Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Precision spectroscopy”

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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Studying f-Electron Contributions in Thorium and Uranium Containing Molecules

The pure rotational spectra of several actinide-containing compounds have been improved upon and, in two cases, been recorded for the first time. The diatomic molecules HfS and ThS have been studied in their ground electronic states but high vibrationally excited states. The results have yielded very accurate locations of the minima of the potential energy curves. The asymmetric molecules OThS and UO2S have been prepared by laser ablation synthesis and their pure rotational spectra recorded for the first time. Precise information pertinent to the geometric and electronic structure of these molecules has been obtained and is compared with other, newly recorded and related species such as OCeS.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Data-Enabled Fusion Technology (Final Scientific/Technical Report)

Advancing Scientific Understanding in Fusion Energy and Machine Learning This research represented a significant step forward in machine learning (ML) applications for fusion energy experiments. The project integrated advanced data-driven modeling, optimization techniques, and artificial intelligence to enhance the predictive capabilities and operational efficiency of plasma-based fusion systems. Specifically, tasks focused on ML-enhanced diagnostics, operator guidance tools, and predictive modeling helped improve the ability to interpret complex fusion experiments. Key areas of advancement included: 1) data-driven plasma control, i.e., using ML algorithms to optimize experimental conditions and classify plasma behaviors based on historical data; 2) spectroscopy and diagnostics, i.e., applying AI models to extract previously inaccessible insights from experimental spectroscopy data; and 3) configuration mapping and operator guidance, i.e., developing a predictive framework to assist scientists in identifying the most effective experimental parameters, reducing reliance on manual adjustments. By refining these ML-driven techniques, the project contributed to the broader scientific community’s understanding of plasma dynamics and fusion energy viability. Technical Effectiveness and Economic Feasibility The methods investigated demonstrated high technical effectiveness, as reflected in milestones assessing the predictive accuracy, performance, and optimization of fusion configurations. The development of an Operator Guidance Tool (OGT), for example, led to more precise control of plasma conditions by learning from experimental data and offering real-time adjustments. From an economic standpoint, DeFT provided: 1) the ability to reduce trial-and-error experimentation, which lowered operational costs; 2) improved data interpretation methods, which enabled more efficient resource allocation in large-scale fusion research projects; and 3) the automation of key diagnostic tasks, which reduced manual labor and human error, increasing overall efficiency. 13 The final assessments of predictive models and optimization strategies demonstrated that these approaches were scalable and could be implemented across multiple fusion energy research programs. Public Benefit and Societal Impact This project contributed directly to the broader goal of achieving sustainable and commercially viable fusion energy, which had profound implications for clean energy production and climate change mitigation. The integration of AI-driven solutions into fusion research: 1) sped up scientific discovery, accelerating progress towards achieving energy breakthroughs; 2) reduced the cost of experimentation, making fusion research more accessible; and 3) provided a framework for future AI applications in high-energy physics, benefiting adjacent fields like space exploration, material science, and renewable energy. Additionally, by fostering collaborations between AI researchers and plasma physicists, this project promoted interdisciplinary innovation that could lead to broader applications beyond fusion research.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Spin squeezing in an ensemble of nitrogen–vacancy centres in diamond

Spin-squeezed states provide a seminal example of how the structure of quantum mechanical correlations can be controlled to produce metrologically useful entanglement. These squeezed states have been demonstrated in a wide variety of quantum systems ranging from atoms in optical cavities to trapped ion crystals. By contrast, despite their numerous advantages as practical sensors, spin ensembles in solid-state materials have yet to be controlled with sufficient precision to generate targeted entanglement such as spin squeezing. Here we report the experimental demonstration of spin squeezing in a solid-state spin system. Our experiments are performed on a strongly interacting ensemble of nitrogen–vacancy colour centres in diamond at room temperature, and squeezing (−0.50 ± 0.13 dB) below the noise of uncorrelated spins is generated by the native magnetic dipole–dipole interaction between nitrogen–vacancy centres. To generate and detect squeezing in a solid-state spin system, we overcome several challenges. First, we develop an approach, using interaction-enabled noise spectroscopy, to characterize the quantum projection noise in our system without directly resolving the spin probability distribution. Second, noting that the random positioning of spin defects severely limits the generation of spin squeezing, we implement a pair of strategies aimed at isolating the dynamics of a relatively ordered sub-ensemble of nitrogen–vacancy centres. Furthermore, our results open the door to entanglement-enhanced metrology using macroscopic ensembles of optically active spins in solids.

