Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
Machine learning for analysis of experimental scattering and spectroscopy data in materials chemistry
The rapid growth of materials chemistry data, driven by advancements in large-scale
radiation facilities as well as laboratory instruments, has outpaced conventional data …
radiation facilities as well as laboratory instruments, has outpaced conventional data …
Capturing dynamical correlations using implicit neural representations
Understanding the nature and origin of collective excitations in materials is of fundamental
importance for unraveling the underlying physics of a many-body system. Excitation spectra …
importance for unraveling the underlying physics of a many-body system. Excitation spectra …
[HTML][HTML] Update of HΦ: Newly added functions and methods in versions 2 and 3
H Φ [aitch-phi] is an open-source software package of numerically exact and stochastic
calculations for a wide range of quantum many-body systems. In this paper, we present the …
calculations for a wide range of quantum many-body systems. In this paper, we present the …
On ultrafast x-ray scattering methods for magnetism
With the introduction of x-ray free electron laser sources around the world, new scientific
approaches for visualizing matter at fundamental length and time-scales have become …
approaches for visualizing matter at fundamental length and time-scales have become …
Engineering the Kitaev spin liquid in a quantum dot system
The Kitaev model on a honeycomb lattice may provide a robust topological quantum
memory platform, but finding a material that realizes the unique spin-liquid phase remains a …
memory platform, but finding a material that realizes the unique spin-liquid phase remains a …
Direct prediction of inelastic neutron scattering spectra from the crystal structure
Inelastic neutron scattering (INS) is a powerful technique to study vibrational dynamics of
materials with several unique advantages. However, analysis and interpretation of INS …
materials with several unique advantages. However, analysis and interpretation of INS …
A perspective on machine learning and data science for strongly correlated electron problems
Numerical approaches to the correlated electron problem have achieved considerable
success, yet are still constrained by several bottlenecks, including high order polynomial or …
success, yet are still constrained by several bottlenecks, including high order polynomial or …
Thermal spin dynamics of Kitaev magnets: Scattering continua and magnetic field induced phases within a stochastic semiclassical approach
The honeycomb magnet α-RuCl 3 is a prime candidate material for realizing the Kitaev
quantum spin liquid (QSL), but it shows long-range magnetic order at low temperature …
quantum spin liquid (QSL), but it shows long-range magnetic order at low temperature …
Simulations of frustrated Ising Hamiltonians using quantum approximate optimization
Novel magnetic materials are important for future technological advances. Theoretical and
numerical calculations of ground-state properties are essential in understanding these …
numerical calculations of ground-state properties are essential in understanding these …
Kernel polynomial method for linear spin wave theory
Calculating dynamical spin correlations is essential for matching model magnetic exchange
Hamiltonians to momentum-resolved spectroscopic measurements. A major numerical …
Hamiltonians to momentum-resolved spectroscopic measurements. A major numerical …