Journal articles: 'Module spectrogram'

1

Sýkorová, Libuše, Oldřich Šuba, and Jana Knedlova. "Laser Micro-Machining and Temperature Field Simulation." Key Engineering Materials 581 (October 2013): 322–25. http://dx.doi.org/10.4028/www.scientific.net/kem.581.322.

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The parametric thermal field analyses were realized by the finite element method. The analysis was run in the software solver COSMOS/DesignSTAR thermal. The thermal module makes possible to realize cases of the thermal dependences on the material properties. Material data can be entered as a function of the temperature. The thermal and physical characteristic of the polymeric materials are changed very expressively. The output of the analysis was temperature distribution described by various colors and assigned values in the spectrogram.

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Hu, Kang, Shaoming Jin, Hong Ding, and Jin Cao. "The Bridge between Screening and Assessment: Establishment and Application of Online Screening Platform for Food Risk Substances." Journal of Food Quality 2021 (September 23, 2021): 1–9. http://dx.doi.org/10.1155/2021/2275471.

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In order to improve the risk identification ability of the technical support system of food safety supervision, an online screening platform for food risk substances (hereafter referred to as “platform”) was established. The platform aims at the qualitative analysis of unknown compounds and consists of three parts: a standard spectrum library, screening model, and online comparison module. The standard library contains the standard spectra of 527 food risk substances by high-performance liquid chromatography/high-resolution mass spectrometry. The screening comparison algorithm, the core of the screening model, is obtained through the improvement of the existing spectral library search algorithm. The inspector uploads the original spectrum file through the online comparison module; the online comparison module calls the corresponding script to convert the original spectrum file into a standard spectrum file and then uses the screening and comparison algorithm to achieve online real-time comparison. The comparison results are used to determine whether the sample to be tested contains the food risk substances contained in the standard library, so as to realize the preliminary screening of potential food risk substances. The platform supports the spectrogram data format of mainstream instrument manufacturers. The standard spectrogram database can be coconstructed and shared by cooperative laboratories to effectively enrich the types of food risk substances. Through laboratory comparison, data calibration, and model optimization, the screening accuracy of the platform can reach more than 97%. The platform adopts the Internet online screening method, which greatly facilitates the risk investigation and control of national food safety inspection and testing institutions. At the same time, the construction of the screening platform for food risk substances based on high-performance liquid chromatography/high-resolution mass spectrometry, the Internet, big data, and other technologies will provide a new technical means for food safety risk management and control. Hence, it can build a bridge between the screening of risk substances and illegally added substances, as well as risk assessment, risk management, and control.

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Jiang, Weiheng, Xiaogang Wu, Yimou Wang, Bolin Chen, Wenjiang Feng, and Yi Jin. "Time–Frequency-Analysis-Based Blind Modulation Classification for Multiple-Antenna Systems." Sensors 21, no. 1 (January 1, 2021): 231. http://dx.doi.org/10.3390/s21010231.

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Blind modulation classification is an important step in implementing cognitive radio networks. The multiple-input multiple-output (MIMO) technique is widely used in military and civil communication systems. Due to the lack of prior information about channel parameters and the overlapping of signals in MIMO systems, the traditional likelihood-based and feature-based approaches cannot be applied in these scenarios directly. Hence, in this paper, to resolve the problem of blind modulation classification in MIMO systems, the time–frequency analysis method based on the windowed short-time Fourier transform was used to analyze the time–frequency characteristics of time-domain modulated signals. Then, the extracted time–frequency characteristics are converted into red–green–blue (RGB) spectrogram images, and the convolutional neural network based on transfer learning was applied to classify the modulation types according to the RGB spectrogram images. Finally, a decision fusion module was used to fuse the classification results of all the receiving antennas. Through simulations, we analyzed the classification performance at different signal-to-noise ratios (SNRs); the results indicate that, for the single-input single-output (SISO) network, our proposed scheme can achieve 92.37% and 99.12% average classification accuracy at SNRs of −4 and 10 dB, respectively. For the MIMO network, our scheme achieves 80.42% and 87.92% average classification accuracy at −4 and 10 dB, respectively. The proposed method greatly improves the accuracy of modulation classification in MIMO networks.

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Seo, Minji, and Myungho Kim. "Fusing Visual Attention CNN and Bag of Visual Words for Cross-Corpus Speech Emotion Recognition." Sensors 20, no. 19 (September 28, 2020): 5559. http://dx.doi.org/10.3390/s20195559.

