Infrared-luminous galaxies are important sites of stellar and black hole mass assembly at most redshifts. Their luminosities are often estimated by fitting spectral energy distribution (SED) models to near- to far-infrared data, but the dependence of these estimates on the data used is not well understood. Here, using observations simulated from a well-studied local sample, we compare the effects of wavelength coverage, signal-to-noise ratio, flux calibration, angular resolution, and redshift on the recovery of starburst, active galactic nucleus (AGN), and host luminosities. We show that the most important factors are wavelength coverage that spans the peak in a SED, and dense wavelength sampling. Such observations recover starburst and AGN infrared luminosities with systematic bias below 20%. Starburst luminosities are best recovered with far-infrared observations, while AGN luminosities are best recovered with near- and mid-infrared observations, though the recovery of both are enhanced with near/mid-infrared and far-infrared observations, respectively. Host luminosities are best recovered with near/far-infrared observations, but are usually biased low, by ≳20%. The recovery of starburst and AGN luminosity is enhanced by observing at high angular resolution. Starburst-dominated systems show more biased recovery of luminosities than do AGN-dominated systems. As redshift increases, far-infrared observations become more capable and mid-infrared observations less capable at recovering luminosities. Our results highlight the transformative power of a far-infrared instrument with dense wavelength coverage, from tens to hundreds of microns, for studying infrared-luminous galaxies. We tabulate estimates of systematic bias and random error for use with JWST and other observatories.

Cosmological simulations suggest that various galaxy properties depend on their location within the cosmic web. Yet direct observational evidence of the dependence of star formation activity on distance to filaments remains scarce and is missing at z ≳ 1. We investigate how starburst, main-sequence (MS), and quenched galaxies are distributed with respect to cosmic web filaments and how this distribution evolves with redshift. We first used the S IMBA cosmological hydrodynamical simulation to predict the redshift evolution of the mean distance to the closest filament from z = 3 to z = 0 for different galaxy populations, after removing stellar-mass dependencies. We then measured the corresponding signal in the COSMOS field, using COSMOS2020 and COSMOS-Web data, where accurate photometric redshifts enable a reconstruction of the projected cosmic web from z = 2 to z = 0.5, and starbursts were identified through far-infrared spectral energy distribution fitting. In agreement with the results from S IMBA , starburst galaxies are found closer to filaments at z > 1 and at larger distances at z < 1, MS galaxies occupy intermediate environments with little evolution, and quenched galaxies show progressively shorter distances to filaments towards low redshift, with a crossing between starburst and MS populations around z ∼ 1. In COSMOS-Web, the relative evolution in the average distance to filaments between starburst and MS galaxies is detected at a significance level of at least 5 σ . We show that a minimal toy model in which the only environmental ingredient is the specific star formation rate-filament distance modulation measured in simulations is sufficient to reproduce the observed differential evolution of the average filament distance between starburst and MS galaxies. These results show evidence for a link between the large-scale environment and the star formation activity of galaxies, as predicted by simulations, from z = 2 down to z = 0.5.

