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J. Gracia-Carpio

Publications and source records attributed to J. Gracia-Carpio.

At least 145 records · Page 8Linked to original sources

Euclid Quick Data Release (Q1) -- Data release overview

The first Euclid Quick Data Release, Q1, comprises 63.1 sq deg of the Euclid Deep Fields (EDFs) to nominal wide-survey depth. It encompasses visible and near-infrared space-based imaging and spectroscopic data, ground-based photometry in the u, g, r, i and z bands, as well as corresponding masks. Overall, Q1 contains about 30 million objects in three areas near the ecliptic poles around the EDF-North and EDF-South, as well as the EDF-Fornax field in the constellation of the same name. The purpose of this data release -- and its associated technical papers -- is twofold. First, it is meant to inform the community of the enormous potential of the Euclid survey data, to describe what is contained in these data, and to help prepare expectations for the forthcoming first major data release DR1. Second, it enables a wide range of initial scientific projects with wide-survey Euclid data, ranging from the early Universe to the Solar System. The Q1 data were processed with early versions of the processing pipelines, which already demonstrate good performance, with numerous improvements in implementation compared to pre-launch development. In this paper, we describe the sky areas released in Q1, the observations, a top-level view of the data processing of Euclid and associated external data, the Q1 photometric masks, and how to access the data. We also give an overview of initial scientific results obtained using the Q1 data set by Euclid Consortium scientists, and conclude with important caveats when using the data. As a complementary product, Q1 also contains observations of a star-forming area in Lynd's Dark Nebula 1641 in the Orion~A Cloud, observed for technical purposes during Euclid's performance-verification phase. This is a unique target, of a type not commonly found in Euclid's nominal sky survey.

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Euclid Quick Data Release (Q1). Photometric redshifts and physical properties of galaxies through the PHZ processing function

The ESA Euclid mission will measure the photometric redshifts of billions of galaxies in order to provide an accurate 3D view of the Universe at optical and near-infrared wavelengths. Photometric redshifts are determined by the PHZ processing function on the basis of the multi-wavelength photometry of Euclid and ground-based observations. In this paper, we describe the PHZ processing used for the Euclid Quick Data Release, the output products, and their validation. The PHZ pipeline is responsible for the following main tasks: source classification into star, galaxy, and QSO classes based on photometric colours; determination of photometric redshifts and of physical properties of galaxies. The classification is able to provide a star sample with a high level of purity, a highly complete galaxy sample, and reliable probabilities of belonging to those classes. The identification of QSOs is more problematic: photometric information seems to be insufficient to accurately separate QSOs from galaxies. The performance of the pipeline in the determination of photometric redshifts has been tested using the COSMOS2020 catalogue and a large sample of spectroscopic redshifts. The results are in line with expectations: the precision of the estimates are compatible with Euclid requirements, while, as expected, a bias correction is needed to achieve the accuracy level required for the cosmological probes. Finally, the pipeline provides reliable estimates of the physical properties of galaxies, in good agreement with findings from the COSMOS2020 catalogue, except for an unrealistically large fraction of very young galaxies with very high specific star-formation rates. The application of appropriate priors is, however, sufficient to obtain reliable physical properties for those problematic objects. We present several areas for improvement for future Euclid data releases.

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Euclid Quick Data Release (Q1): First visual morphology catalogue

We present a detailed visual morphology catalogue for Euclid's Quick Release 1 (Q1). Our catalogue includes galaxy features such as bars, spiral arms, and ongoing mergers, for the 378000 bright ($I_E < 20.5$) or extended (area $\geq 700\,$pixels) galaxies in Q1. The catalogue was created by finetuning the Zoobot galaxy foundation models on annotations from an intensive one month campaign by Galaxy Zoo volunteers. Our measurements are fully automated and hence fully scaleable. This catalogue is the first 0.4% of the approximately 100 million galaxies where Euclid will ultimately resolve detailed morphology.