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Speech emotion recognition (SER) classifies emotions using low-level features or a spectrogram of an utterance. When SER methods are trained and tested using different datasets, they have shown performance reduction. Cross-corpus SER research identifies speech emotion using different corpora and languages. Recent cross-corpus SER research has been conducted to improve generalization. To improve the cross-corpus SER performance, we pretrained the log-mel spectrograms of the source dataset using our designed visual attention convolutional neural network (VACNN), which has a 2D CNN base model with channel- and spatial-wise visual attention modules. To train the target dataset, we extracted the feature vector using a bag of visual words (BOVW) to assist the fine-tuned model. Because visual words represent local features in the image, the BOVW helps VACNN to learn global and local features in the log-mel spectrogram by constructing a frequency histogram of visual words. The proposed method shows an overall accuracy of 83.33%, 86.92%, and 75.00% in the Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS), the Berlin Database of Emotional Speech (EmoDB), and Surrey Audio-Visual Expressed Emotion (SAVEE), respectively. Experimental results on RAVDESS, EmoDB, SAVEE demonstrate improvements of 7.73%, 15.12%, and 2.34% compared to existing state-of-the-art cross-corpus SER approaches.

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5

Lee. "Music and Voice Separation Using Log-Spectral Amplitude Estimator Based on Kernel Spectrogram Models Backfitting." Journal of the Acoustical Society of Korea 34, no. 3 (2015): 227. http://dx.doi.org/10.7776/ask.2015.34.3.227.

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Iñiguez-Garín, E., D. Hiriart, J. Ramirez-Velez, J. M. Núñez-Alfonso, J. Herrera, and J. Castro-Chacón. "A new spectropolarimeter for the San Pedro Martir National Observatory." Proceedings of the International Astronomical Union 9, S302 (August 2013): 154–55. http://dx.doi.org/10.1017/s1743921314001951.

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AbstractWe present the design of a stellar spectropolarimeter to measure the magnetic field of point sources. The polarization module interfaces the Boller and Chivens (B&Ch) intermediate-low resolution (R ~ 500 − 4000) spectrograph to the 2.1-m telescope of the San Pedro Martir National Astronomical Observatory in Mexico. The module uses a Savart plate to split the beam into two orthogonal states of polarization and a quarter (half) waveplate to measure circular (linear) polarization. The module is mounted to the telescope and it feeds the spectrograph through a set of four fibers, two for the polarized star images and two for the spectrograph calibration lamp. The instrument will be capable of measuring polarization in spectral lines to determine the longitudinal and transversal fields in magnetic stars.

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Djermanov, I., S. Iordanova, and I. Koleva. "Spectrograph coupled with CCD module for high resolution spectroscopy measurements." Journal of Physics: Conference Series 63 (April 1, 2007): 012029. http://dx.doi.org/10.1088/1742-6596/63/1/012029.

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Ozaki, Shinobu. "Design study of an image slicer module for a multiobject spectrograph." Journal of Astronomical Telescopes, Instruments, and Systems 5, no. 03 (June 6, 2019): 1. http://dx.doi.org/10.1117/1.jatis.5.3.035001.

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9

KIM, KANG-MIN, BE-HO JANG, INWOO HAN, JEONG GYUN JANG, HYUN CHUL SUNG, MOO-YOUNG CHUN, SIEK HYUNG, TAE-SEOG YOON, and STEVEN S. VOGT. "DESIGN AND MANUFACTURING OF THE CASSEGRAIN INTERFACE MODULE OF THE BOAO ECHELLE SPECTROGRAPH." Journal of The Korean Astronomical Society 35, no. 4 (December 1, 2002): 221–27. http://dx.doi.org/10.5303/jkas.2002.35.4.221.

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10

Bazovkin, V. M., N. A. Valisheva, A. A. Guzev, V. M. Efimov, A. P. Kovchavtsev, G. L. Kuryshev, I. I. Lee, V. G. Polovinkin, and A. S. Stroganov. "Fast IR spectrograph (0.5–3.0 μm) based on a hybrid 1 × 384 InAs module." Optoelectronics, Instrumentation and Data Processing 43, no. 4 (August 2007): 332–36. http://dx.doi.org/10.3103/s875669900704005x.

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11

Pata, Vladimír, Libuše Sýkorová, Oldřich Šuba, and Milena Kubišová. "Simulation of the Transient Temperature Field when Laser Machining Polymeric Materials." Key Engineering Materials 686 (February 2016): 246–51. http://dx.doi.org/10.4028/www.scientific.net/kem.686.246.

