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Mustapha Ishak

Publications and source records attributed to Mustapha Ishak.

At least 19 recordsLinked to original sources

Model-Independent Measurement of Baryon Gas Fractions through Galaxy-Galaxy Lensing and the Kinematic Sunyaev-Zel'dovich Effect

Baryon feedback is a leading source of systematic uncertainty for cosmology from weak lensing, but measurements of the gas distribution around galaxies have largely relied on parametric profile models or simulation-calibrated frameworks. We present model independent measurements of the radial gas fraction profile around galaxies, combining galaxy-galaxy lensing and kinematic Sunyaev-Zel'dovich (kSZ) effect. We introduce a method that applies the same radial $ΔΣ$ aperture filter to both the galaxy-galaxy lensing shear field and the velocity-weighted kSZ temperature maps; their ratio directly yields $ΔΣ$ filtered gas fraction $f_{\rm gas}(R)$, the ratio of ionized gas to total matter as a function of projected radius. We apply this approach to DESI DR2 Bright Galaxy Survey (BGS, $\bar{z}\approx0.26$) and Luminous Red Galaxy (LRG, $0.4<z<1.1$) samples, using ACT DR6 component-separated CMB maps for kSZ and the HSC Year 3 shear catalog for weak lensing. After correcting for ACT beam suppression using a simulation-calibrated compensation factor, we detect baryon depletion relative to the cosmic mean baryon fraction at SNR = 17.1 (BGS) and SNR = 15.8 (LRG bin 1). Comparison with six hydrodynamical simulations from the Illustris, IllustrisTNG, SIMBA, and FLAMINGO suites shows that no single feedback prescription reproduces the observed radial gas distribution across all scales, with the measurements falling between the strongest (Illustris-1) and weaker prescriptions. We caution that comparisons between the South Galactic Cap (SGC) and North Galactic Cap (NGC) show evidence of unexplained residual systematics in kSZ in one redshift bin. The ratio is robust against splits by stellar mass and satellite versus centrals. These results establish $ΔΣ$ filtering of kSZ versus weak lensing signal as a model-independent probe of the baryon distribution around galaxies.

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The Cocytos Stream: A Disrupted Globular Cluster from our Last Major Merger?

The census of stellar streams and dwarf galaxies in the Milky Way provides direct constraints on galaxy formation models and the nature of dark matter. The DESI Milky Way survey -- with a footprint of $14{,}000$ deg$^2$ and a depth of $r<19$ mag -- delivers the largest sample of distant metal-poor stars compared to previous optical fiber-fed spectroscopic surveys. This makes DESI an ideal survey to search for previously undetected streams and dwarf galaxies. We present a detailed characterization of the Cocytos stream, which was re-discovered using a clustering analysis with a catalog of giants in the DESI year 3 data, supplemented with Magellan/MagE spectroscopy. Our analysis reveals a relatively metal-rich ([Fe/H]$=-1.3$) and thick stream (width$=1.6^\circ$) at a heliocentric distance of $\approx 25$ kpc, with an internal velocity dispersion of $6$--$9$ km s$^{-1}$. The stream's metallicity, radial orbit, and proximity to the Virgo stellar overdensities suggest that it is most likely a disrupted globular cluster that came in with the Gaia-Enceladus merger. We also confirm its association with the Pyxis globular cluster. Our result showcases the ability of wide-field spectroscopic surveys to kinematically discover faint disrupted dwarfs and clusters, enabling constraints on the dark matter distribution in the Milky Way.

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The Power of DESI for Photometric Redshift Calibration: A Case Study with KiDS-1000

Accurate redshift estimates are a critical requirement for weak lensing surveys and one of the main uncertainties in constraints on dark energy and large-scale cosmic structure. In this paper, we study the potential to calibrate photometric redshift (photo-z) distributions for gravitational lensing using the Dark Energy Spectroscopic Instrument (DESI). Since beginning its science operations in 2021, DESI has collected more than 50 million redshifts, adding about one million monthly. In addition to its large-scale structure samples, DESI has also acquired over 256k high-quality spectroscopic redshifts (spec-zs) in the COSMOS and XMM and VVDS fields. This is already a factor of 3 larger than previous spec-z calibration compilations in these two regions. Here, we explore calibrating photo-zs for the subset of KiDS-1000 galaxies that fall into joint self-organizing map (SOM) cells overlapping the DESI COSMOS footprint using the DESI COSMOS observations. Estimating the redshift distribution in KiDS-1000 with the new DESI data, we find broad consistency with previously published results while also detecting differences in the mean redshift in some tomographic bins with an average shifts of Delta Mean(z) = -0.028 in the mean and Delta Median(z) = +0.011 in the median across tomographic bins. However, we also find that incompleteness per SOM cell, i.e., groups of galaxies with similar colors and magnitudes, can modify n(z) distributions. Finally, we comment on the fact that larger photometric catalogs, aligned with the DESI COSMOS and DESI XMM and VVDS footprints, would be needed to fully exploit the DESI dataset and would extend the coverage to nearly eight times the area of existing 9-band photometry.

