arXiv subjects

A. D. Myers

Publications and source records attributed to A. D. Myers.

At least 19 recordsLinked to original sources

arXiv2026

1000 cataclysmic variables identified from DESI spectroscopy

Most cataclysmic variables (CVs) are discovered when they have an outburst generating an inherent selection bias against CVs that rarely, or never, outburst. CVs discovered by virtue of their spectroscopic characteristics are particularly valuable to offset this bias and we have used an established machine-learning technique to assist in searching 98 966 000 spectra obtained by the Dark Energy Spectroscopic Survey (DESI) to find such CVs. DESI observations are much deeper than previous spectroscopic surveys and we have identified 1029 CVs, 221 of which are new including ten of the AM CVn subtype. We have spectroscopically confirmed 441 CV candidates and obtained 84 new or improved orbital periods. We present revised space density estimates based upon this new data. We have also added ten more to the eight known examples of an intriguing class of CVs which exhibit peculiar changes in accretion.

astro-ph.SR↗

arXiv2026

DESI DR2 Reference Mocks: Clustering results from UCHUU ELGs and QSOs

High-redshift galaxy clustering provides a powerful probe of the growth of structure, testing models of dark matter, dark energy, and galaxy formation during the epoch when the Universe was rapidly evolving. Emission line galaxies (ELGs) and quasars (QSOs) are used as tracers of dark matter by the Dark Energy Spectroscopic Instrument (DESI) to probe this redshift regime. We present results from ELG and QSO mock catalogs created from the Uchuu N-body simulation and tuned to DESI Data Release 2 (DR2) clustering. Employing a modified subhalo abundance matching (SHAM) technique, we populate Uchuu halos and subhalos with QSOs between 0.8 < z < 2.1. For ELGs, we modify this method to select satellite galaxies with low velocities relative to their associated central halos, and populate a separate set of Uchuu halos and subhalos with ELGs between 0.8 < z < 1.6. In this paper, we reproduce the redshift evolution of number density and clustering statistics across the fitted range of scales. We also measure the large-scale clustering bias of both the data and mock samples. These results improve simulated lightcone construction from cosmological models and enhance our understanding of the galaxy-halo connection.

astro-ph.CO↗

arXiv2026

Clustering of high-redshift quasars with DESI DR2

We present clustering measurements for high-redshift quasars using data from the Dark Energy Spectroscopic Instrument Data Release 2. Our sample consists of quasars with $2.0 < z < 3.5$ in the luminosity range $M_{1450} \leq -19.94$\,mag. We measure the mean quasar bias $b_Q(\bar{z} = 2.48) = 3.61 \pm 0.01$ for the full sample of $\sim 715,000$ quasars and quantify the redshift evolution of quasar bias by dividing the sample into four equal redshift bins. There is strong evolution of the quasar bias with redshift that is well fit by the function $b_Q(z) = a [(1 + z)^2 - 6.565] + b$ with $a=0.230 \pm 0.007$ and $b=2.394 \pm 0.035$, and this fit is also a good match to lower redshift measurements in the literature. This bias evolution is consistent with a characteristic halo mass of $\bar{M}_{\mathrm{h}} \sim 10^{12}\,\mathrm{M_\odot}$ that does not vary significantly with redshift. The inferred duty cycles for quasars in our sample are $f_{\mathrm{duty}} \sim 10^{-2}$, staying mostly constant over redshifts. We investigate the luminosity dependence of quasar clustering by dividing each of our four redshift bins into three luminosity bins. The size of our quasar sample permits the first statistically significant measurement of the luminosity dependence of quasar bias at these redshifts. We measure weak dependence of quasar bias on luminosity at fixed redshift, inconsistent with no dependence, but weaker than predicted by a model in which quasar luminosity is tightly correlated with halo mass. These clustering measurements provide a stringent test for models of active black hole light curves and the black hole-halo connection at high redshift.

astro-ph.CO↗

arXiv2026

DESI Data Release 2 ELGs: Property-dependent subsamples, imaging systematics, and clustering

