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An Image-Plane Approach to Gravitational Lens Modeling of Interferometric Data

Strong gravitational lensing acts as a cosmic telescope, enabling the study of the high-redshift universe. Astronomical interferometers, such as the Atacama Large Millimeter/submillimeter Array (ALMA), have provided high-resolution images of strongly lensed sources at millimeter and submillimeter wavelengths. To model the mass and light distributions of lensing and source galaxies from strongly lensed images, strong lens modeling for interferometric observations is conventionally performed in the visibility space, which is computationally expensive. In this paper, we implement an image-plane lens modeling methodology for interferometric dirty images by accounting for noise correlations. We show that the image-plane likelihood function produces accurate model values when tested on simulated ALMA observations with an ensemble of noise realizations. We also apply our technique to ALMA observations of two sources selected from the South Pole Telescope survey, comparing our results with previous visibility-based models. Our model results are consistent with previous models for both parametric and pixelated source-plane reconstructions. We implement this methodology for interferometric lens modeling in the open-source software package lenstronomy.

Zhang, Nan [Illinois U., Urbana (main)] (ORCID:000↗

Dark Energy Survey Year 3 results: optimized $w$CDM simulation-based inference with weak lensing map-level hybrid statistics

We present cosmological constraints from the Dark Energy Survey Year 3 (DES Y3) weak lensing data using hierarchical hybrid statistics within a Bayesian simulation-based inference framework that is based on the Gower Street simulations. To maximize the precision of the inference, we have developed a new, information-theory based, data compression of the weak lensing maps to just seven highly informative summary statistics. The hybrid scheme exploits the high information content of the power spectrum, compressing both the power spectrum and neural-based summaries that are designed to extract further information. Our simulation-based approach enables principled forward modelling of all major sources of systematic uncertainty and survey properties into realistic mock observations, including the survey mask, photometric redshift uncertainties, intrinsic galaxy alignments, multiplicative shear calibration bias, source galaxy clustering, non-Gaussian shape noise, and non-linear structure formation. The summary statistics are then used in a Bayesian simulation-based inference pipeline. The inference is validated through coverage tests and checks for robustness against baryonic feedback. Assuming a $w$CDM cosmology, our analysis yields $S_8 = 0.808 \pm 0.017$, $Ω_{\rm m} = 0.325 \pm 0.024$, and $w < -0.766$ (marginalized posterior 68 per cent credible intervals). This rigorous combination of information theory, physics- and neural network-based extreme data compression, and principled Bayesian analysis improves the figure of merit for $(Ω_{\rm m}, S_8, w)$ by 60 per cent over the previous state-of-the-art, and by almost a factor of 3 over two-point analyses of the same data. They are the most precise joint constraints on $(Ω_{\rm m}, S_8, w)$ from weak gravitational lensing data alone of any survey to date. We intend to apply this analysis to the more recent DES Y6 data.

Williamson, J. [University Coll. London]↗

Sensitivity of a closed dielectric haloscope to axion dark matter

We present a method to determine the sensitivity of a closed dielectric haloscope to axiondark matter. Dielectric haloscopes aim to probe the theoretically well-motivated axion mass rangeof ∼ 26 µeV to ∼ 500 µeV by utilizing a stack of dielectric disksand a mirror to enhance the axion-photon conversion within an external magnetic field. Theirconversion volume is nearly axion-mass independent, thereby favoring large-scale designs toincrease sensitivity. The large volume causes simulations to be computationally expensive andtime-consuming. This paper presents a simple model that can be used to determine the sensitivityof the experiment with minimal computational resources. The model is able to describe theelectromagnetic response of a closed dielectric haloscope, accounting for realistic geometricimperfections, as well as the noise introduced by the receiver system. It is applied to datataken with a MAgnetized Disk and Mirror Axion Experiment (MADMAX) prototype within the 1.6 TMorpurgo magnet at CERN. This work underpins the first axion dark matter search using adielectric haloscope and provides the foundation for future dark matter searches with MADMAX.

