O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Dataset I-Dataset O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O O O O O O B-Formula I-Formula I-Formula I-Formula I-Formula I-Formula O O O B-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula O B-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula O O O O O O O O O O O O O O B-Dataset I-Dataset O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Model O O O O O O O O O O O O O O O O O O O O O B-CelestialObject I-CelestialObject I-CelestialObject O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

to give a more reliable answer on the issue of zero point of the v sin i data. On the other hand, by checking other (even though sparse and, in general, less accurate) data sources on Praesepe ( Cummings et al. 2017 ; Quinn et al. 2012 ; Pace Pasquini 2004 ; Boesgaard et al. 2004 ; Rachford 1998 ; Malavolta et al. 2016 ; Mann et al. 2017 ) we find that most of the published values (~ 80%) are an average of 10–20% higher than our values. Therefore, we think that the current data lend support to a non-isotropic inclination angle distribution rather than to the isotropic one. Fig. 4 Observed cumulative distributions of sin i and the associated model distributions assuming isotropic and cone distributions (see Jackson et al. 2010 ) for the inclination angle. See Table 3 for the ( α , λ ) parameters used in the cone distributions. The error bars correspond to 1 σ limits derived from the random simulations of the theoretical CDFs. To avoid crowding, we show them only for the isotropic distributions because the errors for the cone distributions are very similar. For the other datasets we see a comfortable overall consistency between the expected distributions and the best fitting models. The optimal cone models (with large parameter scatter, as expected) are indistinguishable from the isotropic model for all field star samples, although there is a slight indication for the underestimation of the observational noise for Field (C): the observed CDF is shallower than that of the isotropic distribution. The opposite is likely to be true for the planetary host samples, especially for the KOI sample. We find that decreasing the noise on v sin i by a factor of two (relative to the values given by Winn et al. 2017 ), the fit improves substantially with σ cone = 0.028 ± 0.008 and cone parameters α = 80 ° ± 11 ° and λ = 27 ° ± 18 ° . These cone parameters may imply the presence of some oblique systems in the KOI sample. Instead of making any far-reaching conclusion of this sort from this test alone, we refer to Hirano et al. (2014) and Winn et al. (2017) for further discussion of the topic. However, we draw attention to the importance of proper noise estimation when modeling the distribution of the inclination angles from spectroscopic rotation velocities. 5 Conclusions By using recently determined stellar rotation periods, available spectroscopic rotation velocities, and evolutionary stellar radii based on IRFM-calibrated effective temperatures, we derived the distribution of the line-of-sight inclination angles from 113 main sequence F − K stars in the Praesepe open cluster. With the aid of statistical modeling, we found signatures of a broad rotational axis alignment. The cone model of Jackson et al. (2010) yielded an overall cone axis angle of 76 ° ± 14 ° and an opening angle of 47 ° ± 24 ° . Isotropic angle distribution is far less likely, except when the spectroscopic rotational velocities used in this work are systematically overestimated. Although we


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We thank Kaitlin Kratter, Paola Pinilla, Philip Pinto, and Peter Behroozi for useful discussions. R.L. acknowledges support from NASA headquarters under the NASA Earth and Space Science Fellowship Program grant NNX16AP53H. A.N.Y. acknowledges partial support from NASA Astrophysics Theory Grant NNX17AK59G and from the NSF through grant AST-1616929. Software: ATHENA (Stone et al. 2008 ; Bai Stone 2010c ), Matplotlib (Hunter 2007 ), Numpy Scipy (Jones et al. 2001 ), emcee v3.0rc2 (Foreman-Mackey et al. 2013 ), PLAN (Li 2019a ), Pyridoxine (Li 2019b ).


O O O O O O O O O O O O O O O O O B-Wavelength I-Wavelength O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O B-Wavelength I-Wavelength I-Wavelength O O O B-CelestialObject O O O O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Wavelength I-Wavelength O O O B-Wavelength I-Wavelength I-Wavelength I-Wavelength I-Wavelength I-Wavelength I-Wavelength I-Wavelength O O O O O O B-Wavelength I-Wavelength I-Wavelength I-Wavelength I-Wavelength I-Wavelength I-Wavelength I-Wavelength I-Wavelength I-Wavelength I-Wavelength O B-Citation I-Citation I-Citation I-Citation O O O O O O O B-Wavelength I-Wavelength O O O O O O O O O O O B-Wavelength I-Wavelength O O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O B-Wavelength I-Wavelength O O O O O O O O O O O O O B-CelestialObject O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Wavelength I-Wavelength O O O O O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O B-Wavelength I-Wavelength O O O O O O O O O O O O O O O O O B-Wavelength O O O O O O O O O O O O O O O B-CelestialObject O O O O O O O O O O O O O O O O O O O O B-Model O O O O O O O O O O B-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-CelestialObject O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O B-Wavelength I-Wavelength O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O B-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

a few megahertz, and this is the reason why some of the unidentified lines seen in the 80–116 GHz range were not properly assigned to CHD 2 CCH and CH 2 DCCD by Agúndez et al. (2019) . In fact, the identification of these two molecules drastically reduces the number of lines pending identification in the λ 3 mm line survey of L483 (see Table A.2 of Agúndez et al. 2019 ). The parameters derived for the lines assigned to the two doubly deuterated isotopologues of methyl acetylene are given in Table 1 and the observed line profiles are shown in Fig. 1 for CHD 2 CCH and in Fig. 2 for CH 2 DCCD. We note that the line at 91971.307 MHz, assigned to the 6 1,6 –5 1,5 transition ofCHD 2 CCH, was incorrectly assigned to the transition 5 3 –4 3 F = 6–5 of CH 3 CN by Agúndez et al. (2019) . The astronomical frequencies observed in the 72–116 GHz range (see Table 1 ) and the laboratory frequencies measured inthe 29–47 GHz range ( Thomas et al. 1955 ) were used to derive more accurate spectroscopic parameters for CHD 2 CCH and CH 2 DCCD (see Table 2 ). These constants are a considerable improvement on those reported by Thomas et al. (1955) and enable us to predict the rotational spectrum of the two molecules with an accuracy better than 0.1 MHz up to 200 GHz. Since the lines of doubly deuterated CH 3 CCH are relatively bright in L483, it would not be surprising to detect the triply deuterated species CHD 2 CCD, which should be three times more abundant than CD 3 CCH. However, the rotational spectrum has only been measured in the 28–43 GHz range with modest accuracy ( Thomas et al. 1955 ), which may translate to frequency errors of a few megahertz for lines lying above 72 GHz. It would therefore be interesting to measure the rotational spectrum of triply deuterated CH 3 CCH at millimeter wavelengths. Table 1 Observed line parameters of CHD 2 CCH and CH 2 DCCD in L483. Notes. Numbers in parentheses are 1 σ uncertainties in units of the last digits. Line parameters were derived from a Gaussian fit to the line profile. Observed frequencies are obtained adopting V LSR = 5.30 km s −1 ( Agúndez et al. 2019 ) and have an uncertainty of 20 kHz for all the lines. The full width at half maximum is Δ v . 3.2 Observed column densities We derived beam-averaged column densities for methyl acetylene and its singly and doubly deuterated isotopologues in L483 assuming local thermodynamic equilibrium. Values for CH 3 CCH and the two singly deuterated forms were already reported by Agúndez et al. (2019) . Here we have revised some of these values including new lines observed in the 72–80 GHz range and using new values for the electric dipole moments. The dipole moment of CH 3 CCH was experimentally measured by Burrell et al. (1980) to be 0.7839 D. For CH 3 CCD, the dipole moment was measured by Muenter Laurie (1966) . Here, we adopt the value measured by these latter authors corrected by using a more accurate value of the dipole moment of OCS, which is used as reference (see


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We are grateful to an anonymous referee for constructive comments, and Hailiang Chen and Thomas Tauris for helpful discussions. This work was supported by the Natural Science Foundation of China under grant nos. 11133001 and 11333004, the Strategic Priority Research Program of CAS under grant no. XDB09010200, and the Munich Institute for Astro- and Particle Physics (MIAPP) of the DFG cluster of excellence “Origin and Structure of the universe.”


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Acknowledgements DG, MB and IP acknowledge support from PRIN-INAF 2014 (PI M. Bondi). DG and IP acknowledge support of the Ministry of Foreign Affairs and International Cooperation, Directorate General for the Country Promotion (Bilateral Grant Agreement ZA14GR02 – Mapping the Universe on the Pathway to SKA).


