Search NASA⌕ Search

SEARCH · Search NASA

Results for “missing information”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 685 records · Page 38

Electroproduction of the Λ/Σ 0 hyperons at Q 2 ≃ 0.5 (GeV/c) 2 at forward angles

In 2018, the E12-17-003 experiment was conducted at the Thomas Jefferson National Accelerator Facility (JLab) to explore the possible existence of an nn⁢Λ state in the reconstructed missing mass distribution from a tritium gas target [K. N. Suzuki et al., Prog. Theor. Exp. Phys. 2022, 013D01 (2022); B. Pandey et al., Phys. Rev. C 105, L051001 (2022)]. As part of this investigation, data were also collected using a gaseous hydrogen target, not only for a precise absolute mass scale calibration but also for the study of Λ/Σ 0 electroproduction. This dataset was acquired at Q 2 ≃ 0.5 (GeV/c) 2 , W = 2.14 GeV, and θ$^{c.m.}_{γK}$ ≃ 8°. It covers forward angles where photoproduction data are scarce and a low-Q 2 region that is of interest for hypernuclear experiments. On the other hand, this kinematic region is at a slightly higher Q 2 than previous hypernuclear experiments, thus providing crucial information for understanding the Q 2 dependence of the differential cross sections for Λ/Σ 0 hyperon electroproduction. Here, this paper reports on the Q 2 dependence of the differential cross section for the e + p → e' + K + + Λ/Σ 0 reaction at 0.2–0.8 (GeV/c) 2 , and provides comparisons with the currently available theoretical models.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Integrating chromatin conformation information in a self-supervised learning model improves metagenome binning

Metagenome binning is a key step, downstream of metagenome assembly, to group scaffolds by their genome of origin. Although accurate binning has been achieved on datasets containing multiple samples from the same community, the completeness of binning is often low in datasets with a small number of samples due to a lack of robust species co-abundance information. In this study, we exploited the chromatin conformation information obtained from Hi-C sequencing and developed a new reference-independent algorithm, Metagenome Binning with Abundance and Tetra-nucleotide frequencies—Long Range (metaBAT-LR), to improve the binning completeness of these datasets. This self-supervised algorithm builds a model from a set of high-quality genome bins to predict scaffold pairs that are likely to be derived from the same genome. Then, it applies these predictions to merge incomplete genome bins, as well as recruit unbinned scaffolds. We validated metaBAT-LR’s ability to bin-merge and recruit scaffolds on both synthetic and real-world metagenome datasets of varying complexity. Benchmarking against similar software tools suggests that metaBAT-LR uncovers unique bins that were missed by all other methods.

59 BASIC BIOLOGICAL SCIENCES↗

Groundwater monitoring report streamlining techniques - 15305

Compliance with national and state environmental regulations (e.g. RCRA and CERCLA [SuperFund] requires Savannah River Site (SRS) to extensively collect and report groundwater monitoring data, with potential fines for missed reporting deadlines. Large reports, which may contain dozens to hundreds of monitoring stations, are especially challenging to present data in a way that is quick and easy to interpret. Initially analyzing hundreds to thousands of records of data to be summarized in the report can be daunting, and producing maps can be extremely time consuming. Several utilities have been developed at SRS to facilitate production of the regulatory reports which include data tables, charts, maps, and cross-sections. Components of each report are generated in accordance with complex sets of regulatory requirements specific to each site monitored. SRS developed a relational database to incorporate the detailed reporting rules with the groundwater data, and created a set of automation tools to interface with the information and generate the report components. Maps produced with ArcGIS use a technique that can be repeatedly used to display data very quickly and in a consistent form. Cross-sections developed with RockWorks provide a more technical and geological analysis and representation of well and boring data, while allowing for automated data placement. These process improvements have streamlined the repetitive job of creating data tables, charts, maps, and cross-sections. It has also enhanced report quality and consistency by centralizing the information, and has reduced manpower and production time through automated efficiencies. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

The Ontology of Biological Attributes (OBA)—computational traits for the life sciences

