adsabs/AstroCLIMB huggingface dataset:
Paper: Classifying Cool Dwarfs: Comprehensive Spectral Typing of Field and Peculiar Dwarfs Using Machine Learning
Authors: Tianxing Zhou, Christopher A. Theissen, S. Jean Feeser, William M. J. Best, Adam J. Burgasser, Kelle L. Cruz, Lexu Zhao
Figure caption: RF model classification of spectral subtypes. All field and peculiar subtypes are included and grouped under their base type (i.e., L6γ goes under L6). This graph demonstrates the predicted label of the RF model compared to the adopted label defined in the data set. The dark gray and light gray shaded regions represent ±1 SpT and ±3 SpT, respectively. Lastly, gray markers represent sources with very low SNR (SNR ≤ 10).
Paper: Classifying Cool Dwarfs: Comprehensive Spectral Typing of Field and Peculiar Dwarfs Using Machine Learning
Authors: Tianxing Zhou, Christopher A. Theissen, S. Jean Feeser, William M. J. Best, Adam J. Burgasser, Kelle L. Cruz, Lexu Zhao
Figure caption: Distribution of SNR for our validation and testing sample. Spectral classes of M, L, and T are distinguished by blue, orange, and green bars, in bins of 20 SNR. The inset plot shows a more granular view of sources with SNR ≤50, in bins of 2 SNR. The majority of very low-SNR (< 10) sources are T dwarfs.
Paper: Classifying Cool Dwarfs: Comprehensive Spectral Typing of Field and Peculiar Dwarfs Using Machine Learning
Authors: Tianxing Zhou, Christopher A. Theissen, S. Jean Feeser, William M. J. Best, Adam J. Burgasser, Kelle L. Cruz, Lexu Zhao
Figure caption: Same as Figure 7, but for metal-poor objects.
Paper: Classifying Cool Dwarfs: Comprehensive Spectral Typing of Field and Peculiar Dwarfs Using Machine Learning
Authors: Tianxing Zhou, Christopher A. Theissen, S. Jean Feeser, William M. J. Best, Adam J. Burgasser, Kelle L. Cruz, Lexu Zhao
Figure caption: Same as Figure 10 for the KNN model.
Paper: Classifying Cool Dwarfs: Comprehensive Spectral Typing of Field and Peculiar Dwarfs Using Machine Learning
Authors: Tianxing Zhou, Christopher A. Theissen, S. Jean Feeser, William M. J. Best, Adam J. Burgasser, Kelle L. Cruz, Lexu Zhao
Figure caption: Same as Figure 10 for the SVM model.
Paper: Classifying Cool Dwarfs: Comprehensive Spectral Typing of Field and Peculiar Dwarfs Using Machine Learning
Authors: Tianxing Zhou, Christopher A. Theissen, S. Jean Feeser, William M. J. Best, Adam J. Burgasser, Kelle L. Cruz, Lexu Zhao
Figure caption: Same as Figure 7, but for low and intermediate surface gravity objects.
Paper: Surface Composition of Asteroid 269 Justitia: Insights from Spectral Mixture Modeling
Authors: Harish, P. O. Hayne, J. P. Emery, W. F. Bottke, Christopher S. Edwards, M. R. El-Maarry, H. AlMazmi
Figure caption: (Top) Best-fit spectral models of Triton tholin for asteroid Justitia. The model spectra correspond to Triton tholin, composed of 99.9% N2 and 0.1% CH4 (Table 1), with particle sizes of 1, 0.9, 0.85, and 0.8 μm. The observed spectrum is shown in green (solid and dotted lines). (Bottom) Residual plot for all the modeled Triton tholin spectra shown in the top figure.
Paper: Surface Composition of Asteroid 269 Justitia: Insights from Spectral Mixture Modeling
Authors: Harish, P. O. Hayne, J. P. Emery, W. F. Bottke, Christopher S. Edwards, M. R. El-Maarry, H. AlMazmi
Figure caption: A linear blend of extensively and weakly weathered silicates (i.e., nonlinear mixtures of pyroxene and Fe metal with particle sizes of 1 and 0.85 μm) with the carbonaceous material is shown by a dashed line. The observed spectrum of Justitia is shown in a solid black line, and the orange line shows the CM2 Murray meteorite spectrum from the ECOSTRESS Spectral library.