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Acknowledgments We thank C.R. Christensen, R. Davé, S. Genel, Z. Hafen, A.V. Kravtsov, M. Kriek, A.L. Muratov, B. D. Oppenheimer, A. J. Richings, J. Rojas-Sandoval, R. S. Somerville and S. Veilleux for useful discussions. We greatly appreciate the referee’s thoughtful comments that helped us improve the paper in several places. DAA acknowledges support by a CIERA Postdoctoral Fellowship. CAFG was supported by NSF through grants AST-1412836 and AST-1517491, by NASA through grant NNX15AB22G and by STScI through grants HST-AR-14293.001-A and HST-GO-14268.022-A. DK was supported by NSF grant AST-1412153 and a Cottrell Scholar Award. Support for PFH was provided by an Alfred P. Sloan Research Fellowship, NASA ATP Grant NNX14AH35G, and NSF Collaborative Research Grant #1411920 and CAREER grant #1455342. EQ was supported by NASA ATP grant 12-ATP12-0183, a Simons Investigator award from the Simons Foundation, and the David and Lucile Packard Foundation. The simulations analysed in this paper were run using the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by NSF grant ACI-1053575 (allocations TG-AST120025, TG-AST130039 and TG-AST140023). This work greatly benefited from the hospitality of the Aspen Center for Physics, supported by NSF grant PHY-1066293.


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ACKNOWLEDGEMENTS PH acknowledges receipt of a Science and Technologies Facilities Council (STFC) studentship. HVA acknowledges the Spanish Plan Nacional de Astronomía y Astrofisća under grant AYA2016-76682-C3-2-P. The European VLBI Network is a joint facility of independent European, African, Asian, and North American radio astronomy institutes. Scientific results from data presented in this publication are derived from the following EVN project codes: EJ016A and EJ016B. e-MERLIN is a National Facility operated by the University of Manchester at Jodrell Bank Observatory on behalf of STFC. We also thank James Nightingale for a helpful discussion on model optimization and the anonymous referee for helpful comments.


O O O O O O O B-Collaboration I-Collaboration O O O O O O O O O O O O O O B-Model I-Model O O O O B-Model O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Formula I-Formula I-Formula I-Formula I-Formula I-Formula O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Formula I-Formula I-Formula I-Formula O B-Formula I-Formula I-Formula O O O O O O O O O O O O O O O B-Formula I-Formula I-Formula O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation O O O O O O O B-CelestialObject O O O O O O O O O B-Software I-Software I-Software I-Software O O O O B-CelestialObject O O O O O O

by the two profiles provided by the IceCube Collaboration, instead of an electromagnetic light curve. The first one (denoted in the following as “Gaussian flare’) is modeled by a Gaussian signal centered on MJD 57004 and with a standard deviation σ = 55.0 days. We considered a period ±5 σ wide, corresponding to 550 flaring days. The second one (referred to as “box flare”) assumes a box-shaped flare starting at MJD 56937.81 and ending at MJD 57096.21, corresponding to 158.40 flaring days. The time-dependent analysis first defines the values of selection cuts that, assuming a power-law neutrino spectrum for the signal, optimizes the Model Rejection Factor. Three different spectral indexes for the neutrino spectrum have been considered ( γ = 2.0, 2.1, and 2.2), and the cut parameters to be optimized are the maximum reconstructed neutrino zenith angle, θ , and the quality of reconstructed tracks, Λ. The resulting optimized set of cuts for the three considered spectral indexes are cos θ > −0.15 and Λ > −5.6. For comparison, the corresponding cuts for the time-integrated search reported in Section 3 are and Λ > −5.2. This means that the time-dependent analysis allows for more downward-going neutrino candidates and tracks with a lower reconstruction quality parameter; refer to Figure 2 of Albert et al. ( 2017a ). According to this set of cuts, the expected background during the box flare has been estimated as 0.04 (4) events within 05 (5°) from the source. This is a factor ∼4 larger than that determined for the time-integrated search. The background increases because a larger fraction of atmospheric muons is mis-reconstructed and because more low-energy atmospheric neutrinos are included. Thanks to the reduced observational time window, the method allows the presence of lower energy cosmic neutrinos and de facto corresponds to an analysis sensitive to a softer neutrino energy spectrum. After the optimization, the data have been unblinded. The results are compatible with the expectation from the atmospheric background, and no signal has been found during either of the considered flares. Within 2° from the source, 10 background events are expected during the analyzed period, while 13 events have been found in data. None of them lie within either of the two considered flaring periods. From these null results, 90% C.L. upper limits have been derived for the neutrino flux. For an E −2.0 ( E −2.1 ) [ E −2.2 ] spectrum they correspond to a normalization factor of GeV −1 cm −2 s −1 for the Gaussian-shaped period. The energy range containing the 5%–95% of the detectable flux is 2.0 (1.3) [1.0] TeV–3.2 (1.6) [1.0] PeV. For the box-shaped period, the flux normalization factors are a factor of 3.3 higher. 5. Conclusions The GCN circular (IceCube Collaboration 2017 ) on the EHE neutrino candidate event, IC170922A, promptly triggered a search for neutrino candidates in the ANTARES online data stream. The position of the IC170922A event at the location of the


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We are grateful to NASA and their SSERVI node, the Center for Lunar and Asteroid Surface Science at UCF. Special thanks go to our research collaborators: IGEP (Germany) and the Center for Microgravity Research at UCF. This material is based upon work supported by NASA under grant no. NNX09AB85G, issued through the Origins of Solar Systems Program, and grant no. NNA14AB05A, issued through the Solar System Exploration Research Virtual Institute, Space Florida, and by the National Science Foundation under grant no. AST-1413332.


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Acknowledgements We gratefully acknowledge the Programme National de Planétologie (telescope time attribution and financial support) of CNRS/INSU and the Swiss National Science Foundation for their support. We warmly thank the OHP staff for their support on the 1.93 m telescope. This work has been carried out in the frame of the National Centre for Competence in Research “PlanetS” supported by the Swiss National Science Foundation (SNSF). J.R. acknowledges support from CONICYT-Becas Chile (Grant No. 72140583). S.C.C.B. acknowledges support from Fundaçāo para a Ciência e a Tecnologia (FCT) through national funds and by FEDER through COMPETE2020 by these grants UID/FIS/04434/2013 POCI-01-0145-FEDER-007672 and PTDC/FIS-AST/1526/2014 POCI-01-0145-FEDER-016886; and also acknowledges support from FCT through Investigador FCT contracts IF/01312/2014/CP1215/CT0004. Finally, we thank the referee for their thorough review and highly appreciate the comments and suggestions, which contributed to improving this publication.


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MDC acknowledges the contribution of the FP7 SPACE project ASTRODEEP (Ref. No. 312725), supported by the European Commission. DAGH was funded by the Ramón y Cajal fellowship number RYC-2013-14182 and he acknowledges support provided by the Spanish Ministry of Economy and Competitiveness (MINECO) under grant AYA-2014-58082-P. FD acknowledges support from the Observatory of Rome.


O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation O O O O O O O O O O B-Model I-Model I-Model O O O O O O O O O O O B-Formula I-Formula I-Formula O O O O O O O O O O O O O O B-Survey I-Survey O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation I-Citation I-Citation B-Citation I-Citation I-Citation I-Citation I-Citation I-Citation B-Citation I-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Model I-Model B-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Model I-Model I-Model I-Model I-Model I-Model O O O B-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula B-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula O B-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula O O O O O O O O O O O O O O O O B-Model