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The optimal redshift for dark energy II: application to cosmological data and the evidence for the phantom crossing of the CPL equation of state

Recent results from DESI and other cosmological datasets have indicated a preference for dynamical dark energy, with a time-evolving equation of state (EOS), $w(z)$. Furthermore, analyses using the CPL parameterization give an EOS with a phantom crossing of the $w(z)=-1$ line. In a companion paper-I, we assumed the CPL parameterization and its generalization, and introduced the formalism of the optimal scale factor (or redshift), a quantity designed to simultaneously maximize the distance from the cosmological constant value of $-1$ and to minimize the uncertainty on the EOS, thereby maximizing the tension with the cosmological constant at that specific redshift for a given dataset combination. In this paper-II, we apply the optimal-redshift formalism to available baryon acoustic oscillation, Cosmic Microwave Background, and supernova dataset combinations, with a particular focus on the phantom-line crossing within CPL. Motivated by the relatively low significance of previous constraints on the EOS in the region below the phantom line, we calculate the optimal redshift for a variety of dataset combinations to identify those that best constrain departures from $w(z)=-1$ before and after the crossing. We find combinations and corresponding optimal redshifts for which $w(z)$ lies below the ``$-1$'' line with new significance levels reaching $3.01$--$3.22σ$ before the crossing point, and $3.30$--$3.55σ$ above ``$-1$" after the crossing. Our focus in this work is the application of a new framework that maximizes the significance of the phantom-crossing signal within CPL using currently available datasets. Determining whether this crossing is effective or intrinsic, and identifying the underlying microphysical models, constitute separate questions from the aim of the present work and remain important directions for future investigation, further motivated by our findings. Abridged.

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The optimal redshift for dark energy I: formalism and interpretation

We introduce the concept of the optimal redshift for dark energy, a statistically motivated redshift at which departures of the dark-energy equation of state (EOS) from the cosmological-constant value are tested most effectively. Within a generalized CPL parameterization, we derive an analytic expression for the optimal redshift by maximizing the separation of the EOS from $w=-1$ relative to the corresponding uncertainty. We establish the optimal redshift relationship to the phantom-crossing and pivot redshifts. As an illustration, we apply the formalism to the dataset combination of DESI DR2 BAO measurements, the DES Year-6 independent BAO measurement, and the recalibrated DES-Dovekie supernova sample. Adopting the null hypothesis $\mathcal{H}_0:w(a_{\rm opt})=-1$, we find a tension of ~$2.8σ$ with the cosmological-constant prediction at the optimal redshift, compared with ~$2.6σ$ at the pivot redshift, despite the latter having a smaller EOS uncertainty. This behavior reflects the specific design of the optimal redshift to maximize the statistical significance of a departure of the EOS from the -1 value of the $Λ$CDM model. We further provide statistical and geometrical interpretations of the optimum. In the CPL parameter space, the pivot corresponds to the projection that minimizes the variance of the equation of state, whereas the optimum maximizes its squared-distance from the cosmological-constant value over its variance. While the optimum is dataset and parameterization dependent, the underlying optimization principle and definition of the optimal redshift can be extended beyond the CPL framework. Future applications to DESI, Rubin LSST, Euclid, Roman Space Telescope, and other Stage-IV dark-energy surveys appear particularly promising.