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The paper deals with possibilities of using the laser in technologies. The parametric temperature field analysis was realized by the finite element method. The analysis was run in COSMOS/M software solver. A thermal module HSTAR makes it possible to realize cases of the temperature dependences on the material properties. Material data can be entered as a function of a temperature. The thermal and physical characteristics of the polymeric materials change significantly. The output of the analysis was described by spectrograms with temperature field distribution of various materials.

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Doherty, Hannah Garcia, Roberto Arnaiz Burgueño, Roeland P. Trommel, Vasileios Papanastasiou, and Ronny I. A. Harmanny. "Attention-based deep learning networks for identification of human gait using radar micro-Doppler spectrograms." International Journal of Microwave and Wireless Technologies 13, no. 7 (July 5, 2021): 734–39. http://dx.doi.org/10.1017/s1759078721000830.

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AbstractIdentification of human individuals within a group of 39 persons using micro-Doppler (μ-D) features has been investigated. Deep convolutional neural networks with two different training procedures have been used to perform classification. Visualization of the inner network layers revealed the sections of the input image most relevant when determining the class label of the target. A convolutional block attention module is added to provide a weighted feature vector in the channel and feature dimension, highlighting the relevant μ-D feature-filled areas in the image and improving classification performance.

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Hong, Minki, Hanse Ahn, Othmane Atif, Jonguk Lee, Daihee Park, and Yongwha Chung. "Field-Applicable Pig Anomaly Detection System Using Vocalization for Embedded Board Implementations." Applied Sciences 10, no. 19 (October 7, 2020): 6991. http://dx.doi.org/10.3390/app10196991.

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Failure to quickly and accurately detect abnormal situations, such as the occurrence of infectious diseases, in pig farms can cause significant damage to the pig farms and the pig farming industry of the country. In this study, we propose an economical and lightweight sound-based pig anomaly detection system that can be applicable even in small-scale farms. The system consists of a pipeline structure, starting from sound acquisition to abnormal situation detection, and can be installed and operated in an actual pig farm. It has the following structure that makes it executable on the embedded board TX-2: (1) A module that collects sound signals; (2) A noise-robust preprocessing module that detects sound regions from signals and converts them into spectrograms; and (3) A pig anomaly detection module based on MnasNet, a lightweight deep learning method, to which the 8-bit filter clustering method proposed in this study is applied, reducing its size by 76.3% while maintaining its identification performance. The proposed system recorded an F1-score of 0.947 as a stable pig’s abnormality identification performance, even in various noisy pigpen environments, and the system’s execution time allowed it to perform in real time.

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Gratton, Raffaele, Markus Kasper, Christophe Vérinaud, Mariangela Bonavita, and Hans M. Schmid. "Science with EPICS, the E-ELT planet finder." Proceedings of the International Astronomical Union 6, S276 (October 2010): 343–48. http://dx.doi.org/10.1017/s1743921311020412.

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AbstractEPICS is the proposed planet finder for the European Extremely Large Telescope. EPICS is a high contrast imager based on a high performing extreme adaptive optics system, a diffraction suppression module, and two scientific instruments: an Integral Field Spectrograph (IFS) for the near infrared (0.95-1.65 μm), and a differential polarization imager (E-POL). Both these instruments should allow imaging and characterization of planets shining in reflected light, possibly down to Earth-size. A few high interesting science cases are presented.

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Cersullo, Federica, François Wildi, Bruno Chazelas, and Francesco Pepe. "A new infrared Fabry-Pérot-based radial-velocity-reference module for the SPIRou radial-velocity spectrograph." Astronomy & Astrophysics 601 (May 2017): A102. http://dx.doi.org/10.1051/0004-6361/201629972.

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Pelletier, M. J., J. Slater, K. L. Davis, W. K. Kowalchyk, and I. R. Lewis. "Robust Fiber-Optic Coupled Confocal Raman Microscopy for Research and Quality Control Applications." Microscopy and Microanalysis 3, S2 (August 1997): 823–24. http://dx.doi.org/10.1017/s1431927600011004.