Aims. Dusty star-forming galaxies (DSFGs) dominate the far-infrared (FIR) and sub-millimetre (sub-mm) number counts, but singledish surveys at these wavelengths suffer from poor angular resolution, making identifications of multi-wavelength counterparts difficult. Prior driven deblending techniques require extensive fine-tuning and struggle to process large fields. This work aims to develop a fast and reliable deep-learning-based deconvolution and denoising super-resolution (SR) technique. Methods. We employed a transformer neural network to improve the resolution of the Herschel /SPIRE 500 µm observations by a factor of 4.5, with input comprised of Spitzer /MIPS 24µm and Herschel /SPIRE 250, 350, 500 µm images. The network was trained on simulations from SIDES and SHARK. To mimic realistic observations, we injected instrumental noise into the input simulated images, while keeping the target images noise-free to enhance the de-noising capabilities of our method. We evaluated the performance of our method on simulated test sets and real JCMT/SCUBA-2 450 µm observations in the COSMOS field that have a superior resolution compared to Herschel . Results. Our SR method achieves an inference time of ∼1 s/deg 2 on consumer-grade GPUs, which is much faster than traditional deblending techniques. Using the simulation test sets, we show that fluxes of the extracted sources from the super-resolved image are accurate to within 5% for sources with an intrinsic flux ≳8 mJy, which is a substantial improvement compared to blind extraction on the native images. Astrometric error is low, at ≲1″ compared to the 12″ pixel scale. In terms of reliability and completeness, ≳90% of the extracted sources brighter than ∼3 mJy are reliable and more than 90% of the input sources with intrinsic fluxes ≳5 mJy are recovered. When applied to the real 500 µm observations, the fluxes of the extracted sources from the super-resolved map agree well with the SCUBA-2 measured fluxes (after converting the 450 µm fluxes to 500 µm using a correction factor of 0.84) for sources above ∼10 mJy. Our 500 µm number counts are also consistent with previous SCUBA-2 measurements. Thanks to its speed, our technique enables SR over hundreds of deg 2 without the need for fine-tuning, facilitating statistical analysis of DSFGs.

Decomposing the contributions of active galactic nuclei (AGNs) from their host galaxies is essential for identifying AGN-dominated galaxies and accurately deriving key physical properties of both supermassive black holes (SMBHs) and their host galaxies, such as black hole accretion rates, stellar masses, and star formation rates. However, decomposing AGN contributions from multi-wavelength photometry remains challenging due to inherent parameter degeneracies in spectral energy distribution (SED) fitting. We establish a unified framework for estimating AGN contribution fractions (fAGN) and host galaxy properties by combining complementary AGN diagnostics: SED decomposition from two independent SED-fitting codes (CIGALE and GRAHSP) and deep learning (DL)-based imaging decomposition. We applied SED decomposition to galaxies in the COSMOS-Web field using multi-wavelength photometry (ultraviolet to far-infrared) and calculated the AGN-to-host galaxy flux ratio ( fSEDAGN f AGN SED $ f_{\mathrm{AGN}}^{\mathrm{SED}} $ ) in the JWST/NIRCam F150W filter. We then compared these SED-fitting derived AGN fractions with those obtained from image decomposition using DL ( fDLAGN f AGN DL $ f_{\mathrm{AGN}}^{\mathrm{DL}} $ ). Strong agreement is found for AGN-negligible galaxies across all methods: ∼82% are identified as such by both SED codes ( fSEDAGN < 0.1 f AGN SED < 0.1 $ f_{\mathrm{AGN}}^{\mathrm{SED}} < 0.1 $ ), and ∼87% of these also show minimal AGN contribution in the DL model. This high concordance demonstrates that current methods reliably identify pure galaxy systems in most cases. However, for potential AGN-dominant galaxies, large discrepancies emerge. Only 2.7% of galaxies show consistent significant AGN identification between SED codes, and merely ∼7.6% of these also exhibit a significant AGN fraction in DL estimation. Forcing DL AGN fraction constraints into SED fitting generally works for SED-significant but imaging-negligible cases, whereas it fails for around 30% of SED-negligible but imaging-significant cases. In summary, our results highlight the degeneracies inherent in current SED-fitting methods based on empirical observations or theoretical templates and demonstrate the power of incorporating independent morphological information to break these degeneracies. We present a more robust framework combining morphological information from high-fidelity imaging from surveys such as the James Webb Space Telescope (JWST) and Euclid, enabling improved AGN–host galaxy decomposition and more reliable measurements of both AGN and galaxy properties.

