figurations were KVN+VERA+Tianma+Nanshan+Ibaraki at 22 GHz and KVN+VERA+Tianma at 43 GHz respectively, while occasionally a few more stations in East Asia (Sejong, Kashima, Nobeyama) and Italy (Medicina, Sardinia) joined if available. During the period outside March-May of each year, the observations were mostly conducted with the KVN and VERA Array (KaVA; Niinuma et al. 2014; Hada et al. 2017; Park et al. 2019), a core array of EAVN.

Each of the KaVA/EAVN sessions was made in a 5–7-hour continuous run at a data recording rate of 1 Gbps (a total bandwidth of 256 MHz in a single polarisation mode). All the data were correlated at the Daejeon hardware correlator installed at KASI. All the EAVN data were calibrated in the standard manner of VLBI data reduction procedures. We used the AIPS (Greisen 2003) software package for the initial calibration of visibility amplitude, bandpass and phase calibration. Imaging with the CLEAN algorithm (Högbom 1974) and self-calibration were performed with the Difmap (Shepherd 1997) software.

### B.1.3. VLBA 24 and 43 GHz

The total on-source time during the full-track segments is about 1.7 hours at 24 GHz and 6 hours at 43 GHz, while for the short segments it amounts to 30 minutes at 43 GHz. The sources OJ 287 and 3C 279 were observed to use as fringe finders and bandpass calibrators. In each band eight 32 MHz-wide frequency channels were recorded in both right and left circular polarisations at a rate of 2048 Mbps, and correlated with the VLBA software correlator in Socorro (Deller et al. 2011). The initial data reduction was conducted using AIPS, following the standard calibration procedures for VLBI data (Crossley et al. 2012; Walker 2014). Deconvolution and self-calibration algorithms, implemented in Difmap, were used for phase and amplitude calibration and for constructing the final images. Amplitude calibration accuracy of 10% is adopted for both frequencies. Images and polarimetric results from part of these VLBA observations are published in Kravchenko et al. (2020) and Park et al. (2021).

### B.1.4. GMVA+ALMA 86 GHz

The participating GMVA stations include the eight VLBA antennas equipped with 3.5 mm receivers, the Effelsberg 100 m telescope, the 100 m Green Bank Telescope, the Metsähovi 14 m telescope, the Onsala 20 m telescope, the IRAM 30 m telescope, and the Yebes 40 m telescope (YS). We note that the participation of ALMA and the GLT has improved the north-south resolution by a factor of ~4 for the observations of M87.

The observations (GMVA project code ML005) were performed for a total of ~13 h (~6 h with five telescopes in Europe (Effelsberg, Metstähovi, Onsala, IRAM30m and Yebes), ~7 h with ALMA, VLBA and GBT, and ~12 h with the GLT). Two bright calibration sources (3C273 and 3C279) were observed every 20-40 minutes in interleaved scans. The data were correlated with the VLBI correlator at the Max Planck Institute for Radio Astronomy using DiFX (Deller et al. 2011).

During these observations, most stations recorded the signals on a circular polarisation basis. However, the phased ALMA recorded the signals on a linear polarisation basis. Consequently, the visibilities between ALMA and the other stations were correlated on a mixed polarisation basis. After correlation, these visibilities were converted into a pure circular basis using the internal calibration of the ALMA interferometric data with the PolConvert algorithm (Martí-Vidal et al. 2016a). In addition,

GLT participated in these observations on a best-effort basis during its commissioning phase. The waveguide phase-shifter of the GLT that was used to convert the on-sky circular-polarisation signals into linear polarisation for detection at the backend was erroneously configured to apply a rotation of 45° (instead of 90°) between the polarisation channels. The instrumental polarisation effects caused by this rotation were removed with a dedicated algorithm after correlation. After this instrumental polarisation calibration, the data were then further calibrated following typical VLBI data reduction procedures in AIPS. Hybrid imaging was performed in the Difmap software with CLEAN and self-calibration. We refer the reader to Lu et al. (2023) for further details of data calibration. Based on the calibration and imaging of the calibrator 3C273, we consider an error budget of 25% for the flux density estimate of M87. While a dedicated study based on these data is presented in Lu et al. (2023), here we provide a peak flux density of the core and VLBI-scale total flux density (Tables C.1 and C.2).

### B.1.5. KVN 22, 43, 86, and 129 GHz

The data were calibrated using a modified version of the KVN pipeline (Hodgson et al. 2016) to include ionospheric delay corrections with total electron content (TEC) maps, parallactic angle corrections, and Earth orientation parameter corrections. Prior to global fringe fitting, the 43, 86, and 129 GHz data were calibrated with the 22 GHz data by means of frequency phase transfer. After the pipeline calibration with AIPS, the inner 75% of each subband (due to flux loss at the bandpass edges) was used for further analysis. Following Kim et al. (2018), the data were averaged by 30 seconds for the 22 GHz and 43 GHz data, and by 10 seconds for the 86 GHz and 129 GHz data. As in M87 MWL2017, we assume a flux density measurement uncertainty of 10% at 43 GHz and 86 GHz, and 30% at 129 GHz. During the observations, a phase instability issue occurred with the 22 GHz receiver at the KVN Yonsei site (KYS) between January and March 2018, and between November 2018 and February 2019. This resulted in a ~50% flux loss for all KYS baselines. From a sample of compact sources within the iMOGABA program, we derived and applied empirical correction factors to the impacted data. An uncertainty of 15% is assumed for the 22 GHz flux density measurements made during observations where the empirical corrections were applied. For observations that were not impacted by the flux loss, an uncertainty of 10% is adopted. A common 1 mas FWHM circular Gaussian beam is used to convolve the 22, 43, 86, 129 GHz CLEAN maps when determining the peak flux density of the core. This is closest to the natural beams of the KVN at 86 and 129 GHz. In Table C.1, we summarise the data obtained during 2018. In Fig. 3, we also add the earlier (2012–2016) data that were originally published in the literature (Kim et al. 2018) but the peak flux densities are recalculated using the procedures applied for 2017–2018 data.

### B.1.6. Global 43 GHz VLBI

The participating stations include Effelsberg, Yebes 40 m, Metsähovi, KVN (three stations), 100-m Green Bank Telescope, VLBA (10 stations), and the phased Jansky Very Large Array (JVLA). The data were recorded with a total recording rate of 2 Gbps, corresponding to 256 MHz bandwidth per polarisation. The scheduling, observation, and data reduction followed the standard procedures using AIPS. Similar to other VLBI data reduction and imaging, the CLEAN imaging and
self-calibration were made using procedures implemented in Difmap. The resulting FWHM angular resolutions are 0.2 × 0.7 (0.12 × 0.47) mas² with the beam position angle ~ 0 deg for the natural (uniform) weighting.

### B.1.7. ALMA 93 GHz and 221 GHz

The VLBI observations were carried out while the array was in its most compact configuration and only antennas within a radius of 180-m (from the array centre) were used for phasing. The observations were performed in full-polarisation mode to supply the inputs to the polarisation conversion process at the VLBI correlators (Martí-Vidal et al. 2016b).

The setup included four spectral windows (SPWs) of 1875 MHz in each band, two in the lower and two in the upper sideband, centred at 86, 88, 98, and 100 GHz in Band 3, and 213, 215, 227, and 229 GHz in Band 6, respectively. The SPWs were correlated with 240 channels per SPW (corresponding to a spectral resolution of 7.8125 MHz). Details about ALMA operations in VLBI mode and a full description of the data processing and calibration can be found in Goddi et al. (2019).

