Euclid Data Release 1 (DR1) Euclid photometric masks

Introduction

The Euclid satellite mission (Euclid Collaboration: Mellier et al. [19]), launched in July 2023, aims to constrain the main cosmological parameters through two primary cosmological probes: gravitational lensing and galaxy clustering ([8, 12]). To this end, it will collect data over the $14\,000$ deg$^2$ Euclid Wide Survey (EWS) and the approximately $63$ deg$^2$ Euclid Deep Survey (EDS; Euclid Collaboration: Scaramella et al. [22]).¹

Euclid has two instruments (Euclid Collaboration: Scaramella et al. [22]): the Visible instrument (VIS, Euclid Collaboration: Cropper et al. [14]) and the Near Infrared Spectrometer and Photometer (NISP, Euclid Collaboration: Jahnke et al. [16]). VIS was designed to provide exquisite imaging in the optical domain for galaxy detection and shear measurements. It consists of a single visible band, $I_{\mathrm{E}}$. NISP provides photometric imaging in three bands, $Y_{\mathrm{E}}$, $J_{\mathrm{E}}$, and $H_{\mathrm{E}}$, for detecting distant galaxies, as well as spectroscopic redshifts for galaxy clustering. The Euclid data are combined with external data (referred to as ‘EXT’, see Euclid Collaboration: Corcho-Caballero et al. [13], for more details) from ground-based photometric surveys such as the Dark Energy Survey (DES, Abbott et al. [6]), the Canada-France Imaging Survey (CFIS, Ibata et al. [2]), the Panoramic Survey Telescope and Rapid Response System on Maui (Pan-STARRS, Magnier et al. [3]), the Waterloo-Hawai’i-IfA G-band Survey (WHIGS), and the Wide Imaging with Subaru HSC of the Euclid Sky (WISHES, Aihara et al. [7]) to

determine photometric redshifts for all VIS- and NISP-detected objects (Euclid Collaboration: Hartley et al. [15]).

The processing of Euclid data (see Euclid Collaboration: Ruffenach et al. [21], for a detailed description) is organised within the Euclid Science Ground Segment (SGS) into pipelines and processing functions (PFs). Each PF is developed and maintained by a corresponding Organisational Unit (OU) within the SGS. This paper describes the OU-LE3 (Organizational Unit Level 3) VMPZ-ID (Visibility Mask PhotoZ-Internal Data) PF (Processing Function) and associated pipelines contributing to the core products of Euclid Data Release 1 (DR1 Euclid Data Release 1 [24]), also known as DR1 Foundation. An overview of the DR1 Foundation products is given in Euclid Collaboration: Aussel et al. [11]. The DR1 sky survey (Euclid Collaboration: Tereno et al. [23]) comprises about $2000$ deg$^2$ of the EWS and the three EDS subfields: Euclid Deep Field Fornax (EDF-F), South (EDF-S), and North (EDF-N). Some Euclid Auxiliary Fields and calibration fields are also released.

The main VMPZ-ID products are HEALPix² sky maps, which are called photometric masks hereafter, tracking spatial variations in the properties of the Euclid survey, the instrumental performance of VIS and NISP, the quality of EXT data, and foreground sky emission. These variations could propagate into the final Euclid catalogues and bias the estimation of cosmological parameters, as reported for other photometric surveys, such as KiDS and DES (see Weverderyck et al. 2026; Yan et al. [5], and references therein). These masks will be also useful in selecting Euclid galaxy samples for statistical studies in non-cosmological analyses.

The main inputs to the VMPZ-ID PF are merged sky images and associated RMS noise and flags (see Euclid Collaboration: Kümmel et al. [18], for further description). Star catalogues and star polygons including the central diffraction lobe and diffraction spikes, which are constructed from the Gaia survey, are also used (Gaia Collaboration et al. [25]).

This document is structured as follows. § 2 presents the VMPZ-ID pipeline and the products delivered in DR1. § 3 details the VMPZ-ID photometric masks, § 4 discusses the main EWS photometric masks, and § 5 describes the masks for the EDFs. Conclusions are presented in § 6.

VMPZ-ID pipeline and products

The DR1 VMPZ-ID pipeline is based on the Q1 pipeline described in Euclid Collaboration: Aussel et al. [10] and has since been improved and extended to include additional sky masks. Information associated to the VIS, NIR, and EXT MER (MERge processing, Euclid Collaboration: Kümmel et al. [18]) images at exposure (e.g. integration time, star polygons, satellite position angles, PSF width) and tile (e.g. image footprint, mask flags and noise) levels is combined into a series of masks in the HEALPix format using nested ordering, explicit indexing and $N_{\mathrm{side}} = 16\,384$, which corresponds to a resolution of approximately $12^{\prime\prime}88$. This resolution was selected as a good compromise between usability, allowing for loading an all-sky mask in the memory of a Euclid Science Data Centre node, and preserving as much as possible of the fine spatial information given by the pixel scale masks of the original MER images (Euclid Collaboration: Kümmel et al. [18]).

VMPZ-ID also produces, at the same resolution, the so-called DpdHealpixInfoMapVMPZ product, which enables satellite and instrumental properties to be tracked and projected onto the sky. This allows straightforward cross-checks between spatial information (for example, the noise at a given point in the survey) and temporal information (for example, the value of a temperature sensor on the Euclid focal plane), and facilitates searches for possible effects on Euclid performance. Finally, random galaxy catalogues are also produced to mimic spatial variations in the combined coverage of all bands used for photometry.

Pipeline

VMPZ-ID is the first OU-LE3 PF to be executed after OU-LE2 processing (Euclid Collaboration: Ruffenach et al. [21]). The photometric masks are constructed from MER data products and Gaia cutouts (Euclid Collaboration: Kümmel et al. [18]) at the tile (see tessellation scheme in Euclid Collaboration: Scaramella et al. [22]) level using two main pipelines named VMPZ_Star_Pipeline and VMPZ_Mosaic_Pipeline. These two pipelines are triggered by the operations team, as described in Euclid Collaboration: Ruffenach et al. [21], as soon as the MER (see Euclid Collaboration: Kümmel et al. [18], for details) data products are available for a given tile. The VMPZ_Star_Pipeline mainly produces masks related to properties of the stellar distribution on the sky. The VMPZ_Mosaic_Pipeline handles survey, satellite, instrumental and sky properties.

Main data products

The main products of the VMPZ_Star_Pipeline and VMPZ_Mosaic_Pipeline pipelines consist of the following six main types of photometric masks and a random catalogue.

• DpdHealpixFootprintMaskVMPZ: integer values, equal to 1 if the sky region has been observed and 0 otherwise. For DR1, instances have been produced for the Euclid bands, $I_{\mathrm{E}}$, $J_{\mathrm{E}}$, $H_{\mathrm{E}}$, and $Y_{\mathrm{E}}$, and for all available external bands (Euclid Collaboration: Corcho-Caballero et al. [13]).

• DpdHealpixCoverageVMPZ: float values between 0 and 1, representing the coverage, i.e., the fraction of HEALPix pixels covered by the available valid data for each of the Euclid and EXT bands, as for DpdHealpixFootprintMaskVMPZ.

• DpdHealpixEffectiveCoverageVMPZ: float values between 0 and 1, representing the effective coverage, i.e., the fraction of HEALPix pixels covered by valid data combining the Euclid and EXT bands.

• DpdHealpixBitMaskVMPZ: unsigned integer values whose bits are associated with the flags of the MerBksMosaic (see Euclid Collaboration: Kümmel et al. [18], for details).

• DpdHealpixDepthMapVMPZ: float values representing the RMS-derived depth for each Euclid and EXT band.

• DpdHealpixInfoMapVMPZ: float values representing different quantities of interest. To discriminate between the masks associated to different physical quantities we define the so-called InfoMap type as described in § 3 and Table 1.

