arXiv subjects

Tim Eifler

Publications and source records attributed to Tim Eifler.

At least 19 recordsLinked to original sources

arXiv2026

Direct shear $\times$ kSZ correlation: controlling baryons without modeling galaxies

Baryonic feedback redistributes gas within and around dark matter haloes, suppressing the small-scale matter power spectrum at a level that is now the leading systematic for upcoming weak-lensing surveys. The kinetic Sunyaev-Zeldovich (kSZ) effect directly probes this redistributed gas, but existing measurements around galaxies are either tied to the properties of the chosen galaxy sample or are susceptible to biases from other extragalactic foregrounds. We address both by cross-correlating a kSZ template constructed from the tomographic weak-lensing convergence maps and the radial velocity maps reconstructed from galaxy surveys via the continuity equation, with the observed CMB temperature. We forecast the detectability for Rubin LSST Y10 and Roman kinematic lensing samples combined with ACT, SO, and CMB-HD, finding signal-to-noise ratios of $\sim$ 5-15 for current and upcoming CMB data and $\gtrsim 100$ for CMB-HD, corresponding to few-per-cent and sub-per-cent constraints, respectively, on the baryonic suppression of the matter power spectrum. This method should thus achieve sufficient statistical precision to model baryonic feedback effects for Rubin, without the systematic challenge of modeling any galaxy-matter connection.

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arXiv2026

Multi-sensor fusion for fine-guidance and milliarcsecond-level attitude estimation of balloon-borne telescope

Balloon-borne telescopes rely on fine-guidance systems to achieve milliarcsecond image stability despite residual disturbances from the balloon environment. In these systems, the Fast Steering Mirror (FSM) stabilizes the image in two focal-plane axes, but leaves systematic, field-dependent residual motion induced by boresight roll. This effect, referred to as roll leakage, becomes more important for wider fields of view. In this work, roll leakage is characterized using data from the 2023 Superpressure Balloon-borne Imaging Telescope (SuperBIT) science flight. SuperBIT is a 0.5-m near-ultraviolet to near-infrared telescope that demonstrated milliarcsecond-level image stability during its 45-night science flight. We find that passive focal-plane star-camera measurements correlate strongly with independent roll measurements across a large set of science exposures, showing that boresight roll frequently drives residual focal-plane motion. We then develop a simulation framework combining optical ray tracing, asynchronous guide-star measurements, estimation, and FSM control to study this behavior. The framework is used to compare single-star and multi-star guidance architectures under realistic flight disturbances. For the SuperBIT geometry, we find that multi-star estimation reduces average roll-induced science-field image motion by 31.8%, increasing to 77.4% for a representative geometry of GigaBIT, SuperBIT's planned larger-aperture successor. These results motivate further investigation of multi-star fine-guidance architectures for GigaBIT.

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arXiv2026

Accurate modeling for 3$\times$2pt analyses in Roman and Rubin: a study of model approximations

One of the pillars of modern cosmology is the use of galaxy imaging surveys to extract information from the large-scale structure. In recent surveys, this measurement is typically performed through a 3$\times$2pt analysis, which combines auto- and cross-correlations between galaxy density and galaxy weak lensing. In this paper, we carry out a systematic study of three modeling approximations commonly used in such analyses: 1) applying the Limber approximation, 2) neglecting redshift-space distortions, and 3) using less accurate models for the nonlinear matter power spectrum. We carry out the study in the context of the final data from two major Stage-IV galaxy imaging surveys: the Nancy Grace Roman Space Telescope's High Latitude Imaging Survey and the Vera C. Rubin Observatory's Legacy Survey of Space and Time. To do this, we first validate our modeling pipeline, implemented in the software package CoCoA, against an established code base, CCL. Next, we perform a simulated likelihood analysis to assess the impact of these approximations on the cosmological constraints. We find all three effects to be important; neglecting any of them can induce biases in cosmological constraints approaching or exceeding $1\sigma$, and exceeding $2\sigma$ for Rubin in several cases. Moreover, we explore how the lens-galaxy sample configuration and scale-cut choice can influence the constraints.