Imaging was performed with the Common Astronomy Software Applications package (CASA, version 6.4.1 used; McMullin et al. 2007; CASA Team 2022) task tclean. Only phased antennas were used to produce the final images (with baselines <360 m), yielding synthesised beam sizes ~2.5" in Band 3 and ~ 1" in Band 6, respectively. To isolate the core emission from the jet, we compute the sum of the central nine pixels of the model (cleaning component) map, an area of 3 × 3 pixels; the contribution from the jet is accounted for by also summing the clean components along the jet. While the extended emission accounts for less than 20% of the total emission at 1.3 mm, at 3mm it also includes emission from the radio lobes, accounting for more than 60% of the total emission. The absolute amplitude scale calibration has a 5%/10% uncertainty in Band 3/6, respectively. Details about the imaging and flux extraction methods can be found in Goddi et al. (2021).

### B.1.8. SMA 200 & 345 GHz

Data from this program are updated regularly and are available at the SMA Observer Center website (SMAOC<fnref n="7" />). Data were primarily obtained in a compact configuration (baselines from 10 to 75 m) though some were obtained at longer baselines up to 210 m. The effective spatial resolution was therefore generally around 3". We have limited analysis to projected baselines longer than 30 kλ (effective spatial scales smaller than 6.8"). The flux density was obtained by vector averaging of the calibrated visibility data from each observation.

Interferometric observations of M87 were additionally conducted as part of the 2017 and 2018 EHT campaigns, concurrent with the SMA running in phased-array mode operating at 230 GHz. In 2017 the SMA was in compact configuration, while in 2018 the SMA was in extended configuration (baselines 25 m to 210 m). In both years, the interferometer operated in dual-polarisation mode. The SMA correlator produces four separate but contiguous 2 GHz spectral windows per sideband, resulting in frequency coverage of 208 – 216 and 224 – 232 GHz. Data were passband and amplitude calibrated using 3C279, with flux calibration performed using either Callisto, Ganymede, or Titan. Phase calibration was done through self-calibration of the M87 data itself, assuming a point-source model.

## B.2. Optical and UV observations

### B.2.1. Optical observations by the Kanata telescope

We adopted standard reduction procedures for the images: bias- or dark-frame subtraction, correction of bad pixels, flattening correction, removal of contamination of CR signals, sky-background subtraction, solving the corresponding coordinates in the World Coordinate System (WCS) using field stars, and stacking of the images aligned with the coordinates of WCS.

We performed an aperture photometry of field stars in the stacked images using Source Extractor software (Bertin & Arnouts 1996). The value of FLUX_AUTO was adopted as the photometric measurements. We estimated zero points of the images in the AB magnitude system using nearby stars whose actual magnitudes have been provided in the references: the Pan-STARRS1 catalogue (Flewelling et al. 2020) of the optical band after conversion of the filter system (Tonry et al. 2012) and the 2MASS catalogue (Skrutskie et al. 2006) of the near-infrared band.

### B.2.2. Optical and UV observations from Swift-UVOT

UVOT data in all filters were analysed with the uvotimsum and uvotsource tasks included in the HEASoft package (v6.32) and the 20231208 CALDB-UVOTA release. Source counts were extracted from a circular region of 5" radius centred on the source, while background counts were derived from a circular region with 30" radius in a source-free region located outside the host galaxy radius (~ 120"). The UVOT magnitudes are corrected for the host galaxy contamination (see Table C.6) and the Galactic extinction using an E(B-V) value of 0.020 from Schlafly & Finkbeiner (2011) and the extinction laws from Cardelli et al. (1989) and converted to flux densities using the conversion factors from Breeveld et al. (2010). We have used the same host galaxy model as presented in Table A2 of EHT MWL Science Working Group (2021). However, we have to note that flux densities of the host galaxy listed in Table A2 of EHT MWL Science Working Group (2021) did not have aspect corrections although the correct values of the host galaxy as given in Table C.6 were used in the data reduction of Swift-UVOT data in EHT MWL Science Working Group (2021).

### B.2.3. Far-UV observations from AstroSat-UVIT

For the AstroSat-UVIT analysis, the VIS data are used for drift correction of the images in NUV and FUV channels. The FUV and NUV detectors work in photon-counting mode and the VIS detector works in integration mode. Each of these channels is equipped with a number of narrow and wide band filters (for details refer to Tandon et al. 2017, 2020). Out of the two AstroSat pointing observations (i.e. A04_115T02_9000001900 and A04_115T02_9000002042), only the UVIT data of the second one are available. These observations are made in the BaF2 band (F154W: $\lambda_{eff} \sim 1541$ Å, with $\Delta\lambda_{eff} \sim 380$ Å). The level-1 data, downloaded from the AstroSat data archive 'astrobrowse', is used to create the image using the CCDLAB software package (Postma & Leahy 2017) incorporating the corrections for the spacecraft drift, geometrical distortions and flat-fielding.

A two-dimensional (2D) image decomposition method was used with IMFIT<fnref n="8" /> (Erwin 2015) tool. The following combination of 2D models is used to create the model image of M87 using UVIT: PointSource + PointSource +

<footnote n="7">⁷ http://sma1.sma.hawaii.edu/callist/callist.html</footnote>

<footnote n="8">⁸ https://www.mpe.mpg.de/~erwin/code/imfit</footnote>
Core-Sersic + SersicJet + Flat-Sky. The point sources used here are convolved with the PSF of the UVIT instrument.

The UVIT-BaF2 image, centred at M87 and zooming into a small region around it is shown in Fig. B.1. The two point source models are added to account for the contributions from M87*'s core and the HST-1 knot. The Core-Sersic model (Graham et al. 2004) is used to represent the emission from the host galaxy. In order to take the asymmetric jet into account we created a modified version of the Sersic model by adding an asymmetry term to the originally symmetric Sersic function. But even with the added asymmetry, the shape of the bright spots towards the end of the jet is too complex to develop a good analytical model to describe it. Motivated by the above we masked this irregular complex part of the jet with a rectangular mask. The Flat-Sky model (Mondal et al. 2018) was used to include a component for the sky background. The best fit composite model corresponds to a reduced $\chi^2$ value of 1.

This model is then used to represent the composite radial profile for the host and jet. We then performed aperture photometry of the image using the Python package photutils<fnref n="9" /> with a source region of 5" centred at the position of M87*. The contributions of other prominent components to this region were estimated using the modelled radial profile for composite emission from the jet, the host galaxy and the sky. The corrected magnitude is then converted to flux using an appropriate flux conversion factor as provided by the instrument team. The corresponding numbers are shown in the Table C.8.

## B.3. X-ray observations

### B.3.1. Chandra and NuSTAR observations and joint spectral analysis

We keep the data processing and analysis as consistent as possible with our previous work on the *Chandra* and *NuSTAR* data taken in parallel with the 2017 EHT campaign described in M87 MWL2017. We only briefly summarise them here. For the *Chandra* data, we used standard data reduction procedures in CIAO (Fruscione et al. 2006) version 4.9 to extract 0.4–8 keV spectra from the spatially resolved components, the core, the HST-1 knot, and the outer jet, along with the corresponding instrumental response files. The *NuSTAR* observation was processed following standard procedures outlined in Perri et al. (2017), using NuSTARDAS version 1.8.0 to produce 3–79 keV spectra and instrumental responses with CALDB version 20180312. Source and background regions for Focal Plane Module A and B (FPMA, FPMB) were the same as in M87 MWL2017: 45" circles that are large enough to include all of the *Chandra* spatial components mentioned above as well as much of the surrounding diffuse emission from the intracluster medium (ICM).