Paper: Surface Composition of Asteroid 269 Justitia: Insights from Spectral Mixture Modeling
Authors: Harish, P. O. Hayne, J. P. Emery, W. F. Bottke, Christopher S. Edwards, M. R. El-Maarry, H. AlMazmi
Figure caption: Best-fit nonlinear spectral mixing models of space-weathered silicates (99.6% Pyx and 0.4% Fe metal, and 95% Pyx and 5% Fe metal with particle sizes of 2, 1, and 0.85 μm) for Justitia in the VNIR spectral region. The observed spectrum is shown in green (solid and dotted lines).
Paper: Surface Composition of Asteroid 269 Justitia: Insights from Spectral Mixture Modeling
Authors: Harish, P. O. Hayne, J. P. Emery, W. F. Bottke, Christopher S. Edwards, M. R. El-Maarry, H. AlMazmi
Figure caption: A linear blend of extensively and weakly weathered silicates (from model 2) with the carbonaceous material is shown by dashed lines. The observed spectrum of Justitia is shown in green (solid and dotted lines), and the orange line shows the CM2 Murray meteorite spectrum from the PDS Geosciences Node Spectral library.
Paper: Surface Composition of Asteroid 269 Justitia: Insights from Spectral Mixture Modeling
Authors: Harish, P. O. Hayne, J. P. Emery, W. F. Bottke, Christopher S. Edwards, M. R. El-Maarry, H. AlMazmi
Figure caption: Spectral models of Triton tholin (dashed blue line) for asteroid Justitia in the TIR spectral region. The model spectrum corresponds to Triton tholin, composed of 99.9% N2 and 0.1% CH4 (Table 1), with particle sizes of 1, 0.9, 0.85, and 0.8 μm. The observed reflectance spectrum for Justitia is shown in a solid black line, which is inverted from the emissivity spectrum of Justitia from O. A. Humes et al. (2024) according to Kirchhoff’s law.
Paper: Surface Composition of Asteroid 269 Justitia: Insights from Spectral Mixture Modeling
Authors: Harish, P. O. Hayne, J. P. Emery, W. F. Bottke, Christopher S. Edwards, M. R. El-Maarry, H. AlMazmi
Figure caption: Nonlinear spectral mixing models of space-weathered silicates (99.6% Pyx and 0.4% Fe metal, and 95% Pyx and 5% Fe metal with particle sizes of 1 and 0.8 μm) for asteroid Justitia in the TIR spectral region. The observed TIR spectrum for Justitia is shown by the solid black line.
Paper: Surface Composition of Asteroid 269 Justitia: Insights from Spectral Mixture Modeling
Authors: Harish, P. O. Hayne, J. P. Emery, W. F. Bottke, Christopher S. Edwards, M. R. El-Maarry, H. AlMazmi
Figure caption: Space-weathered carbonaceous material (composed of 95% CM2 Murray material and 5% of Fe metal with mixture particle sizes of 10 μm-dotted magenta line and 1 μm-dotted blue line) and modeled CM2 Murray material spectra at 10 μm—dashed magenta line and at 1 μm—dashed blue line. The observed spectrum of Justitia is shown in a black solid line.
Paper: Classifying Cool Dwarfs: Comprehensive Spectral Typing of Field and Peculiar Dwarfs Using Machine Learning
Authors: Tianxing Zhou, Christopher A. Theissen, S. Jean Feeser, William M. J. Best, Adam J. Burgasser, Kelle L. Cruz, Lexu Zhao
Figure caption: Same as Figure 22, but for KNN.