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Luminosity function of quasars at $1.0<z<3.5$ from SDSS and DESI

We present a study of the evolution of type 1 quasars at $1.0<z<3.5$, covering the peak epoch of quasar activity. The quasar evolution has been extensively explored by a variety of previous works and the derived quasar luminosity functions (QLFs) are not well consistent with each other, presumably due to the complexities introduced by different quasar selection techniques and associated completeness corrections. We use a new strategy to construct QLFs based on a library of all known quasars. We focus on a wide region of $\sim$1700 deg$^2$ and a deep field of $\sim$265 deg$^2$ that have rich spectroscopic data primarily from SDSS and DESI. We then apply traditional color cuts in the rest-frame UV/optical to select quasar candidates and use the quasar library to identify them. Our final sample consists of 62,426 quasars at $1.0<z<3.5$, with a high completeness ($\sim$96%) and a high purity ($\sim$93%) in the color selection. Simple color cuts can potentially minimize selection biases for the study of quasar evolution. We derive binned QLFs and characterize them using a double power-law model. Sample incompleteness and contamination are considered as part of the uncertainties in the calculation. Compared to previous results, our QLFs are slightly higher at the faint end, and also higher at the bright end at $2.5<z<3.5$. The QLFs suggest that the quasar evolution at $1.0 < z < 2.5$ can be well described by the pure luminosity evolution model, while at $2.5 < z < 3.5$, it can be described by either the pure luminosity evolution or the pure density evolution model.

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Frequentist Cosmological Constraints from Full-Shape Clustering Measurements in DESI DR1

We present a frequentist analysis of clustering measurements from Data Release 1 of the Dark Energy Spectroscopic Instrument (DESI) using the standard profile likelihood method. While Bayesian inferences for effective field theory models of galaxy clustering can be highly sensitive to prior choices for extended cosmological models, frequentist inferences are not susceptible to such effects. We compare frequentist and Bayesian constraints for the parameter set $\{σ_8, H_0, Ω_{\rm{m}}, w_0, w_a\}$ using the full-shape power spectrum multipoles, post-reconstruction baryon acoustic oscillation (BAO) measurements, and external datasets from the CMB and type Ia supernovae measurements. The frequentist confidence intervals are significantly shifted relative to the Bayesian credible intervals for the $w_0w_a$CDM model, unless supernovae data are included. When DESI full-shape and BAO data are fit jointly, we obtain the following $1σ$ frequentist confidence intervals for $Λ$CDM ($w_0w_a$CDM): $σ_8 = 0.863^{+0.048}_{-0.040} , \ H_0 = 68.96^{+0.81}_{-0.80} \ \rm{km \ s^{-1}Mpc^{-1}} , \ Ω_{\rm{m}} = 0.3034\pm0.0110$ ($σ_8 = 0.782^{+0.060}_{-0.036} , \ H_0 = 63.7^{+4.2}_{-2.0} \ \rm{km \ s^{-1}Mpc^{-1}} , \ Ω_{\rm{m}} = 0.378^{+0.024}_{-0.047} , \ w_0 = -0.16^{+0.10}_{-0.50} , \ w_a = -3.0^{+1.7}_{}$), corresponding to 0.8$σ$, 0.3$σ$, 0.7$σ$ (2.1$σ$, 4.1$σ$, 6.5$σ$, 6.3$σ$, 6.6$σ$) shifts between the maximum likelihood estimate and the Bayesian posterior mean for $Λ$CDM ($w_0w_a$CDM) respectively.

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Cosmic Pairs: A DESI Census of Dual and Offset AGN as Precursors to Massive Black Hole Binaries

We present a systematic census of dual and offset active galactic nuclei (AGN) using spectroscopic data from the first data release (DR1) of the Dark Energy Spectroscopic Instrument (DESI). After correcting for observational systematics, our final sample contains $>7,000$ dual AGN and 27,000 galaxy pairs containing one AGN over the redshift range $0 \lesssim z \lesssim 3.6$. This sample expands the known dual AGN sample by $\sim 1-2$ orders of magnitude at $0.2 \lesssim z \lesssim 0.4$, includes $\sim 50$ dwarf dual AGN candidates in a regime where only a handful were previously known, and triples the census at $z>2$. Dual AGN are preferentially found at small separations, consistent with merger-driven triggering of AGN activity. The two members of a pair differ in their star formation response: the more massive (primary) host changes little with separation, while the less massive (secondary) lies $\sim 0.3$ dex above matched inactive and one-AGN companions at the same projected separation in main-sequence offset. Using ASTRID simulations, we predict that the fraction of DESI dual AGN whose central black holes will merge by $z \sim 0$ increases with redshift, reaching $\sim 76\%$ by $z \sim 2$, while the fraction producing LISA-detectable mergers peaks at $\sim 37\%$ near $z \sim 0.9$. These results provide the largest uniformly selected spectroscopic sample of kpc-scale dual and offset AGN candidates from a single survey, connecting their host-galaxy and AGN demographics to the progenitor population of massive black hole mergers detectable by LISA.