We proceed to joint spectral modelling of the *Chandra* and *NuSTAR* data in order to take advantage of the high spatial resolution of *Chandra* and the high-energy sensitivity of *NuSTAR*. Our modelling strategy, described in detail in M87 MWL2017, properly accounts for the effects of pileup in *Chandra* data and includes consideration of the cross-normalisation between the instruments with respect to the modelled diffuse ICM emission that is differently sampled by *Chandra* and *NuSTAR*. For the diffuse component, we adopt a spectral model with two APEC components (Smith et al. 2001) with different temperatures and variable elemental abundances, three additional emission lines,

and a cutoff component for the low-mass X-ray binary contribution from within the host galaxy. For the core, the HST-1 knot, and the remainder of the jet, we modelled their continuum emission using PLs. All spectral models include interstellar absorption (Wilms et al. 2000). The absorption column towards the core was previously found to be higher (e.g. Perlman & Wilson 2005), that we allow for by including an extra layer of absorption in the model for this component.

We performed spectral fitting on spectra binned using a custom algorithm that ensures a minimum signal-to-noise ratio within each energy bin (as described in M87 MWL2017). To find the best-fit model parameters we minimised the Cash statistic (Cash 1979) as appropriate for the low-count regime and our binning strategy. Our best fit has a Cash statistic of 1219.023 for 1034 data bins and 37 free parameters. Our multi-component best-fit model is shown along with the data in Fig. 21; red lines represent the model for each dataset, and the *NuSTAR* model is the sum of all the other spatial components. We derive uncertainties using a Markov Chain Monte Carlo (MCMC) sampler emcee (Foreman-Mackey et al. 2013) set to run for 60,000 steps with 10 walkers for each of 37 parameters (a total of 22.2 million model evaluations). We discarded the first 185 000 evaluations for calculating chain statistics. Unless otherwise noted, quoted uncertainties represent minimum width intervals containing 90% of the probability function for each spectral parameter.

### B.3.2. Swift-XRT observations and analysis

The standard pipeline xrtpipeline version 0.13.5 was used to create level 3 cleaned event files for each Swift-XRT observation. We use a circular source region of radius 35" for spectral extraction, encompassing all three of the X-ray sources examined individually in the *Chandra* analysis. For background extraction, we create an annular background region with inner and outer radii of 130" and 150", respectively. Using xselect (version 2.4k), we extract spectra for the source and background regions after correcting for pile-up in the source region. If the source region count rate exceeded 0.5 ct s⁻¹ for any observations, we applied a pile-up correction by using an annular region to exclude central pixels affected by pile-up.

Creating ancillary response files for each spectrum with the xrtmkarf task, we grouped the spectral files for each epoch to a minimum of 20 counts per bin using the grppha command to facilitate $\chi^2$ fitting using xspec. Since the spectral resolution of *Chandra* is better than Swift-XRT, we adopted the source and background model fitted in the *Chandra* analysis. All spectral parameters of that model were frozen at the *Chandra* best-fit values (see Sect. 2.3.1) except the normalisation of the APEC and line emission backgrounds and the joint normalisation of the three power law components for the core, the HST-1 knot, and jet emission. The relative normalisation between the two APEC background components and between the three PL source components were kept frozen at the *Chandra* values. We use $\chi^2$ fitting via xspec to conduct this X-ray analysis. In this way, we evaluate the changing total and small-scale components (core, the HST-1 knot and inner jet) fluxes from the source.

### B.3.3. AstroSat-SXT observations and analysis

We used sxtpipeline (version 1.4b) along with the standard filtering criteria to generate the cleaned events file. The standard procedure includes time-tagging of events, removing hot pixels, bias corrections, coordinate transformation, filter-

<footnote n="9">⁹ https://photutils.readthedocs.io/en/stable/aperture.html</footnote>
<figure><img src="image_23.png" /><figcaption>**Fig. B.1.** AstroSat UVIT observations of M87. Left: M87 in BaF2 band. Right: Difference image of M87. The patched area is basically the masked region of the jet.</figcaption></figure>

ing (South Atlantic Anomaly passage, Sun-angle, Moon-angle), charge transfer inefficiency corrections, and generation of full-frame products. The processed event lists obtained in this way were then input to `xselect` to extract spectra, light curves, and images.

We used a circular source region of radius of 15' centred on the brightest pixel in the SXT image ($\alpha = 12:30:50.41, \delta = +12:22:32.4$), that is consistent with the peak of the flux distribution in *Chandra* and *NuSTAR* images. From the PSF size of the SXT we estimate that this region includes over 97% of the total number of detected photons. The background spectrum extracted using deep blank sky observations and distributed by the instrument team<fnref n="10" /> is used to model the spectrum. We used the tool `sxtARFModule` (version 0.3) along with the full-frame ARF (`sxt_pc_excl00_v04.arf`) distributed by the SXT Payload Operation Center<fnref n="11" /> to create ARF for the specific source region selection. We utilised the RMF file `sxt_pc Mat g0to12.rmf` corresponding to the default 0–12 grade selection.

For spectral fitting we used a model defined with the following expression in `xspec`: $TBabs \times (vvapec + vvapec + cutoffpl + TBabs \times powerlaw + powerlaw + powerlaw + Gaussian + vvapec)$. This is similar to the model adopted for *Chandra* and *NuSTAR* spectral analysis, except one Gaussian component, that is added in order to fit the broad hump-like residuals around 1.4 keV. An additional `vvapec` component is included to account for the diffuse emission from cluster gas in the outer regions because the SXT samples a larger portion of it (radius ≈15') than other focusing X-ray instruments considered in this work. The parameters of the three `vvapec` components, except the temperature and normalisation, are fixed to the values obtained from joint *Chandra* and *NuSTAR* spectral modelling (Sect. 2.3.1). To reduce the number of free parameters, we tied together the temperature and normalisation parameters of the `vvapec` components with a multiplicative factor. We adopt the sum of these three components with different temperatures to represent the large-scale emission from hot gas in the galaxy and the surrounding cluster. Three PL components are representative of the core, the HST-1 knot, and jet contributions; their PL photon indices are kept fixed based on values determined from the analysis of *Chandra* and *NuSTAR* data. We keep the normalisation of the core contribution free in the fitting, while

the normalisation of the HST-1 knot and jet components is tied with the core normalisation using the multiplicative factors also employed in *Swift-XRT* spectral modelling in Sect. 2.3.2, as well as in M87 MWL2017.

As in Sect. 2.3.1, we used the Cash statistic to find the best-fitting composite model. To account for the systematics introduced by the procedures related to ARF generation (such as vignetting model and PSF-based scaling of the effective area, etc.), we included an additional 1% uncertainty to the observed spectra. Constraints on the free parameters of the model are given in Table C.9. Figure B.2 shows the *AstroSat*-SXT individual PL components to be interpreted as upper limits due to the angular resolution of the instrument.

## B.4. γ-ray observations

### B.4.1. Fermi-LAT observations

*Fermi*-LAT (Atwood et al. 2009) is a γ-ray telescope that detects photons by conversion into electron-positron pairs, and it has an operational energy range from 20 MeV to more than 300 GeV. Since its launch in June 2008, it mostly works in survey mode covering the whole sky in about three hours and with a remarkable overall uptime of 99.8% (Ajello et al. 2021).