photometric redshifts, we can constrain cosmology, in particular measure σ 8 at high redshifts. Since the galaxy power spectrum constrains σ 8 × b gal in the linear regime, we need to add at least another measurement. The possibilities include: galaxy overdensity–weak lensing correlations; constrain the bias itself using counts-in-cells distributions (Szapudi Pan 2004 ; Repp Szapudi 2019 ), and then fit σ 8 ; compute higher order statistics, going to three-point correlations instead of using two-point correlations only (e.g. Pan Szapudi 2005 ). In summary, we found that within the context of Planck concordance cosmology, a linear bias model adequately explains the clustering of galaxies at z ≃ 3–6.5. With 10 times more data in the near future and better redshift calibration, the H20 survey will produce high-redshift constraints on cosmological parameters and galaxy formation. APPENDIX A: AN ANALYSIS OF MAGNIFICATION BIAS The galaxy overdensity that is observed in magnitude-limited galaxy samples can be modulated by an effect known as magnification bias. Foreground matter density can enhance (or diminish) observed source counts via weak gravitational lensing, by pushing sources above (or below) the detection limit. Here, we provide an analysis of how magnification bias affects our results. First, we give a short summary of how the modelling described in Section 3 changes due to the inclusion of magnification bias. The formulae are based on the works of Hui, Gaztañaga Loverde ( 2007 ), Loverde et al. ( 2008 ), Ziour Hui ( 2008 ), and Joachimi Bridle ( 2010 ), refer to these for more theoretical details. Instead of measuring the galaxy overdensity directly, the overdensity we observe can be written as where O denotes observed, and μ denotes the magnification contribution. Accordingly, the empirical spherical autocorrelation power spectrum of this observed overdensity becomes , and the theoretical model for it is The g μ and μμ terms can be computed through the analogues of equation ( 6 ), and where we introduced the kernel function for lensing magnification Above, H 0 is the Hubble constant at present time, Ω m denotes the cosmological mass density parameter, c is the speed of light, is the slope of the galaxy number count function at the limiting magnitude m 0 , and finally is the lensing weight function. Again, we adopt the Limber approximation (Limber 1953 ) to speed up the computation, yielding and Examining the components of in equation ( A2 ), it is clear that scales with (see equation 9 ), scales with b gal , and does not depend on the galaxy bias. We evaluated the theoretical expressions via sphericosmo , and performed the linear galaxy bias fit on the dropout samples using our fiducial EAZY-new-sm Π ( z ) distribution. The results are b gal, g = 3.89 ± 0.29, b gal, r = 8.44 ± 0.55, and b gal, i = 11.93 ± 2.00 (statistical error only) for the three dropout galaxy samples. These values are indistinguishable from the original EAZY-new-sm


O O O O O O B-CelestialRegion I-CelestialRegion O O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Software O O O O O O O B-Citation I-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Software O O O O O O O O O O O O O O O O O O O

minor mergers are common in the local Universe (e.g. see Frenk et al. 1988 ; Carlberg Couchman 1989 ; Lacey Cole 1993 ; Gao et al. 2004 ; Fakhouri Ma 2008 ; Jogee et al. 2009 ; Kaviraj et al. 2009 ), therefore the findings of this paper are in apparent tension with the high frequency of the bar incidence in nearby galaxies. In addition, a galaxy might undergo multiple minor merger events during their entire lifetime (e.g. see Hopkins et al. 2009 ); thus, making the bar weakening event more inevitable. However, in reality, the situation is different as a galaxy might be accreting cold gas (e.g. Birnboim Dekel 2003 ; Kereš et al. 2005 ; Dekel Birnboim 2006 ; Ocvirk, Pichon Teyssier 2008 ; Cornuault et al. 2018 ) either during the mergers or at a later stage and this, in turn, could rejuvenate the bar (e.g. see Semelin Combes 2002 ; Bournaud et al. 2005 ; Combes 2008 ; Marino et al. 2011 ). Indeed, recent observational studies have pointed out such indication of bar rejuvenation event (e.g. Barway Saha 2020 ). Hence, the bar-weakening scenario during a minor merger event as shown in this paper is more appropriate for early-type disc galaxies, which are in general gas poor (e.g. Young Scoville 1991 ). The fraction of galaxies hosting bars decreases from the late-type gas-rich disc galaxies to early-type gas-poor disc galaxies (e.g. see Nair Abraham 2010 ). The bar fraction in disc galaxies tends to reach their minimum values for the lenticular/S0 galaxies (e.g. see Aguerri et al. 2009 ; Buta et al. 2010 ; Nair Abraham 2010 ; Barway, Wadadekar Kembhavi 2011 ). Thus, the recent minor merger events which are dry to a large extent can be a plausible explanation for the absence of strong bars in the early-type galaxies. 6.3 Other issues Here, we discuss a few points relevant for this work. First of all, the bulges present in the GalMer simulations are spherical and initially non-rotating. Previously, Saha Gerhard ( 2013 ) investigated the impact of a rotating classical bulge on the bar growth and the kinematics of the resulting boxy/peanut bulge. Their simulation of isolated galaxies showed that the bar strength decreases in cases with rotating bulges but at the end of 3 Gyr (see their Fig. 2 ), the bar strength with a rotating bulge (one with the maximum rotation) are within 10 per cent of the non-rotating case. In Fig. 5 , we compared the isolated runs and the one with the minor mergers. It appears that the minor merger events can reduce the bar strength nearly by a factor of two (at the end of 3 Gyr) from what it was in the isolated case. Given our understanding of the impact of rotating bulges on the bar strength, it might not overwhelm the impact of minor mergers. However, a detailed analysis and new simulations need to be run to understand and quantify this effect in the context of minor mergers. Secondly, the GalMer suite of simulations make use of the ‘hybrid particle’ scheme to represent the interstellar gas. This approach of gradually


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We would like to thank A. L. Varri and D. Heggie for helpful suggestions and M. Trenti for useful conversations about the topics addressed in this paper. We are also grateful to S. Degl’Innocenti and to P. G. Prada Moroni for discussions related to the properties of stellar populations in globular clusters. A.Z. thanks M. Gieles and V. Hénault-Brunet for many interesting discussions. This work was partially supported by the Italian MIUR. A.Z. acknowledges financial support from the Royal Society (Newton International Fellowship).


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We want to thank Dr. William Grundy for his useful comments that helped to improve this manuscript. V.L. and J.L. gratefully acknowledge support from the Spanish “Ministerio de Economía y Competitividad” (MINECO) projects AYA2012-39115-C03-03 and ESP2013-47816-C4-2-P. Based on observations made with the William Herschel Telescope operated on the island of La Palma by the Isaac Newton Group in the Spanish Observatorio del Roque de los Muchachos of the Instituto de Astrofísica de Canarias.


O O O O O B-Person I-Person B-Person I-Person O B-Person I-Person O O O O O O O B-Person I-Person O O O O O O O O O O O O O O O O O O O O O O O O B-Organization O B-Grant

ACKNOWLEDGEMENTS We are grateful to Shane Davis, Kent Yagi, and Hang Yu for useful conversations. We thank the referee, Andreas Reisenegger, for a careful report, and specifically for pointing out an error in our original calculation of the absorption coefficient. This research was supported by NASA grant NNX14AB40G.


O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Identifier I-Identifier I-Identifier O B-Identifier O O O O O O O O O O O O O O O O O O B-Dataset I-Dataset O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-CelestialObject O O O O O O O O O O O O O O O B-Dataset I-Dataset O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Formula I-Formula I-Formula O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Formula I-Formula I-Formula O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Formula I-Formula I-Formula O O O O O O O O O O O O B-CelestialObject I-CelestialObject O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Formula I-Formula I-Formula O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-CelestialObject I-CelestialObject I-CelestialObject O O O O B-Observatory I-Observatory I-Observatory I-Observatory O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O B-Wavelength I-Wavelength O O B-Citation I-Citation O O B-Observatory O O

components. We first performed a maximum likelihood analysis over the full time range considered here, that is 2008 Aug. 04 15:43:36.000 UTC to 2018 Sep 01 00:00:00.000 UTC (MET 1 239557417 to 557452805). In the initial fit, we modeled the ROI sources adopting the spectral shapes and parameters reported in the 3FGL catalog. We fit as free parameters the normalization and spectral index of the target source, and the normalization of all sources within 5° of the ROI center, in addition to the isotropic diffuse and Galactic components. Since our data set more than doubles the integration time with respect to the 3FGL catalog, we looked for potentially new sources, present in the ROI, with an iterative procedure. We produced a Test Statistic (TS) map. The TS is defined as 2log( L / L 0 ) where L is the likelihood of the model with a point source at a given position, and L 0 is the likelihood without the source. A value of TS = 25 corresponds to a significance of 4.2 σ , when accounting for two degrees of freedom ( Mattox et al. 1996 ). A TS map was produced by including a test source at each map pixel and evaluating its significance over the current model. We looked for significant (TS > 25) peaks in the TS map, with a minimum separation of 0.3°, and added a new point source to the model at the position of the most significant peak found, assuming a power-law spectrum. We then fit again the ROI, and produced a new TS map. This process was iterated until no more significant excesses were found 2 . We also performed a best-fit position localization for the target source and all new sources with TS > 25 found in the ROI. In order to investigate the temporal variability of PKS 0346−27, we computed several light curves with different time binning (see Sect. 3.1 ). In each light curve, we performed a full likelihood fit in each time bin. The number of free parameters in the fit depends on the statistics in each bin. We first attempted a fit leaving the normalisation and index of the target source and the normalization of all sources in the inner 3° of the ROI free to vary. If the fit did not converge or resulted in a non-detection (TS 25), we progressively restricted the number of free parameters in the fit in an iterative fashion. First we reduced the radius including sources with free normalization to 1°, then we left only the spectrum of the target source free to vary, and finally we fixed all parameters to their average values except for the target source’s normalization. We consider the target source to be detected if TS > 9 in the corresponding bin, and the signal-to-noise ratio (that is, flux over its error, or F /Δ F ) in that bin is larger than two. If this is not the case, we reported a 95% confidence upper limit. 2.2. Swift-XRT/UVOT PKS 0346−27 was observed with the Neil Gehrels Swift Observatory ( Gehrels et al. 2004 ) as a Target of Opportunity (ToO), following the detection of the first γ -ray flare ( Angioni 2018 ). The Swift data were


