arXiv subjects

Anže Slosar

Publications and source records attributed to Anže Slosar.

At least 19 recordsLinked to original sources

arXiv2026

Fisher Forecasting for the DESC with $\texttt{Augur}$

The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) has begun its ten-year survey of the entire visible southern hemisphere. To ensure robust cosmological measurements, computationally inexpensive investigations of modeling choices must be made to gauge the performance of proposed cosmological analyses. In this paper, we introduce the $\texttt{Augur}$ tool of the Dark Energy Science Collaboration (DESC), which provides Fisher forecasts for cosmological inference for the LSST using software frameworks designed for DESC science. We test the pipeline by comparing it to forecasts produced by external code and direct sampling of the posterior via nested sampling methods, finding good agreement between all methods. We additionally investigate a range of modeling and hyperparameter choices for a 3$\times$2pt investigation in harmonic space, providing users with diagnostics to obtain reliable forecasts. $\texttt{Augur}$ will be continually updated to be compatible with the other tools in the DESC software ecosystem as additional probes and functionality become available.

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arXiv2026

The Lunar Farside Transients and Technology Telescope (LFT3) Mission

We present here an overview of the Lunar Farside Transients and Technology Telescope (LFT3) mission to take advantage of the extremely clear radio frequency environment on the lunar farside. Radio observations performed from the lunar farside effectively and fully mitigate two unavoidable limitations of terrestrial-based radio telescopes: (i) the prevalence of interfering radio transmitters from human activity; and (ii) the impact of the Earth's ionosphere. However, in the era of cost-effective access to the Moon, there are many scheduled lunar missions over the next few years, and the window of opportunity to perform radio interference-free observations from the lunar farside is closing fast. LFT3 is the only mission proposed to go to the lunar farside and exploit this unique opportunity in human history. LFT3 will observe in an uncluttered radio environment to conduct unambiguous technosignature searches, transient surveys, solar physics and planetary emissions studies, spectral line observations, and cosmological science observations. LFT3 will provide an important incumbent use of the microwave spectrum for cislunar radio astronomy.

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arXiv2026

Joint Estimation of Properties of the Lunar Subsurface and Galactic Foregrounds with LuSEE-Night

The Lunar Surface Electromagnetics Experiment (LuSEE-Night) is a joint NASA-DOE-ESA low-frequency radio telescope that will reach the lunar far side in 2027. The unknown dielectric properties of the subsurface at the LuSEE-Night landing site impose the most significant limitation for precision instrument calibration, as reflections from the lunar subsurface can change the primary beam at the 10-20% level. Simulations of these effects have provided insight and concern, showing that the lunar subsurface modeled as a lossy dielectric can absorb a large amount of the power of the sky signal. While this absorption may not strongly impact the signal-to-noise ratio in a sky-noise-dominated regime, it could complicate the beam pattern and make the signal more difficult to model and interpret. We have simulated the far-field properties of the LuSEE-Night beam for varying dielectric profiles of the lunar subsurface. We find that varying the properties of the lunar subsurface has the most significant impact around the antenna resonance, impacting its amplitude, position and width. Conversely, changing the properties of the foreground impacts the data across the band. We use a Bayesian inference pipeline to jointly estimate parameters of a galactic foreground model and dielectric properties of the lunar subsurface around the LuSEE-Night landing site and find that parameters of both the galaxy and subsurface properties can be estimated jointly. While the modeling is somewhat idealized, we believe that the results are largely robust owing to the fact that spectral variations for plausible subsurface and galaxy models have very different spectral signatures.

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arXiv2026

Field-level likelihood for projected fields: Evolved projected fields from initial projected fields

The evolved cosmological matter density field is fully determined by the initial matter density field at fixed cosmological parameters. However, the two-dimensional cosmological projected matter density field, relevant for weak-lensing and photometric galaxy studies, is fully determined by the initial projected matter density field only at the linear order. At non-linear order, the entire volume of initial matter contributes. We study a model for the evolved projected density field that is deterministic in the initial projected density fields and probabilistic in the effects of the remaining modes in the initial conditions. We write down predictions for the mean evolved projected field model using Lagrangian perturbation theory. We run a suite of small $N$-body simulations with fixed projected initial conditions and measure the statistical properties of the ensemble of evolved projected fields. Measurements and theory are in good agreement and show that the information on the initial projected fields is exponentially suppressed on non-linear scales. We implement this approach in a likelihood code and use Hamiltonian Monte-Carlo sampling to show that initial fields can be reconstructed even in the presence of non-trival mask features.