Regarding the data selection, we used P8R3 (v3) SOURCE class events (Bruel et al. 2018), in the energy range between 100 MeV and 1 TeV, in a region of interest (ROI) of 15° × 15° centred on the position of M87. The low-energy threshold is motivated by the large uncertainties in the arrival directions of the photons below 100 MeV, leading to possible confusion between point-like sources and the Galactic diffuse component (see Principe et al. (2018) for a different analysis implementation to solve this and other issues at low energies with *Fermi*-LAT).

The analysis (that consists of the following steps: model optimisation, source localisation, spectrum and emission variability studies) was performed with FermiPyr<fnref n="12" /> (v1.0.1; Wood et al. 2017), that uses the Fermi Tools, version 2-0-18. We created counts maps using a pixel size of 0.1°. All γ-rays with zenith angle larger than 95° were excluded in order to limit the contamination from secondary γ-rays from the Earth's limb (Abdo et al. 2009). In order to optimise the analysis, we applied different cuts for the data selections at low energies and selected event

<footnote n="10">¹⁰ AstroSat Science Support Cell: http://astrosat-ssc.iucaa.in</footnote>

<footnote n="11">¹¹ TIFR, Mumbai: www.tifr.res.in/~astrosat_sxt</footnote>

<footnote n="12">¹² http://fermipy.readthedocs.io/en/latest/</footnote>
<figure><img src="image_24.png" /><figcaption>**Fig. B.2.** AstroSat-SXT observations of M87 with SED estimates from spectral modelling. Dashed-dotted and dotted lines are representative of observations made in February and March 2018, respectively. The grey, light-blue and light-red shaded regions around the lines are $1\sigma$ uncertainty regime derived using parameter estimations, each representing core, jet and the HST-1 knot sub-components, respectively. The downward arrows are indicative that given the limitations of the instrumental capabilities, these estimations should be treated as upper limits for further investigations.</figcaption></figure>

types with the best PSF<sup>13</sup>. In particular, for energies below 300 MeV, we excluded events with zenith angle larger than 85°, as well as photons from PSF0 and PSF1 event types. Between 300 MeV and 1 GeV we excluded events with zenith angle larger than 95°, as well as photons from the PSF0 event type. Above 1 GeV we used all events with zenith angles less than 105°. The P8R3_Source_V3 instrument response functions (IRFs) were used. The model used to describe the sky includes all point-like and extended sources located at a distance <15° from the source position and listed in the 4FGL-DR2 (Abdollahi et al. 2020) as well as the Galactic diffuse and isotropic emission. For the latter contributions, we used the same templates<sup>14</sup> adopted to derive the 4FGL catalogue.

We performed the spectral analysis, allowing the diffuse background template normalisation and the spectral parameters of the sources to vary within 3° from our targets. For the sources in a radius between 3°–5° and all variable sources only the normalisation was fit, while we fixed to their 4FGL values the parameters of all the remaining sources within the ROI at larger angular distances from our target. We modelled the spectrum of M87 with a PL function.

Finally, for the analysis on the 12 years of LAT data we extracted a light curve using time bins of one month. Similarly, for analysis on a one-month scale centred on EHT observations, the light curve analysis was repeated using time intervals of two days in order to investigate the emission variability on short time scales. We tried also different time intervals with both fixed (1 day and 1 week) or customised duration (discriminating between

before, during and after the VHE γ-ray flare). The fluxes in each interval were obtained by leaving only the normalisation free to vary and freezing the other spectral parameters to the best-fit values obtained from the full range analysis.

## B.4.2. Very high energy observations: H.E.S.S., MAGIC, VERITAS

H.E.S.S. observations were performed with a wobble mode with an offset of 0.7° from the position of M87, that allows for a simultaneous background estimation. The analysis and reconstruction of the Cherenkov shower images were done with the ImPACT maximum likelihood-based technique (Parsons & Hinton 2014). The separation between γ-rays and hadrons was performed with a boosted decision tree classification method (Ohm et al. 2009). For the signal estimation, the background was estimated using the “ring-background model” whereas the calculation of the light curve and the spectrum was done using the “reflected-background model” (Berge et al. 2007). A source with 1% of the Crab Nebula’s flux can be detected above 100 GeV in ~10 hours.

The stereoscopic MAGIC observations were conducted in wobble mode with an offset of 0.4°. Image reconstruction and data analysis were performed with the standard MAGIC analysis framework MARS (MAGIC Analysis and Reconstruction Software; Zanin 2013; Aleksić et al. 2016). To estimate the instrument’s PSF in true energy we used the spatial likelihood analysis package SkyPrism from Vovk et al. (2018). The observations on MJD 58232 were taken with a strong moonlight background present and therefore analysed as described in Ahnen et al. (2017). MAGIC’s integral sensitivity is 1% of the Crab Nebula’s flux in ~26 hours above an analysis energy threshold of 290 GeV.

Data analysis of the observations in 2019 was performed identically to the aforementioned 2018 observations. The reconstructed flux levels in 2019 are compatible with the previously observed quiescent flux (see, e.g. MAGIC Collaboration 2020; EHT MWL Science Working Group 2021). The MAGIC fluxes published in MAGIC Collaboration (2020) use an analysis threshold of 300 GeV for the light curve. Instead of scaling the VHE fluxes between 2012 and 2015 according to the PL spectrum, we repeated the flux calculations with a threshold of 350 GeV, using the original high-level analysis files of the authors of MAGIC Collaboration (2020).

The stereoscopic VERITAS observations were conducted in wobble mode with an offset of 0.5°. The data were analysed using the VERITAS standard analysis procedure (Daniel 2008). The main software package used in this work is called Event-display. An overview of this analysis package can be found in Maier & Holder (2018). In addition, a cross-check analysis was performed using an independent software package called VEGAS (Cogan 2007). VERITAS is designed to measure γ rays with energies from ~85 GeV and it is able to detect a source with about 1% of the Crab Nebula within 25 hours (Park 2016).

To explore possible systematic flux scale offsets between VERITAS, MAGIC, and H.E.S.S. and investigate how the uncertain flux scales might affect the results in Sect. 2.4.2, we applied two cross-normalisation factors ($f_1$ and $f_2$) to the VERITAS and MAGIC fluxes as extra fitting parameters. We note that statistical errors on individual flux points were not altered. We note that this choice is purely arbitrary and that the cross-normalisation factors could be applied to any two of the three IACTs. For an earlier study of systematic offsets between IACTs see Meyer et al. (2010). In our case, the maximum flux scale offsets between the instruments are set to 15%. These offsets are

<footnote n="13"><sup>13</sup> A measure of the quality of the direction reconstruction is used to assign events to four quartiles. γ-rays in Pass 8 data can be separated into 4 PSF event types: 0, 1, 2, 3, where PSF0 has the worst resolution and PSF3 has the best one.</footnote>

<footnote n="14"><sup>14</sup> https://fermi.gsfc.nasa.gov/ssc/data/access/lat/BackgroundModels.html</footnote>
<table><caption>**Table B.1.** Best fit results for a constant and a Gaussian model (Eq. 1) describing the temporal progression of the flare as seen by VERITAS, MAGIC, and H.E.S.S.</caption><thead><tr><th>Model</th><th>χ<sup>2</sup>/d.o.f.</th><th>p value</th><th>f<sub>1</sub></th><th>f<sub>2</sub></th><th>F<sub>0</sub><br>(10<sup>-12</sup><br>ph cm<sup>-2</sup>s<sup>-1</sup>)</th><th>F<sub>1</sub><br>(10<sup>-12</sup><br>ph cm<sup>-2</sup>s<sup>-1</sup>)</th><th>t<sub>0</sub><br>(MJD)</th><th>σ<br>(days)</th></tr></thead><tbody><tr><td>Constant</td><td>33.66/14</td><td>2.3 × 10<sup>-3</sup></td><td>1.32 ± 0.41</td><td>1.35 ± 0.42</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td>Gaussian</td><td>10.68/11</td><td>0.47</td><td>1.35 ± 0.25</td><td>1.30 ± 0.49</td><td>(1.60 ± 0.62)</td><td>(3.18 ± 0.73)</td><td>58228.99 ± 0.26</td><td>1.11 ± 0.36</td></tr></tbody></table>

used to constrain the fitting range of $f_1$ and $f_2$. The results of the fit of a constant and a Gaussian function (Eq. (1)) are shown in Table B.1.
**Appendix C: Tabulated data**