Abstract Existing phenotype ontologies were originally developed to represent phenotypes that manifest as a character state in relation to a wild-type or other reference. However, these do not include the phenotypic trait or attribute categories required for the annotation of genome-wide association studies (GWAS), Quantitative Trait Loci (QTL) mappings or any population-focussed measurable trait data. The integration of trait and biological attribute information with an ever increasing body of chemical, environmental and biological data greatly facilitates computational analyses and it is also highly relevant to biomedical and clinical applications. The Ontology of Biological Attributes (OBA) is a formalised, species-independent collection of interoperable phenotypic trait categories that is intended to fulfil a data integration role. OBA is a standardised representational framework for observable attributes that are characteristics of biological entities, organisms, or parts of organisms. OBA has a modular design which provides several benefits for users and data integrators, including an automated and meaningful classification of trait terms computed on the basis of logical inferences drawn from domain-specific ontologies for cells, anatomical and other relevant entities. The logical axioms in OBA also provide a previously missing bridge that can computationally link Mendelian phenotypes with GWAS and quantitative traits. The term components in OBA provide semantic links and enable knowledge and data integration across specialised research community boundaries, thereby breaking silos.

59 BASIC BIOLOGICAL SCIENCES↗

Enabling probabilistic learning on manifolds through double diffusion maps

Here, we present a generative learning framework for probabilistic sampling that extends Probabilistic Learning on Manifolds (PLoM), which is designed to generate statistically consistent realizations of a random vector in a finite-dimensional Euclidean space, informed by a (representative) set of observations. In its original form, PLoM constructs a reduced-order probabilistic model by combining three main components: (a) kernel density estimation to approximate the underlying probability measure, (b) Diffusion Maps to characterize the manifold of the data, and (c) a reduced-order Itô Stochastic Differential Equation (ISDE) to sample from the learned distribution. However, its sampling dynamics are posed in the ambient space and the retained number of reduced coordinates is chosen by projection-reconstruction error. In practice, this often (i) requires more coordinates than the data’s intrinsic dimension to achieve stable sampling and (ii) lacks a smooth, basis-independent lifting back to the data domain; moreover, standard Diffusion Maps emphasize harmonic eigenfunctions and can miss non-harmonic latent structure. We address these limitations by decoupling geometry learning from sampling: a first Diffusion Maps pass identifies non-harmonic coordinates on which we formulate a full-order ISDE directly in the latent space, while Double Diffusion Maps captures multiscale geometric features and Geometric Harmonics (GH) learns a smooth lifting map to the ambient variables that is independent of the particular diffusion basis. This hybrid design preserves the system’s dynamical richness with a compact geometric representation and enables principled out-of-sample inference. The effectiveness and robustness of the proposed method are illustrated through two numerical studies: one based on data generated from two-dimensional Hermite polynomial functions and another based on high-fidelity simulations of a detonation wave in a reactive flow.

Double diffusion maps↗

A Global Aerosol Model Forecast for the ACE-Asia Field Experiment

We present the results of aerosol forecast during the Aerosol Characterization Experiment (ACE-Asia) field experiment in spring 2001, using the Georgia Tech/Goddard Global Ozone Chemistry Aerosol Radiation and Transport (GOCART) model and the meteorological forecast fields from the Goddard Earth Observing System Data Assimilation System (GEOS DAS). The aerosol model forecast provides direct information on aerosol optical thickness and concentrations, enabling effective flight planning, while feedbacks from measurements constantly evaluate the model, making successful model improvements. We verify the model forecast skill by comparing model predicted total aerosol extinction, dust, sulfate, and SO2 concentrations with those quantities measured by the C-130 aircraft during the ACE-Asia intensive operation period. The GEOS DAS meteorological forecast system shows excellent skills in predicting winds, relative humidity, and temperature for the ACE-Asia experiment area as well as for each individual flight, with skill scores usually above 0.7. The model is also skillful in forecast of pollution aerosols, with most scores above 0.5. The model correctly predicted the dust outbreak events and their trans-Pacific transport, but it constantly missed the high dust concentrations observed in the boundary layer. We attribute this missing dust source to the desertification regions in the Inner Mongolia Province in China, which have developed in recent years but were not included in the model during forecasting. After incorporating the desertification sources, the model is able to reproduce the observed high dust concentrations at low altitudes over the Yellow Sea. Two key elements for a successful aerosol model forecast are correct source locations that determine where the emissions take place, and realistic forecast winds and convection that determine where the aerosols are transported. We demonstrate that our global model can not only account for the large-scale intercontinental transport, but also produce the small-scale spatial and temporal variations that are adequate for aircraft measurements planning.