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In this paper we report the continuing development of a novel fiber-optic coupled confocal Raman microscope which can offer spectral resolutions up to 0.6 cm−1 per pixel, spatial resolutions of 1 micron or less with axial resolutions of 2-3 microns. The system is based around a compact base unit which comprises a compact solid-state laser, a proprietary f/1.8 imaging spectrograph, and a TE-cooled CCD detector operating at −70°C.In Figure 1 a schematic of the fiber coupled microscope is shown. The microscope includes a integrated holographic filter module to prevent silica Raman generated in the excitation fiber from reaching the sample and to reject radiation at the excitation wavelength from being returned to the spectrograph via the collection fiber(s). The architecture has been designed to allow both fluorescence imaging and Raman microspectroscopy to be accomplished without removing the sample. The figure also depicts the positions of linear polarizers which can be used to collect polarized Raman spectra from small particles or thin polymer laminate samples.

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Tursunov, Anvarjon, Mustaqeem, Joon Yeon Choeh, and Soonil Kwon. "Age and Gender Recognition Using a Convolutional Neural Network with a Specially Designed Multi-Attention Module through Speech Spectrograms." Sensors 21, no. 17 (September 1, 2021): 5892. http://dx.doi.org/10.3390/s21175892.

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Speech signals are being used as a primary input source in human–computer interaction (HCI) to develop several applications, such as automatic speech recognition (ASR), speech emotion recognition (SER), gender, and age recognition. Classifying speakers according to their age and gender is a challenging task in speech processing owing to the disability of the current methods of extracting salient high-level speech features and classification models. To address these problems, we introduce a novel end-to-end age and gender recognition convolutional neural network (CNN) with a specially designed multi-attention module (MAM) from speech signals. Our proposed model uses MAM to extract spatial and temporal salient features from the input data effectively. The MAM mechanism uses a rectangular shape filter as a kernel in convolution layers and comprises two separate time and frequency attention mechanisms. The time attention branch learns to detect temporal cues, whereas the frequency attention module extracts the most relevant features to the target by focusing on the spatial frequency features. The combination of the two extracted spatial and temporal features complements one another and provide high performance in terms of age and gender classification. The proposed age and gender classification system was tested using the Common Voice and locally developed Korean speech recognition datasets. Our suggested model achieved 96%, 73%, and 76% accuracy scores for gender, age, and age-gender classification, respectively, using the Common Voice dataset. The Korean speech recognition dataset results were 97%, 97%, and 90% for gender, age, and age-gender recognition, respectively. The prediction performance of our proposed model, which was obtained in the experiments, demonstrated the superiority and robustness of the tasks regarding age, gender, and age-gender recognition from speech signals.

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Bogatirov, Igor, Helena Ponuzhdayeva, Denis Koliushko, Serhii Rudenko, and Alexander Istomin. "DIELECTRIC OIL`S TEST MACHINE WISH VOLTAGE RISE ELECTRONIC MODULE." Bulletin of the National Technical University «KhPI» Series: New solutions in modern technologies, no. 1(7) (April 23, 2021): 103–8. http://dx.doi.org/10.20998/2413-4295.2021.01.15.

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For test operations according to the liquid dielectric breakdown voltage measurement method we use high voltage machines that consist of high-voltage step-up transformer, voltage rise block, test cell with electrodes and so on. Described dielectric oil's test machine UIM – 90 with electromechanical voltage rise block. Cause of hard requirements in specification documents about voltage sine wave form on cell's electrodes, we performed field tests for UIM – 90 that help to evaluate the mains voltage impact on the test voltage distortion and measurement accuracy. Was discovered that during usage of electromechanical voltage rise block voltage steps disrupt sine wave’s form proportionally to step-up transformer’s transformation coefficient. Performed analysis of this block’s construction and established that usage of ЛАТР and mechanical voltage controller could lead to additional sine’s wave disruption. Decided to develop electronic voltage rise block which will allow to get rid of mains influence on test data. Created the algorithm of wave shaping from microcontroller, which generates voltage ramp to the amplifier representing pulse width modulator, then to the step-up transformers cascade. Proposed to use additional transformer for level matching of amplifier’s output voltage and main high voltage transformer’s input voltage. Presented flow sheet for UIM – 90 with electronic voltage step-up block and cascading start ofstep-up transformers. Provided voltage oscillograph trace and it spectrograph on the main transformer’s primary side, received due to the implementation of developed electronic voltage step-up block, prove that voltage sine wave form doesn’t rely on mains quality. After upgraded UIM – 90 and it world analogues technical parameters analysis we could make a conclusion about it competitive capability on global level.

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Tamura, Naoyuki. "Prime Focus Spectrograph: A very wide-field, massively multiplexed, optical & near-infrared spectrograph for Subaru Telescope." Proceedings of the International Astronomical Union 11, S319 (August 2015): 55. http://dx.doi.org/10.1017/s1743921315010480.

