arXiv subjects

Tom Abel

Publications and source records attributed to Tom Abel.

At least 37 records · Page 2Linked to original sources

arXiv2023

Robust cosmological inference from non-linear scales with k-th nearest neighbor statistics

We present the methodology for deriving accurate and reliable cosmological constraints from non-linear scales (<50Mpc/h) with k-th nearest neighbor (kNN) statistics. We detail our methods for choosing robust minimum scale cuts and validating galaxy-halo connection models. Using cross-validation, we identify the galaxy-halo model that ensures both good fits and unbiased predictions across diverse summary statistics. We demonstrate that we can model kNNs effectively down to transverse scales of rp ~ 3Mpc/h and achieve precise and unbiased constraints on the matter density and clustering amplitude, leading to a 2% constraint on sigma_8. Our simulation-based model pipeline is resilient to varied model systematics, spanning simulation codes, halo finding, and cosmology priors. We demonstrate the effectiveness of this approach through an application to the Beyond-2p mock challenge. We propose further explorations to test more complex galaxy-halo connection models and tackle potential observational systematics.

astro-ph.CO↗

arXiv2023

Small-scale signatures of primordial non-Gaussianity in k-Nearest Neighbour cumulative distribution functions

Searches for primordial non-Gaussianity in cosmological perturbations are a key means of revealing novel primordial physics. However, robustly extracting signatures of primordial non-Gaussianity from non-linear scales of the late-time Universe is an open problem. In this paper, we apply k-Nearest Neighbor cumulative distribution functions, kNN-CDFs, to the \textsc{quijote-png} simulations to explore the sensitivity of kNN-CDFs to primordial non-Gaussianity. An interesting result is that for halo samples with $M_h<10^{14}$ M$_\odot$/h, the kNN-CDFs respond to \textit{equilateral} PNG in a manner distinct from the other parameters. This persists in the galaxy catalogs in redshift space and can be differentiated from the impact of galaxy modelling, at least within the halo occupation distribution (HOD) framework considered here. kNN-CDFs are related to counts-in-cells and, through mapping a subset of the kNN-CDF measurements into the count-in-cells picture, we show that our results can be modeled analytically. A caveat of the analysis is that we only consider the HOD framework, including assembly bias. It will be interesting to validate these results with other techniques for modeling the galaxy--halo connection, e.g., (hybrid) effective field theory or semi-analytical methods.

astro-ph.CO↗

arXiv2023

Computational Fluid Dynamics with the Coupled Discrete Unified Gas Kinetic Scheme (CDUGKS)

In this paper, we introduce our open source implementation of the Coupled Discrete Unified Gas Kinetic Scheme (CDUGKS) of https://journals.aps.org/pre/abstract/10.1103/PhysRevE.98.053310, a phase space scheme capable of handling a wide range of flow regimes. We demonstrate its performance on several problems including a number of well known test problems from the astrophysical fluid dynamics literature such as the 1D Sod shock tube, 2D Kelvin-Helmholtz instability, 1D thermoacoustic wave, a triangular Gresho vortex, a sine wave velocity perturbation. For these problems, we show that the code can simulate flows ranging from the inviscid/Eulerian regime to the free-streaming regime, capturing shocks and emergent diffusive processes in the appropriate regimes. We also use a variety of Prandtl numbers to demonstrate the scheme's ability to simulate different thermal conductivities at fixed viscosity. The scheme is second-order accurate in space and time and, unlike many solvers, uses a time step that is independent of the mean free path of the gas. Our code (MP-CDUGKS) is public under a CC0 1.0 Universal license and is available on https://github.com/alvarozamora/CDUGKS

astro-ph.IM↗

arXiv2023

2D k-th nearest neighbor statistics: a highly informative probe of galaxy clustering

Beyond standard summary statistics are necessary to summarize the rich information on non-linear scales in the era of precision galaxy clustering measurements. For the first time, we introduce the 2D k-th nearest neighbor (kNN) statistics as a summary statistic for discrete galaxy fields. This is a direct generalization of the standard 1D kNN by disentangling the projected galaxy distribution from the redshift-space distortion signature along the line-of-sight. We further introduce two different flavors of 2D $k$NNs that trace different aspects of the galaxy field: the standard flavor which tabulates the distances between galaxies and random query points, and a ''DD'' flavor that tabulates the distances between galaxies and galaxies. We showcase the 2D kNNs' strong constraining power both through theoretical arguments and by testing on realistic galaxy mocks. Theoretically, we show that 2D kNNs are computationally efficient and directly generate other statistics such as the popular 2-point correlation function, voids probability function, and counts-in-cell statistics. In a more practical test, we apply the 2D kNN statistics to simulated galaxy mocks that fold in a large range of observational realism and recover parameters of the underlying extended halo occupation distribution (HOD) model that includes velocity bias and galaxy assembly bias. We find unbiased and significantly tighter constraints on all aspects of the HOD model with the 2D kNNs, both compared to the standard 1D kNN, and the classical redshift-space 2-point correlation functions.

