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At least 595 records · Page 33

Trigger-based Incremental Data Processing with Unified Sync and Async Model

In recent years, more and more applications in the cloud have needs to process large-scale on-line datasets, which evolve over time as new entries are added and existing entries are modified. Several programming frameworks, such as Percolator and Oolong, are proposed for such incremental data processing and can achieve efficient processing with an event-driven abstraction. However, these frameworks are inherently asynchronous, leaving the heavy burden of managing synchronization to applications' developers, which further significantly restricts their usabilities. In this study, we propose a trigger-based incremental computing framework in the cloud, called Domino, with both synchronous and asynchronous mechanisms to coordinate parallel triggers. With this new framework, both synchronous and asynchronous applications can be seamlessly developed. Use cases and extensive evaluation results confirm that it can deliver sufficient performance, and also is easy to use for incremental applications in large-scale distributed computing.

97 MATHEMATICS AND COMPUTING↗

Fiber loop quantum buffer for photonic qubits

Abstract We report a fiber loop quantum buffer based on a low-loss 2 × 2 switch and a unit delay made of a fiber delay line. We characterize the device by using a two-photon polarization entangled state in which one photon of the entangled photon pair is stored and retrieved at a repetition rate up to 78 kHz. The device, which enables integer multiples of a unit delay, can store the qubit state in a unit of fiber delay line up to 5.4 km and the number of loop round-trips up to 3. Furthermore, we configure the device with other active elements to realize integer multiplier and divider of a unit delay of a qubit. The quantum state tomography is performed on the retrieved photon and its entangled photon. We obtain a state fidelity > 94 % with a maximum storage time of 52 s with an insertion loss of 5.56 dB. To further characterize the storing and retrieving processes of the device, we perform entanglement-assisted quantum process tomography on the buffered qubit state. The process fidelity of the device is > 0.98. Our result implies that the device preserves the superposition and entanglement of a qubit state from a two-photon polarization-entangled state. This is a significant step towards facilitating applications in optical asynchronous transfer mode based quantum networks.

Fook Lee, Kim (ORCID:0000000290901640)↗

Enhancing Operational Performance and Productivity Benefits in Breweries through Smart Manufacturing Technologies

This article uses case studies to demonstrate the potential of smart manufacturing (SM) and Internet of Things (IoT) technologies to enhance operational performance and productivity in industry. The analysis highlights benefits such as cost reduction, production flexibility, shorter product time-to-market, energy/water efficiency and environmental impact reduction, and increased productivity. To illustrate the effectiveness of SM and IoT approaches, the authors sought out manufacturers currently implementing or seeking to implement SM and IoT technologies. The authors identified beer brewing (NAICS Code 312120) as a rapidly expanding industry whose members appear eager to implement SM technologies to optimize production lines by revealing bottlenecks and identifying performance-reducing nodes. This article presents two case studies based on SM and IoT technologies in breweries. It briefly describes a systematic framework introduced elsewhere by the authors and uses it to assess the energy productivity and competitiveness of SM applications in breweries. This article addresses questions concerning the information and communications technology infrastructure needed to build smart breweries and how corporations simplify the installation and deployment of SM and IoT components. This article was originally published in the Proceedings of the 2019 ACEEE Summer Study on Energy Efficiency in Industry.

42 ENGINEERING↗

Soft-Shear-Aligned Vertically Oriented Lamellar Block Copolymers for Template-Free Sub-10 nm Patterning and Hybrid Nanostructures

The template-free unidirectional alignment of lamellar block copolymers (l-BCPs) for sub-10 nm high-resolution patterning and hybrid multicomponent nanostructures is important for technological applications. Here we demonstrate a modified soft-shear directed self-assembly (SDSA) approach for aligning pristine l-BCPs and l-BCPs with incorporated polymer grafted nanoparticles (PGNPs), as well as the l-BCPs conversion to aligned gold nanowires, and hybrid of metallic gold nanowire and dielectric silica nanoparticle in the form of line-dot nanostructures. The smallest patterns have a half-pitch as small as 9.8 nm. In all cases, soft-shear is achieved using a high molecular mass polymer topcoat layer, with support on a neutral bottom layer. We also show that the hybrid line-dot nanostructures have a red-shifted plasmonic response in comparison to the neat gold nanowires. These template-free aligned BCPs and nanowires have potential use in nanopatterning applications and the line-dot nanostructures should be useful in the plasmonic sensing of biomolecules and other molecular species based on the plasmonic response of the nanowires.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High-throughput Single-Cell Proteomics and Transcriptomics from the Same Cells with a Nanoliter-Scale Spin-Transfer Approach