Mask name	Mask family	Mask product type	Information map type	Numerical type	Units	Per-band mask
Tile index	Survey	DpdHealpixInfoMapVMPZ	Tile	int64	...	no
Solar aspect angle	Survey/Satellite	DpdHealpixInfoMapVMPZ	SAA	float32	deg	no
Alpha angle	Survey/Satellite	DpdHealpixInfoMapVMPZ	AA	float32	deg	no
Beta angle	Survey/Satellite	DpdHealpixInfoMapVMPZ	BA	float32	deg	no
Integration time	Survey	DpdHealpixInfoMapVMPZ	Exposures	float32	sec	Euclid only
Footprint	Survey/Instrument	DpdHealpixFootprintMaskVMPZ	...	float32	...	yes
Coverage	Survey/Instrument	DpdHealpixCoverageMaskVMPZ	...	float32	...	yes
Effective coverage	Survey/Instrument	DpdHealpixEffectiveCoverageMaskVMPZ	...	float32	...	combined
Bit mask	Instrument	DpdHealpixBitMaskVMPZ	...	uint32	...	yes
Depth	Instrument	DpdHealpixDepthMapVMPZ	...	float32	AB mag	yes
RMS noise	Instrument	DpdHealpixInfoMapVMPZ	Noise	float32	ADU	yes
Point-spread function	Instrument	DpdHealpixInfoMapVMPZ	PSF	float32	arcsec	yes
Persistence	Instrument	DpdHealpixInfoMapVMPZ	Persistence	float32	...	NIR only
NIR PRMS	Instrument	DpdHealpixInfoMapVMPZ	NIR_PRMS	float32	mas	NIR only
Pan-STARRS artefacts	Instrument	DpdHealpixInfoMapVMPZ	PanStarrsArtefacts	float32	...	Pan-STARRS only
Zodiacal light	Sky/Instrument	DpdHealpixInfoMapVMPZ	ZodiacalLight	float32	erg cm$^{-2}$ Å arcsec$^{-2}$	Euclid only
Galactic extinction	Sky/Instrument	DpdHealpixInfoMapVMPZ	GalacticExtinction	float32	mag	Euclid only
Star number density	Sky emission	DpdHealpixInfoMapVMPZ	StarNumberDensity	float32	counts/pixel	no
Star mean flux	Sky emission	DpdHealpixInfoMapVMPZ	StarBrightnessMean	float32	e$^{-}$/s	Gaia G
Star RMS flux	Sky emission	DpdHealpixInfoMapVMPZ	StarBrightnessRms	float32	e$^{-}$/s	Gaia G
Star std flux	Sky emission	DpdHealpixInfoMapVMPZ	StarBrightnessStd	float32	e$^{-}$/s	Gaia G

• DpdHealpixRandomCatalogueVMPZ: generic container for storing simulated galaxy catalogues.

Detailed mask description

The VMPZ-ID pipelines have produced 104 photometric masks for DR1. Table 1 summarises the main properties of these masks. A more detailed description of each mask is given below. We warn the reader that these masks present in some cases redundant or correlated information.

Survey-definition masks and random catalogues

The main masks accounting for the Euclid survey coverage and the spatial distribution of the EXT data are presented here.

• Tile index: for each HEALPix pixel, it encodes the number of the MER tile on which it lies. This is stored as a DpdHealpixInfoMapVMPZ product with information map type Tile. Tile numbers are given as signed 64-bit integers.

• Footprint: defines the observed or valid sky area. This is stored as a DpdHealpixFootprintMaskVMPZ product with a weight of 1 for valid HEALPix pixels. It is available for the Euclid and EXT bands. The mask is constructed from the MerBksMosaic maps, with observed sky regions set to 1 and the others to 0. Additional flagging at the MER processing level, encoded in the MerBksMosaic RMS maps, is also taken into account. MER tile pixels with zero RMS or above a given fixed threshold, $\sigma_{\mathrm{thresh}} = 10\,000$ ADU, are considered unobserved and treated accordingly when

computing the footprint. Finally, all MER tile pixels lying within a HEALPix pixel are combined using a logical OR operator.

– Coverage: determines the relative coverage, float number between 0 and 1, for each HealPix pixel and for each Euclid and EXT band. The coverage per band (Euclid and EXT) is calculated from the MerBksMosaic maps. MER tile pixels for which the RMS value is zero or exceeds $\sigma_{\mathrm{thresh}}$ are considered unobserved. Furthermore, for the Euclid bands, polygonal masks are used to exclude sky regions affected by bright-star emission. For each HEALPix pixel, the coverage is given by the fraction of valid MER tile pixels.

– Effective coverage: defines the fraction of sky simultaneously observed in all photometric bands. An initial effective coverage mask is constructed at the MER mosaic resolution (19 200 × 19 200 pixels), before projection onto the HEALPix grid. As defined the initial effective coverage mask is binary (either 0 or 1) while the HEALPix one can have float values between 0 and 1. In this initial mask, for each available VIS, NIR, or EXT band, MER tile pixels for which the RMS value is zero or above $\sigma_{\mathrm{thresh}}$ are considered unobserved. In some cases, multiple EXT data sets in equivalent photometric bands (e.g. HSC $R$, HSC $R2$, HSC $I$, HSC $I2) are used to cover the same sky. To handle this, effective EXT bands are defined; for each of them, multiple input data sets are available, and their validity masks are first combined using a logical OR operator. The masks from the different effective bands are then combined using a logical AND operator, thereby retaining only regions observed in all effective bands.

Regions affected by bright stars are subsequently excluded. For the $I_{\mathrm{E}}$, $Y_{\mathrm{E}}$, $J_{\mathrm{E}}$, and $H_{\mathrm{E}}$ bands, when stellar polygons describing stellar lobes and diffraction spikes are available, they are directly rasterised onto the initial MER effective coverage grid. For the EXT data, an additional mask is constructed using Gaia star catalogues. Stars with magnitude in the $G$ red band $G_{\mathrm{RP}} < 14$ are masked³ with circular regions whose radii, expressed in arcmin, follow the empirical relation (see left panel of Figure 1)

The resulting radii are enlarged by 20% when constructing the circular masks to minimise the number of spurious detections while preserving galaxy counts in the final Euclid catalogues. Bleeding trails (see [9 for a discussion]) are additionally masked for stars with $G_{\mathrm{RP}} < 10.3; their width is described by the empirical polynomial (see Figure 1b)

with the polynomial value saturated at $G_{\mathrm{RP}} = 4$ for the brightest stars. The resulting rectangular masks have a magnitude-dependent total angular width of $2r_{\mathrm{bleed}}$ and a fixed extent of 0.488 in the perpendicular direction to the bleed.

A pre-selected set of extended objects is also masked. This set comprises globular clusters and planetary nebulae from the New General Catalogue⁴ (NGC) and nearby galaxies from the Siena Galaxy Atlas⁵ (SGA). NGC objects are masked using their radii, while SGA galaxies with an approximate Vega magnitude of MAG_LEDA < 16.5 are masked using elliptical regions bleeding on their major and minor axes and position angles, with their dimensions enlarged by 30%. The resulting initial effective coverage mask is projected and averaged onto an $N_{\mathrm{side}} = 16\,384$ HEALPix grid to produce the final effective coverage mask. This mask is saved as a DpdHealpixEffectiveCoverageMaskVMPZ product. Additionally, the initial effective coverage mask is used to construct a flag called EFF_COV for each object in the DpdMerFinalCatalog. This flag is 1 if the object position⁶ lies on a pixel with non-zero initial effective coverage, and 0 otherwise. This flag is stored in the second extension of the effective coverage FITS⁷ file.

– Random catalogues: random galaxy catalogues are generated from a uniform distribution weighted at each position by the effective coverage value. The positions of the simulated galaxies (RA and Dec) are stored as tables in DpdHealpixRandomCatalogueVMPZ products for each tile. Figure 2 shows an example of a random catalogue.

Survey-related masks

Masks related to the satellite’s position and integration time during operations are presented here.

– Solar aspect angle: defines the Euclid satellite solar aspect angle in degrees as described in Euclid Collaboration: Scaramella et al. [22]. This is stored in a DpdHealpixInfoMapVMPZ information map of type SAA. It is computed from the MER layering files, which contain both the integration time and the satellite angles for each exposure. The final mask is obtained by computing the exposure-time-weighted mean value for each HEALPix pixel.

– Alpha/beta angles: defines the Euclid satellite Alpha and Beta angles in degrees (Euclid Collaboration: Scaramella et al. [22]). Both are computed and stored like SAA, using information map types AA and BA, respectively.