Chin, Mian↗

Machine Learning Based AFP Inspection: A Tool for Characterization and Integration

Automated Fiber Placement (AFP) has become a standard manufacturing technique in the creation of large scale composite structures due to its high production rates. However, the associated rapid layup that accompanies AFP manufacturing has a tendency to induce defects. We forward an inspection system that utilizes machine learning (ML) algorithms to locate and characterize defects from profilometry scans coupled with a data storage system and a user interface (UI) that allows for informed manufacturing. A Keyence LJ-7080 blue light profilometer is used for fast 2D height profiling. After scans are collected, they are process by ML algorithms, displayed to an operator through the UI, and stored in a database. The overall goal of the inspection system is to add an additional tool for AFP manufacturing. Traditional AFP inspection is done manually adding to manufacturing time and being subject to inspector errors or fatigue. For large parts, the inspection process can be cumbersome. The proposed inspection system has the capability of accelerating this process while still keeping a human inspector integrated and in control. This allows for the rapid capability of the automated inspection software and the robustness of a human checking for defects that the system either missed or misclassified.

Sacco, Christopher↗

Simulator study of a pictorial display for general aviation instrument flight

A simulation study of a computer drawn pictorial display involved a flight task that included an en route segment, terminal area maneuvering, a final approach, a missed approach, and a hold. The pictorial display consists of the drawing of boxes which either move along the desired path or are fixed at designated way points. Two boxes may be shown at all times, one related to the active way point and the other related to the standby way point. Ground tracks and vertical profiles of the flights, time histories of the final approach, and comments were obtained from time pilots. The results demonstrate the accuracy and consistency with which the segments of the flight are executed. The pilots found that the display is easy to learn and to use; that it provides good situation awareness, and that it could improve the safety of flight. The small size of the display, the lack of numerical information on pitch, roll, and heading angles, and the lack of definition of the boundaries of the conventional glide slope and localizer areas were criticized.

Adams, J. J.↗

Progress in Development of the Axel Rovers

Progress has been made in the development of a family of robotic land vehicles having modular and minimalist design features chosen to impart a combination of robustness, reliability, and versatility. These vehicles at earlier stages of development were described in two previous NASA Tech Briefs articles: "Reconfigurable Exploratory Robotic Vehicles" (NPO-20944), Vol. 25, No. 7 (July 2001), page 56; and "More About Reconfigurable Exploratory Robotic Vehicles" (NPO-30890), Vol. 33, No. 8 (August 2009), page 40. Conceived for use in exploration of the surfaces of Mars and other remote planets, these vehicles could also be adapted to terrestrial applications, including exploration of volcanic craters or other hostile terrain, military reconnaissance, inspection of hazardous sites, and searching for victims of earthquakes, landslides, avalanches, or mining accidents. In addition, simplified versions of these vehicles might be marketable as toys. The most basic module in this family of reconfigurable robots is the Axel rover, which has a cylindrical body with two main wheels and a trailing link. Inside its body are three motors and associated mechanisms for driving the two wheels and for rotating the link 360 around its symmetrical body. The actuated link serves several purposes: It is used as a lever arm to react to the wheels thrust to move Axel in multiple directions. It is used to rotate the Axel housing in order to tilt, to the desired angle, any sensors and instruments mounted on or in the Axel housing. It provides an alternative mobility mode, which is primarily used in its tethered configuration. Turn ing the link into the ground in lieu of driving the wheels causes the Axel housing and wheels to roll as a unit and thereby leads to a tumbling motion along the ground. With a tether mounted around Axel s cylindrical body, the link serves as a winch mechanism to reel and unreel the tether raising and lowering Axel over steep and vertical surfaces (Figure 1). Sensors, computation, and communication modules are also housed inside Axel s body. A pair of stereo vision cameras provides three-dimensional view for autonomous navigation and avoiding obstacles. Inertial sensors determine the tilt of the robot and are used for estimating its motion. In a fully developed version, power would be supplied by rechargeable batteries aboard Axel; at the time of reporting the information for this article, power was supplied from an external source via a cable. In and of itself, the Axel rover is fully capable of traversing and sampling terrains on planetary surfaces. By use of only the two main wheel actuators and the caster link actuator, Axel can be made to follow an arbitrary path, turn in place, and operate upside- down or right-side-up. If operated in a tethered configuration, as shown in Figure 1, it can be made to move down and up a steep crater wall, descend from an overhang to a cave, and ascend from the cave back to the overhang, all by use of the same three actuators. Such tethered operation could be useful in searching for accident victims or missing persons in mines, caves, and rubble piles. Running the tether through the caster link enhances the stability of Axel and provides a restoring force that keeps the link off the ground for the most part during operation on a steep slope. In its extended configuration, two Axel modules can dock to either side of a payload module to form the four wheeled Axel2 rover (Figure 2). Additional payload and Axel modules can dock to either side of the Axel2 to form the Axel3 rover, extending its payload capacity and its mobility capabilities.

