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19932026
most citedAdvanced capabilities for materials modelling with Quantum ESPRESSO

7.7k citations

Showing 2023Show all

35 papers · 1 filter

physics.ins-det2023

A demonstrator for a real-time AI-FPGA-based triggering system for sPHENIX at RHIC

J. Kvapil, G. Borca-Tasciuc, H. Bossi +28

The RHIC interaction rate at sPHENIX will reach around 3 MHz in pp collisions and requires the detector readout to reject events by a factor of over 200 to fit the DAQ bandwidth of…

cs.RO2023★ 1 cited

Towards a Unified Naming Scheme for Thermo-Active Soft Actuators: A Review of Materials, Working Principles, and Applications

Trevor Exley, Emilly Hays, Daniel Johnson +3

Soft robotics is a rapidly growing field that spans the fields of chemistry, materials science, and engineering. Due to the diverse background of the field, there have been contras…

cs.DC2023

HEET: A Heterogeneity Measure to Quantify the Difference across Distributed Computing Systems

Ali Mokhtari, Saeid Ghafouri, Pooyan Jamshidi +1

Although system heterogeneity has been extensively studied in the past, there is yet to be a study on measuring the impact of heterogeneity on system performance. For this purpose,…

astro-ph.GA2023★ 23 cited

An Atlas of Gas Motions in the TNG-Cluster Simulation: from Cluster Cores to the Outskirts

Mohammadreza Ayromlou, Dylan Nelson, Annalisa Pillepich +6

Galaxy clusters are unique laboratories for studying astrophysical processes and their impact on gas kinematics. Despite their importance, the full complexity of gas motion within…

astro-ph.GA2023★ 13 cited

High-Spectral Resolution Observations of the Optical Filamentary Nebula in NGC 1275

Benjamin Vigneron, Julie Hlavacek-Larrondo, Carter Lee Rhea +18

We present new high-spectral resolution observations (R = = 7000) of the filamentary nebula surrounding NGC 1275, the central galaxy of the Perseus cluster. These observatio…

cs.LG2023★ 1 cited

Addressing Weak Decision Boundaries in Image Classification by Leveraging Web Search and Generative Models

Preetam Prabhu Srikar Dammu, Yunhe Feng, Chirag Shah

Machine learning (ML) technologies are known to be riddled with ethical and operational problems, however, we are witnessing an increasing thrust by businesses to deploy them in se…