Luminous infrared (IR) galaxies are key sites of obscured stellar mass assembly at z > 0.5. Their star formation rates (SFRs) are often estimated using the luminosities of the 6.2 and 11.2 μ m polycyclic aromatic hydrocarbon (PAH) features or those of the [Ne ii ] and [Ne iii ] fine-structure lines, as they are minimally affected by obscuration. It is uncertain whether the calibration of these features as SFR tracers depends on the starburst bolometric luminosity or the level of active galactic nucleus (AGN) activity. We here investigate the relationship between the luminosities of PAH and neon lines with SFR for highly luminous objects using radiative transfer modeling and archival observations of 42 local ultraluminous (≥10 ^12 L _⊙ ) IR galaxies (ULIRGs). We find that PAH and [Ne ii ] features arise mainly in star-forming regions, with small contributions from the AGN or host, but that the [Ne iii ] line has a mixed contribution from both star formation and AGN activity. We present relations between L _PAH and L _[Ne _II _] , and both starburst luminosity and SFR. We find relations for lower-luminosity ( L _IR ≃ 10 ^10 –10 ^12 L _⊙ ) systems underestimate the SFRs in local ULIRGs by up to ∼1 dex. The 6.2 and 11.2 μ m PAH features, and the [Ne ii ] line, are thus good tracers of SFR in ULIRGs. We do not find that a more luminous AGN affects the relationship between SFR and PAH or neon luminosity but that it can make PAH emission harder to discern. Our results and derived relations are relevant to studies of star-forming and composite galaxies at z < 3 with the James Webb Space Telescope.

Feedback from active galactic nuclei (AGN) is now recognized as a key component of galaxy formation models. It plays a central role in regulating the growth and quenching of galaxies in the center of groups. However, the impact of AGN feedback from central galaxies on satellite galaxies remains largely unexplored. Here based on the largest sample to date of radio AGNs in galaxy groups (Yang et al. 2007) and a comprehensive consideration of multiple physical parameters that may influence the star formation of satellite galaxies, we demonstrate that the quiescent satellite fraction around radio AGNs is higher than that around normal galaxies. The most significant enhancement is observed around AGNs with large radio lobes. These findings demonstrate that the impact of kinetic AGN feedback beyond their host galaxies to their satellites. These results provide novel insights into the physical origins of some long-standing puzzles in extragalactic astronomy, including, e.g., galactic conformity and the strong small-scale clustering of quiescent galaxies.

Decomposing active galactic nucleus (AGN) emission from host-galaxy light is essential for identifying AGN-dominated systems and accurately deriving host-galaxy physical properties. However, estimating AGN contributions from multi-wavelength photometry remains challenging due to inherent parameter degeneracies in spectral energy distribution (SED) fitting. In this work, we establish a unified framework for estimating AGN contribution fractions and host-galaxy properties by combining complementary diagnostics: SED decomposition with two independent fitting codes, CIGALE and GRAHSP, and deep-learning-based imaging decomposition. We apply this framework to galaxies in the COSMOS-Web field using multi-wavelength photometry from the ultraviolet to the far-infrared. We calculate the AGN contribution fraction in the JWST/NIRCam F150W filter and compare the SED-derived estimates with independent AGN fractions obtained from deep-learning image decomposition. Our results reveal significant degeneracies in current SED-fitting approaches based on empirical or theoretical AGN templates and demonstrate that incorporating independent morphological information can help break these degeneracies and improve the reliability of AGN and host-galaxy property estimates.