– Exposures: for each of the Euclid bands, this represents the total integration time in seconds per HEALPix pixel and is calculated from the MER layering files described above. This is stored as a DpdHealpixInfoMapVMPZ product.

Instrumental-property masks

For each of the Euclid and EXT bands, masks of the main instrumental properties are obtained from the MerBksMosaic maps. For each HEALPix pixel, the weighted average of the instrumental properties is computed. As for the previously described masks, zero weight is assigned to MER tile pixels with RMS equal to zero or above a given threshold representing bad or corrupted data.

– RMS noise: represents the average root mean square (RMS) noise of the Euclid and EXT images. This is computed from the MerBksMosaic RMS noise maps in ADU units, which are averaged and projected onto HEALPix maps. The resulting maps are stored as DpdHealpixInfoMapVMPZ products of information map type Noise. For unobserved regions, the RMS noise value is set to zero.

– Depth: represents the average depth at each sky position and is stored as DpdHealpixDepthMapVMPZ products. This is computed from the Euclid and EXT MerBksMosaic RMS maps according to the following definition:

where RMS and ZP are the RMS noise value and photometric zero point, respectively, as defined in the MerBksMosaic maps. The detection threshold, $d_{\mathrm{thresh}}$, is set to 5, corresponding to a 5 $\sigma$ detection, while $A_{\mathrm{aper}}$ and $A_{\mathrm{pixel}}$ represent the detection aperture and pixel areas, respectively. A 2″-diameter aperture is used to compute the depth.

– PSF FWHM: defines the average full width at half maximum (FWHM), in arcsec, at each sky position for the Euclid and EXT bands. This is stored in a DpdHealpixInfoMapVMPZ product of information map type PSF. For the MerBksMosaic maps, FWHM estimates are available only at the positions of bright stars in the tile field. A two-pass 2D interpolation (cubic spline then nearest-neighbour on the remaining not sampled areas) is therefore performed across the tile area, starting from a sufficiently coarse grid to avoid artefacts in the final derived mask.

– Bit mask: is an effective bit mask stored as a DpdHealpixBitMaskVMPZ product. For each HEALPix pixel in the final mask, it is computed by applying a bitwise OR operation to the Bit-mask values of all MerBksMosaic pixels falling within it. The meaning of the different bits is described in the MER data model presented in Euclid Collaboration: Kümmel et al. [18].

– Persistence: reflects the overall contamination of the NIR photometric data by persistence (see Euclid Collaboration: Kubik et al. [17], for a detailed description of persistence effects) at each sky position. This is stored as a DpdHealpixInfoMapVMPZ product with information map type Persistence. The HEALPix persistence mask is derived from bit 13 of the MerBksMosaic bit mask, which flags regions severely affected by persistence. It ranges from 0 to 1 and gives the fraction of each HEALPix pixel affected by persistence, but does not provide information on the level of persistence.

• NIR PRMS: represents the maximum RMS offset in milliarcseconds (mas) of the NIR stack astrometric residuals. The maximum RMS offset is computed for each stacked catalogue generated for a specific observation ID at a resolution of about 30″, following the procedure described in Euclid Collaboration: Radovich et al. [20]. The maps for all observation IDs corresponding to the EWS are then projected and averaged onto a common HEALPix grid. The resulting mask is stored as a DpdHealpixInfoMapVMPZ product with information map type NIR_PRMS.

• Pan-STARRS artefacts: defines regions in the Pan-STARRS i-band EXT images (see Euclid Collaboration: Corcho-Caballero et al. [13]) that are affected by systematic effects. This is stored as a DpdHealpixInfoMapVMPZ product with information map type PanStarrsArtefacts. The mask is built from the MER final catalogues (see Euclid Collaboration: Kümmel et al. [18]) by selecting sources with anomalous Pan-STARRS/VIS flux ratios, defined by default as $F_{\mathrm{PS}}/F_{\mathrm{VIS}} > 3.5$ or $F_{\mathrm{PS}}/F_{\mathrm{VIS}} < 1/3.5$, and requiring a flux-ratio signal-to-noise $> 3$. Their spatial distribution is smoothed with an Epanechnikov kernel density estimator⁸ (KDE) with a 30″ bandwidth, evaluated on a regular 10″ RA–Dec grid. An adaptive density threshold derived from the KDE value distribution defines candidate contaminated regions, after which connected regions smaller than 30 grid pixels are discarded. The resulting binary mask is then projected onto a HEALPix grid, recording whether each HEALPix pixel is masked. This results into a binary mask.

Sky emission masks

Following the models presented in Euclid Collaboration: Scaramella et al. [22], per-tile masks of zodiacal light emission and Galactic extinction are constructed for the Euclid bands.

• Galactic extinction: defines, for each sky position, the total extinction in magnitudes for each of the Euclid bands, as defined in equation 5 of Euclid Collaboration: Scaramella et al. [22]. This is stored as a DpdHealpixInfoMapVMPZ product with information map type GalacticExtinction.

• Zodiacal light: gives, for each sky position, the zodiacal light flux for each Euclid band normalised by the effective wavelength of the band, $F/\lambda_{\mathrm{eff}}$, as defined in table 4 of Euclid Collaboration: Scaramella et al. [22]. This is stored as a DpdHealpixInfoMapVMPZ product with information map type ZodiacalLight.

Star masks

The masks monitoring stellar density and flux across the sky are presented here. They are built by the VMPZ_Star_Pipeline using the DpdExtGaiaCutout products, which contain a reduced Gaia star catalogue for each tile. Only stars with a Gaia G-band flux above zero and a valid parallax angle are considered.

• Star number density: represents the number density of stars in each HEALPix pixel. This is stored as a DpdHealpixInfoMapVMPZ product with information map type StarNumberDensity.

• Mean star brightness: provides the mean flux of all stars lying within a given HEALPix pixel. This is stored as a DpdHealpixInfoMapVMPZ product with information map type StarBrightnessMean.

• Star brightness RMS: provides the RMS flux of all stars lying within a given HEALPix pixel. This is stored as a DpdHealpixInfoMapVMPZ product with information map type StarBrightnessRms.

• Star brightness standard deviation: provides the standard deviation of the flux of all stars lying within a given HEALPix pixel. this is stored as a DpdHealpixInfoMapVMPZ product with information map type StarBrightnessStd.

Examples for most of the masks are given in Appendix § 8 and are discussed in Sect. 4.2.

EWS masks

Full survey masks

A subset of the DR1 EWS masks is shown in full-sky orthographic projection in Figure 3, including the North (left hemisphere) and South (right hemisphere) regions. The effective coverage, presented in Figure 3 (a), is crucial for scientific analyses to account for variations in sky coverage. Overall, the effective coverage is close to 1 (full coverage), except in regions around stars and near the edges of the coverage (see Figure 2), which appear as blue dots in the figure. This is also clearly illustrated in Figure 4, which displays the integrated coverage weighted area as a function of minimum selected coverage. The expected total area of the DR1 EWS is 2008.8 deg$^2$ (computed from the sum of the area of the regions for which we have one VIS exposure), of which 1642.4 deg$^2$ is preserved by the effective coverage mask. This effective area is obtained by summing the WEIGHT values in the effective coverage mask, multiplied by the HEALPix pixel area. Figure 3 also shows that the effective area for pixels with effective coverage above 0.8 corresponds to about 99% of the total effective area presented above. The orientation angles of the Euclid satellite are shown in Figure 3 (b), (c), and (d). As expected, they are all within survey specifications. Moreover, the beta angle and the solar aspect angle are anti-correlated.

Figure 3 (e) shows that the VIS ($I_{\mathrm{E}}$ band) integration time is highly uniform across the survey, with only weak large-scale variations. This uniformity is expected from the survey design, such that most of the survey area is covered by 3- or 4-single-dither exposure (Euclid Collaboration: Tereno et al. [23]). Table 2 shows that the typical integration time values in the EWS are about 2735 and 338 s for the VIS and NISP instruments, respectively. As a consequence, the VIS $I_{\mathrm{E}}$ RMS noise and depth masks also show small spatial variations across the survey. Similar conclusions can be drawn for the NISP bands. The left panel of Figure 5 shows that the noise decreases as expected with increasing integration time. The 1D distribution of depth for the four Euclid bands is shown in the middle panel of Figure 5. The distributions have narrow, well-defined peaks, with median depth values of 25.69, 24.14, 24.3, and 24.29 AB mag for the $I_{\mathrm{E}}$, $Y_{\mathrm{E}}$, $J_{\mathrm{E}}$ and $H_{\mathrm{E}}$ bands, respectively. The standard deviation is below 0.2 AB mag for all bands. A more detailed statistical description of the EWS RMS noise and depth distributions is also given in Table 2.