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arXiv2026

Lensing in the Blue III: Weak Lensing Shape Catalogs of 30 Merging Galaxy Clusters

We present the weak gravitational lensing dataset from the Super-pressure Balloon-Borne Imaging Telescope (SuperBIT), which imaged 30 galaxy clusters during its 45 night flight in April to May 2023. SuperBIT is a first-of-its-kind balloon-borne imaging telescope that achieved near diffraction-limited observations in near-space conditions above 98% of the Earth's atmosphere. We use the metacalibration algorithm to obtain calibrated galaxy shapes for our target clusters and several calibration fields, enabling unbiased reconstruction of the weak-lensing signal. We employ several diagnostics throughout the pipeline, including assessments of point-spread function (PSF) modeling residuals and their impact on weak-lensing measurements, as well as tests for correlations between galaxy shapes and measured galaxy and PSF properties. To assess the multiplicative shear bias of the pipeline, we analyze a parallel set of simulated images that incorporate the real observing conditions from the flight, including measured SuperBIT PSFs, observed sky backgrounds, and detector noise, yielding a bias of $(1.1 \pm 7.8)$~per~cent.

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arXiv2026

Learning to See Sharper: A Physics-Informed Artificial Intelligence Framework for Super-Resolving Galaxy Spectra

The information recoverable from galaxy spectra depends fundamentally on spectral resolution, yet assembling large samples at high resolution remains observationally expensive. We present a deep-learning framework for spectral super-resolution that enhances low-resolution galaxy spectra by a factor of $\sim$10 in resolving power ($R\sim100$ to $R\sim1000$). The model is trained on 1,187 paired JWST/NIRSpec observations from the JADES program, where low-resolution prism spectra are matched with medium-resolution grating spectra (G140M, G235M, G395M) combined into a unified reference covering 1-5 $\mu$m. Our three-stage architecture performs an initial super-resolution, infers the redshift from the coarse reconstruction, and then applies a physics-informed residual refinement that uses attention across emission-line tokens to learn inter-line relationships and predict parametric line profiles, alongside a convolutional branch for continuum corrections. Evaluated on a 20% held-out sample, the model achieves noise-limited residuals over most of the spectral range and systematically improves the signal-to-noise ratio of key diagnostic lines including [OII], H$\beta$, [OIII], and H$\alpha$, often by factors of several. The super-resolved spectra successfully deblend features that are entirely unresolved at prism resolution, such as the [OIII] $\lambda\lambda4959,5007$ doublet and H$\beta$. As a proof of concept using JWST data, this approach is readily extensible to the low-resolution grism spectroscopy that will be delivered by Euclid and the Roman Space Telescope, potentially enabling population-level diagnostics across millions of galaxy spectra that would otherwise be inaccessible at grism resolution.

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arXiv2026

Emulation of SPHEREx Galaxy Power Spectra I: Neural Network Details and Optimization

We present neural networks to generate redshift-space galaxy power spectrum multipoles for multiple tracer and redshift bins simultaneously given a set of input cosmology and galaxy bias parameters. This emulator utilizes a combination of fully-connected layers and transformer architecture to accurately predict galaxy power spectrum multipoles $900$ times faster than the SPHEREx pipeline. We quantify network performance using both $\Delta \chi^2$, and likelihood contours for simulated SPHEREx analyses, using two correlated tracer bins and two independent redshift bins. After optimizing network architecture, the loss function, and training set sampling strategy, we achieve $\operatorname{Med}\left( \Delta \chi^2\right) = 0.069$ when comparing to our testing set. At the contour-level our emulator agrees with EFT predictions over a realistic parameter range, with an average 1D best-fit shift of $0.078\sigma$ and $0.82 \%$ change in 1D error bars. These results demonstrate the feasibility of using neural-network emulators to accelerate SPHEREx redshift-space power-spectrum analyses.