astro-ph.CO↗

arXiv2023

Full forward model of galaxy clustering statistics with AbacusSummit lightcones

Novel summary statistics beyond the standard 2-point correlation function (2PCF) are necessary to capture the full astrophysical and cosmological information from the small-scale (r < 30Mpc/h) galaxy clustering. However, the analysis of beyond-2PCF statistics on small scales is challenging because we lack the appropriate treatment of observational systematics for arbitrary summary statistics of the galaxy field. In this paper, we develop a full forward modeling pipeline for a wide range of summary statistics using the large high-fidelity AbacusSummit lightcones that accounts for many systematic effects but also remains flexible and computationally efficient to enable posterior sampling. We apply our forward model approach to a fully realistic mock galaxy catalog and demonstrate that we can recover unbiased constraints on the underlying galaxy-halo connection model using two separate summary statistics: the standard 2PCF and the novel k-th nearest neighbor (kNN) statistics, which are sensitive to correlation functions of all orders. We will extend this method to a full cosmology emulator in a follow up paper. We expect this to become a powerful approach when applying to upcoming surveys such as DESI where we can leverage a multitude of summary statistics across a wide redshift range to maximally extract information from the non-linear scales.

astro-ph.CO↗

arXiv2022

Testing the mean field theory of scalar field dark matter

Scalar field dark matter offers an interesting alternative to the traditional WIMP dark matter picture. Astrophysical and cosmological simulations are useful to constraining the mass of the dark matter particle in this model. This is particularly true at low mass where the wavelike nature of the dark matter particle manifests on astrophysical scales. These simulations typical use a classical field approximation. In this work, we look at extending these simulations to include quantum corrections. We look into both the ways in which large corrections impact the predictions of scalar field dark matter, and the timescales on which these corrections grow large. Corrections tend to lessen density fluctuations and increase the effect of "quantum pressure". During collapse, these corrections grow exponentially, quantum corrections would become important in about ~30 dynamical times. This implies that the predictions of classical field simulations may differ from those with quantum corrections for systems with short dynamical times.

astro-ph.CO↗

arXiv2022

Tracer-Field Cross-Correlations with $k$-Nearest Neighbor Distributions

In astronomy and cosmology, significant effort is devoted to characterizing and understanding spatial cross-correlations between points - e.g. galaxy positions, high energy neutrino arrival directions, X-ray and AGN sources, and continuous field - e.g. weak lensing and Cosmic Microwave Background (CMB) maps. Recently, we introduced the $k$-nearest neighbor formalism to better characterize the clustering of discrete (point) datasets. Here we extend it to the point-field cross-correlation analysis. It combines $k$NN measurements of the point data set with measurements of the field smoothed on many scales. The resulting statistics are sensitive to all orders in the joint clustering of the points and the field. We demonstrate that this approach, unlike the 2-pt cross-correlation, can measure the statistical dependence of two datasets even when there are no linear (Gaussian) correlations. We further demonstrate that this framework is far more effective than the two-point function in detecting cross-correlations when the continuous field is contaminated by high levels of noise. For a particularly high level of noise, the cross-correlations between halos and the underlying matter field in a cosmological simulation, between $10h^{-1}{\rm Mpc}$ and $30h^{-1}{\rm Mpc}$, is detected at $>5σ$ significance using the technique presented here, when the two-point cross-correlation significance is $\sim 1σ$. Finally, we show that the $k$NN cross-correlations of halos and the matter field can be well-modeled on quasilinear scales by the Hybrid Effective Field Theory (HEFT) framework, with the same set of bias parameters as are used for the two-point cross-correlations. The substantial improvement in the statistical power of detecting cross-correlations with this method makes it a promising tool for various cosmological applications.

astro-ph.CO↗

arXiv2022

Detection of spatial clustering in the 1000 richest SDSS DR8 redMaPPer clusters with Nearest Neighbor distributions

