and lipidomics analyses from the same sample.

Nakayasu, Ernesto S.↗

Grover-QAOA for 3-SAT: quadratic speedup, fair-sampling, and parameter clustering

Abstract The SAT problem is a prototypical NP-complete problem of fundamental importance in computational complexity theory with many applications in science and engineering; as such, it has long served as an essential benchmark for classical and quantum algorithms. This study shows numerical evidence for a quadratic speedup of the Grover Quantum Approximate Optimization Algorithm (G-QAOA) over random sampling for finding all solutions to 3-SAT (All-SAT) and Max-SAT problems. G-QAOA is less resource-intensive and more adaptable for these problems than Grover’s algorithm, and it surpasses conventional QAOA in its ability to sample all solutions. We show these benefits by classical simulations of many-round G-QAOA on thousands of random 3-SAT instances. We also observe G-QAOA advantages on the IonQ Aria quantum computer for small instances, finding that current hardware suffices to determine and sample all solutions. Interestingly, a single-angle-pair constraint that uses the same pair of angles at each G-QAOA round greatly reduces the classical computational overhead of optimizing the G-QAOA angles while preserving its quadratic speedup. We also find parameter clustering of the angles. The single-angle-pair protocol and parameter clustering significantly reduce obstacles to classical optimization of the G-QAOA angles.

Zhang, Zewen (ORCID:000000032258613X)↗

Improved Compression of Wavelet-Transformed Images

A recently developed data-compression method is an adaptive technique for coding quantized wavelet-transformed data, nominally as part of a complete image-data compressor. Unlike some other approaches, this method admits a simple implementation and does not rely on the use of large code tables. A common data compression approach, particularly for images, is to perform a wavelet transform on the input data, and then losslessly compress a quantized version of the wavelet-transformed data. Under this compression approach, it is common for the quantized data to include long sequences, or runs, of zeros. The new coding method uses prefixfree codes for the nonnegative integers as part of an adaptive algorithm for compressing the quantized wavelet-transformed data by run-length coding. In the form of run-length coding used here, the data sequence to be encoded is parsed into strings consisting of some number (possibly 0) of zeros, followed by a nonzero value. The nonzero value and the length of the run of zeros are encoded. For a data stream that contains a sufficiently high frequency of zeros, this method is known to be more effective than using a single variable length code to encode each symbol. The specific prefix-free codes used are from two classes of variable-length codes: a class known as Golomb codes, and a class known as exponential-Golomb codes. The codes within each class are indexed by a single integer parameter. The present method uses exponential-Golomb codes for the lengths of the runs of zeros, and Golomb codes for the nonzero values. The code parameters within each code class are determined adaptively on the fly as compression proceeds, on the basis of statistics from previously encoded values. In particular, a simple adaptive method has been devised to select the parameter identifying the particular exponential-Golomb code to use. The method tracks the average number of bits used to encode recent runlengths, and takes the difference between this average length and the code parameter. When this difference falls outside a fixed range, the code parameter is updated (increased or decreased). The Golomb code parameter is selected based on the average magnitude of recently encoded nonzero samples. The coding method requires no floating- point operations, and more readily adapts to local statistics than other methods. The method can also accommodate arbitrarily large input values and arbitrarily long runs of zeros. In practice, this means that changes in the dynamic range or size of the input data set would not require a change to the compressor. The algorithm has been tested in computational experiments on test images. A comparison with a previously developed algorithm that uses large code tables (generated via Huffman coding on training data) suggests that the data-compression effectiveness of the present algorithm is comparable to the best performance achievable by the previously developed algorithm.

Kiely, Aaron↗

Exploiting stochastic locality in lattice QCD: hadronic observables and their uncertainties

Abstract Because of the mass gap, lattice QCD simulations exhibit stochastic locality: distant regions of the lattice fluctuate independently. There is a long history of exploiting this to increase statistics by obtaining multiple spatially-separated samples from each gauge field; in the extreme case, we arrive at the master-field approach in which a single gauge field is used. Here we develop techniques for studying hadronic observables using position-space correlators, which are more localized, and compare with the standard time-momentum representation. We also adapt methods for estimating the variance of an observable from autocorrelated Monte Carlo samples to the case of correlated spatially-separated samples.

Physics↗

Adaptive X-ray imaging with reinforcement learning

X-ray imaging is a powerful technique to scan samples in a variety of contexts including biological, environmental and materials science, but commonly requires a synchrotron light source to produce X-rays at sufficient intensity. As these facilities are expensive to operate, the available beam time is limited and always in high demand. Particularly if the illuminated samples are sparse, standard raster scanning methods can be time-consuming, with a majority of that time being spent on areas of the image that carry little information. To increase the efficiency and maximize the information gain for a given time budget, we split the scanning process into a series of steps where previous measurements are used to inform the decision making and adapt the exposure distribution at later stages of the sequence. We formulate this task as a reinforcement learning problem where the goal is to produce a sequence of exposure maps that maximize a predefined scalar metric. We demonstrate the potential of this approach in simulations where the adaptive illumination can accelerate the measurement process by up to an order of magnitude compared with standard raster scanning. Finally, we present the first results from deploying the trained agents on an X-ray fluorescence beamline at the Stanford Synchrotron Radiation Lightsource.