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Euclid Quick Data Release (Q1), A first look at the fraction of bars in massive galaxies at $z<1$

Stellar bars are key structures in disc galaxies, driving angular momentum redistribution and influencing processes such as bulge growth and star formation. Quantifying the bar fraction as a function of redshift and stellar mass is therefore important for constraining the physical processes that drive disc formation and evolution across the history of the Universe. Leveraging the unprecedented resolution and survey area of the Euclid Q1 data release combined with the Zoobot deep-learning model trained on citizen-science labels, we identify 7711 barred galaxies with $M_* \gtrsim 10^{10}M_\odot$ in a magnitude-selected sample $I_E < 20.5$ spanning $63.1 deg^2$. We measure a mean bar fraction of $0.2-0.4$, consistent with prior studies. At fixed redshift, massive galaxies exhibit higher bar fractions, while lower-mass systems show a steeper decline with redshift, suggesting earlier disc assembly in massive galaxies. Comparisons with cosmological simulations (e.g., TNG50, Auriga) reveal a broadly consistent bar fraction, but highlight overpredictions for high-mass systems, pointing to potential over-efficiency in central stellar mass build-up in simulations. These findings demonstrate Euclid's transformative potential for galaxy morphology studies and underscore the importance of refining theoretical models to better reproduce observed trends. Future work will explore finer mass bins, environmental correlations, and additional morphological indicators.

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Euclid Quick Data Release (Q1) Exploring galaxy properties with a multi-modal foundation model

Modern astronomical surveys, such as the Euclid mission, produce high-dimensional, multi-modal data sets that include imaging and spectroscopic information for millions of galaxies. These data serve as an ideal benchmark for large, pre-trained multi-modal models, which can leverage vast amounts of unlabelled data. In this work, we present the first exploration of Euclid data with AstroPT, an autoregressive multi-modal foundation model trained on approximately 300 000 optical and infrared Euclid images and spectral energy distributions (SEDs) from the first Euclid Quick Data Release. We compare self-supervised pre-training with baseline fully supervised training across several tasks: galaxy morphology classification; redshift estimation; similarity searches; and outlier detection. Our results show that: (a) AstroPT embeddings are highly informative, correlating with morphology and effectively isolating outliers; (b) including infrared data helps to isolate stars, but degrades the identification of edge-on galaxies, which are better captured by optical images; (c) simple fine-tuning of these embeddings for photometric redshift and stellar mass estimation outperforms a fully supervised approach, even when using only 1% of the training labels; and (d) incorporating SED data into AstroPT via a straightforward multi-modal token-chaining method improves photo-z predictions, and allow us to identify potentially more interesting anomalies (such as ringed or interacting galaxies) compared to a model pre-trained solely on imaging data.

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Euclid Quick Data Release (Q1). First Euclid statistical study of the active galactic nuclei contribution fraction

Active galactic nuclei (AGN) play a key role in galaxy evolution but are challenging to identify due to their varied observational signatures. Furthermore, understanding their impact requires quantifying their strength relative to their host galaxies. We developed a deep learning (DL) model for identifying AGN in imaging data by deriving the contribution of the central point source. Trained on Euclidised mock galaxy images with injected AGN levels, in the form of varying contributions of the point-spread function (PSF), our model can precisely and accurately recover the injected AGN contribution fraction $f_{\rm PSF}$, with a mean difference between the predicted and true $f_{\rm PSF}$ of $-0.0078$ and an overall root mean square error (RMSE) of 0.051. This method moves beyond binary AGN classification, enabling precise AGN contribution measurements. Applying our model to a stellar-mass-limited sample ($M_{\ast} \ge 10^{9.8} M_{\odot}$, $0.5 \le z \le 2.0$) from the first \Euclid quick data release (Q1), we identify $48,840 \pm 78$ AGN over 63.1 deg$^2$ ($7.8\pm0.1$%) using a threshold of $f_{\rm PSF} > 0.2$. We compare our DL-selected AGN with those identified in X-ray, mid-infrared (MIR), and optical spectroscopy and investigate their overlapping fractions depending on different thresholds on the PSF contribution. We find that the overlap increases with increasing X-ray or bolometric AGN luminosity. The AGN luminosity in the $I_{\rm E}$ filter correlates with host galaxy stellar mass, suggesting faster supermassive black hole (SMBH) growth in more massive galaxies. Moreover, the mean relative contribution of the AGN is higher in quiescent galaxies than in star-forming ones. Starburst galaxies and the most massive galaxies (across the star-formation main sequence) tend to host the most luminous AGN, indicating concomitant assembly of the SMBH and the host galaxy.

