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Cora Dvorkin

Publications and source records attributed to Cora Dvorkin.

At least 37 records · Page 2Linked to original sources

Report of the Topical Group on Cosmic Probes of Dark Matter for Snowmass 2021

Cosmological and astrophysical observations currently provide the only robust, positive evidence for dark matter. Cosmic probes of dark matter, which seek to determine the fundamental properties of dark matter through observations of the cosmos, have emerged as a promising means to reveal the nature of dark matter. This report summarizes the current status and future potential of cosmic probes to inform our understanding of the fundamental nature of dark matter in the coming decade.

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Inferring subhalo effective density slopes from strong lensing observations with neural likelihood-ratio estimation

Strong gravitational lensing has emerged as a promising approach for probing dark matter models on sub-galactic scales. Recent work has proposed the subhalo effective density slope as a more reliable observable than the commonly used subhalo mass function. The subhalo effective density slope is a measurement independent of assumptions about the underlying density profile and can be inferred for individual subhalos through traditional sampling methods. To go beyond individual subhalo measurements, we leverage recent advances in machine learning and introduce a neural likelihood-ratio estimator to infer an effective density slope for populations of subhalos. We demonstrate that our method is capable of harnessing the statistical power of multiple subhalos (within and across multiple images) to distinguish between characteristics of different subhalo populations. The computational efficiency warranted by the neural likelihood-ratio estimator over traditional sampling enables statistical studies of dark matter perturbers and is particularly useful as we expect an influx of strong lensing systems from upcoming surveys.

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Going Beyond the Galaxy Power Spectrum: an Analysis of BOSS Data with Wavelet Scattering Transforms

We perform the first application of the wavelet scattering transform (WST) to actual galaxy observations, through a WST analysis of the BOSS DR12 CMASS dataset. We included the effects of redshift-space anisotropy, non-trivial survey geometry, systematic weights, and the Alcock-Paczynski distortion effect, following the commonly adopted steps for the power spectrum analysis. In order to capture the cosmological dependence of the WST, we use galaxy mocks obtained from the state-of-the-art ABACUSSUMMIT simulations, tuned to match the anisotropic correlation function of the BOSS CMASS sample in the redshift range $0.46<z<0.60$. Using our model for the WST coefficients, as well as for the first 2 multipoles of the galaxy power spectrum, that we use as reference, we perform a likelihood analysis of the CMASS data. We obtain the posterior probability distributions of 4 cosmological parameters, $\{ω_b,ω_c,n_s,σ_8\}$, as well as the Hubble constant, derived from a fixed value of the angular size of the sound horizon at last scattering measured by the Planck satellite, all of which are marginalized over the 7 nuisance parameters of the Halo Occupation Distribution model. The WST is found to deliver a substantial improvement in the values of the predicted $1σ$ errors compared to the regular power spectrum, which are tighter by a factor of $3-5$ in the case of flat and uninformative priors and by a factor of $3-8$, when a Big Bang Nucleosynthesis prior is applied on the value of $ω_b$. Our results are investigative and subject to certain approximations, which we discuss in the text.

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Weak Lensing Trispectrum and Kurt-Spectra

We introduce two kurt-spectra to probe fourth-order statistics of weak lensing convergence maps. Using state-of-the-art numerical simulations, we study the shapes of these kurt-spectra as a function of source redshifts and smoothing angular scales. We employ a pseudo-$C_{\ell}$ approach to estimate the spectra from realistic convergence maps in the presence of an observational mask and noise for stage-IV large-scale structure surveys. We compare these results against theoretical predictions calculated using the FFTLog formalism, and find that a simple nonlinear clustering model-the hierarchical ansatz-can reproduce the numerical trends for the kurt-spectra in the nonlinear regime. In addition, we provide estimators for beyond fourth-order spectra where no definitive analytical results are available, and present corresponding results from numerical simulations.

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Report of the Topical Group on Cosmic Probes of Fundamental Physics for for Snowmass 2021

Cosmic Probes of Fundamental Physics take two primary forms: Very high energy particles (cosmic rays, neutrinos, and gamma rays) and gravitational waves. Already today, these probes give access to fundamental physics not available by any other means, helping elucidate the underlying theory that completes the Standard Model. The last decade has witnessed a revolution of exciting discoveries such as the detection of high-energy neutrinos and gravitational waves. The scope for major developments in the next decades is dramatic, as we detail in this report.

