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Clecio R. Bom

Publications and source records attributed to Clecio R. Bom.

At least 19 recordsLinked to original sources

Search For a Counterpart to the Subsolar Mass Gravitational Wave Candidate S251112cm

The recent candidate gravitational-wave (GW) alert from a compact object merger involving at least one subsolar mass (SSM) object has prompted questions about their origins. S251112cm is reported by LIGO/Virgo with a false alarm rate of 1 per 6.2 years, nearby luminosity distance $93 \pm 27$ Mpc, and probability of containing a SSM object of 100%. Such a system, if astrophysical, likely did not involve the supersolar neutron stars or black holes invoked to explain kilonovae. One must then also invoke hitherto unobserved and speculative models to produce SSM mergers which may have electromagnetic (EM) counterparts. We introduce a framework which vets and scores candidate counterparts to SSM GW events to inform follow-up in search of any among the zoo of potential EM transients: kilonovae, kilonovae-within-supernovae, super-kilonovae, or AGN flares from binary black hole mergers. We use a suite of telescopes to perform tiling, galaxy-targeted observations, and photometric/spectroscopic follow-up of promising candidates. In near-real time, we ingest candidates reported by the community, including some of the first observations reported by the Vera C. Rubin Observatory. We vet and score a total of 456 candidates, including 67 from Rubin, but find no likely counterpart. We nonetheless highlight candidates which demonstrate the ability of our framework to distinguish between different transient types and describe strategies to maximize the chances of detecting a counterpart to the next SSM event. Our framework will be implemented in the forthcoming Multimessenger Tool for Rapid Object Vetting and Examination (TROVE).

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Physics-guided discovery of dynamical dark-energy equations of state through iterative AI reasoning

Phenomenological model building has traditionally relied on human reasoning: equations are proposed from theoretical intuition, analogy, or empirical convenience, and only then tested against data. Here we show that this cycle can be recast as an iterative AI reasoning process for dynamical dark energy. Our framework uses a large language model to propose equations of state together with cosmological rationales, grounded by retrieval from the dark-energy literature and refined through autonomous evaluation. Each candidate is embedded in a cosmological model, optimized against observations, and assessed using likelihood performance and theoretical consistency. An independent language-model critic scores the physical motivation, novelty, clarity, stability and implementation validity of both the equation and its rationale, allowing subsequent proposals to evolve jointly in mathematical structure and physical reasoning. Applied to cosmological data combinations including supernovae, baryon acoustic oscillations and Planck likelihoods, the framework identifies two parameterizations that, to the best of our knowledge, have not previously been explored and that are competitive with established forms. For Pantheon+ supernovae, DESI DR2 baryon acoustic oscillations and the full Planck 2018 temperature, polarization, and lensing likelihoods, the best AI-selected model attains larger Bayesian evidence than the traditional parameterizations considered here by more than one unit. These results show that AI-guided reasoning can complement physical model building by proposing and evaluating interpretable phenomenological parameterizations for dynamical dark energy.

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SLSim: a strong lensing population simulation package

Gravitational lensing offers unique insights into cosmology by bending light around massive objects. Strong gravitational lensing, in particular, produces magnified and often multiple images of distant sources, crucial for precise cosmological measurements and understanding the distribution of dark matter in the universe. Current studies are limited by the number of strong gravitational lenses. From upcoming cosmological surveys, we anticipate observing a several orders of magnitude increase in the number of lenses, for both static and transient phenomena. However, detecting and analyzing these events from vast surveys like Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) presents significant challenges. To prepare for these challenges, we introduce SLSim, a versatile simulation tool tailored for the Vera C. Rubin Observatory. SLSim integrates advanced astrophysical models with computational efficiency to generate synthetic strong lens populations under realistic observational conditions. SLSim simulates static and variable lensing scenarios, essential for cosmological studies, training and testing lens search and data analysis pipelines. This paper details SLSim,'s design and implementation, emphasizing its modularity and capabilities across various astrophysical regimes. Validation against observational data and existing simulations confirms SLSim's accuracy in reproducing observed lensing phenomena. SLSim is publicly available at https://github.com/LSST-strong-lensing/slsim, and we anticipate continued development and expansion of its capabilities. Users are encouraged to check the repository for updates and to contribute to ongoing community efforts in strong lensing simulations.