Reinforcement Learning↗

In situ Stripline Electrochemical NMR for Batteries

Here, there exist some long outstanding technical challenges that continue to be of hindrance to fully harnessing the unique investigative advantages of nuclear magnetic resonance (NMR) spectroscopy in the in situ investigation of rechargeable battery chemistry. For instance, the conducting materials and circuitry necessary for an operational battery always deteriorate the coil–based NMR sensitivity when placed inside the coil, and the shape mismatch between them leads to low sample filling factors and even higher detection limits. We report herein a novel and successful adaptation of stripline NMR detection that integrates seamlessly the NMR detection with construction of an electro–chemical device in general (or a battery in particular) which leads to a technique with much higher detection sensitivity, higher sample filling factors, and which is particularly suitable for mass–limited samples.

25 ENERGY STORAGE↗

A search for moderate-redshift survivors from the population of luminous compact passive galaxies at high redshift

From a search of a ∼2400 deg{sup 2} region covered by both the Sloan Digital Sky Survey and UKIRT Infrared Deep Sky Survey databases, we have attempted to identify galaxies at z ∼ 0.5 that are consistent with their being essentially unmodified examples of the luminous passive compact galaxies found at z ∼ 2.5. After isolating good candidates via deeper imaging, we further refine the sample with Keck moderate-resolution spectroscopy and laser guide star adaptive-optics imaging. For four of the five galaxies that so far remain after passing through this sieve, we analyze plausible star-formation histories based on our spectra in order to identify galaxies that may have survived with little modification from the population formed at high redshift. We find two galaxies that are consistent with having formed ≳ 95% of their mass at z > 5. We attempt to estimate masses both from our stellar population determinations and from velocity dispersions. Given the high frequency of small axial ratios, both in our small sample and among samples found at high redshifts, we tentatively suggest that some of the more extreme examples of passive compact galaxies may have prolate morphologies.

79 ASTRONOMY AND ASTROPHYSICS↗

TH-E-17A-06: Anatomical-Adaptive Compressed Sensing (AACS) Reconstruction for Thoracic 4-Dimensional Cone-Beam CT

Purpose: The Feldkamp-Davis-Kress (FDK) algorithm currently used for clinical thoracic 4-dimensional (4D) cone-beam CT (CBCT) reconstruction suffers from noise and streaking artifacts due to projection under-sampling. Compressed sensing theory enables reconstruction of under-sampled datasets via total-variation (TV) minimization, but TV-minimization algorithms such as adaptive-steepest-descent-projection-onto-convex-sets (ASD-POCS) often converge slowly and are prone to over-smoothing anatomical details. These disadvantages can be overcome by incorporating general anatomical knowledge via anatomy segmentation. Based on this concept, we have developed an anatomical-adaptive compressed sensing (AACS) algorithm for thoracic 4D-CBCT reconstruction. Methods: AACS is based on the ASD-POCS framework, where each iteration consists of a TV-minimization step and a data fidelity constraint step. Prior to every AACS iteration, four major thoracic anatomical structures - soft tissue, lungs, bony anatomy, and pulmonary details - were segmented from the updated solution image. Based on the segmentation, an anatomical-adaptive weighting was applied to the TV-minimization step, so that TV-minimization was enhanced at noisy/streaky regions and suppressed at anatomical structures of interest. The image quality and convergence speed of AACS was compared to conventional ASD-POCS using an XCAT digital phantom and a patient scan. Results: For the XCAT phantom, the AACS image represented the ground truth better than the ASD-POCS image, giving a higher structural similarity index (0.93 vs. 0.84) and lower absolute difference (1.1*10{sup 4} vs. 1.4*10{sup 4}). For the patient case, while both algorithms resulted in much less noise and streaking than FDK, the AACS image showed considerably better contrast and sharpness of the vessels, tumor, and fiducial marker than the ASD-POCS image. In addition, AACS converged over 50% faster than ASD-POCS in both cases. Conclusions: The proposed AACS algorithm was shown to reconstruct thoracic 4D-CBCT images more accurately and with faster convergence compared to ASD-POCS. The superior image quality and rapid convergence makes AACS promising for future clinical use.

60 APPLIED LIFE SCIENCES↗

Adaptively pointing spaceborne radar for precipitation measurements

An auxiliary concept of adaptive pointing is presented as an aid to space-based measurements of precipitation using microwave radar. It is recommended that the instantaneous field of view (IFOV) be limited to cloudy regions of possible precipitation rather than scanning clear-sky areas of no interest. A microwave imager is proposed for scanning ahead of the satellite in order to identify areas of precipitation, and then an on-board antenna controller can reposition the scanning antenna to obtain reflectivities for use in rainfall-reflectivity relationships. The precursor beam could delineate the storm boundaries and determine points of peak intensity which can then be selectively sampled to find the rainfall rate distribution for the storm. The adaptive-beam system is suggested to be implementable using an IR sensor on-board geosynchronous satellites.

Atlas, D.↗