Using emission-line galaxies (ELGs) from the Dark Energy Spectroscopic Instrument (DESI) Data Release 2, we evaluate a property-dependent correction to imaging systematics. We derive systematic weights following the same linear regression method used for other DESI tracers, but do so separately on ELG subsamples to provide a physically-informed alternative to the fiducial, neural-network-based approach. In doing so, we show that the deeper imaging in the Dark Energy Survey (DES) footprint leads to a higher overall number density but a lack of targets with extreme $g-r$ and $r-z$ colors. ELGs in the DES region also show a distinct redshift distribution when subsampled by position in the $g-r$ vs. $r-z$ plane. To address these effects, we implement a separate treatment of the DES footprint within the DESI catalog production pipeline, which is generally well-motivated and, in some cases, imperative for accurate clustering measurements. With DES treated separately, we find that property-dependent systematic weights further mitigate spurious clustering signal in $\sim$10% of subsamples, while the fiducial scheme remains optimal for the full sample.

astro-ph.CO↗

arXiv2026

Tomography of the gamma-ray sky from cross-correlation with DESI DR2 and unWISE galaxies

We study the origin of extragalactic gamma-ray emission observed by Fermi-LAT, using the cross-correlation of the gamma-ray sky with maps of large-scale structure provided by the DESI and unWISE surveys. Tomographic cross-correlation reveals the bias-weighted redshift distributions of gamma-ray sources. We first illustrate this method by cross-correlating detected gamma-ray point sources with large-scale structure. We find a significant cross-correlation and infer a point source redshift distribution broadly consistent with the distribution of identified optical counterparts previously reported in the literature, as well as a similar linear bias ($b \approx 2$) to massive galaxies that host bright active galactic nuclei. We then study the clustering of the Fermi unresolved gamma-ray background (UGRB), both in auto-correlation and in cross-correlation with large-scale structure. We detect the cross-correlation of the UGRB and LSS at $\sim 10σ$ in total, with highly significant detections from both DESI and unWISE. Our measurements suggest that the redshift distribution of the UGRB is broadly consistent with the redshift distribution of detected point sources. Additionally, we find a relatively weak amplitude for the cross-correlation with large-scale structure at z < 2, suggesting a significant fraction of the UGRB does not come from z < 2 large-scale structure. A natural candidate is contamination of from residual Galactic emission, and our best estimate of the contamination level derived from the UGRB auto-spectrum suggests that the mean bias of UGRB sources is indeed quite similar to the bias of detected Fermi point sources. However, we cannot exclude additional emission from gamma-ray sources at high redshift, z > 2, and we suggest that cross-correlation with tracers at z > 2, including CMB lensing, would be the ideal way to determine the fraction of z > 2 emission.

astro-ph.CO↗

arXiv2026

The DESI Y1 RR Lyrae catalog I: Empirical modeling of the cyclic variation of spectroscopic properties and a chemodynamical analysis of the outer halo

We present the catalog of RR Lyrae stars (RRLs) observed in the first year of operations of the Dark Energy Spectroscopic Instrument (DESI) survey. This catalog contains 6,240 RRLs out to $\sim120$\,kpc from the Galactic center and over 12,000 individual epochs with homogeneously-derived stellar atmospheric parameters. We introduce a novel methodology to model the cyclical variation of the spectroscopic properties of RRLs from single-epoch measurements. We employ this method to infer the systemic velocities and mean temperatures of fundamental and first-overtone mode RRLs in our sample (without distinguishing between individual spectral lines). For fundamental mode pulsators, we obtain radial velocity curves with amplitudes of $\sim$30--80\,km\,s$^{-1}$ and effective temperature curves with 300--1,000\,K variations, whereas for first-overtone pulsators these amplitudes are $\sim20$\,km\,s$^{-1}$ and $\sim 600$\,K, respectively. We use our sample to study the metallicity distribution of the halo and its dependence on Galactocentric distance ($R_{\rm GC}$). Using a radius-dependent mixture model, we split the data into chemodynamically distinct components and find that our inner halo sample ($R_{\rm GC}\lesssim50$\,kpc) is predominantly composed of stars with [Fe/H] $\sim-1.5$ and largely radial orbits (with an anisotropy parameter $β\sim0.94$), that we associate with the Gaia-Sausage-Enceladus merger. Stars in the halo field exhibit a broader and more metal-poor [Fe/H] distribution with more circular orbits ($β\sim0.39$). The metallicity gradient of the metal-rich and the metal-poor components is found to be $0.005$ and $0.010$\,dex\,kpc$^{-1}$, respectively. Our catalog highlights DESI's tantalizing potential for studying the Milky Way and the pulsation properties of RRLs in the era of large spectroscopic surveys.

