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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.

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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2011

Modeling the tagged-neutron UXO identification technique using the Geant4 toolkit

It is proposed to use 14 MeV neutrons tagged by the associated particle neutron time-of-flight technique (APnTOF) to identify the fillers of unexploded ordnances (UXO) by characterizing their carbon, nitrogen and oxygen contents. To facilitate the design and construction of a prototype system, a preliminary simulation model was developed, using the Geant4 toolkit. This work established the toolkit environment for (a) generating tagged neutrons, (b) their transport and interactions within a sample to induce emission and detection of characteristic gamma-rays, and (c) 2D and 3D-image reconstruction of the interrogated object using the neutron and gamma-ray time-of-flight information. Using the modeling, this article demonstrates the novelty of the tagged-neutron approach for extracting useful signals with high signal-to-background discrimination of an object-of-interest from that of its environment. Simulations indicated that an UXO filled with the RDX explosive, hexogen (C{sub 3}H{sub 6}O{sub 6}N{sub 6}), can be identified to a depth of 20 cm when buried in soil.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2013

Molecular-level Design of Heterogeneous Chiral Catalysts

Understanding and controlling selectivity is one of the key challenges in heterogeneous catalysis. Among problems in catalytic selectivity enantioselectivity is perhaps the most the most challenging. The primary goal of the project on “Molecular-level Design of Heterogeneous Chiral Catalysts” is to understand the origins of enantioselectivity on chiral heterogeneous surfaces and catalysts. The efforts of the project team include preparation of chiral surfaces, characterization of chiral surfaces, experimental detection of enantioselectivity on such surfaces and computational modeling of the interactions of chiral probe molecules with chiral surfaces. Over the course of the project period the team of PI’s has made some of the most detailed and insightful studies of enantioselective chemistry on chiral surfaces. This includes the measurement of fundamental interactions and reaction mechanisms of chiral molecules on chiral surfaces and leads all the way to rationale design and synthesis of chiral surfaces and materials for enantioselective surface chemistry. The PI’s have designed and prepared new materials for enantioselective adsorption and catalysis. Naturally Chiral Surfaces • Completion of a systematic study of the enantiospecific desorption kinetics of R-3-methylcyclohexanone (R-3-MCHO) on 9 achiral and 7 enantiomeric pairs of chiral Cu surfaces with orientations that span the stereographic triangle. • Discovery of super-enantioselective tartaric acid (TA) and aspartic acid (Asp) decomposition as a result of a surface explosion mechanism on Cu(643)R&S. Systematic study of super-enantiospecific TA and Asp decomposition on five enantiomeric pairs of chiral Cu surfaces. • Initial observation of the enantiospecific desorption of R- and S-propylene oxide (PO) from Cu(100) imprinted with {3,1,17} facets by L-lysine adsorption. Templated Chiral Surfaces • Initial observation of the enantiospecific desorption of R- and S-PO from Pt(111) and Pd(111) modified by a variety of chiral templates. • Demonstrated enantioselective separation of racemic PO on chemically synthesized chiral gold nanoparticles. • Discovery of zwitterionic adsorption states of amino acids on Pd(111). • First structure determinations of adsorbed amino acids and identification of tetrameric chiral template structures. • Exploration of the enantiospecific interaction of PO and R-3-MCHO adsorption on chirally modified Cu(100), Cu(110) and Cu(111). One-to-One Interactions • Determination of cinchona orientation on Pt surfaces in situ at the solid-liquid interface using FT-IRAS. • Systematic study of the influence of solution properties on the adsorption of modified cinchonas alkaloids onto Pt surfaces. • Correlation of cinchona adsorption with catalytic activity, as affected by concentration, the nature of the solvent, and dissolved gases in the liquid phase. • Measurement of enantioselective chemisorption on 1-(1-naphthyl) ethylamine (NEA) modified Pt(111) and Pd(111) surfaces. • Imaging of chiral docking complexes between NEA and methyl pyruvate on Pd(111). Chiral Catalyst Synthesis • Anchoring of cinchona alkaloid to surfaces • Synthesis of chiral Au nanoparticles and demonstration of their enantiospecific interactions with R- and S-PO. • Elucidation of the driving forces for chiral imprinting of Cu(100) by L- and D-lysine to form Cu(3,1,17)R&S facets.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Possibility to Identify the Contributions from Collapsars, Supernovae, and Neutron Star Mergers from the Evolution of the r-process Mass Abundance Distribution