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arXiv2026

Towards the Two-Loop EFTofLSS in Galaxy Lensing Surveys

Extracting cosmological information from Stage IV weak lensing surveys requires non-linear modelling of the matter power spectrum that is accurate across a broad range of scales and redshifts and robust to baryonic feedback. We forecast the application of the two-loop effective field theory of large-scale structure (EFTofLSS) to Roman Space Telescope, carefully considering parameterization, scale cuts, and priors. We develop neural network emulators for the two-loop integrals, allowing rapid evaluation of the likelihood. Weak lensing demands a continuous-in-redshift description of the EFT, potentially introducing tens of nuisance parameters. We address this by calibrating the counterterm redshift evolution against the Euclid Emulator 2 and accounting for the residual freedom in redshift with spline functions. A principal component analysis of the free parameters reduces the dimensionality to a few degrees of freedom that the data can constrain. Next, we calibrate the priors on those degrees of freedom by using a suite of hydrodynamical simulations. We forecast the $S_8$ constraints as a function of scale cuts, showing that the two-loop EFT with Roman cosmic shear provides unbiased $S_8=\sigma_8\sqrt{\Omega_{\rm m}/0.3}$ constraints with relative errors of about $0.9\%$ and $1.4\%$ when allowing for $5\%$ and $1\%$ contamination from ultraviolet modes, respectively. The two-loop EFT improves the scale reach beyond the one-loop EFT and non-linear dark matter-only models when baryonic effects are included. This framework provides a robust path for extracting small-scale information from future cosmic shear data.

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arXiv2026

A Path to an All-Sky Survey with Roman

A deep, space-based, all-sky near-infrared survey carried out with the Nancy Grace Roman Space Telescope would constitute a foundational astronomical infrastructure for decades to come. In this white paper, we present a concrete and feasible path to imaging the entire sky at $\sim0.1''$ resolution, beginning with high-impact fields in Cycle 1 and scaling to ultra-wide coverage within the nominal mission. This first-epoch survey will reach $\mathrm{H}\sim25.5$ AB mag (5$\sigma$) and maximize synergies with contemporaneous observatories, while preserving substantial time for other ambitious Roman programs. We outline representative scheduling scenarios and an example Cycle 1 program that triples early Roman-LSST overlap and delivers high-value community data products such as LSST forced photometry, joint \textit{Gaia}-Roman astrometry, and catalogs of Galactic substructure, stong lenses, and other rare systems. The Cycle 1 program will lay the foundation for an eventual all-sky survey, while also delivering high-impact early science. We invite broad community participation in shaping and carrying out both the initial program and the long-term vision of an all-sky Roman survey.

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arXiv2026

Modeling Redshift Uncertainties in Roman Weak Lensing Cosmology

Cosmological constraints using weak gravitational lensing measurements from the Roman Space Telescope will require a powerful method for modelling uncertainties in the galaxy redshift distribution. In this work, we use an optimized version of the principal component analysis (PCA) to model uncertainties in the full shape of the redshift distributions, a method proposed by \cite{pca_method} and recently used in the Dark Energy Survey Y6 analysis. Here, we implement this new approach within the Roman High Latitude Imaging Survey (HLIS) Cosmology Project Infrastructure Team (PIT) pipeline, namely Cobaya-Cosmolike Joint Architecture (\texttt{CoCoA}). To validate the PCA in mitigating biases on cosmological parameters, $S_8$ and $\Omega_m$, we use a set of redshift distributions from \texttt{Cardinal} generated for a variety of Roman configurations. Overall, when the simulated cosmic shear data vector is not strongly miscalibrated relative to the fiducial one, both the mean-shift and the PCA-based approaches produce consistent cosmological constraints when marginalizing over nuisance parameters. For mild to strong miscalibration, including additional PCs progressively mitigates biases in $S_8$ and $\Omega_m$, and can achieve comparable performance with fewer parameters than the nine tomographic-bin mean-shift model.

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arXiv2026

Fisher Forecasts for Cosmological Yields from $3\!\times\!2$pt Analysis of the Roman Space Telescope High Latitude Imaging Survey