Nesnas, Issa A.↗

System Modeling of a Lunar Molten Regolith Electrolysis Plant

Introduction: In-Situ Resource Utilization (ISRU) is the process of extracting local resources to produce commodities for propulsion, life support systems, and off-planet construction rather than transporting consumables from Earth. Molten Regolith Electrolysis (MRE) is a novel ISRU method of extracting oxygen gas and metal alloy from lunar regolith. The MRE process involves placing lunar regolith between two electrodes, through which current is passed, to melt the regolith and reduce the metal oxide constituents by direct electrolysis (e.g. FeO, SiO2, MgO, Al2O3) into oxygen gas and metal alloys. The oxygen is liquefied and used as propellant for landers, while the metals (e.g. Ferro-alloys) are further processed and used in structural building materials and parts manufacturing. A system model was developed that accounted for the major processes of an MRE plant (from excavation of raw materials to storage of products) to assess the feasibility of a lunar MRE plant. The System Engineering and Integration (SE&I) ISRU Modeling and Analysis (SIMA) team utilized its previously documented system sizing model, the Mission Analysis and Integration Tool (MAIT) [1] as framework of the system model. MAIT uses MATLAB/Simulink to integrate subsystem models into a complete system model of the MRE plant. Total mass, volume, and power requirements were computed for numerous iterations of a MRE plant. System Model: Figure 1: MRE Plant Block Diagram The regolith excavation model determines the mass and power needed to excavate sufficient regolith. The preheating auger initiates the regolith heating process before regolith enters the MRE re-actor to reduce the energy required to turn the solid into a molten liquid. The MRE reactor is modeled in COMSOL Multiphysics and based on the research by Dominguez, Sibille, and Schreiner [2, 3, 4]. This preliminary reactor model provides an accurate calculation of thermal equilibrium during electrochemical operation of the reactor system to assess the optimal mass and power required to process the inlet flow of regolith. The model also computes the outlet flowrates of oxygen and molten products. For this analysis, the primary components of the metal alloy considered were iron and silicon. The oxygen is then purified using an Yttrium Stabilized Zirconia (YSZ) electrode, followed by liquefaction using a 90K cryocooler to be stored as liquid oxygen in insulated cylindrical tanks. In future iterations of the system model, the molten metal tapped from the MRE reactor will undergo additional processing or refinement. However, downstream handling of metals is currently a technology gap that is missing a high TRL subsystem model. Therefore, for this analysis, the accumulated metal alloy stream terminates after leaving the MRE reactor. Study Goals: This analysis investigates multiple input variables to the system to determine the sensitivity of a (near) complete plant at full-scale. This preliminary investigation ran parametric sweeps on the MRE reactor geometry, electrical current supply, layers of multi-layer insulation (MLI) on the reactor, size of the electrodes in the oxygen purification model, and regolith composition (based on landing site location). Three production targets of oxygen (1,000, 10,000, and 50,000 kg/yr) were investigated for this analysis. The parametric sweeps conducted in this analysis provide valuable insight into the expected impact of the various model inputs on plant size. This information can be used to identify the most critical components of the plant and guide future decisions on allocating funding for research and development, providing subsystem developers with appropriate interfaces with downstream and upstream processes, and assessing the overall feasibility of MRE when compared to other ISRU plants. References: [1] Carlson, A. et al. (2024) ICES, ICES-2024-53. [2] Dominguez, D.A., and Sibille, L. (2011) AIAA, AIAA-2011-700. [3] Schreiner, S.S. (2015) MIT, Dissertation. [4] Schreiner, S.S. et al. (2016) ASR, 57(7), pp.1585-1603.