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arXiv2026

Steeling Weak Lensing Source Galaxy Samples against Systematics using Wide Field Spectroscopy

We investigate the cosmological constraining power of combined weak galaxy lensing and galaxy clustering probes, i.e. $3\times2$-point analyses, assuming flexible models for redshift uncertainty, and Lagrangian perturbation theory and hybrid effective field theory models for galaxy intrinsic alignments, galaxy bias and baryonic physics. In this context, we provide a detailed accounting of the limiting systematics on $3\times2$-point analyses. Our main finding is that in the presence of current levels of uncertainty on baryonic physics, the information content of weak lensing analyses saturates on quasi-linear scales, allowing the use of source galaxy samples that are significantly less dense, e.g. with number densities of $5\rm \, arcmin^{-2}$, without sacrificing constraining power, provided that redshift distributions can be calibrated at the $σ(\langle z\rangle)=0.005$ level. We show that for sufficiently narrow lens and source redshift distributions, intrinsic alignment contributions can be largely self-calibrated, though sufficient flexibility must be given to the redshift and scale dependence of this signal. The near optimality of such relatively sparse source galaxy samples opens the possibility to directly calibrate the redshift distributions and intrinsic alignment contamination of such a sample using a spectroscopic instrument like DESI, thus mitigating the dominant systematics in weak lensing analyses.

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arXiv2026

Linear map-making with LuSEE-Night

LuSEE-Night is a pathfinder radio telescope on the lunar far side employing four 3-m monopole antennas arranged as two horizontal cross pseudo-dipoles on a rotational stage and sensitive to the radio sky in the 1-50 MHz frequency band. LuSEE-Night measures the corresponding 16 correlation products as a function of frequency. While each antenna combination measures radiation coming from a large area of the sky, their aggregate information as a function of phase in the lunar cycle and rotational stage position can be deconvolved into a low-resolution map of the sky. We study this deconvolution using linear map-making based on the Wiener filter algorithm. We illustrate how systematic effects can be effectively marginalised over as contributions to the noise covariance and demonstrate this technique on beam knowledge uncertainty and gain fluctuations. With reasonable assumptions about instrument performance, we show that LuSEE-Night should be able to map the sub-50 MHz sky at a ~5-degree resolution.

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arXiv2026

Electrical coupling of a horizontal dipole antenna to a dielectric half-space: applications to radio astronomy from the lunar surface

The far side of the Moon, shielded from terrestrial radio frequency interference and beyond the influence of Earth's ionosphere, should offer a uniquely quiet environment for radio astronomy and cosmological experiments. The radio sky below 30 MHz is largely unexplored and is thought to contain spectral signatures of new physics in the early, high-redshift Universe. Achieving precision measurements in this band requires accurate understanding of antenna performance and systematics. For upcoming lunar surface radio astronomy missions, this modeling will be challenging because antennas will deploy at heights that are only a small fraction of a wavelength above the lunar regolith, where strong coupling between the antenna and the surface can significantly alter impedance, radiation patterns, and efficiency. The challenge is compounded by the layered dielectric structure of the regolith and the tendency for permittivity to increase with depth, both of which are difficult to represent faithfully in numerical simulations. In this work, we review theoretical predictions for the behavior of a simple horizontal dipole above a dielectric half-space, representing the lunar regolith, and compare them with simulation results obtained using the Ansys HFSS integral equation solver. We quantify how the antenna impedance and beam pattern couple to the sky for a representative lunar surface radio astronomy experiment. The results show that surface induced effects decrease rapidly, even for modest increases in antenna height above the regolith. Conversely, a dipole antenna placed on or very near the lunar surface will exhibit complex spectral response that renders systematics control very difficult without detailed information on regolith properties.