Single-cell multiomic platforms provide a comprehensive snapshot of cellular states and cell types by offering critical insights into the spatiotemporal regulation of biomolecular networks at a systems level, thereby defining the basis of multicellularity. Here, we introduce nanoSPINS, an advanced platform that enables high-throughput profiling and integrative analysis of the transcriptome and proteome from the same single cells using RNA sequencing and isobaric labeling LC-MS-based proteomics, respectively. NanoSPINS can efficiently transfer mRNA-containing droplets across two microarrays via a centrifugation-based approach, while proteins are retained on the initial platform. Benchmarking of nanoSPINS on two cell lines demonstrates its ability to generate global proteomic and transcriptomic profiles that align well with previously established methodologies/platforms. The incorporation of isobaric TMTpro labeling into this single-cell multiomics platform significantly enhances the throughput of single-cell proteomic analyses. Through the high-throughput quantification of the proteome and transcriptome, nanoSPINS not only facilitates the identification of molecular features at both mRNA and protein level but also provides larger sample sizes for improved statistical power in clustering and differential abundance. Given the broad applicability of single-cell multiomics in biological research and clinical settings, we believe nanoSPINS represents a powerful platform for the characterization of heterogeneous cell populations.

multi 'omics↗

A Comprehensive Investigation of Active Learning Strategies for Conducting Anti-Cancer Drug Screening

It is well-known that cancers of the same histology type can respond differently to a treatment. Thus, computational drug response prediction is of paramount importance for both preclinical drug screening studies and clinical treatment design. To build drug response prediction models, treatment response data need to be generated through screening experiments and used as input to train the prediction models. In this study, we investigate various active learning strategies of selecting experiments to generate response data for the purposes of (1) improving the performance of drug response prediction models built on the data and (2) identifying effective treatments. Here, we focus on constructing drug-specific response prediction models for cancer cell lines. Various approaches have been designed and applied to select cell lines for screening, including a random, greedy, uncertainty, diversity, combination of greedy and uncertainty, sampling-based hybrid, and iteration-based hybrid approach. All of these approaches are evaluated and compared using two criteria: (1) the number of identified hits that are selected experiments validated to be responsive, and (2) the performance of the response prediction model trained on the data of selected experiments. The analysis was conducted for 57 drugs and the results show a significant improvement on identifying hits using active learning approaches compared with the random and greedy sampling method. Active learning approaches also show an improvement on response prediction performance for some of the drugs and analysis runs compared with the greedy sampling method.

60 APPLIED LIFE SCIENCES↗

Kepler Binary Stars in the NGC 6819 Open Cluster: KIC 5113146 and KIC 5111815

In this study, an investigation of two double-lined binary stars KIC 5113146 and KIC 5111815 in the NGC 6819 open cluster is presented based on both photometric and spectroscopic data. Simultaneous analysis of light and radial velocity curves was made and the absolute parameters of the systems’ components were determined for the first time. We find that both systems have F-type main-sequence components. The masses and radii were found to be M 1 = 1.29 ± 0.02M ⊙ , R 1 = 1.47 ± 0.03 R ⊙ and M 2 = 1.19 ± 0.02 M ⊙ , R 2 = 1.13 ± 0.02 R ⊙ for the primary and secondary components of KIC 5113146; and M 1 = 1.51 ± 0.08 M ⊙ , R 1 = 2.02 ± 0.05 R ⊙ and M 2 = 1.19 ± 0.07 M ⊙ , R 2 = 1.32 ± 0.04 R ⊙ for the components of KIC 5111815, respectively. The evolutionary status of the components was evaluated based on the MESA evolutionary tracks and isochrones. The ages of KIC 5111815 and KIC 5113146 were derived to be about 2.50 ± 0.35 Gyr and 1.95 ± 0.40 Gyr, respectively. Photometric distances were calculated to be 2850 ± 185 pc for KIC 5113146 and 3120 ± 260 pc for KIC 5111815. The results reveal that both KIC 5113146 and KIC 5111815 systems are the most likely members of NGC 6819.