Ivanov, A. [Munich, Max Planck Inst. Quantenopt.]↗

Generalized Wigner theorem for noninvertible symmetries

In this article, we establish the conditions under which a conservation law associated with a non-invertible operator may be realized as a symmetry in quantum physics. As established by Wigner, all quantum symmetries must be represented by either unitary or antiunitary transformations. Relinquishing an implicit assumption of invertibility, we demonstrate that the fundamental invariance of quantum transition probabilities under the application of symmetries mandates that all non-invertible symmetries may only correspond to projective unitary or antiunitary transformations, i.e., partial isometries. This extends the notion of physical states beyond conventional rays in Hilbert space to equivalence classes in an extended, gauged Hilbert space, thereby broadening the traditional understanding of symmetry transformations in quantum theory. Our generalized theorem applies irrespective of the origin of the (non)invertible symmetry, holds in arbitrary spatial dimensions, and is independent of the Hamiltonian or action. We explore its physical consequences and, using simple model systems, illustrate how the distinction between invertible and non-invertible symmetries can sometimes be tied to the choice of boundary conditions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

First constraints from marked angular power spectra with Subaru Hyper Suprime-Cam Survey First-Year Data

We present the first application of marked power spectra to weak lensing data, using maps from the Subaru Hyper Suprime-Cam Year 1 (HSC-Y1) survey. Marked convergence fields, constructed by weighting the convergence field with non-linear functions of its smoothed version, are designed to encode higher-order information while remaining computationally tractable. Using simulations tailored to the HSC-Y1 data, we test three mark functions that up- or down-weight different density environments. Our results show that combining multiple types of marked auto and cross-spectra improves constraints on the clustering amplitude parameter S8≡σ8Ωm/0.3 by ≈43 per cent compared to standard two-point power spectra. When applied to the HSC-Y1 data, this translates into a constraint on S8=0.807±0.024⁠. We assess the sensitivity of the marked power spectra to systematics, including baryonic effects, intrinsic alignment, photometric redshifts, and multiplicative shear bias. We note that some of the additional information introduced by the marked field originates from scales smaller than the scale cut, and is partly Gaussian in nature. This does not invalidate our systematic tests. These results demonstrate the promise of marked statistics as a practical and powerful tool for extracting non-Gaussian information from weak lensing surveys.

Cowell, Jessica A. [Oxford U.; Tokyo U., IPMU] (OR↗

Cosmological constraints using Minkowski functionals from the first year data of the Hyper Suprime-Cam

We use Minkowski functionals to analyse weak lensing convergence maps from the first-year data release of the Subaru Hyper Suprime-Cam (HSC-Y1) survey. Minkowski functionals provide a description of the morphological properties of a field, capturing the non-Gaussian features of the Universe matter-density distribution. Using simulated catalogues that reproduce survey conditions and encode cosmological information, we emulate Minkowski functionals predictions across a range of cosmological parameters to derive the best-fit from the data. By applying multiple scales cuts, we rigorously mitigate systematic effects, including baryonic feedback and intrinsic alignments. From the analysis, combining constraints of the angular power spectrum and Minkowski functionals, we obtain S8≡σ8Ωm/0.3=0.808−0.046+0.033 and Ωm=0.293−0.043+0.157⁠. These results represent a 40 per cent improvement on the S8 constraints compared to using power spectrum only. Minkowski functionals results are consistent with other two-point, and higher order statistics constraints using the same data, being in agreement with CMB results from the Planck S8 measurements. Our study demonstrates the power of Minkowski functionals beyond two-point statistics to constrain and break the degeneracy between Ωm and σ8⁠.

79 ASTRONOMY AND ASTROPHYSICS↗

Measurement and feedback-driven adaptive dynamics in the classical and quantum kicked top

In classical dynamical systems, stochastic feedback can stabilize otherwise unstable periodic orbits, giving rise to distinct controlled and uncontrolled phases as the rate of control application is varied. In this work, we apply these control protocols in classical, semiclassical, and quantum regimes to the kicked top, a paradigmatic model of quantum chaos. The quantum kicked top, modeled as the dynamics of a spin-S object, naturally interpolates between these regimes with the spin size S acting as an effective Planck constant. We show that the dynamics of the kicked top in classical, semiclassical, and fully quantum limits can all be controlled using stochastic feedback protocols. Comparing the full quantum dynamics to a truncated Wigner approximation that captures quantum noise but neglects interference beyond the Ehrenfest time, we find that low-moment observables are largely accounted for semiclassically, while the remaining discrepancy in higher moments is consistent with contributions from interference and possibly nonlinearities in rare trajectories that explore the compact phase space. We also find rapid purification in the numerics studied for all rates of control considered, suggesting that control quenches the top's ability to encode a qubit of quantum information even in the uncontrolled phase.