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arXiv2026

Constraints from CMB lensing tomography with projected bispectra

We measure the angular power spectrum and bispectrum of the projected overdensity of photometric DESI luminous red galaxies, and its cross-correlation with maps of the Cosmic Microwave Background lensing convergence from \planck. This analysis is enabled by the use of the ``filtered-squared bispectrum'' approach, introduced in previous work, which we generalise here to the case of cross-correlations between multiple fields. The projected galaxy bispectrum is detected at very high significance (above $30σ$ in all redshift bins), and the galaxy-galaxy-convergence bispectrum is detected above $5σ$ in the three highest-redshift bins. We find that the bispectrum is reasonably well described over a broad range of scales by a tree-level prediction using the linear galaxy bias measured from the power spectrum. We carry out the first cosmological analysis combining projected power spectra and bispectra under a relatively simple model, and show that the galaxy bispectrum can be used in combination with the power spectrum to place a constraint on the amplitude of matter fluctuations, $σ_8$, an on the non-relativistic matter fraction $Ω_m$. We find that data combinations involving the galaxy bispectrum recover constraints on these parameters that are in good agreement with those found from the traditional ``2$\times$2-point'' combination of galaxy-galaxy and galaxy-convergence power spectra, across all redshift bins.

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arXiv2025

Fast Projected Bispectra: the filter-square approach

The study of third-order statistics in large-scale structure analyses has been hampered by the increased complexity of bispectrum estimators (compared to power spectra), the large dimensionality of the data vector, and the difficulty in estimating its covariance matrix. In this paper we present the filtered-squared bispectrum (FSB), an estimator of the projected bispectrum effectively consisting of the cross-correlation between the square of a field filtered on a range of scales and the original field. Within this formalism, we are able to recycle much of the infrastructure built around power spectrum measurement to construct an estimator that is both fast and robust against mode-coupling effects caused by incomplete sky observations. Furthermore, we demonstrate that the existing techniques for the estimation of analytical power spectrum covariances can be used within this formalism to calculate the bispectrum covariance at very high accuracy, naturally accounting for the most relevant Gaussian and non-Gaussian contributions in a model-independent manner.

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arXiv2024

Superhorizon isocurvature fluctuations relax tensions

We present a new class of models that have potential to alleviate tensions present in the cosmological data today. We postulate about variation in the sound horizon scale on superhorizon scales, i.e., on scales that are larger than that of the present observable low-redshift Universe ($\gtrsim 1\,$Gpc) while at the same time smaller than the largest scales probed by the cosmic microwave background (CMB) ($\lesssim10\,$Gpc). In this scenario, CMB peaks are naturally smoothed as preferred by the Planck data, while at the same time the low-redshift baryon acoustic oscillation calibration is partially decoupled from the CMB. Taking superhorizon variations in baryon fraction as an example and using approximate modeling, we find improvement in the best fit Planck power spectrum model $Δχ^2 \sim 6$ for 1 extra degree of freedom with the relevant extension parameter $10^3 σ_b = 2.10 \pm 0.60 $, implying about 10\% variations in baryon fraction across the Universe. At the same time, $S_8$ drops by about 1 sigma, easing tension with weak lensing surveys. We find that the combination of Planck 2018 data, eBOSS BAO data, and Riess \textit{et al.} distance ladder Hubble parameter determination produce a satisfactory fit in our model if we allow for a phantom dark energy equation of state.

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arXiv2024

Searching for Parity Violation in SDSS DR16 Lyman-α Forest Data

The four-point correlation function is the lowest order correlation function for scalar fields that can be used to probe statistical parity invariance in an isotropic universe. There are intriguing claims of detection of parity violation in the 4-point function of BOSS galaxy clustering data. We apply the same estimator to the public SDSS Data Release 16 Lyman-$α$ forest data. Lyman-$α$ forest data probes a different redshift range and is sensitive to a different density regime using a completely different technique. A detection would therefore be a strong indication of new physics. We identify accurate covariance matrix as a crucial impediment to performing this measurement accurately, consistent with existing literature on galaxy 4-point function. We discuss several approaches to estimating the covariance matrix, several of which produce spurious detection. Using a robust, but very suboptimal, covariance matrix derived from subsample bootstrapping, we find no evidence for parity violation.

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arXiv2024

Point Spread Function Deconvolution Using a Convolutional Autoencoder for Astronomical Applications

A major issue in optical astronomical image analysis is the combined effect of the instrument's point spread function (PSF) and the atmospheric seeing that blurs images and changes their shape in a way that is band and time-of-observation dependent. In this work we present a very simple neural network based approach to non-blind image deconvolution that relies on feeding a Convolutional Autoencoder (CAE) input images that have been preprocessed by convolution with the corresponding PSF and its regularized inverse, a method which is both conceptually simple and computationally less intensive. We also present here, a new approach for dealing with limited input dynamic range of neural networks compared to the dynamic range present in astronomical images.

