Research
Research
Research
Research
28,154+ open-access research outputs.
Describing the proton structure function $F_2$ in the non-perturbative and transition regimes of quantum chromodynamics (QCD) remains a significant theoretical challenge. In this work, we introduce a …
This study focuses on energy conversion related to tearing-driven magnetic reconnection in the context of weakly collisional astrophysical plasmas. We present results from a two-dimensional hybrid par…
Chirality in superconductor-ferromagnet hybrids strongly influences phenomena such as the observable signatures of long-range triplet superconductivity, but its microscopic origin in nominally centros…
Unlocking the full physical information encoded in low-resolution spectra poses a significant challenge for astronomical survey analysis. Such a task demands modeling spectra and optimizing astrophysi…
Wide-field slitless grism spectroscopy is difficult in the co-spatial regime, where multiple sources share one cross-dispersion PSF element and catalogue-level decontamination (aXe/LINEAR/Grizli) does…
Existing LLM agents for computational materials science are constrained by pipeline-bounded architectures tied to specific simulation codes and by dependence on manually written tool functions that gr…
We introduce a wavelength-multiplexed massively parallel diffractive information storage platform composed of dielectric surfaces that are structurally optimized at the wavelength scale using deep lea…
The persistent absence of signals in traditional dark matter searches has intensified interest in scenarios beyond the canonical weakly interacting massive particle paradigm. In this work, we investig…
Maximally-localized Wannier functions are quantum wavefunctions resembling atomic orbitals that are used to describe electrons in condensed matter. Since their introduction in 1997, these functions ha…
Molybdenum sulfides are in the spotlight of materials science thanks to their interesting properties for applications in optoelectronics, nanocomposites, lubricants, and catalysis. The structural char…
Matrix multiplication (MatMul) is the computational backbone of modern machine learning, yet its classical complexity remains a bottleneck for large-scale data processing. We propose a hybrid quantum-…
The demand for safe, high-energy-density batteries has spotlighted halide solid-state electrolytes, which offer the potential for enhanced ionic mobility, electrochemical stability, and interfacial de…
Two-dimensional (2D) carbon networks, from pristine graphene to defect-rich and amorphous monolayers, exhibit a complex structure-energy landscape governed not only by local bonding but also by medium…
Deep generative models such as diffusion and flow matching are powerful machine learning tools capable of learning and sampling from high-dimensional distributions. They are particularly useful when t…
The inherent compositional heterogeneity of multi-principal element alloys (MPEAs) gives rise to complex, spatially varying mechanical fields that cannot be uniquely determined from coarse-grained com…
Stochastic kinetic models are ubiquitous in physics, yet inferring their parameters from experimental data remains challenging. In deterministic models, parameter inference often relies on gradients, …
The choice between conservative and non-conservative formulations is a fundamental dilemma in CFD. While non-conservative forms offer intuitive modeling in primitive variables, they typically produce …
Some notable systems, such as room-temperature superconductors and materials for controlled nuclear fusion, require an accurate description of finite-temperature quantum matter. Stochastic path integr…
The sensitivity of continuous gravitational-wave searches is strictly limited by non-Gaussian spectral artefacts that accumulate coherent power over long observation baselines. In this paper, we prese…
The pressure Poisson equation (PPE) represents the primary computational bottleneck in fractional step methods for incompressible flow simulations, requiring iterative solutions of large-scale linear …
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