Hierarchical merging of galaxies plays an important role in galaxy formation and evolution. Mergers could trigger key evolutionary phases such as starburst activities and active accretion periods onto supermassive black holes at the centres of galaxies. We aim to detect mergers and merger stages (pre- and post-mergers) across cosmic history and test whether it is better to detect mergers and their merger stages simultaneously or hierarchically. In addition, we want to test the impact of merger time relative to the coalescence of merging galaxies. First, we generated realistic mock JWST images of simulated galaxies selected from the IllustrisTNG cosmological hydrodynamical simulations. Then we trained deep learning (DL) models in the Zoobot Python package to classify galaxies into merging/non-merging galaxies and their merger stages. We used two different set-ups: (i) two-stage, in which we classify galaxies into mergers and non-mergers and then classify the mergers into pre-mergers and post-mergers, and (ii) one-stage, in which merger/non-merger and merger stages are classified simultaneously. We found that the one-stage classification set-up moderately outperforms the two-stage set-up, offering better overall accuracy and precision, particularly for the non-merger class. Pre-mergers can be classified with the highest precision in both set-ups, possibly due to the more recognisable merging features and the presence of merging companions. The image signal-to-noise ratio affects the performance of the DL classifiers, but not much after a certain threshold is crossed. Both precision and recall of the classifiers depend strongly on merger time, finding it more difficult to identify true mergers observed at stages that are more distant to coalescence. For pre-mergers, we recommend selecting mergers which will merge in the next 0.4 Gyrs, to achieve a good balance between precision and recall.

The star-forming main sequence (SFMS) is a tight relation observed between stellar masses and star formation rates (SFR) in a population of galaxies. This relation is observed at different redshifts, in various morphological, and environmental domains, and is key to understanding the underlying relations between a galaxy budget of cold gas and its stellar content. Euclid Quick Data Release 1 (Q1) gives us the opportunity to investigate this fundamental relation in galaxy formation and evolution. We complement the Euclid release with public IRAC observations of the Euclid Deep Fields, improving the quality of recovered photometric redshifts, stellar masses, and SFRs, as is shown both with simulations and a comparison with available spectroscopic redshifts. From Q1 data alone, we recover more than ∼ 30 k galaxies with Mstarwun > 11, giving a precise constraint of the SFMS at the high-mass end. We investigated the SFMS, in a redshift interval between $0.2$ and $3.0$, comparing our results with the existing literature and fitting them with a parameterisation taking into account the presence of a bending of the relation at the high-mass end, depending on the bending mass, M_0. We find good agreement with previous results in terms of M_0 values, and an increasing trend for the relation scatter at higher stellar masses. We also investigate the distribution of physical (e.g. dust absorption, A_V, and formation age) and morphological properties (e.g., Sérsic index and radius) in the SFR--stellar mass plane, and their relation with the SFMS. These results highlight the potential of Euclid in studying the fundamental scaling relations that regulate galaxy formation and evolution in anticipation of the forthcoming Data Release 1.

In this Letter, we report the dark matter search results from the commissioning run (Run0) and the first science run (Run1) of the PandaX-4T experiment. The two datasets were processed with a unified procedure, with the Run1 data treated blindly. The data processing is improved compared to previous work, unifying the low-level signal reconstruction in a wide energy range up to 120 keV. With a total exposure of 1.54  tonne·year, no significant excess of nuclear recoil events is found. The lowest 90% confidence level exclusion on the spin-independent cross section is 1.6×10^{-47}  cm^{2} at a dark matter mass of 40  GeV/c^{2}. Our results represent the most stringent constraint for a dark matter mass above 100  GeV/c^{2}.

We combine near-infrared imaging in two bands from the Hubble Space Telescope with archival observations of molecular gas to study SDSS J160705.16+533558.6 (J1607), an extremely luminous broad-line quasar at z = 3.65 that is also bright in the submillimeter. Via subtraction of the quasar point-spread function, we show that its host galaxy is massive, with a stellar mass of (5.8 ± 3.0) × 10 ^11 M _⊙ , making it comparable to giant early-type galaxies (ETGs) at z ∼ 0. If the supermassive black hole in the quasar is accreting at the Eddington limit, then its mass is 3.5 × 10 ^9 M _⊙ , which is also consistent with local massive ETGs. The host has an extremely high star formation rate of 4300 ± 500 M _⊙ yr ^−1 and a molecular gas mass of (2.4 ± 0.9) × 10 ^10 M _⊙ . The quasar has two companions: one at a projected separation of 11 kpc with a stellar mass of (7.9 ± 5.0) × 10 ^10 M _⊙ but no detected molecular gas and one 6 kpc further away in the same direction with a molecular gas mass of (2.6 ± 1.3) × 10 ^10 M _⊙ but no detected stellar emission. Since neither companion shows evidence for active galactic nucleus activity, this may represent merger-driven quenching, in which the dynamics of the merger strip molecular gas from infalling galaxies. Overall, irrespective of whether the host is merging with the companions, these properties mark J1607 as forming what will become an extremely massive (∼10 ^12 M _⊙ ) galaxy by z = 0.