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Probing Dark Matter with Strong Gravitational Lensing through an Effective Density Slope

Many dark matter (DM) models that are consistent with current cosmological data show differences in the predicted (sub)halo mass function, especially at sub-galactic scales, where observations are challenging due to the inefficiency of star formation. Strong gravitational lensing has been shown to be a useful tool for detecting dark low-mass (sub)halos through perturbations in lensing arcs, therefore allowing the testing of different DM scenarios. However, measuring the total mass of a perturber from strong lensing data is challenging. Over or underestimating perturber masses can lead to incorrect inferences about the nature of DM. In this paper, we argue that inferring an effective slope of the dark matter density profile, which is the power-law slope of perturbers at intermediate radii, where we expect the perturber to have the largest observable effect, is a promising way to circumvent these challenges. Using N-body simulations, we show that (sub)halo populations under different DM scenarios differ in their effective density slope distributions. Using realistic mocks of Hubble Space Telescope observations of strong lensing images, we show that the effective density slope of perturbers can be robustly measured with high enough accuracy to discern between different models. We also present our measurement of the effective density slope $γ=1.96\substack{+0.12 \\ -0.12}$ for the perturber in JVAS B1938+666, which we find to be a $2σ$ outlier of the cold dark matter scenario. More measurements of this kind are needed to be able to draw robust conclusions about the nature of dark matter.

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Snowmass2021 Cosmic Frontier White Paper: Probing dark matter with small-scale astrophysical observations

The current understanding of dark matter comes largely from measurements of the total matter content in the universe, from the distribution of gravitating matter on very large scales, and from rotation curves and velocity dispersions on sub-galactic scales. However, small-scale structure may well hold the key to unlocking the particle physics of the still-mysterious 85% of matter in the universe. Novel small-scale astrophysical probes of new particles and dark matter will become possible with a large data volume of high-precision measurements enabled by next-generation gravitational-wave detectors and advanced astrometry instruments. Cosmic microwave background and large-scale structure surveys will provide complementary constraints on dark matter models with unique small-scale signatures. We lay out the studies of small-scale structures and compact objects as dark matter probes, and summarize the requirements to achieve the goals.

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Substructure Detection Reanalyzed: Dark Perturber shown to be a Line-of-Sight Halo

Observations of structure at sub-galactic scales are crucial for probing the properties of dark matter, which is the dominant source of gravity in the universe. It will become increasingly important for future surveys to distinguish between line-of-sight halos and subhalos to avoid wrong inferences on the nature of dark matter. We reanalyze a sub-galactic structure (in lens JVAS B1938+666) that has been previously found using the gravitational imaging technique in galaxy-galaxy lensing systems. This structure has been assumed to be a satellite in the halo of the main lens galaxy. We fit the redshift of the perturber of the system as a free parameter, using the multi-plane thin-lens approximation, and find that the redshift of the perturber is $z_\mathrm{int} = 1.42\substack{+0.10 \\ -0.15}$ (with a main lens redshift of $z=0.881$). Our analysis indicates that this structure is more massive than the previous result by an order of magnitude. This constitutes the first dark perturber shown to be a line-of-sight halo with a gravitational lensing method.

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Skewing the CMB$\times$LSS: a Fast Method for Bispectrum Analysis

Upcoming cosmic microwave background (CMB) lensing measurements and tomographic galaxy surveys are expected to provide us with high-precision data sets in the coming years, thus paving the way for fruitful cross-correlation analyses. In this paper we study the information content of the weighted skew-spectrum, a nearly-optimal estimator of the angular bispectrum amplitude, as a means to extract non-Gaussian information on both bias and cosmological parameters from the bispectra of galaxies cross-correlated with CMB lensing, while gaining significantly on speed. Our results show that for the combination of the Planck satellite and the Dark Energy Spectroscopic Instrument (DESI), the difference in the constraints on bias and cosmological parameters from the skew-spectrum and the bispectrum is at most $17\%$. We further compare and find agreement between our theoretical skew-spectra and those estimated from N-body simulations, for which it is important to include gravitational non-linearities beyond perturbation theory and the post-Born effect for CMB lensing. We define an algorithm to apply the skew-spectrum estimator to the data and, as a preliminary step, we use the skew-spectra to constrain bias parameters and the amplitude of shot noise from the simulations through a Markov chain Monte Carlo likelihood analysis, finding that it may be possible to reach percent-level estimates for the linear bias parameter $b_1$.