79 ASTRONOMY AND ASTROPHYSICS↗

Chemical Complexity of Phosphorous-bearing Species in Various Regions of the Interstellar Medium

Phosphorus-related species are not known to be as omnipresent in space as hydrogen, carbon, nitrogen, oxygen, and sulfur-bearing species. Astronomers spotted very few P-bearing molecules in the interstellar medium and circumstellar envelopes. Limited discovery of the P-bearing species imposes severe constraints in modeling the P-chemistry. In this paper, we carry out extensive chemical models to follow the fate of P-bearing species in diffuse clouds, photon-dominated or photodissociation regions (PDRs), and hot cores/corinos. We notice a curious correlation between the abundances of PO and PN and atomic nitrogen. Since N atoms are more abundant in diffuse clouds and PDRs than in the hot core/corino region, PO/PN reflects <1 in diffuse clouds, ≪1 in PDRs, and >1 in the late warm-up evolutionary stage of the hot core/corino regions. During the end of the post-warm-up stage, we obtain PO/PN > 1 for hot core and <1 for its low-mass analog. We employ a radiative transfer model to investigate the transitions of some of the P-bearing species in diffuse cloud and hot core regions and estimate the line profiles. Our study estimates the required integration time to observe these transitions with ground-based and space-based telescopes. We also carry out quantum chemical computation of the infrared features of PH{sub 3}, along with various impurities. We notice that SO{sub 2} overlaps with the PH{sub 3} bending-scissoring modes around ∼1000–1100 cm{sup −1}. We also find that the presence of CO{sub 2} can strongly influence the intensity of the stretching modes around ∼2400 cm{sup −1} of PH{sub 3}.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Bayesian Component Separation for DESI LAE Automated Spectroscopic Redshifts and Photometric Targeting

Lyα emitters (LAEs) are valuable high-redshift cosmological probes traditionally identified using specialized narrowband photometric surveys. In ground-based spectroscopy, it can be difficult to distinguish the sharp LAE peak from residual sky emission lines using automated methods, leading to misclassified redshifts. We present a Bayesian spectral component separation technique to automatically determine spectroscopic redshifts for LAEs while marginalizing over sky residuals. We use visually inspected spectra of LAEs obtained using the Dark Energy Spectroscopic Instrument (DESI) to create a data-driven prior and can determine redshift by jointly inferring sky residual, LAE, and residual components for each individual spectrum. We demonstrate this method on 881 spectroscopically observed z = 2–4 DESI LAE candidate spectra and determine their redshifts with >90% accuracy when validated against visually inspected redshifts. Using the Δχ$^{2}$ value from our pipeline as a proxy for detection confidence, we then explore potential survey design choices and implications for targeting LAEs with medium-band photometry. This method allows for scalability and accuracy in determining redshifts from DESI spectra, and the results provide recommendations for LAE targeting in anticipation of future high-redshift spectroscopic surveys.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Narrow-line Seyfert 1 galaxies in Sloan Digital Sky Survey: a new optical spectroscopic catalogue

ABSTRACT Narrow-line Seyfert 1 (NLSy1) galaxies are an enigmatic class of active galactic nuclei (AGN) that exhibit peculiar multiwavelength properties across the electromagnetic spectrum. For example, these sources have allowed us to explore the innermost regions of the central engine of AGN using X-ray observations and have also provided clues about the origin of relativistic jets considering radio and gamma-ray bands. Keeping in mind the ongoing and upcoming wide-field, multifrequency sky surveys, we present a new catalogue of NLSy1 galaxies. This was done by carrying out a detailed decomposition of >2 million optical spectra of quasars and galaxies from the Sloan Digital Sky Survey Data Release 17 (SDSS-DR17) using the publicly available software ‘Bayesian AGN Decomposition Analysis for SDSS Spectra’. The catalogue contains 22656 NLSy1 galaxies which is more than twice the size of the previously identified NLSy1s based on SDSS-DR12. As a corollary, we also release a new catalogue of 52273 broad-line Seyfert 1 (BLSy1) galaxies. The estimated optical spectral parameters and derived quantities confirm the previously known finding of NLSy1 galaxies being AGN powered by highly accreting, low-mass black holes. We conclude that this enlarged sample of NLSy1 and BLSy1 galaxies will enable us to explore the low-luminosity end of the AGN population by effectively utilizing the sensitive, high-quality observations delivered by ongoing/upcoming wide-field sky surveys. The catalogue has been made public at https://www.ucm.es/blazars/seyfert.

