arXiv subjects

Christian Arnold

Publications and source records attributed to Christian Arnold.

At least 19 recordsLinked to original sources

arXiv2024

Structuring Quantitative Image Analysis with Object Prominence

When photographers or media professionals compose an image, they make deliberate choices about what to foreground and what to background, shaping how viewers interpret visual content. Yet most quantitative approaches to image analysis overlook this structure and treat detected objects as equally important. We introduce a framework for measuring object prominence-- the relative salience of objects in an image-- as a means to make computational image analysis attentive to the compositional emphasis a curator has built into an image. Drawing on research in cognitive psychology and computer vision, we outline three approaches for estimating object prominence: size and centeredness, inferred depth, and saliency maps. Validating that curator-composed prominence measurably shifts human visual attention in a pre-registered eye-tracking study, we illustrate this framework's benefits in two further applications. First, we demonstrate how weighting features in line with their prominence can enhance the unsupervised ideological scaling of U.S. newspaper images. Second, we examine gendered visual prominence in U.S. presidential campaign ads from 2016 and 2020, showing that Republican candidates depict women less prominently than their Democratic counterparts. Our framework lets researchers analyze image data at scale while remaining attentive to its communicative structure and intent.

cs.CV↗

arXiv2024

Causal Effects of Trigger Words in Social Media Discussions: A Large-Scale Case Study about UK Politics on Reddit

Political debates on social media often escalate quickly, leading to increased engagement as well as more emotional and polarised exchanges. Trigger points (Mau, Lux, and Westheuser 2023) represent moments when individuals feel that their understanding of what is fair, normal, or appropriate in society is being questioned. Analysing Reddit discussions, we examine how trigger points shape online debates and assess their impact on engagement and affect. Our analysis is based on over 100 million comments from subreddits centred on a predefined set of terms identified as trigger words in UK politics. We find that mentions of these terms are associated with higher engagement and increased animosity, including more controversial, negative, angry, and hateful responses. These results position trigger words as a useful concept for modelling and analysing online polarisation.

cs.SI↗

arXiv2024

Alignment Helps Make the Most of Multimodal Data

Political scientists increasingly analyze multimodal data. However, the effective analysis of such data requires aligning information across different modalities. In our paper, we demonstrate the significance of such alignment. Informed by a systematic review of 2,703 papers, we find that political scientists typically do not align their multimodal data. Introducing a decision tree that guides alignment choices, our framework highlights alignment's untapped potential and provides concrete advice in research design and modeling decisions. We illustrate alignment's analytical value through two applications: predicting tonality in U.S. presidential campaign ads and cross-modal querying of German parliamentary speeches to examine responses to the far-right AfD.

cs.CL↗

arXiv2023

Machine Learning and Structure Formation in Modified Gravity

In General Relativity approximations based on the spherical collapse model such as Press--Schechter theory and its extensions are able to predict the number of objects of a certain mass in a given volume. In this paper we use a machine learning algorithm to test whether such approximations hold in screened modified gravity theories. To this end, we train random forest classifiers on data from N-body simulations to study the formation of structures in $Λ$CDM as well as screened modified gravity theories, in particular $f(R)$ and nDGP gravity. The models are taught to distinguish structure membership in the final conditions from spherical aggregations of density field behaviour in the initial conditions. We examine the differences between machine learning models that have learned structure formation from each gravity, as well as the model that has learned from $Λ$CDM. We also test the generalisability of the $Λ$CDM model on data from $f(R)$ and nDGP gravities of varying strengths, and therefore the generalisability of Extended-Press-Schechter spherical collapse to these types of modified gravity.

astro-ph.CO↗

arXiv2023

Galaxy evolution in modified gravity simulations: using passive galaxies to constrain gravity with upcoming surveys

We present a quantitative analysis of the properties of galaxies and structures evolving in universes dominated by different modified gravitational models, including two variants of the f(R)-gravity (F) and two of the Dvali-Gabdadze-Poratti (N) braneworld model, which respectively feature the chameleon and Vainshtein screening mechanisms. Using the Simulation HYdrodynamics BeyONd Einstein (SHYBONE) cosmological hydrodynamical full-physics simulations suite, we study the departures in the properties of galaxies residing in different environments with respect to the standard model (GR). Using two different criteria to compare, we find that structures formed within modified gravity tend to show a denser gas density profile than their GR counterparts. Within the different modified gravity models, N1 and F5 gravity models show greater departures from the standard model, with gas density profiles $ρ_{\rm IGM} \geq 30\%$ denser in the outskirts for the N1 model, and in the inner parts for the F5 model. Additionally, we find that haloes evolving in MG universes show, in general, larger quenched fractions than GR, reaching up to $20\%$ larger quenching fractions in F5 regardless of the stellar mass of the galaxy. With respect to the other models, F6, N1 and N5 show slightly larger quenched fractions, but no strong differences can be found. These results directly impact the colour distribution of galaxies, making them in MG models redder and older than their GR counterparts. Like GR, once the environment starts to play a role, galaxies rapidly get quenched and the differences between models vanish.

