32 citations · 120 across the 11 of their papers we have counts for
13 papers
IR extremality and UV softness in string bootstrap
Shi-Lin Wan, Ji-Yang Wang, Shuang-Yong Zhou
Whether string amplitudes can be characterized by extremality within the space of consistent S-matrices is an intriguing question. We address this question within the framework of…
Recovering Sharp Conductivity Features in the Finite-Data Calderón Problem with Physics-Informed Neural Networks
Ali AlHadi Kalout, Pablo Tejerina-Pérez, Konstantin Karchev +5
Physics-informed neural networks (PINNs) have recently emerged as a promising framework for addressing the Calderón inverse problem from limited boundary data. In this work, we rev…
The colour variability of low-z SNe Ia is entirely explained by dust
Marco Giunta, Konstantin Karchev, Roberto Trotta
The relative importance of intrinsic colour variability of supernovae type Ia (SN Ia) versus dust-induced reddening remains an open question with important ramifications for unders…
CIGaRS I: Combined simulation-based inference from type Ia supernovae and host photometry
Konstantin Karchev, Roberto Trotta, Raul Jimenez
Using type Ia supernovae as cosmological probes requires empirical corrections that are correlated with their host environment. Here we present a unified Bayesian hierarchical mode…
SIDE-real: Supernova Ia Dust Extinction with truncated marginal neural ratio estimation applied to real data
Konstantin Karchev, Matthew Grayling, Benjamin M. Boyd +3
We present the first fully simulation-based hierarchical analysis of the light curves of a population of low-redshift type Ia supernovae (SNae Ia). Our hardware-accelerated forward…
SimSIMS: Simulation-based Supernova Ia Model Selection with thousands of latent variables
Konstantin Karchev, Roberto Trotta, Christoph Weniger
We present principled Bayesian model comparison through simulation-based neural classification applied to SN Ia analysis. We validate our approach on realistically simulated SN Ia…
Analytic auto-differentiable CDM cosmography
Konstantin Karchev
I present general analytic expressions for distance calculations (comoving distance, time coordinate, and absorption distance) in the standard CDM cosmology, allowing for the pr…
Strong-Lensing Source Reconstruction with Denoising Diffusion Restoration Models
Konstantin Karchev, Noemi Anau Montel, Adam Coogan +1
Analysis of galaxy--galaxy strong lensing systems is strongly dependent on any prior assumptions made about the appearance of the source. Here we present a method of imposing a dat…
One never walks alone: the effect of the perturber population on subhalo measurements in strong gravitational lenses
Adam Coogan, Noemi Anau Montel, Konstantin Karchev +3
Analyses of extended arcs in strong gravitational lensing images to date have constrained the properties of dark matter by measuring the parameters of one or two individual subhalo…
SICRET: Supernova Ia Cosmology with truncated marginal neural Ratio EsTimation
Konstantin Karchev, Roberto Trotta, Christoph Weniger
Type Ia supernovae (SNae Ia), standardisable candles that allow tracing the expansion history of the Universe, are instrumental in constraining cosmological parameters, particularl…
Estimating the warm dark matter mass from strong lensing images with truncated marginal neural ratio estimation
Noemi Anau Montel, Adam Coogan, Camila Correa +2
Precision analysis of galaxy-galaxy strong gravitational lensing images provides a unique way of characterizing small-scale dark matter halos, and could allow us to uncover the fun…
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…
Strong-lensing source reconstruction with variationally optimised Gaussian processes
Konstantin Karchev, Adam Coogan, Christoph Weniger
Strong-lensing images provide a wealth of information both about the magnified source and about the dark matter distribution in the lens. Precision analyses of these images can be…