We study the evolution of rapid neutron-capture process (r-process) isotopes in the galaxy. We analyze relative contributions from core-collapse supernovae (CCSNe), neutron star mergers, and collapsars under a range of astrophysical conditions and nuclear input data. Here we show that, although the r-process in each of these sites can lead to a similar (universal) elemental distribution, the detailed isotopic abundances can differ from one site to another. These differences may allow for the identification of which sources contributed to the early evolution of r-process material in the galaxy. Our simulations suggest that the early evolution was dominated by CCSNe and collapsar r-process nucleosynthesis. This conclusion may be testable if the next generation of observatories can deduce isotopic r-process abundances.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Illuminating the North Korean nuclear explosion test in 2017 using remote infrasound observations

North Korea conducted its sixth underground nuclear explosion test (mb 6.3) on 2017 September 3. The underground explosion produced substantial low-frequency atmospheric waves, which were detected by infrasound arrays located up to a distance of 566 km. These infrasound waves are formed by the conversion of seismic energy to acoustic energy across the lithosphere–atmosphere interface. While infrasound records at regional distances produce estimates of ground motion amplitude over spatially extended regions covering about 26 500 km 2 , 3-D full seismo-acoustic simulations within the lithosphere and atmosphere provide quantitative information about seismo-acoustic energy partitioning. Our results demonstrate the capability of remote infrasound observations combined with 3-D propagation modelling to further develop discrimination methods for underground sources. These results contribute to enhance the confidence of source identification and characterization in nuclear test monitoring research, which is essential for the enforcement of the Comprehensive Nuclear-Test-Ban Treaty.

58 GEOSCIENCES↗
DOE OSTI2026

Latent space dynamics identification for interface tracking with application to shock-induced pore collapse

Capturing sharp, evolving interfaces remains a central challenge in reduced-order modeling, especially when data is limited and the system exhibits localized nonlinearities or discontinuities. Here, we propose LaSDI-IT (Latent Space Dynamics Identification for Interface Tracking), a data-driven framework that combines low-dimensional latent dynamics learning with explicit interface-aware encoding to enable accurate and efficient modeling of physical systems involving moving material boundaries. At the core of LaSDI-IT is a revised autoencoder architecture that jointly reconstructs the physical field and an indicator function representing material regions or phases, allowing the model to track complex interface evolution without requiring detailed physical models or mesh adaptation. The latent dynamics are learned through linear regression in the encoded space and generalized across parameter regimes using Gaussian process interpolation with greedy sampling. We demonstrate LaSDI-IT on the problem of shock-induced pore collapse in high explosives, a process characterized by sharp temperature gradients and dynamically deforming pore geometries. The method achieves relative prediction errors below 9% across the parameter space, accurately recovers key quantities of interest such as pore area and hot spot formation, and matches the performance of dense training with only half the data. This latent dynamics prediction was 10 6 times faster than the conventional high-fidelity simulation, proving its utility for multi-query applications. These results highlight LaSDI-IT as a general, data-efficient framework for modeling discontinuity-rich systems in computational physics, with potential applications in multiphase flows, fracture mechanics, and phase change problems.

Gaussian process↗
DOE OSTI2015

Big Data Analytics for Demand Response: Clustering Over Space and Time

The pervasive deployment of advanced sensing infrastructure in Cyber-Physical systems, such as the Smart Grid, has resulted in an unprecedented data explosion. Such data exhibit both large volumes and high velocity characteristics, two of the three pillars of Big Data, and have a time-series notion as datasets in this context typically consist of successive measurements made over a time interval. Time-series data can be valuable for data mining and analytics tasks such as identifying the “right” customers among a diverse population, to target for Demand Response programs. However, time series are challenging to mine due to their high dimensionality. In this paper, we motivate this problem using a real application from the smart grid domain. We explore novel representations of time-series data for BigData analytics, and propose a clustering technique for determining natural segmentation of customers and identification of temporal consumption patterns. Our method is generizable to large-scale, real-world scenarios, without making any assumptions about the data. We evaluate our technique using real datasets from smart meters, totaling ~ 18,200,000 data points, and show the efficacy of our technique in efficiency detecting the number of optimal number of clusters.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1990