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Probing the origin of the kilonova candidate GRB 230307A: analysis of host galaxy and offset

We investigate the host galaxy of the long gamma-ray burst GRB 230307A, which is associated with a kilonova candidate likely produced by a binary neutron-star (BNS) merger. The transient occurred at a projected offset of ~40 kpc from its host. We consider two explanations for this large distance: (i) NSs that merge inside a remote globular cluster, or (ii) a BNS that formed in the disk whose orbit was strongly modified by the NS natal kicks. Using JWST data and comparisons with known globular clusters, we show that a globular-cluster origin is unlikely. Using JWST and MUSE data, we derive the host galaxy morphology, stellar mass, estimate the atomic gas (HI+He) contribution, and the host rotation curve. Assuming an NFW halo and applying Bayesian inference, we obtain a mass model for the host. From this model, we compute the time required for a disk-formed BNS, with a given natal kick, to reach the observed offset while marginalizing over uncertainties and over the initial position in the disk. We compare these results with BNS-merger simulations from a population-synthesis code combined with stellar evolutionary tracks, which provide the coalescence time and kick velocity for each realization. The two approaches have an overlap in the kick-time diagram, but only 0.1% of the simulated systems is compatible with the galaxy-mass model. This indicates that a disk origin is possible, but requires fine-tuned conditions for the kilonova to occur at such a large distance from the host galaxy.

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A second-generation star in a relic dwarf galaxy

Stars that contain only trace amounts of elements heavier than helium, referred to as having low "metallicity", preserve the chemical fingerprints of the first generation of stars and supernovae. In the Milky Way, the lowest metallicity stars show an extreme over-abundance of carbon relative to other elements, which has been hypothesized to be a unique result of the first low-energy supernovae. However, the origin of this signature has remained a mystery, since no such stars have been discovered in the ancient dwarf galaxies where they are thought to have formed. Here, we present observations of a star in the >10 billion year old ultra-faint dwarf galaxy Pictor II, that shows the lowest iron and calcium abundances outside the Milky Way (<1/43,000th solar and ~1/160,000th solar), with a factor of >3000x relative carbon enhancement. As the first unambiguous second-generation star in a relic dwarf galaxy, this object demonstrates that carbon-enhanced second-generation stars can originate in primordial small-scale systems. This star supports the hypothesis that carbon-enhancement is produced by low-energy-supernovae, since the yields of energetic supernovae are harder to retain in small-scale environments. This key local signature of chemical enrichment by the first stars traces a regime inaccessible to current high-redshift observations, which cannot detect the early enrichment of the smallest galaxies.

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Caught in the web: galaxy mergers along cosmic filaments

Galaxy clusters grow through the accretion of galaxies from groups, filaments, and other clusters. During this process, galaxies may undergo pre-processing in lower-density environments, where galaxy-galaxy mergers and other interactions can significantly alter their properties prior to cluster infall. We investigate the role of galaxy mergers in the pre-processing of galaxies prior to cluster infall by studying the spatial distribution of mergers across the cosmic web. We use a sample of 43,922 galaxies targeted by the 4MOST CHANCES survey in and around 33 low-redshift clusters (z < 0.07). Using Zoobot, a deep-learning framework trained on Galaxy Zoo data, we identify 698 galaxy mergers. We measure their distances to cosmic web filaments and compare them with those of non-merging galaxies. We find that galaxy mergers are significantly closer to filaments than the non-merging galaxy population, with this trend being strongest beyond the cluster virial radius. This suggests that filaments provide conditions conducive to mergers, possibly moderating relative velocities and enhancing gas availability. Our findings support a scenario in which filaments play a key role in transforming galaxies through pre-processing by promoting mergers before they enter cluster cores where star formation quenches.