Atomic and molecular physics↗
DOE OSTI2024

Aspects of Physics at Jefferson Lab’s Halls A, B, and C

CEBAF delivers the world?s highest intensity and highest precision multi-GeV electron beams and has been do so for more than 25 years. In Fall 2017, with the completion of the 12 GeV upgrade and the start of the 12 GeV science program, a new era at the Laboratory began. The 12 GeV era is now well under way and many experimental results are delivered from the three Halls A, B, and C that receive electron beams. This talk will cover measurements of the J/? photo- and electroproduction cross section near threshold by different experiments in Halls B and C, the spectroscopy of strange and multi-strange baryons with the CLAS12 spectrometer in Hall B, and the rich program in hypernuclear physics that will get addressed by an extended measurement campaign in Hall C. Future equipment in Hall A (SoLID) will extend the J/? studies in photo- and electroproduction with increased luminosity and kinematic reach.

Achenbach, Patrick↗
DOE OSTI2020

Photoinduced charge transfer in transition metal dichalcogenide heterojunctions – towards next generation energy technologies

Increasing interest in using two-dimensional transition metal dichalcogenides (2D TMDCs) in optical energy conversion technologies creates a demand for improving the yields and lifetimes of photogenerated charge carriers. Despite inherently fast photocarrier decay in neat 2D TMDCs, the unique photophysics in these quantum-confined systems motivates continued effort to control the evolution of photoexcited states and create functional devices. Here, an intriguing strategy to accomplish this goal is to employ TMDCs in heterojunctions with appropriate semiconductors, where energy level offsets drive photoinduced charge transfer (PCT) across material interfaces. PCT in TMDC-based systems can be optimized for many different applications, such as driving free carriers to photocatalytic sites for redox reactions like water splitting, extracting charge to perform work in photovoltaics or photodetectors, and manipulating the spin and momentum valley electronic degrees of freedom for quantum computing systems. Here, we review recent strides in optimizing PCT for such applications through greater fundamental understanding of the photophysics that occurs at TMDC/semiconductor interfaces. After giving an overview of isolated TMDC properties, synthetic methods, and the basics of PCT, we discuss TMDCs in heterojunctions with several classes of materials, including other TMDCs, small molecule semiconductors, polymers, single-walled carbon nanotubes, quantum dots, perovskites, and electrolytes. In addition to highlighting the unique benefits of each materials category, we also identify parallels across common themes, such as the roles of charge-transfer states, spin, electronic coupling, delocalization, interfacial atomic morphology, and the precise design of energy landscapes to direct charge and energy motion. We hope to capture a broad range of the valuable work in this fast-paced field to inspire new research directions for employing PCT in targeted TMDC-based systems.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2023

Combining femtosecond laser annealing and shallow ion implantation for local color center creation in diamond

A common technique for color center creation in wideband gap semiconductors employs ion implantation and a subsequent thermal annealing. In general, this annealing process is conducted in a vacuum oven. Here, we exploit the annealing based on femtosecond laser pulses. For that purpose, we implant fluorine ions at 54 keV and chlorine ions at 74 keV in diamond and perform micrometer precise annealing using focused femtosecond laser pulses at 800 ± (30) nm with different pulse numbers and repetition rates. In this way, we were able to create shallow spots with color centers of varying brightness.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Optical Transmission Spectroscopy of the Terrestrial Exoplanet LHS 3844b from 13 Ground-based Transit Observations