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AbstractThis short article is about Prime Focus Spectrograph (PFS), a very wide-field, massively-multiplexed, and optical & near-infrared (NIR) spectrograph as a next generation facility instrument on Subaru Telescope. More details and updates are available on the PFS official website (http://pfs.ipmu.jp), blog (http://pfs.ipmu.jp/blog/), and references therein.The project, instrument, & timelinePFS will position 2400 fibers to science targets or blank sky in the 1.3 degree field on the Subaru prime focus. These fibers will be quickly (~60sec) reconfigurable and feed the photons during exposures to the Spectrograph System (SpS). SpS consists of 4 modules each of which accommodate ~600 fibers and deliver spectral images ranging from 380nm to 1260nm simultaneously at one exposure via the 3 arms of blue, red, and NIR cameras. The instrument development has been undertaken by the international collaboration at the initiative of Kavli IPMU. The project is now going into the construction phase aiming at system integration and on-sky engineering observations in 2017-2018, and science operation in 2019.The survey design has also been under development envisioning a survey spanning ~300 nights over ~5 years in the framework of Subaru Strategic Program (SSP). The key science areas are: Cosmology, galaxy/AGN evolution, and Galactic Archaeology (GA) (Takada et al. 2014). The cosmology program will be to constrain the nature of dark energy via a survey of emission line galaxies over a comoving volume of 10 Gpc3 at z=0.8-2.4. In the galaxy/AGN program, the wide wavelength coverage of PFS as well as the large field of view will be exploited to characterize the galaxy populations and its clustering properties over a wide redshift range. A survey of color-selected galaxies/AGN at z = 1-2 will be conducted over 20 square degrees yielding a fair sample of galaxies with stellar masses down to ~1010M⊙. In the GA program, radial velocities and chemical abundances of stars in the Milky Way, dwarf spheroids, and M31 will be used to understand the past assembly histories of those galaxies and the structures of their dark matter halos. Spectra will be taken for 1 million stars as faint as V = 22 mag therefore out to large distances from the Sun.PFS will provide powerful spectroscopic capabilities even in the era of Euclid, LSST, WFIRST and TMT, and the effective synergies are expected for further unique science outputs.

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Seregin, A. G., D. A. Seregin, G. I. Lebedeva, and A. V. Bagrov. "Aiming systems of the OSIRIS stellar interferometer and of a simulator of the interference module of a beamsplitter-spectrograph." Journal of Optical Technology 69, no. 11 (November 1, 2002): 832. http://dx.doi.org/10.1364/jot.69.000832.

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21

Kaplun, Dmitry, Alexander Voznesensky, Sergei Romanov, Valery Andreev, and Denis Butusov. "Classification of Hydroacoustic Signals Based on Harmonic Wavelets and a Deep Learning Artificial Intelligence System." Applied Sciences 10, no. 9 (April 29, 2020): 3097. http://dx.doi.org/10.3390/app10093097.

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This paper considers two approaches to hydroacoustic signal classification, taking the sounds made by whales as an example: a method based on harmonic wavelets and a technique involving deep learning neural networks. The study deals with the classification of hydroacoustic signals using coefficients of the harmonic wavelet transform (fast computation), short-time Fourier transform (spectrogram) and Fourier transform using a kNN-algorithm. Classification quality metrics (precision, recall and accuracy) are given for different signal-to-noise ratios. ROC curves were also obtained. The use of the deep neural network for classification of whales’ sounds is considered. The effectiveness of using harmonic wavelets for the classification of complex non-stationary signals is proved. A technique to reduce the feature space dimension using a ‘modulo N reduction’ method is proposed. A classification of 26 individual whales from the Whale FM Project dataset is presented. It is shown that the deep-learning-based approach provides the best result for the Whale FM Project dataset both for whale types and individuals.

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Vasilyev, V. N., D. A. Sazonenko, D. E. Kukushkin, A. V. Bakholdin, G. G. Valyavin, V. D. Bychkov, G. A. Galazutdinov, A. F. Valeev, and M. V. Yushkin. "A high spectral resolution spectrograph with fiber input for the Big Azimuthal Telescope of SAO RAS. Improvement of the spectral module." Optical Review 23, no. 5 (September 14, 2016): 878–84. http://dx.doi.org/10.1007/s10043-016-0271-1.

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23

Riffel, Rogemar A. "Evidence for an accreting massive black hole in He 2–10 from adaptive optics integral field spectroscopy." Monthly Notices of the Royal Astronomical Society 494, no. 2 (April 13, 2020): 2004–11. http://dx.doi.org/10.1093/mnras/staa903.