O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O O O O O B-Formula I-Formula I-Formula O O O O O O O O O O O O O B-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Formula I-Formula I-Formula I-Formula I-Formula I-Formula I-Formula O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Formula I-Formula I-Formula O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation O B-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Wavelength O O O O O O O O O O O O O O O O O O B-CelestialObject O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation O O O B-Formula I-Formula I-Formula I-Formula I-Formula O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

perpendicular to the reconnection plane, and 0 ε 1 the peakedness parameter of the current concentration in the magnetic islands. Subsequent numerical simulations have shown that, for a large range of S δ , the coalescence growth rate is much greater than the tearing growth rate (Pritchett Wu 1979 ) and that it depends critically on the value for ε (Bhattacharjee, Brunel Tajima 1983 ), linear tearing corresponding to ε = 0. The coalescence instability is characterized by two time-scales associated with its distinct phases (Kliem 1995 ). During the ideal phase, the current loops approach each other on a hydromagnetic time-scale, whereby the length-scale is given by the separation distance of paired current loops λ C , with δ ≲ λ C ≲ λ max . In general, , yet no magnetic energy is dissipated in the process. During the resistive phase, when the current loops merge, ‘anti-reconnection’ occurs in between the approaching islands. The reconnection rate is enhanced by the external driving forces of the converging current loops, such that in general . Moreover, for strongly peaked current concentrations (ε → 1), we have . For cm, the coalescence time-scale becomes comparable to the magnetospheric light crossing time, i.e. ms. Coalescence following tearing converts the bulk of the free magnetic energy in the current sheet, such that the island growth phase may act as mere prelude to the explosive energy release of merging current loops (Leboeuf, Tajima Dawson 1982 ). Its rapid development and ability to convert a significant fraction of magnetic energy argue in favour of coalescence, rather than tearing, as an explanation for the impulsive phase of flares (Tajima, Brunel Sakai 1982 ; Sakai Ohsawa 1987 ; Tajima et al. 1987 ; Kliem 1995 ; Schumacher Kliem 1997 ). The observed giant flare emission may therefore be a proxy of the non-linear, rather than the linear, tearing phase. Furthermore, for higher values of and σ m , a non-linear process known as ‘impulsive bursty reconnection’ may occur, whereby a cycle of slow tearing, rapid coalescence, current sheet thinning, and further secondary tearing (i.e. the plasmoid instability) at an increased rate repeats successively (Leboeuf et al. 1982 ; Priest 1985 ; Uzdensky, Loureiro Schekochihin 2010 ; Takamoto 2013 ). Consequently, energy is released during separate coalescence events in a fragmentary and quasi-periodic manner. This process is advanced to explain the periodic temporal fine structure of HXR emission and coherent drifting radio bursts associated with discrete (bidirectional) electron beams observed during the impulsive phase of solar flares (Aschwanden et al. 1995 ; Kliem, Karlicky Benz 2000 ; Karlicky 2004 ). QPOs of ν ∼ 10 2 Hz, which might be associated with separate energy injections, have also been detected during the initial phases of the magnetar giant flares: see Section 2.2 . These distinct energy surges may be interpreted as quasi-periodic peaks in coalescence rates, 13 resulting from


O O O O O O O O O O O O O O O O O O O B-Model O B-Model O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Wavelength O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Wavelength O O B-Model O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Wavelength O O O B-Model O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Model O O O O O O O O O O O O O O O O O O O O O O O O O O B-Model O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Tag I-Tag I-Tag O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation I-Citation I-Citation O O O O O B-Wavelength O O O O B-Survey I-Survey I-Survey B-Survey B-Citation I-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O B-Formula I-Formula I-Formula O B-Formula I-Formula I-Formula O O O O O O B-Wavelength I-Wavelength O O O O O O O O O O O O O O O O O O O O


O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Instrument O B-Wavelength O B-Wavelength O O B-Wavelength O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

respectively. For each of these frequency windows we compute the power spectral density. We selected windows of 16 h to compute each bin. In order to avoid segments containing magnetic experiments or events as the ones reported in Tables 2 and 1 , we apply a mask to the data. To do so we take as a figure of merit the amplitude spectral density in the range . Those segments where this figure of merit is exceed by five sigma are discarded from our analysis. Following this criterion, we exclude 9 segments out of 300. This analysis allows a generic description of the statistical behaviour of the fluctuations without any previous assumption on its stationarity. Fig. 4 shows the results for both frequency ranges. In agreement with our previous analysis, the amplitude of the fluctuations for the low-frequency bin is coherent and follows the same statistical distribution for all four magnetometers. Bins are statistically distributed with similar median values, namely These values are based on the 16th, 50th, and 84th percentiles of the histogram. Also, in this case we can derive a common mean value for the fluctuations in this frequency range of . On the other hand, the noise power in the higher frequency bins show a different amplitude spectral density for each magnetometer. The median values in this case are In the latter we observe that the distribution of the median values is narrower and not overlapping between them. Both behaviours are clearly distinguished in the histograms of Fig. 4 , which characterizes the variability of the magnetic field fluctuations on-board for the two frequency regimes that we have previously identified. Figure 4. Time evolution and statistical distribution of the X-component of the magnetic field fluctuations as measured on-board, for two different frequency regimes. Colours correspond to magnetometers: PX (blue), MX (red), PY (yellow), and MY (green). Time is indicated in DAL, while ASD stands for Amplitude Spectral Density. Top: Fluctuations in the frequency range . Bottom: Fluctuations in the frequency range . In the framework of future gravitational wave detectors in space, the variability in the spectra of magnetic field fluctuations is particularly relevant in the low-frequency regime. There are two main reasons for that: first, the mHz band is the main objective of a gravitational wave detector in space, since these observatories are designed to study the gravitational wave universe in this frequency band. Second, at the same time, the low-frequency fluctuations will be precisely the main contribution to the magnetic induced force noise in the free-falling test masses. According to Armano et al. ( 2016 ), magnetic induced forces could contribute to a maximum of 3 of the measured 12 at 0.1 mHz of the differential acceleration measured on LPF test masses. Although the precise determination of the magnetic noise contribution is still pending, the current estimate is expected to be of the order of other


B-Instrument O O O O O B-Instrument O O B-CelestialObject I-CelestialObject O O B-Citation I-Citation I-Citation I-Citation B-Proposal I-Proposal O B-Person O O O O O O O O B-Instrument O O O O O O O O O O O O O O O O O O O O O B-Instrument O O O O O B-Wavelength O O O B-Wavelength I-Wavelength O B-Wavelength I-Wavelength I-Wavelength O B-Wavelength I-Wavelength O B-Wavelength I-Wavelength I-Wavelength O O B-Instrument O O O O O O O B-Wavelength I-Wavelength I-Wavelength O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Instrument O O O O O O O O O B-Instrument O O O O O O B-CelestialObject I-CelestialObject O O O O O O O B-Instrument B-Wavelength O B-Instrument B-ObservationalTechniques O O O O O O O B-Wavelength O O O O O O O O O O O O O O O O O O O O O O B-Instrument O O O O O O O O O O O O O O O O O O O O O B-Wavelength O O O O O O O O O O O O B-Wavelength O O O O O O O O B-CelestialObject I-CelestialObject O O B-Instrument O O O B-Instrument O O O O O O O O O O O O O O O O O O O O O O O O B-ObservationalTechniques O O B-Instrument O O O O O O O O O O O O O O O O O O O O O O O O O O B-Instrument O O O O O O O O O O O O O O O O B-Wavelength I-Wavelength I-Wavelength O O O O O O O O B-ObservationalTechniques O O O O O O O O O O O O O O B-Instrument O B-Instrument O O O O O O O O O O B-Model I-Model I-Model O B-Citation I-Citation I-Citation I-Citation O O B-Formula I-Formula I-Formula I-Formula I-Formula B-Formula I-Formula I-Formula I-Formula O B-Formula I-Formula I-Formula I-Formula O O O O O O O O O O O O O O O O O O O O B-CelestialObject I-CelestialObject O O O O O O O O O O B-Instrument O B-ObservationalTechniques I-ObservationalTechniques O O O O O O O O O O O O O O B-CelestialObject I-CelestialObject O O B-Instrument O O O O O O O O O O O O O O O O O O O O O B-ObservationalTechniques O O O O O O O O O O O B-Instrument O O O O O O O O O O O O O O O O O O O O O O O O O B-Instrument B-ObservationalTechniques O O O O O O O O O O O O O O B-Wavelength O O B-Wavelength I-Wavelength O O O O O O O O O O O O O O O O O O O O B-Formula I-Formula I-Formula I-Formula I-Formula O O