Atmospheric studies of spectroscopically accessible terrestrial exoplanets lay the groundwork for comparative planetology between these worlds and the solar system terrestrial planets. LHS 3844b is a highly irradiated terrestrial exoplanet (R = 1.303 ± 0.022R {sub ⊕}) orbiting a mid-M dwarf 15 parsecs away. Work based on near-infrared Spitzer phase curves ruled out atmospheres with surface pressures ≥10 bars on this planet. We present 13 transit observations of LHS 3844b taken with the Magellan Clay telescope and the LDSS3C multi-object spectrograph covering 620–1020 nm. We analyze each of the 13 data sets individually using a Gaussian process regression, and present both white and spectroscopic light curves. In the combined white light curve we achieve an rms precision of 65 ppm when binning to 10 minutes. The mean white light-curve value of (R {sub p}/R {sub s}){sup 2} is 0.4170 ± 0.0046%. To construct the transmission spectrum, we split the white light curves into 20 spectrophotometric bands, each spanning 20 nm, and compute the mean values of (R {sub p}/R {sub s}){sup 2} in each band. We compare the transmission spectrum to two sets of atmospheric models. We disfavor a clear, solar composition atmosphere (μ = 2.34) with surface pressures ≥0.1 bar to 5.2σ confidence. We disfavor a clear, H{sub 2}O steam atmosphere (μ = 18) with surface pressures ≥0.1 bar to low confidence (2.9σ). Our observed transmission spectrum favors a flat line. For solar composition atmospheres with surface pressures ≥1 bar we rule out clouds with cloud-top pressures of 0.1 bar (5.3σ), but we cannot address high-altitude clouds at lower pressures. Our results add further evidence that LHS 3844b is devoid of an atmosphere.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

New experimental approach to understanding the chemical reactivity of oxide surfaces

Metal oxides have been an attractive option for a range of applications, including hydrogen sensors, microelectronics, and catalysis, due to their reactivity and tunability. The properties of metal oxides can vary greatly on their precise surface structure; however, few surface science techniques can achieve atomistic-level determinations of surface structure, and fewer yet can do so for insulator surfaces. Low energy ion beam analysis offers a potential insulator-compatible solution to characterizing the surface structure of metal oxides. As a feasibility study, we apply low energy ion beam analysis to investigate the surface structure of a magnetite single crystal, Fe 3 O 4 (100). We obtain multi-angle maps using both forward-scattering low energy ion scattering (LEIS) and backscattering impact-collision ion scattering spectroscopy (ICISS). Both sets of experimental maps have intensity patterns that reflect the symmetries of the Fe 3 O 4 (100) surface structure. However, analytical interpretation of these intensity patterns to extract details of the surface structure is significantly more complex than previous LEIS and ICISS structural studies of one-component metal crystals, which had far more symmetries to exploit. To gain further insight into the surface structure, we model our experimental measurements with ion-trajectory tracing simulations using molecular dynamics. Our simulations provide a qualitative indication that our experimental measurements agree better with a subsurface cation vacancy model than a distorted bulk model.

36 MATERIALS SCIENCE↗
DOE OSTI2023

High-resolution rovibrational spectroscopy of trans -formic acid in the v 1 OH stretching fundamental: Dark state coupling and evidence for charge delocalization dynamics

High-resolution infrared (IR) reduced-Doppler absorption spectra of jet-cooled gas phase trans-formic acid in the v 1 OH stretching fundamental region are reported for the first time, obtained by supersonically expanding trans- formic acid/Ar mixtures through a slit jet nozzle source and rotationally cooling to T rot ≈ 10.9(5) K, with ab- sorption signals recorded by high-resolution difference-frequency IR absorption spectroscopy. Two a/b-type rovibrational bands of comparable intensity, one ~10-fold weaker b-type band, and one ~6-fold weaker a-type band are observed, with vibrational band origins at 3570.493(5), 3566.793(5), 3560.032(9), and 3534.6869(2) cm –1 , respectively. Based on previous Raman jet spectroscopic work by Nejad and Sibert [A. Nejad, E.L. Sibert III, The Raman jet spectrum of trans-formic acid and its deuterated isotopologs: Combining theory and experi- ment to extend the vibrational database, J. Chem. Phys. 154(6) (2021) 064301.], these four rovibrational bands have been assigned to v 1 , (v 2 + v 7 ), (v 6 + 2v 7 + 2v 9 ), and 2v 3 , respectively. Specifically, two of the three upper dark states (2 1 7 1 (a') and 6 1 7 2 9 2 (a')) are close enough to the “bright” 1 1 (a') state to facilitate strong anharmonic resonance interactions, which results in intensity mixing into the two zero-order bands that would otherwise be “dark”. Furthermore, our high-resolution spectral analysis reveals that there are local rotational crossings be- tween these zero-order 1 1 and 2 1 7 1 states resulting in extra lines (i.e., some upper levels in the nominally v 1 band have majority zero-order 2 1 7 1 state character). This motivates development of a 3 coupled state (1 1 , 2 1 7 1 , and 6 1 7 2 9 2 ) picture to aid in the spectral analysis, which is able to match all 3 observed band origins and relative band intensities, as well as indicate the necessity of multistate (> 2) coupling. Though limited by range of J and Ka levels (J’ ≤ 9 and K a ’ ≤ 3) populated at supersonic jet temperatures, this work offers first precision spec- troscopic analysis of trans-formic acid in the v 1 OH stretch region, which should aid in assignment of the more complete yet highly congested room temperature FTIR spectra. Lastly, and in sharp contrast to the spectral complexity in the three predominantly b-type bands, the lone a-type 2v 3 rovibrational band at 3534.6869(2) cm –1 is well described by a simple, rigid asymmetric top Hamiltonian.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

