Publications related to Objections to evolution

Variational quantum time evolution without the quantum geometric tensor

Giuseppe Carleo, Riccardo Rossi, Julien Sebastian Gacon, Jannes Willy E. Nys, Stefan Woerner

Realand imaginary -time quantum state evolutions are crucial in physics and chemistry for exploring quantum dynamics, preparing ground states, and computing thermodynamic observables. On near -term devices, variational quantum time evolution is a promising ...

Amer Physical Soc2024

Stability of a liquid layer draining around a horizontal cylinder: Interplay of capillary and gravity forces

François Gallaire, Shahab Eghbali, Simeon Vladimirov Djambov

We study the drainage of a viscous liquid film coating the outside of a solid horizontal cylinder, where gravity acts vertically. We focus on the limit of large Ohnesorge numbers Oh, where inertia is negligible compared to viscous effects. We first study t ...

Amer Physical Soc2024

Gaia's brightest very metal-poor (VMP) stars Metallicity catalogue of a thousand VMP stars from Gaia's radial velocity spectrometer spectra

Nicolas Lawrence Etienne Longeard

Context. Gaia DR3 has offered the scientific community a remarkable dataset of approximately one million spectra acquired with the radial velocity spectrometer (RVS) in the calcium II triplet region, which is well suited to identify very metal-poor (VMP) s ...

Edp Sciences S A2024

Adaptive projected variational quantum dynamics

Giuseppe Carleo, David Linteau, Stefano Barison

We propose an adaptive quantum algorithm to prepare accurate variational time evolved wave functions. The method is based on the projected variational quantum dynamics (pVQD) algorithm, that performs a global optimization with linear scaling in the number ...

Amer Physical Soc2024

Learning the intrinsic dynamics of spatio-temporal processes through Latent Dynamics Networks

Alfio Quarteroni, Francesco Regazzoni, Stefano Pagani

Predicting the evolution of systems with spatio-temporal dynamics in response to external stimuli is essential for scientific progress. Traditional equations-based approaches leverage first principles through the numerical approximation of differential equ ...

Nature Portfolio2024

Influence of sun cups on surface albedo of wet Alpine snowpack

Michael Lehning, Mathias Thierry Pierre Bavay, Francesca Carletti

In high elevation Alpine areas, characterised by high snow accumulation and radiation-driven melt processes, the formation of peculiar ablation features called sun cups can be observed. Sun cups likely influence the energy and mass balance of the wet snowp ...

2024

Uncertainty-aware Flexibility Envelope Prediction in Buildings with Controller-agnostic Battery Models

Colin Neil Jones, Paul Scharnhorst, Rafael Eduardo Carrillo Rangel, Pierre-Jean Alet, Baptiste Schubnel

Buildings are a promising source of flexibility for the application of demand response. In this work, we introduce a novel battery model formulation to capture the state evolution of a single building. Being fully data-driven, the battery model identificat ...

IEEE2023

Graph-based approximate message passing iterations

Raphaël Jean Berthier

Approximate message passing (AMP) algorithms have become an important element of high-dimensional statistical inference, mostly due to their adaptability and concentration properties, the state evolution (SE) equations. This is demonstrated by the growing ...

OXFORD UNIV PRESS2023

Breakdown development in a nanosecond pulsed dielectric barrier discharge in humid air in plane-to-plane geometry

Ivo Furno, Xin Yang, Lorenzo Ibba

We used the ns electric field induced second harmonic (EFISH) generation diagnostic to measure the electric field evolution in a 200 ns pulse, dielectric barrier, plane-to-plane discharge in humid air, on the time scale shorter than the laser pulse duratio ...

Iop Publishing Ltd2023

Information Theory in Transmembrane Transport

Solange Marie Flatt

The past decades have seen the advent of information theory in various fields, from quantum physics to cosmology. At an intermediary scale between atomic and cosmological scales are biological systems and in particular the cell, as a constitutive element o ...

EPFL2023

How roughness emerges on natural and engineered surfaces

Jean-François Molinari, Ramin Aghababaei

Roughness, defined as unevenness of material surfaces, plays an important role in determining how engineering components or natural objects interact with other bodies and their environment. The emergence of fractal roughness on natural and engineered surfa ...

SPRINGER HEIDELBERG2023

Modeling the mechanics and rheology of porous and granular media: an elastoplastic continuum approach

Lars Kristoffer Uhlen Blatny

The complex mechanics of porous and granular media play a significant role in various industrial processes and natural phenomena. As an example, understanding the mechanics of how failure occurs, localizes and propagates in porous brittle solids under vari ...

EPFL2023

The evolution of the Milky Way's thin disc radial metallicity gradient with K2 asteroseismic ages

Saniya Khan

The radial metallicity distribution of the Milky Way's disc is an important observational constraint for models of the formation and evolution of our Galaxy. It informs our understanding of the chemical enrichment of the Galactic disc and the dynamical pro ...

Oxford Univ Press2023

Rationalizing Performance Losses of Wide Bandgap Perovskite Solar Cells Evident in Data from the Perovskite Database

Christian Michael Wolff, Tor Jesper Jacobsson

Metal halide perovskites (MHPs) have become a widely studied class of semiconductors for various optoelectronic devices. The possibility to tune their bandgap (E-g) over a broad spectral range from 1.2 eV to 3 eV by compositional engineering makes them par ...

Wiley-V C H Verlag Gmbh2023

Graph neural networks for dynamic modeling of roller bearings

Olga Fink, Vinay Sharma

Machine learning has paved the way for the real-time monitoring of complex infrastructure and industrial systems. However, purely data-driven methods have not been able to learn the underlying dynamics and generalize them to operating conditions that have ...

PHM Society2023

Scaling Description of Dynamical Heterogeneity and Avalanches of Relaxation in Glass-Forming Liquids

Matthieu Wyart, Ali Tahaei

We provide a theoretical description of dynamical heterogeneities in glass-forming liquids, based on the premise that relaxation occurs via local rearrangements coupled by elasticity. In our framework, the growth of the dynamical correlation length e and o ...

American Physical Society2023

Novel quantitative bioengineered tools to track human bone marrow niche cellular constituents in health and disease

Rita Sarkis

Acute leukemia has a high mortality rate of approximately 50%, and current methods are not effective in predicting disease progression and relapse. To improve our understanding of hematopoiesis and develop new markers for predicting disease relapse in dead ...

EPFL2023

GTC Follow-up Observations of Very Metal-poor Star Candidates from DESI

Pascale Jablonka, Arjun Dey

The observations from the Dark Energy Spectroscopic Instrument (DESI) will significantly increase the numbers of known extremely metal-poor stars by a factor of similar to 10, improving the sample statistics to study the early chemical evolution of the Mil ...

Iop Publishing Ltd2023

Planted XY model: Thermodynamics and inference

Lenka Zdeborová, Guanhao Huang, Siyu Chen, Giovanni Piccioli

In this paper we study a fully connected planted spin glass named the planted XY model. Motivation for studying this system comes both from the spin glass field and the one of statistical inference where it models the angular synchronization problem. We de ...

2022

Multi-layer State Evolution Under Random Convolutional Design

Florent Gérard Krzakala, Lenka Zdeborová

Signal recovery under generative neural network priors has emerged as a promising direction in statistical inference and computational imaging. Theoretical analysis of reconstruction algorithms under generative priors is, however, challenging. For generati ...

2022