SPHERE data We also re-reduced the SPHERE observations of HD 4113 published in Moutou et al. (2017) (Program 096.C-0249, PI: Moutou), taken on 2015-10-08. These observations were taken in IRDIFS-EXT mode following an observing strategy that is similar to our observationsas described above, and are summarized in Table 2 . The IRDIS data were taken in the K1-K2 mode ( λ K 1 = 2.1025 μ m, λ K 2 = 2.2255 μ m), while the IFS data cover a range of wavelengths from 0.97–1.66 μ m with an average spectral resolution of 34.5. These data include a maximum field rotation of 51 deg between coronagraphic frames. Our data reduction procedure was identical to that of the IRDIFS data described in the previous section. 4 Results 4.1 SPHERE 2016 high-contrast imaging data The source HD 4113C was detected at high significance in both IRDIS H2 and IRDIS SDI reductions, but was not recovered in the H3 filter, suggesting the presence of strong methane absorption. The measured relative photometry and astrometry are given in Table 3 , while the IRDIS PSF-subtracted images are shown in Fig. 2 . We adopt a lower limit on the contrast of 14.8 mag for the H3 filter, using the 3 σ contrast curve at the location of the H2 detection. Table 3 Measured astrometry and photometry of HD 4113C from the SPHERE observations. In the IFS data using PCA alone, no significant detection was found in any individual wavelength channel or in the mean taken over wavelength. After we applied SDI to the IFS data, we clearly detected the companion, with 14 of the wavelength channels showing an excess of flux above 1.5 σ significance at the location of the IRDIS detection. A weighted-mean image is shown in Fig. 2 . The data reduction for wavelengths below 1.02 μ m suffer from considerably more residual noise in the SDI+PCA reduction and are not included in the subsequent analysis. The measured contrast ratios from IFS and IRDIS were converted into apparent flux measurements through multiplication by a BT-NextGen spectral model ( Allard et al. 2012 ) with T eff = 5700 K, [Fe/H] = 0.3 dex and log g = 4.5, close to the values determined in Sect. 2 . The model spectrum was flux-scaled using the distance and radius of HD 4113A. The extracted spectrum is shown in Fig. 4 . 4.2 SPHERE archival high-contrast imaging data After processing the 2015 data, we were unable to unambiguously recover the companion HD 4113C in the IRDIS images. Close to the location of the 2016 detection, we find an excess of flux with 2–3 σ significance in the SDI reduction. However, because of the lower S/N, our reduction of the IRDIS data does not provide substantial constraints on the position or flux of the companion, and we have excluded it from the following analysis. In the IFS SDI reduction, we also find an excess of flux in wavelength channels corresponding to the J - and H -band peaks found in the2016 data, again with lower significance. We find six channels at which the companion is visible at S ∕ N > 4, and by


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Acknowledgments The research leading to these results has received funding from the European Union Seventh Framework Programme FP7-2011 under grant agreement no 284405. WASP-South is hosted by the South African Astronomical Observatory, and Super-WASP-North by the Isaac Newton Group and the Instituto de Astrofisica de Canarias; we are grateful for their ongoing support and assistance. Funding for WASP comes from consortium universities and from the UKs Science and Technology Facilities Council. This publication makes use of VOSA, developed under the Spanish Virtual Observatory project supported from the Spanish MICINN through grant AyA2008-02156.


O O O O O O O O O O O O O O O O O O O O B-Wavelength O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Software O B-Identifier I-Identifier B-Citation I-Citation I-Citation O B-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation O B-Citation I-Citation O B-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Wavelength O O O O O O O O O O O O O O O O O O O O O O O O O O B-Model O O B-Software O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Software I-Software O O O O B-Software O O O O O O O O O O B-Wavelength O O O O O O O O O O O O O O O O O O O B-Software O O O O O O O O O B-Software I-Software I-Software O B-Software I-Software O O O O O O O B-Software I-Software I-Software I-Software O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Software

in hadronic scenario, with spectrum and emissivity directly related to the spectrum of highest energy CRs. The simplified model of gamma-ray evolution, used in our paper, is not strongly influenced by the shape of the spectrum as it approximates it with E 2 . 2.1 Hydrodynamic modelling The dynamical evolution of an SNR was modelled by numerically solving the time-dependent HD equations of mass, momentum and energy conservation: where is the mass density, is the flow velocity, P is the thermal pressure, is the unit vector, E is the total energy density and is the adiabatic index. The total energy density is the sum of the thermal and kinetic components: We adopt the pluto code (Version 4.2; Mignone etal. 2007 , 2012 ) to solve the system of HD conservation laws by using a cell-centred finite-volume approach based on Godunov-type schemes. The code design enables efficient usage of massively parallel computers through the message passing interface standard (MPI) for interprocessor communications. We do not include radiative cooling and thermal conduction in our HD equations, describing only the free and Sedov expansion phases of the SNR evolution in a tenuous, collisionless medium. The transition time from Sedov to radiative phase for an SNR is described with the approximation (e.g. Blondin etal. 1998 ; Petruk 2005 ; Orlando etal. 2011 ) where E 51 E 0 /(10 51 erg) and E 0 is the initial total explosion energy, contained mostly in the form of kinetic energy. In our set of simulations, t tr 0.5Myr and therefore our modelled SNRs never reach the radiative phase. We will compute the radio emission from the SNR but with assumption that the radiation has no impact yet on its dynamical evolution. Throughout our modelling, we do not activate the MHD solver of pluto because it is in any case powerless in describing the generation of magnetic turbulence by CRs upstream of the shock and corresponding MFA. Such an amplified magnetic field is dominant compared to the field compressed only due to fluid compression, especially for young SNRs where non-linearity is very pronounced. NLDSA module, which runs parallel with pluto HD code, simultaneously performs calculations of MFA, synthesize the global radio emission in this amplified field and also accounts for its impact on hydrodynamics. We used the following set of pluto algorithms in our simulations: linear interpolation with default limiter, HLLC Riemann solver and RK2 algorithm for the time evolution. Additionally, we used MULTID shock flattening algorithm for the numerical dissipation near the strong shocks. Our three-dimensional (3D) computations were carried out in spherical coordinates ( r , , ), by using a static logarithmic grid, with mesh size increasing with the SNR radius. Detection and tracking of the SNR shock waves in the fluid, travelling in some direction x , is based on two standard numerical conditions, namely and , where p represents parameter, setting the shock strength. We modified pluto


O O B-CelestialObject O O O O O O O O O O O O O O O O O B-CelestialObject O O O O O O O O B-CelestialObject I-CelestialObject O O O B-Wavelength O O O O O O O O B-CelestialObject B-CelestialObject O B-CelestialObject O O O O O O O O O O O O O B-CelestialObject O O O B-CelestialObject O O O O O O O O O O O O O O O O O O O O O B-CelestialObject O O O O O O O B-CelestialObject O B-CelestialObject O O O O O O O O O O O O B-CelestialObject O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-CelestialObject O O O O O B-CelestialObject O B-CelestialObject O O O O O O O O O O O O O O O B-CelestialObject O O O O O O O B-Wavelength O O O O O O O O O O O O O B-CelestialObject O O B-Wavelength O O B-Telescope O B-Telescope O O O O O O O O O O B-Wavelength O O O O O B-CelestialObject O O O O O O O O O O O O O O O O O B-Wavelength O O O B-CelestialObject O O O O O O O O O O O O O O O O O B-CelestialObject O O O O O O O O O O O O B-Wavelength O O O O O O O O O O O O O O O O O O O O B-CelestialObject O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-TextGarbage O B-CelestialObject I-CelestialObject I-CelestialObject O O O O O O O O O B-CelestialObject O O O O O O B-Telescope O O O O O B-TextGarbage B-Citation I-Citation I-Citation I-Citation B-CelestialObject I-CelestialObject O B-CelestialObject O O O B-CelestialObject I-CelestialObject B-CelestialObject O O O O B-CelestialObject I-CelestialObject O O O O O O O O O O O O O O O O O O B-TextGarbage O O O O O B-Wavelength O O B-Telescope O O B-Telescope O O O O O O O O O O O O O O O O O O B-Survey I-Survey I-Survey I-Survey I-Survey I-Survey O O O O B-CelestialObject O O O O O O O O O O O O B-Survey I-Survey O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O B-Wavelength I-Wavelength O O B-CelestialObject O O O O O B-CelestialRegion I-CelestialRegion I-CelestialRegion O O O O O O O O O O O O O O O O O O O O O B-Wavelength O O O O O O O O O O O O