Band	Quantity	Mean	Median	Std	$Q_{16}$	$Q_{25}$	$Q_{75}$	$Q_{84}$	IQR$^{a}$
$I_{\mathrm{E}}$	Exposures [s]	2735	2421	922	1861	2332	3071	3632	740
	Noise [ADU]	0.003882	0.003716	0.001423	0.003238	0.003421	0.004085	0.004239	0.0006632
	Depth [AB mag]	25.68	25.69	0.224	25.56	25.59	25.78	25.84	0.186
	PSF FWHM [arcsec]	0.2029	0.2028	0.004051	0.1991	0.2004	0.2053	0.2066	0.004964
$Y_{\mathrm{E}}$	Exposures [s]	338	349	117	262	262	349	436	87
	Noise [ADU]	2.089	2.077	0.4039	1.794	1.867	2.253	2.333	0.3855
	Depth [AB mag]	24.15	24.14	0.1699	24.01	24.05	24.25	24.3	0.2038
	PSF FWHM [arcsec]	0.4879	0.4883	0.01016	0.4791	0.4825	0.4939	0.4968	0.01142
$J_{\mathrm{E}}$	Exposures [s]	338	349	118	262	262	349	436	87
	Noise [ADU]	2.393	2.379	0.4584	2.057	2.139	2.574	2.67	0.4349
	Depth [AB mag]	24.3	24.29	0.1717	24.16	24.2	24.41	24.45	0.2009
	PSF FWHM [arcsec]	0.5138	0.5143	0.01071	0.5045	0.5081	0.5201	0.5232	0.01206
$H_{\mathrm{E}}$	Exposures [s]	339	349	117	262	262	349	436	87
	Noise [ADU]	2.194	2.183	0.4215	1.887	1.963	2.364	2.45	0.4013
	Depth [AB mag]	24.29	24.28	0.1704	24.16	24.2	24.4	24.44	0.202
	PSF FWHM [arcsec]	0.5589	0.5593	0.009184	0.5512	0.5542	0.5642	0.5666	0.009917

The EWS VIS PSF FWHM mask, which represents the VIS PSF FWHM, is shown in Figure 3 (h). A very uniform spatial distribution is again observed. Similar results are obtained for the NISP bands. A statistical description of the 1D distribution of the PSF FWHM for the VIS and NISP bands is also given in Table 2. The median FWHM values are 0″.2, 0″.48, 0″.51, and 0″.56 for the $I_{\mathrm{E}}$, $Y_{\mathrm{E}}$, $J_{\mathrm{E}}$, and $H_{\mathrm{E}}$ bands, respectively. The standard deviation of the spatial variation is below 0″.01.

High-resolution view

Additional examples of the EWS masks are presented in Appendix § 8 for observation Path ID 4. Figure A.1 shows the main survey masks, including the tile index, alpha angle, beta angle, solar aspect angle, and integration time for the four Euclid bands. The latter shows clear spatial patterns corresponding mainly to longer integration time in the overlap regions between adjacent tiles. These patterns are also reflected in the RMS noise and depth maps, as shown in Fig. A.3. This figure also presents the PSF FWHM, NIR PRMS, and persistence masks. The measured FWHM is larger in tile-overlap regions, where multiple exposures are combined. The NIR PRMS mask also shows these spatial variations with smaller NIR pointing RMS residuals in the overlapping regions. The persistence mask additionally exhibits tile-correlated structures, although they are less distinct and more difficult to interpret.

Finally, Fig. A.4 presents the main sky emission masks, including Galactic extinction, zodiacal light, star number density, mean star brightness, star brightness RMS, and star brightness standard deviation. Regions with larger stellar number density and mean brightness correspond to regions flagged on the effective coverage mask presented in Fig. A.3. This figure also shows the expected correlation between persistence and bright-star positions.

EDF masks

Figure 6 presents examples of the main VMPZ-ID photometric masks in the EDF-F (left panel), EDF-N (middle panel), and EDF-S (right panel). The effective coverage masks clearly show fully masked regions (dark blue in the figure) due to star contamination, as discussed in previous sections. The integrated coverage weighted area is shown in the top panels of Figure 7 for the three EDFs. Following the discussion in Sect. 4.1, the total (effective) observed area is 13.2 (11.8), 28.5 (21.1), and 33.0 (27.9) deg$^2$ for the EDF-F, EDF-N, and EDF-S, respectively. Thus, the effective coverage mask preserves 89.3, 74.0, and 84.5% of this area. Furthermore, 75, 72, and 92% of the preserved regions have effective coverage greater than 0.8.

Figure 6 also shows that the $I_{\mathrm{E}}$ integration time has small spatial variations for EDF-N and EDF-S, while more significant structure is observed for EDF-F. This can be explained by the

Notes. $^{(a)}$ Interquartile range $\equiv Q_{75} - Q_{25}$.

significantly larger number of exposures and multiple exposure angles in EDF-N and EDF-S compared with EDF-F. A similar behaviour is observed for the $I_{\mathrm{E}}$ and $H_{\mathrm{E}}$ depth masks. This is also visible in the bottom panel of Figure 7, where the 1D depth distributions are shown for the four Euclid bands and the three EDFs. A detailed statistical description of these distributions is given in Tables B.1, B.2, and B.3. The median $I_{\mathrm{E}}$ depth (integration time) values in AB mag (seconds) are 25.93 (4842), 26.91 (25 330), and 26.85 (23 560) for EDF-F, EDF-N, and EDF-S, respectively. These values are consistent with the corresponding numbers of visits, namely 2, 11, and 10 ([23]).

Summary and conclusions

In this paper, a series of photometric masks has been presented in the form of HEALPix maps at a resolution of $N_{\mathrm{side}} = 16\,384$ for each tile of the DR1 EWS and EDS. These masks were built using the OU-LE3 VMPZ-ID PF and pipelines within the Eu-

clid SGS. They represent spatial variations in the observational properties across the DR1 survey (integration time and satellite position angles), the instrumental properties for the Euclid and EXT bands (coverage, instrumental noise and depth, PSF width, systematic flags, NIR persistence, and astrometric uncertainties), foreground sky emission (Galactic extinction and zodiacal light), and the stellar distribution (star number density and star flux properties).

A mask representing the overall effective coverage of DR1 and combining information from the Euclid and EXT bands is also provided. This mask also accounts for bright-star contamination, including diffraction spikes and bleeding effects in the Euclid and EXT images. Overall, the effective coverage mask reduces the available area by 18.1% in the DR1 EWS and by 11 to 26% in the EDFs. Nevertheless, the effective coverage mask should be used to avoid spurious objects and artefacts in the data when selecting Euclid DR1 photometric galaxy samples for scientific analyses.

The instrumental performance in the VIS and NISP photometric bands is very stable across the survey. Spatial variations in instrumental RMS noise are strongly correlated with integration time, as expected. For the DR1 EWS, the standard deviation of depth (for a 2″ aperture) is below 0.2 AB mag, with median values of 25.69, 24.14, 24.3, and 24.29 for the $I_{\mathrm{E}}$, $Y_{\mathrm{E}}$, $J_{\mathrm{E}}$, and $H_{\mathrm{E}}$ bands, respectively. Furthermore, the spatial standard deviations of the PSF FWHM are of the order of 0″.01, with median values of 0″.2, 0″.48, 0″.51, and 0″.56 for the $I_{\mathrm{E}}$, $Y_{\mathrm{E}}$, $J_{\mathrm{E}}$, and $H_{\mathrm{E}}$ bands, respectively. At small angular scales, however, some structured patterns in integration time are observed.