Prasad, Mahaveer [Tata Inst.; Singapore U. Tech. D↗

Dark Energy Survey Year 3 results: $w$CDM cosmology from simulation-based inference with persistent homology on the sphere

We present cosmological constraints from Dark Energy Survey Year 3 (DES Y3) weak lensing data using persistent homology, a topological data analysis technique that tracks how features like clusters and voids evolve across density thresholds. For the first time, we apply spherical persistent homology to galaxy survey data through the algorithm TopoS2, which is optimized for curved-sky analyses and HEALPix compatibility. Employing a simulation-based inference framework with the Gower Street simulation suite, specifically designed to mimic DES Y3 data properties, we extract topological summary statistics from convergence maps across multiple smoothing scales and redshift bins. After neural network compression of these statistics, we estimate the likelihood function and validate our analysis against baryonic feedback effects, finding minimal biases (under $0.3σ$) in the $Ω_\mathrm{m}-S_8$ plane. Assuming the $w$CDM model, our combined Betti numbers and second moments analysis yields $S_8 = 0.821 \pm 0.018$ and $Ω_\mathrm{m} = 0.304\pm0.037$-constraints 70% tighter than those from cosmic shear two-point statistics in the same parameter plane. Our results demonstrate that topological methods provide a powerful and robust framework for extracting cosmological information, with our spherical methodology readily applicable to upcoming Stage IV wide-field galaxy surveys.

Prat, J. [Nordita; Royal Inst. Tech., Sodertalje; ↗

Dark Energy Survey Year 6 Results: Galaxy-galaxy lensing

We present galaxy--galaxy lensing (GGL) measurements from the full six years of data from the Dark Energy Survey (DES Y6), covering $4031\,\mathrm{deg}^2$ and used in the DES Y6 $3\times2$pt cosmological analysis. We use the MagLim++ lens sample, containing $\sim 9$ million galaxies divided into six redshift bins, and the Metadetection source catalog, including $\sim 140$ million galaxies divided into four redshift bins. The mean tangential shear signal achieves a total signal-to-noise ratio (S/N) of $173$, corresponding to a $17\%$ improvement over DES Y3. After applying the scale cuts used in the cosmological analysis, with $R_{\min}=6\,\mathrm{Mpc}/h$ ($4\,\mathrm{Mpc}/h$) for the linear (nonlinear) galaxy-bias model, the S/N is reduced to $75$ (90). A comprehensive suite of validation tests demonstrates that the measurement is robust against observational and astrophysical systematics at the statistical precision required for the DES Y6 analysis. Although not used in the main cosmological analysis, we extract high--signal-to-noise geometric shear-ratio measurements from the galaxy--galaxy lensing signal on small angular scales. These measurements provide an internal consistency check on the photometric redshift distributions and shear calibration used in the $3\times2$pt analysis.

Giannini, G. [Barcelona, IEEC; Chicago U., KICP; B↗

A Multi-Scale Computational Platform for Predictive Modeling of Corrosion in Al-Steel Joints (Final Report)