237 Np Fission Spectrum Cumulative Fission Product Yield Measurement Using Godiva IV Critical Assembly

Precise integral measurement of fast neutron-induced fission product yields for various actinides is of high interest for applied nuclear science. The goal of this effort is to improve uncertainties in fission product yield values of 237 Np. Fission was induced in a NpO 2 (NO 3 ) target using the Godiva IV critical assembly in burst mode. The irradiated sample was transferred to a high-resolution γ-ray detection setup within 50 minutes. γ-ray list mode data was collected from 50 minutes to 1 week after the irradiation. γ-ray spectroscopy was performed to analyze the time dependent γ-ray yields using an automated peak search algorithm to identify isotopes by their decay γ-ray energy and half-life. Finally, the initial activity for each isotope identified was used to calculate their fission product yield.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

239 Pu Fission Spectrum Cumulative Fission Product Yield Measurement Using Godiva IV Critical Assembly

Precise integral measurement of fast neutron-induced fission product yields for various actinides is of high interest for applied nuclear science. The goal of this effort is to improve uncertainties in fission product yield values of 239 Pu. Fission was induced in a pure 239 Pu (>99%) target using the Godiva IV critical assembly in burst mode. Further, the irradiated sample was transferred to a high-resolution γ-ray detector within 45 minutes. γ-ray list mode data was collected from 45 minutes to 1 week after the irradiation. γ-ray spectroscopy was performed to analyze the time dependent γ-ray yields using an automated peak search algorithm to identify isotopes by their decay γ-ray energy and half-life. The initial activity for each isotope identified was used to calculate their fission product yield.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Quantifying the Impact of Metal Population Distribution in MFI-Supported Mo Catalysts for Methane Dehydroaromatization

Precise evaluation of intrinsic kinetic behavior in Mo/MFI catalysts for methane dehydroaromatization (MDA) is confounded by variations in Mo dispersion and speciation, which are influenced by metal loading and zeolite acidity. This work advances the utility of H 2 -temperature programmed reduction (H 2 -TPR) for characterizing Mo/MFI catalysts by enabling quantitative comparison of MoO x populations distinguished by reduction behavior and linked to initial catalytic performance. A comprehensive H 2 reduction pathway is established through systematic H 2 - TPR studies varying catalyst composition (1–10 wt % Mo, Si/Al = 15, 40, ∞), supplemented by UV-Raman spectroscopy, X-ray powder diffraction, N 2 physisorption, NH 3 -TPD, and advanced spectroscopic analysis (in situ XAS with principal component analysis/multivariate curve resolution—alternating least squares). Two low-temperature H 2 -TPR regions capture distinct Mo populations undergoing initial Mo(VI)→Mo(IV) reduction: a lower-temperature population (Mo-RI) associated primarily with highly dispersed, anchored MoO x species expected to predominantly reside within MFI channels, and a higher-temperature population (Mo-RII) corresponding to a broader set of MoO x species that becomes increasingly bulk-like/extrazeolitic at higher Mo loading. Quantification of these populations provides practical, kinetically relevant descriptors for comparing initial MDA rates across catalysts with varying Mo loading, Si/Al ratio, and MoO x heterogeneity. Application of lower-temperature Mo-RI estimates to kinetic measurements reveals a minimum threshold of ∼0.12 × 10 –3 mol Mo-RI/g cat , above which initial forward benzene rates normalized to this population converge despite differences in metal loading and zeolite Brønsted acidity. This threshold coincides with a transition toward a common C 2 -mediated benzene-forming regime, as indicated by approach-to-equilibrium analysis of methane-to-ethane, ethane-to-ethylene, and ethylene-to-benzene reaction steps. Above this threshold, normalized initial benzene rates are nearly invariant with increasing Mo-RII/Mo-RI population ratio, indicating that excess Mo-RII populations, including bulk-like/extrazeolitic MoO x domains present at higher loading, do not measurably suppress benzene formation associated with anchored and mostly channel-confined Mo population under the initial-rate conditions examined.