ISRU↗

Fused x-ray and fast neutron CT reconstruction for imaging large and dense objects

Megavolt x-ray computed tomography (CT) is a powerful tool for three-dimensional characterization. However, its utility is limited for large objects composed of high-atomic number (Z) materials, where x rays fail to penetrate. Information from fast neutron CT (FNCT) can complement x-ray CT reconstructions since fast neutrons can more readily penetrate high-Z objects. In this work, we demonstrate a method for combining FNCT and x-ray CT data to create a single reconstruction, more accurate than could be achieved with either x rays or fast neutrons alone. The algorithm was tested on an exemplar comprising multiple concentric, nested cylinders of different materials. Simulated and empirical x-ray CT data were acquired for the exemplar using a 9 MV bremsstrahlung spectrum. Additional simulated and empirical FNCT data were acquired using an accelerator based fast neutron source. The FNCT data were used to synthesize x-ray CT data and augment the x-ray CT data missing due to lack of penetration. This approach mitigates artifacts that would otherwise negatively affect the accuracy and resolution of a single-modality reconstructed volume.

47 OTHER INSTRUMENTATION↗

The Primary Flight Display and Its Pathway Guidance: Workload, Performance, and Situation Awareness

In two experiments carried out in a high fidelity general aviation flight simulator, 42 instrument rated pilots flew a pathway-in-the-sky (tunnel) display through a series of multi-leg curved stepdown approaches through mountainous terrain. Both experiments examined how properties of the tunnel influenced flight path tracking performance, traffic awareness, terrain awareness and workload (assessed both by subjective and secondary task performance measures). Experiment 1, flown in simulated VMC, compared high and low intensity tunnels, with a less cluttered follow-me-airplane (FMA). The results revealed that both tunnels supported better flight path tracking than the FMA, because of the availability of more preview information. Increasing tunnel intensity, while reducing subjective workload, had no benefit on tracking, and degraded traffic detection performance. In Experiment 2, flown mostly in IMC, the low intensity tunnel was flown with a large (10 inch x 8 inch) and small (8 inch x 6.5 inch) display, representing a geometric field of view (GFOV) of either 30 degrees or 60 degrees. Most measures of flight path tracking performance favored the smaller display, and particularly the 60 degree GFOV, which presented a smaller appearing tunnel, and a wider range of terrain depiction. The larger GFOV also supported better terrain awareness, and yielded a lower secondary task assessment of workload. In both experiments, the final landing approach was terminated by a runway obstruction, and the tunnel guided pilots on a missed approach. In nearly all cases, pilots failed to notice an air hazard that lay in the missed approach path, but was only depicted in the outside view.

