arXiv subjects

Anže Slosar

Publications and source records attributed to Anže Slosar.

At least 37 records · Page 2Linked to original sources

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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arXiv2023

Galaxy bias in the era of LSST: perturbative bias expansions

Upcoming imaging surveys will allow for high signal-to-noise measurements of galaxy clustering at small scales. In this work, we present the results of the LSST bias challenge, the goal of which is to compare the performance of different nonlinear galaxy bias models in the context of LSST Y10 data. Specifically, we compare two perturbative approaches, Lagrangian perturbation theory (LPT) and Eulerian PT (EPT) to two variants of Hybrid Effective Field Theory (HEFT), with our fiducial implementation of these models including terms up to second order in the bias expansion as well as nonlocal bias and deviations from Poissonian stochasticity. We consider different simulated galaxy samples and test the performance of the bias models in a tomographic joint analysis of LSST-Y10-like galaxy clustering, galaxy-galaxy-lensing and cosmic shear. We find both HEFT methods as well as LPT and EPT combined with non-perturbative predictions for the matter power spectrum to yield unbiased constraints on cosmological parameters up to at least a maximal scale of $k_{\mathrm{max}}=0.4 \; \mathrm{Mpc}^{-1}$ for all samples considered, even in the presence of assembly bias. While we find that we can reduce the complexity of the bias model for HEFT without compromising fit accuracy, this is not generally the case for the perturbative models. We find significant detections of non-Poissonian stochasticity in all cases considered, and our analysis shows evidence that small-scale galaxy clustering predominantly improves constraints on galaxy bias rather than cosmological parameters. These results therefore suggest that the systematic uncertainties associated with current nonlinear bias models are likely to be subdominant compared to other sources of error for tomographic analyses of upcoming photometric surveys, which bodes well for future galaxy clustering analyses using these high signal-to-noise data. [abridged]

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arXiv2023

Hyper Suprime-Cam Year 3 Results: Cosmology from Cosmic Shear Power Spectra

We measure weak lensing cosmic shear power spectra from the three-year galaxy shear catalog of the Hyper Suprime-Cam (HSC) Subaru Strategic Program imaging survey. The shear catalog covers $416 \ \mathrm{deg}^2$ of the northern sky, with a mean $i$-band seeing of 0.59 arcsec and an effective galaxy number density of 15 $\mathrm{arcmin}^{-2}$ within our adopted redshift range. With an $i$-band magnitude limit of 24.5 mag, and four tomographic redshift bins spanning $0.3 \leq z_{\mathrm{ph}} \leq 1.5$ based on photometric redshifts, we obtain a high-significance measurement of the cosmic shear power spectra, with a signal-to-noise ratio of approximately 26.4 in the multipole range $300<\ell<1800$. The accuracy of our power spectrum measurement is tested against realistic mock shear catalogs, and we use these catalogs to get a reliable measurement of the covariance of the power spectrum measurements. We use a robust blinding procedure to avoid confirmation bias, and model various uncertainties and sources of bias in our analysis, including point spread function systematics, redshift distribution uncertainties, the intrinsic alignment of galaxies and the modeling of the matter power spectrum. For a flat $Λ$CDM model, we find $S_8 \equiv σ_8 (Ω_m/0.3)^{0.5} =0.776^{+0.032}_{-0.033}$, which is in excellent agreement with the constraints from the other HSC Year 3 cosmology analyses, as well as those from a number of other cosmic shear experiments. This result implies a $\sim$$2σ$-level tension with the Planck 2018 cosmology. We study the effect that various systematic errors and modeling choices could have on this value, and find that they can shift the best-fit value of $S_8$ by no more than $\sim$$0.5σ$, indicating that our result is robust to such systematics.