The High Latitude Imaging Survey (HLIS) of NASA's Nancy Grace Roman Space Telescope will provide powerful tests of cosmological models through sensitive measurements of cosmic shear, galaxy-galaxy lensing (GGL), and galaxy clustering. As part of the HLIS Project Infrastructure Team's Data Challenge 1 (DC1), we carry out Fisher forecasts of cosmological parameter constraints from combinations of these probes, focusing on inverse-variance figures of merit (FoMs) for the parameters $\sigma_8$ and $\Omega_{\rm{m}}$, which scale the amplitude of weak lensing signals. We find good agreement between Fisher analysis and Markov chain Monte Carlo (MCMC) analysis of the DC1 baseline data vector, and we investigate varied priors on cosmological parameters and on nuisance parameters describing unknown biases in photometric redshifts or shear measurements. The DC1 benchmark modeling assumes a ``lens $=$ source'' analysis with linear galaxy bias and no marginalization over baryonic physics. Under these assumptions, the forecast constraints from GGL+clustering are substantially stronger than those from cosmic shear, with the combination of all three probes (``$3\!\times\!2$pt'') providing moderate further improvement. Adding tight external priors on the power spectrum shape parameters $n_{\rm{s}}$, $\Omega_{\rm{b}}$, and $h_0$ can improve the $(\sigma_8, \Omega_{\rm{m}})$ FoMs by factors of $1.2$--$3.5$. The smallest scale angular bins provide much more information than the largest scale bins, and the highest redshift tomographic bins provide more information than the lowest redshift bins. Factor-of-two changes in the priors on photo-$z$ and shear biases, relative to the benchmark values based on anticipated calibration accuracy, produce changes of $\lesssim 20\%$ in FoMs.

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arXiv2025

The SPHEREx Satellite Mission

SPHEREx, a NASA explorer satellite launched on 11 March 2025, is carrying out the first all-sky near-infrared spectral survey. The satellite observes in 102 spectral bands from 0.75 to 5.0 um with a resolving power ranging from 35 to 130 in 6.2 arcsecond pixels. The observatory obtains a 5-sigma depth of 19.5 - 19.9 AB mag for 0.75 to 3.8 um and 17.8 - 18.8 AB mag for 3.8 to 5.0 um after mapping the full sky four times over two years. Scientifically, SPHEREx will produce a large galaxy redshift survey over the full sky, intended to constrain the amplitude of inflationary non-Gaussianity. The observations will produce two deep spectral maps near the ecliptic poles that will use intensity mapping to probe the evolution of galaxies over cosmic history. By mapping the depth of infrared absorption features over the Galactic plane, SPHEREx will comprehensively survey the abundance and composition of water and other biogenic ice species in the interstellar medium. The initial data are rapidly released in the form of spectral images to the public. The project will release specialized data products over the life of the mission as the surveys proceed. The science team will also produce specialized spectral catalogs on planet-bearing and low-mass stars, solar system objects, and galaxy clusters 3 years after launch. We describe the design of the instrument and spacecraft, which flow from the core science requirements. Finally, we present an initial evaluation of the in-flight performance and key characteristics.

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arXiv2025

Constraining baryonic feedback and cosmology from DES Y3 and Planck PR4 6$\times$2pt data. I. $\Lambda$CDM models

We combine weak lensing, galaxy clustering, cosmic microwave background (CMB) lensing, and their cross-correlations (so-called 6$\times$2pt) to constrain cosmology and baryonic feedback scenarios using data from the Dark Energy Survey (DES) Y3 Maglim catalog and the Planck satellite PR4 data release. We include all data points in the DES Y3 cosmic shear two-point correlation function (2PCF) down to 2.$^\prime$5 and model baryonic feedback processes via principal components (PCs) that are constructed from the ANTILLES simulations. We find a tight correlation between the amplitude of the first PC $Q_1$ and mean normalized baryon mass fraction $\bar{Y_\mathrm{b}}=\bar{f}_\mathrm{b}/(\Omega_\mathrm{b}/\Omega_\mathrm{m})$ from the ANTILLES simulations and employ an independent $\bar{Y_\mathrm{b}}$ measurement from Akino et al. (2022) as a prior of $Q_1$. We train a neural network $6\times2$pt emulator to boost the analysis speed by $\mathcal{O}(10^3)$, which enables us to run an impressive number of simulated analyses to validate our analysis against various systematics. For our 6$\times$2pt analysis, we find $S_8=0.8073\pm0.0094$ when including a $Q_1$ prior from $\bar{Y_\mathrm{b}}$ observations. This level of cosmological constraining power allows us to put tight constraints on the strength of baryonic feedback. We find $Q_1=0.025^{+0.024}_{-0.029}$ for our 6$\times$2pt analysis and $Q_1=0.043\pm{0.016}$ when combining with external information from Planck, ACT, DESI. All these results indicate weak feedback, e.g., the tensions to Illustris ($Q_1=0.095$) and OWLS AGN T8.7 ($Q_1=0.137$) are 2.9$\sigma$-3.3$\sigma$ and 4.7$\sigma$-5.9$\sigma$, respectively.