For the DR1 EDS, multiple visits at different observation angles tend to smooth out spatial variations in the instrumental properties, particularly in EDF-N and EDF-S. Median depth values of 26.91, 25.30, 25.44, and 25.45 are achieved for the $I_{\mathrm{E}}$, $Y_{\mathrm{E}}$, $J_{\mathrm{E}}$, and $H_{\mathrm{E}}$ bands, respectively. The standard deviation of depth is below 0.16, 0.44, and 0.40 AB mag for EDF-F, EDF-N, and EDF-S, respectively.

The VMPZ-ID photometric masks will be particularly relevant for forthcoming Euclid photometric astrophysical and cosmological analyses. They will be key for monitoring and correcting potential systematic spatial variations in galaxy number density, which could otherwise bias important derived quantities, such as cosmological parameter estimates.

Acknowledgements

Acknowledgements. The Euclid Consortium acknowledges the European Space Agency and a number of agencies and institutes that have supported the development of Euclid, in particular the Agenzia Spaziale Italiana, the Austrian Forschungsförderungsgesellschaft funded through BMIMI, the Belgian Science Policy, the Canadian Euclid Consortium, the Deutsches Zentrum für Luft- und Raumfahrt, the DTU Space and the Niels Bohr Institute in Denmark, the French Centre National d’Etudes Spatiales, the Fundação para a Ciência e a Tecnologia, the Hungarian Academy of Sciences, the Ministerio de Ciencia, Innovación y Universidades, the National Aeronautics and Space Administration, the National Astronomical Observatory of Japan, the Nederlandse Onderzoekschool Voor Astronomie, the Norwegian Space Agency, the Research Council of Finland, the Romanian Space Agency, the Swiss Space Office (SSO) at the State Secretariat for Education, Research, and Innovation (SERI), and the United Kingdom Space Agency. A complete and detailed list is available on the Euclid web site (www.euclid-ec.org/consortium/community/). This work has made use of the Euclid Data Release 1 (DR1) from the European Space Agency (ESA) mission Euclid, available at https://www.cosmos.esa.int/web/euclid/data-release-dr1.

Authors and affiliations

Euclid Collaboration: J. Odier^⋆,1, J. F. Macias-Perez¹, G. Alguero¹, C. Benoist², M. Radovich³, P. Corcho-Caballero⁴, H. Aussel⁵, P. Casenove⁶, M. Ruffenach⁶, S. Farrens⁵, B. Kubik⁷, M. Kümmel⁸, S. Andreon⁹, C. Baccigalupi^{10, 11, 12, 13}, M. Baldi^{14, 15, 16}, A. Balestra³, S. Bardelli¹⁵, P. Battaglia¹⁵, A. Biviano^{11, 10}, M. Bolzonella¹⁵, E. Branchini^{17, 18, 9}, M. Brescia^{19, 20}, J. Brinchmann^{21, 22, 23}, S. Camera^{24, 25, 26}, G. Cañas-Herrera²⁷, V. Capobianco²⁶, C. Carbone²⁸, F. J. Castander^{29, 30}, M. Castellano³¹, G. Castignani¹⁵, S. Cavuoti^{20, 32}, A. Cimatti³³, G. Congedo³⁴, L. Conversi^{35, 36}, Y. Copin⁷, A. Costille³⁷, M. Cropper³⁸, A. Da Silva^{39, 40}, R. da Silva^{31, 41}, G. De Lucia¹¹, X. Dupac³⁶, S. Escoffier⁴², M. Farina⁴³, R. Farinelli¹⁵, S. Ferriol⁷, S. Fotopoulou⁴⁴, N. Fourmanoit⁴², M. Frailis¹¹, L. Gabarra⁴⁵, S. Galeotta¹¹, K. George⁴⁶, C. Giocoli^{15, 16}, F. Grupp^{47, 8}, L. Guzzo^{48, 9, 49}, W. G. Hartley⁵⁰, S. V. H. Haugan⁵¹, S. Hemmati⁵², H. Hoekstra²⁷, F. Hormuth⁵³, K. Jahnke⁵⁴, M. Jhabvala⁵⁵, S. Kermiche⁴², A. Kiessling⁵⁶, M. Kunz⁵⁷, H. Kurki-Suonio^{58, 59}, P. Liebing³⁸, S. Ligori²⁶, P. B. Lilje⁵¹, I. Lloro⁶⁰, M. Magliocchetti⁴³, O. Marggraf⁶¹, M. Martinelli^{31, 62}, N. Martinet³⁷, R. J. Massey⁶³, N. Mauri^{33, 16}, H. J. McCracken⁶⁴, E. Medinaceli¹⁵, M. Meneghetti^{15, 16}, E. Merlin³, G. Meylan⁶⁵, P. Monaco^{66, 11, 12, 10}, M. Moresco^{67, 15}, L. Moscardini^{67, 15, 16}, R. Nakajima⁶¹, C. Neissner^{68, 69}, R. C. Nichol⁷⁰, S.-M. Niemi⁷¹, C. Padilla⁶⁸, F. Pasian¹¹, J. A. Peacock³⁴, W. J. Percival^{72, 73, 74}, V. Pettorino⁷¹, S. Pires⁵, G. Polenta⁴¹, M. Poncet⁶, L. A. Popa⁷⁵, L. Pozzetti¹⁵, A. Refregier⁷⁶, A. Renzi^{77, 78, 15}, J. Rhodes⁵⁶, G. Riccio²⁰, E. Romelli¹¹, M. Roncarelli¹⁵, B. Rusholme⁵², R. Saglia^{8, 47}, Z. Sakr^{79, 80, 81}, M. Schirmer⁵⁴, P. Schneider⁶¹, A. Secroun⁴², E. Sihvola^{58, 59}, P. Simon⁶¹, C. Sirignano^{77, 78}, G. Sirri¹⁶, J. Skottfelt⁸², L. Stanco⁷⁸, P. Tallada-Crespí^{83, 69}, H. I. Teplitz⁸⁴, I. Tereno^{39, 40}, N. Tessore³⁸, S. Toft^{85, 86}, R. Toledo-Moreo^{87, 88}, I. Tutusaus^{29, 30, 80}, J. Valiviita^{58, 59}, T. Vassallo^{11, 46}, A. Veropalumbo^{9, 18, 17}, Y. Wang⁵², J. Weller^{8, 47}, A. Zacchei^{11, 10}, G. Zamorani¹⁵, F. M. Zerbi⁹, E. Zucca¹⁵, V. Allevato²⁰, M. Ballardini^{89, 90, 15}, S. Borgani^{66, 10, 11, 12, 91}, E. Bozzo⁵⁰, C. Burigana^{92, 93}, M. Calabrese^{94, 28}, F. Caro³¹, T. Castro^{95, 11, 10}, S. Conseil^{96, 7}, D. Di Ferdinando¹⁶, J. A. Escartin Vigo⁴⁷, G. Fabbian⁹⁷, T. Gasparetto³¹, A. Gregorio^{66, 11, 12}, C. M. Gutierrez^{98, 99}, Y. Kang¹⁰⁰, A. Loureiro^{101, 102}, R. Maoli^{103, 31}, R. B. Metcalf^{67, 15}, M. Pöntinen⁵⁸, E. Sarpa¹¹, V. Scottez^{104, 105}, M. Sereno^{15, 16}, K. Tanidis¹⁰⁶, M. Tenti¹⁶, M. Wiesmann⁵¹, Abdurro’uf¹⁰⁷, J. A. Acevedo Barroso⁵⁶, Y. Akrami^{79, 108}, G. Angora^{20, 89}, S. Anselmi^{78, 77, 109}, M. Archidiacono^{48, 49}, G. Aricò¹⁶, F. Atrio-Barandela¹¹⁰, M. Aubert⁷, M. Baes¹¹¹, N. Bartolo^{77, 78, 3}, L. Bazzanini⁹, J. R. Bermejo-Climent^{112, 113}, D. Bertacca^{77, 3, 78}, M. Bethermin¹¹⁴, F. Bouché^{115, 32}, A. Calabro³¹, C. S. Carvahllo¹¹⁶, N. Chartab⁵², C. Cogato¹⁵, T. E. Collett¹¹⁷, M. Comerón^{31, 41}, B. Csizi¹⁰⁰, O. Cucciati¹⁵, T. de Boer¹¹⁸, G. Desprez⁴, A. Díaz-Sánchez¹¹⁹, S. Di Domizio^{17, 18}, V. Duret¹²⁰, A. Enia^{121, 15}, A. Farina^{9, 18}, A. Fontana³¹, A. Franco^{122, 123, 124}, N. Frusciante^{125, 126}, A. Fumagalli¹¹, Y. Fu^{27, 4}, K. Ganga¹²⁷, R. Gavazzi^{37, 64}, E. Gaztanaga^{29, 30, 117}, Z. Ghaffari^{11, 10}, F. Giannotti¹⁵, G. Gozaliasl^{128, 58}, M. Guidi^{14, 15}, H. Hildebrandt¹²⁹, J. Hjorth¹³⁰, D. Karagiannis^{131, 89, 132}, J. Kim⁴⁵, C. C. Kirkpatrick¹³³, A. Kovács^{113, 112}, I. Kovačić¹¹¹, K. Koyama¹¹⁷, S. Kruk³⁶, M. C. Lam³⁴, M. Lembo⁶⁴, M. D. Lepinzan¹¹, L. Linke¹⁰⁰, F. Mannucci¹³⁴, C. J. A. P. Martins^{135, 22}, M. Migliaccio^{136, 137}, M. Miluzio^{36, 138}, E. Moresi¹⁵, K. N. M. Morante¹¹⁷, A. Navarro-Alsina⁶¹, S. Nesseris⁷⁹, L. Nicastro¹⁵, F. Oppizzi^{18, 78, 77}, F. Pace^{24, 25, 26, 40}, M. J. Page³⁸, D. Paoletti^{15, 93}, F. Pasqualacqua⁷⁸, K. Paterson⁵⁴, C. Pattison¹¹⁷, A. Pisani⁴², L. Pizzuti¹³⁹, J. J. Popp¹⁴⁰, D. Potter¹⁴¹, M. Poulain¹⁴², G. W. Pratt⁵, S. Quai^{67, 15}, F. Ricci^{143, 31}, G. Rodighiero^{77, 3}, W. Roster⁴⁷, M. Sahlén¹⁴⁴, D. B. Sanders¹¹⁸, A. Schneider⁴¹, S. Serjeant¹⁴⁰, L. C. Smith¹⁴⁵, E. Soubrie⁹⁷, I. Szapudi¹¹⁸, G. Testera¹⁸, R. Teyssier¹⁴⁶, S. Tosi^{17, 9, 18}, C. Uhlemann¹⁴⁷, C. Valieri¹⁶, A. Viitanen^{50, 133, 31}, S. Vinciguerra³⁷, M. von Wietersheim-Kramsta^{63, 148}, and D. Scott¹⁴⁹