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arXiv2022

Combining cosmic shear data with correlated photo-$z$ uncertainties: constraints from DESY1 and HSC-DR1

An accurate calibration of the source redshift distribution $p(z)$ is a key aspect in the analysis of cosmic shear data. This, one way or another, requires the use of spectroscopic or high-quality photometric samples. However, the difficulty to obtain colour-complete spectroscopic samples matching the depth of weak lensing catalogs means that the analyses of different cosmic shear datasets often use the same samples for redshift calibration. This introduces a source of statistical and systematic uncertainty that is highly correlated across different weak lensing datasets, and which must be accurately characterised and propagated in order to obtain robust cosmological constraints from their combination. In this paper we introduce a method to quantify and propagate the uncertainties on the source redshift distribution in two different surveys sharing the same calibrating sample. The method is based on an approximate analytical marginalisation of the $p(z)$ statistical uncertainties and the correlated marginalisation of residual systematics. We apply this method to the combined analysis of cosmic shear data from the DESY1 data release and the HSC-DR1 data, using the COSMOS 30-band catalog as a common redshift calibration sample. We find that, although there is significant correlation in the uncertainties on the redshift distributions of both samples, this does not change the final constraints on cosmological parameters significantly. The same is true also for the impact of residual systematic uncertainties from the errors in the COSMOS 30-band photometric redshifts. Additionally, we show that these effects will still be negligible in Stage-IV datasets. Finally, the combination of DESY1 and HSC-DR1 allows us to constrain the ``clumpiness'' parameter to $S_8 = 0.768^{+0.021}_{-0.017}$. This corresponds to a $\sim\sqrt{2}$ improvement in uncertainties with respect to either DES or HSC alone.

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arXiv2022

Astrometry in two-photon interferometry using Earth rotation fringe scan

Optical interferometers may not require a phase-stable optical link between the stations if instead sources of quantum-mechanically entangled pairs could be provided to them, enabling long baselines. We developed a new variation of this idea, proposing that photons from two different astronomical sources could be interfered at two decoupled stations. Interference products can then be calculated in post-processing or requiring only a slow, classical connection between stations. In this work, we investigated practical feasibility of this approach. We developed a Bayesian analysis method for the earth rotation fringe scanning technique and showed that in the limit of high signal-to-noise ratio it reproduced the results from a simple Fisher matrix analysis. We identify candidate stair pairs in the northern hemisphere, where this technique could be applied. With two telescopes with an effective collecting area of $\sim 2$ m$^2$, we could detect fringing and measure the astrometric separation of the sources at $\sim 10\,μ$as precision in a few hours of observations, in agreement with previous estimates.

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arXiv2022

Fitting covariance matrix models to simulations

Data analysis in cosmology requires reliable covariance matrices. Covariance matrices derived from numerical simulations often require a very large number of realizations to be accurate. When a theoretical model for the covariance matrix exists, the parameters of the model can often be fit with many fewer simulations. We write a likelihood-based method for performing such a fit. We demonstrate how a model covariance matrix can be tested by examining the appropriate $χ^2$ distributions from simulations. We show that if model covariance has amplitude freedom, the expectation value of second moment of $χ^2$ distribution with a wrong covariance matrix will always be larger than one using the true covariance matrix. By combining these steps together, we provide a way of producing reliable covariances without ever requiring running a large number of simulations. We demonstrate our method on two examples. First, we measure the two-point correlation function of halos from a large set of $10000$ mock halo catalogs. We build a model covariance with $2$ free parameters, which we fit using our procedure. The resulting best-fit model covariance obtained from just $100$ simulation realizations proves to be as reliable as the numerical covariance matrix built from the full $10000$ set. We also test our method on a setup where the covariance matrix is large by measuring the halo bispectrum for thousands of triangles for the same set of mocks. We build a block diagonal model covariance with $2$ free parameters as an improvement over the diagonal Gaussian covariance. Our model covariance passes the $χ^2$ test only partially in this case, signaling that the model is insufficient even using free parameters, but significantly improves over the Gaussian one.