Near-infrared mapping of spiral barred galaxies

In external galaxies, near-infrared emission originates from stellar populations, hot dust, free-free emission from H+ regions, gaseous emission, non-thermal nucleus if any. Because of the low extinction compared to the visible, infrared wavelengths are useful to probe regions obscured by dust such as central parts where starburst phenomena can occur because of the large quantity of matter. The results presented were obtained with a 32 x 32 InSb charge injection device (CID) array cooled at 4K, at the f/36 cassegrain focus of the 3m60 Canada-France-Hawaii telescope with a spatial resolution of 0.5 inches per pixel. The objects presented are spiral barred galaxies mapped at J(1.25 microns), H(1.65 microns) and K(2.2 microns). The non-axisymetric potential due to the presence of a bar induces dynamical processes leading to the confinement of matter and peculiar morphologies. Infrared imaging is used to study the link between various components. Correlations with other wavelengths ranges and 2-colors diagrams ((J-H), (H-K)) lead to the identification of star forming regions, nucleus. Maps show structures connected to the central core. The question is, are they flowing away or toward the nucleus. Observations of M83 lead to several conclusions. The star forming region, detected in the visible and the infrared cannot be very compact and must extend to the edge of the matter concentration. The general shape of the near-infrared emission and the location of radio and 10 micron peaks suggest the confinement of matter between the inner Linblad resonances localized from CO measurements about 100 and 400 pc. The distribution of color indices in the arc from southern part to the star forming region suggests an increasing amount of gas and a time evolution eventually triggered by supernova explosions. Close to the direction of the bar, a bridge-like structure connects the arc to the nucleus with peculiar color indices. Perhaps, this structure can be linked to a height velocity component seen in UV and we can attribute it to a jet and/or a matter flow along the bar toward the nucleus, fuelling it. NGC 1068 is the nearest Seyfert 2 galaxy. It has been a subject of many studies at all wavelengths. This object was mapped at J, H, K, L and M, and in polaro-imagery. Results are given.

Gallais, P.↗
DOE OSTI2015

Large Scale Comparative Visualisation of Regulatory Networks with TRNDiff

The advent of Next Generation Sequencing (NGS) technologies has seen explosive growth in genomic datasets, and dense coverage of related organisms, supporting study of subtle, strain-specific variations as a determinant of function. Such data collections present fresh and complex challenges for bioinformatics, those of comparing models of complex relationships across hundreds and even thousands of sequences. Transcriptional Regulatory Network (TRN) structures document the influence of regulatory proteins called Transcription Factors (TFs) on associated Target Genes (TGs). TRNs are routinely inferred from model systems or iterative search, and analysis at these scales requires simultaneous displays of multiple networks well beyond those of existing network visualisation tools [1]. In this paper we describe TRNDiff, an open source system supporting the comparative analysis and visualization of TRNs (and similarly structured data) from many genomes, allowing rapid identification of functional variations within species. The approach is demonstrated through a small scale multiple TRN analysis of the Fur iron-uptake system of Yersinia, suggesting a number of candidate virulence factors; and through a larger study exploiting integration with the RegPrecise database (http://regprecise.lbl.gov; [2]) - a collection of hundreds of manually curated and predicted transcription factor regulons drawn from across the entire spectrum of prokaryotic organisms.

Bioinformatics, Visualisation, Transcription, Regu↗
DOE OSTI2023

Seismoacoustic Data Fusion for Ground Coupled Airwaves: a FACT Case Study for Calibration and Array Processing

This report covers an inquiry into seismoacoustic array processing using infrasound arrivals combined with resulting Ground Coupled Airwaves (GCA) that are present on collocated seismic sensors. In preparation, data calibration and denoising is completed for a seismoacoustic sensor array that was deployed at the Facility for Acceptance, Calibration, and Testing on Kirtland Airforce Base from August through September of 2021. The events of interest for this study are small, local explosive sources that lead to short duration, impulsive signals on the instruments. The goal is to determine if combining infrasound signals with the corresponding GCAs on collocated seismic sensors can be used to improve the results returned by automated signal detection and characterization (e.g., back azimuth estimates). Preparation for seismic and infrasound data involves removing the instrument response so that sensors have flat power spectra over the frequency range 0.1-10 Hz, where signal from events of interest may be detected. After instrument response removal, deployment conditions specific to this array require a retrospective noise analysis to determine station emplacement characteristics. Once all data is calibrated, a manual search is performed for possible GCA arrivals across the seismoacoustic network. These arrivals are then processed through beamforming and subsequent event identification, resulting in a catalogue of seismoacoustic GCA arrivals with corresponding back azimuth and trace velocity estimations.