Wickens, Christopher D.↗

Search for higgsinos in compressed mass spectra using low-momentum tracks in pp collisions at s=13 TeV with the ATLAS detector

This paper presents two searches for the electroweak production of higgsinos with compressed mass spectra using 140 fb−1 of s=13$$ \sqrt{s}=13 $$ TeV proton-proton collision data collected by the ATLAS experiment at the Large Hadron Collider. Events are required to feature an energetic jet, large missing transverse momentum, and at least one low-momentum charged particle that serves as a candidate higgsino decay product. In the first search, targeting higgsino mass splittings in the range of 0.3–1 GeV, the higgsinos are expected to predominantly decay into pions that are identified as low-momentum charged particles with large transverse impact parameters due to the long higgsino lifetime (cτ ≈ ?(0.1–10 mm)), and neural networks are used to discriminate between signal and background processes. The second search targets larger mass splittings in the range of 1–3 GeV, where the higgsinos are expected to decay promptly into low-momentum leptons, one of which is identified by dedicated low-momentum electron or muon taggers based on neural networks utilising tracking and calorimeter information. No significant excess above the Standard Model prediction is observed in either search and the results are interpreted within simplified models, to set lower limits on the masses of the higgsino-like charginos and neutralinos. Together, these searches exclude chargino masses below 126 GeV at 95% confidence level for mass splittings between the chargino and lightest neutralino in the range of 0.3–2 GeV. This represents the first ATLAS constraints in a portion of this parameter space and surpasses the limits previously set by other experiments.

Aad, G↗

Fine-Grained Application Energy and Power Measurements on the Frontier Exascale System

The increasing complexity and power/energy demands of heterogeneous exascale systems, such as the Frontier supercomputer, present significant challenges for measuring and optimizing power consumption in applications. Current tools either lack the resolution to capture fine-grained power and energy measurements, fail to validate in-band measurements against out-of-band power sensors, or cannot integrate this information with application performance events in a scalable manner. This paper introduces a novel open-source performance toolkit that integrates extended PAPI components with Score-P plugins to enable in-band, fine-grained power and energy measurements, while also supporting validation using power meter measurements for both CPUs and GPUs. One key contribution is the ability to perform millisecond-level power and energy measurements for AMD MI250X GPUs, mapping them to application performance events within a single trace and measurement system that scales. Our toolkit combines coarse-grained measurements from cray_pm counters with high-resolution metrics from rocm_smi and RAPL, converting GPU instantaneous accumulated energy into power to capture both transient and steady-state power behavior, a capability often missed by out-of-band and monitoring tools. By mapping these metrics to specific application regions, developers can identify energy hotspots, address inefficiencies in GPU kernel execution, and validate in-band measurements against external measurements. We demonstrate the effectiveness of this approach through case studies using benchmarks such as GPU rocblas_sgemm, BLIS c_blas_dgemm, and rocHPL, highlighting the variability of the measurements and the impact of transient power spikes on kernel-level efficiency.

Hernandez Mendoza, Oscar [ORNL] (ORCID:00000002538↗

New physics in the visible final states of B → D(*) τν

We derive compact expressions for the helicity amplitudes of the many-body B → D (*) (→ DY)τ(→ Xν)ν decays, specifically for X = ℓν or π and Y = π or γ. We include contributions from all ten possible new physics four-Fermi operators with arbitrary couplings. Our results capture interference effects in the full phase space of the visible τ and D * decay products which are missed in analyses that treat the τ or D * or both as stable. The τ interference effects are sizable, formally of order m τ /m B for the standard model, and may be of order unity in the presence of new physics. Treating interference correctly is essential when considering kinematic distributions of the τ or D * decay products, and when including experimentally unavoidable phase space cuts. Our amplitude-level results also allow for efficient exploration of new physics effects in the fully differential phase space, by enabling experiments to perform such studies on fully simulated Monte Carlo datasets via efficient event reweighing. As an example, we explore a class of new physics interactions that can fit the observed R(D (*) ) ratios, and show that analyses including more differential kinematic information can provide greater discriminating power for new physics, than single kinematic variables alone.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Aerosol Thermodynamics (Aerosol Liquid Water Concentration and Aerosol pH) at S2 during CoURAGE