¹ Univ. Grenoble Alpes, CNRS, Grenoble INP, LPSC-IN2P3, 53, Avenue des Martyrs, 38000 Grenoble, France

² Université Côte d’Azur, Observatoire de la Côte d’Azur, CNRS, Laboratoire Lagrange, Bd de l’Observatoire, CS 34229, 06304 Nice cedex 4, France

³ INAF-Osservatorio Astronomico di Padova, Via dell’Osservatorio 5, 35122 Padova, Italy

⁴ Kapteyn Astronomical Institute, University of Groningen, PO Box 800, 9700 AV Groningen, The Netherlands

⁵ Université Paris-Saclay, Université Paris Cité, CEA, CNRS, AIM, 91191, Gif-sur-Yvette, France

⁶ Centre National d’Etudes Spatiales – Centre spatial de Toulouse, 18 avenue Edouard Belin, 31401 Toulouse Cedex 9, France

⁷ Université Lyon 1, CNRS/IN2P3, IP2I Lyon, Villeurbanne, France

⁸ Universitäts-Sternwarte München, Fakultät für Physik, Ludwig-Maximilians-Universität München, Scheinerstr. 1, 81679 München, Germany

⁹ INAF-Osservatorio Astronomico di Brera, Via Brea 28, 20122 Milano, Italy

¹⁰ IFPU, Institute for Fundamental Physics of the Universe, via Beirut 2, 34151 Trieste, Italy

¹¹ INAF-Osservatorio Astronomico di Trieste, Via G. B. Tiepolo 11, 34143 Trieste, Italy

¹² INFN, Sezione di Trieste, Via Valerio 2, 34127 Trieste TS, Italy

¹³ SISSA, International School for Advanced Studies, Via Bonomea 265, 34136 Trieste TS, Italy

¹⁴ Dipartimento di Fisica e Astronomia, Università di Bologna, Via Gobetti 93/2, 40129 Bologna, Italy

¹⁵ INAF-Osservatorio di Astrofisica e Scienza dello Spazio di Bologna, Via Piero Gobetti 93/3, 40129 Bologna, Italy

¹⁶ INFN-Sezione di Bologna, Viale Berti Pichat 6/2, 40127 Bologna, Italy affiliation: aff-17 | Dipartimento di Fisica, Università di Genova | | Italy | Via Dodecaneso 33, 16146, Genova affiliation: aff-18 | INFN-Sezione di Genova | | Italy | Via Dodecaneso 33, 16146, Genova affiliation: aff-19 | Department of Physics "E. Pancini", University Federico II | | Italy | Via Cinthia 6, 80126, Napoli affiliation: aff-20 | INAF-Osservatorio Astronomico di Capodimonte | | Italy | Via Moiariello 16, 80131 Napoli affiliation: aff-21 | European Southern Observatory | | Germany | Karl-Schwarzschild-Str. 2, 85748 Garching affiliation: aff-22 | Instituto de Astrofísica e Ciências do Espaço, Universidade do Porto, CAUP | | Portugal | Rua das Estrelas, PT4150-762 Porto affiliation: aff-23 | Faculdade de Ciências da Universidade do Porto | | Portugal | Rua do Campo de Alegre, 4150-007 Porto affiliation: aff-24 | Dipartimento di Fisica, Università degli Studi di Torino | | Italy | Via P. Giuria 1, 10125 Torino affiliation: aff-25 | INFN-Sezione di Torino | | Italy | Via P. Giuria 1, 10125 Torino affiliation: aff-26 | INAF-Osservatorio Astrofisico di Torino | | Italy | Via Osservatorio 20, 10025 Pino Torinese (TO) affiliation: aff-27 | Leiden Observatory, Leiden University | | The Netherlands | Einsteinweg 55, 2333 CC Leiden affiliation: aff-28 | INAF-IASF Milano | | Italy | Via Alfonso Corti 12, 20133 Milano affiliation: aff-29 | Institute of Space Sciences (ICE, CSIC) | | Spain | Campus UAB, Carrer de Can Magrans, s/n, 08193 Barcelona affiliation: aff-30 | Institut d’Estudis Espacials de Catalunya (IEEC) | | Spain | Edifici RDIT, Campus UPC, 08860 Castelldefels, Barcelona affiliation: aff-31 | INAF-Osservatorio Astronomico di Roma | | Italy | Via Frascati 33, 00078 Monteporzio Catone affiliation: aff-32 | INFN – Sezione di Napoli | | Italy | Via Cinthia 6, 80126, Napoli affiliation: aff-33 | Dipartimento di Fisica e Astronomia "Augusto Righi" - Alma Mater Studiorum Università di Bologna | | Italy | Viale Berti Pichat 6/2, 40127 Bologna affiliation: aff-34 | Institute for Astronomy, University of Edinburgh | | UK | Royal Observatory, Blackford Hill, Edinburgh EH9 3HJ affiliation: aff-35 | European Space Agency/ESRIN | | Italy | Largo Galileo Galilei 1, 00044 Frascati, Roma affiliation: aff-36 | ESAC/ESA | | Spain | Camino Bajo del Castillo, s/n., Urb. 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Galilei", Università di Padova | | Italy | Via Marzolo 8, 35131 Padova affiliation: aff-78 | INFN-Padova | | Italy | Via Marzolo 8, 35131 Padova affiliation: aff-79 | Instituto de Física Teórica UAM-CSIC | | Spain | Campus de Cantoblanco, 28049 Madrid affiliation: aff-80 | Institut de Recherche en Astrophysique et Planétologie (IRAP), Université de Toulouse, CNRS, UPS, CNES | | France | 14 Av. Edouard Belin, 31400 Toulouse 81 Université St Joseph; Faculty of Sciences, Beirut, Lebanon