astro-ph.GA↗

arXiv2023

An emulator-based halo model in modified gravity -- I. The halo concentration-mass relation and density profile

In this series of papers we present an emulator-based halo model for the non-linear clustering of galaxies in modified gravity cosmologies. In the first paper, we present emulators for the following halo properties: the halo mass function, concentration-mass relation and halo-matter cross-correlation function. The emulators are trained on data extracted from the \textsc{FORGE} and \textsc{BRIDGE} suites of $N$-body simulations, respectively for two modified gravity (MG) theories: $f(R)$ gravity and the DGP model, varying three standard cosmological parameters $Ω_{\mathrm{m0}}, H_0, σ_8$, and one MG parameter, either $\bar{f}_{R0}$ or $r_{\mathrm{c}}$. Our halo property emulators achieve an accuracy of $\lesssim 1\%$ on independent test data sets. We demonstrate that the emulators can be combined with a galaxy-halo connection prescription to accurately predict the galaxy-galaxy and galaxy-matter correlation functions using the halo model framework.

astro-ph.CO↗

arXiv2022

MGLenS: Modified gravity weak lensing simulations for emulation-based cosmological inference

We present MGLenS, a large series of modified gravity lensing simulations tailored for cosmic shear data analyses and forecasts in which cosmological and modified gravity parameters are varied simultaneously. Based on the FORGE and BRIDGE $N$-body simulation suites presented in companion papers, we construct 500,000 deg$^2$ of mock Stage-IV lensing data, sampling a pair of 4-dimensional volumes designed for the training of emulators. We validate the accuracy of MGLenS with inference analyses based on the lensing power spectrum exploiting our implementation of $f(R)$ and nDGP theoretical predictions within the cosmoSIS cosmological inference package. A Fisher analysis reveals that the vast majority of the constraining power from such a survey comes from the highest redshift galaxies alone. We further find from a full likelihood sampling that cosmic shear can achieve 95% CL constraints on the modified gravity parameters of log$_{10}\left[ f_{R_0}\right] < -5.24$ and log$_{10}\left[ H_0 r_c\right] > -0.05$, after marginalising over intrinsic alignments of galaxies and including scales up to $\ell=5000$. Such a survey setup could in fact detect with more than $3σ$ confidence $f(R)$ values larger than $3 \times 10^{-6}$ and $H_0 r_c$ smaller than 1.0. Scale cuts at $\ell=3000$ reduce the degeneracy breaking between $S_8$ and the modified gravity parameters, while photometric redshift uncertainty seem to play a subdominant role in our error budget. We finally explore the consequences of analysing data with the wrong gravity model, and report the catastrophic biases for a number of possible scenarios. The Stage-IV MGLenS simulations, the FORGE and BRIDGE emulators and the cosmoSIS interface modules will be made publicly available upon journal acceptance.

astro-ph.CO↗

arXiv2022

Fingerprints of modified gravity on galaxies in voids

We search for detectable signatures of f(R) gravity and its chameleon screening mechanism in the baryonic and dark matter (DM) properties of simulated void galaxies. The enhancement of the gravitational acceleration can have a meaningful impact on the scaling relations as well as on the halo morphology. The galaxy rotational velocity field (calculated with the velocity of the gas disc and the acceleration fields) deviates from the typical values of the Tully-Fisher Relation (TFR) in GR. For a given stellar mass, f(R) gravity tends to produce greater maximum velocities. On the other hand, the mass in haloes in f(R) gravity is more concentrated than their counterparts in GR. This trend changes when the concentration is calculated with the dynamical density profile, which takes into account the unscreened outer regions of the halo. Stellar discs interact with the overall potential well in the central regions, modifying the morphology of the screening regions and reshaping them. We find a trend for galaxies with a more dominant stellar disc to deviate further from round screening regions. We find that small haloes are less triaxial and more round in f(R) than their GR counterparts. The difference between halo morphology becomes smaller in f(R) haloes whose inner regions are screened. These results suggest possible observables that could unveil modified gravity effects on galaxies in voids in future cosmological tests of gravity.

astro-ph.GA↗

arXiv2022

A general framework to test gravity using galaxy clusters VI: Realistic galaxy formation simulations to study clusters in modified gravity