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Opportunities in AI/ML for the Rubin LSST Dark Energy Science Collaboration

The Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) will produce unprecedented volumes of heterogeneous astronomical data (images, catalogs, and alerts) that challenge traditional analysis pipelines. The LSST Dark Energy Science Collaboration (DESC) aims to derive robust constraints on dark energy and dark matter from these data, requiring methods that are statistically powerful, scalable, and operationally reliable. Artificial intelligence and machine learning (AI/ML) are already embedded across DESC science workflows, from photometric redshifts and transient classification to weak lensing inference and cosmological simulations. Yet their utility for precision cosmology hinges on trustworthy uncertainty quantification, robustness to covariate shift and model misspecification, and reproducible integration within scientific pipelines. This white paper surveys the current landscape of AI/ML across DESC's primary cosmological probes and cross-cutting analyses, revealing that the same core methodologies and fundamental challenges recur across disparate science cases. Since progress on these cross-cutting challenges would benefit multiple probes simultaneously, we identify key methodological research priorities, including Bayesian inference at scale, physics-informed methods, validation frameworks, and active learning for discovery. With an eye on emerging techniques, we also explore the potential of the latest foundation model methodologies and LLM-driven agentic AI systems to reshape DESC workflows, provided their deployment is coupled with rigorous evaluation and governance. Finally, we discuss critical software, computing, data infrastructure, and human capital requirements for the successful deployment of these new methodologies, and consider associated risks and opportunities for broader coordination with external actors.

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Symbolic Regression Is All You Need: From Simulations to Scaling Laws in Binary Neutron Star Mergers

Gravitational wave sources with electromagnetic counterparts have highlighted the need for predictive, interpretable models linking the parameters of compact binary systems to post-merger remnants and mass outflows. In this work, we explore AI-driven symbolic regression (SR) frameworks to derive updated analytical relations for disk ejecta mass in binary neutron star mergers, trained on state-of-the-art numerical relativity simulations. Our method reveals a set of compact equations that outperform existing fitting formulae across multiple statistical metrics while remaining physically interpretable. Notably, SR also enables alternative predictor sets (e.g., $\{M_1,M_2,\tildeΛ\}$) that match or exceed the accuracy of models relying solely on compactness of the lightest neutron star ($C_1$), enabling new parameter constraints from electromagnetic observations. Unlike traditional black-box machine learning models, these closed-form expressions generalize robustly to regions of the parameter space not represented in the training data, offering a physics-informed tool for multimessenger observations and constraints on the neutron star equation of state.

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Optimizing Kilonova Searches: A Case Study of the Type IIb SN 2025ulz in the Localization Volume of the Low-Significance Gravitational Wave Event S250818k

Kilonovae, the ultraviolet/optical/infrared counterparts to binary neutron star mergers, are an exceptionally rare class of transients. Optical follow-up campaigns are plagued by contaminating transients, which may mimic kilonovae, but do not receive sufficient observations to measure the full photometric evolution. In this work, we present an analysis of the multi-wavelength dataset of supernova (SN) 2025ulz, a proposed kilonova candidate following the low-significance detection of gravitational waves originating from the potential binary neutron star merger S250818k. Despite an early rapid decline in brightness, our multi-wavelength observations of SN 2025ulz reveal that it is a type IIb supernova. As part of this analysis, we demonstrate the capabilities of a novel quantitative scoring algorithm to determine the likelihood that a transient candidate is a kilonova, based primarily on its 3D location and light curve evolution. We also apply our scoring algorithm to other transient candidates in the localization volume of S250818k and find that, at all times after the discovery of SN 2025ulz, there are $\geq 4$ candidates with a score comparable to SN 2025ulz, indicating that the kilonova search may have benefited from the additional follow-up of other candidates. During future kilonova searches, this type of scoring algorithm will be useful to rule out contaminating transients in real time, optimizing the use of valuable telescope resources.

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The DELVE Quadruple Quasar Search I. A Lensed Low Luminosity AGN

A quadruply lensed source, J125856.3-031944, has been discovered using the DELVE survey and WISE W1 - W2 colors. Followup direct imaging carried out with the Magellan Baade 6.5 m telescope is analyzed, as is spectroscopy from the 2.5 m Nordic Optical Telescope. The lensed image configuration is kite-like, with the major axis of the lensing galaxy along the symmetry axis of the kite, and with the faintest image at its tail. Redward of 6000 AA the tail image is strongly blended with the lensing galaxy. The Sloan g direct imaging carried out with Magellan permits deblending. As the lensed image configuration is nearly circular, simple models give high predicted magnifications for all four images. The source's narrow emission lines at redshift z=2.225 and low intrinsic luminosity qualify it as a Type 2 AGN. The Magellan image shows a substantial residual that suggests a second lensing galaxy.