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arXiv2022

Two-photon amplitude interferometry for precision astrometry

Improved quantum sensing of photons from astronomical objects could provide high resolution observations in the optical benefiting numerous fields, including general relativity, dark matter studies, and cosmology. It has been recently proposed that stations in optical interferometers would not require a phase-stable optical link if instead sources of quantum-mechanically entangled pairs could be provided to them, potentially enabling hitherto prohibitively long baselines. A new refinement of this idea is developed, in which two photons from different sources are interfered at two separate and decoupled stations, requiring only a slow classical information link between them. We rigorously calculate the observables and contrast this new interferometric technique with the Hanbury Brown & Twiss intensity interferometry. We argue this technique could allow robust high-precision measurements of the relative astrometry of the two sources. A basic calculation suggests that angular precision on the order of $10$~microarcsecond in the relative opening angle could be achieved in a single night's observation of two bright stars.

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arXiv2022

A Self-Learning Neural Network Approach for RFI Detection and Removal in Radio Astronomy

We present a novel neural network (NN) method for the detection and removal of Radio Frequency Interference (RFI) from the raw digitized signal in the signal processing chain of a typical radio astronomy experiment. The main advantage of our method is that it does not require a training set. Instead, our method relies on the fact that the true signal of interest coming from astronomical sources is thermal and therefore described as a Gaussian random process, which cannot be compressed. We employ a variational encoder/decoder network to find the compressible information in the datastream that can explain the most variance with the fewest degrees of freedom. We demonstrate it on a set of toy problems and stored ringbuffers from the Baryon Mapping eXperiment (BMX) prototype. We find that the RFI subtraction is effective at cleaning simulated timestreams: while we find that the power spectra of the RFI-cleaned timestreams output by the NN suffer from extra signal consistent with additive noise, we find that it is generally around percent level across the band and sub 10 percent in contaminated spectral channels even when RFI power is an order of magnitude larger than the signal. We discuss advantages and limitations of this method and possible implementation in the front-end of future radio experiments.

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arXiv2022

Non-linearities in the Lyman-$α$ forest and in its cross-correlation with dark matter halos

Three-dimensional correlations of the Lyman-$α$ (Ly$α$) forest and cross correlations between the Ly$α$ forest and quasars have been measured on large scales, allowing a precise measurement of the baryon acoustic oscillation (BAO) feature at redshifts $z>2$. These 3D correlations are often modelled using linear perturbation theory, but full-shape analyses to extract cosmological information beyond BAO will require more realistic models capable of describing non-linearities present at smaller scales. We present a measurement of the Ly$α$ forest flux power spectrum from large hydrodynamic simulations -- the Sherwood simulations -- and compare it to different models describing the small-scale deviations from linear theory. We confirm that the model presented in Arinyo-i-Prats et al. (2015) fits the measured 3D power up to $k=10\, h\rm{Mpc^{-1}}$ with an accuracy better than 5%, and show that the same model can also describe the 1D correlations with similar precision. We also present, for the first time, an equivalent study for the cross-power spectrum of halos with the Ly$α$ forest, and we discuss different challenges we face when modelling the cross-power spectrum beyond linear scales. We make all our measured power spectra public in \url{https://github.com/andreufont/sherwood_p3d}. This study is a step towards joint analyses of 1D and 3D flux correlations, and towards using the quasar-Ly$α$ cross-correlation beyond BAO analyses.

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arXiv2022

Snowmass2021 Cosmic Frontier: Report of the CF04 Topical Group on Dark Energy and Cosmic Acceleration in the Modern Universe

Cosmological observations in the new millennium have dramatically increased our understanding of the Universe, but several fundamental questions remain unanswered. This topical group report describes the best opportunities to address these questions over the coming decades by extending observations to the $z<6$ universe. The greatest opportunity to revolutionize our understanding of cosmic acceleration both in the modern universe and the inflationary epoch would be provided by a new Stage V Spectroscopic Facility (Spec-S5) which would combine a large telescope aperture, wide field of view, and high multiplexing. Such a facility could simultaneously provide a dense sample of galaxies at lower redshifts to provide robust measurements of the growth of structure at small scales, as well as a sample at redshifts $2<z<5$ to measure cosmic structure at the largest scales, spanning a sufficient volume to probe primordial non-Gaussianity from inflation, to search for features in the inflationary power spectrum on a broad range of scales, to test dark energy models in poorly-explored regimes, and to determine the total neutrino mass and effective number of light relics. A number of compelling opportunities at smaller scales should also be pursued alongside Spec-S5. The science collaborations analyzing DESI and LSST data will need funding for a variety of activities, including cross-survey simulations and combined analyses. The results from these experiments can be greatly improved by smaller programs to obtain complementary data, including follow-up studies of supernovae and spectroscopy to improve photometric redshift measurements. The best future use of the Vera C. Rubin Observatory should be evaluated later this decade after the first LSST analyses have been done. Finally, investments in pathfinder projects could enable powerful new probes of cosmology to come online in future decades.