astro-ph.GA↗

arXiv2026

DESI Strong Lens Foundry III: Keck Spectroscopy for Strong Lenses Discovered Using Residual Neural Networks

We present spectroscopic data of strong lenses and their source galaxies using the Keck Near-Infrared Echellette Spectrometer (NIRES) and the Dark Energy Spectroscopic Instrument (DESI), providing redshifts necessary for nearly all strong-lensing applications with these systems, especially the extraction of physical parameters from lensing modeling. These strong lenses were found in the DESI Legacy Imaging Surveys using Residual Neural Networks (ResNet) and followed up by our Hubble Space Telescope program, with all systems displaying unambiguous lensed arcs. With NIRES, we target eight lensed sources at redshifts difficult to measure in the optical range and determine the source redshifts for six, between $z_s$ = 1.675 and 3.332. DESI observed one of the remaining source redshifts, as well as an additional source redshift within the six systems. The two systems with non-detections by NIRES were observed for a considerably shorter 600s at high airmass. Combining NIRES infrared spectroscopy with optical spectroscopy from our DESI Strong Lensing Secondary Target Program, these results provide the complete lens and source redshifts for six systems, a resource for refining automated strong lens searches in future deep- and wide-field imaging surveys and addressing a range of questions in astrophysics and cosmology.

astro-ph.CO↗

arXiv2026

Deep Spectroscopy with DESI for Photometric Redshift Training and Calibration

Deep spectroscopic samples can be used to improve photometric redshift (photo-$z$) estimates and reduce uncertainties on redshift distributions. Such improvements can increase the cosmological constraining power of large imaging-based experiments such as the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) and mitigate what may be a limiting systematic effect. We present results from the ``DESI-Deep pilot'' program, which was designed to assess the capability of the Dark Energy Spectroscopic Instrument (DESI) on the 4m Mayall telescope to measure redshifts of galaxies as faint as expected lensing samples for early LSST data ($m_i \leq 24.5$). We find that DESI is remarkably efficient at this task, with redshift success rates comparable to the results of observations from 10m-class telescopes with only $\sim2\times$ longer integration time (rather than $\sim 8\times$ longer as would be expected from aperture-area scaling), while simultaneously achieving $\sim30$ times larger multiplexing. We also find that the signal-to-noise ratio of the spectra scales as expected for background-limited observations even for the longest exposure times ($\sim 7$ hours) and faintest targets in the program. These results demonstrate that DESI could provide the definitive redshift sample for the early years of LSST with a modest investment of observing time. Based upon the results of this program, we provide updated predictions for the time required to collect benchmark samples for photo-$z$ training and calibration using a variety of spectroscopic facilities. Finally, we describe a potential "DESI-Deep" survey designed to train and calibrate photo-$z$'s for imaging experiments, and provide forecasts of its impact on cosmological inference.

astro-ph.IM↗

arXiv2026

ODIN: Spectroscopic Validation of Ly$α$-Emitting Galaxy Samples with DESI

The One-hundred-deg^2 DECam Imaging in Narrowbands (ODIN) survey is conducting the widest-field deep narrow-band imaging of the equatorial and southern skies. ODIN uses three custom-built narrow-band (NB) filters that sample Lya-emitting galaxies (LAEs) within thin cosmic slices centered at z=2.4, 3.1, and 4.5. In this work, we utilize extensive DESI spectroscopy of ODIN-selected galaxies in the COSMOS and XMM-LSS fields to validate our LAE selection. 2-4 hr exposures with DESI yielded redshift confirmation of 3,075 ODIN LAE candidates with NB magnitudes brighter than 26~mag. Restricting to objects that yield high-confidence redshifts, the confirmation rates are (93, 96, 92)% at z=(2.4, 3.1, 4.5). The primary contaminants consist of active galactic nuclei at the expected Lya redshift range and lower redshifts (C IV, C III]), with the remainder being star-forming galaxies ([O II] and [O III]). We find minimal contamination from [O II] emitters in our sample (<~1%), implying that our REW>20 A narrow-band excess photometry requirement is sufficient to remove them.

