57 citations · 397 across the 18 of their papers we have counts for
19 papers
Cosmology with Persistent Homology: a Fisher Forecast
Jacky H. T. Yip, Matteo Biagetti, Alex Cole +2
Persistent homology naturally addresses the multi-scale topological characteristics of the large-scale structure as a distribution of clusters, loops, and voids. We apply this tool…
Constraining the X-ray heating and reionization using 21-cm power spectra with Marginal Neural Ratio Estimation
Anchal Saxena, Alex Cole, Simon Gazagnes +3
Cosmic Dawn (CD) and Epoch of Reionization (EoR) are epochs of the Universe which host invaluable information about the cosmology and astrophysics of X-ray heating and hydrogen rei…
Fisher Forecasts for Primordial non-Gaussianity from Persistent Homology
Matteo Biagetti, Juan Calles, Lina Castiblanco +2
We study the information content of summary statistics built from the multi-scale topology of large-scale structures on primordial non-Gaussianity of the local and equilateral type…
Probing the Structure of String Theory Vacua with Genetic Algorithms and Reinforcement Learning
Alex Cole, Sven Krippendorf, Andreas Schachner +1
Identifying string theory vacua with desired physical properties at low energies requires searching through high-dimensional solution spaces - collectively referred to as the strin…
Fast and Credible Likelihood-Free Cosmology with Truncated Marginal Neural Ratio Estimation
Alex Cole, Benjamin Kurt Miller, Samuel J. Witte +4
Sampling-based inference techniques are central to modern cosmological data analysis; these methods, however, scale poorly with dimensionality and typically require approximate or…
EuCAPT White Paper: Opportunities and Challenges for Theoretical Astroparticle Physics in the Next Decade
R. Alves Batista, M. A. Amin, G. Barenboim +134
Astroparticle physics is undergoing a profound transformation, due to a series of extraordinary new results, such as the discovery of high-energy cosmic neutrinos with IceCube, the…
Truncated Marginal Neural Ratio Estimation
Benjamin Kurt Miller, Alex Cole, Patrick Forré +2
Parametric stochastic simulators are ubiquitous in science, often featuring high-dimensional input parameters and/or an intractable likelihood. Performing Bayesian parameter infere…
Shocks and Information Exchange in de Sitter Space
Lars Aalsma, Alex Cole, Edward Morvan +2
We discuss some implications of recent progress in understanding the black hole information paradox for complementarity in de Sitter space. Extending recent work by two of the auth…
Topological Echoes of Primordial Physics in the Universe at Large Scales
Alex Cole, Matteo Biagetti, Gary Shiu
We present a pipeline for characterizing and constraining initial conditions in cosmology via persistent homology. The cosmological observable of interest is the cosmic web of larg…
Interpretable Phase Detection and Classification with Persistent Homology
Alex Cole, Gregory J. Loges, Gary Shiu
We apply persistent homology to the task of discovering and characterizing phase transitions, using lattice spin models from statistical physics for working examples. Persistence i…
Simulation-efficient marginal posterior estimation with swyft: stop wasting your precious time
Benjamin Kurt Miller, Alex Cole, Gilles Louppe +1
We present algorithms (a) for nested neural likelihood-to-evidence ratio estimation, and (b) for simulation reuse via an inhomogeneous Poisson point process cache of parameters and…
A New Spin on the Weak Gravity Conjecture
Lars Aalsma, Alex Cole, Gregory J. Loges +1
The mild form of the Weak Gravity Conjecture states that quantum or higher-derivative corrections should decrease the mass of large extremal charged black holes at fixed charge. Th…
Quantitative and Interpretable Order Parameters for Phase Transitions from Persistent Homology
Alex Cole, Gregory J. Loges, Gary Shiu
We apply modern methods in computational topology to the task of discovering and characterizing phase transitions. As illustrations, we apply our method to four two-dimensional lat…
The Persistence of Large Scale Structures I: Primordial non-Gaussianity
Matteo Biagetti, Alex Cole, Gary Shiu
We develop an analysis pipeline for characterizing the topology of large scale structure and extracting cosmological constraints based on persistent homology. Persistent homology i…
Searching the Landscape of Flux Vacua with Genetic Algorithms
Alex Cole, Andreas Schachner, Gary Shiu
In this paper, we employ genetic algorithms to explore the landscape of type IIB flux vacua. We show that genetic algorithms can efficiently scan the landscape for viable solutions…
Weak Gravity Conjecture, Black Hole Entropy, and Modular Invariance
Lars Aalsma, Alex Cole, Gary Shiu
In recent literature, it has been argued that a mild form of the Weak Gravity Conjecture (WGC) is satisfied by wide classes of effective field theories in which higher-derivative c…
Topological Data Analysis for the String Landscape
Alex Cole, Gary Shiu
Persistent homology computes the multiscale topology of a data set by using a sequence of discrete complexes. In this paper, we propose that persistent homology may be a useful too…
Persistent Homology and Non-Gaussianity
Alex Cole, Gary Shiu
In this paper, we introduce the topological persistence diagram as a statistic for Cosmic Microwave Background (CMB) temperature anisotropy maps. A central concept in `Topological…
Gravitational Decoupling and Picard-Lefschetz
Jon Brown, Alex Cole, William Cottrell +1
In this work, we consider tunneling between non-metastable states in gravitational theories. Such processes arise in various contexts, e.g., in inflationary scenarios where the inf…