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Alleviating prior dependencies for DESI DR1 clustering fits through reparameterization

Bayesian analyses of the full-shape clustering of Dark Energy Spectroscopic Instrument (DESI) Data Release 1 (DR1) exhibit prior-volume projection effects, whereby weakly constrained nuisance parameters of the Effective Field Theory of Large Scale Structure (EFTofLSS) shift marginalized cosmological posteriors away from the posterior maximum. We reanalyze DESI DR1 power spectrum multipoles using two complementary mitigation strategies: (i) nonlinear orthogonalization to decorrelate nuisance and cosmological parameter priors, and (ii) a fully reparameterization-invariant Jeffreys prior over all EFTofLSS coefficients, evaluated on-the-fly via closed-form Jacobians. Including data from DESI, Big-Bang Nuclesynthesis and a constraint on $n_{\mathrm{s}}$, baseline priors lead to multi-$σ$ projection in the Hubble parameter $H_{0}$ and dark energy equation of state parameters $w_{0}$ and $w_{a}$; the Jeffreys prior successfully recenters these posteriors to enclose the maximum a posteriori estimate within the 68\% credible regions, demonstrating clear mitigation of projection effects for these late-time expansion parameters. A hybrid Jeffreys+baseline-Gaussian configuration controls residual over-broad tails in the physical cold dark matter density $ω_{\mathrm{c}}$ while preserving the volume correction, and is our favoured approach. We compare the credible intervals derived using our methodology to those obtained using Halo Occupation Distribution (HOD)-informed priors and to confidence intervals derived using frequentist profile likelihood analyses, finding agreement in both central values and degeneracy directions in the $w_{0}$--$w_{a}$ plane. This demonstrates that, once projection effects are properly controlled, we can make robust inferences about the late-time cosmological expansion independent of the statistical framework adopted.

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Early results in the search for extreme coronal line emitters with the Dark Energy Spectroscopic Instrument

Here we present the results of our search through the Early Data Release (EDR) of the Dark Energy Spectroscopic Instrument (DESI) for extreme coronal line emitters (ECLEs) - a rare classification of galaxies displaying strong, high-ionization iron coronal emission lines within their spectra. With the requirement of a strong X-ray continuum to generate the coronal emission, ECLEs have been linked to both active galactic nuclei (AGNs) and tidal disruption events (TDEs). We focus our search on identifying TDE-linked ECLEs. We identify three such objects within the EDR sample, highlighting DESI's effectiveness for discovering new nuclear transients, and determine a galaxy-normalized TDE-linked ECLE rate of $R_\mathrm{G}=5~^{+5}_{-3}\times10^{-6}~\mathrm{galaxy}^{-1}~\mathrm{yr}^{-1}$ at a median redshift of z = 0.2 - broadly consistent with previous works. Additionally, we also identify more than 200 AGNs displaying coronal emission lines, which serve as the primary astrophysical contaminants in searches for TDE-related events. We also include an outline of the custom python code developed for this search.

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The 3D clustering of Lyman Alpha Emitters measured with DESI

We present a clustering analysis of Lyman-$α$ emitters (LAEs) using spectroscopic observations from the Dark Energy Spectroscopic Instrument (DESI) of candidates selected from the Blanco/DECam Intermediate-Band Imaging Survey (IBIS). We measure the two-point correlation function and the power spectrum, including cross-correlations with DESI quasars. Using both analytical and halo occupation distribution (HOD) simulation-based modeling, we find a linear bias of $b \sim 2.31$--$2.62$ for LAEs over the redshift range $2.26 < z < 3.41$. The analytical modeling also provides constraints on the strength of radiative transfer effects, while the HOD analysis characterizes the LAE-halo connection across multiple models. Finally, we quantify the magnitude of non-perturbative clustering effects such as Fingers of God in the LAE population, providing essential input for the accurate modeling of LAE-based cosmological analyses in forthcoming high-redshift surveys such as DESI-II.