This section contains the list of tabulated data from observations described in Sect. 2, as follows:

1. Summary of radio observations and flux densities at centimetre wavelengths in Table C.1 and millimetre wavelengths in Table C.2;

2. Kanata Telescope flux densities at the optical wavelength of 634.9 nm in Table C.3 and near-infrared wavelength of 1250 nm in Table C.4;

3. Optical and ultraviolet flux densities of Swift-UVOT in Table C.5, while Table C.6 contains of the host galaxy;

4. Photometry at the ultraviolet wavelength of 154 nm from AstroSat-UVIT in Table C.8;

5. Optical HST observations in Table C.7;

6. Parameters of the composite spectral model for AstroSat-SXT data in Table C.9;

7. Summary of *Swift-XRT* observations and fluxes in the 2–10 keV band in Table C.10;

8. Summary of *Chandra* core fluxes for the observations performed in 2017 and 2018. in Table C.11, while the *Chandra+NuSTAR* spectral values for stacked observation, normalised on 2018 emission are reported in Table C.12;

9. Summary of *Fermi*-LAT fluxes for the customised-bin light curve analysis on April 2018. in Table C.13;

10. Summary of VHE γ-ray observations and fluxes above energies of 350 GeV in Table C.14 and parameters of the spectral models fitted to data from H.E.S.S., MAGIC, and VERITAS in Table C.15;

11. Spectral energy distribution for M87 observed during the 2018 EHT campaign in Table C.1;

12. In addition the spectral models (Model-A-PL, Model-A, BPL, Model-B) used to describe the MWL SED (see Sect. 4) are also reported as supplementary material.

Tables C.1 to C.15 are available at the CDS. Furthermore, these data are provided to the community in machine-readable form via the EHTC Data Webpage<fnref n="15" /> along with associated documentation and files needed for spectral modelling of the X-ray data.

<footnote n="15">¹⁵ https://eventhorizontelescope.org/for-astronomers/data</footnote>
<caption>**Table C.1.** Spectral Energy Distribution for M87 during the 2018 EHT-MWL campaign.</caption>