We present a retuning of the IllustrisTNG baryonic physics model which can be used to run large-box realistic cosmological simulations with a lower resolution. This new model employs a lowered gas density threshold for star formation and reduced energy releases by stellar and black hole feedback. These changes ensure that our simulations can produce sufficient star formation to closely match the observed stellar and gas properties of galaxies and galaxy clusters, despite having $\sim$160 times lower mass resolution than the simulations used to tune the fiducial IllustrisTNG model. Using the retuned model, we have simulated Hu-Sawicki $f(R)$ gravity within a $301.75h^{-1}{\rm Mpc}$ box. This is, to date, the largest simulation that incorporates both screened modified gravity and full baryonic physics, offering a large sample ($\sim$500) of galaxy clusters and $\sim$8000 galaxy groups. We have reanalysed the effects of the $f(R)$ fifth force on the scaling relations between the cluster mass and four observable proxies: the mass-weighted gas temperature, the Compton $Y$-parameter of the thermal Sunyaev-Zel'dovich effect, the X-ray analogue of the $Y$-parameter, and the X-ray luminosity. We show that a set of mappings between the $f(R)$ scaling relations and their $Λ$CDM counterpart, which have been tested in a previous work using a much smaller cosmological volume, are accurate to within a few percent for the $Y$-parameters and $\lesssim7\%$ for the gas temperature for cluster-sized haloes ($10^{14}M_{\odot}\lesssim M_{500}\lesssim10^{15}M_{\odot}$). These mappings will be important for unbiased constraints of gravity using the data from ongoing and upcoming cluster surveys.

astro-ph.CO↗

arXiv2022

Fast full N-body simulations of generic modified gravity: conformal coupling models

We present MG-GLAM, a code developed for the very fast production of full $N$-body cosmological simulations in modified gravity (MG) models. We describe the implementation, numerical tests and first results of a large suite of cosmological simulations for three classes of MG models with conformal coupling terms: the $f(R)$ gravity, symmetron and coupled quintessence models. Derived from the parallel particle-mesh code GLAM, MG-GLAM incorporates an efficient multigrid relaxation technique to solve the characteristic nonlinear partial differential equations of these models. For $f(R)$ gravity, we have included new variants to diversify the model behaviour, and we have tailored the relaxation algorithms to these to maintain high computational efficiency. In a companion paper, we describe versions of this code developed for derivative coupling MG models, including the Vainshtein- and K-mouflage-type models. MG-GLAM can model the prototypes for most MG models of interest, and is broad and versatile. The code is highly optimised, with a tremendous speedup of a factor of more than a hundred compared with earlier $N$-body codes, while still giving accurate predictions of the matter power spectrum and dark matter halo abundance. MG-GLAM is ideal for the generation of large numbers of MG simulations that can be used in the construction of mock galaxy catalogues and the production of accurate emulators for ongoing and future galaxy surveys.

astro-ph.CO↗

arXiv2022

The matter density PDF for modified gravity and dark energy with Large Deviations Theory

We present an analytical description of the probability distribution function (PDF) of the smoothed three-dimensional matter density field for modified gravity and dark energy. Our approach, based on the principles of Large Deviations Theory, is applicable to general extensions of the standard $Λ$CDM cosmology. We show that late-time changes to the law of gravity and background expansion can be included through Einstein-de Sitter spherical collapse dynamics combined with linear theory calculations and a calibration measurement of the non-linear variance of the smoothed density field from a simple numerical simulation. In a comparison to $N$-body simulations for $f(R)$, DGP and evolving dark energy theories, we find percent level accuracy around the peak of the distribution for predictions in the mildly non-linear regime. A Fisher forecast of an idealised experiment with a Euclid-like survey volume demonstrates the power of combining measurements of the 3D matter PDF with the 3D matter power spectrum. This combination is shown to halve the uncertainty on parameters for an evolving dark energy model, relative to a power spectrum analysis on its own. The PDF is also found to substantially increase the detection significance for small departures from General Relativity, with improvements of up to six times compared to the power spectrum alone. This analysis is therefore very promising for future studies including non-Gaussian statistics, as it has the potential to alleviate the reliance of these analyses on expensive high resolution simulations and emulators.