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$4\times3$ Point Correlation Functions in Galaxy Surveys: Impact of Baryonic Feedback

We investigate the impact of baryonic feedback on two-point and three-point correlation functions (2PCFs and 3PCFs hereafter, respectively) involving galaxy density fields (g) and weak lensing shear fields (G), from simulated photometric catalogs of galaxies. Specifically, we baryonify high-resolution simulation using a baryonic correction model (BCM) and explore the consequences down to sub-arcminute (arcmin) scales, varying two model parameters with the largest impact on our probes: $M_{\rm c}$, which governs the amount of gas expelled beyond the halo boundary, and $θ_{\rm ej}$, which encodes the maximal ejection radius relative to halo boundary. We create lensing maps and galaxy catalogs assuming survey properties of the upcoming Year-10 data for the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST), and investigate the impact of baryonic feedback on the observed correlations, including the galaxy--galaxy--shear (ggG) and the galaxy--shear--shear (gGG) 3PCFs, which are measured, for the first time from simulations, with \textsc{TreeCorr}. Focusing on equilateral 3PCFs, we find that small scales are more heavily affected by baryonic effects than the corresponding 2PCFs, by up to 90 percent depending on the probe, redshift and BCM model. The galaxy--galaxy--galaxy (ggg) 3PCF is significantly affected at scales smaller than about 4 arcmin; a similar effect occurs at 10 arcmin for the ggG 3PCF, at 40 arcmin for the gGG 3PCF, and at about a degree for the shear--shear--shear (GGG) 3PCF. These four three-point statistics, which are collectively referred to as the $4\times3$PCFs, can be used at large scales to robustly constrain cosmological parameters. At smaller scales, their enhanced sensitivity to baryonic effects provides valuable leverage for constraining the BCM parameters and supplying informative priors. [Abridged]

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Constraining primordial non-Gaussianity from DESI DR1 quasars and Planck PR4 CMB Lensing

We present the first measurement of local-type primordial non-Gaussianity from the cross-correlation between $1.2$ million spectroscopically confirmed quasars from the first data release (DR1) of the Dark Energy Spectroscopic Instrument (DESI) and the Planck PR4 CMB lensing reconstructions. The analysis is performed in three tomographic redshift bins covering $0.8 < z < 3.5$, covering a sky fraction of $\sim 20\%$. We adopt a catalog-based pseudo-$C_\ell$ estimator and apply linear imaging weights validated on noiseless mocks. Compared to previous analyses using photometric quasar samples, our results benefit from the high purity of the DESI spectroscopic sample, the reduced noise of PR4 lensing, and the absence of excess large-scale power in the spectroscopic quasar auto-correlation. Fitting simultaneously for the non-Gaussianity parameter $f_{\mathrm{NL}}$ and the linear bias amplitude in each redshift bin, we obtain $f_{\mathrm{NL}} = 2^{+28}_{-34}$ for a response parameter $p=1.6$, and $f_{\mathrm{NL}} = 6^{+20}_{-24}$ for $p=1.0$. These results improve the constraints on $f_{\mathrm{NL}}$ by $\sim 35\%$ compared to the previous analysis based on the Legacy Imaging Survey DR9. Additionally, we derive an optimal weighting scheme to maximize the constraining power. In this case, and assuming $p=1.6$, we obtain $f_\mathrm{NL}=19^{+25}_{-31}$. Our results demonstrate the statistical power of DESI quasars for probing inflationary physics, and highlight the promise of future DESI data releases.

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A Natural $\gtrsim 100\times$ Telescope: Discovery of the Strongly Lensed Type II SN 2025mkn at $z=1.37$

We present the discovery of SN 2025mkn, a gravitationally lensed Type II supernova. First detected as a blue transient in ZTF, 0.83$^{\prime\prime}$ from a $z=0.42$ elliptical galaxy, follow-up SNIFS/UH2.2m and LRIS/Keck spectra revealed absorption lines at $z=1.371$. Later JWST NIRCam imaging shows that the bright transient is a close pair of point sources separated by $\sim 0.07^{\prime\prime}$, and a 30 times fainter counterimage opposite the lens, for which NIRSpec reveals strong H$α$ emission also at $z=1.371$. The light curves and spectra are consistent with the Type II supernova source being magnified $\gtrsim 100$ times, with $\sim 250$ required to reconcile its luminosity with that of nearby events such as SN 2023ixf. Lens models are consistent with such high magnifications, and always show that the faint image arrived first (undetected in earlier ZTF imaging), consistent with the later spectral phase of this fainter image. A fourth image is also predicted and possibly detected in the NIRSpec data. Light-curve-based time-delay measurements are not possible due to the first image being the faintest; however, the resolved NIRSpec spectra offer a future opportunity for time-delay cosmography through supernova phase measurements.