<table><thead><tr><th>Observatory</th><th>Band</th><th>γ [Hz]</th><th>Angular Scale<sup>(1)</sup> ["]</th><th>Obs. date [MJD]</th><th>Flux [Jy]</th><th>νF<sub>ν</sub> [×10<sup>-12</sup> erg cm<sup>-2</sup> s<sup>-1</sup>]</th><th>Sect.</th></tr></thead><tbody><tr><td>VERA</td><td>22 GHz</td><td>2.2 × 10<sup>10</sup></td><td>1 × 10<sup>-3</sup></td><td>2018-04-26 / 58234</td><td>1.12 ± 0.11</td><td>0.246 ± 0.024</td><td>2.1.1.</td></tr><tr><td>EAVN/KaVA</td><td>22 GHz</td><td>2.2 × 10<sup>10</sup></td><td>1 × 10<sup>-3</sup></td><td>2018-05-08 / 58246</td><td>1.01 ± 0.10</td><td>0.232 ± 0.023</td><td>2.1.2.</td></tr><tr><td>EAVN/KaVA</td><td>43 GHz</td><td>4.3 × 10<sup>10</sup></td><td>1 × 10<sup>-3</sup></td><td>2018-04-21 / 58229</td><td>0.94 ± 0.09</td><td>0.404 ± 0.039</td><td>2.1.2.</td></tr><tr><td>VLBA</td><td>24 GHz</td><td>2.4 × 10<sup>10</sup></td><td>6 × 10<sup>-4</sup></td><td>2018-04-27 / 58235</td><td>0.88 ± 0.09</td><td>0.211 ± 0.021</td><td>2.1.3.</td></tr><tr><td>VLBA</td><td>43 GHz</td><td>4.3 × 10<sup>10</sup></td><td>4 × 10<sup>-4</sup></td><td>2018-04-27 / 58235</td><td>0.59 ± 0.06</td><td>0.254 ± 0.024</td><td>2.1.3.</td></tr><tr><td>Global VLBI</td><td>43 GHz</td><td>4.3 × 10<sup>10</sup></td><td>2.5 × 10<sup>-4</sup></td><td>2018-02-01 / 58150</td><td>0.65 ± 0.06</td><td>0.279 ± 0.027</td><td>2.1.6.</td></tr><tr><td>GMVA+ALMA</td><td>86 GHz</td><td>8.6 × 10<sup>10</sup></td><td>2.0 × 10<sup>-4</sup></td><td>2018-04-14 / 58222</td><td>0.53 ± 0.10</td><td>0.458 ± 0.086</td><td>2.1.5.</td></tr><tr><td>KVN</td><td>86.8 GHz</td><td>8.68 × 10<sup>10</sup></td><td>1.0 × 10<sup>-3</sup></td><td>2018-04-19 / 58227</td><td>0.93 ± 0.09</td><td>0.807 ± 0.078</td><td>2.1.5.</td></tr><tr><td>KVN</td><td>129.3 GHz</td><td>1.29 × 10<sup>11</sup></td><td>1.0 × 10<sup>-3</sup></td><td>2018-04-19 / 58227</td><td>0.65 ± 0.20</td><td>0.84 ± 0.26</td><td>2.1.5.</td></tr><tr><td>ALMA</td><td>93 GHz</td><td>9.3 × 10<sup>10</sup></td><td>2.4</td><td>2018-04-15 / 58223</td><td>1.41 ± 0.07</td><td>1.31 ± 0.07</td><td>2.1.7.</td></tr><tr><td>ALMA</td><td>221 GHz</td><td>2.21 × 10<sup>11</sup></td><td>0.85</td><td>2018-04-21 / 58229</td><td>1.10 ± 0.11</td><td>2.43 ± 0.24</td><td>2.1.7.</td></tr><tr><td>SMA</td><td>221 GHz</td><td>2.21 × 10<sup>11</sup></td><td>≈ 3.0</td><td>2018-04-22 / 58230</td><td>1.33 ± 0.07</td><td>2.94 ± 0.15</td><td>2.1.8.</td></tr><tr><td>EHT</td><td>230 GHz</td><td>2.3 × 10<sup>11</sup></td><td>2 × 10<sup>-5</sup></td><td>2018-04-21 / 58229</td><td>0.5–1.0</td><td>1.15–2.30</td><td>1.</td></tr><tr><td>Kanata</td><td>1250 nm</td><td>2.4 × 10<sup>14</sup></td><td>≈10</td><td>2018-04-21 / 58229</td><td>&lt; 2.16 × 10<sup>-3</sup></td><td>&lt; 5.18</td><td>2.2.1.</td></tr><tr><td>Kanata</td><td>634.9 nm</td><td>4.7 × 10<sup>14</sup></td><td>≈10</td><td>2018-04-21 / 58229</td><td>&lt; 1.05 × 10<sup>-3</sup></td><td>&lt; 4.96</td><td>2.2.1.</td></tr><tr><td>HST</td><td>236.0 nm</td><td>1.27 × 10<sup>15</sup></td><td>≈0.1</td><td>2018-07-30/58329</td><td>(1.51 ± 0.77) × 10<sup>-4</sup></td><td>1.92 ± 0.96</td><td>2.2.3.</td></tr><tr><td>AstroSat-UVIT</td><td>173–135 nm</td><td>1.95 × 10<sup>15</sup></td><td>≈300</td><td>2018-04-21 / 58229</td><td>&lt; 1.05 × 10<sup>-3</sup></td><td>&lt; 5.13</td><td>2.2.4.</td></tr><tr><td>AstroSat-SXT</td><td>0.2–1 keV</td><td>1.21 × 10<sup>17</sup></td><td>≈900</td><td>2018-04-21 / 58229</td><td>&lt; 7.75 × 10<sup>-6</sup></td><td>&lt; 15.0</td><td>2.2.4.</td></tr><tr><td>AstroSat-SXT</td><td>1–3 keV</td><td>4.84 × 10<sup>17</sup></td><td>≈900</td><td>2018-04-21 / 58229</td><td>&lt; 3.01 × 10<sup>-6</sup></td><td>&lt; 14.6</td><td>2.2.4.</td></tr><tr><td>AstroSat-SXT</td><td>3–8 keV</td><td>7.26 × 10<sup>17</sup></td><td>≈900</td><td>2018-04-21 / 58229</td><td>&lt; 1.18 × 10<sup>-7</sup></td><td>&lt; 14.3</td><td>2.2.4.</td></tr><tr><td>Swift-UVOT</td><td>546.8 nm</td><td>5.48 × 10<sup>14</sup></td><td>≈3</td><td>2018-04-21 / 58229</td><td>(1.92 ± 0.79) × 10<sup>-3</sup></td><td>10.5 ± 4.1</td><td>2.2.2.</td></tr><tr><td>Swift-UVOT</td><td>439.2 nm</td><td>6.83 × 10<sup>14</sup></td><td>≈3</td><td>2018-04-21 / 58229</td><td>(1.66 ± 0.27) × 10<sup>-3</sup></td><td>11.4 ± 1.8</td><td>2.2.2.</td></tr><tr><td>Swift-UVOT</td><td>346.5 nm</td><td>8.65 × 10<sup>14</sup></td><td>≈3</td><td>2018-04-21 / 58229</td><td>(6.01 ± 0.09) × 10<sup>-4</sup></td><td>5.22 ± 0.82</td><td>2.2.2.</td></tr><tr><td>Swift-UVOT</td><td>260.0 nm</td><td>1.15 × 10<sup>15</sup></td><td>≈3</td><td>2018-04-21 / 58229</td><td>(1.47 ± 0.69) × 10<sup>-4</sup></td><td>1.69 ± 0.79</td><td>2.2.2.</td></tr><tr><td>Swift-UVOT</td><td>224.6 nm</td><td>1.33 × 10<sup>15</sup></td><td>≈3</td><td>2018-04-21 / 58229</td><td>(3.35 ± 0.41) × 10<sup>-4</sup></td><td>4.45 ± 0.54</td><td>2.2.2.</td></tr><tr><td>Swift-UVOT</td><td>192.8 nm</td><td>1.55 × 10<sup>15</sup></td><td>≈3</td><td>2018-04-21 / 58229</td><td>(1.60 ± 0.51) × 10<sup>-4</sup></td><td>2.48 ± 0.76</td><td>2.2.2.</td></tr><tr><td>Swift-XRT</td><td>2–10 keV</td><td>1.08 × 10<sup>18</sup></td><td>≈36</td><td>2018-04-21 / 58229</td><td>(2.19 ± 0.22) × 10<sup>-7</sup></td><td>4.24 ± 0.43</td><td>2.3.2.</td></tr><tr><td>Chandra + NuSTAR</td><td>0.4 – 0.51 keV</td><td>1.09 × 10<sup>17</sup></td><td>0.8</td><td>2018-04-22–24 / 58230–58232</td><td>(1.67 ± 0.17) × 10<sup>-6</sup></td><td>1.83 ± 0.19</td><td>2.3.2.</td></tr><tr><td>Chandra + NuSTAR</td><td>0.51 – 0.65 keV</td><td>1.40 × 10<sup>17</sup></td><td>0.8</td><td>2018-04-22–24 / 58230–58232</td><td>(1.29 ± 0.11) × 10<sup>-6</sup></td><td>1.81 ± 0.16</td><td>2.3.2.</td></tr><tr><td>Chandra + NuSTAR</td><td>0.65 – 0.84 keV</td><td>1.79 × 10<sup>17</sup></td><td>0.8</td><td>2018-04-22–24 / 58230–58232</td><td>(1.00 ± 0.07) × 10<sup>-6</sup></td><td>1.78 ± 0.13</td><td>2.3.2.</td></tr><tr><td>Chandra + NuSTAR</td><td>0.84 – 1.07 keV</td><td>2.29 × 10<sup>17</sup></td><td>0.8</td><td>2018-04-22–24 / 58230–58232</td><td>(7.67 ± 0.47) × 10<sup>-7</sup></td><td>1.77 ± 0.11</td><td>2.3.2.</td></tr><tr><td>Chandra + NuSTAR</td><td>1.07 – 1.37 keV</td><td>2.93 × 10<sup>17</sup></td><td>0.8</td><td>2018-04-22–24 / 58230–58232</td><td>(5.92 ± 0.29) × 10<sup>-7</sup></td><td>1.73 ± 0.08</td><td>2.3.2.</td></tr><tr><td>Chandra + NuSTAR</td><td>1.37 – 1.75 keV</td><td>3.75 × 10<sup>17</sup></td><td>0.8</td><td>2018-04-22–24 / 58230–58232</td><td>(4.57 ± 0.17) × 10<sup>-7</sup></td><td>1.71 ± 0.06</td><td>2.3.2.</td></tr><tr><td>Chandra + NuSTAR</td><td>1.75 – 2.24 keV</td><td>4.79 × 10<sup>17</sup></td><td>0.8</td><td>2018-04-22–24 / 58230–58232</td><td>(3.52 ± 0.08) × 10<sup>-7</sup></td><td>1.69 ± 0.05</td><td>2.3.2.</td></tr><tr><td>Chandra + NuSTAR</td><td>2.24 – 2.87 keV</td><td>6.13 × 10<sup>17</sup></td><td>0.8</td><td>2018-04-22–24 / 58230–58232</td><td>(2.71 ± 0.07) × 10<sup>-7</sup></td><td>1.67 ± 0.04</td><td>2.3.2.</td></tr><tr><td>Chandra + NuSTAR</td><td>2.87 – 3.67 keV</td><td>7.84 × 10<sup>17</sup></td><td>0.8</td><td>2018-04-22–24 / 58230–58232</td><td>(2.10 ± 0.07) × 10<sup>-7</sup></td><td>1.64 ± 0.06</td><td>2.3.2.</td></tr><tr><td>Chandra + NuSTAR</td><td>3.67 – 4.69 keV</td><td>1.00 × 10<sup>18</sup></td><td>0.8</td><td>2018-04-22–24 / 58230–58232</td><td>(1.62 ± 0.07) × 10<sup>-7</sup></td><td>1.62 ± 0.07</td><td>2.3.2.</td></tr><tr><td>Chandra + NuSTAR</td><td>4.69 – 6.00 keV</td><td>1.28 × 10<sup>18</sup></td><td>0.8</td><td>2018-04-22–24 / 58230–58232</td><td>(1.25 ± 0.07) × 10<sup>-7</sup></td><td>1.60 ± 0.09</td><td>2.3.2.</td></tr><tr><td>Chandra + NuSTAR</td><td>6.00 – 7.67 keV</td><td>1.64 × 10<sup>18</sup></td><td>0.8</td><td>2018-04-22–24 / 58230–58232</td><td>(9.66 ± 0.67) × 10<sup>-8</sup></td><td>1.59 ± 0.11</td><td>2.3.2.</td></tr><tr><td>Chandra + NuSTAR</td><td>7.67 – 9.81 keV</td><td>2.10 × 10<sup>18</sup></td><td>0.8</td><td>2018-04-22–24 / 58230–58232</td><td>(7.47 ± 0.62) × 10<sup>-8</sup></td><td>1.57 ± 0.13</td><td>2.3.2.</td></tr><tr><td>Chandra + NuSTAR</td><td>9.81 – 12.6 keV</td><td>2.68 × 10<sup>18</sup></td><td>0.8</td><td>2018-04-22–24 / 58230–58232</td><td>(5.77 ± 0.56) × 10<sup>-8</sup></td><td>1.55 ± 0.15</td><td>2.3.2.</td></tr></tbody></table>
<table><caption>Table C.1. continued.</caption><thead><tr><th>Observatory</th><th>Band</th><th>ν [Hz]</th><th>Angular Scale<sup>(1)</sup> [’]</th><th>Obs. date [MJD]</th><th>Flux [Jy]</th><th>ν F<sub>ν</sub> [×10<sup>-12</sup> erg cm<sup>-2</sup> s<sup>-1</sup>]</th><th>Sect.</th></tr></thead><tbody><tr><td>Chandra + NuSTAR</td><td>12.6 - 16.1 keV</td><td>3.43 × 10<sup>18</sup></td><td>0.8</td><td>2018-04-22-24 / 58230-58232</td><td>(4.48 ± 0.49) × 10<sup>-8</sup></td><td>1.53 ± 0.17</td><td>2.3.2.</td></tr><tr><td>Chandra + NuSTAR</td><td>16.1 - 20.5 keV</td><td>4.39 × 10<sup>18</sup></td><td>0.8</td><td>2018-04-22-24 / 58230-58232</td><td>(3.45 ± 0.43) × 10<sup>-8</sup></td><td>1.51 ± 0.19</td><td>2.3.2.</td></tr><tr><td>Chandra + NuSTAR</td><td>20.5 - 26.3 keV</td><td>5.62 × 10<sup>18</sup></td><td>0.8</td><td>2018-04-22-24 / 58230-58232</td><td>(2.66 ± 0.37) × 10<sup>-8</sup></td><td>1.50 ± 0.21</td><td>2.3.2.</td></tr><tr><td>Chandra + NuSTAR</td><td>26.3 - 33.6 keV</td><td>7.18 × 10<sup>18</sup></td><td>0.8</td><td>2018-04-22-24 / 58230-58232</td><td>(2.06 ± 0.31) × 10<sup>-8</sup></td><td>1.48 ± 0.23</td><td>2.3.2.</td></tr><tr><td>Chandra + NuSTAR</td><td>33.6 - 43.0 keV</td><td>9.19 × 10<sup>18</sup></td><td>0.8</td><td>2018-04-22-24 / 58230-58232</td><td>(1.59 ± 0.27) × 10<sup>-8</sup></td><td>1.47 ± 0.24</td><td>2.3.2.</td></tr><tr><td>Chandra + NuSTAR</td><td>43.0 - 55.0 keV</td><td>1.18 × 10<sup>19</sup></td><td>0.8</td><td>2018-04-22-24 / 58230-58232</td><td>(1.23 ± 0.22) × 10<sup>-8</sup></td><td>1.45 ± 0.26</td><td>2.3.2.</td></tr><tr><td>Fermi-LAT</td><td>0.1 - 0.32 GeV</td><td>4.31 × 10<sup>22</sup></td><td>≈7000</td><td>2018-04-08-05-08 / 58216-58246</td><td>&lt; 2.17 × 10<sup>-11</sup></td><td>&lt; 11.6</td><td>2.4.1.</td></tr><tr><td>Fermi-LAT</td><td>0.32 - 0.75 GeV</td><td>1.18 × 10<sup>23</sup></td><td>≈4500</td><td>2018-04-08-05-08 / 58216-58246</td><td>(6.61 ± 2.89) × 10<sup>-12</sup></td><td>6.88 ± 3.01</td><td>2.4.1.</td></tr><tr><td>Fermi-LAT</td><td>0.75 - 1.78 GeV</td><td>2.79 × 10<sup>23</sup></td><td>≈2800</td><td>2018-04-08-05-08 / 58216-58246</td><td>(1.70 ± 0.88) × 10<sup>-12</sup></td><td>4.24 ± 2.20</td><td>2.4.1.</td></tr><tr><td>Fermi-LAT</td><td>1.78 - 4.22 GeV</td><td>6.63 × 10<sup>24</sup></td><td>≈1100</td><td>2018-04-08-05-08 / 58216-58246</td><td>(6.91 ± 4.01) × 10<sup>-13</sup></td><td>4.08 ± 2.37</td><td>2.4.1.</td></tr><tr><td>Fermi-LAT</td><td>4.22 - 10 GeV</td><td>1.57 × 10<sup>24</sup></td><td>≈700</td><td>2018-04-08-05-08 / 58216-58246</td><td>&lt; 4.32 × 10<sup>-11</sup></td><td>&lt; 6.04</td><td>2.4.1.</td></tr><tr><td>Fermi-LAT</td><td>10 - 100 GeV</td><td>7.65 × 10<sup>24</sup></td><td>≈350</td><td>2018-04-08-05-08 / 58216-58246</td><td>&lt; 2.42 × 10<sup>-11</sup></td><td>&lt; 5.27</td><td>2.4.1.</td></tr><tr><td>H.E.S.S.</td><td>0.32 - 0.46 TeV</td><td>9.35 × 10<sup>25</sup></td><td>≈360</td><td>2018-04-18-24 / 58226-58232</td><td>(6.40 ± 1.65) × 10<sup>-15</sup></td><td>2.17 ± 0.65</td><td>2.4.2.</td></tr><tr><td>H.E.S.S.</td><td>0.46 - 0.68 TeV</td><td>1.37 × 10<sup>26</sup></td><td>≈360</td><td>2018-04-18-24 / 58226-58232</td><td>(4.08 ± 0.85) × 10<sup>-15</sup></td><td>2.17 ± 0.45</td><td>2.4.2.</td></tr><tr><td>H.E.S.S.</td><td>0.68 - 1.00 TeV</td><td>2.00 × 10<sup>26</sup></td><td>≈360</td><td>2018-04-18-24 / 58226-58232</td><td>(2.09 ± 0.50) × 10<sup>-15</sup></td><td>1.62 ± 0.39</td><td>2.4.2.</td></tr><tr><td>H.E.S.S.</td><td>1.00 - 1.47 TeV</td><td>2.93 × 10<sup>26</sup></td><td>≈190</td><td>2018-04-18-24 / 58226-58232</td><td>(1.75 ± 0.38) × 10<sup>-15</sup></td><td>1.99 ± 0.43</td><td>2.4.2.</td></tr><tr><td>H.E.S.S.</td><td>1.47 - 2.15 TeV</td><td>4.30 × 10<sup>26</sup></td><td>≈190</td><td>2018-04-18-24 / 58226-58232</td><td>(9.30 ± 2.49) × 10<sup>-16</sup></td><td>1.53 ± 0.41</td><td>2.4.2.</td></tr><tr><td>H.E.S.S.</td><td>2.15 - 3.16 TeV</td><td>6.29 × 10<sup>26</sup></td><td>≈190</td><td>2018-04-18-24 / 58226-58232</td><td>(10.56 ± 2.21) × 10<sup>-16</sup></td><td>2.58 ± 0.54</td><td>2.4.2.</td></tr><tr><td>H.E.S.S.</td><td>3.16 - 4.64 TeV</td><td>9.21 × 10<sup>26</sup></td><td>≈190</td><td>2018-04-18-24 / 58226-58232</td><td>(4.83 ± 1.48) × 10<sup>-16</sup></td><td>1.73 ± 0.53</td><td>2.4.2.</td></tr><tr><td>H.E.S.S.</td><td>4.64 - 6.81 TeV</td><td>1.36 × 10<sup>27</sup></td><td>≈190</td><td>2018-04-18-24 / 58226-58232</td><td>(3.22 ± 1.10) × 10<sup>-16</sup></td><td>1.69 ± 0.58</td><td>2.4.2.</td></tr><tr><td>VERITAS</td><td>0.32 - 0.50 TeV</td><td>9.62 × 10<sup>25</sup></td><td>≈360</td><td>2018-04-10-21 / 58218-58229</td><td>(4.75 ± 1.26) × 10<sup>-15</sup></td><td>2.07 ± 0.55</td><td>2.4.2.</td></tr><tr><td>VERITAS</td><td>0.50 - 0.79 TeV</td><td>1.53 × 10<sup>26</sup></td><td>≈360</td><td>2018-04-10-21 / 58218-58229</td><td>(1.70 ± 0.60) × 10<sup>-15</sup></td><td>1.19 ± 0.42</td><td>2.4.2.</td></tr><tr><td>VERITAS</td><td>0.79 - 1.26 TeV</td><td>2.42 × 10<sup>26</sup></td><td>≈360</td><td>2018-04-10-21 / 58218-58229</td><td>(2.07 ± 0.4) × 10<sup>-15</sup></td><td>2.35 ± 0.53</td><td>2.4.2.</td></tr><tr><td>VERITAS</td><td>1.26 - 2.00 TeV</td><td>3.83 × 10<sup>26</sup></td><td>≈360</td><td>2018-04-10-21 / 58218-58229</td><td>(4.19 ± 2.07) × 10<sup>-16</sup></td><td>0.75 ± 0.37</td><td>2.4.2.</td></tr><tr><td>MAGIC</td><td>0.03 - 0.075 TeV</td><td>1.21 × 10<sup>25</sup></td><td>≈330</td><td>2018-04-12-25 / 58220-58233</td><td>&lt; 3.47 × 10<sup>-13</sup></td><td>&lt; 37.84</td><td>2.4.2.</td></tr><tr><td>MAGIC</td><td>0.075 - 0.19 TeV</td><td>3.04 × 10<sup>25</sup></td><td>≈300</td><td>2018-04-12-25 / 58220-58233</td><td>(9.03 ± 5.96) × 10<sup>-15</sup></td><td>2.51 ± 1.66</td><td>2.4.2.</td></tr><tr><td>MAGIC</td><td>0.19 - 0.48 TeV</td><td>7.64 × 10<sup>25</sup></td><td>≈240</td><td>2018-04-12-25 / 58220-58233</td><td>(2.39 ± 1.20) × 10<sup>-15</sup></td><td>1.68 ± 0.84</td><td>2.4.2.</td></tr><tr><td>MAGIC</td><td>0.48 - 1.2 TeV</td><td>1.92 × 10<sup>26</sup></td><td>≈190</td><td>2018-04-12-25 / 58220-58233</td><td>(7.58 ± 3.50) × 10<sup>-16</sup></td><td>1.32 ± 0.61</td><td>2.4.2.</td></tr></tbody></table>