in the Bar regions are primarily on the near side (low fraction), lending support to the foreground location of the Bar. Finally, we compared the populations of SNRs in Local Group galaxies via their X-ray luminosity function. The XLF of SNRs in the SMC, M31, and M33 are relatively homogeneous over all the observed luminosity range, although that of the SMC is flatter. The LMC XLF is remarkable by its prominent bright end. The largest population of SNRs brighter than erg s is found in the LMC (13 SNRs vs. 8 and 7 in M31 and M33, respectively). This is possibly an effect of the lower metallicity in the LMC: massive stars have smaller mass loss rates (less heavy elements to drive stellar winds) and the interaction of SN ejecta with less massive CSM shells produce brighter remnants. The number of SNRs brighter than erg s in the LMC is comparable to that in M31 and M33, likely owing to its high recent SFR and high current type Ia SN rate. The LMC XLF flattens significantly because of incompleteness: many X-ray-faint SNRs have been missed so far, due to the incomplete coverage of the LMC with sensitive X-ray instruments (i.e. Chandra or XMM-Newton ). This work presents the state of the art on X-ray emission of SNRs in the LMC. However, it is clear that the current sample is incomplete, as evidenced by the flattening of the X-ray luminosity function of LMC SNRs (Sect. 7 ). In the last 15 years, new SNRs were confirmed or discovered in the LMC at an almost constant rate (one or few per year), principally using X-ray observations. There is no indication that this trend will stop in the near future, so that more observations of the LMC will increase the sample of SNRs. Nevertheless, the observing time of major observatories is limited and expensive. We conclude this work by offering several strategies to maximise the chance of finding “missing” SNRs: As shown in Sect. 8 , star formation is intensearound the SGS LMC 4, and the edges of the shellabound in SNRs. Many LMC SGS have not been (fully) surveyedby XMM-Newton , for instance (in the notationof Kim et al. 1999 )SGS 3 and 6 in the north, SGS 2 and5 in the west, and SGS 4 in the south. Targeting inparticular SGSs associated to star formation (e.g. withH ii region along the rims) warrants successfulSNR searches. The follow-up observations of X-ray-selected candidates (usually ROSAT sources) with XMM-Newton have been extremely successful. Such programmes should be continued until completion of the list of candidates. Even the ROSAT (targeted) survey of the LMC was not covering the LMC up to its outskirts. To find SNRs in these regions, the future eROSITA survey ( Merloni et al. 2012 ) will be most useful, covering the full sky in the 0.58 keV band. The LMC is located close to the South Ecliptic Pole and will be observed with a deeper exposure than the rest of the sky. Looking for new SNR candidates, especially evolved X-ray-only SNRs, will be of special interest. Even in existing data, some SNRs


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with other techniques for measuring half-mass radii are presented in Suess et al. ( 2019 ). Suess et al. ( 2019 ) also show that the half-mass radii recovered using our technique are not significantly biased by the galaxy’s half-light radius, stellar mass, or redshift. In Figure 1 , we show the strength of galaxy color gradients (i.e., r e,mass / r e,light ) as a function of stellar mass for two redshift slices in our new low-redshift sample. We divide the sample into star-forming and quiescent populations using the UVJ diagram and the quiescent definition from Whitaker et al. ( 2012 ). In Suess et al. ( 2019 ), we found that there was a significant trend between color gradient strength and stellar mass for galaxies at 1.0 ≤ z ≤ 2.5. Here, we find that this trend continues to lower redshifts. The only exception is in the lowest-redshift quiescent bin, where our sample is quite small. In the lower panels of Figure 1 , we also show how the best-fit relation between r e,mass / r e,light and stellar mass varies as a function of redshift for our full 0 ≲ z ≤ 2.5 sample. Figure 1. Top: color gradient strength as a function of stellar mass for two redshift intervals. Small light blue points and light red squares show individual star-forming and quiescent galaxies; large blue points and red squares show a running median. The blue and red lines show best-fit linear relations to each trend; lines are outlined in black if the slope of the relation is inconsistent with zero, and outlined in gray if the slope is consistent with zero. Dashed vertical blue and red lines show the mass completeness of the star-forming and quiescent samples. Bottom: best-fit relation between color gradient strength and stellar mass for star-forming (left) and quiescent (right) galaxies as a function of redshift. Dashed lines represent fits whose slopes are consistent with zero. We see clear redshift evolution in the best-fit color gradient-mass relations for both quiescent and star-forming galaxies. In Figure 2 , we show the median strength of color gradients for all galaxies with , the completeness limit of our full sample. In Suess et al. ( 2019 ), we showed that the strength of galaxy color gradients decreases sharply between z ∼ 2.5 and z ∼ 1. Here we find that this evolution may flatten below z ∼ 1; r e,mass / r e,light for both quiescent and star-forming galaxies remains roughly constant at a value of ∼0.7. Figure 2. Median half-mass to half-light radius ratio for star-forming and quiescent galaxies (blue circles and red squares) as a function of redshift. r mass / r light traces the strength of radial color gradients; values less than one indicate negative color gradients, where the center of the galaxy is redder than the outskirts. Only galaxies with , where our sample is complete, are included. Error bars show the central 68% of 500 bootstrap samples. The strong color gradient evolution previously observed at z ≳ 1 appears to flatten at z ≲ 1. 3. The Growth of Quiescent


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We are grateful to the referee whose comments led to an improved version of the paper. We acknowledge useful discussions with Tobias Heinemann, Oliver Gressel, and Leonardo Krapp. We are grateful to Thomas Berlok for help with the simulations and for useful comments on the manuscript. The research leading to these results has received funding from the European Research Council under the European Unions Seventh Framework Programme (FP/2007-2013) under ERC grant agreement 306614.


O O O O O O B-Grant I-Grant I-Grant I-Grant I-Grant I-Grant I-Grant I-Grant I-Grant I-Grant I-Grant O B-Grant O O O B-Organization I-Organization I-Organization B-Grant B-Grant O O B-Organization I-Organization I-Organization I-Organization I-Organization B-Grant O O O O O O O O O O O O O O O O O O B-Organization I-Organization O O O O O O O O B-Organization I-Organization I-Organization B-Person O O O O O B-Organization I-Organization O B-Grant I-Grant O B-Grant B-Person O O O O B-Grant I-Grant I-Grant I-Grant I-Grant I-Grant I-Grant O O B-Organization I-Organization I-Organization B-Person O O O O O B-Organization B-Organization B-Grant I-Grant O B-Organization B-Location B-Person O O O O O O B-Organization I-Organization I-Organization I-Organization I-Organization B-Organization O O B-Fellowship I-Fellowship I-Fellowship I-Fellowship B-Fellowship O O O O O O O B-Observatory O B-Identifier B-Observatory O O O O O B-Observatory O O O O B-Organization B-Location O B-Organization B-Location O O O B-Organization B-Location B-Organization O B-Organization B-Location O B-Organization B-Location I-Location I-Location O O O O B-Location I-Location I-Location O B-Observatory I-Observatory I-Observatory O O O O B-Observatory B-Organization O B-Observatory O O O O O O O O O O B-Telescope I-Telescope I-Telescope I-Telescope B-Telescope O O O O O O O B-Organization I-Organization I-Organization B-Organization B-Observatory B-Telescope B-Telescope B-Telescope O B-Telescope I-Telescope I-Telescope O B-Observatory I-Observatory I-Observatory O O B-Observatory I-Observatory I-Observatory B-Observatory O B-Telescope O O O O O B-Observatory O O O O O O B-Organization I-Organization I-Organization O O B-Organization I-Organization I-Organization O O O O O O B-Software I-Software I-Software I-Software I-Software O B-Location I-Location O O O O O O O O O B-Telescope I-Telescope I-Telescope O O B-Organization O B-Location O O O O O O B-Software I-Software I-Software I-Software I-Software I-Software B-Citation I-Citation I-Citation I-Citation O O O O O O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization O O O O O B-Software B-Citation I-Citation O B-Software B-Citation I-Citation I-Citation I-Citation O B-Software B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation I-Citation B-TextGarbage I-TextGarbage B-Software B-Citation I-Citation I-Citation I-Citation O B-Citation O B-Citation O B-Software B-Citation I-Citation I-Citation I-Citation O B-Software I-Software B-Citation I-Citation I-Citation I-Citation O B-Software I-Software B-Citation I-Citation O