Paliya, Vaidehi S. (ORCID:0000000177745308)↗

Fast response, optical radiance measurements of low intensity impurity emission in WEST plasmas with staggered wavelength filters

Fast response acquisition of atomic line emission through the use of a filterscope has been implemented on the WEST tokamak at multiple poloidal locations. Filterscopes consist of a fiber-optic-based transmission from the tokamak to specifically engineered optical bandpasses and photomultiplier tubes (PMT) that collect the emission intensity to measure a radiance, L [W/cm2/str], over the specified bandpass. This diagnostic records plasma-wall interaction (PWI) properties (e.g. impurity emission and recycling of main fuel ions) up to a max acquisition rate of 100 kHz. These PMT radiometric measurements are calibrated into a line-normalized radiance, LN [photons/sec/cm2/str], similar to traditional spectrometers, which can later be converted to a particle flux. Low intensity emission peaks are difficult to quantify due to often comparable continuum levels, thus a secondary filter shifted to a judiciously-selected, line-free region (~1 nm away) allows for background subtraction. The system currently installed on WEST targets tungsten (W) gross sputtering specifically by monitoring, with a filter pair, the spectral region near the neutral W line emission (W I 400.9 nm). The line and background filters of the pair are centered at 400.6 nm and 403.1 nm, respectively. Through a set beam splitters on each sight line, the filter pair are measuring from the same location. The two L signals near W I are then subtracted from each other yielding only the W I LN. W I LN data from a recent WEST experimental campaign is presented and compared with plasma parameters and traditional spectrometer measurements of W I line emission to demonstrate the capabilities of this staggered-filter filterscope method. Specifically, the choice of WEST-specific bandpass curves for the W I LN will be illustrated based on this latter comparison.

Neff, Anton↗

Quantum computing based hybrid deep learning for fault diagnosis in electrical power systems

Quantum computing (QC) and deep learning have shown promise of supporting transformative advances and have recently gained popularity in a wide range of areas. Here, this paper proposes a hybrid QC-based deep learning framework for fault diagnosis of electrical power systems that combine the feature extraction capabilities of conditional restricted Boltzmann machine with an efficient classification of deep networks. Computational challenges stemming from the complexities of such deep learning models are overcome by QC-based training methodologies that effectively leverage the complementary strengths of quantum assisted learning and classical training techniques. The proposed hybrid QC-based deep learning framework is tested on a simulated electrical power system with 30 buses and wide variations of substation and transmission line faults, to demonstrate the framework’s applicability, efficiency, and generalization capabilities. High computational efficiency is enjoyed by the proposed hybrid approach in terms of computational effort required and quality of diagnosis performance over classical training methods. In addition, superior and reliable fault diagnosis performance with faster response time is achieved over state-of-the-art pattern recognition methods based on artificial neural networks (ANN) and decision trees (DT).

42 ENGINEERING↗

Frequency Disturbance Event Detection Based on Synchrophasors and Deep Learning

Power system frequency disturbances are caused by various generation and transmission events including generator trips, load disconnections, line trips, etc. Accurate detections of the events are crucial to bulk power system situation awareness and event investigation. This paper utilizes the recent advances of deep learning to build a convolutional neural network model to detect events in an accurate yet straightforward manner. Herein, the rate of change of frequency and the relative angle shift are converted to images as the inputs of the proposed model. Finally, this paper uses two convolutional neural networks and classifier fusion to achieve the detection result. Compared with the conventional event detection algorithm and the frequency only deep learning model, the proposed model improves the detection accuracy by over 48%. As a promising tool for bulk power system situation awareness, the proposed model requires a short decision time, which is suitable for practical scenarios.

42 ENGINEERING↗

Role of Coulomb interaction in the phase formation of fcc Ce: Correlation matrix renormalization theory

The effect of electronic Coulomb interaction on the phase formation of fcc Ce lattice is investigated by full ab initio calculations without adjustable Coulomb U and J parameters using the Gutzwiller wavefunction-based correlation matrix renormalization theory (CMRT). Its total energy and pressure as a function of volume agree reasonably well with existing DFT+Gutzwiller calculations and experiments, indicating correct capture of electronic correlation and screening effects within the CMRT formalism. Here, a stable phase is found in line with the experimental α-Ce phase, and a lurking phase is identified supposedly linked with the experimental γ-Ce phase. A criterion based on the local 4f electron charge fluctuation is introduced to confirm the distinct electronic correlation natures of both phases.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Homotopy characterization of non-Hermitian Hamiltonians

We revisit the problem of classifying topological band structures in non-Hermitian systems. Recently, a solution has been proposed, which is based on redefining the notion of energy band gap in two different ways, leading to the so-called “point-gap” and “line-gap” schemes. However, simple Hamiltonians without band degeneracies can be constructed which correspond to neither of the two schemes. Here, we resolve this shortcoming of the existing classifications by developing the most general topological characterization of non-Hermitian bands for systems without a symmetry. Our approach, which is based on homotopy theory, makes no particular assumptions on the band gap, and predicts significant extensions to the previous classification frameworks. In particular, we show that the one-dimensional invariant generalizes from $\mathbb{Z}$ winding number to the non-Abelian braid group, and that depending on the braid group invariants, the two-dimensional invariants can be cyclic groups $\mathbb{Z}_n$ (rather than $\mathbb{Z}$ Chern number). Finally, we interpret these results in terms of a correspondence with gapless systems, and we illustrate them in terms of analogies with other problems in band topology, namely, the fragile topological invariants in Hermitian systems and the topological defects and textures of nematic liquids.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Multi-frequency electrical impedance tomography