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arXiv2022

The MegaMapper: A Stage-5 Spectroscopic Instrument Concept for the Study of Inflation and Dark Energy

In this white paper, we present the MegaMapper concept. The MegaMapper is a proposed ground-based experiment to measure Inflation parameters and Dark Energy from galaxy redshifts at $2<z<5$. In order to achieve path-breaking results with a mid-scale investment, the MegaMapper combines existing technologies for critical path elements and pushes innovative development in other design areas. To this aim, we envision a 6.5-m Magellan-like telescope, with a newly designed wide field, coupled with DESI spectrographs, and small-pitch robots to achieve multiplexing of at least 26,000. This will match the expected achievable target density in the redshift range of interest and provide a 10x capability over the existing state-of the art, without a 10x increase in project budget.

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arXiv2022

Generalized Redundant Calibration of Radio Interferometers

Redundant calibration is a technique in radio astronomy that allows calibration of radio arrays whose antennas lie on a lattice by exploiting the fact that redundant baselines should see the same sky signal. Because the number of measured visibilities scales quadratically with the number of antennas but the number of unknowns describing the individual antenna responses and the available information about the sky scales only linearly with the array size, the problem is always over-constrained as long as the array is big and dense enough. This is true even for non-lattice array configurations. In this work we study a generalized algorithm in which a per-antenna gain is replaced with a number of gains. We show that it can successfully fit data from an approximately redundant array on square lattice with pointing and geometry errors, but that the models parameters are difficult to link to the quantities of interest. We discuss the parameterization, limitations, and possible extensions of this algorithm.

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arXiv2022

Galaxy Deblending using Residual Dense Neural networks

We present a new neural network approach for deblending galaxy images in astronomical data using Residual Dense Neural network (RDN) architecture. We train the network on synthetic galaxy images similar to the typical arrangements of field galaxies with a finite point spread function (PSF) and realistic noise levels. The main novelty of our approach is the usage of two distinct neural networks: i) a deblending network which isolates a single galaxy postage stamp from the composite and, ii) a classifier network which counts the remaining number of galaxies. The deblending proceeds by iteratively peeling one galaxy at a time from the composite until the image contains no further objects as determined by the classifier, or by other stopping criteria. By looking at the consistency in the outputs of the two networks, we can assess the quality of the deblending. We characterize the flux and shape reconstructions in different quality bins and compare our deblender with the industry standard, SExtractor. We also discuss possible future extensions for the project with variable PSFs and noise levels.

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arXiv2022

Perturbation theory models for LSST-era galaxy clustering: tests with sub-percent mock catalog measurements in Fourier and configuration space

We analyze the clustering of galaxies using the z=1.006 snapshot of the CosmoDC2 simulation, a high-fidelity synthetic galaxy catalog designed to validate analysis methods for the Large Synoptic Survey Telescope (LSST). We present sub-percent measurements of the galaxy auto-correlation and galaxy-dark matter cross correlations in Fourier space and configuration space for a magnitude-limited galaxy sample. At these levels of precision, the statistical errors of the measurement are comparable to the systematic effects present in the simulation and measurement procedure; nevertheless, using a hybrid-PT model, we are able to model non-linear galaxy bias with 0.5% precision up to scales of $k_{\rm max}= 0.5 \ h/{\rm Mpc}$ and $r_{\rm min}= 4 \ {\rm Mpc}/h$. While the linear bias parameter is measured with 0.01% precision, other bias parameters are determined with considerably weaker constraints and sometimes bimodal posterior distributions. We compare our fiducial model with lower dimensional models where the higher-order bias parameters are fixed at their co-evolution values and find that leaving these parameters free provides significant improvements in our ability to model small scale information. We also compare bias parameters for galaxy samples defined using different magnitude bands and find agreement between samples containing equal numbers of galaxies. Finally, we compare bias parameters between Fourier space and configuration space and find moderate tension between the two approaches. Although our model is often unable to fit the CosmoDC2 galaxy samples within the 0.1% precision of our measurements, our results suggest that the hybrid-PT model used in this analysis is capable of modeling non-linear galaxy bias within the percent level precision needed for upcoming galaxy surveys.