Paper: The ODYSSEUS Survey. Characterizing Magnetospheric Geometries and Hotspot Structures in T Tauri Stars
Authors: Caeley V. Pittman, Catherine C. Espaillat, Connor E. Robinson, Thanawuth Thanathibodee, Sophia Lopez, Nuria Calvet, Zhaohuan Zhu, Frederick M. Walter, John Wendeborn, Carlo F. Manara, Justyn Campbell-White, Rik Claes, Min Fang, Antonio Frasca, Jorge F. Gameiro, Manuele Gangi, Jesus Hernández, Ágnes Kóspál, Karina Maucó, James Muzerolle, Michał Siwak, Łukasz Tychoniec, Laura Venuti
Figure caption: Empirical relationships between accretion, FUV line, and U-band continuum luminosities. In the orange and red subfigures, black circles indicate values taken from K. France et al. (2023), and black stars indicate fluxes measured in this work. In the purple subfigure (bottom right), all points are our measurements. Low-opacity colored lines show 100 bootstrapped linear fits, fitting 85% of points at a time. Thick colored lines show the median best-fit line, with the equation indicated in the legend. The Pearson correlation coefficient is given in colored text. Top panels: accretion luminosity vs. Si IV, C IV, and He II emission-line luminosities in units of L⊙. Middle panels: same as above, but in units of L⋆,f. The best-fit relations found from N. Calvet et al. (2004), which were fit to a sample of nine intermediate-mass TTSs, are plotted as gray dashed lines for comparison. Bottom-left panel: LSiIV vs. LCIV plotted with the line ratio model for the pre- and post-shock emission from D. R. Ardila et al. (2013). AA Tau, which was analyzed by D. R. Ardila et al. (2013), is also marked. Bottom-right panel: Lacc vs. excess U-band luminosity LU,excess plotted along with relations from the literature. The extent of the lines indicates the LU,excess range over which the relations were determined.
Paper: The ODYSSEUS Survey. Characterizing Magnetospheric Geometries and Hotspot Structures in T Tauri Stars
Authors: Caeley V. Pittman, Catherine C. Espaillat, Connor E. Robinson, Thanawuth Thanathibodee, Sophia Lopez, Nuria Calvet, Zhaohuan Zhu, Frederick M. Walter, John Wendeborn, Carlo F. Manara, Justyn Campbell-White, Rik Claes, Min Fang, Antonio Frasca, Jorge F. Gameiro, Manuele Gangi, Jesus Hernández, Ágnes Kóspál, Karina Maucó, James Muzerolle, Michał Siwak, Łukasz Tychoniec, Laura Venuti
Figure caption: Phase-folded accretion rates (black circles with error bars) divided into their constituent ﹩{ \mathcal F }﹩ components (colored bars) for multiepoch accretion shock modeling presented by C. E. Robinson & C. C. Espaillat (2019, RE19) and J. Wendeborn et al. (2024a, W24a). These results are not included in Figure 3, as the modeling was performed by the aforementioned authors and is simply phase-folded here. The year of observation is shown in parentheses. The assumed rotation period and total number of periods spanned are in the upper-right corners. The color bar is the same as Figure 3, with the four ﹩{ \mathcal F }﹩ values being 1010, 1011, 1012, and 1012.5 erg s−1 cm−2. Sine function fits to ﹩\dot{M}﹩ are shown as dotted red lines to guide the eye.
Paper: The ODYSSEUS Survey. Characterizing Magnetospheric Geometries and Hotspot Structures in T Tauri Stars
Authors: Caeley V. Pittman, Catherine C. Espaillat, Connor E. Robinson, Thanawuth Thanathibodee, Sophia Lopez, Nuria Calvet, Zhaohuan Zhu, Frederick M. Walter, John Wendeborn, Carlo F. Manara, Justyn Campbell-White, Rik Claes, Min Fang, Antonio Frasca, Jorge F. Gameiro, Manuele Gangi, Jesus Hernández, Ágnes Kóspál, Karina Maucó, James Muzerolle, Michał Siwak, Łukasz Tychoniec, Laura Venuti
Figure caption: Accretion rate results for each CTTS, ordered from low to high ﹩\dot{M}﹩ (note that the y-axis limits change between the subfigures). Each bar shows the contribution of accretion columns with energy flux densities ﹩{ \mathcal F }﹩ given by the color bar.
