Related papers: Unlocking Hidden Information in Sparse Small-Angle…
As an alternative to the traditional sampling theory, compressed sensing allows acquiring much smaller amount of data, still estimating the spectra of frequency-sparse signals accurately. However, compressed sensing usually requires random…
The available data on neutron scattering were analyzed to constrain a hypothetical new short-range interaction. We show that these constraints are several orders of magnitude better than those usually cited in the range between 1 pm and 5…
Posterior sampling with the spike-and-slab prior [MB88], a popular multimodal distribution used to model uncertainty in variable selection, is considered the theoretical gold standard method for Bayesian sparse linear regression [CPS09,…
Inverse Synthetic Aperture Radar (ISAR) imaging presents a formidable challenge when it comes to small everyday objects due to their limited Radar Cross-Section (RCS) and the inherent resolution constraints of radar systems. Existing ISAR…
Coherent elastic neutrino-nucleus scattering (CE$\nu$NS), a process recently measured for the first time at ORNL's Spallation Neutron Source, is directly sensitive to the weak form factor of the nucleus. The European Spallation Source…
We have determined a value for the $^1S_0$ neutron-neutron scattering length ($a_{nn}$) from high-precision measurements of time-of-flight spectra of neutrons from the $^2H(\pi^-,n \gamma)n$ capture reaction. The measurements were done at…
A neutron spectrometer, the European Low-Energy Neutron Spectrometer (ELENS), has been constructed to study exotic nuclei in inverse-kinematics experiments. The spectrometer, which consists of plastic scintillator bars, can be operated in…
3D Gaussian splatting (3DGS) is an innovative rendering technique that surpasses the neural radiance field (NeRF) in both rendering speed and visual quality by leveraging an explicit 3D scene representation. Existing 3DGS approaches require…
Imaging through scattering is a pervasive and difficult problem in many biological applications. The high background and the exponentially attenuated target signals due to scattering fundamentally limits the imaging depth of fluorescence…
Deep learning has been the engine powering many successes of data science. However, the deep neural network (DNN), as the basic model of deep learning, is often excessively over-parameterized, causing many difficulties in training,…
There is currently a big effort put into the operation and construction of world class neutron scattering facilities (SNS and SNS-TS2 in the US, J-PARC in Japan, ESS in Europe, CSS in China, PIK in Russia). On the other hand, there exists a…
The last decade has witnessed the development of several alternative neutron detector technologies, as a consequence of upcoming neutron sources and upgrades, as well the world-wide shortage of $^3$He. One branch of development is the…
Based on $\alpha$-stable random projections with small $\alpha$, we develop a simple algorithm for compressed sensing (sparse signal recovery) by utilizing only the signs (i.e., 1-bit) of the measurements. Using only 1-bit information of…
We report results of tests of the MISANS technique at the CG-1D beamline at High Flux Isotope Reactor (HFIR), Oak Ridge National Laboratory (ORNL). A chopper at 40 Hz simulated a pulsed neutron source at the beamline. A compact turn-key…
We consider the high energy physics unfolding problem where the goal is to estimate the spectrum of elementary particles given observations distorted by the limited resolution of a particle detector. This important statistical inverse…
Neutron imaging is an invaluable noninvasive technique for exploring new science and assisting industrial manufacture. However, state-of-the-art neutron facilities are extremely expensive and inconvenient to access, while the flux of…
We present a Bayesian method to constrain the masses and radii of neutron stars (NSs) using the information encoded in the X-ray pulse profiles of accreting millisecond pulsars. We model the shape of the pulses using "oblate Schwarzschild"…
Computing the optimal transport distance between statistical distributions is a fundamental task in machine learning. One remarkable recent advancement is entropic regularization and the Sinkhorn algorithm, which utilizes only matrix…
We present a new experimental method for measuring the process of Coherent Elastic Neutrino Nucleus Scattering (CENNS). This method uses a detector situated transverse to a high energy neutrino beam production target. This detector would be…
We establish a general form of explicit, input-dependent, measure-valued warpings for learning nonstationary kernels. While stationary kernels are ubiquitous and simple to use, they struggle to adapt to functions that vary in smoothness…