astro-ph.GA↗

arXiv2025

Probing the environment around GW170817 with DESI: insights on galaxy group peculiar velocities for standard siren measurements

We present a new measurement of the Hubble constant, $H_0$, following the gravitational wave event GW170817 and Dark Energy Spectroscopic Instrument (DESI) observations. A standard siren measurement with a nearby (luminosity distance $\sim 40 $ Mpc) event such as GW170817 is typically sensitive to the peculiar motion of the host galaxy due to local dynamics. Previous measurements from this event have taken advantage of peculiar velocity measurements of nearby galaxies, including a handful of objects in the galaxy group that the host of the event, NGC 4993, has been associated with. Still, the group's properties and NGC 4993's membership were debated. We present DESI observations of thousands of galaxies in the vicinity of NGC 4993, resulting in 39 group galaxies and a five-fold increase in galaxies compared to previous observations with many of these galaxies contributing to a peculiar velocity measurement. Examining the local dynamics, our observations support the presence of a galaxy group of which NGC 4993 is part with a halo mass of order $\sim$$10^{13}~M_\odot$. Using peculiar velocity measurements from our Fundamental Plane galaxies observations, we find $H_0 =70.9^{+6.4}_{-8.5}$ km s$^{-1}$ Mpc$^{-1}$. In addition, using a peculiar velocity measurement for NGC 4993 from Surface Brightness Fluctuations in Cosmicflows-4 we find $H_0 =73.4^{+3.3}_{-3.9}$ km s$^{-1}$ Mpc$^{-1}$. We study the impact of different galaxy selection criteria on the determination of the peculiar velocity and, in turn, on the $H_0$ measurement. Our results highlight the importance of multiplexed spectroscopic observations of the environments of gravitational wave events to probe local dynamics, which can ultimately affect standard siren measurements.

astro-ph.CO↗

arXiv2025

Validating the Galaxy and Quasar Catalog-Level Blinding Scheme for the DESI 2024 analysis

In the era of precision cosmology, ensuring the integrity of data analysis through blinding techniques is paramount -- a challenge particularly relevant for the Dark Energy Spectroscopic Instrument (DESI). DESI represents a monumental effort to map the cosmic web, with the goal to measure the redshifts of tens of millions of galaxies and quasars. Given the data volume and the impact of the findings, the potential for confirmation bias poses a significant challenge. To address this, we implement and validate a comprehensive blind analysis strategy for DESI Data Release 1 (DR1), tailored to the specific observables DESI is most sensitive to: Baryonic Acoustic Oscillations (BAO), Redshift-Space Distortion (RSD) and primordial non-Gaussianities (PNG). We carry out the blinding at the catalog level, implementing shifts in the redshifts of the observed galaxies to blind for BAO and RSD signals and weights to blind for PNG through a scale-dependent bias. We validate the blinding technique on mocks, as well as on data by applying a second blinding layer to perform a battery of sanity checks. We find that the blinding strategy alters the data vector in a controlled way such that the BAO and RSD analysis choices do not need any modification before and after unblinding. The successful validation of the blinding strategy paves the way for the unblinded DESI DR1 analysis, alongside future blind analyses with DESI and other surveys.

astro-ph.CO↗

arXiv2025

DESI Strong Lens Foundry II: DESI Spectroscopy for Strong Lens Candidates

We present the Dark Energy Spectroscopic Instrument (DESI) Strong Lensing Secondary Target Program. This is a spectroscopic follow-up program for strong gravitational lens candidates found in the DESI Legacy Imaging Surveys footprint. Spectroscopic redshifts for the lenses and lensed source are crucial for lens modeling to obtain physical parameters. The spectroscopic catalog in this paper consists of 73 candidate systems from the DESI Early Data Release (EDR). We have confirmed 20 strong lensing systems and determined four to not be lenses. For the remaining systems, more spectroscopic data from ongoing and future observations will be presented in future publications. We discuss the implications of our results for lens searches with neural networks in existing and future imaging surveys as well as for lens modeling. This Strong Lensing Secondary Target Program is part of the DESI Strong Lens Foundry project, and this is Paper II of a series on this project.

astro-ph.CO↗

arXiv2025

Using Active Learning to Improve Quasar Identification for the DESI Spectra Processing Pipeline