Notes. (a) Spatial scale of the source emission (FWHM of the instrumental beam or PSF). Besides the EHT observation for other radio observations if the core is not resolved we use the flux peak obtained from the beam size as an upper limit on the core emission. For elliptical beams, we list the average of the axes as a representative angular scale. At higher energies, the scale typically corresponds to the PSF within a given band or the diameter of the region used for data extraction.
<table><caption>**Table D.1.** Fractional variability of the VHE γ-ray and X-ray bands during the observational campaign in March 2018. For comparison, we also show $F_{var}$ for the same bands in 2017. The calculation of $F_{var}$ of the total flux in 2018 could not be performed because the calculated sample variance was smaller than the measurement uncertainties.</caption><thead><tr><th rowspan="2">Year</th><th rowspan="2">VHE γ-rays</th><th colspan="2">F<sub>var</sub> in band</th></tr><tr><th>Swift-XRT total<br>(2–10 keV)</th><th>Swift-XRT core + HST-1 + jet<br>(2–10 keV)</th></tr></thead><tbody><tr><td>2017</td><td>0.34 ± 0.41</td><td>0.06 ± 0.05</td><td>0.39 ± 0.05</td></tr><tr><td>2018</td><td>0.17 ± 0.25</td><td>-</td><td>0.26 ± 0.06</td></tr></tbody></table>