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Bayesian Component Separation for DESI LAE Automated Spectroscopic Redshifts and Photometric Targeting

Lyman Alpha Emitters (LAEs) are valuable high-redshift cosmological probes traditionally identified using specialized narrow-band photometric surveys. In ground-based spectroscopy, it can be difficult to distinguish the sharp LAE peak from residual sky emission lines using automated methods, leading to misclassified redshifts. We present a Bayesian spectral component separation technique to automatically determine spectroscopic redshifts for LAEs while marginalizing over sky residuals. We use visually inspected spectra of LAEs obtained using the Dark Energy Spectroscopic Instrument (DESI) to create a data-driven prior and can determine redshift by jointly inferring sky residual, LAE, and residual components for each individual spectrum. We demonstrate this method on 881 spectroscopically observed $z = 2-4$ DESI LAE candidate spectra and determine their redshifts with $>$90% accuracy when validated against visually inspected redshifts. Using the $Δχ^2$ value from our pipeline as a proxy for detection confidence, we then explore potential survey design choices and implications for targeting LAEs with medium-band photometry. This method allows for scalability and accuracy in determining redshifts from DESI spectra, and the results provide recommendations for LAE targeting in anticipation of future high-redshift spectroscopic surveys.

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Detection of the Pairwise Kinematic Sunyaev-Zel'dovich Effect and Pairwise Velocity with DESI DR1 Galaxies and ACT DR6 and Planck CMB Data

We present a 9.3-sigma detection of the pairwise kinematic Sunyaev-Zeldovich (kSZ) effect by combining a sample of 913,286 Luminous Red Galaxies (LRGs) from the Dark Energy Spectroscopic Instrument Data Release 1 (DESI DR1) catalog and co-added Atacama Cosmology Telescope (ACT DR6) and Planck cosmic microwave background (CMB) temperature maps. This represents the highest-significance pairwise kSZ measurement to date. The analysis uses three ACT CMB temperature maps: co-added 150 GHz, total frequency maps, and a component-separated Internal Linear Combination (ILC) map, all of which cover 19,000 square degrees of the sky from Advanced ACTPol observations conducted between 2017 and 2022. Comparison of the results of these three maps serves as a consistency check for potential foreground contamination that may depend on the observation frequency. An estimate of the best-fit mass-averaged optical depth is obtained by comparing the pairwise kSZ curve with the linear-theory prediction of the pairwise velocity under the best-fit Planck cosmology, and is compared with predictions from simulations. This estimate serves as a reference point for future comparisons with thermal SZ-derived optical depth measurements for the same DESI cluster samples, which will be presented in a companion paper. Finally, we employ a machine-learning approach trained on simulations to estimate the optical depth for 456,803 DESI LRG-identified clusters within the simulated mass range (greater than about 1e13 solar masses). These are combined with the measured kSZ signal to infer the individual cluster peculiar velocities, providing the opportunity to constrain the behavior of gravity and the dark sector over a range of cosmic scales and epochs.

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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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The DESI Transients Survey: Legacy Classifications and Methodology

We present the first systematic spectroscopic observations of extragalactic transients from the Dark Energy Spectroscopic Instrument (DESI), as part of the DESI Transients Survey program. With 5,000 fibers and an ${\sim} 8$ deg$^2$ field of view, we exploit DESI as a machine for the discovery and classification of transients. We present transient classifications from archival DESI data in Data Releases 1 and 2, relying on a combination of a secondary target program and serendipitous observations. We also present observations from the first 6 months of the DESI spare fiber program dedicated to transients. The program is run in coordination with a dedicated DECam time-domain survey, serving as a pathfinder for what we will be able to achieve in conjunction with the Rubin Observatory Legacy Survey of Space and Time (LSST). We classify over 250 transients, of which the majority were previously unclassified. The sample comprises thermonuclear and core-collapse supernovae and tidal disruption events (TDEs), including a TDE observed before its discovery in imaging. We demonstrate DESI's ability to classify a population of faint transients down to $r\sim 22.5$ mag during main survey operations, with negligible impacts on DESI's main observations.

astro-ph.HE