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Euclid Quick Data Release (Q1) First study of red quasars selection

Red quasars constitute an important but elusive phase in the evolution of supermassive black holes, where dust obscuration can significantly alter their observed properties. They have broad emission lines, like other quasars, but their optical continuum emission is significantly reddened, which is why they were traditionally identified based on near- and mid-infrared selection criteria. This work showcases the capability of the \Euclid space telescope to find a large sample of red quasars, using \Euclid near infrared (NIR) photometry. We first conduct a forecast analysis, comparing a synthetic catalogue of red QSOs with COSMOS2020. Using template fitting, we reconstruct \Euclid-like photometry for the COSMOS sources and identify a sample of candidates in a multidimensional colour-colour space achieving $98\%$ completeness for mock red QSOs with $30\%$ contaminants. To refine our selection function, we implement a probabilistic Random Forest classifier, and use UMAP visualisation to disentangle non-linear features in colour-space, reaching $98\%$ completeness and $88\%$ purity. A preliminary analysis of the candidates in the \Euclid Deep Field Fornax (EDF-F) shows that, compared to VISTA+DECAm-based colour selection criteria, \Euclid's superior depth, resolution and optical-to-NIR coverage improves the identification of the reddest, most obscured sources. Notably, the \Euclid exquisite resolution in the $I_E$ filter unveils the presence of a candidate dual quasar system, highlighting the potential for this mission to contribute to future studies on the population of dual AGN. The resulting catalogue of candidates, including more the 150 000 sources, provides a first census of red quasars in \Euclid Q1 and sets the groundwork for future studies in the Euclid Wide Survey (EWS), including spectral follow-up analyses and host morphology characterisation.

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Euclid Quick Data Release (Q1). An investigation of optically faint, red objects in the Euclid Deep Fields

Our understanding of cosmic star-formation at $z>3$ used to largely rely on rest-frame UV observations. However, these observations overlook dusty and massive sources, resulting in an incomplete census of early star-forming galaxies. Recently, infrared data from Spitzer and the James Webb Space Telescope (JWST) have revealed a hidden population at $z\sim$3-6 with extreme red colours. Taking advantage of the overlap between imaging in the Euclid Deep Fields (EDFs), covering $\sim$ 60 deg$^2$, and ancillary Spitzer observations, we identified 27000 extremely red objects with $H_E-{\rm IRAC}2>2.25$ (dubbed HIEROs) down to a $10σ$ completeness magnitude limit of IRAC2 $=$ 22.5 AB. After a visual inspection to discard artefacts and objects with troubling photometry, we ended up with a final sample of 3900 candidates. We retrieved the physical parameter estimates for these objects from the SED-fitting tool CIGALE. Our results confirm that HIERO galaxies may populate the high-mass end of the stellar mass function at $z>3$, with some reaching extreme stellar masses ($M_*>10^{11}M_\odot$) and exhibiting high dust attenuation ($A_V>3$). However, we consider stellar mass estimates unreliable for $z>3.5$, favouring a lower-z solution. The challenges faced by SED-fitting tools in characterising these objects highlight the need for further studies, incorporating shorter-wavelength and spectroscopic data. Euclid spectra will help resolve degeneracies and better constrain the physical properties of the brightest galaxies. Given the extreme nature of this population, characterising these sources is crucial for understanding galaxy evolution. This work demonstrates Euclid's potential to provide statistical samples of rare, massive, dust-obscured galaxies at $z>3$, which will be prime targets for JWST, ALMA, and ELT.