47 OTHER INSTRUMENTATION↗
NASA NTRS1995

A Hubble Space Telescope study of the underlying white dwarf in the dwarf nova VW Hydri during quiescence

We have analyzed a far-ultraviolet spectrum of the dwarf nova VW Hyi obtained during quiescence with the Hubble Space Telescope Faint Object Spectrograph (HST FOS). The observation occurred 10 days after the return to optical quiescence from a superoutburst of VW Hyi. The spectrum reveals a very strong Stark-broadened Ly-alpha absorption with narrow geocoronal emission, and a very rich metallic absorption-line spectrum dominated by strong resonance absorption features of singly and doubly ionized silicon and carbon, the first solid identification of metallic absorption features arising in the accreted atmosphere of the white dwarf. We confirm the reported low-resolution IUE detection of the underlying white dwarf photosphere by Mateo & Szkody. A synthetic spectral analysis with hot, high-gravity LTE model atmospheres yields a best-fit model with the following parameters: T(sub eff) = 22,000 +/- 1000 K, log g = 8.0 +/- 0.3, with chemical abundances for oxygen of 0.3 times solar, for nitrogen of 5 times solar, and for all other heavy elements of 0.15 times solar. Based upon our absorption-line measurements of the observations at different orbital phases, we find no conclusive evidence of equivalent width variations with orbital phase. In the absence of any significant reduction of the white dwarf's core mass by past nova explosions, its lower limit cooling age is approximately 50 million years.

Sion, Edward M.↗
DOE OSTI2025

Exploiting correlations in multi-coincidence Coulomb explosion patterns for differentiating molecular structures using machine learning

Coulomb explosion imaging (CEI) is a powerful technique for capturing the real-time motion of individual atoms during ultrafast photochemical reactions. CEI generates high-dimensional data with naturally embedded correlations that allow mapping the coordinated motion of nuclei in molecules. This enables reliable separation of competing reaction pathways and makes this approach uniquely suited for characterizing weak reaction channels. However, rich information contained in experimental CEI patterns remains largely underexploited due to challenges in visualizing correlations between multiple observables in multi-dimensional parameter space. Here we present a new approach to CEI of intermediate-sized polyatomic molecules, detecting up to eight ionic fragments in coincidence and leveraging machine-learning-based analysis to identify patterns and correlations in the resulting high-dimensional momentum-space data, enabling robust molecular structure identification and differentiation. Our approach provides high-dimensional background-free data encoding exceptionally rich structural information and establishes an automated, scalable framework for extracting insightful information from the data. As a demonstration, we apply this method to image and distinguish dichloroethylene isomers, showcasing its potential for broader applications in molecular imaging. Our results pave the way for channel-specific analysis of ultrafast structural dynamics in chemically relevant systems, particularly for disentangling mixed reaction pathways and detecting contributions from weak channels and minority species.

Chemical Physics (physics.chem-ph)↗
NASA NTRS2022

The 2019 Raikoke volcanic eruption -Part 2: Particle-phase dispersion and concurrent wildfire smoke emissions

Between 27 June and 14 July 2019 aerosol layers were observed by the United Kingdom (UK) Raman lidar network in the upper troposphere and lower stratosphere. The arrival of these aerosol layers in late June caused some concern within the London Volcanic Ash Advisory Centre (VAAC) as according to dispersion simulations the volcanic plume from the 21 June 2019 eruption of Raikoke was not expected over the UK until early July. Using dispersion simulations from the Met Office Numerical Atmospheric-dispersion Modelling Environment (NAME), and supporting evidence from satellite and in situ aircraft observations, we show that the early arrival of the stratospheric layers was not due to aerosols from the explosive eruption of the Raikoke volcano but due to biomass burning smoke aerosols associated with intense forest fires in Alberta, Canada, that occurred 4 d prior to the Raikoke eruption. We use the observations and model simulations to describe the dispersion of both the volcanic and forest fire aerosol clouds and estimate that the initial Raikoke ash aerosol cloud contained around 15 Tg of volcanic ash and that the forest fires produced around 0.2 Tg of biomass burning aerosol. The operational monitoring of volcanic aerosol clouds is a vital capability in terms of aviation safety and the synergy of NAME dispersion simulations, and lidar data with depolarising capabilities allowed scientists at the Met Office to interpret the various aerosol layers over the UK and attribute the material to their sources. The use of NAME allowed the identification of the observed stratospheric layers that reached the UK on 27 June as biomass burning aerosol, characterised by a particle linear depolarisation ratio of 9 %, whereas with the lidar alone the latter could have been identified as the early arrival of a volcanic ash–sulfate mixed aerosol cloud. In the case under study, given the low concentration estimates, the exact identification of the aerosol layers would have made little substantive difference to the decision-making process within the London VAAC. However, our work shows how the use of dispersion modelling together with multiple observation sources enabled us to create a more complete description of atmospheric aerosol loading.