We conducted a Ka -band (26.1–35 GHz) line survey toward Orion KL using the TianMa 65 m Radio Telescope (TMRT). It is the first blind line survey in the Ka band and achieves a sensitivity at the mK level (1–3 mK at a spectral resolution of ∼1 km s ^−1 ). In total, 592 Gaussian features are extracted. Among them, 257 radio recombination lines (RRLs) are identified. The maximum Δ n of RRLs of H, He, and C are 20, 15, and 5, respectively. Through stacking, we have detected the β lines of ion RRLs (RRLs of C ^+ with the possible contribution of other ions like O ^+ ) for the first time, and a tentative signal of the γ lines of ion RRLs can also be seen on the stacked spectrum. Besides this, 318 other line features were assigned to 37 molecular species, and 10 of these species were not detected in the Q -band survey of TMRT. The vibrationally excited states of nine species were also detected. The emission of most species can be modeled under LTE. A number of transitions of E-CH3OH ( J _2 − J _1 ) display maser effects, which are confirmed by our modeling, and besides the bumping peak at J ∼ 6, there is another peak at J ∼ 13. Methylcyanoacetylene (CH _3 C _3 N) is detected in Orion KL for the first time. This work emphasizes that the Ka band, which was long ignored for spectral line surveys, is very useful for surveying RRLs and molecular lines simultaneously.

Single-dish far-infrared (far-IR) and sub-millimetre (sub-mm) point source catalogues and their connections with catalogues at other wavelengths are of paramount importance. However, due to the large mismatch in spatial resolution, cross-matching galaxies at different wavelengths is challenging. This work aims to develop the next-generation deblended far-IR and sub-mm catalogues and present the first application in the COSMOS field. Our progressive deblending used the Bayesian probabilistic framework known as XID+. The deblending started from the Spitzer/MIPS 24 micron data, using an initial prior list composed of sources selected from the COSMOS2020 catalogue and radio catalogues from the VLA and the MeerKAT surveys, based on spectral energy distribution modelling which predicts fluxes of the known sources at the deblending wavelength. To speed up flux prediction, we made use of a neural network-based emulator. After deblending the 24 micron data, we proceeded to the Herschel PACS (100 160 micron) and SPIRE wavebands (250, 350 500 micron). Each time we constructed a tailor-made prior list based on the predicted fluxes of the known sources. Using simulated far-IR and sub-mm sky, we detailed the performance of our deblending pipeline. After validation with simulations, we then deblended the real observations from 24 to 500 micron and compared with blindly extracted catalogues and previous versions of deblended catalogues. As an additional test, we deblended the SCUBA-2 850 micron map and compared our deblended fluxes with ALMA measurements, which demonstrates a higher level of flux accuracy compared to previous results.We publicly release our XID+ deblended point source catalogues. These deblended long-wavelength data are crucial for studies such as deriving the fraction of dust-obscured star formation and better separation of quiescent galaxies from dusty star-forming galaxies.

