Instanton theory of ground-state tunneling splittings with general paths

À propos
Confidentialité
Mentions légales

Graph Chatbot

Publications associées (32)

Optimization Methods for Control: From Embedded Programmable Hardware to Data-Driven Process Optimization

Harsh Ambarishkumar Shukla

The research community has been making significant progress in hardware implementation, numerical computing and algorithm development for optimization-based control. However, there are two key challenges that still have to be overcome for optimization-base ...

EPFL2021

Automated Design: A Journey Across Modelling, Optimization, and Education

Cyril Picard

Machine intelligence greatly impacts almost all domains of our societies. It is profoundly changing the field of mechanical engineering with new technical possibilities and processes. The education of future engineers also needs to adapt in terms of techni ...

EPFL2021

Motile dislocations knead odd crystals into whorls

Alexis Poncet, Sofia Magkiriadou

The competition between thermal fluctuations and potential forces governs the stability of matter in equilibrium, in particular the proliferation and annihilation of topological defects. However, driving matter out of equilibrium allows for a new class of ...

NATURE PORTFOLIO2022

Physics-enhanced machine learning with symmetry-adapted and long-range representations

Andrea Grisafi

Theoretical and computational approaches to the study of materials and molecules have, over the last few decades, progressed at an exponential rate. Yet, the possibility of producing numerical predictions that are on par with experimental measurements is t ...

EPFL2021

Learning convergence prediction of astrobots in multi-object spectrographs

Denis Gillet, Jean-Paul Richard Kneib, Matin Macktoobian, Francesco Basciani

Astrobot swarms are used to capture astronomical signals to generate the map of the observable universe for the purpose of dark energy studies. The convergence of each swarm in the course of its coordination has to surpass a particular threshold to yield a ...

2021

Local invertibility and sensitivity of atomic structure-feature mappings

Michele Ceriotti, Sergey Pozdnyakov

Background: The increasingly common applications of machine-learning schemes to atomic-scale simulations have triggered efforts to better understand the mathematical properties of the mapping between the Cartesian coordinates of the atoms and the variety o ...

2021

Modeling and optimization of dedicated bus lanes space allocation in large networks with dynamic congestion

Nikolaos Geroliminis, Anastasios Kouvelas, Dimitrios Tsitsokas

Dedicated bus lanes provide a low cost and easily implementable strategy to improve transit service by minimizing congestion-related delays. Identifying the best spatial distribution of bus-only lanes in order to maximize traffic performance of an urban ne ...

2021

Linearized supergravity with a dynamical preferred frame

Sergey Sibiryakov

We study supersymmetric extension of the Einstein-aether gravitational model where local Lorentz invariance is broken down to the subgroup of spatial rotations by a vacuum expectation value of a timelike vector field called aether. Embedding aether into a ...

Springer Nature2021

Thin Liquid Film Dynamics on a Spinning Spheroid

Edouard Boujo

The present work explores the impact of rotation on the dynamics of a thin liquid layer deposited on a spheroid (bi-axial ellipsoid) rotating around its vertical axis. An evolution equation based on the lubrication approximation was derived, which takes in ...

MDPI2021

Controlling the rotation of drift tearing modes by biased electrode in ADITYA-U tokamak

Sameer Kumar, Abhijit Sen, Harshita Raj, Ankit Kumar, Rohit Kumar

The influence of background plasma poloidal rotation on the rotation frequency of the m/n = 2/1 drift tearing mode (DTM) has been studied in ADITYA-U tokamak. The poloidal rotation velocity of the background plasma in the ion diamagnetic direction is incre ...

2021

Increasing Superstructure Optimization Capacity Through Self-Learning Surrogate Models

François Maréchal, Ivan Daniel Kantor, Julia Granacher

Simulation-based optimization models are widely applied to find optimal operating conditions of processes. Often, computational challenges arise from model complexity, making the generation of reliable design solutions difficult. We propose an algorithm fo ...

2021

Optimal Control Combining Emulation and Imitation to Acquire Physical Assistance Skills

Sylvain Calinon, Teguh Santoso Lembono, Amirreza Razmjoo Fard

paper studies exploiting action-level learning (imitation) in the optimal control problem context. Cost functions defined by the optimal control methods are similar to the goal-level learning (emulation) in animals. However, imitating the robot's or others ...

IEEE2021

Page 2 sur 2