Paper: The ODYSSEUS Survey. Characterizing Magnetospheric Geometries and Hotspot Structures in T Tauri Stars
Authors: Caeley V. Pittman, Catherine C. Espaillat, Connor E. Robinson, Thanawuth Thanathibodee, Sophia Lopez, Nuria Calvet, Zhaohuan Zhu, Frederick M. Walter, John Wendeborn, Carlo F. Manara, Justyn Campbell-White, Rik Claes, Min Fang, Antonio Frasca, Jorge F. Gameiro, Manuele Gangi, Jesus Hernández, Ágnes Kóspál, Karina Maucó, James Muzerolle, Michał Siwak, Łukasz Tychoniec, Laura Venuti
Figure caption: Lacc and LHα are strongly correlated, with a Pearson correlation coefficient of 0.91. The color bar indicates ﹩{\mathrm{log}}\,_{10}﹩L⋆ and shows that both Lacc and LHα are correlated with L⋆. The low-opacity solid gray lines show 200 bootstrapped linear fits, and the thick black line shows the median relation from this work. The dashed gray line shows the empirical Lacc–LHα relation from J. M. Alcalá et al. (2017), and the dotted gray line shows the relation from L. Ingleby et al. (2013). The four outlier points below the fit lines are Sz 69, CHX18N, Sz 111, and SZ Cha from lower left to upper right.
Paper: The ODYSSEUS Survey. Characterizing Magnetospheric Geometries and Hotspot Structures in T Tauri Stars
Authors: Caeley V. Pittman, Catherine C. Espaillat, Connor E. Robinson, Thanawuth Thanathibodee, Sophia Lopez, Nuria Calvet, Zhaohuan Zhu, Frederick M. Walter, John Wendeborn, Carlo F. Manara, Justyn Campbell-White, Rik Claes, Min Fang, Antonio Frasca, Jorge F. Gameiro, Manuele Gangi, Jesus Hernández, Ágnes Kóspál, Karina Maucó, James Muzerolle, Michał Siwak, Łukasz Tychoniec, Laura Venuti
Figure caption: Accretion rate ﹩\dot{M}﹩ from the shock model vs stellar mass M⋆, with points colored by the median age of the host region. The two likely nondetections (SSTc2d J161243.8-381503 and Sz 130) are marked as triangles. The L. Hartmann et al. (2016) ﹩\dot{M}﹩–M⋆ relation found from U-band excesses is plotted (thick black line), along with its standard deviation of 0.75 dex (thin black line). ULLYSES targeted CTTSs with ﹩-9.7\lt \dot{M}\lt -7﹩ M⊙ yr−1 (dashed gray lines), and our accretion rates are consistent with that sample bias. Small gray points show the ﹩\dot{M}﹩–M⋆ pairs from C. F. Manara et al. (2023), which are consistent with our results.
Paper: The ODYSSEUS Survey. Characterizing Magnetospheric Geometries and Hotspot Structures in T Tauri Stars
Authors: Caeley V. Pittman, Catherine C. Espaillat, Connor E. Robinson, Thanawuth Thanathibodee, Sophia Lopez, Nuria Calvet, Zhaohuan Zhu, Frederick M. Walter, John Wendeborn, Carlo F. Manara, Justyn Campbell-White, Rik Claes, Min Fang, Antonio Frasca, Jorge F. Gameiro, Manuele Gangi, Jesus Hernández, Ágnes Kóspál, Karina Maucó, James Muzerolle, Michał Siwak, Łukasz Tychoniec, Laura Venuti
Figure caption: Comparison between accretion rates measured using the accretion shock and accretion flow models. Points are marked at the location of the weighted mean ﹩\dot{M}﹩flow, and the arrows show the range between the minimum and maximum accretion rates found across all epochs of observation. The color bar shows the stellar mass. Object names indicate the archival ULLYSES targets whose HST spectra were taken years before the Hα spectra. The gray lines show a one-to-one relationship and a 0.4 dex deviation, which is the typical variability-induced spread of ﹩\dot{M}﹩ for a given CTTS (C. F. Manara et al. 2023). The accretion rates are strongly correlated, with a Pearson correlation coefficient of 0.87.