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DELVE-DEEP Survey: The Faint Satellite System of NGC 55

We report the first comprehensive census of the satellite dwarf galaxies around NGC 55 ($2.1$ Mpc) as a part of the DECam Local Volume Exploration DEEP (DELVE-DEEP) survey. NGC 55 is one of four isolated, Magellanic analogs in the Local Volume around which DELVE-DEEP aims to identify faint dwarfs and other substructures. We employ two complementary detection methods: one targets fully resolved dwarf galaxies by identifying them as stellar over-densities, while the other focuses on semi-resolved dwarf galaxies, detecting them through shredded unresolved light components. As shown through extensive tests with injected galaxies, our search is sensitive to candidates down to $M_V \lesssim -6.6$ and surface brightness $μ\lesssim 28.5$ mag arcsec$^{-2}$, and $\sim 80\%$ complete down to $M_V \lesssim -7.8$. We do not report any new confirmed satellites beyond two previously known systems, ESO 294-010 and NGC 55-dw1. We construct the satellite luminosity function of NGC 55 and find it to be consistent with the predictions from cosmological simulations. As one of the first complete luminosity functions for a Magellanic analog, our results provide a glimpse of the constraints on low-mass-host satellite populations that will be further explored by upcoming surveys, such as the Vera C. Rubin Observatory's Legacy Survey of Space and Time.

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The NGC3109 Satellite System: The First Systematic Resolved Search for Dwarf Galaxies Around a SMC-mass Host

We report the results of the deepest search to date for dwarf galaxies around NGC3109, a barred spiral galaxy with a mass similar to that of the Small Magellanic Cloud (SMC), using a semi-automated search method. Using the Dark Energy Camera (DECam), we survey a region covering a projected distance of $\sim$70 kpc of NGC 3109 ($D$ = 1.3 Mpc, $R_\mathrm{vir}\sim$ 90 kpc, $M\sim10^8M_\ast$) as part of the MADCASH and DELVE-DEEP programs. Through our resolved and newly designed semi-resolved searches, we successfully recover the known satellites Antlia and Antlia B. We identified a promising candidate, which was later confirmed to be a background dwarf through deep follow-up observations. Our detection limits are well defined, with the sample $\sim 80\%$ complete down to $M_V\sim-$8.0 , and includes detections of dwarf galaxies as faint as $M_V\sim-$6.0. This is the first comprehensive study of a satellite system through resolved star around an SMC mass host. Our results show that NGC 3109 has more bright ($M_V\sim-$9.0) satellites than the mean predictions from cold dark matter (CDM) models, but well within the host-to-host scatter. A larger sample of LMC/SMC-mass hosts is needed to test whether or not the observations are consistent with current model expectations.

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Deep Photometric Observations of Ultra-Faint Milky Way Satellites Centaurus I and Eridanus IV

We present deep Magellan$+$Megacam imaging of Centaurus I (Cen I) and Eridanus IV (Eri IV), two recently discovered Milky Way ultra-faint satellites. Our data reach $\sim2-3$ magnitudes deeper than the discovery data from the DECam Local Volume Exploration (DELVE) Survey. We use these data to constrain their distances, structural properties (e.g., half-light radii, ellipticity, and position angle), and luminosities. We investigate whether these systems show signs of tidal disturbance, and identify new potential member stars using Gaia EDR3. Our deep color-magnitude diagrams show that Cen I and Eri IV are consistent with an old ($τ\sim 13.0$ Gyr) and metal-poor ($\text{[Fe/H]}\le-2.2$) stellar population. We find Cen I to have a half-light radius of $r_{h}=2.60\pm0.30'$ ($90.6\pm11$ pc), an ellipticity of $ε=0.36\pm0.05$, a distance of $D=119.8\pm4.1$ kpc ($m-M=20.39\pm0.08$ mag), and an absolute magnitude of $M_{V}=-5.39\pm0.19$. Similarly, Eri IV has $r_{h}=3.24\pm0.48'$ ($65.9\pm10$ pc), $ε=0.26\pm0.09$, $D=69.9\pm3.6$ kpc ($m-M=19.22\pm0.11$ mag), and $M_{V}=-3.55\pm0.24$. These systems occupy a space on the size-luminosity plane consistent with other known Milky Way dwarf galaxies which supports the findings from our previous spectroscopic follow-up. Cen I has a well-defined morphology which lacks any clear evidence of tidal disruption, whereas Eri IV hosts a significant extended feature with multiple possible interpretations.