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arXiv2024

LuSEE-Night power requirements and power generation strategy

The Lunar Surface Electromagnetics Experiment at Night (LuSEE-Night) is a project designed to investigate the feasibility of observing the Cosmic Dark Ages using an instrument on the lunar far-side. LuSEE-Night will measure the redshifted 21 cm transition of neutral hydrogen over a frequency range of 0.1-50 MHz, covering the redshift range 27 < z < 1100. The LuSEE-Night instrument is a radio frequency spectrometer, consisting of four horizontal monopole antennas, arranged to give wide zenith-pointing beams with two orthogonal linear polarizations. This combination of polarization, spectral, and angular sensitivity will be necessary to separate the cosmological signal from significantly stronger foreground emissions. LuSEE-Night will observe in drift scan during lunar night while the moon shields it from radio frequency interference from both the Earth and sun, and will transmit science and telemetry data back to Earth via an orbital relay during the lunar day. LuSEE-Night will have to operate in a challenging environment: its electronics must operate under hard radiation, the instrument must be thermally isolated during the cold 100~K lunar night, and have a thermal rejection path to survive the 390~K daytime temperature, and its photovoltaic and battery systems must provide sufficient power to operate during two weeks of lunar night. Furthermore, the instrument spectrometer must be powered throughout the lunar night using only a 7~kWh battery, due to mass limitations. Here we describe the power generation, storage, and delivery subsystems of the LuSEE-Night instrument, and the simulations which were performed to design the power subsystems and ensure instrument survival and operation throughout the long lunar night. We also describe the Concept of Operations (ConOps) developed for the LuSEE-Night mission, which derives from the power management simulations.

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arXiv2024

The Completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: Cosmological Implications from two Decades of Spectroscopic Surveys at the Apache Point observatory

We present the cosmological implications from final measurements of clustering using galaxies, quasars, and Ly$α$ forests from the completed Sloan Digital Sky Survey (SDSS) lineage of experiments in large-scale structure. These experiments, composed of data from SDSS, SDSS-II, BOSS, and eBOSS, offer independent measurements of baryon acoustic oscillation (BAO) measurements of angular-diameter distances and Hubble distances relative to the sound horizon, $r_d$, from eight different samples and six measurements of the growth rate parameter, $fσ_8$, from redshift-space distortions (RSD). This composite sample is the most constraining of its kind and allows us to perform a comprehensive assessment of the cosmological model after two decades of dedicated spectroscopic observation. We show that the BAO data alone are able to rule out dark-energy-free models at more than eight standard deviations in an extension to the flat, $Λ$CDM model that allows for curvature. When combined with Planck Cosmic Microwave Background (CMB) measurements of temperature and polarization the BAO data provide nearly an order of magnitude improvement on curvature constraints. The RSD measurements indicate a growth rate that is consistent with predictions from Planck primary data and with General Relativity. When combining the results of SDSS BAO and RSD with external data, all multiple-parameter extensions remain consistent with a $Λ$CDM model. Regardless of cosmological model, the precision on $Ω_Λ$, $H_0$, and $σ_8$, remains at roughly 1\%, showing changes of less than 0.6\% in the central values between models. The inverse distance ladder measurement under a o$w_0w_a$CDM yields $H_0= 68.20 \pm 0.81 \, \rm km\, s^{-1} Mpc^{-1}$, remaining in tension with several direct determination methods. (abridged)

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arXiv2024

Recovering 21cm Monopole Signals Without Smoothness

We expect the monopole signal at the lowest frequencies below $100\,$MHz to be composed of two components: the deep Rayleigh-Jeans tail of the cosmic microwave background and two distinct features: the dark ages trough at $\sim 17\,$MHz and the cosmic dawn trough at $\sim 75\,$Mhz. These are hidden under orders of magnitude brighter foregrounds whose emission is approximately a power-law with a spectral index $\approx -2.5$. It is usually assumed that monopole signals of interest are separable from foregrounds based on spectral smoothness. We argue that this is a difficult approach and likely impossible for the Dark Ages trough. Instead, we suggest that the fluctuations in the foreground emission around the sky should be used to build a model distribution of possible shapes of foregrounds, which can be used to constrain the presence of a monopole signal. We implement this idea using normalizing flows and show that this technique allows for efficient unsupervised detection of the amplitude, width, and center of the Dark Ages trough as well as the Rayleigh-Jeans tail of the cosmic microwave background for a sufficiently sensitive experiment. We show that achromatic and smooth response significantly helps with foreground separation. We discuss the limitations of the inherent assumptions in this method and the impact on the design of future low-frequency experiments.

