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Aging Behaviors in a La-Based Metallic Glass Revealed by Two-Time Correlation Functions
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Assessing Exchange-Correlation Functionals for Heterogeneous Catalysis of Nitrogen Species
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Machine learning accurate exchange and correlation functionals of the electronic density
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A linear response framework for quantum simulation of bosonic and fermionic correlation functions
Response functions are a fundamental aspect of physics; they represent the link between experimental observations and the underlying quantum many-body state. However, this link is often under-appreciated, as the Lehmann formalism for obtaining response functions in linear response has no direct link to experiment. Within the context of quantum computing, and via a linear response framework, we restore this link by making the experiment an inextricable part of the quantum simulation. This method can be frequency- and momentum-selective, avoids limitations on operators that can be directly measured, and can be more efficient than competing methods. As prototypical examples of response functions, we demonstrate that both bosonic and fermionic Green’s functions can be obtained, and apply these ideas to the study of a charge-density-wave material on the ibm_auckland superconducting quantum computer. The linear response method provides a robust framework for using quantum computers to study systems in physics and chemistry.
Imaginary-time correlation function thermometry: A new, high-accuracy and model-free temperature analysis technique for x-ray Thomson scattering data
The accurate interpretation of experiments with matter at extreme densities and pressures is a notoriously difficult challenge. In a recent work [Dornheim et al., Nat. Commun. 13, 7911 (2022)], we have introduced a formally exact methodology that allows extracting the temperature of arbitrary complex materials without any model assumptions or simulations. Here, we provide a more detailed introduction to this approach and analyze the impact of experimental noise on the extracted temperatures. In particular, we extensively apply our method both to synthetic scattering data and to previous experimental measurements over a broad range of temperatures and wave numbers. We expect that our approach will be of high interest to a gamut of applications, including inertial confinement fusion, laboratory astrophysics, and the compilation of highly accurate equation-of-state databases.
The effects of massive neutrinos on the linear point of the correlation function
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Proton number cumulants and correlation functions in Au-Au collisions at s N N = 7.7 –200 GeV from hydrodynamics
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Long-range electroweak amplitudes of single hadrons from Euclidean finite-volume correlation functions
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Field sparsening for the construction of the correlation functions in lattice QCD
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Sparsening algorithm for multihadron lattice QCD correlation functions
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Characterization and Optimization of the Fitting of Quantum Correlation Functions
This case study presents a characterization and optimization of an application code for extracting parton distribution functions from high energy electron-proton scattering data. Profiling this application code reveals that the phase-space density computation accounts for 93% of the overall execution time for a single iteration on a single core. When executing multiple iterations in parallel on a multicore system, the application spends 78% of its overall execution time idling due to load imbalance. We address these issues by first transforming the application code from Python to C++ and then tackling the application load imbalance via a hybrid scheduling strategy that combines dynamic and static scheduling. These techniques result in a 62% reduction in CPU idle time and a 2.46x speedup in overall execution time per node. In addition, the typically enabled power-management mechanisms in supercomputers (e.g., AMD Turbo Core, Intel Turbo Boost, and RAPL) can significantly impact intra-node scalability when more than 50% of the CPU cores are used. This finding underscores the importance of understanding system interactions with power management, as they can adversely impact application performance, and highlights the necessity of intra-node scaling tests to identify performance degradation that inter-node scaling tests might otherwise overlook.
High-order cumulants and correlation functions near the critical point from molecular dynamics
Tabulated data for publication Phys. Rev. C 113 (2026) 045209
Solar Wind Magnetic Field Correlation Length: Correlation Functions versus Cross-field Displacement Diffusivity Test
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Some notes concerning the Fourier transformation of auto-correlation functions
Passage of autocorrelation function to frequency spectrum by numerical Fourier transformation
Correlation function apparatus Patent
Circuitry for developing autocorrelation function continuously within signal receiving period