The research team proposed to develop innovative multi-scale models to predict corrosion and the resulting mechanical performances in aluminum-steel joints. The methods of joining considered are resistance spot welding, self-piercing riveting, and rivet-welding, all suitable for mass production applications. The multi-scale models integrate high throughput first-principle calculations based on density functional theory (DFT), high throughput calculation of phase diagrams (CALPHAD) modeling, and finite element method (FEM) simulations. These models are to be validated through laboratory experiments. Furthermore, the models are available as open source so as to enable scientists and engineers in the community to adapt and contribute to the development and application. The approaches rely on the research team’s extensive experience on the prediction of properties of individual phases at finite temperatures and variable compositions through DFT calculations, and our broad expertise on dissimilar material joining and their corrosion. The proposed computational framework enables high throughput computations for improved predictions of corrosion and the associated mechanical performance in dissimilar material joints, resulting in significant reduction in computational time needed by the current state-of-the-art methods. With the participation of researchers from three universities, an auto manufacturer, two manufacturing technology/equipment suppliers, and a software developer/vendor, the interdisciplinary research team applies the technical development on both phase-based modeling and laboratory experiments into the automobile body joining processes for validation and technology demonstration. The global cost of corrosion was estimated at about 3.4% of the global GDP in 2013. By using available corrosion control practices, it is estimated a saving between 15-35% of the cost of corrosion. In the U.S., more than $276 billion is spent repairing corrosion damage. Prediction of the corrosion and its impact on performance of the dissimilar material joints is critical for reducing the massive number of the current corrosion-based recalls for automobiles. Thus, the project goal is to develop models to enable predictive maintenance and end-of-life planning of multi-metal joints with risk of corrosion under different conditions such as exposure to high temperatures in summer and salt solutions in winter, quantified through its pH. An academia-industry consortium led by the University of Michigan and including Pennsylvania State University, University of Illinois Urbana-Champaign, University of Georgia, General Motors Company, Livermore Software Technology Corporation, and Optimal Process Technologies, LLC. created multi-scale models for prediction of corrosion in aluminum-steel joint structures such of them used in vehicle subassemblies – chassis and transmission systems. Starting from the first principle calculations, the team developed mathematical and data-driven models to predict the metallic components, which are formed during joining of two metals, for example aluminum and steel - a lightweight multilateral system which is currently used in more than 60% car bodies. These models were used for simulating chemical reactions that are happening when the joining metallic components are exposed to high temperatures and different pH values. The team was able to predict how the corrosion installs on the metallic components and how they lead to a sudden failure of components in cars. Newly developed machine learning algorithms combining Science, Technology, Engineering and Math disciplines, advanced finite element simulation and experimental validations have been integrated in a platform for prediction of the corrosion evolution and prediction the failure of joints under mechanical loadings and fatigue. Moreover, based on machine learning and inverse analysis, the team proposed solutions for designing new metallic alloys less susceptible to corrosion when joining multi-material assembles. An average of 4% error compared with experiments was achieved for the most common joints that are used in vehicle subassemblies.

36 MATERIALS SCIENCE↗

Effects of forest structural and compositional change on forest microclimates across a gradient of disturbance severity

Forest structural diversity and community composition are key in regulating forest microclimates. When disturbance affects structural diversity or composition, forest microclimates may be altered due to changes in soil temperature, soil water content, and light availability. It is unclear however which structural or compositional components, when changed or to what extent, result in microclimatic change. To address this question, we used data from a large scale, manipulative stem-girdling experiment in northern, lower Michigan—the Forest Resilience and Threshold Experiment (FoRTE). FoRTE follows a factorial design with multiple levels of disturbance severity (0, 45, 65, 85%) based on targeted reductions in gross leaf area index via stem-girdling induced mortality. These disturbance severity treatments are applied in two ways: either as top-down (largest trees are killed) or bottom-up (small to medium trees killed) treatments. We examined how multiple components of structural diversity and community composition changed as a product of disturbance severity and type, and then tested for resulting effects on forest microclimates (light availability, soil temperature, and soil water), using a multivariate, Random Forest framework. We found that measures of community composition (species richness, species evenness, and Shannon-Wiener Diversity Index) and stand structure (basal area, standard deviation of DBH, tree size diversity) declined more following disturbance than did measures of canopy cover, heterogeneity, arrangement, or height. However, when changes in each variable from pre- to post-disturbance, measured as log change, were employed in a multivariate, Random Forest regression framework, structural diversity measures of heterogeneity (rugosity, top rugosity), cover (canopy cover), and arrangement (porosity) were the most influential variables, but with differences among bottom-up and top-down treatments We found that the death of large trees from disturbance impacts soil temperature, water, and light environments more substantially and uniformly across disturbance gradients than does the death of smaller trees. Furthermore, our results have implications for both statistical and process-based modeling of forest disturbance.

54 ENVIRONMENTAL SCIENCES↗

The DESI DR1 Peculiar Velocity Survey: Growth Rate Measurements from the Galaxy Power Spectrum