These data report aerosol liquid water content (ALWC) and aerosol pH for the S2 (Mt. Airy) site during CoURAGE for April - June 2025. The ISORROPIA-II aerosol thermodynamic equilibrium model was used to compute ALWC and pH. The model was run in forward mode, with solids formation disabled (metastable mode), according to Pye et al. (Atmospheric Chemistry and Physics, 2020). Information about the model can be found at https://www.epfl.ch/labs/lapi/models-and-software/isorropia/, and in Fountoukis and Nenes (Atmospheric Chemistry and Physics, 2007). Inputs to the model were: (1) measured Temperature and relative humidity, both from the DoE ARM “metwxt” data products at S2, (2) aerosol chemical composition from the ARM ACSM, and (3) gas-phase ammonia concentrations. For ISORROPIA-II, ambient RH values above 0.995 were input to the model as 0.995; therefore, caution should be exercised interpreting ALWC when RH was above 0.995. Aerosol composition or NH3(g) concentrations below the LOD were input into the model as 0.5*LOD. Model runs were only conducted for data points at 30-min resolution with all three inputs (meteorology, ACSM, and NH3). If any of the three model inputs were missing, aerosol thermodynamic outputs are flagged as -999. Similarly, aerosol thermodynamic outputs are flagged as -999 if measured NH3(g) and aerosol ammonium (NH4+) were simultaneously below the respective LODs. The ALWC includes liquid water from inorganic aerosol components, calculated directly by ISORROPIA-II, as well as liquid water from organics, estimated from the ACSM organics assuming a kappa value of 0.12 according to Guo et al. (Atmospheric Chemistry and Physics, 2015).

Aerosol Liquid Water Content↗

Suppressing Quantum Circuit Errors Due to System Variability

We present a quantum circuit optimization technique that takes into account the variability in error rates that is inherent across present-day noisy quantum computing platforms. This method can be run after qubit routing or postcompilation and consists of computing isomorphic subgraphs to input circuits and scoring each using heuristic cost functions derived from system calibration data. Using an independent standard algorithmic test suite, we show that it is possible to recover on average nearly 40% of missing fidelity using better qubit selection via efficient to compute cost functions. We demonstrate additional performance gains by considering qubit placement over multiple quantum processors. The overhead from these tools is minimal with respect to other compilation steps, such as qubit routing, as the number of qubits increases. As such, our method can be used to find qubit mappings for problems at the scale of quantum advantage and beyond.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Searching for pulsars using image pattern recognition

In the modern era of big data, many fields of astronomy are generating huge volumes of data, the analysis of which can sometimes be the limiting factor in research. Fortunately, computer scientists have developed powerful data-mining techniques that can be applied to various fields. In this paper, we present a novel artificial intelligence (AI) program that identifies pulsars from recent surveys by using image pattern recognition with deep neural nets—the PICS (Pulsar Image-based Classification System) AI. The AI mimics human experts and distinguishes pulsars from noise and interference by looking for patterns from candidate plots. Different from other pulsar selection programs that search for expected patterns, the PICS AI is taught the salient features of different pulsars from a set of human-labeled candidates through machine learning. The training candidates are collected from the Pulsar Arecibo L-band Feed Array (PALFA) survey. The information from each pulsar candidate is synthesized in four diagnostic plots, which consist of image data with up to thousands of pixels. The AI takes these data from each candidate as its input and uses thousands of such candidates to train its ∼9000 neurons. The deep neural networks in this AI system grant it superior ability to recognize various types of pulsars as well as their harmonic signals. The trained AI's performance has been validated with a large set of candidates from a different pulsar survey, the Green Bank North Celestial Cap survey. In this completely independent test, the PICS ranked 264 out of 277 pulsar-related candidates, including all 56 previously known pulsars and 208 of their harmonics, in the top 961 (1%) of 90,008 test candidates, missing only 13 harmonics. The first non-pulsar candidate appears at rank 187, following 45 pulsars and 141 harmonics. In other words, 100% of the pulsars were ranked in the top 1% of all candidates, while 80% were ranked higher than any noise or interference. The performance of this system can be improved over time as more training data are accumulated. This AI system has been integrated into the PALFA survey pipeline and has discovered six new pulsars to date.

79 ASTRONOMY AND ASTROPHYSICS↗