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arXiv2022

Snowmass2021 Cosmic Frontier White Paper: 21cm Radiation as a Probe of Physics Across Cosmic Ages

The 21cm line refers to a forbidden transition in neutral hydrogen associated with alignment of spins of the proton and electron. It is a very low energy transition that is emitted whenever there is neutral hydrogen in the Universe. Since baryons are mostly (~75%) hydrogen, one can in principle detect this emission throughout much of the history of the Universe. The dominant emission mechanism is different across cosmic ages. Before the photons decouple from matter, hydrogen is in an ionized state and does not emit in 21cm. After recombination and during the Dark Ages, at z ~ 30-1000, the 21cm emission is associated with density fluctuations in the neutral hydrogen medium. After the first stars turn on and galaxies begin to form, the 21cm emission traces bubbles of ionized hydrogen in the sea of the neutral medium. This epoch, spanning z ~ 6-30, is often referred to as cosmic dawn and the Epoch of Reionization (EoR). At redshifts below z<6, the intergalactic medium is largely ionized, but pockets of self-shielded neutral gas form in dense galactic environments and 21cm emission traces the distribution of galaxies. The vastly different emission mechanisms allow us to probe very different physics at different redshifts, corresponding to different observational frequencies. The instrumental challenges, namely building very sensitive and exquisitely calibrated radio telescopes, however, share many commonalities across frequency bands. The potential of the 21cm probe has been recognized by the Decadal Survey of Astronomy & Astrophysics, whose Panel on Cosmology identified the Dark Ages as its sole discovery area. We argue that HEP should recognize the potential of 21cm as a probe of fundamental physics across many axes and invest in the technology development that will enable full exploitation of this rich technique.

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arXiv2022

Snowmass2021 Cosmic Frontier White Paper: Observational Facilities to Study Dark Matter

We present an overview of future observational facilities that will significantly enhance our understanding of the fundamental nature of dark matter. These facilities span a range of observational techniques including optical/near-infrared imaging and spectroscopy, measurements of the cosmic microwave background, pulsar timing, 21-cm observations of neutral hydrogen at high redshift, and the measurement of gravitational waves. Such facilities are a critical component of a multi-pronged experimental program to uncover the nature of dark matter, while often providing complementary measurements of dark energy, neutrino physics, and inflation.

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arXiv2022

Validating Synthetic Galaxy Catalogs for Dark Energy Science in the LSST Era

Large simulation efforts are required to provide synthetic galaxy catalogs for ongoing and upcoming cosmology surveys. These extragalactic catalogs are being used for many diverse purposes covering a wide range of scientific topics. In order to be useful, they must offer realistically complex information about the galaxies they contain. Hence, it is critical to implement a rigorous validation procedure that ensures that the simulated galaxy properties faithfully capture observations and delivers an assessment of the level of realism attained by the catalog. We present here a suite of validation tests that have been developed by the Rubin Observatory Legacy Survey of Space and Time (LSST) Dark Energy Science Collaboration (DESC). We discuss how the inclusion of each test is driven by the scientific targets for static ground-based dark energy science and by the availability of suitable validation data. The validation criteria that are used to assess the performance of a catalog are flexible and depend on the science goals. We illustrate the utility of this suite by showing examples for the validation of cosmoDC2, the extragalactic catalog recently released for the LSST DESC second Data Challenge.

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