We present a plan for sub/millimeter-wave line intensity mapping (LIM) using an imaging spectrograph based on the Terahertz Integral Field Units with Universal Nanotechnology (TIFUUN) architecture. We aim to measure the dust-enshrouded cosmic star formation rate density within the first 2 billion years by conducting LIM observations of ionized carbon [C II] 158 μm and oxygen [O III] 88 μm lines, redshifted to sub/millimeter wavelengths. The proposed imaging spectrograph will simultaneously observe two frequency bands: Band-1 (139-179 GHz) and Band-2 (248-301 GHz). Each band will feature up to ∼100 imaging pixels (spaxels), with each spaxel having 100 spectral channels, providing a modest spectral resolution (R~500). The total number of detectors (voxels) will reach ~20,000. This dual-band configuration will allow simultaneous measurement of key spectral lines, e.g., [C II] 158 μm and [O III] 88 μm lines at z = 10.2 - 12.6, and CO(4-3), (7-6), [C I](1-0) and (2-1) at z = 1.9 - 2.2, enabling cross-correlation analysis. We will develop data-scientific methods to remove atmospheric noise using sparse modeling and to extract signals from the observed data using deep learning.

Galaxy morphology is a powerful diagnostic to assess the realism of cosmological hydrodynamical simulations. Determining the morphology of simulated galaxies requires the generation of synthetic images through 3D radiative transfer post-processing that properly accounts for different stellar populations and interstellar dust attenuation. We use the SKIRT code to generate the TNG50-SKIRT Atlas, a synthetic UV to near-infrared broadband image atlas for a complete stellar-mass selected sample of 1154 galaxies extracted from the TNG50 cosmological simulation at z=0. The images have a high spatial resolution (100 pc) and a wide field of view (160 kpc). In addition to the dust-obscured images, we also release dust-free images and physical parameter property maps with matching characteristics. As a sanity check and preview application we discuss the UVJ diagram of the galaxy sample. We investigate the effect of dust attenuation on the UVJ diagram and find that it affects both the star-forming and the quiescent galaxy populations. The quiescent galaxy region is polluted by younger and star-forming highly inclined galaxies, while dust attenuation induces a separation in inclination of the star-forming galaxy population, with low-inclination galaxies remaining at the blue side of the diagram and high-inclination galaxies systematically moving towards the red side. This image atlas can be used for a variety of other applications, including galaxy morphology studies and the investigation of local scaling relations. We publicly release the images and parameter maps, and we invite the community to use them.

Galaxy sizes correlate with many other important properties of galaxies, and the cosmic evolution of galaxy sizes is an important observational diagnostic for constraining galaxy evolution models. The effective radius is probably the most widely used indicator of galaxy size. We used the TNG50-SKIRT Atlas to investigate the wavelength dependence of the effective radius of galaxies at optical and near-infrared (NIR) wavelengths. We find that, on average, the effective radius in every band exceeds the stellar mass effective radius, and that this excess systematically decreases with increasing wavelength. The optical g-band (NIR Ks-band) effective radius is on average 58% (13%) larger than the stellar mass effective radius. Effective radii measured from dust-obscured images are systematically larger than those measured from dust-free images, although the effect is limited (8.7% in the g-band, 2.1% in the Ks-band). We find that stellar population gradients are the dominant factor (about 80%) in driving the wavelength dependence of the effective radius, and that differential dust attenuation is a secondary factor (20%). Comparing our results to recent observational data, we find offsets in the absolute values of the median effective radii, up to 50% for the population of blue galaxies. We find better agreement in the slope of the wavelength dependence of the effective radius, with red galaxies having a slightly steeper slope than green–blue galaxies. Comparing our effective radii with those of galaxies from the Siena Galaxy Atlas in separate bins in z-band absolute magnitude and g − z colour, we find excellent agreement for the reddest galaxies, but again significant offsets for the blue populations: up to 70% for galaxies around Mz = −21.5. This difference in median effective radius for the bluer galaxies is most probably due to intrinsic differences in the morphological structure of observed and TNG50 simulated galaxies. Finally, we find that the median effective radius in any broadband filter increases systematically with decreasing u − r colour and with increasing galaxy stellar mass, total SFR, sSFR, and dust-to-stellar-mass ratio. For the slope of the wavelength dependence of Re, however, there does not seem to be a systematic, monotonic correlation with any of these global properties.