This work is supported by the ERC Synergy Grant “BlackHoleCam: Imaging the Event Horizon of Black Holes,” grant 610058. We thank the National Science Foundation (AST-1126433, AST-1716536) and the Gordon and Betty Moore Foundation (GBMF-5278) for financial support of this work. This work was supported in part by the black hole initiative at Harvard University, which is supported by a grant from the John Templeton Foundation. M.K. acknowledges the financial support of JSPS KAKENHI grant Nos. JP18K03656 and JP18H03721. R.-S.L. is supported by the National Youth Thousand Talents Program of China and the Max-Planck Partner Group. L.L. acknowledges the financial support of DGAPA, UNAM (project IN112417), and CONACyT, México. I.C. acknowledges the financial support of the National Research Foundation of Korea (NRF) via a Global PhD Fellowship Grant (NRF-2015H1A2A1033752). This paper makes use of the following ALMA data: ADS/JAO.ALMA2016.1.00413.V. ALMA is a partnership of the ESO (representing its member states), NSF (USA), and NINS (Japan), together with the NRC (Canada), MOST and ASIAA (Taiwan), and KASI (Republic of Korea), in cooperation with the Republic of Chile. The Joint ALMA Observatory is operated by the ESO, AUI/NRAO, and NAOJ. This research has made use of data obtained with the Global Millimeter VLBI Array (GMVA), which consists of telescopes operated by the Max-Planck-Institut für Radioastronomie (MPIfR), IRAM, Onsala, Metsahovi, Yebes, the Korean VLBI Network, the Green Bank Observatory, and the Long Baseline Observatory (LBO). The VLBA is an instrument of the LBO, which is a facility of the National Science Foundation operated by Associated Universities, Inc. The data were correlated at the DiFX correlator of the MPIfR in Bonn, Germany. This work is partly based on observations with the 100 m telescope of the MPIfR at Effelsberg. This work made use of the Swinburne University of Technology software correlator (Deller et al. 2011 ), developed as part of the Australian Major National Research Facilities Programme and operated under license. Software: AIPS (Greisen 2003 ), DiFX (Deller et al. 2011 ), HOPS (Whitney et al. 2004 ; L. Blackburn et al. 2019, in preparation), KORAL (Sadowski et al. 2013 , 2014 , 2017 ), PolConvert (Martí-Vidal et al. 2016 ), eht-imaging library (Chael et al. 2016 ), Stochastic Optics (Johnson 2016 ).


O O O O O O O O B-Person I-Person O B-Person I-Person O O O O O O O O O O O O O O O O O B-Person O O O B-Organization B-Person O O O O O O O B-Organization B-Grant I-Grant I-Grant I-Grant I-Grant I-Grant O O O B-Organization I-Organization I-Organization I-Organization B-Organization O O O O O B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization B-Organization O B-Location I-Location O O O B-Survey I-Survey I-Survey I-Survey I-Survey O O O O O B-Organization I-Organization I-Organization I-Organization O B-Location B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization O O O O B-Survey O O O O O O B-ComputingFacility I-ComputingFacility I-ComputingFacility I-ComputingFacility O O B-Organization I-Organization I-Organization O B-Survey O O O B-URL O B-Survey O O O O B-Collaboration I-Collaboration I-Collaboration O O O O O O B-Collaboration I-Collaboration O O B-Collaboration I-Collaboration I-Collaboration O B-Organization I-Organization I-Organization I-Organization B-Organization I-Organization I-Organization O B-Collaboration I-Collaboration I-Collaboration O B-Collaboration I-Collaboration I-Collaboration B-Organization I-Organization I-Organization I-Organization B-Organization I-Organization I-Organization I-Organization I-Organization O B-Organization I-Organization I-Organization B-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization I-Organization B-Organization B-Organization I-Organization B-Organization I-Organization I-Organization I-Organization B-Organization I-Organization I-Organization I-Organization I-Organization B-Organization B-Organization I-Organization I-Organization B-Organization B-Location B-Organization I-Organization I-Organization B-Organization B-Location B-Organization I-Organization I-Organization I-Organization B-Organization B-Observatory I-Observatory I-Observatory I-Observatory I-Observatory B-Organization I-Organization I-Organization I-Organization B-Organization I-Organization I-Organization B-Organization I-Organization I-Organization I-Organization B-Observatory I-Observatory B-Organization I-Organization I-Organization I-Organization B-Organization I-Organization I-Organization B-Observatory I-Observatory I-Observatory B-Collaboration I-Collaboration I-Collaboration I-Collaboration B-Organization I-Organization I-Organization I-Organization I-Organization B-Organization I-Organization I-Organization B-Organization I-Organization I-Organization I-Organization B-Organization I-Organization I-Organization B-Organization I-Organization I-Organization B-Organization I-Organization I-Organization B-Organization I-Organization I-Organization B-Organization I-Organization I-Organization B-Organization I-Organization I-Organization B-Organization I-Organization O B-Organization I-Organization

ACKNOWLEDGEMENTS The authors would like to gratefully acknowledge Eric Emsellem and Cheng Li for useful discussions on the subject, and the anonymous referee for useful comments that improved this paper. AFM acknowledges support from STFC. MAF is grateful for financial support from the CONICYT Astronomy Program CAS-CONICYT project No. CAS17002, sponsored by the Chinese Academy of Sciences (CAS), through a grant to the CAS South America Center for Astronomy (CASSACA) in Santiago, Chile. Funding for the Sloan Digital Sky Survey IV has been provided by the Alfred P. Sloan Foundation, the U.S. Department of Energy Office of Science, and the Participating Institutions. SDSS-IV acknowledges support and resources from the Center for High-Performance Computing at the University of Utah. The SDSS web site is www.sdss.org . SDSS-IV is managed by the Astrophysical Research Consortium for the Participating Institutions of the SDSS Collaboration including the Brazilian Participation Group, the Carnegie Institution for Science, Carnegie Mellon University, the Chilean Participation Group, the French Participation Group, Harvard-Smithsonian Center for Astrophysics, Instituto de Astrofísica de Canarias, The Johns Hopkins University, Kavli Institute for the Physics and Mathematics of the Universe (IPMU)/University of Tokyo, Lawrence Berkeley National Laboratory, Leibniz Institut für Astrophysik Potsdam (AIP), Max-Planck-Institut für Astronomie (MPIA Heidelberg), Max-Planck-Institut für Astrophysik (MPA Garching), Max-Planck-Institut für Extraterrestrische Physik (MPE), National Astronomical Observatories of China, New Mexico State University, New York University, University of Notre Dame, Observatário Nacional/MCTI, The Ohio State University, Pennsylvania State University, Shanghai Astronomical Observatory, United Kingdom Participation Group, Universidad Nacional Autónoma de México, University of Arizona, University of Colorado Boulder, University of Oxford, University of Portsmouth, University of Utah, University of Virginia, University of Washington, University of Wisconsin, Vanderbilt University, and Yale University.


B-Observatory O O O O O O O O O O O O O O O O O B-CelestialObject I-CelestialObject O O B-Observatory O B-Observatory O O O O O B-Observatory O O O O O O O O O O O O O O O O O O O O O O O O O B-Observatory O O B-CelestialObject I-CelestialObject O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Observatory O O B-CelestialObject I-CelestialObject O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Observatory O B-Observatory O O B-CelestialObject I-CelestialObject O O O B-Identifier I-Identifier O O B-Software I-Software I-Software B-Citation I-Citation I-Citation O B-Citation I-Citation O B-Citation O O O O B-Model I-Model I-Model I-Model B-Model O O O O O O O B-Software O O B-URL O O B-Citation I-Citation I-Citation I-Citation I-Citation I-Citation O O O B-Software O O O B-Model I-Model I-Model O O O B-Citation I-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O B-Software I-Software O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Observatory O B-Observatory O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation O O B-Observatory O B-Observatory O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Dataset I-Dataset I-Dataset B-Citation I-Citation I-Citation I-Citation