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Towards an Optimal Estimation of Cosmological Parameters with the Wavelet Scattering Transform

Optimal extraction of the non-Gaussian information encoded in the Large-Scale Structure (LSS) of the universe lies at the forefront of modern precision cosmology. We propose achieving this task through the use of the Wavelet Scattering Transform (WST), which subjects an input field to a layer of non-linear transformations that are sensitive to non-Gaussianity in spatial density distributions through a generated set of WST coefficients. In order to assess its applicability in the context of LSS surveys, we apply the WST on the 3D overdensity field obtained by the Quijote simulations, out of which we extract the Fisher information in 6 cosmological parameters. It is subsequently found to deliver a large improvement in the marginalized errors on all parameters, ranging between $1.2-4\times$ tighter than the corresponding ones obtained from the regular 3D cold dark matter + baryon power spectrum, as well as a $50 \%$ improvement over the neutrino mass constraint given by the marked power spectrum. Through this first application on 3D cosmological fields, we demonstrate the great promise held by this novel statistic and set the stage for its future application to actual galaxy observations.

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Cosmological Constraints on Light (but Massive) Relics

Many scenarios of physics beyond the standard model predict new light, weakly coupled degrees of freedom, populated in the early universe and remaining as cosmic relics today. Due to their high abundances, these relics can significantly affect the evolution of the universe. For instance, massless relics produce a shift $ΔN_{\rm eff}$ to the cosmic expectation of the effective number of active neutrinos. Massive relics, on the other hand, additionally become part of the cosmological dark matter in the later universe, though their light nature allows them to freely stream out of potential wells. This produces novel signatures in the large-scale structure (LSS) of the universe, suppressing matter fluctuations at small scales. We present the first general search for such light (but massive) relics (LiMRs) with cosmic microwave background (CMB) and LSS data, scanning the 2D parameter space of their masses $m_X$ and temperatures $T_X^{(0)}$ today. In the conservative minimum-temperature ($T_X^{(0)}=0.91$ K) scenario, we rule out Weyl (and higher-spin) fermions -- such as the gravitino -- with $m_X\geq 2.26$ eV at 95% C.L., and set analogous limits of $m_X\leq 11.2, 1.06, 1.56$ eV for scalar, vector, and Dirac-fermion relics. This is the first search for LiMRs with joint CMB, weak-lensing, and full-shape galaxy data; we demonstrate that weak-lensing data is critical for breaking parameter degeneracies, while full-shape information presents a significant boost in constraining power relative to analyses with only baryon acoustic oscillation parameters. Under the combined strength of these datasets, our constraints are the tightest and most comprehensive to date.

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New limits on light dark matter - proton cross section from the cosmic large-scale structure

We set the strongest limits to-date on the velocity-independent dark matter (DM) - proton cross section $σ$ for DM masses $m = 10\,\mathrm{keV}$ to $100\,\mathrm{GeV}$, using large-scale structure traced by the Lyman-alpha forest: e.g., a 95% lower limit $σ< 6 \times 10^{-30}\,\mathrm{cm}^2$, for $m = 100\,\mathrm{keV}$. Our results complement direct detection, which has limited sensitivity to sub-GeV DM. We use an emulator of cosmological simulations, combined with data from the smallest cosmological scales used to-date, to model and search for the imprint of primordial DM-proton collisions. Cosmological bounds are improved by up to a factor of 25.

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Snowmass2021 Cosmic Frontier: Cosmic Microwave Background Measurements White Paper

This is a solicited whitepaper for the Snowmass 2021 community planning exercise. The paper focuses on measurements and science with the Cosmic Microwave Background (CMB). The CMB is foundational to our understanding of modern physics and continues to be a powerful tool driving our understanding of cosmology and particle physics. In this paper, we outline the broad and unique impact of CMB science for the High Energy Cosmic Frontier in the upcoming decade. We also describe the progression of ground-based CMB experiments, which shows that the community is prepared to develop the key capabilities and facilities needed to achieve these transformative CMB measurements.