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Euclid Quick Data Release (Q1): The Strong Lensing Discovery Engine A -- System overview and lens catalogue

We present a catalogue of 497 galaxy-galaxy strong lenses in the Euclid Quick Release 1 data (63 deg$^2$). In the initial 0.45\% of Euclid's surveys, we double the total number of known lens candidates with space-based imaging. Our catalogue includes 250 grade A candidates, the vast majority of which (243) were previously unpublished. Euclid's resolution reveals rare lens configurations of scientific value including double-source-plane lenses, edge-on lenses, complete Einstein rings, and quadruply-imaged lenses. We resolve lenses with small Einstein radii ($θ_{\rm E} < 1''$) in large numbers for the first time. These lenses are found through an initial sweep by deep learning models, followed by Space Warps citizen scientist inspection, expert vetting, and system-by-system modelling. Our search approach scales straightforwardly to Euclid Data Release 1 and, without changes, would yield approximately 7000 high-confidence (grade A or B) lens candidates by late 2026. Further extrapolating to the complete Euclid Wide Survey implies a likely yield of over 100000 high-confidence candidates, transforming strong lensing science.

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Euclid Quick Data Release (Q1) The Strong Lensing Discovery Engine B -- Early strong lens candidates from visual inspection of high velocity dispersion galaxies

We present a search for strong gravitational lenses in Euclid imaging with high stellar velocity dispersion ($σ_ν> 180$ km/s) reported by SDSS and DESI. We performed expert visual inspection and classification of $11\,660$ \Euclid images. We discovered 38 grade A and 40 grade B candidate lenses, consistent with an expected sample of $\sim$32. Palomar spectroscopy confirmed 5 lens systems, while DESI spectra confirmed one, provided ambiguous results for another, and help to discard one. The \Euclid automated lens modeler modelled 53 candidates, confirming 38 as lenses, failing to model 9, and ruling out 6 grade B candidates. For the remaining 25 candidates we could not gather additional information. More importantly, our expert-classified non-lenses provide an excellent training set for machine learning lens classifiers. We create high-fidelity simulations of \Euclid lenses by painting realistic lensed sources behind the expert tagged (non-lens) luminous red galaxies. This training set is the foundation stone for the \Euclid galaxy-galaxy strong lensing discovery engine.

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Euclid Quick Data Release (Q1). The Strong Lensing Discovery Engine D -- Double-source-plane lens candidates

Strong gravitational lensing systems with multiple source planes are powerful tools for probing the density profiles and dark matter substructure of the galaxies. The ratio of Einstein radii is related to the dark energy equation of state through the cosmological scaling factor $β$. However, galaxy-scale double-source-plane lenses (DSPLs) are extremely rare. In this paper, we report the discovery of four new galaxy-scale double-source-plane lens candidates in the Euclid Quick Release 1 (Q1) data. These systems were initially identified through a combination of machine learning lens-finding models and subsequent visual inspection from citizens and experts. We apply the widely-used {\tt LensPop} lens forecasting model to predict that the full \Euclid survey will discover 1700 DSPLs, which scales to $6 \pm 3$ DSPLs in 63 deg$^2$, the area of Q1. The number of discoveries in this work is broadly consistent with this forecast. We present lens models for each DSPL and infer their $β$ values. Our initial Q1 sample demonstrates the promise of \Euclid to discover such rare objects.

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Euclid Quick Data Release (Q1). Galaxy shapes and alignments in the cosmic web

Galaxy morphologies and shape orientations are expected to correlate with their large-scale environment, since they grow by accreting matter from the cosmic web and are subject to interactions with other galaxies. Cosmic filaments are extracted in projection from the Euclid Quick Data Release 1 (covering 63.1 $\mathrm{deg}^2$) at $0.5 10^{10} M_\odot$) in the projected cosmic web is analysed as a function of morphology measured from VIS data. Specifically, the 2D alignment of galaxy shapes with large-scale filaments is quantified as a function of Sérsic indices and masses. We find the known trend that more massive galaxies are closer to filament spines. At fixed stellar masses, morphologies correlate both with densities and distances to large-scale filaments. In addition, the large volume of this data set allows us to detect a signal indicating that there is a preferential alignment of the major axis of massive early-type galaxies along projected cosmic filaments. Overall, these results demonstrate our capabilities to carry out detailed studies of galaxy environments with Euclid, which will be extended to higher redshift and lower stellar masses with the future Euclid Deep Survey.