82 Centre for Electronic Imaging, Open University, Walton Hall, Milton Keynes, MK7 6AA, UK

83 Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Avenida Complutense 40, 28040 Madrid, Spain

84 Infrared Processing and Analysis Center, California Institute of Technology, Pasadena, CA 91125, USA

85 Cosmic Dawn Center (DAWN)

86 Niels Bohr Institute, University of Copenhagen, Jagtvej 128, 2200 Copenhagen, Denmark

87 Universidad Politécnica de Cartagena, Departamento de Electrónica y Tecnología de Computadoras, Plaza del Hospital 1, 30202 Cartagena, Spain

88 European University of Technology EUt+, European Union

89 Dipartimento di Fisica e Scienze della Terra, Università degli Studi di Ferrara, Via Giuseppe Saragat 1, 44122 Ferrara, Italy

90 Istituto Nazionale di Fisica Nucleare, Sezione di Ferrara, Via Giuseppe Saragat 1, 44122 Ferrara, Italy

91 ICSC - Centro Nazionale di Ricerca in High Performance Computing, Big Data e Quantum Computing, Via Magnanelli 2, Bologna, Italy

92 INAF, Istituto di Radioastronomia, Via Piero Gobetti 101, 40129 Bologna, Italy

93 INFN-Bologna, Via Irnerio 46, 40126 Bologna, Italy

94 Astronomical Observatory of the Autonomous Region of the Aosta Valley (OAVdA), Loc. Lignan 39, I-11020, Nus (Aosta Valley), Italy

95 Department of Mathematical Physics, Institute of Physics, University of São Paulo, R. do Matão 1371, 05508-090, São Paulo, SP, Brazil

96 Centre de Recherche Astrophysique de Lyon, UMR5574, CNRS, Université Claude Bernard Lyon 1, ENS de Lyon, 69230, Saint-Genis-Laval, France

97 Université Paris-Saclay, CNRS, Institut d’astrophysique spatiale, 91405, Orsay, France

98 Instituto de Astrofísica de Canarias, E-38205 La Laguna, Tenerife, Spain

99 Universidad de La Laguna, Dpto. Astrofísica, E-38206 La Laguna, Tenerife, Spain

100 Universität Innsbruck, Institut für Astro- und Teilchenphysik, Technikerstr. 25/8, 6020 Innsbruck, Austria

101 Oskar Klein Centre for Cosmoparticle Physics, Department of Physics, Stockholm University, Stockholm, SE-106 91, Sweden

102 Astrophysics Group, Blackett Laboratory, Imperial College London, London SW7 2AZ, UK

103 Dipartimento di Fisica, Sapienza Università di Roma, Piazzale Aldo Moro 2, 00185 Roma, Italy

104 Institut d’Astrophysique de Paris, 98bis Boulevard Arago, 75014, Paris, France

105 ICL, Junia, Université Catholique de Lille, LITL, 59000 Lille, France

106 Center for Astrophysics and Cosmology, University of Nova Gorica, Nova Gorica, Slovenia

107 Department of Astronomy, Indiana University, 727 East Third Street, Bloomington, IN 47405, USA

108 CERCA/ISO, Department of Physics, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH 44106, USA

109 Laboratoire Univers et Théorie, Observatoire de Paris, Université PSL, Université Paris Cité, CNRS, 92190 Meudon, France

110 Departamento de Física Fundamental. Universidad de Salamanca. Plaza de la Merced s/n. 37008 Salamanca, Spain

111 Universiteit Gent, Department of Physics and Astronomy, Proeftuinstraat 86 N3, 9000 Ghent, Belgium

112 Konkoly Observatory, HUN-REN CSFK, MTA Centre of Excellence, Budapest, Konkoly Thege Miklós út 15-17. H-1121, Hungary

113 MTA-CSFK Lendület Large-Scale Structure Research Group, Konkoly-Thege Miklós út 15-17, H-1121 Budapest, Hungary

114 Université de Strasbourg, CNRS, Observatoire astronomique de Strasbourg, UMR 7550, 67000 Strasbourg, France

115 Scuola Superiore Meridionale, Via Mezzocannone 4, 80138, Napoli, Italy

116 Instituto de Astrofísica e Ciências do Espaço, Faculdade de Ciências, Universidade de Lisboa, Tapada da Ajuda, 1349-018 Lisboa, Portugal

117 Institute of Cosmology and Gravitation, University of Portsmouth, Portsmouth PO1 3FX, UK

118 Institute for Astronomy, University of Hawaii, 2680 Woodlawn Drive, Honolulu, HI 96822, USA

119 Departamento Física Aplicada, Universidad Politécnica de Cartagena, Campus Muralla del Mar, 30202 Cartagena, Murcia, Spain

120 Univ. Grenoble Alpes, CNRS, IPAG, 38000 Grenoble, France

121 CEA Saclay, DFR/IRFU, Service d’Astrophysique, Bat. 709, 91191 Gif-sur-Yvette, France

122 Department of Mathematics and Physics E. De Giorgi, University of Salento, Via per Arnesano, CP-193, 73100, Lecce, Italy

123 INFN, Sezione di Lecce, Via per Arnesano, CP-193, 73100, Lecce, Italy

124 INAF-Sezione di Lecce, c/o Dipartimento Matematica e Fisica, Via per Arnesano, 73100, Lecce, Italy

125 Dipartimento di Fisica "E. Pancini", Università degli Studi di Napoli Federico II, Via Cinthia 6, 80126, Napoli, Italy

126 INFN Sezione di Napoli, Universita degli Studi di Napoli "Federico II", Compl. Univ. di Monte S. Angelo, Edificio G, Via Cinthia, I-80126, Napoli, Italy

127 Université Paris Cité, CNRS, Astroparticule et Cosmologie, 75013 Paris, France

128 Department of Computer Science, Aalto University, PO Box 15400, Espoo, FI-00 076, Finland

129 Ruhr University Bochum, Faculty of Physics and Astronomy, Astronomical Institute (AIRUB), German Centre for Cosmological Lensing (GCCL), 44780 Bochum, Germany

130 DARK, Niels Bohr Institute, University of Copenhagen, Jagtvej 155, 2200 Copenhagen, Denmark

131 Van Swinderen Institute, University of Groningen, Nijenborgh 3, 9747 AG Groningen, The Netherlands

132 Department of Physics and Astronomy, University of the Western Cape, Bellville, Cape Town, 7535, South Africa

133 Department of Physics and Helsinki Institute of Physics, Gustaf Hällströminkatu 2, University of Helsinki, 00014 Helsinki, Finland

134 INAF-Osservatorio Astrofisico di Arcetri, Largo E. Fermi 5, 50125, Firenze, Italy

135 Centro de Astrofísica da Universidade do Porto, Rua das Estrelas, 4150-762 Porto, Portugal

136 Dipartimento di Fisica, Università di Roma Tor Vergata, Via della Ricerca Scientifica 1, Roma, Italy

137 INFN, Sezione di Roma 2, Via della Ricerca Scientifica 1, Roma, Italy

138 HE Space for European Space Agency (ESA), Camino bajo del Castillo, s/n, Urbanizacion Villafranca del Castillo, Villanueva de la Cañada, 28692 Madrid, Spain

139 Dipartimento di Fisica “G. Occhialini”, Università degli Studi di Milano Bicocca, Piazza della Scienza 3, 20126 Milano, Italy

140 School of Physical Sciences, The Open University, Milton Keynes, MK7 6AA, UK

141 Department of Astrophysics, University of Zurich, Winterthurerstrasse 190, 8057 Zurich, Switzerland

142 Space physics and astronomy research unit, University of Oulu, Pentti Kaiteran katu 1, FI-90014 Oulu, Finland

143 Department of Mathematics and Physics, Roma Tre University, Via della Vasca Navale 84, 00146 Rome, Italy

144 Theoretical astrophysics, Department of Physics and Astronomy, Uppsala University, Box 524, 751 20 Uppsala, Sweden

145 Institute of Astronomy, University of Cambridge, Madingley Road, Cambridge CB3 0HA, UK

{sup}146` Department of Astrophysical Sciences, Peyton Hall, Princeton University, Princeton, NJ 08544, USA

{sup}147` Fakultät für Physik, Universität Bielefeld, Postfach 100131, 33501 Bielefeld, Germany

{sup}148` Department of Physics, Centre for Extragalactic Astronomy, Durham University, South Road, Durham, DH1 3LE, UK

{sup}149` Department of Physics and Astronomy, University of British Columbia, Vancouver, BC V6T 1Z1, Canada

Zoom-in on the DR1 EWS masks

Examples of the DR1 EWS masks are presented here for observation Patch ID 4, in Figs. A.1, A.2, A.3, and A.4.