astro-ph.CO↗

arXiv2021

Making use of sub-resolution halos in N-body simulations

Conservative mass limits are often imposed on the dark matter halo catalogues extracted from N-body simulations. By comparing simulations with different mass resolutions, at $z=0$ we find that even for halos resolved by 100 particles, the lower resolution simulation predicts a cumulative halo abundance that is 5 per cent lower than in the higher resolution simulation. We propose a simple weighting scheme to utilise the halos that are usually regarded as being `sub-resolution'. With the scheme, we are able to use halos which contain only 11 particles to reproduce the clustering measured in the higher resolution simulation to within 5 per cent on scales down to $2 h^{-1}$ Mpc, thereby extending the useful halo resolution by a factor of ten below the mass at which the mass functions in the two simulations first start to deviate. The performance of the method is slightly worse at higher redshift. Our method allows a simulation to be used to probe a wider parameter space in clustering studies, for example, in a halo occupation distribution analysis. This reduces the cost of generating many simulations to estimate the covariance matrix on measurements or using a larger volume simulation to make large-scale clustering predictions.

astro-ph.CO↗

arXiv2021

Testing the theory of gravity with DESI: estimators, predictions and simulation requirements

Shortly after its discovery, General Relativity (GR) was applied to predict the behavior of our Universe on the largest scales, and later became the foundation of modern cosmology. Its validity has been verified on a range of scales and environments from the Solar system to merging black holes. However, experimental confirmations of GR on cosmological scales have so far lacked the accuracy one would hope for -- its applications on those scales being largely based on extrapolation and its validity sometimes questioned in the shadow of the unexpected cosmic acceleration. Future astronomical instruments surveying the distribution and evolution of galaxies over substantial portions of the observable Universe, such as the Dark Energy Spectroscopic Instrument (DESI), will be able to measure the fingerprints of gravity and their statistical power will allow strong constraints on alternatives to GR. In this paper, based on a set of $N$-body simulations and mock galaxy catalogs, we study the predictions of a number of traditional and novel estimators beyond linear redshift distortions in two well-studied modified gravity models, chameleon $f(R)$ gravity and a braneworld model, and the potential of testing these deviations from GR using DESI. These estimators employ a wide array of statistical properties of the galaxy and the underlying dark matter field, including two-point and higher-order statistics, environmental dependence, redshift space distortions and weak lensing. We find that they hold promising power for testing GR to unprecedented precision. The major future challenge is to make realistic, simulation-based mock galaxy catalogs for both GR and alternative models to fully exploit the statistic power of the DESI survey and to better understand the impact of key systematic effects. Using these, we identify future simulation and analysis needs for gravity tests using DESI.

astro-ph.CO↗

arXiv2021

Really Useful Synthetic Data -- A Framework to Evaluate the Quality of Differentially Private Synthetic Data

Recent advances in generating synthetic data that allow to add principled ways of protecting privacy -- such as Differential Privacy -- are a crucial step in sharing statistical information in a privacy preserving way. But while the focus has been on privacy guarantees, the resulting private synthetic data is only useful if it still carries statistical information from the original data. To further optimise the inherent trade-off between data privacy and data quality, it is necessary to think closely about the latter. What is it that data analysts want? Acknowledging that data quality is a subjective concept, we develop a framework to evaluate the quality of differentially private synthetic data from an applied researcher's perspective. Data quality can be measured along two dimensions. First, quality of synthetic data can be evaluated against training data or against an underlying population. Second, the quality of synthetic data depends on general similarity of distributions or specific tasks such as inference or prediction. It is clear that accommodating all goals at once is a formidable challenge. We invite the academic community to jointly advance the privacy-quality frontier.

stat.ML↗

arXiv2021

Fast full $N$-body simulations of generic modified gravity: derivative coupling models

We present MG-GLAM, a code developed for the very fast production of full $N$-body cosmological simulations in modified gravity (MG) models. We describe the implementation, numerical tests and first results of a large suite of cosmological simulations for two broad classes of MG models with derivative coupling terms -- the Vainshtein- and Kmouflage-type models -- which respectively features the Vainshtein and Kmouflage screening mechanism. Derived from the parallel particle-mesh code GLAM, MG-GLAM incorporates an efficient multigrid relaxation technique to solve the characteristic nonlinear partial differential equations of these models. For Kmouflage, we have proposed a new algorithm for the relaxation solver, and run the first simulations of the model to understand its cosmological behaviour. In a companion paper, we describe versions of this code developed for conformally-coupled MG models, including several variants of $f(R)$ gravity, the symmetron model and coupled quintessence. Altogether, MG-GLAM has so far implemented the prototypes for most MG models of interest, and is broad and versatile. The code is highly optimised, with a tremendous (over two orders of magnitude) speedup when comparing its running time with earlier $N$-body codes, while still giving accurate predictions of the matter power spectrum and dark matter halo abundance. MG-GLAM is ideal for the generation of large numbers of MG simulations that can be used in the construction of mock galaxy catalogues and accurate emulators for ongoing and future galaxy surveys.