Paper: The ODYSSEUS Survey. Characterizing Magnetospheric Geometries and Hotspot Structures in T Tauri Stars
Authors: Caeley V. Pittman, Catherine C. Espaillat, Connor E. Robinson, Thanawuth Thanathibodee, Sophia Lopez, Nuria Calvet, Zhaohuan Zhu, Frederick M. Walter, John Wendeborn, Carlo F. Manara, Justyn Campbell-White, Rik Claes, Min Fang, Antonio Frasca, Jorge F. Gameiro, Manuele Gangi, Jesus Hernández, Ágnes Kóspál, Karina Maucó, James Muzerolle, Michał Siwak, Łukasz Tychoniec, Laura Venuti
Figure caption: Accretion variability over different timescales. Left panel: gray points show pairwise variability of accretion rates from the flow model fits to multiple epochs of Hα observations. Black points show the median and 1σ standard deviation within the time bins indicated by the x-axis error bars. The median variability within ∼1 day is 0.06 dex with a standard deviation of 0.08 dex. Right panel: gray points show variability of accretion rates between the shock model fits to UV-optical spectra and flow model fits to multiple epochs of Hα observations. Black points are the same as in the left panel. The baseline variability within ∼1 day is 0.16 dex with a standard deviation of 0.19 dex.
Paper: The ODYSSEUS Survey. Characterizing Magnetospheric Geometries and Hotspot Structures in T Tauri Stars
Authors: Caeley V. Pittman, Catherine C. Espaillat, Connor E. Robinson, Thanawuth Thanathibodee, Sophia Lopez, Nuria Calvet, Zhaohuan Zhu, Frederick M. Walter, John Wendeborn, Carlo F. Manara, Justyn Campbell-White, Rik Claes, Min Fang, Antonio Frasca, Jorge F. Gameiro, Manuele Gangi, Jesus Hernández, Ágnes Kóspál, Karina Maucó, James Muzerolle, Michał Siwak, Łukasz Tychoniec, Laura Venuti
Figure caption: Comparison between accretion rates measured by fitting the shock models to the full 0.2–1.0 μm region (﹩\dot{M}﹩NUV) and to the 0.31–1.0  μm region accessible from the ground (﹩\dot{M}﹩opt). The color bar shows the logarithmic change of the mean energy flux density of the shock model. The gray lines show a one-to-one relationship and a 0.4 dex deviation, which is the typical variability-induced spread of ﹩\dot{M}﹩ for a given CTTS (C. F. Manara et al. 2023).
Paper: The ODYSSEUS Survey. Characterizing Magnetospheric Geometries and Hotspot Structures in T Tauri Stars
Authors: Caeley V. Pittman, Catherine C. Espaillat, Connor E. Robinson, Thanawuth Thanathibodee, Sophia Lopez, Nuria Calvet, Zhaohuan Zhu, Frederick M. Walter, John Wendeborn, Carlo F. Manara, Justyn Campbell-White, Rik Claes, Min Fang, Antonio Frasca, Jorge F. Gameiro, Manuele Gangi, Jesus Hernández, Ágnes Kóspál, Karina Maucó, James Muzerolle, Michał Siwak, Łukasz Tychoniec, Laura Venuti
Figure caption: Histogram of the total hotspot surface coverage given by the accretion shock model. Bars are broken down into logarithmically spaced stellar mass bins, as indicated in the legend.