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The Physics of Light Relics

Many well-motivated extensions of the Standard Model predict the existence of new light species that may have been produced in the early universe. Prominent examples include axions, sterile neutrinos, gravitinos, dark photons, and more. The gravitational influence of light relics leaves imprints in the cosmic microwave background fluctuations, the large-scale structure of the universe and the primordial element abundances. In this paper, we detail the physics of cosmological light relics, and describe how measurements of their relic density and mass serve as probes of physics beyond the Standard Model. A measurement of the light relic density at the precision of upcoming cosmological surveys will point the way toward new physics or severely constrain the range of viable extensions to the Standard Model.

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Machine Learning and Cosmology

Methods based on machine learning have recently made substantial inroads in many corners of cosmology. Through this process, new computational tools, new perspectives on data collection, model development, analysis, and discovery, as well as new communities and educational pathways have emerged. Despite rapid progress, substantial potential at the intersection of cosmology and machine learning remains untapped. In this white paper, we summarize current and ongoing developments relating to the application of machine learning within cosmology and provide a set of recommendations aimed at maximizing the scientific impact of these burgeoning tools over the coming decade through both technical development as well as the fostering of emerging communities.

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Dark Matter Physics from the CMB-S4 Experiment

The nature of dark matter is one of the major puzzles of fundamental physics, integral to the understanding of our universe across almost every epoch. The search for dark matter takes place at different energy scales, and use data ranging from particle colliders to astrophysical surveys. We focus here on CMB-S4, a future ground-based Cosmic Microwave Background (CMB) experiment, which is expected to provide exquisite measurements of the CMB temperature and polarization anisotropies. These measurements (on their own and in combination with other surveys) will allow for new means to shed light on the nature of dark matter.

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Snowmass2021: Vera C. Rubin Observatory as a Flagship Dark Matter Experiment

Establishing that Vera C. Rubin Observatory is a flagship dark matter experiment is an essential pathway toward understanding the physical nature of dark matter. In the past two decades, wide-field astronomical surveys and terrestrial laboratories have jointly created a phase transition in the ecosystem of dark matter models and probes. Going forward, any robust understanding of dark matter requires astronomical observations, which still provide the only empirical evidence for dark matter to date. We have a unique opportunity right now to create a dark matter experiment with Rubin Observatory Legacy Survey of Space and Time (LSST). This experiment will be a coordinated effort to perform dark matter research, and provide a large collaborative team of scientists with the necessary organizational and funding supports. This approach leverages existing investments in Rubin. Studies of dark matter with Rubin LSST will also guide the design of, and confirm the results from, other dark matter experiments. Supporting a collaborative team to carry out a dark matter experiment with Rubin LSST is the key to achieving the dark matter science goals that have already been identified as high priority by the high-energy physics and astronomy communities.

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Extracting the Subhalo Mass Function from Strong Lens Images with Image Segmentation

Detecting substructure within strongly lensed images is a promising route to shed light on the nature of dark matter. However, it is a challenging task, which traditionally requires detailed lens modeling and source reconstruction, taking weeks to analyze each system. We use machine-learning to circumvent the need for lens and source modeling and develop a neural network to both locate subhalos in an image as well as determine their mass using the technique of image segmentation. The network is trained on images with a single subhalo located near the Einstein ring across a wide range of apparent source magnitudes. The network is then able to resolve subhalos with masses $m\gtrsim 10^{8.5} M_{\odot}$. Training in this way allows the network to learn the gravitational lensing of light, and remarkably, it is then able to detect entire populations of substructure, even for locations further away from the Einstein ring than those used in training. Over a wide range of the apparent source magnitude, the false-positive rate is around three false subhalos per 100 images, coming mostly from the lightest detectable subhalo for that signal-to-noise ratio. With good accuracy and a low false-positive rate, counting the number of pixels assigned to each subhalo class over multiple images allows for a measurement of the subhalo mass function (SMF). When measured over three mass bins from $10^9M_{\odot}$--$10^{10} M_{\odot}$ the SMF slope is recovered with an error of 36% for 50 images, and this improves to 10% for 1000 images with Hubble Space Telescope-like noise.

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