(NFO, including corrections). The resultant light curves are displayed in Figure 2 . Figure 2. Photometric observations of V506 Oph from the URSA and NFO telescopes, along with the residuals. NFO is displaced vertically for clarity. Enlargements of the minima are shown at the bottom. Our adopted model discussed in Section 5 is overplotted. Table 5 URSA Observations of V506 Oph (This table is available in its entirety in machine-readable form.) Only a portion of this table is shown here to demonstrate its form and content. A machine-readable version of the full table is available. Table 6 NFO Observations of V506 Oph (This table is available in its entirety in machine-readable form.) Only a portion of this table is shown here to demonstrate its form and content. A machine-readable version of the full table is available. 5. Light-curve Analysis The URSA and NFO photometry of V506 Oph was analyzed using version 2013 of the Wilson–Devinney LC program (Wilson Devinney 1971 ; Wilson 1979 , 1990 ) called within a Markov chain Monte Carlo (MCMC) scheme. Our method of solution used the emcee 5 5 http://dfm.io/emcee/current code of Foreman-Mackey et al. ( 2013 ), which is a Python implementation of the affine-invariant MCMC ensemble sampler proposed by Goodman Weare ( 2010 ). We typically used 100 walkers and uniform priors within suitable limits for all fitted quantities. As the system is well detached, we used the LC program in mode 2, along with the option of simple reflection and synchronous rotation of both components (see Section 6 ). The ephemeris and mass ratio of the binary were held fixed at the values in Table 4 , and the primary temperature was set to 6840 K (Section 2 ). The main parameters of the fit were the inclination angle, i ; the temperature of the secondary, T eff,2 ; the surface potentials, Φ 1 and Φ 2 ; a phase shift, Δ φ ; and the out-of-eclipse magnitude difference at phase 0.25, m 0 . We assumed initial measurement errors for the URSA and NFO observations of 0.02 mag, and a scale factor, f (with a log-uniform prior), was included as an additional adjustable parameter, which we solved for self-consistently and simultaneously with the other parameters (see Gregory 2005 ). Convergence of the chains was checked visually, with the additional requirement of a Gelman–Rubin statistic of 1.05 or smaller for each parameter (Gelman Rubin 1992 ). The URSA and NFO data sets were initially analyzed separately. Tests indicated the best results were obtained by solving also for the linear limb-darkening coefficients of each star ( x 1 , x 2 ), as well as the gravity-darkening exponents ( β 1 , β 2 ). More complicated limb-darkening laws did not provide any improvement. The albedos for both components were held fixed at a value of 0.5, commonly adopted for convective stars, as experiments with other values gave poorer results. No significant third light was detected, consistent with the fact that the Gaia /DR2 catalog (Gaia Collaboration et al.


O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Telescope O O O O O O O O O O O O O O O O O B-Wavelength I-Wavelength O O O O O O B-Telescope O O O O O O O O B-CelestialObject I-CelestialObject O B-Telescope O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O O O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O B-Citation I-Citation O B-Citation I-Citation O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B-Citation I-Citation I-Citation I-Citation I-Citation I-Citation O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

of A for to match is then (taking ). This factor could include contributions from the turnaround time at each end of the corona or from other physical processes. magnetohydrodynamic calculations (Edwin Roberts 1983 ) show that magnetic fields affect the frequency of various modes of oscillation. Detailed calculations of expected values of A are beyond the scope of this work. Remillard McClintock ( 2006 ; fig. 10) show that QPO frequency correlates with disc flux in hard/steep power-law-intermediate states. The observations presented here have a weaker disc component, which is not unambiguously detected but may be clearer at soft energies, so this could be investigated, for example, with NICER . While the QPO is most dominant at high energies, it is also strongly detected in the 3–10 keV band, which is also covered by NICER . Owing to the more frequent coverage of MAXI J1820+070 by NICER , a more detailed analysis of the QPO progression can be made with these data. 4.3 Coronal temperature The corona also shows changes in its mean properties: the temperature anticorrelates with flux. This has been observed in other individual XRBs (Joinet, Kalemci Senziani 2008 ; Motta, Belloni Homan 2009 ) and AGN (Lubiński et al. 2010 ). This could happen because pair production from photon collisions is regulating the temperature (Svensson 1984 ; Zdziarski 1985 ; Fabian et al. 2015 ): at higher fluxes, there are more photons, which allows sufficient pairs to be produced at lower temperatures. The coronal temperatures observed here are allowed by the pair thermostat, being below the pair-production limit that is observed to limit accreting sources as a population (Fabian et al. 2015 ). The lower temperatures than the pair limit can be explained by a deviation from a pure thermal distribution, which is expected as the cooling time-scale is less than the collision time-scale (Fabian et al. 2017 ). The presence of a non-thermal tail to the particle distribution reduces the critical temperature (Fabian et al. 2017 ). These considerations do not take substructure in the corona into account; this remains a potential caveat when estimating the coronal compactness from its total luminosity and size. We consider this correlation in more detail by comparing the corona’s radiative compactness with its electron temperature. We take electron temperatures from our fits and calculate the coronal compactness following the methodology of Fabian et al. ( 2015 ). We take the luminosity from the total direct flux of our best-fittng models at a distance of 3.5 kpc. Calculation of the compactness also requires a radius; the coronal prescription used here (including contributions from two points) does not readily convert to an equivalent spherical size so we try several prescriptions. First, we consider a fiducial size for all observations. We also consider the effect of a shrinking radius, as could be implied by the reduction in illumination of the outer disc with time. We reduce


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This work was supported in Italy by ASI contract I/004/11/1. Facility: Swift


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the methodology of Rowan-Robinson et al. (2005 , 2008) and as in Wang Rowan-Robinson (2009) , with a combination of two cirrus templates, three starburst templates and an AGN dust torus template. The total IR luminosity L IR (integrated between 8 and 1000 μ m) is estimated based on the fitted templates. The methodology of Rowan-Robinson et al. (2008) is followed to calculate stellar masses and SFR. Briefly, the rest-frame 3.6 μ m luminosity is estimated and converted to stellar mass using the mass-to-light ratio derived from stellar synthesis models. To estimate SFR, the conversion recipes of Rowan-Robinson et al. (1997) and Rowan-Robinson (2001) are used where η is the fraction of UV light absorbed by dust, taken as 2/3. The SFRs are calculated for a Salpeter (1955) IMF between 0.1 and 100 M ⊙ . To convert to Kroupa (2001) IMF, we divide the values by 1.5. We can also estimate SFR based on the total IR luminosity L IR following the widely used recipe of Kennicutt (1998) after converting to Kroupa IMF, In principle, the formula of Eq. ( 2 ) is only suitable for dusty starburst galaxies in which all of the radiation from young stars is assumed to be absorbed by dust and subsequently re-emitted in the IR. In practice, Eq. ( 2 ) has been found to also apply to normal galaxies (e.g. Rosa-González et al. 2002 ; Charlot et al. 2002 ). The explanation is that there are two competing effects, which are overestimation in SFR caused by assuming all of the IR luminosity arises from recent star formation (as opposed to old stellar populations) and underestimation in SFR caused by neglecting the possibility that some of the young stellar radiation is not absorbed by dust. It is a coincidence that these two effects cancel out (e.g. Inoue 2002 ; Hirashita et al. 2003 ). For sources in the RIFSCz which have been cross-matched to SDSS DR 10, we also have SFR estimates based on the H α line luminosity, SFR Hα , corrected for dust attenuation and aperture effects provided in the MPA-JPU database ( Brinchmann et al. 2004 ). 2.2. The LOFAR survey Exploiting the unique capabilities of LOFAR ( van Haarlem et al. 2013 ), LoTSS is an ongoing sensitive, high-resolution, low-frequency (120−168 MHz) radio survey of the northern sky and is described in Shimwell et al. (2017) . LoTSS provides the astrometric precision needed for accurate and robust identification of optical and NIR counterparts (e.g. McAlpine et al. 2012 ) and a sensitivity that, for typical radio sources, is superior to previous wide area surveys at higher frequencies such as the NRAO VLA Sky Survey (NVSS; Condon et al. 1998 ) and Faint Images of the Radio Sky at Twenty-Centimeters (FIRST; Becker et al. 1995 ) and is similar to forthcoming higher frequency surveys such as the Evolutionary Map of the Universe (EMU; Norris et al. 2011 ), and the APERture Tile In Focus survey (e.g. Röttgering et al. 2011 ). The primary observational objectives of LoTSS are to reach a sensitivity of less than 100 μ Jy


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S.C. is supported by the Netherlands Organization for Scientific Research (NWO; VIDI project 639.042.017) and by the European Research Council (ERC; project PALs 320620). This work was supported by the MOST grants MOST 106-2112-M-008-019-(Y.J.C.) and by the Spanish MINECO under projects AYA2011-29375, AYA2014-60585-P, and AYA2015-71975-REDT (R.M.-D. and G.M.M.C.). We acknowledge Dr. Wing-Fai Thi for useful feedback on the manuscript. We would like to thank the anonymous referee for valuable comments, which helped to improve the manuscript.