Home

Publication

Nuclei with Up to A=6 Nucleons with Artificial Neural Network Wave Functions

About
Privacy
Disclaimer

Graph Chatbot

Related publications (35)

Page 2 of 2

Grand canonical Brownian dynamics simulations of adsorption and self-assembly of SAS-6 rings on a surface

Pierre Gönczy, Niccolo Banterle

The Spindle Assembly Abnormal Protein 6 (SAS-6) forms dimers, which then self-assemble into rings that are critical for the nine-fold symmetry of the centriole organelle. It has recently been shown experimentally that the self-assembly of SAS-6 rings is st ...

AIP Publishing2023

Search for medium effects using jets from bottom quarks in PbPb collisions at √sNN = 5.02 TeV

Jian Wang, Matthias Finger, Qian Wang, Yiming Li, João Miguel das Neves Duarte, Matthias Wolf, Varun Sharma, Yi Zhang, Lei Zhang, Tian Cheng, Yixing Chen, Alexis Kalogeropoulos, Ioannis Papadopoulos, Hua Zhang, Siyuan Wang, Xin Chen, Michele Bianco, Sebastiana Gianì, Sun Hee Kim, Davide Di Croce, Jian Zhao, Rakesh Chawla, Jan Steggemann, Konstantin Androsov, Anna Mascellani, Federica Legger, Matteo Galli, Gabriele Grosso

The first study of the shapes of jets arising from bottom (b) quarks in heavy ion collisions is presented. Jet shapes are studied using charged hadron constituents as a function of their radial distance from the jet axis. Lead-lead (PbPb) collision data at ...

Elsevier2023

A Theory of Finite-Width Neural Networks: Generalization, Scaling Laws, and the Loss Landscape

Berfin Simsek

Deep learning has achieved remarkable success in various challenging tasks such as generating images from natural language or engaging in lengthy conversations with humans. The success in practice stems from the ability to successfully train massive neural ...

EPFL2023

Expectation consistency for calibration of neural networks

Lenka Zdeborová, Florent Gérard Krzakala, Bruno Loureiro, Lucas Andry Clarte

Despite their incredible performance, it is well reported that deep neural networks tend to be overoptimistic about their prediction confidence. Finding effective and efficient calibration methods for neural networks is therefore an important endeavour tow ...

2023

Hadronic nature of high-energy emission from the Galactic ridge

Andrii Neronov

We show that the IceCube observation of the Galactic neutrino-flux component confirms the hint of detection of neutrinos from the Galactic ridge (the inner part of the Milky Way disk within the Galactic longitude IlI < 30(degrees)), previously reported by ...

American Physical Society2023

Stable parameterization of continuous and piecewise-linear functions

Michaël Unser, Alexis Marie Frederic Goujon, Joaquim Gonçalves Garcia Barreto Campos

Rectified-linear-unit (ReLU) neural networks, which play a prominent role in deep learning, generate continuous and piecewise-linear (CPWL) functions. While they provide a powerful parametric representation, the mapping between the parameter and function s ...

2023

Anomaly-free scale symmetry and gravity

Mikhail Chapochnikov, Anna Tokareva

In this Letter, we address the question of whether the conformal invariance can be considered as a global symmetry of a theory of fundamental interactions. To describe Nature, this theory must contain a mechanism of spontaneous breaking of the scale symmet ...

ELSEVIER2023

Density-wave ordering in a unitary Fermi gas with photon-mediated interactions

Jean-Philippe Brantut, Victor Youri Helson, Kevin Etienne Robert Roux, Hideki Konishi, Timo Zwettler

A density wave (DW) is a fundamental type of long-range order in quantum matter tied to self-organization into a crystalline structure. The interplay of DW order with superfluidity can lead to complex scenarios that pose a great challenge to theoretical an ...

NATURE PORTFOLIO2023

Benign Overfitting in Deep Neural Networks under Lazy Training

Volkan Cevher, Grigorios Chrysos, Fanghui Liu, Zhenyu Zhu

This paper focuses on over-parameterized deep neural networks (DNNs) with ReLU activation functions and proves that when the data distribution is well-separated, DNNs can achieve Bayesoptimal test error for classification while obtaining (nearly) zero-trai ...

2023

A Neural-Network-Based Convex Regularizer for Inverse Problems

Michaël Unser, Alexis Marie Frederic Goujon, Pakshal Narendra Bohra, Sebastian Jonas Neumayer, Stanislas Ducotterd

The emergence of deep-learning-based methods to solve image-reconstruction problems has enabled a significant increase in quality. Unfortunately, these new methods often lack reliability and explainability, and there is a growing interest to address these ...

2023

Engineering SYK Interactions in Disordered Graphene Flakes under Realistic Experimental Conditions

Oleg Yazyev, Yifei Guan, Marta Agnieszka Brzezinska

We model interactions following the Sachdev-Ye-Kitaev (SYK) framework in disordered graphene flakes up to 300 000 atoms in size (-100 nm in diameter) subjected to an out-of-plane magnetic field B of 5-20 Tesla within the tight-binding formalism. We investi ...

AMER PHYSICAL SOC2023

Optical manipulation of plasmonic nanoparticles: Applications in surface chemistry and nano-optics

Jeonghyeon Kim

Optical tweezers are devices that can manipulate nano- and microparticles using a laser. The principle of optical tweezers is to apply a force to an object using the momentum of light. This force is very small, but it is sufficient to move things in the mi ...

EPFL2023

Search for new physics in multijet events with at least one photon and large missing transverse momentum in proton-proton collisions at 13 TeV

Jian Wang, Matthias Finger, Qian Wang, Yiming Li, João Miguel das Neves Duarte, Matthias Wolf, Varun Sharma, Yi Zhang, Tian Cheng, Yixing Chen, Alexis Kalogeropoulos, Ioannis Papadopoulos, Hua Zhang, Siyuan Wang, Xin Chen, Michele Bianco, Sebastiana Gianì, Sun Hee Kim, Rakesh Chawla, Jan Steggemann, Konstantin Androsov, Anna Mascellani, Federica Legger, Matteo Galli, Gabriele Grosso

A search for new physics in final states consisting of at least one photon, multiple jets, and large missing transverse momentum is presented, using proton-proton collision events at a center-of-mass energy of 13 TeV. The data correspond to an integrated l ...

Springer Nature2023

Towards a muon collider

Varun Sharma, Riccardo Rattazzi, Xavier Buffat, Andrea Wulzer, Alexej Grudiev, Roberto Franceschini, Alfredo Glioti, Siyu Chen, Brian Quinn Henning, Riccardo Torre, Lorenzo Ricci, Xiaoran Zhao, Filippo Nardi

A muon collider would enable the big jump ahead in energy reach that is needed for a fruitful exploration of fundamental interactions. The challenges of producing muon collisions at high luminosity and 10 TeV centre of mass energy are being investigated by ...

Springer2023

3D trigonal FAPbI(3)-based multilevel resistive switching nonvolatile memory for artificial neural synapse

Mohammad Khaja Nazeeruddin, Paul Joseph Dyson, Yong Ding, Li Tao

Hybrid perovskites have attracted enormous attention in the next generation resistive switching (RS) memristor for the artificial synapses, owing to their ambipolar charge transport, long diffusion length, and tunable visible bandgap. However, the variable ...

WILEY2023