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Streams, Shells, and Substructures in the Accretion-Built Stellar Halo of NGC 300

We present deep optical observations of the stellar halo of NGC 300, an LMC-mass galaxy, acquired with the DEEP sub-component of the DECam Local Volume Exploration survey (DELVE) using the 4 m Blanco Telescope. Our resolved star analysis reveals a large, low surface brightness stellar stream ($M_{V}\sim-8.5$; [Fe/H] $= -1.4\pm0.15$) extending more than 40 kpc north from the galaxy's center. We also find other halo structures, including potentially an additional stream wrap to the south, which may be associated with the main stream. The morphology and derived low metallicities of the streams and shells discovered surrounding NGC 300 are highly suggestive of a past accretion event. Assuming a single progenitor, the accreted system is approximately Fornax-like in luminosity, with an inferred mass ratio to NGC 300 of approximately $1:15$. We also present the discovery of a metal-poor globular cluster ($R_{\rm{proj}}=23.3$~kpc; $M_{V}=-8.99\pm0.16$; [Fe/H] $\approx-1.6\pm0.6$) in the halo of NGC 300, the furthest identified globular cluster associated with NGC 300. The stellar structures around NGC 300 represent the richest features observed in a Magellanic Cloud analog to date, strongly supporting the idea that accretion and subsequent disruption is an important mechanism in the assembly of dwarf galaxy stellar halos.

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Rubin ToO 2024: Envisioning the Vera C. Rubin Observatory LSST Target of Opportunity program

The Legacy Survey of Space and Time (LSST) at Vera C. Rubin Observatory is planned to begin in the Fall of 2025. The LSST survey cadence has been designed via a community-driven process regulated by the Survey Cadence Optimization Committee (SCOC), which recommended up to 3% of the observing time to carry out Target of Opportunity (ToO) observations. Experts from the scientific community, Rubin Observatory personnel, and members of the SCOC were brought together to deliver a recommendation for the implementation of the ToO program during a workshop held in March 2024. Four main science cases were identified: gravitational wave multi-messenger astronomy, high energy neutrinos, Galactic supernovae, and small potentially hazardous asteroids possible impactors. Additional science cases were identified and briefly addressed in the documents, including lensed or poorly localized gamma-ray bursts and twilight discoveries. Trigger prioritization, automated response, and detailed strategies were discussed for each science case. This document represents the outcome of the Rubin ToO 2024 workshop, with additional contributions from members of the Rubin Science Collaborations. The implementation of the selection criteria and strategies presented in this document has been endorsed in the SCOC Phase 3 Recommendations document (PSTN-056). Although the ToO program is still to be finalized, this document serves as a baseline plan for ToO observations with the Rubin Observatory.

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Standard Siren Cosmology with Gravitational Waves from Binary Black Hole Mergers in Active Galaxy Nuclei