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arXiv2024

Can we constrain structure growth from galaxy proper motions?

Galaxy peculiar velocities can be used to trace the growth of structure on cosmological scales. In the radial direction, peculiar velocities cause redshift space distortions, an established cosmological probe, and can be measured individually in the presence of an independent distance indicator. In the transverse direction, peculiar velocities cause proper motions. In this case, however, the proper motions are too small to detect on a galaxy-by-galaxy basis for any realistic experiment in the foreseeable future, but could be detected statistically in cross-correlation with other tracers of the density fluctuations. We forecast the sensitivity for a detection of transverse peculiar velocities through the cross-correlation of a proper motion survey, modelled after existing extragalactic samples measured by Gaia, and an overlaping galaxy survey. In particular, we consider a low-redshift galaxy sample, and a higher-redshift quasar sample. We find that, while the expected cosmological signal is below the expected statistical uncertainties from current data using cross-correlations, the sensitivity can improve fast with future experiments, and the threshold for detection may not be too far away in the future. Quantitatively, we find that the signal-to-noise ratio for detection is in the range $S/N\sim0.3$, with most of the signal concentrated at low redshifts $z\lesssim0.3$. If detected, this signal is sensitive to the product of the expansion and growth rates at late times, and thus would constitute an independent observable, sensitive to both background expansion and large-scale density fluctuations.

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arXiv2023

Neural Network Based Point Spread Function Deconvolution For Astronomical Applications

Optical astronomical images are strongly affected by the point spread function (PSF) of the optical system and the atmosphere (seeing) which blurs the observed image. The amount of blurring depends both on the observed band, and on the atmospheric conditions during observation. A typical astronomical image will likely have a unique PSF, that is non-circular and different in different bands. At the same time, observations of known stars also give us an accurate determination of this PSF. Therefore, any serious candidate for production analysis of astronomical images must take the known PSF into account during the image analysis. So far, the majority of applications of neural networks (NN) to astronomical image analysis have ignored this problem by assuming a fixed PSF in training and validation. We present a neural-network based deconvolution algorithm based on Deep Wiener Deconvolution Network (DWDN). This algorithm belongs to a class of non-blind deconvolution algorithms, since it assumes the PSF shape is known. We study the performance of different versions of this algorithm under realistic observational conditions in terms of the recovery of the most relevant astronomical quantities such as colors, ellipticities and orientations. We investigate custom loss functions that optimize the recovery of astronomical quantities with mixed results.

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arXiv2023

Cosmology with 6 parameters in the Stage-IV era: efficient marginalisation over nuisance parameters

The analysis of photometric large-scale structure data is often complicated by the need to account for many observational and astrophysical systematics. The elaborate models needed to describe them often introduce many ``nuisance parameters'', which can be a major inhibitor of an efficient parameter inference. In this paper we introduce an approximate method to analytically marginalise over a large number of nuisance parameters based on the Laplace approximation. We discuss the mathematics of the method, its relation to concepts such as volume effects and profile likelihood, and show that it can be further simplified for calibratable systematics by linearising the dependence of the theory on the associated parameters. We quantify the accuracy of this approach by comparing it with traditional sampling methods in the context of existing data from the Dark Energy Survey, as well as futuristic Stage-IV photometric data. The linearised version of the method is able to obtain parameter constraints that are virtually equivalent to those found by exploring the full parameter space for a large number of calibratable nuisance parameters, while reducing the computation time by a factor 3-10. Furthermore, the non-linearised approach is able to analytically marginalise over a large number of parameters, returning constraints that are virtually indistinguishable from the brute-force method in most cases, accurately reproducing both the marginalised uncertainty on cosmological parameters, and the impact of volume effects associated with this marginalisation. We provide simple recipes to diagnose when the approximations made by the method fail and one should thus resort to traditional methods. The gains in sampling efficiency associated with this method enable the joint analysis of multiple surveys, typically hindered by the large number of nuisance parameters needed to describe them.

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