Apparatus includes a plurality of geological subsurface electrical line sensors spaced apart from each other proximate a predetermined geological subsurface region of interest, with at least one of the electrical line sensors situated as a line source to produce a multi-frequency electrical impedance tomography source signal, and with at least one of the electrical line sensors situated as a line detector to receive the multi-frequency electrical impedance tomography response signal associated with the source signal that propagates through the predetermined geological subsurface region of interest, and a controller including a processor and a memory configured with instructions that, when executed by the processor, cause the processor to determine an electrical mapping over the predetermined geological subsurface region of interest based on the multi-frequency electrical impedance tomography source signal, response signal, and the spatial positions of the geological subsurface electrical line sensors.

Karra, Satish↗

22 GeV CEBAF with Novel Fixed Field Alternating Gradient Design

Extending the energy reach of CEBAF up to 22 GeV within the existing tunnel is being explored. Proposed energy upgrade can be achieved by increasing the number of recirculations, while using the existing CEBAF SRF cavity system. Presented scheme is based on an exciting new approach to acceleratie electrons efficiently with multiple passes in a single FFA beam line. Encouraged by recent success of the CBETA Test Accelerator, a proposal was formulated raise CEBAF energy by replacing the highest-energy arcs with Fixed Field Alternating Gradient (FFA) arcs. The new pair of arcs configured with FFA lattice would support simultaneous transport of additional 6 passes with energies spanning a factor of two, using the non-scaling FFA principle implemented with Halbach-derived permanent magnets - a novel magnet technology that significantly saves energy and lowers operating costs. One of the challenges of the multi-pass (11) linac optics is to provide uniform focusing in a vast range of energies, using fixed field lattice. Here, we propose a triplet lattice scaled up with increasing momentum along the linac. This would provide a stable periodic solution covering energy ratio of 1:33. The current CEBAF configured with a 123 MeV injector, makes optical matching in the first linac virtually impossible due to extremely high energy span ratio (1:175). Therefore, we envision replacement of the current injector with a 650 MeV 3-pass recirculating injector based on the existing LERF facility. Finally, the 22 GeV CEBAF would promise to deliver in 10-passes a beam with normalized emittance of 80 mm·mrad and with a relative energy spread of 1.5 × 10-3. Further recirculation beyond 22 GeV is limited by large, 974 MeV per electron, energy loss due to synchrotron radiation.

Bogacz, Slawomir↗

Detecting low-mass perturbers in cluster lenses using curved arc bases

ABSTRACT Strong gravitationally lensed arcs produced by galaxy clusters have been observationally detected for several decades now. These strong lensing constraints provided high-fidelity mass models for cluster lenses that include substructure down to $10^{9{-}10}\, \mathrm{M}_\odot$. Optimizing lens models, where the cluster mass distribution is modelled by a smooth component and subhaloes associated with the locations of individual cluster galaxies, has enabled deriving the subhalo mass function, providing important constraints on the nature and granularity of dark matter. In this work, we explore and present a novel method to detect and measure individual perturbers (subhaloes, line-of-sight haloes, and wandering supermassive black holes) by exploiting their proximity to highly distorted lensed arcs in galaxy clusters, and by modelling the local lensing distortions with curved arc bases. This method offers the possibility of detecting individual low-mass perturber subhaloes in clusters and haloes along the line of sight down to a mass resolution of $10^8\, \mathrm{M}_\odot$. We quantify our sensitivity to low-mass perturbers ($M\sim 10^{7{-}9}\, \mathrm{M}_\odot$) in clusters (M ∼ 1014–15 M⊙), by creating realistic mock data. Using three lensed images of a background galaxy in the cluster SMACS J0723, taken by JWST, we study the retrieval of the properties of potential perturbers with masses $M=10^{7{-}9}\, \mathrm{M}_\odot$. From the derived posterior probability distributions for the perturber, we constrain its concentration, redshift, and ellipticity. By allowing us to probe lower mass substructures, the use of curved arc bases can lead to powerful constraints on the nature of dark matter as discrimination between dark matter models appears on smaller scales.

Astronomy & Astrophysics↗