The detection of gravitational waves (GW) with an electromagnetic counterpart enabled the first Hubble Constant $H_0$ measurement through the standard siren method. Current constraints suggest that $\sim 20-30\%$ of LIGO/Virgo/KAGRA (LVK) Binary Black Hole (BBH) mergers might occur in Active Galactic Nuclei (AGN) disks. The claim for a possible association of several BBH mergers with flaring AGNs suggests that cosmological analyses using BBH and AGNs might be promising. We explore standard siren analyses through a method that takes into account the presence of background flaring AGNs, without requiring a unique host galaxy identification, and apply it to realistic GW simulations. Depending on the fraction of LVK BBHs that induce flares, we expect to constrain $H_0$ at the $\sim 6-7\%$ ($\sim 4-5\%$) precision with $\sim 2-3$ years or $\sim 160-240$ events ($\sim 1$ year or $500$ events) of LVK at design (A+) sensitivity, assuming that systematic BBH follow-up searches are performed. %Assuming a more restrictive $Ω_{\rm m}$ prior and that at least $20\%$ of BBHs produces detectable flares, we may reach a $3\%$ ($2\%$) precision in $H_0$ after 2 (1) year of LVK at design (A+) sensitivity. We also show that in a scenario where only $\sim 1\%$ of the BBHs induce detectable flares it is possible to achieve an $H_0$ precision from $7.5\%$ to $15\%$ with $\sim 240$ events. In addition, a $\sim 5-27\%$ precision is achievable with complete AGN catalogs and 1 year of LVK run, without the need of any flare identification.

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The Fourth S-PLUS Data Release: 12-filter photometry covering $\sim3000$ square degrees in the southern hemisphere

The Southern Photometric Local Universe Survey (S-PLUS) is a project to map $\sim9300$ sq deg of the sky using twelve bands (seven narrow and five broadbands). Observations are performed with the T80-South telescope, a robotic telescope located at the Cerro Tololo Observatory in Chile. The survey footprint consists of several large contiguous areas, including fields at high and low galactic latitudes, and towards the Magellanic Clouds. S-PLUS uses fixed exposure times to reach point source depths of about $21$ mag in the $griz$ and $20$ mag in the $u$ and the narrow filters. This paper describes the S-PLUS Data Release 4 (DR4), which includes calibrated images and derived catalogues for over 3000 sq deg, covering the aforementioned area. The catalogues provide multi-band photometry performed with the tools \texttt{DoPHOT} and \texttt{SExtractor} -- point spread function (\PSF) and aperture photometry, respectively. In addition to the characterization, we also present the scientific potential of the data. We use statistical tools to present and compare the photometry obtained through different methods. Overall we find good agreement between the different methods, with a slight systematic offset of 0.05\,mag between our \PSF and aperture photometry. We show that the astrometry accuracy is equivalent to that obtained in previous S-PLUS data releases, even in very crowded fields where photometric extraction is challenging. The depths of main survey (MS) photometry for a minimum signal-to-noise ratio $S/N = 3$ reach from $\sim19.5$ for the bluer bands to $\sim21.5$ mag on the red. The range of magnitudes over which accurate \PSF photometry is obtained is shallower, reaching $\sim19$ to $\sim20.5$ mag depending on the filter. Based on these photometric data, we provide star-galaxy-quasar classification and photometric redshift for millions of objects.

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Kilonova Spectral Inverse Modelling with Simulation-Based Inference: An Amortized Neural Posterior Estimation Analysis

Kilonovae represent a category of astrophysical transients, identifiable as the electromagnetic observable counterparts associated with the coalescence events of binary systems comprising neutron stars and neutron star-black hole pairs. They act as probes for heavy-element nucleosynthesis in astrophysical environments. These studies rely on inference of the physical parameters (e.g., ejecta mass, velocity, composition) that describe kilonovae based on electromagnetic observations. This is a complex inverse problem typically addressed with sampling-based methods such as Markov-chain Monte Carlo (MCMC) or nested sampling algorithms. However, repeated inferences can be computationally expensive due to the sequential nature of these methods. This poses a significant challenge to ensuring the reliability and statistical validity of the posterior approximations and, thus, the inferred kilonova parameters themselves. We present a novel approach: Simulation-Based Inference (SBI) using simulations produced by KilonovaNet. Our method employs an ensemble of Amortized Neural Posterior Estimation (ANPE) with an embedding network to directly predict posterior distributions from simulated spectral energy distributions (SEDs). We take advantage of the quasi-instantaneous inference time of ANPE to demonstrate the reliability of our posterior approximations using diagnostics tools, including coverage diagnostic and posterior predictive checks. We further test our model with real observations from AT2017gfo, the only kilonova with multi-messenger data, demonstrating agreement with previous likelihood-based methods while reducing inference time down to a few seconds. The inference results produced by ANPE appear to be conservative and reliable, paving the way for testable and more efficient kilonova parameter inference.

astro-ph.HE