The Dark Energy Spectroscopic Instrument (DESI) survey uses an automatic spectral classification pipeline to classify spectra. QuasarNET is a convolutional neural network used as part of this pipeline originally trained using data from the Baryon Oscillation Spectroscopic Survey (BOSS). In this paper we implement an active learning algorithm to optimally select spectra to use for training a new version of the QuasarNET weights file using only DESI data, specifically to improve classification accuracy. This active learning algorithm includes a novel outlier rejection step using a Self-Organizing Map to ensure we label spectra representative of the larger quasar sample observed in DESI. We perform two iterations of the active learning pipeline, assembling a final dataset of 5600 labeled spectra, a small subset of the approx 1.3 million quasar targets in DESI's Data Release 1. When splitting the spectra into training and validation subsets we meet or exceed the previously trained weights file in completeness and purity calculated on the validation dataset with less than one tenth of the amount of training data. The new weights also more consistently classify objects in the same way when used on unlabeled data compared to the old weights file. In the process of improving QuasarNET's classification accuracy we discovered a systemic error in QuasarNET's redshift estimation and used our findings to improve our understanding of QuasarNET's redshifts.

astro-ph.IM↗

arXiv2025

STag II: Classification of Serendipitous Supernovae Observed by Galaxy Redshift Surveys

With the number of supernovae observed expected to drastically increase thanks to large-scale surveys like the Dark Energy Spectroscopic Instrument (DESI), it is necessary that the tools we use to classify these objects keep up with this increase. We previously created Supernova Tagging and Classification (STag) to address this problem by employing machine learning techniques alongside logistic regression in order to assign 'tags' to spectra based on spectral features. STag II is a continuation of this work, which now makes use of model supernova spectra combined with real DESI spectra in order to train STag to better deal with realistic data. We also make use of the rlap score as a trustworthiness cut, making for a more robust and accurate supernova classifier than before.

astro-ph.CO↗

arXiv2025

Strong Lens Discoveries in DESI Legacy Imaging Surveys DR10 with Two Deep Learning Architectures

We have conducted a search for strong gravitational lensing systems in the Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Surveys Data Release 10 (DR10). This paper is the fourth in a series of searches (following Huang et al. 2020; Huang et al. 2021; Storfer et al. 2024, Paper I, II, & III respectively). This is the first catalog of lens candidates covering nearly the entirety of the extragalactic sky south of declination $δ\approx +32$ deg, all of it observed by the DECam, covering $\sim$14,000 $deg^2$. We impose a $z$-band magnitude cut of < 20 in AB magnitude. We deploy a Residual Neural Network and EfficientNet as an ensemble trained on a compilation of known lensing systems and high-grade candidates as well as nonlenses in the same footprint. The predictions from these two base models are aggregated using a meta-learner. After applying our ensemble to the survey data, we exclude known candidates and systems, and use our own visual inspection portal to rank images in the top 0.01 percentile of all neural network recommendations. We have found 811 new lens candidates. These include 484 new candidates in the Legacy Surveys DR9 footprint, all parts of which have been searched for strong lenses at least once before, either by our group or others. Combining the discoveries from this work with those from Paper I (335), II (1210), and III (1512), we have discovered a total of 3868 new candidates in the DESI Legacy Surveys.

astro-ph.CO↗

arXiv2025

Construction of the Damped Ly$α$ Absorber Catalog for DESI DR2 Ly$α$ BAO

We present the Damped Ly$α$ Toolkit for automated detection and characterization of Damped Ly$α$ absorbers (DLA) in quasar spectra. Our method uses quasar spectral templates with and without absorption from intervening DLAs to reconstruct observed quasar forest regions. The best-fitting model determines whether a DLA is present while estimating the redshift and \texttt{HI} column density. With an optimized quality cut on detection significance ($Δχ_{r}^2>0.03$), the technique achieves an estimated 80\% purity and 79\% completeness when evaluated on simulated spectra with S/N~$>2$ that are free of broad absorption lines (BAL). We provide a catalog containing candidate DLAs from the DLA Toolkit detected in DESI DR1 quasar spectra, of which 21,719 were found in S/N~$>2$ spectra with predicted $\log_{10} (N_\texttt{HI}) > 20.3$ and detection significance $Δχ_{r}^2 >0.03$. We compare the Damped Ly$α$ Toolkit to two alternative DLA finders based on a convolutional neural network (CNN) and Gaussian process (GP) models. We present a strategy for combining these three techniques to produce a high-fidelity DLA catalog from DESI DR2 for the Ly$α$ forest baryon acoustic oscillation measurement. The combined catalog contains 41,152 candidate DLAs with $\log_{10} (N_\texttt{HI}) > 20.3$ from quasar spectra with S/N~$>2$. We estimate this sample to be approximately 85\% pure and 79\% complete when BAL quasars are excluded.