Distances to the $k$-nearest-neighbor ($k$NN) data points from volume-filling query points are a sensitive probe of spatial clustering. Here we present the first application of $k$NN summary statistics to observational clustering measurement, using the 1000 richest redMaPPer clusters ($0.1\leqslant z\leqslant 0.3$) from the SDSS DR8 catalog. A clustering signal is defined as a difference in the cumulative distribution functions (CDFs) of $k$NN distances from fixed query points to the observed clusters versus a set of unclustered random points. We find that the $k=1,2$-NN CDFs of redMaPPer deviate significantly from the randoms' across scales of 35 to 155 Mpc, which is a robust signature of clustering. In addition to $k$NN, we also measure the two-point correlation function for the same set of redMaPPer clusters versus random points, which shows a noisier and less significant clustering signal within the same radial scales. Quantitatively, the $χ^2$ distribution for both the $k$NN-CDFs and the two-point correlation function measured on the randoms peak at $χ^2\sim 50$ (null hypothesis), whereas the $k$NN-CDFs ($χ^2\sim 300$, $p = 1.54\times 10^{-36}$) pick up a much more significant clustering signal than the two-point function ($χ^2\sim 100$, $p = 1.16\times 10^{-6}$) when measured on redMaPPer. Finally, the measured 3NN and 4NN CDFs deviate from the predicted $k=3, 4$-NN CDFs assuming an ideal Gaussian field, indicating a non-Gaussian clustering signal for redMaPPer clusters, although its origin might not be cosmological due to observational systematics. Therefore, $k$NN serves as a more sensitive probe of clustering complementary to the two point correlation function, providing a novel approach for constraining cosmology and galaxy-halo connection.

astro-ph.CO↗

arXiv2022

When quantum corrections alter the predictions of classical field theory for scalar field dark matter

We investigate the timescale on which quantum corrections alter the predictions of classical field theory for scalar field dark matter. This is accomplished by including second order terms in the evolution proportional to the covariance of the field operators. When this covariance is no longer small compared to the mean field value, we say that the system has reached the ``quantum breaktime" and the predictions of classical field theory will begin to differ from those of the full quantum theory. While holding the classical field theory evolution fixed, we determine the change of the quantum breaktime as total occupation number is increased. This provides a novel numerical estimation of the breaktime based at high occupations $n_{tot}$ and mode number $N=256$. We study the collapse of a sinusoidal overdensity in a single spatial dimension. We find that the breaktime scales as $\log(n_{tot})$ prior to shell crossing and then then as a powerlaw following the collapse. If we assume that the collapsing phase is representative of halos undergoing nonlinear growth, this implies that the quantum breaktime of typical systems may be as large as $\sim 30$ of dynamical times even at occupations of $n_{tot}\sim 10^{100}$.

hep-ph↗

arXiv2022

Modeling Nearest Neighbor distributions of biased tracers using Hybrid Effective Field Theory

We investigate the application of Hybrid Effective Field Theory (HEFT) -- which combines a Lagrangian bias expansion with subsequent particle dynamics from $N$-body simulations -- to the modeling of $k$-Nearest Neighbor Cumulative Distribution Functions ($k{\rm NN}$-${\rm CDF}$s) of biased tracers of the cosmological matter field. The $k{\rm NN}$-${\rm CDF}$s are sensitive to all higher order connected $N$-point functions in the data, but are computationally cheap to compute. We develop the formalism to predict the $k{\rm NN}$-${\rm CDF}$s of discrete tracers of a continuous field from the statistics of the continuous field itself. Using this formalism, we demonstrate how $k{\rm NN}$-${\rm CDF}$ statistics of a set of biased tracers, such as halos or galaxies, of the cosmological matter field can be modeled given a set of low-redshift HEFT component fields and bias parameter values. These are the same ingredients needed to predict the two-point clustering. For a specific sample of halos, we show that both the two-point clustering \textit{and} the $k{\rm NN}$-${\rm CDF}$s can be well-fit on quasi-linear scales ($\gtrsim 20 h^{-1}{\rm Mpc}$) by the second-order HEFT formalism with the \textit{same values} of the bias parameters, implying that joint modeling of the two is possible. Finally, using a Fisher matrix analysis, we show that including $k{\rm NN}$-${\rm CDF}$ measurements over the range of allowed scales in the HEFT framework can improve the constraints on $σ_8$ by roughly a factor of $3$, compared to the case where only two-point measurements are considered. Combining the statistical power of $k{\rm NN}$ measurements with the modeling power of HEFT, therefore, represents an exciting prospect for extracting greater information from small-scale cosmological clustering.