The large-scale structure of the Universe and its evolution encapsulate a wealth of cosmological information. A powerful means of unlocking this knowledge lies in measuring the auto-power spectrum and/or the cross-power spectrum of the galaxy density and momentum fields, followed by the estimation of cosmological parameters based on these spectrum measurements. In this study, we generalize the cross-power spectrum model to accommodate scenarios where the density and momentum fields are derived from distinct galaxy surveys. The growth rate of the large-scale structures of the Universe, commonly represented as $fσ_8$, is extracted by jointly fitting the monopole and quadrupole moments of the auto-density power spectrum, the monopole of the auto-momentum power spectrum, and the dipole of the cross-power spectrum. Our estimators, theoretical models and parameter-fitting framework have been tested using mocks, confirming their robustness and accuracy in retrieving the fiducial growth rate from simulation. These techniques are then applied to analyze the power spectrum of the DESI Bright Galaxy Survey and Peculiar Velocity Survey, and the fit result of the growth rate is $fσ_8=0.440^{+0.080}_{-0.096}$ at effective redshift $z_{\rm eff}=0.07$. By synthesizing the fitting outcomes from correlation functions, maximum likelihood estimation and power spectrum, yields a consensus value of $fσ_8(z_{\rm eff}=0.07) = 0.450 ^{+0.055}_{-0.055}$, and correspondingly we obtain $γ=0.580^{+0.110}_{-0.110}$, $Ω_\mathrm{m}=0.301^{+0.011}_{-0.011}$ and $σ_8=0.834^{+0.032}_{-0.032}$. The measured $fσ_8$ and $γ$ are consistent with the prediction of the $Λ$ Cold Dark Matter Model and General Relativity.

Qin, F. [Marseille, CPPM] (ORCID:0000000179507864)↗

Direct Measurement of Galaxy Assembly Bias using DESI DR1 Data

We report the first direct measurement of galaxy assembly bias, a critical systematic in cosmology, from the Dark Energy Spectroscopic Instrument (DESI) Bright Galaxy Survey. We introduce a novel, cosmology-independent method to measure the halo occupation distribution (HOD) by combining a state-of-the-art group catalog with weak gravitational lensing. For groups binned by total luminosity, we determine the galaxy occupation number $N_{\rm gal}$ from group-galaxy cross-correlations, while weak lensing constrains the average halo mass $M_h$. Applying this to a volume-limited sample at $z{\in}[0.05,0.2]$, we measure the dependence of HOD, $N_{\rm gal}(M_h)$, on large-scale overdensity $δ_{g}$. Focusing on the satellite galaxies, we find an assembly bias parameter of $Q_{\rm sat}{=}0.05{\pm}0.14$, a result consistent with zero and in tension with many empirical galaxy formation models. Our method provides a robust approach for characterizing galaxy assembly bias to achieve precision cosmology with DESI and future Stage-V surveys.

Shao, Zhiwei [Shanghai Jiaotong U.; Shanghai Jiao ↗

Forest Structural Complexity and Biomass Predict First-Year Carbon Cycling Responses to Disturbance

The pre-disturbance vegetation characteristics that predict carbon (C) cycling responses to disturbance are not well known. To address this gap, we initiated the Forest Resilience Threshold Experiment, a manipulative study in which more than 3600 trees were stem girdled to achieve replicated factorial combinations of four levels (control, 45, 65, and 85% gross defoliation) of disturbance severity and two disturbance types (targeting upper or lower canopy strata). Applying a standardized stability framework in which initial C cycling resistance to disturbance was calculated as the first-year natural log response ratio of disturbance and control treatments, we investigated to what extent pre-disturbance levels of species diversity, aboveground woody biomass, leaf area index, and canopy rugosity—a measure of structural complexity—predict the initial responses of subcanopy light-saturated leaf CO 2 assimilation (A sat ), aboveground wood NPP (ANPP w ), and soil respiration (R s ) to phloem-disrupting disturbance. In the year following stem girdling, we found that above-ground C cycling processes, A sat and ANPP w , were highly resistant to increases in disturbance severity, while Rs resistance declined as severity increased. Disturbance type had no effect on first-year resistance. Pre-disturbance aboveground woody biomass, and canopy rugosity were positive predictors of ANPP w resistance and, conversely, negatively related to R s resistance. Subcanopy A sat resistance was not related to pre-disturbance vegetation characteristics. Stability of C uptake processes along with R s declines suggest the net C sink was sustained in the initial months following disturbance. Therefore, we conclude that biomass and complexity are significant, but not universal, predictors of initial C cycling resistance to disturbance. Moreover, our findings highlight the utility of standardized stability measures when comparing functional responses to disturbance.