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arXiv2025

Cosmic shear with one component and its application to future radio surveys

We present a new approach to measuring cosmic shear: the one-component kinematic lensing (KL) method. This technique provides a simplified implementation of KL that reduces shape noise in weak lensing (WL) by combining kinematic information with imaging data, while requiring less observational effort than the full two-component KL. We perform simulated likelihood analyses to assess the performance of the one-component KL and demonstrate its applicability to future radio surveys. Our forecasts indicate that, for radio surveys, the one-component KL is not yet competitive with traditional WL due to the shallow redshift distribution of Hi-selected galaxies. However, when applying this method to deeper spectroscopic surveys with stronger emission lines, the one-component KL approach could surpass WL in constraining power, offering a promising and efficient pathway for future shear analyses.

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arXiv2025

Attention-based Neural Network Emulators for Multi-Probe Data Vectors Part III: Modeling The Next Generation Surveys

Machine learning can accelerate cosmological inferences that involve many sequential evaluations of computationally expensive data vectors. Previous works in this series have examined how machine learning architectures impact emulator accuracy and training time for optical shear and galaxy clustering 2-point function. In this final manuscript, we explore neural network performance when emulating Cosmic Microwave Background temperature and polarization power spectra. We maximize the volume of applicability in the parameter space of our emulators within the standard $\Lambda$-cold-dark-matter model while ensuring that errors are below cosmic variance. Relative to standard multi-layer perceptron architectures, we find the dot-product-attention mechanism reduces the number of outliers among testing cosmologies, defined as the fraction of testing points with $\Delta \chi^2 > 0.2$ relative to \textsc{CAMB} outputs, for a wide range of training set sizes. Such precision enables attention-based emulators to be directly applied to real data without requiring any additional correction via importance sampling. Combined with pre-processing techniques and optimized activation and loss functions, attention-based models can meet the precision criteria set by current and future CMB and lensing experiments. For each of Planck, Simons Observatory, CMB S4, and CMB HD, we find the fraction of outlier points to be less than $10\%$ with around $2\times10^5$ to $4\times10^5$ training data vectors. We further explore the applications of these methods to supernova distance, weak lensing, and galaxy clustering, as well as alternative architectures and pre-processing techniques.

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arXiv2024

Cosmology from weak lensing, galaxy clustering, CMB lensing and tSZ: II. Optimizing Roman survey design for CMB cross-correlation science

We explore synergies between the Nancy Grace Roman Space Telescope High Latitude Wide Area Survey (HLWAS) and CMB experiments, specifically Simons Observatory (SO) and CMB-Stage4 (S4). Our simulated analyses include weak lensing, photometric galaxy clustering, CMB lensing, thermal SZ, and cross-correlations between these probes. While we assume the nominal 16,500 square degree area for SO and S4, we consider multiple survey designs for Roman that overlap with Rubin Observatory's Legacy Survey of Space and Time (LSST): the 2000 square degree reference survey using four photometric bands, and two shallower single-band surveys that cover 10,000 and 18,000 square degree, respectively. We find a ~2x increase in the dark energy figure of merit when including CMB-S4 data for all Roman survey designs. We further find a strong increase in constraining power for the Roman wide survey scenario cases, despite the reduction in galaxy number density, and the increased systematic uncertainties assumed due to the single band coverage. Even when tripling the already worse systematic uncertainties in the Roman wide scenarios, which reduces the 10,000 square degree FoM from 269 to 178, we find that the larger survey area is still significantly preferred over the reference survey (FoM 64). We conclude that for the specific analysis choices and metrics of this paper, a Roman wide survey is unlikely to be systematics-limited (in the sense that one saturates the improvement that can be obtained by increasing survey area). We outline several specific implementations of a two-tier Roman survey (1000 square degree with 4 bands, and a second wide tier in one band) that can further mitigate the risk of systematics for Roman wide concepts.