## Appendix D: Multi-wavelength light curve variability

We estimate the degree of variability in different wavebands by calculating the fractional variability $F_{var}$ from Eq. (10) in Vaughan et al. (2003):

$$F_{\text{var}} = \sqrt{\frac{S^2 - \sigma_{\text{err}}^2}{\bar{x}^2}} \qquad (\text{D.1})$$

where $S^2 = \frac{1}{N-1} \sum_{i=1}^{N} (x_i - \bar{x})^2$ is the sample variance where $\bar{x}$ is the arithmetic mean of the flux measurements $x_i$ and $\sigma_{\text{err}}^2 = \frac{1}{N} \sum_{i=1}^{N} \sigma_{\text{err},i}^2$ the mean squared measurement uncertainty. The uncertainties of $F_{var}$ are calculated following Poutanen et al. (2008) as:

$$\Delta F_{\text{var}} = \sqrt{F_{\text{var}}^2 + \text{err}(\sigma_{\text{NXS}}^2)} - F_{\text{var}} \qquad (\text{D.2})$$

$$\text{err}(\sigma_{\text{NXS}}^2) = \sqrt{\left(\sqrt{\frac{2}{N}\frac{\sigma_{\text{err}}^2}{\bar{x}^2}}\right)^2 + \left(\sqrt{\frac{\sigma_{\text{err}}^2}{N}\frac{2F_{\text{var}}}{\bar{x}^2}}\right)^2}. \qquad (\text{D.3})$$

We present the calculated values of $F_{var}$ for the 2018 observational campaign in Table D.1 and also show the same values of $F_{var}$ during the 2017 campaign (M87 MWL2017). As described in Sect. 2.4.2 the observed VHE flare has a time variability scale $\mathcal{O}(1$ day). Therefore, following the Nyquist-Shannon sampling theorem (Whittaker 1915), flux points closer than 0.5 days are combined using their weighted average value. To be able to compare the fractional variabilities of different bands it is necessary to only select simultaneous data. Therefore, we can only compare the fractional variability of the VHE γ-ray instruments and Swift-XRT listed in Table D.1.