astro-ph.CO↗

arXiv2021

On the single classical field description of interacting scalar fields

We test the degree to which interacting Bosonic systems can be approximated by a classical field as total occupation number is increased. This is done with our publicly available code repository, \href{https://github.com/andillio/QIBS}{QIBS}, a massively parallel solver for these systems. We use a number of toy models well studied in the literature and track when the classical field description admits quantum corrections, called the quantum breaktime. This allows us to test claims in the literature regarding the rate of convergence of these systems to the classical evolution. We test a number of initial conditions, including coherent states, number eigenstates, and field number states. We find that of these initial conditions, only number eigenstates do not converge to the classical evolution as occupation number is increased. We find that systems most similar to scalar field dark matter exhibit a logarithmic enhancement in the quantum breaktime with total occupation number. Systems with contact interactions or with field number state initial conditions, and linear dispersions, exhibit a power law enhancement. Finally, we find that the breaktime scaling depends on both model interactions and initial conditions.

hep-ph↗

arXiv2021

Field moment expansion method for interacting Bosonic systems

We introduce a numerical method and python package, https://github.com/andillio/CHiMES, that simulates quantum systems initially well approximated by mean field theory using a second order extension of the classical field approach. We call this the field moment expansion method. In this way, we can accurately approximate the evolution of first and second field moments beyond where the mean field theory breaks down. This allows us to estimate the quantum breaktime of a classical approximation without any calculations external to the theory. We investigate the accuracy of the field moment expansion using a number of well studied quantum test problems. Interacting Bosonic systems similar to scalar field dark matter are chosen as test problems. We find that successful application of this method depends on two conditions: the quantum system must initially be well described by the classical theory, and that the growth of the higher order moments be hierarchical.

physics.comp-ph↗

arXiv2021

Self-Similarity of $k$-Nearest Neighbor Distributions in Scale-Free Simulations

We use the $k$-nearest neighbor probability distribution function ($k$NN-PDF, Banerjee & Abel 2021) to assess convergence in a scale-free $N$-body simulation. Compared to our previous two-point analysis, the $k$NN-PDF allows us to quantify our results in the language of halos and numbers of particles, while also incorporating non-Gaussian information. We find good convergence for 32 particles and greater at densities typical of halos, while 16 particles and fewer appears unconverged. Halving the softening length extends convergence to higher densities, but not to fewer particles. Our analysis is less sensitive to voids, but we analyze a limited range of underdensities and find evidence for convergence at 16 particles and greater even in sparse voids.

astro-ph.CO↗

arXiv2021

The AGORA High-resolution Galaxy Simulations Comparison Project. III: Cosmological zoom-in simulation of a Milky Way-mass halo

We present a suite of high-resolution cosmological zoom-in simulations to $z=4$ of a $10^{12}\,{\rm M}_{\odot}$ halo at $z=0$, obtained using seven contemporary astrophysical simulation codes widely used in the numerical galaxy formation community. Physics prescriptions for gas cooling, heating, and star formation, are similar to the ones used in our previous {\it AGORA} disk comparison but now account for the effects of cosmological processes. In this work, we introduce the most careful comparison yet of galaxy formation simulations run by different code groups, together with a series of four calibration steps each of which is designed to reduce the number of tunable simulation parameters adopted in the final run. After all the participating code groups successfully completed the calibration steps, we reach a suite of cosmological simulations with similar mass assembly histories down to $z=4$. With numerical accuracy that resolves the internal structure of a target halo, we find that the codes overall agree well with one another in e.g., gas and stellar properties, but also show differences in e.g., circumgalactic medium properties. We argue that, if adequately tested in accordance with our proposed calibration steps and common parameters, the results of high-resolution cosmological zoom-in simulations can be robust and reproducible. New code groups are invited to join this comparison by generating equivalent models by adopting the common initial conditions, the common easy-to-implement physics package, and the proposed calibration steps. Further analyses of the simulations presented here will be in forthcoming reports from our Collaboration.

astro-ph.GA↗

arXiv2021

Nearest Neighbor distributions: new statistical measures for cosmological clustering

The use of summary statistics beyond the two-point correlation function to analyze the non-Gaussian clustering on small scales is an active field of research in cosmology. In this paper, we explore a set of new summary statistics -- the $k$-Nearest Neighbor Cumulative Distribution Functions ($k{\rm NN}$-${\rm CDF}$). This is the empirical cumulative distribution function of distances from a set of volume-filling, Poisson distributed random points to the $k$-nearest data points, and is sensitive to all connected $N$-point correlations in the data. The $k{\rm NN}$-${\rm CDF}$ can be used to measure counts in cell, void probability distributions and higher $N$-point correlation functions, all using the same formalism exploiting fast searches with spatial tree data structures. We demonstrate how it can be computed efficiently from various data sets - both discrete points, and the generalization for continuous fields. We use data from a large suite of $N$-body simulations to explore the sensitivity of this new statistic to various cosmological parameters, compared to the two-point correlation function, while using the same range of scales. We demonstrate that the use of $k{\rm NN}$-${\rm CDF}$ improves the constraints on the cosmological parameters by more than a factor of $2$ when applied to the clustering of dark matter in the range of scales between $10h^{-1}{\rm Mpc}$ and $40h^{-1}{\rm Mpc}$. We also show that relative improvement is even greater when applied on the same scales to the clustering of halos in the simulations at a fixed number density, both in real space, as well as in redshift space. Since the $k{\rm NN}$-${\rm CDF}$ are sensitive to all higher order connected correlation functions in the data, the gains over traditional two-point analyses are expected to grow as progressively smaller scales are included in the analysis of cosmological data.

