152 citations · 586 across the 20 of their papers we have counts for
21 papers
Emulating the complex galactic-scale orbital dynamics of LISA massive black hole pairs with normalizing flows
Pedro R. Capelo, Carlos Moreno Martinez, Nodens Koren +6
Massive black hole (MBH) pairs, formed in galaxy mergers, may coalesce in a burst of gravitational waves. Estimating the coalescence time-scales and rates is a long-standing astrop…
Scaling Behavior of Discrete Diffusion Language Models
Dimitri von Rütte, Janis Fluri, Omead Pooladzandi +3
Modern LLM pre-training consumes vast amounts of compute and training data, making the scaling behavior, or scaling laws, of different models a key distinguishing factor. Discrete…
Dark Energy Survey Year 3 results: Simulation-based CDM inference from weak lensing and galaxy clustering maps with deep learning: Analysis design
A. Thomsen, J. Bucko, T. Kacprzak +99
Data-driven approaches using deep learning are emerging as powerful techniques to extract non-Gaussian information from cosmological large-scale structure. This work presents the f…
Generalized Interpolating Discrete Diffusion
Dimitri von Rütte, Janis Fluri, Yuhui Ding +3
While state-of-the-art language models achieve impressive results through next-token prediction, they have inherent limitations such as the inability to revise already generated to…
CosmoGridV1: a simulated CDM theory prediction for map-level cosmological inference
Tomasz Kacprzak, Janis Fluri, Aurel Schneider +2
We present CosmoGridV1: a large set of lightcone simulations for map-level cosmological inference with probes of large scale structure. It is designed for cosmological parameter me…
Assessing theoretical uncertainties for cosmological constraints from weak lensing surveys
Ting Tan, Dominik Zuercher, Janis Fluri +3
Weak gravitational lensing is a powerful probe which is used to constrain the standard cosmological model and its extensions. With the enhanced statistical precision of current…
Towards a full CDM map-based analysis for weak lensing surveys
Dominik Zürcher, Janis Fluri, Virginia Ajani +3
The next generation of weak lensing surveys will measure the matter distribution of the local Universe with unprecedented precision, allowing the resolution of non-Gaussian feature…
DeepLSS: breaking parameter degeneracies in large scale structure with deep learning analysis of combined probes
Tomasz Kacprzak, Janis Fluri
In classical cosmological analysis of large scale structure surveys with 2-pt functions, the parameter measurement precision is limited by several key degeneracies within the cosmo…
A Full CDM Analysis of KiDS-1000 Weak Lensing Maps using Deep Learning
Janis Fluri, Tomasz Kacprzak, Aurelien Lucchi +3
We present a full forward-modeled CDM analysis of the KiDS-1000 weak lensing maps using graph-convolutional neural networks (GCNN). Utilizing the , a novel m…
A tomographic spherical mass map emulator of the KiDS-1000 survey using conditional generative adversarial networks
Timothy Wing Hei Yiu, Janis Fluri, Tomasz Kacprzak
Large sets of matter density simulations are becoming increasingly important in large-scale structure cosmology. Matter power spectra emulators, such as the Euclid Emulator and Cos…
Symbolic Implementation of Extensions of the Boltzmann Solver
Beatrice Moser, Christiane S. Lorenz, Uwe Schmitt +5
is a Python-based framework for the fast computation of cosmological model predictions. One of its core features is the symbolic representation of the Einstein-B…
Dark Energy Survey Year 3 results: Cosmology with peaks using an emulator approach
D. Zürcher, J. Fluri, R. Sgier +119
We constrain the matter density and the amplitude of density fluctuations within the CDM cosmological model with shear peak statistics and angular converg…
Combined -point analysis of the Cosmic Microwave Background and Large-Scale Structure: implications for the -tension and neutrino mass constraints
Raphael Sgier, Christiane Lorenz, Alexandre Refregier +3
We present cosmological constraints for the flat CDM model, including the sum of neutrino masses, by performing a multi-probe analysis of a total of 13 tomographic auto- and cro…
Cosmological Parameter Estimation and Inference using Deep Summaries
Janis Fluri, Aurelien Lucchi, Tomasz Kacprzak +2
The ability to obtain reliable point estimates of model parameters is of crucial importance in many fields of physics. This is often a difficult task given that the observed data c…
Fast Lightcones for Combined Cosmological Probes
Raphael Sgier, Janis Fluri, Jörg Herbel +4
The combination of different cosmological probes offers stringent tests of the CDM model and enhanced control of systematics. For this purpose, we present an extension of the li…
Cosmological Forecast for non-Gaussian Statistics in large-scale weak Lensing Surveys
Dominik Zürcher, Janis Fluri, Raphael Sgier +2
Cosmic shear data contains a large amount of cosmological information encapsulated in the non-Gaussian features of the weak lensing mass maps. This information can be extracted usi…
Predicting Cosmological Observables with PyCosmo
F. Tarsitano, U. Schmitt, A. Refregier +7
Current and upcoming cosmological experiments open a new era of precision cosmology, thus demanding accurate theoretical predictions for cosmological observables. Because of the co…
Cosmological constraints with deep learning from KiDS-450 weak lensing maps
Janis Fluri, Tomasz Kacprzak, Aurelien Lucchi +4
Convolutional Neural Networks (CNN) have recently been demonstrated on synthetic data to improve upon the precision of cosmological inference. In particular they have the potential…
Cosmological constraints from noisy convergence maps through deep learning
Janis Fluri, Tomasz Kacprzak, Aurelien Lucchi +3
Deep learning is a powerful analysis technique that has recently been proposed as a method to constrain cosmological parameters from weak lensing mass maps. Due to its ability to l…
Weak lensing peak statistics in the era of large scale cosmological surveys
Janis Fluri, Tomasz Kacprzak, Raphael Sgier +2
Weak lensing peak counts are a powerful statistical tool for constraining cosmological parameters. So far, this method has been applied only to surveys with relatively small areas,…
Fast cosmic web simulations with generative adversarial networks
Andres C. Rodriguez, Tomasz Kacprzak, Aurelien Lucchi +5
Dark matter in the universe evolves through gravity to form a complex network of halos, filaments, sheets and voids, that is known as the cosmic web. Computational models of the un…