Mo/MFI↗
DOE OSTI2023

Tracking Active Phase Behavior on Boron Nitride during the Oxidative Dehydrogenation of Propane Using Operando X-ray Raman Spectroscopy

Hexagonal boron nitride (hBN) is a highly selective catalyst for the oxidative dehydrogenation of propane (ODHP) to propylene. Using a variety of ex situ characterization techniques, the activity of the catalyst has been attributed to the formation of an amorphous boron oxyhydroxide surface layer. The ODHP reaction mechanism proceeds via a combination of surface mediated and gas phase propagated radical reactions with the relative importance of both depending on the surface-to-void-volume ratio. Here we demonstrate the unique capability of operando X-ray Raman spectroscopy (XRS) to investigate the oxyfunctionalization of the catalyst under reaction conditions (1 mm outer diameter reactor, 500 to 550 °C, P = 30 kPa C 3 H 8 , 15 kPa O 2 , 56 kPa He). We probe the effect of a water cofeed on the surface of the activated catalyst and find that water removes boron oxyhydroxide from the surface, resulting in a lower reaction rate when the surface reaction dominates and an enhanced reaction rate when the gas phase contribution dominates. Computational description of the surface transformations at an atomic-level combined with high precision XRS spectra simulations with the OCEAN code rationalize the experimental observations. Finally, this work establishes XRS as a powerful technique for the investigation of light element-containing catalysts under working conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Multiscale characterization and representation of variability in ceramic matrix composites

Low density, high strength, and high creep and oxidation resistance properties of ceramic matrix composites (CMCs) make them an ideal choice for use in extreme environments in space and military applications. This paper presents a detailed characterization study of structural and manufacturing flaws in Carbon fiber Silicon-Carbide-Nitride matrix (C/SiNC) CMCs at different length-scales. Energy-dispersive spectroscopy (EDS) is used for the chemical characterization of the material’s elemental constituents. High-resolution multiscale graphs obtained from scanning electron microscope (SEM) and confocal laser scanning microscope (LSM) are used to characterize the distribution and morphology of defects at different length scales. This is followed by the classification and quantification of the common manufacturing defects. An image processing algorithm based on the image segmentation process is developed to quantify the variability of various scale-dependent architectural parameters. Finally, a three-dimensional stochastic representative volume element (SRVE) generation algorithm is developed to provide precise representations of material textures at multiple length scales. The developed algorithm accurately accounts for material features and flaws based on a range of multiscale structural and defects characterization results.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Finite- and infinite-volume study of DDπ scattering

We develop a comprehensive framework for extracting the pole position and properties of the doubly-charmed tetraquark $T$$^{+}_{cc}$(3875) from lattice QCD data using the relativistic three-particle formalism. This approach incorporates the effect of the one-pion exchange diagram in DDπ and DD ∗ scattering, making it applicable at energies coinciding with the left-hand cut in the partial-wave projected DD ∗ amplitude. We present an example application of this framework to existing lattice QCD data at mπ = 280 MeV. We solve the integral equations describing the DDπ reaction, use LSZ reduction to determine the corresponding DD ∗ amplitude, and find the values of the infinite-volume two- and three-body K matrices that lead to agreement with lattice DD ∗ phase shifts within their uncertainties. Using these K matrices in the three-particle quantization condition, we describe the finite- volume DD ∗ spectrum and find good agreement with the lattice QCD energies. Our results suggest that, at this pion mass, the tetraquark appears as a pair of subthreshold complex poles whose precise location strongly depends on the value of the DDπ three-particle K matrix.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Evaluation of a novel mid-infrared pyrometer for dynamic material experiments

