Related papers: GRASS II: Simulations of Potential Granulation Noi…
Recent success in the field of single image super-resolution (SISR) is achieved by optimizing deep convolutional neural networks (CNNs) in the image space with the L1 or L2 loss. However, when trained with these loss functions, models…
We report the detection of Voigt spectral line profiles of radio recombination lines (RRLs) toward Sagittarius B2(N) with the 100-m Green Bank Telescope (GBT). At radio wavelengths, astronomical spectra are highly populated with RRLs, which…
The Sun is the only star where the superficial turbulent convection can be observed at very high spatial resolution. The Solar Dynamics Observatory (SDO) has continuously observed the full Sun from space with multi-wavelength filters since…
Rice has been one of the staple foods that contribute significantly to human food supplies. Numerous rice varieties have been cultivated, imported, and exported worldwide. Different rice varieties could be mixed during rice production and…
Solar surface magneto-convection appears as granulation pattern that impacts spectral lines in terms of both shape and wavelength. Such induced effects also tend to vary over the observed solar disc because of the changing observation angle…
Recent results from high-resolution solar granulation observations indicate the existence of a population of small granular cells that are smaller than 600 km in diameter. These small convective cells strongly contribute to the total area…
The new CRISP filter at the Swedish 1-m Solar Telescope provides opportunities for observing the solar atmosphere with unprecedented spatial resolution and cadence. In order to benefit from the high quality of observational data from this…
In photometry, the short-timescale stellar variability ("flicker"), such as that caused by granulation and oscillations, can reach amplitudes comparable to the transit depth of Earth-sized planets and is correlated over the typical transit…
Gradient-based data attribution methods, such as influence functions, are critical for understanding the impact of individual training samples without requiring repeated model retraining. However, their scalability is often limited by the…
We present a Bayesian analysis of data from the FIELDS instrument on board the Parker Solar Probe (PSP) spacecraft with the aim of constraining low frequency ($\lesssim$ 6 MHz) sky in preparation for several upcoming lunar-based…
Gaussian Splatting has revolutionized the world of novel view synthesis by achieving high rendering performance in real-time. Recently, studies have focused on enriching these 3D representations with semantic information for downstream…
Context: Measuring amplitudes of solar-like oscillations and the granulation power spectral density constitute two promising sources of information to improve our understanding and description of the convection in outer layers of stars.…
The background noise between 1 and 1.8 microns in ground-based instruments is dominated by atmospheric emission from hydroxyl molecules. We have built and commissioned a new instrument, GNOSIS, which suppresses 103 OH doublets between 1.47…
Coarse-graining has become an area of tremendous importance within many different research fields. For molecular simulation, coarse-graining bears the promise of finding simplified models such that long-time simulations of large-scale…
We use numerical simulations of ray tracing through N-body simulations to investigate weak lensing by large-scale structure. These are needed for testing the analytic predictions of two-point correlators, to set error estimates on them and…
We present the initial results of an observational study into the variation of the dominant length-scale of quiet solar emission: supergranulation. This length-scale reflects the radiative energy in the plasma of the upper solar…
Implicit Neural Representations (INRs) encode discrete signals in a continuous manner using neural networks, demonstrating significant value across various multimedia applications. However, the vulnerability of INRs presents a critical…
Existing prompt learning for VLMs exhibits a modality asymmetry, predominantly optimizing text tokens while still relying on frozen visual encoder as holistic extractor and neglecting the spectral granularity essential for fine-grained…
In this paper we present new optimization strategies for the reconstruction of X-ray images of solar flares by means of the data collected by the Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI). The imaging concept of the…
Reconstructing the causal network in a complex dynamical system plays a crucial role in many applications, from sub-cellular biology to economic systems. Here we focus on inferring gene regulation networks (GRNs) from perturbation or gene…