Paper: TiDES: The 4MOST Time Domain Extragalactic Survey
Authors: C. Frohmaier, M. Vincenzi, M. Sullivan, S.F. Hönig, M. Smith, H. Addison, T. Collett, G. Dimitriadis, R. S. Ellis, P. Gandhi, O. Graur, I. Hook, L. Kelsey, Y.-L. Kim, C. Lidman, K. Maguire, L. Makrygianni, B. Martin, A. Möller, R. C. Nichol, M. Nicholl, P. Schady, B. D. Simmons, S. J. Smartt, E. Tempel, P. Wiseman
Figure caption: The distribution of the SNR15Å parameter for SNe Ia is shown and split across several different redshift bins. The shape of the distribution is dictated both by the supernova phase at which the spectrum was acquired and by the exposure time of the 4MOST observation. In the lowest redshift bin, supernovae can be observed at their peak phases in longer exposures, resulting in a higher SNR spectra; they can also be observed at later and fainter phases to produce the low SNR spectra. For the highest redshift bins, the SNe Ia are only observable at the peak brightness phase in the longest 4MOST exposures. Given the known uniformity of intrinsic brightness of SNe Ia at peak, this produces a narrower distribution, albeit at the lowest SNR. The dotted and dashed lines in each distribution represent the quartiles of the distribution.
Paper: TiDES: The 4MOST Time Domain Extragalactic Survey
Authors: C. Frohmaier, M. Vincenzi, M. Sullivan, S.F. Hönig, M. Smith, H. Addison, T. Collett, G. Dimitriadis, R. S. Ellis, P. Gandhi, O. Graur, I. Hook, L. Kelsey, Y.-L. Kim, C. Lidman, K. Maguire, L. Makrygianni, B. Martin, A. Möller, R. C. Nichol, M. Nicholl, P. Schady, B. D. Simmons, S. J. Smartt, E. Tempel, P. Wiseman
Figure caption: Example observer-frame light curves of SNe Ia from LSST are shown. Each row presents light curves over different redshift ranges, with the dotted line showing the depth of 4MOST after 1 hr integrated exposure (the maximum exposure for a single visit). The pink arrows denote the epoch/phase at which the object met the triggering requirements detailed in Section 3.5, and the black arrow indicates when 4MOST obtained the spectrum in our simulations. Note that even in our highest redshift bin, the uncertainties on the LSST observations are small and constraining due to the superior depth of LSST (5σ detection, r = 24.3 Ž. Ivezić & the LSST Science Collaboration 2018). A SALT2 light curve model (Section 5.1) was also fit to the observed light curves and we show the best fit result here.
Paper: TiDES: The 4MOST Time Domain Extragalactic Survey
Authors: C. Frohmaier, M. Vincenzi, M. Sullivan, S.F. Hönig, M. Smith, H. Addison, T. Collett, G. Dimitriadis, R. S. Ellis, P. Gandhi, O. Graur, I. Hook, L. Kelsey, Y.-L. Kim, C. Lidman, K. Maguire, L. Makrygianni, B. Martin, A. Möller, R. C. Nichol, M. Nicholl, P. Schady, B. D. Simmons, S. J. Smartt, E. Tempel, P. Wiseman
Figure caption: The fraction of spectra, split by SNR15Å ≥ 3 (red) and ≥5 (blue), as a function of the object’s redshift is shown for our SNe Ia sample. In the top panel, we show the efficiency for all SNe Ia 4MOST attempted to observe. In the bottom panel we show the fraction of all LSST SNe Ia that 4MOST successfully observed. While 4MOST-TiDES will provide a revolutionary sample of SNe Ia for cosmology, at best we will only be able to observe ∼3% of the SNe Ia that LSST discovers in any given redshift bin. Statistical-only uncertainties are shown following the same method as Figure 5
Paper: TiDES: The 4MOST Time Domain Extragalactic Survey
Authors: C. Frohmaier, M. Vincenzi, M. Sullivan, S.F. Hönig, M. Smith, H. Addison, T. Collett, G. Dimitriadis, R. S. Ellis, P. Gandhi, O. Graur, I. Hook, L. Kelsey, Y.-L. Kim, C. Lidman, K. Maguire, L. Makrygianni, B. Martin, A. Möller, R. C. Nichol, M. Nicholl, P. Schady, B. D. Simmons, S. J. Smartt, E. Tempel, P. Wiseman
Figure caption: ΩM − w contours for the simulated LSST+TiDES-Live and LSST+TiDES-Host combined (filled contours). For comparison, we present the cosmological contours from a DES-SN 5YR-like simulation (dotted–dashed contours). Only statistical uncertainties are included in both the LSST+TiDES and DES-like contours.