The assembly of stellar and supermassive black hole (SMBH) mass in elliptical galaxies since z ∼ 1 can help to diagnose the origins of locally observed correlations between SMBH mass and stellar mass. We therefore construct three samples of elliptical galaxies, one at z ∼ 0 and two at 0.7 ≲ z ≲ 2.5, and quantify their relative positions in the M BH − M * plane. Using a Bayesian analysis framework, we find evidence for translational offsets in both stellar mass and SMBH mass between the local sample and both higher-redshift samples. The offsets in stellar mass are small, and consistent with measurement bias, but the offsets in SMBH mass are much larger, reaching a factor of 7 between z ∼ 1 and z ∼ 0. The magnitude of the SMBH offset may also depend on redshift, reaching a factor of ∼20 at z ∼ 2. The result is robust against variation in the high- and low-redshift samples and changes in the analysis approach. The magnitude and redshift evolution of the offset are challenging to explain in terms of selection and measurement biases. We conclude that either there is a physical mechanism that preferentially grows SMBHs in elliptical galaxies at z ≲ 2, or that selection and measurement biases are both underestimated, and depend on redshift.

The Southern Wide-field Gamma-ray Observatory (SWGO) is an international collaboration working on a ground-based gamma-ray observatory that will be located in the southern hemisphere. A crucial step in the analysis is to identify the showers produced by gamma rays and separate them from the abundant background of hadronic showers. In this work, we propose to adapt the observable $S_b$ used successfully to composition studies in the Pierre Auger Observatory to the SWGO detector. This observable takes into account the signal and the position of each triggered detector. It characterizes the shape of the lateral distribution of the signal, which depends on the nature of the primary particle. The value of $S_b$ is therefore suited to identify gamma induced showers and to reject the more frequent hadronic showers. This analysis has been performed using a scaling factor to link the observable $S_b$ between the central and outrigger array. Also we explore how this new observable improves the separation of primary proton and gamma-induced air showers in terms of the merit factor.

Observations have found black holes spanning 10 orders of magnitude in mass across most of cosmic history. The Kerr black hole solution is, however, provisional as its behavior at infinity is incompatible with an expanding universe. Black hole models with realistic behavior at infinity predict that the gravitating mass of a black hole can increase with the expansion of the universe independently of accretion or mergers, in a manner that depends on the black hole’s interior solution. We test this prediction by considering the growth of supermassive black holes in elliptical galaxies over 0 < z ≲ 2.5. We find evidence for cosmologically coupled mass growth among these black holes, with zero cosmological coupling excluded at 99.98% confidence. The redshift dependence of the mass growth implies that, at z ≲ 7, black holes contribute an effectively constant cosmological energy density to Friedmann’s equations. The continuity equation then requires that black holes contribute cosmologically as vacuum energy. We further show that black hole production from the cosmic star formation history gives the value of Ω _Λ measured by Planck while being consistent with constraints from massive compact halo objects. We thus propose that stellar remnant black holes are the astrophysical origin of dark energy, explaining the onset of accelerating expansion at z ∼ 0.7.

We have conducted long-slit spectroscopic observations and analyzed archival radio data for the ultraluminous X-ray source (ULX) NGC 4861 X-1. Our spectral line analysis unveils NGC 4861 X-1 as the fourth ULX situated within an X-ray photoionized nebula, following three previous findings made approximately two decades ago. Remarkably, we discover NGC 4861 X-1 also possesses a radio nebula emitting optically thin synchrotron radiation, which contradicts its X-ray photoionization and raises doubts about the four ULXs being a mere coincidence. Instead of gradually accumulating from different bands bit by bit, our multiband discovery is made all at once. Moreover, we tentatively perceive a faint continuum spectrum of the optical nebula. Further observations are needed to ascertain its radio structures and verify the optical continuum.