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Euclid Quick Data Release (Q1): From spectrograms to spectra: the SIR spectroscopic Processing Function

The Euclid space mission aims to investigate the nature of dark energy and dark matter by mapping the large-scale structure of the Universe. A key component of Euclid's observational strategy is slitless spectroscopy, conducted using the Near Infrared Spectrometer and Photometer (NISP). This technique enables the acquisition of large-scale spectroscopic data without the need for targeted apertures, allowing precise redshift measurements for millions of galaxies. These data are essential for Euclid's core science objectives, including the study of cosmic acceleration and the evolution of galaxy clustering, as well as enabling many non-cosmological investigations. This study presents the SIR processing function (PF), which is responsible for processing slitless spectroscopic data. The objective is to generate science-grade fully-calibrated one-dimensional spectra, ensuring high-quality spectroscopic data. The processing function relies on a source catalogue generated from photometric data, effectively corrects detector effects, subtracts cross-contaminations, minimizes self-contamination, calibrates wavelength and flux, and produces reliable spectra for later scientific use. The first Quick Data Release (Q1) of Euclid's spectroscopic data provides approximately three million validated spectra for sources observed in the red-grism mode from a selected portion of the Euclid Wide Survey. We find that wavelength accuracy and measured resolving power are within requirements, thanks to the excellent optical quality of the instrument. The SIR PF represents a significant step in processing slitless spectroscopic data for the Euclid mission. As the survey progresses, continued refinements and additional features will enhance its capabilities, supporting high-precision cosmological and astrophysical measurements.

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Euclid preparation: VI. Verifying the Performance of Cosmic Shear Experiments

Our aim is to quantify the impact of systematic effects on the inference of cosmological parameters from cosmic shear. We present an end-to-end approach that introduces sources of bias in a modelled weak lensing survey on a galaxy-by-galaxy level. Residual biases are propagated through a pipeline from galaxy properties (one end) through to cosmic shear power spectra and cosmological parameter estimates (the other end), to quantify how imperfect knowledge of the pipeline changes the maximum likelihood values of dark energy parameters. We quantify the impact of an imperfect correction for charge transfer inefficiency (CTI) and modelling uncertainties of the point spread function (PSF) for Euclid, and find that the biases introduced can be corrected to acceptable levels.

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Deriving a multivariate CO-to-H$_2$ conversion function using the [CII]/CO(1-0) ratio and its application to molecular gas scaling relations

We present Herschel PACS observations of the [CII] 158 micron emission line in a sample of 24 intermediate mass (9<logM$_\ast$/M$_\odot$<10) and low metallicity (0.4< Z/Z$_\odot$<1.0) galaxies from the xCOLD GASS survey. Combining them with IRAM CO(1-0) measurements, we establish scaling relations between integrated and molecular region [CII]/CO(1-0) luminosity ratios as a function of integrated galaxy properties. A Bayesian analysis reveals that only two parameters, metallicity and offset from the star formation main sequence, $Δ$MS, are needed to quantify variations in the luminosity ratio; metallicity describes the total dust content available to shield CO from UV radiation, while $Δ$MS describes the strength of this radiation field. We connect the [CII]/CO luminosity ratio to the CO-to-H$_2$ conversion factor and find a multivariate conversion function $α_{CO}$, which can be used up to z~2.5. This function depends primarily on metallicity, with a second order dependence on $Δ$MS. We apply this to the full xCOLD GASS and PHIBSS1 surveys and investigate molecular gas scaling relations. We find a flattening of the relation between gas mass fraction and stellar mass at logM$_\ast$/M$_\odot$<10. While the molecular gas depletion time varies with sSFR, it is mostly independent of mass, indicating that the low L$_{CO}$/SFR ratios long observed in low mass galaxies are entirely due to photodissociation of CO, and not to an enhanced star formation efficiency.