Martin J Osborne↗
NASA NTRSDate not supplied

A Survey Protocol to Assess Meaningfulness and Usefulness of Automated Topic Finding in the NASA Aviation Safety Reporting System

Context: The NASA Aviation Safety Reporting System (ASRS) is a voluntary confidential aviation safety reporting system. The ASRS receives reports from pilots, air traffic controllers, flight attendants and other involved in aviation operations. The reports are de-identified and coded by ASRS expert safety analysts and a short descriptive synopsis is written to describe the safety issue. The de-identified reports are then disseminated to the aviation community in a number of ways including entry into an online database, Safety Alert Bulletins and For Your Information Notices, and the CALLBACK newsletter. Key to these publications are the timely processing (de-identification, coding and summarization) of new reports, which is currently done by ASRS expert safety analysts. Thus, we believe topic modelling could decrease effort in ASRS, if topics are comprehensible. Aim: We propose a methodology to evaluate whether automated topic finding using topic modelling provides meaningful and useful topics. Method: We extend the total error survey methodology to evaluate user topic comprehension of machine learning outputs. To accomplish this we performed a literature review to identify existing methods and define a construct for topic comprehension, utilizing existing ASRS synopsis writing practices to more precisely define meaningfulness and usefulness. Results: A survey protocol was created that addresses the limitations of other survey protocols found in the literature review, which we found lacking in rationale and clear protocol definition. Conclusion: The surveying of user understanding in machine learning outputs presents challenges due to the explosion of parameters to control for and the lack of systematic approach presented in the literature. More reproducible work and survey protocols are needed in the literature and our work is one step towards that direction.

topic finding↗
NASA NTRS1997

Relaxation Revisited: A Fresh Look at Multigrid for Steady Flows

The year 1971 saw the publication of one of the landmark papers in computational aerodynamics, that of Murman and Cole. As with many seminal works, its significance lies not so much in the specific problem that it addressed| small disturbance, plane transonic flow - but in the identification of a general approach to the solution of a technically important and theoretically difficult problem. The key features of Murman and Cole's work were the use of type- dependent differencing to correctly account for the proper domain of dependence of a mixed elliptic/hyperbolic equation, and the introduction of line relaxation to solve the steady flow equation. All subsequent work in transonic potential flows was based on these concepts. Jameson extended Murman and Cole's ideas to the full potential equation with two important contributions. First, he introduced the rotated difference stencil, which generalized the Murman and Cole type-dependent difference operator to general coordinates. Second, he used the interpretation, introduced by Garabedian, of relaxation as an iteration in artificial time to construct stable relaxation schemes, generalizing the original line relaxation method of Reference. The decade of the 1970s saw an explosion of activity in the solution of transonic potential flows, which has been summarized in the review article of Caughey.

Roberts, Thomas W.↗
DOE OSTI2014

Optimized Uncertainty Quantification Algorithm Within a Dynamic Event Tree Framework