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arXiv2024

Impact of cosmology dependence of baryonic feedback in weak lensing

Robust modeling of non-linear scales is critical for accurate cosmological inference in Stage IV surveys. For weak lensing analyses in particular, a key challenge arises from the incomplete understanding of how non-gravitational processes, such as supernovae and active galactic nuclei - collectively known as baryonic feedback - affect the matter distribution. Several existing methods for modeling baryonic feedback treat it independently from the underlying cosmology, an assumption which has been found to be inaccurate by hydrodynamical simulations. In this work, we examine the impact of this coupling between baryonic feedback and cosmology on parameter inference at LSST Y1 precision. We build mock 3$\times$2pt data vectors using the Magneticum suite of hydrodynamical simulations, which span a wide range of cosmologies while keeping subgrid parameters fixed. We perform simulated likelihood analyses for two baryon mitigation techniques: (i) the Principal Component Analysis (PCA) method which identifies eigenmodes for capturing the effect baryonic feedback on the data vector and (ii) HMCode2020 (Mead et al. 2021) which analytically models the modification in the matter distribution using a halo model approach. Our results show that the PCA method is robust to the coupling between cosmology and baryonic feedback, whereas, when using HMCode2020 there can be up to $0.5\sigma$ bias in $\Omega_\text{m}$-$S_8$. For HMCode2020, the bias also correlates with the input cosmology while for PCA we find no such correlation.

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arXiv2024

Testing the thermal Sunyaev-Zel'dovich power spectrum of a halo model using hydrodynamical simulations

Statistical properties of LSS serve as powerful tools to constrain the cosmological properties of our Universe. Tracing the gas pressure, the tSZ effect is a biased probe of mass distribution and can be used to test the physics of feedback or cosmological models. Therefore, it is crucial to develop robust modeling of hot gas pressure for applications to tSZ surveys. Since gas collapses into bound structures, it is expected that most of the tSZ signal is within halos produced by cosmic accretion shocks. Hence, simple empirical halo models can be used to predict the tSZ power spectra. In this study, we employed the HMx halo model to compare the tSZ power spectra with those of several hydrodynamical simulations: the Horizon suite and the Magneticum simulation. We examined various contributions to the tSZ power spectrum across different redshifts, including the one- and two-halo term decomposition, the amount of bound gas, the importance of different masses and the electron pressure profiles. Our comparison of the tSZ power spectrum reveals discrepancies that increase with redshift. We find a 20% to 50% difference between the measured and predicted tSZ angular power spectrum over the multipole range $\ell=10^3-10^4$. Our analysis reveals that these differences are driven by the excess of power in the predicted two-halo term at low k and in the one-halo term at high k. At higher redshifts (z~3), simulations indicate that more power comes from outside the virial radius than from inside suggesting a limitation in the applicability of the halo model. We observe differences in the pressure profiles, despite the fair level of agreement on the tSZ power spectrum at low redshift with the default calibration of the halo model. In conclusion, our study suggests that the properties of the halo model need to be carefully controlled against real or mock data to be proven useful for cosmological purposes.

astro-ph.CO↗

arXiv2024

Kinematic Lensing Inference II: Cluster Lensing with $\mathcal{O}$(1) Galaxies

We present the first detection of a cluster lensing signal with `Kinematic Lensing' (KL), a novel weak lensing method that combines photometry, spectroscopy, and the Tully-Fisher relation to enable shear measurements with individual source galaxies. This is the second paper in a two-part series aimed at measuring a KL signal from data. The first paper, arXiv:2209.11811, describes the inference pipeline, which jointly forward models galaxy imaging and spectroscopy, and demonstrates unbiased shear inference with simulated data. This paper presents measurements of the lensing signal from the galaxy cluster Abell 2261. We obtain spectroscopic observations of background disk galaxies in the cluster field selected from the CLASH Subaru catalog. The final sample consists of three source galaxies while the remaining are rejected due to insufficient signal-to-noise, spectroscopic failures, and inadequately sampled rotation curves. We apply the KL inference pipeline to the three sources and find the shear estimates to be in broad agreement with traditional weak lensing measurements. The typical shear measurement uncertainty for our sources is $\sigma(g_+)\approx 0.026$, which represents approximately a ten-fold improvement over the weak lensing shape noise. We identify target selection and observing strategy as the key avenues of improvement for future KL programs.

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