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Search for Molecular Outflows in Local Volume AGN with Herschel-PACS

We present the results from a systematic search for galactic-scale, molecular (OH 119 $μ$m) outflows in a sample of 52 Local Volume ($d < 50$ Mpc) Burst Alert Telescope detected active galactic nuclei (BAT AGN) with \emph{Herschel}-PACS. We combine the results from our analysis of the BAT AGN with the published \emph{Herschel}/PACS data of 43 nearby ($z<0.3$) galaxy mergers, mostly ultraluminous infrared galaxies (ULIRGs) and QSOs. The objects in our sample of BAT AGN have, on average, $\sim 10-100$ times lower AGN luminosities, star formation rates (SFRs), and stellar masses than those of the ULIRG and QSO sample. OH 119 $μ$m is detected in 42 of our BAT AGN targets. Evidence for molecular outflows (i.e. OH absorption profiles with median velocities more blueshifted than $-$50 km s$^{-1}$ and/or blueshifted wings with 84-percentile velocities less than $-$300 km s$^{-1}$) is seen in only four BAT AGN (NGC~7479 is the most convincing case). Evidence for molecular inflows (i.e. OH absorption profiles with median velocities more redshifted than 50 km s$^{-1}$) is seen in seven objects, although an inverted P-Cygni profile is detected unambiguously in only one object (Circinus). Our data show that both the starburst and AGN contribute to driving OH outflows, but the fastest OH winds require AGN with quasar-like luminosities. We also confirm that the total absorption strength of OH 119 $μ$m is a good proxy for dust optical depth as it correlates strongly with the 9.7 $μ$m silicate absorption feature, a measure of obscuration originating in both the nuclear torus and host galaxy disk.

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On the relation of optical obscuration and X-ray absorption in Seyfert galaxies

The optical classification of a Seyfert galaxy and whether it is considered X-ray absorbed are often used interchangeably. But there are many borderline cases and also numerous examples where the optical and X-ray classifications appear to be in conflict. In this article we re-visit the relation between optical obscuration and X-ray absorption in AGNs. We make use of our "dust color" method (Burtscher et al. 2015) to derive the optical obscuration A_V and consistently estimated X-ray absorbing columns using 0.3--150 keV spectral energy distributions. We also take into account the variable nature of the neutral gas column N_H and derive the Seyfert sub-classes of all our objects in a consistent way. We show in a sample of 25 local, hard-X-ray detected Seyfert galaxies (log L_X / (erg/s) ~ 41.5 - 43.5) that there can actually be a good agreement between optical and X-ray classification. If Seyfert types 1.8 and 1.9 are considered unobscured, the threshold between X-ray unabsorbed and absorbed should be chosen at a column N_H = 10^22.3 / cm^2 to be consistent with the optical classification. We find that N_H is related to A_V and that the N_H/A_V ratio is approximately Galactic or higher in all sources, as indicated previously. But in several objects we also see that deviations from the Galactic ratio are only due to a variable X-ray column, showing that (1) deviations from the Galactic N_H/A_V can simply be explained by dust-free neutral gas within the broad line region in some sources, that (2) the dust properties in AGNs can be similar to Galactic dust and that (3) the dust color method is a robust way to estimate the optical extinction towards the sublimation radius in all but the most obscured AGNs.

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Obscuration in AGNs: near-infrared luminosity relations and dust colors

We combine two approaches to isolate the AGN luminosity at near-infrared wavelengths and relate the near-IR pure AGN luminosity to other tracers of the AGN. Using integral-field spectroscopic data of an archival sample of 51 local AGNs, we estimate the fraction of non-stellar light by comparing the nuclear equivalent width of the stellar 2.3 micron CO absorption feature with the intrinsic value for each galaxy. We compare this fraction to that derived from a spectral decomposition of the integrated light in the central arc second and find them to be consistent with each other. Using our estimates of the near-IR AGN light, we find a strong correlation with presumably isotropic AGN tracers. We show that a significant offset exists between type 1 and type 2 sources in the sense that type 1 sources are 7 (10) times brighter in the near-IR at log L_MIR = 42.5 (log L_X = 42.5). These offsets only becomes clear when treating infrared type 1 sources as type 1 AGNs. All AGNs have very red near-to-mid-IR dust colors. This, as well as the range of observed near-IR temperatures, can be explained with a simple model with only two free parameters: the obscuration to the hot dust and the ratio between the warm and hot dust areas. We find obscurations of A_V (hot) = 5 - 15 mag for infrared type 1 sources and A_V (hot) = 15 - 35 mag for type 2 sources. The ratio of hot dust to warm dust areas of about 1000 is nicely consistent with the ratio of radii of the respective regions as found by infrared interferometry.

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