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ABSTRACT Henize 2–10 is a blue dwarf galaxy with intense star formation and one the most intriguing question about it is whether or not it hosts an accreting massive black hole. We use H and K-band integral field spectra of the inner 130 pc × 130 pc of He 2–10 to investigate the emission and kinematics of the gas at unprecedented spatial resolution. The observations were done using the Gemini Near-Infrared Integral Field Spectrograph (NIFS) operating with the ALTAIR adaptive optics module and the resulting spatial resolutions are 6.5 and 8.6 pc in the K and H bands, respectively. Most of the line emission is due to excitation of the gas by photoionization and shocks produced by the star forming regions. In addition, our data provide evidence of emission of gas excited by an active galactic nucleus located at the position of the radio and X-ray sources, as revealed by the analysis of the emission-line ratios. The emission lines from the ionized gas in the field present two kinematic components: one narrow with a velocity field suggesting a disc rotation and a broad component due to winds from the star forming regions. The molecular gas shows only the narrow component. The stellar velocity dispersion map presents an enhancement of about 7 km s−1 at the position of the black hole, consistent with a mass of $1.5^{+1.3}_{-1.3}\times 10^6$ M⊙.

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Rodet, L., M. Bonnefoy, S. Durkan, H. Beust, A. M. Lagrange, J. E. Schlieder, M. Janson, et al. "Dynamical masses of M-dwarf binaries in young moving groups." Astronomy & Astrophysics 618 (October 2018): A23. http://dx.doi.org/10.1051/0004-6361/201832924.

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Context. Evolutionary models are widely used to infer the mass of stars, brown dwarfs, and giant planets. Their predictions are thought to be less reliable at young ages (< 200 Myr) and in the low-mass regime (< 1 M⊙). GJ 2060 AB and TWA 22 AB are two rare astrometric M-dwarf binaries, respectively members of the AB Doradus (AB Dor) and Beta Pictoris (β Pic) moving groups. As their dynamical mass can be measured to within a few years, they can be used to calibrate the evolutionary tracks and set new constraints on the age of young moving groups. Aims. We provide the first dynamical mass measurement of GJ 2060 and a refined measurement of the total mass of TWA 22. We also characterize the atmospheric properties of the individual components of GJ 2060 that can be used as inputs to the evolutionary models. Methods. We used NaCo and SPHERE observations at VLT and archival Keck/NIRC2 data to complement the astrometric monitoring of the binaries. We combined the astrometry with new HARPS radial velocities (RVs) and FEROS RVs of GJ 2060. We used a Markov chain Monte-Carlo (MCMC) module to estimate posteriors on the orbital parameters and dynamical masses of GJ 2060 AB and TWA 22 AB from the astrometry and RVs. Complementary data obtained with the integral field spectrograph VLT/SINFONI were gathered to extract the individual near-infrared (1.1–2.5 μm) medium-resolution (R ∼ 1500 − 2000) spectra of GJ 2060 A and B. We compared the spectra to those of known objects and to grids of BT-SETTL model spectra to infer the spectral type, bolometric luminosities, and temperatures of those objects. Results. We find a total mass of 0.18 ± 0.02 M⊙ for TWA 22, which is in good agreement with model predictions at the age of the β Pic moving group. We obtain a total mass of 1.09 ± 0.10 M⊙ for GJ 2060. We estimate a spectral type of M1 ± 0.5, L/L⊙ = −1.20 ± 0.05 dex, and Teff = 3700 ± 100 K for GJ 2060 A. The B component is a M3 ± 0.5 dwarf with L/L⊙ = −1.63 ± 0.05 dex and Teff = 3400 ± 100 K. The dynamical mass of GJ 2060 AB is inconsistent with the most recent models predictions (BCAH15, PARSEC) for an AB Dor age in the range 50–150 Myr. It is 10%–20% (1–2σ, depending on the assumed age) above the model’s predictions, corresponding to an underestimation of 0.10–0.20 M⊙. Coevality suggests a young age for the system (∼50 Myr) according to most evolutionary models. Conclusions. TWA 22 validates the predictions of recent evolutionary tracks at ∼20 Myr. On the other hand, we evidence a 1–2σ mismatch between the predicted and observed mass of GJ 2060 AB. This slight departure may indicate that one of the stars hosts a tight companion. Alternatively, this would confirm the model’s tendency to underestimate the mass of young low-mass stars.

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Journal articles on the topic 'Module spectrogram'

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