Photometric and instrumental properties of the Euclid Deep Fields

Tables B.1, B.2, and B.3 present statistical information for the EDFs.

Band	Quantity	Mean	Median	Std	$Q_{16}$	$Q_{25}$	$Q_{75}$	$Q_{84}$	IQR
$I_{\mathrm{E}}$	Exposures [s]	4642	4842	1070	4103	4192	5403	5492	1211
$I_{\mathrm{E}}$	Noise [ADU]	0.003197	0.003033	0.0008102	0.002836	0.002918	0.003204	0.003328	0.0002856
$I_{\mathrm{E}}$	Depth [AB mag]	25.89	25.93	0.1783	25.83	25.87	25.97	26	0.1014
$I_{\mathrm{E}}$	PSF FWHM [arcsec]	0.2035	0.2033	0.004154	0.1994	0.2005	0.2064	0.2077	0.005833
$Y_{\mathrm{E}}$	Exposures [s]	582.5	610.7	134.7	523.5	523.5	698	698	174.5
$Y_{\mathrm{E}}$	Noise [ADU]	1.74	1.675	0.3142	1.529	1.583	1.78	1.88	0.1968
$Y_{\mathrm{E}}$	Depth [AB mag]	24.34	24.37	0.159	24.25	24.31	24.43	24.47	0.1272
$Y_{\mathrm{E}}$	PSF FWHM [arcsec]	0.4896	0.4899	0.007884	0.4828	0.4853	0.4942	0.4965	0.008924
$J_{\mathrm{E}}$	Exposures [s]	579.4	610.7	135.3	523.5	523.5	698	698	174.5
$J_{\mathrm{E}}$	Noise [ADU]	2.017	1.939	0.3633	1.768	1.835	2.072	2.178	0.2366
$J_{\mathrm{E}}$	Depth [AB mag]	24.48	24.51	0.1596	24.39	24.44	24.57	24.61	0.1317
$J_{\mathrm{E}}$	PSF FWHM [arcsec]	0.5155	0.5158	0.008394	0.5083	0.511	0.5205	0.5229	0.009538
$H_{\mathrm{E}}$	Exposures [s]	570.3	610.7	144.1	436.2	523.5	698	698	174.5
$H_{\mathrm{E}}$	Noise [ADU]	1.864	1.776	0.3511	1.618	1.679	1.928	2.044	0.2489
$H_{\mathrm{E}}$	Depth [AB mag]	24.47	24.51	0.1694	24.35	24.42	24.57	24.61	0.1501
$H_{\mathrm{E}}$	PSF FWHM [arcsec]	0.5602	0.5606	0.00712	0.5543	0.5565	0.5644	0.5664	0.007904

Band	Quantity	Mean	Median	Std	$Q_{16}$	$Q_{25}$	$Q_{75}$	$Q_{84}$	IQR
$I_{\mathrm{E}}$	Exposures [s]	21 373	25 332	8888	8092	17 687	27 282	28 111	9595
$I_{\mathrm{E}}$	Noise [ADU]	0.001635	0.001221	0.001115	0.001162	0.001176	0.001454	0.002123	0.0002775
$I_{\mathrm{E}}$	Depth [AB mag]	26.72	26.91	0.4366	26.31	26.72	26.95	26.97	0.23
$I_{\mathrm{E}}$	PSF FWHM [arcsec]	0.2033	0.2032	0.002332	0.2016	0.2021	0.2043	0.2049	0.002179
$Y_{\mathrm{E}}$	Exposures [s]	2565	2966	1048	1047	2268	3228	3315	960
$Y_{\mathrm{E}}$	Noise [ADU]	0.92	0.7123	0.8847	0.6729	0.684	0.8261	1.202	0.1421
$Y_{\mathrm{E}}$	Depth [AB mag]	25.12	25.3	0.402	24.73	25.14	25.34	25.36	0.205
$Y_{\mathrm{E}}$	PSF FWHM [arcsec]	0.4918	0.4924	0.005346	0.4888	0.4902	0.4944	0.4954	0.004196
$J_{\mathrm{E}}$	Exposures [s]	2490	2966	1006	960	2181	3141	3228	960
$J_{\mathrm{E}}$	Noise [ADU]	1.055	0.8213	1.07	0.7784	0.7898	0.9519	1.372	0.1621
$J_{\mathrm{E}}$	Depth [AB mag]	25.27	25.44	0.3952	24.89	25.28	25.49	25.5	0.2026
$J_{\mathrm{E}}$	PSF FWHM [arcsec]	0.5181	0.5186	0.005552	0.5149	0.5163	0.5207	0.5218	0.004441
$H_{\mathrm{E}}$	Exposures [s]	2554	2966	1044	1047	2181	3228	3315	1047
$H_{\mathrm{E}}$	Noise [ADU]	0.9624	0.7467	0.8437	0.705	0.7167	0.8694	1.257	0.1528
$H_{\mathrm{E}}$	Depth [AB mag]	25.27	25.45	0.401	24.88	25.28	25.49	25.51	0.2098
$H_{\mathrm{E}}$	PSF FWHM [arcsec]	0.5631	0.5637	0.004943	0.5605	0.5618	0.5655	0.5664	0.003773

Band	Quantity	Mean	Median	Std	$Q_{16}$	$Q_{25}$	$Q_{75}$	$Q_{84}$	IQR
$I_{\mathrm{E}}$	Exposures [s]	20 275	23 561	7669	10 245	18 898	25 040	25 714	6142
$I_{\mathrm{E}}$	Noise [ADU]	0.00168	0.001296	0.001154	0.001246	0.00126	0.001451	0.001962	0.0001915
$I_{\mathrm{E}}$	Depth [AB mag]	26.68	26.85	0.4079	26.4	26.73	26.88	26.89	0.1537
$I_{\mathrm{E}}$	PSF FWHM [arcsec]	0.2035	0.2034	0.002228	0.2019	0.2024	0.2044	0.205	0.002045
$Y_{\mathrm{E}}$	Exposures [s]	2505	2879	947	1221	2356	3141	3228	785
$Y_{\mathrm{E}}$	Noise [ADU]	0.9221	0.7313	0.932	0.6972	0.7065	0.8173	1.099	0.1109
$Y_{\mathrm{E}}$	Depth [AB mag]	25.11	25.27	0.3784	24.83	25.15	25.31	25.32	0.1583
$Y_{\mathrm{E}}$	PSF FWHM [arcsec]	0.4916	0.4921	0.005175	0.4887	0.49	0.4941	0.4951	0.004157
$J_{\mathrm{E}}$	Exposures [s]	2514	2966	953	1221	2356	3141	3228	785
$J_{\mathrm{E}}$	Noise [ADU]	1.048	0.8318	0.9247	0.7931	0.8035	0.9321	1.253	0.1286
$J_{\mathrm{E}}$	Depth [AB mag]	25.27	25.43	0.378	24.99	25.31	25.47	25.48	0.1612
$J_{\mathrm{E}}$	PSF FWHM [arcsec]	0.5177	0.5182	0.005378	0.5146	0.5159	0.5203	0.5214	0.004376
$H_{\mathrm{E}}$	Exposures [s]	2511	2966	952.7	1221	2268	3141	3228	872
$H_{\mathrm{E}}$	Noise [ADU]	0.9673	0.7651	1.208	0.7291	0.7388	0.8596	1.155	0.1209
$H_{\mathrm{E}}$	Depth [AB mag]	25.26	25.42	0.3795	24.97	25.3	25.46	25.47	0.1645
$H_{\mathrm{E}}$	PSF FWHM [arcsec]	0.5629	0.5634	0.00469	0.5603	0.5615	0.5652	0.5661	0.003726