Methods for developing Phenomenological Identification and Ranking Tables (PIRT) for nuclear power plants have been a useful tool in providing insight into modelling aspects that are important to safety. These methods have involved expert knowledge with regards to reactor plant transients and thermal-hydraulic codes to identify are of highest importance. Quantified PIRT provides for rigorous method for quantifying the phenomena that can have the greatest impact. The transients that are evaluated and the timing of those events are typically developed in collaboration with the Probabilistic Risk Analysis. Though quite effective in evaluating risk, traditional PRA methods lack the capability to evaluate complex dynamic systems where end states may vary as a function of transition time from physical state to physical state . Dynamic PRA (DPRA) methods provide a more rigorous analysis of complex dynamic systems. A limitation of DPRA is its potential for state or combinatorial explosion that grows as a function of the number of components; as well as, the sampling of transition times from state-to-state of the entire system. This paper presents a method for performing QPIRT within a dynamic event tree framework such that timing events which result in the highest probabilities of failure are captured and a QPIRT is performed simultaneously while performing a discrete dynamic event tree evaluation. The resulting simulation results in a formal QPIRT for each end state. The use of dynamic event trees results in state explosion as the number of possible component states increases. This paper utilizes a branch and bound algorithm to optimize the solution of the dynamic event trees. The paper summarizes the methods used to implement the branch-and-bound algorithm in solving the discrete dynamic event trees.

42 ENGINEERING↗
DOE OSTI2023

Quantification of spatial and seasonal trends in the atmosphere and construction of statistical models for infrasonic propagation

SUMMARY Infrasonic waves are influenced by variations in the density, pressure and temperature as well as the ambient winds. Modelling infrasonic propagation can be challenging due to the dynamic nature of the atmosphere as well as the sparseness of measurements which result in variability and notable uncertainty. A framework is presented to quantify spatial and seasonal trends in atmospheric structure via analysis of the effective sound speed profile and identification of temporal trends in the middle atmospheric waveguide produced by the circumpolar vortex winds. Seasonal definitions identifying typical atmospheric structures during the summer, winter and spring/fall transition periods are identified using atmospheric data from 2010 through 2020. Seasonal trend analysis is conducted for a number of locations across the contiguous United States to quantify spatial variations in atmospheric structure that impact infrasonic propagation. For each season and location, empirical orthogonal function analysis is used to reduce the historical archive of atmospheric data into a smaller representative set that can be analysed using numerical tools more efficiently. Infrasonic ray tracing and finite-frequency modal propagation analyses are applied to construct propagation path geometry and transmission loss statistics which are useful in localization and yield estimation for infrasonic sources, respectively. An example application is detailed in which transmission loss statistics are combined with an explosive source model and noise statistics to quantify the capability of a network to detect nearby sources.

58 GEOSCIENCES↗
DOE OSTI2021

Level structure of the T z = –1 nucleus 34 Ar and its relevance for nucleosynthesis in ONe novae

The 24 Mg+ 12 C fusion reaction was used to perform a detailed γ-ray spectroscopy study of the astrophysically important nucleus 34 Ar. In particular, an experimental setup, coupling the advanced γ-ray tracking array GRETINA with the well-established Argonne fragment mass analyzer (FMA), was employed to obtain excitation energies and spin-parity assignments for excited states in 34 Ar, both above and below the proton separation energy. For the first time, an angular distribution analysis of in-beam γ rays from fusion-evaporation reactions, using a tracking array, has been performed and Coulomb energy differences of analog states in the T = 1, A = 34 mirror system, explored from 0 to 6 MeV. Lastly, we present a comprehensive discussion of the astrophysical 33 Cl(p,γ) stellar reaction rate, together with implications for the identification of nova presolar grains from sulfur isotopic abundances.

20 ≤ A ≤ 38↗
DOE OSTI2014

A BLUE POINT SOURCE AT THE LOCATION OF SUPERNOVA 2011DH

We present Hubble Space Telescope (HST) observations of the field of the Type IIb supernova (SN) 2011dh in M51 performed at ≈1161 rest-frame days after explosion using the Wide Field Camera 3 and near-UV filters F225W and F336W. A star-like object is detected in both bands and the photometry indicates it has negative (F225W – F336W) color. The observed object is compatible with the companion of the now-vanished yellow supergiant progenitor predicted in interacting binary models. We consider it unlikely that the SN is undergoing strong interaction and thus estimate that it makes a small contribution to the observed flux. The possibilities of having detected an unresolved light echo or an unrelated object are briefly discussed and judged unlikely. Adopting a possible range of extinction by dust, we constrain parameters of the proposed binary system. In particular, the efficiency of mass accretion onto the binary companion must be below 50%, if no significant extinction is produced by newly formed dust. Further multiband observations are required in order to confirm the identification of the object as the companion star. If confirmed, the companion star would already be dominant in the UV-optical regime, so it would readily provide a unique opportunity to perform a detailed study of its properties.

79 ASTRONOMY AND ASTROPHYSICS↗