astro-ph.CO↗

arXiv2021

Cosmological cross-correlations and nearest neighbor distributions

Cross-correlations between datasets are used in many different contexts in cosmological analyses. Recently, $k$-Nearest Neighbor Cumulative Distribution Functions ($k{\rm NN}$-${\rm CDF}$) were shown to be sensitive probes of cosmological (auto) clustering. In this paper, we extend the framework of nearest neighbor measurements to describe joint distributions of, and correlations between, two datasets. We describe the measurement of joint $k{\rm NN}$-${\rm CDF}$s, and show that these measurements are sensitive to all possible connected $N$-point functions that can be defined in terms of the two datasets. We describe how the cross-correlations can be isolated by combining measurements of the joint $k{\rm NN}$-${\rm CDF}$s and those measured from individual datasets. We demonstrate the application of these measurements in the context of Gaussian density fields, as well as for fully nonlinear cosmological datasets. Using a Fisher analysis, we show that measurements of the halo-matter cross-correlations, as measured through nearest neighbor measurements are more sensitive to the underlying cosmological parameters, compared to traditional two-point cross-correlation measurements over the same range of scales. Finally, we demonstrate how the nearest neighbor cross-correlations can robustly detect cross correlations between sparse samples -- the same regime where the two-point cross-correlation measurements are dominated by noise.

astro-ph.CO↗

arXiv2021

First Star Formation in the Presence of Primordial Magnetic Fields

It has been recently claimed that primordial magnetic fields could relieve the cosmological Hubble tension. We consider the impact of such fields on the formation of the first cosmological objects, mini-halos forming stars, for present-day field strengths in the range of $2\times 10^{-12}$ - $2\times 10^{-10}$ G. These values correspond to initial ratios of Alvén velocity to the speed of sound of $v_a/c_s\approx 0.03 - 3$. We find that when $v_a/c_s\ll 1$, the effects are modest. However, when $v_a\sim c_s$, the starting time of the gravitational collapse is delayed and the duration extended as much as by $Δ$z = 2.5 in redshift. When $v_a > c_s$, the collapse is completely suppressed and the mini-halos continue to grow and are unlikely to collapse until reaching the atomic cooling limit. Employing current observational limits on primordial magnetic fields we conclude that inflationary produced primordial magnetic fields could have a significant impact on first star formation, whereas post-inflationary produced fields do not.

astro-ph.CO↗

arXiv2020

Nonthermal electron and ion acceleration by magnetic reconnection in large laser-driven plasmas

Magnetic reconnection is a fundamental plasma process that is thought to play a key role in the production of nonthermal particles associated with explosive phenomena in space physics and astrophysics. Experiments at high-energy-density facilities are starting to probe the microphysics of reconnection at high Lundquist numbers and large system sizes. We have performed particle-in-cell (PIC) simulations to explore particle acceleration for parameters relevant to laser-driven reconnection experiments. We study particle acceleration in large system sizes that may be produced soon with the most energetic laser drivers available, such as at the National Ignition Facility. In these conditions, we show the possibility of reaching the multi-plasmoid regime, where plasmoid acceleration becomes dominant. Our results show the transition from \textit{X} point to plasmoid-dominated acceleration associated with the merging and contraction of plasmoids that further extend the maximum energy of the power-law tail of the particle distribution for electrons. We also find for the first time a system-size-dependent emergence of nonthermal ion acceleration in driven reconnection, where the magnetization of ions at sufficiently large sizes allows them to be contained by the magnetic field and energized by direct \textit{X} point acceleration. For feasible experimental conditions, electrons and ions can attain energies of $ε_{max,e} / k_{B} T_{e} > 100$ and $ε_{max,i} / k_{B} T_{i} > 1000$. Using PIC simulations with binary Monte Carlo Coulomb collisions we study the impact of collisionality on plasmoid formation and particle acceleration. The implications of these results for understanding the role reconnection plays in accelerating particles in space physics and astrophysics are discussed.

physics.plasm-ph↗