astro-ph.CO↗

arXiv2021

A general framework to test gravity using galaxy clusters IV: Cluster and halo properties in DGP gravity

We study and model the properties of galaxy clusters in the normal-branch Dvali-Gabadadze-Porrati (nDGP) model of gravity, which is representative of a wide class of theories which exhibit the Vainshtein screening mechanism. Using the first cosmological simulations which incorporate both full baryonic physics and nDGP, we find that, despite being efficiently screened within clusters, the fifth force can raise the temperature of the intra-cluster gas, affecting the scaling relations between the cluster mass and three observable mass proxies: the gas temperature, the Compton $Y$-parameter of the Sunyaev-Zel'dovich effect and the X-ray analogue of the $Y$-parameter. Therefore, unless properly accounted for, this could lead to biased measurements of the cluster mass in tests that make use of cluster observations, such as cluster number counts, to probe gravity. Using a suite of dark-matter-only simulations, which span a wide range of box sizes and resolutions, and which feature very different strengths of the fifth force, we also calibrate general fitting formulae which can reproduce the nDGP halo concentration at percent accuracy for $0\leq z\leq1$, and halo mass function with $\lesssim3\%$ accuracy at $0\leq z\leq1$ (increasing to $\lesssim5\%$ for $1\leq z\leq 2$), over a halo mass range spanning four orders of magnitude. Our model for the concentration can be used for converting between halo mass overdensities and predicting statistics such as the nonlinear matter power spectrum. The results of this work will form part of a framework for unbiased constraints of gravity using the data from ongoing and upcoming cluster surveys.

astro-ph.CO↗

arXiv2021

A general framework to test gravity using galaxy clusters V: A self-consistent pipeline for unbiased constraints of $f(R)$ gravity

We present a Markov chain Monte Carlo pipeline that can be used for robust and unbiased constraints of $f(R)$ gravity using galaxy cluster number counts. This pipeline makes use of a detailed modelling of the halo mass function in $f(R)$ gravity, which is based on the spherical collapse model and calibrated by simulations, and fully accounts for the effects of the fifth force on the dynamical mass, the halo concentration and the observable-mass scaling relations. Using a set of mock cluster catalogues observed through the thermal Sunyaev-Zel'dovich effect, we demonstrate that this pipeline, which constrains the present-day background scalar field $f_{R0}$, performs very well for both $Λ$CDM and $f(R)$ fiducial cosmologies. We find that using an incomplete treatment of the scaling relation, which could deviate from the usual power-law behaviour in $f(R)$ gravity, can lead to imprecise and biased constraints. We also find that various degeneracies between the modified gravity, cosmological and scaling relation parameters can significantly affect the constraints, and show how this can be rectified by using tighter priors and better knowledge of the cosmological and scaling relation parameters. Our pipeline can be easily extended to other modified gravity models, to test gravity on large scales using galaxy cluster catalogues from ongoing and upcoming surveys.

astro-ph.CO↗

arXiv2021

FORGE -- the f(R) gravity cosmic emulator project I: Introduction and matter power spectrum emulator

We present a large suite of cosmological simulations, the FORGE (F-of-R Gravity Emulator) simulation suite, which is designed to build accurate emulators for cosmological observables in galaxy clustering, weak gravitational lensing and galaxy clusters, for the $f(R)$ gravity model. The total of 200 simulations explore the cosmological parameter space around the Planck(2018) cosmology with a Latin hypercube, for 50 combinations of $\bar{f}_{R0}$, $Ω_m$, $σ_8$ and $h$ with all other parameters fixed. For each parameter combination, or node, we ran four independent simulations, one pair using $1024^3$ particles in $500 h^{-1} Mpc$ simulation boxes to cover small scales, and another pair using $512^3$ simulation particles in $1500 h^{-1} Mpc$ boxes for larger scales. Each pair of initial conditions are selected such that sample variance on large scales is minimised on average. In this work we present an accurate emulator for the matter power spectrum in $f(R)$ gravity trained on FORGE. We have verified, using the cross-validation technique, that the emulator accuracy is better than $2.5\%$ for the majority of nodes, particularly around the center of the explored parameter space, up to scales of $k = 10 h Mpc^{-1}$. We have also checked the power spectrum emulator against simulations which are not part of our training set and found excellent agreement. Due to its high accuracy on small scales, the FORGE matter power spectrum emulator is well suited for weak lensing analysis and can play a key tool in constraining $f(R)$ gravity using current and future observational data.

astro-ph.CO↗