astro-ph.CO↗

arXiv2025

Full-Shape analysis of the power spectrum and bispectrum of DESI DR1 LRG and QSO samples

We present the first joint analysis of the power spectrum and bispectrum using the Data Release 1 (DR1) of the Dark Energy Spectroscopic Instrument (DESI), focusing on Luminous Red Galaxies (LRGs) and quasars (QSOs) across a redshift range of $0.4\leq z\leq2.1$. By combining the two- and three-point statistics, we are able to partially break the degeneracy between the logarithmic growth rate, $f(z)$, and the amplitude of dark matter fluctuations, $σ_\textrm{s8}(z)$, which cannot be measured separately in analyses that only involve the power spectrum. In comparison with the (fiducial) Planck $Λ$CDM cosmology we obtain $f/f^\textrm{fid}=\{0.888_{-0.089}^{+0.186},0.977_{-0.220}^{+0.182},1.030_{-0.085}^{+0.368}\}$, $σ_{s8}/σ^\textrm{fid}_\textrm{s8}=\{1.224_{-0.133}^{+0.091},1.071_{-0.163}^{+0.278},1.000_{-0.223}^{+0.088}\}$ respectively for the three LRG redshift bins, corresponding to a cumulative 10.1\% constraint on $f$, and of 8.4\% on $σ_\textrm{s8}$, including the systematic error budget. The cumulative constraints for the ShapeFit compressed parameters from our joint power spectrum-bispectrum analysis are respectively $σ_{α_\textrm{iso}}=0.9\%$ (9\% improvement with respect to our power spectrum-only analysis); $σ_{α_\textrm{AP}}=2.3\%$ (no improvement with respect to power spectrum-only analysis, which is expected given that the bispectrum monopole has no significant anisotropic signal); $σ_{fσ_\textrm{s8}}=5.1\%$ (9\% improvement); $σ_{m+n}=2.3\%$ (11\% improvement). These results are fully consistent with the main DESI power spectrum analysis, demonstrating the robustness of the DESI cosmological constraints, and compatible with Planck $Λ$CDM cosmology.

astro-ph.CO↗

arXiv2025

Fiducial-Cosmology-dependent systematics for the DESI 2024 BAO Analysis

When measuring the Baryon Acoustic Oscillations (BAO) scale from galaxy surveys, one typically assumes a fiducial cosmology when converting redshift measurements into comoving distances and also when defining input parameters for the reconstruction algorithm. A parameterised template for the model to be fitted is also created based on a (possibly different) fiducial cosmology. This model reliance can be considered a form of data compression, and the data is then analysed allowing that the true answer is different from the fiducial cosmology assumed. In this study, we evaluate the impact of the fiducial cosmology assumed in the BAO analysis of the Dark Energy Spectroscopic Instrument (DESI) survey Data Release 1 (DR1) on the final measurements in DESI 2024 III. We utilise a suite of mock galaxy catalogues with survey realism that mirrors the DESI DR1 tracers: the bright galaxy sample (BGS), the luminous red galaxies (LRG), the emission line galaxies (ELG) and the quasars (QSO), spanning a redshift range from 0.1 to 2.1. We compare the four secondary AbacusSummit cosmologies against DESI's fiducial cosmology (Planck 2018). The secondary cosmologies explored include a lower cold dark matter density, a thawing dark energy universe, a higher number of effective species, and a lower amplitude of matter clustering. The mocks are processed through the BAO pipeline by consistently iterating the grid, template, and reconstruction reference cosmologies. We determine a conservative systematic contribution to the error of $0.1\%$ for both the isotropic and anisotropic dilation parameters $α_{\rm iso}$ and $α_{\rm AP}$. We then directly test the impact of the fiducial cosmology on DESI DR1 data.

astro-ph.CO↗