Dynamic experiments create high-pressure shock waves on the microsecond time scale (or smaller), compressing materials to high pressures and temperatures and enabling the study of material properties at these conditions. Other dynamic studies use quasi-isentropic compression to produce similar high pressures at much lower temperatures. High pressure experiments performed on dynamic platforms such as gas-guns, laser, and pinch machines generate up to several hundred GPa in the sample pressure conditions12. Related static studies include diamond anvil cells, which obtain high pressures and have extremely high precision, but are most often conducted at room temperature or modest temperature increases (often <2000K). By combining these methods, material properties across a wide range of thermodynamic conditions can be probed, and a high quality equation of state (EOS) constructed.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Resistive Switching of Spinel Li 4 Ti 5 O 12 Lithium-Ion Battery Material for Neuromorphic Computing

The rapid rise of AI has exposed significant limitations in conventional Von Neumann computing architecture, particularly in regard to speed and energy efficiency. To address these challenges, researchers are exploring a brain-inspired neuromorphic architecture that mimics biological neural networks, enabling massive parallel processing with reduced power consumption for complex AI computational demands. Recent interest has focused on utilizing battery electrodes and solid electrolyte materials for their resistive switching properties in developing a neuromorphic architecture. These properties are precisely tuned through local- and bulk-level chemical composition modifications via voltage bias stimuli. In this study, we demonstrate fabricating a three-terminal lithium-ion electrochemical transistor based on lithium titanium oxide (Li 4 Ti 5 O 12 ), a popular lithium-ion battery anode material. We deposited and characterized LTO thin films using RF sputtering, demonstrating a 6 orders of magnitude increase in electronic conductivity upon lithiation, with conductivity plateauing after 20% lithiation. Density functional theory calculations revealed transformation from the insulating to conducting state, supported by experimental characterization through X-Ray Photoelectron Spectroscopy (XPS) and Direct Current (DC) polarization analyses. The fabricated transistor consisted of LTO as the channel layer, gold as source/drain terminals, lithium phosphorus oxynitride (LiPON) as the lithium-ion conductor, and copper as the gate terminal. The device exhibited clear hysteresis in transfer characteristics due to lithium insertion/extraction processes. Long-term potentiation (LTP) and long-term depression (LTD) measurements showed an asymmetric ratio of 1.425 and maximum/minimum conductance ratio of 7.83. When implemented in a deep neural network (DNN) for MNIST handwritten digit recognition, the device achieved 92.03% accuracy over 20 training epochs. Detailed transport mechanism analysis revealed the crucial role of oxygen vacancies and interface effects in device operation. Our preliminary findings establish LTO-based lithium-ion electrochemical transistors as promising candidates for energy-efficient neuromorphic computing applications, offering potential solutions to traditional Von Neumann architecture limitations.

25 ENERGY STORAGE↗
DOE OSTI2022

SDSS-IV MaNGA: Unveiling Galaxy Interaction by Merger Stages with Machine Learning

We use machine-learning techniques to classify galaxy merger stages, which can unveil physical processes that drive the star formation and active galactic nucleus (AGN) activities during galaxy interaction. The sample contains 4690 galaxies from the integral field spectroscopy survey SDSS-IV MaNGA and can be separated into 1060 merging galaxies and 3630 nonmerging or unclassified galaxies. For the merger sample, there are 468, 125, 293, and 174 galaxies (1) in the incoming pair phase, (2) in the first pericentric passage phase, (3) approaching or just passing the apocenter, and (4) in the final coalescence phase or post-mergers. With the information of projected separation, line-of-sight velocity difference, Sloan Digital Sky Survey (SDSS) gri images, and MaNGA Hα velocity map, we are able to classify the mergers and their stages with good precision, which is the most important score to identify interacting galaxies. For the two-phase classification (binary; nonmerger and merger), the performance can be high (precision > 0.90) with LGBMClassifier . We find that sample size can be increased by rotation, so the five-phase classification (nonmerger, and merger stages 1, 2, 3, and 4) can also be good (precision > 0.85). The most important features come from SDSS gri images. The contribution from the MaNGA Hα velocity map, projected separation, and line-of-sight velocity difference can further improve the performance by 0%–20%. In other words, the image and the velocity information are sufficient to capture important features of galaxy interactions, and our results can apply to all the MaNGA data, as well as future all-sky surveys.

79 ASTRONOMY AND ASTROPHYSICS↗