Paper: TiDES: The 4MOST Time Domain Extragalactic Survey
Authors: C. Frohmaier, M. Vincenzi, M. Sullivan, S.F. Hönig, M. Smith, H. Addison, T. Collett, G. Dimitriadis, R. S. Ellis, P. Gandhi, O. Graur, I. Hook, L. Kelsey, Y.-L. Kim, C. Lidman, K. Maguire, L. Makrygianni, B. Martin, A. Möller, R. C. Nichol, M. Nicholl, P. Schady, B. D. Simmons, S. J. Smartt, E. Tempel, P. Wiseman
Figure caption: As in Figure 12, but showing constraints in the wa/w0 plane. Additionally, we show the contours combining SN data with a DESI-BAO-Y1-like prior, both for DES-SN 5YR-like simulation (red dashed line) and LSST+TiDES simulation (red solid line).
Paper: TiDES: The 4MOST Time Domain Extragalactic Survey
Authors: C. Frohmaier, M. Vincenzi, M. Sullivan, S.F. Hönig, M. Smith, H. Addison, T. Collett, G. Dimitriadis, R. S. Ellis, P. Gandhi, O. Graur, I. Hook, L. Kelsey, Y.-L. Kim, C. Lidman, K. Maguire, L. Makrygianni, B. Martin, A. Möller, R. C. Nichol, M. Nicholl, P. Schady, B. D. Simmons, S. J. Smartt, E. Tempel, P. Wiseman
Figure caption: The TiDES Hubble diagram made up of the final SN Ia sample presented in Section 5. The upper panel shows the redshift distribution of the TiDES-Live, TiDES-Hosts, and low-z sample (D. O. Jones et al. 2019). The lower panel shows the residuals in the redshift bins from the cosmological fit (Hubble residuals).
Paper: TiDES: The 4MOST Time Domain Extragalactic Survey
Authors: C. Frohmaier, M. Vincenzi, M. Sullivan, S.F. Hönig, M. Smith, H. Addison, T. Collett, G. Dimitriadis, R. S. Ellis, P. Gandhi, O. Graur, I. Hook, L. Kelsey, Y.-L. Kim, C. Lidman, K. Maguire, L. Makrygianni, B. Martin, A. Möller, R. C. Nichol, M. Nicholl, P. Schady, B. D. Simmons, S. J. Smartt, E. Tempel, P. Wiseman
Figure caption: For the live-SNe Ia observed by 4MOST, we compare the phase at which we trigger follow-up requests to the phase the first spectrum was eventually taken in the rest-frame. In our simulations, the vast majority of our SNe Ia were identified and sent to 4MOST before maximum brightness. The spectra were taken most frequently around 1 week after the peak.
Paper: TiDES: The 4MOST Time Domain Extragalactic Survey
Authors: C. Frohmaier, M. Vincenzi, M. Sullivan, S.F. Hönig, M. Smith, H. Addison, T. Collett, G. Dimitriadis, R. S. Ellis, P. Gandhi, O. Graur, I. Hook, L. Kelsey, Y.-L. Kim, C. Lidman, K. Maguire, L. Makrygianni, B. Martin, A. Möller, R. C. Nichol, M. Nicholl, P. Schady, B. D. Simmons, S. J. Smartt, E. Tempel, P. Wiseman
Figure caption: The redshift distribution of the host galaxies targeted by 4MOST-TiDES. The solid lines show the sample receiving at least some fiber-hours of observation, while the dashed lines show the subsample reaching SNR1Å ≥ 3. Redshifts shown are the simulated galaxy redshifts.