54 ENVIRONMENTAL SCIENCES↗

Lensing Without Borders: Measurements of galaxy-galaxy lensing and projected galaxy clustering in DESI DR1

We present Galaxy-Galaxy Lensing measurements obtained by cross-correlating spectroscopically observed galaxies from the first data release of the Dark Energy Spectroscopic Instrument (DESI) with source galaxies from the Hyper Suprime-Cam Subaru Strategic Survey, the Kilo-Degree Survey, the Sloan Digital Sky Survey, and the Dark Energy Survey. Specifically, we measure the excess surface mass density $ΔΣ$ and tangential shear $γ_\mathrm{t}$ for the Bright Galaxy Sample and Luminous Red Galaxies measured within the first year of observations with DESI. To ensure robustness, we test the measurements for systematic biases, finding no significant trends related to the properties of the \acrshort{desi} lens galaxies. We identify a significant trend with the average redshift of source galaxies, however, this trend vanishes once we apply shifts to the Hyper Suprime-Cam Subaru Strategic Survey redshift distributions that are also favored by their fiducial cosmology analysis. Additionally, we compare the observed scatter in the measurements with the theoretical covariance and find excess scatter, driven primarily by small-scale measurements of $r\leq 1 \, \mathrm{Mpc}/h$; measurements on larger scales are consistent at the $2\,σ$ level. We further present the projected clustering measurements $w_p$ of the galaxy samples in the the first data release of DESI. These measurements, which will be made publicly available, serve as a foundation for forthcoming cosmological analyses.

Heydenreich, S. [Lick Observ.] (ORCID:000000027273↗

Clustering redshift distribution calibration of weak lensing surveys using the DESI-DR1 spectroscopic dataset

We estimate the source redshift distribution of current weak lensing surveys by applying the clustering-based redshift calibration technique, using the galaxy redshift sample provided by the Dark Energy Spectroscopic Instrument Data Release 1 (DESI-DR1). We cross-correlate the Bright Galaxy Survey (BGS), Luminous Red Galaxies (LRGs) and Emission Line Galaxies (ELGs) from DESI, within the redshift range $0.1 < z < 1.6$, with overlapping tomographic source samples from the Dark Energy Survey (DES), Kilo-Degree Survey (KiDS), and Hyper Suprime-Cam (HSC) survey. Using realistic mock catalogues, we test the stability of the clustering-redshift signal to fitting scale, reference-sample choice, and the evolution of source galaxy bias, and we explicitly model and marginalise over magnification contributions, which become non-negligible at $z \gtrsim 1$ due to the depth of the DESI ELG sample. We then compare the resulting bias-weighted redshift distributions to those calibrated using self-organising map (SOM) techniques, finding agreement within uncertainties for all surveys and tomographic bins. Our results demonstrate that clustering redshifts enabled by DESI's unprecedented spectroscopic sample provides a robust, complementary, and independent constraint capable of reducing one of the dominant systematic uncertainties in weak lensing cosmology.

Ruggeri, R. [Queensland U.]↗

The Linear Point Standard Ruler with DESI DR1 and DR2 Data

The linear point, a purely geometric feature in the monopole of the two-point correlation function, has been proposed as an alternative standard ruler. Compared to the peak in the correlation function, it is more robust to late-time nonlinear effects at the percent level. In light of improved simulations and high quality data, we revisit the robustness of the linear point and use it as an alternative to template-based fitting approaches typically used in BAO analyses. We present the linear point measurements on galaxy samples from the first and second data releases (DR1 and DR2) of the DESI survey. We convert the linear point into a dimensionless parameter $α_{iso,LP}$, defined as the ratio of the linear point in the fiducial cosmology and the observed value, analogous to the isotropic BAO scaling parameter $α_{iso}$ used in previous BAO measurements. Using the 2nd generation of AbacusSummit mock catalogs, we find that linear point measurements are more precise when calculated in the post-reconstruction regime with 15-60% smaller uncertainties than those pre-reconstruction. We find a systematic shift in the linear point measurements compared against the isotropic BAO measurements in mocks; we attribute this to the isotropic damping parameter responsible for smearing the linear point in the nonlinear regime. We propose a sample-dependent correction that mitigates the impact of late-time nonlinear effects. While this introduces a cosmology dependence in an otherwise model-independent measurement, this is necessary given the sub-percent precision dictated by current cosmological surveys. Comparing $α_{iso,LP}$ with isotropic BAO measurements made on the DESI DR1 and DR2 galaxy samples, we find excellent agreement after applying this correction, particularly post-reconstruction. We discuss future scope regarding cosmological inference with linear point measurements.

Uberoi, N. [Yale U.] (ORCID:0000000275179629)↗