Imagen de Portada

Progress on Data-Driven, Multi-Objective Quantum Optimization

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Plehn, Thomas, Barragan-Yani, Daniel, Breitbarth, Eric, Requena, Guillermo, Melching, David
Formato:	Preprint
Publicado:	2025
Materias:	Materials Science
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Trustworthy AI-based crack-tip segmentation using domain-guided explanations
por: Talies, Jesco, et al.
Publicado: (2025)

A universal crack tip correction algorithm discovered by physical deep symbolic regression
por: Melching, David, et al.
Publicado: (2024)

Annotated digital image correlation displacement fields from fatigue crack growth experiments
por: Melching, David, et al.
Publicado: (2026)

Identification and characterization of three-dimensional crack propagation mechanism in the Aluminium alloy AA2024-T3 using high-resolution Digital Image Correlation
por: Schöne, Vanessa, et al.
Publicado: (2024)

Advanced crack tip stress analysis using interaction integrals in high-resolution digital image correlation fields
por: Paysan, Florian, et al.
Publicado: (2024)

Generating artificial digital image correlation data using physics-guided adversarial networks
por: Melching, David, et al.
Publicado: (2023)

Assessing the potential of perfect screw dislocations in SiC for solid-state quantum technologies
por: Barragan-Yani, Daniel, et al.
Publicado: (2023)

Electronic and optical properties of native point defects in CuInS$_2$ and CuGaS$_2$
por: Fried, Henry Phillip, et al.
Publicado: (2025)

Coherent Collections of Rules Describing Exceptional Materials Identified with a Multi-Objective Optimization of Subgroups
por: Foppa, Lucas, et al.
Publicado: (2024)

Accelerated Multi-Objective Alloy Discovery through Efficient Bayesian Methods: Application to the FCC Alloy Space
por: Hastings, Trevor, et al.
Publicado: (2024)

A High-Throughput and Data-Driven Computational Framework for Novel Quantum Materials
por: Kastuar, Srihari M., et al.
Publicado: (2024)

Towards Self-Optimizing Electron Microscope: Robust Tuning of Aberration Coefficients via Physics-Aware Multi-Objective Bayesian Optimization
por: Pratiush, Utkarsh, et al.
Publicado: (2026)

Generative Multi-Objective Bayesian Optimization with Scalable Batch Evaluations for Sample-Efficient De Novo Molecular Design
por: Muthyala, Madhav R., et al.
Publicado: (2025)

DataScribe: An AI-Native, Policy-Aligned Web Platform for Multi-Objective Materials Design and Discovery
por: Singh, Divyanshu, et al.
Publicado: (2026)

Beyond Scalar Objectives: Expert-Feedback-Driven Autonomous Experimentation for Scientific Discovery at the Nanoscale
por: Bulanadi, Ralph, et al.
Publicado: (2026)

Recent Progress in Studies of Cobalt-based Quasi-1-dimensional Quantum Magnets
por: Jin, Lun, et al.
Publicado: (2025)

Data-Driven Topological Analysis of Polymorphic Crystal Structures
por: Dey, Sourin, et al.
Publicado: (2025)

Multi-fidelity Bayesian Data-Driven Design of Energy Absorbing Spinodoid Cellular Structures
por: Guo, Leo, et al.
Publicado: (2025)

Accelerating Multi-Objective Collaborative Optimization of Doped Thermoelectric Materials via Artificial Intelligence
por: Zeng, Yuxuan, et al.
Publicado: (2025)

XtalOpt Version 13: Multi-Objective Evolutionary Search for Novel Functional Materials
por: Hajinazar, Samad, et al.
Publicado: (2024)

Medium-Throughput Evaluation of Quantum Geometry-Driven Topological Transports in Altermagnets
por: Li, Fu, et al.
Publicado: (2026)

Multimode Objective Lens for Momentum Microscopy and XPEEM: Experiments
por: Tkach, O., et al.
Publicado: (2024)

Deciphering Chemical Ordering in High Entropy Materials: A Machine Learning-Accelerated High-throughput Cluster Expansion Approach
por: Vazquez, Guillermo, et al.
Publicado: (2024)

Data-Driven Exploration and Insights into Temperature-Dependent Phonons in Inorganic Materials
por: Lee, Huiju, et al.
Publicado: (2026)

Data-Driven Insights into Rare Earth Mineralization: Machine Learning Applications Using Functional Material Synthesis Data
por: Liu, Juejing, et al.
Publicado: (2025)

Finite Element Simulation of NMC Particle Fracture during Calendering: a Route to Optimize Electrode Microstructures
por: Guichard, Pierrick, et al.
Publicado: (2026)

Data-Driven Discovery of Unconventional Antiferromagnets
por: Cui, Qirui, et al.
Publicado: (2026)

Objective Moiré Pattern
por: Feng, Fan
Publicado: (2024)

Electron-induced non-monotonic pressure dependence of the lattice thermal conductivity of θ-TaN
por: Kundu, Ashis, et al.
Publicado: (2023)

Data Driven Insights into Composition Property Relationships in FCC High Entropy Alloys
por: Flores, Nicolas, et al.
Publicado: (2025)

From Data-Driven Models to Physical Insight: Vibrational Entropy Governed by Atomic Volume
por: Tripathi, Shivam, et al.
Publicado: (2026)

At-Scale Data-Driven Exploration of High-Voltage Cathode-Active Materials for Sodium Batteries
por: Akter, Suchona, et al.
Publicado: (2026)

Quantum-Accurate Machine Learning Potentials for Metal-Organic Frameworks using Temperature Driven Active Learning
por: Sharma, Abhishek, et al.
Publicado: (2024)

Systematic Improvement of Quantum Monte Carlo Calculations in Transition Metal Oxides: sCI-Driven Wavefunction Optimization for Reliable Band Gap prediction
por: Shin, Hyeondeok, et al.
Publicado: (2024)

Hyperparameter Optimization for Atomic Cluster Expansion Potentials
por: Toit, Daniel F. Thomas du, et al.
Publicado: (2024)

A Unified Simulation Framework for Correlated Driven-Dissipative Quantum Dynamics
por: Blommel, Thomas, et al.
Publicado: (2025)

Data-Driven Modeling of Dislocation Mobility from Atomistics using Physics-Informed Machine Learning
por: Tian, Yifeng, et al.
Publicado: (2024)

Topology-Driven Vibrations in a Chiral Polar Vortex Lattice
por: Hoglund, Eric R., et al.
Publicado: (2025)

Curiosity Driven Exploration to Optimize Structure-Property Learning in Microscopy
por: Vatsavai, Aditya, et al.
Publicado: (2025)

Optimized Sandwich and Topological Structures for Enhanced Haptic Transparency
por: Daunizeau, Thomas, et al.
Publicado: (2023)