We show how the parton distributions in the photon can be accurately measured in the photoproduction of large-pt jets at HERA. A short review is given of the beyond Leading Logarithm formalism for the photon structure function, with a discussion of...
We present analysis of the asteroid surface density distribution of main belt asteroids (mean perihelion $Δ\simeq 2.404$ AU) in five ecliptic latitude fields, $-17 \gtsimeq β(\degr) \ltsimeq +15$, derived from deep \textit{Large Binocular Telesco...
In the present article, the main attention is given to fractal sets whose elements have certain restrictions on using digits or combinations of digits in own nega-P-representation. Topological, metric, and fractal properties of images of certain self...
Estimating Option-Implied Probability Distributions for Equity Pricing (⭐ 11)
Accurate electromagnetic (EM) feature extraction, including element characterization, eigenmodes, and field distributions, is essential for superconducting quantum circuit design. To streamline this process, we present a workflow built around Palace,...
We investigate the sets of joint probability distributions that maximize the average multi-information over a collection of margins. These functionals serve as proxies for maximizing the multi-information of a set of variables or the mutual informati...
This note is commenting on Ronald Gallant's (2015) reflections on the construction of Bayesian prior distributions from moment conditions. The main conclusion is that the paper does not deliver a working principle that could justify inference based o...
We consider the problems of statically refuting equivalence and similarity of output distributions defined by a pair of probabilistic programs. Equivalence and similarity are two fundamental relational properties of probabilistic programs that are es...
We present an accreditation protocol for analogue, i.e., continuous-time, quantum simulators. For a given simulation task, it provides an upper bound on the variation distance between the probability distributions at the output of an erroneous and er...
We consider the problem of sampling a multimodal distribution with a Markov chain given a small number of samples from the stationary measure. Although mixing can be arbitrarily slow, we show that if the Markov chain has a $k$th order spectral gap, i...
Self-supervised pre-training of language models usually consists in predicting probability distributions over extensive token vocabularies. In this study, we propose an innovative method that shifts away from probability prediction and instead focuse...
A detailed investigation on the relative isotopic distributions has been carried out for the first time in case of even-even correlated fission fragments for the $^{235}$U($n_{th}$,$f$) fission reaction. High-statistics data were obtained in a prompt...
Identification of the center of a data cloud is one of the basic problems in statistics. One popular choice for such a center is the median, and several versions of median in finite dimensional spaces have been studied in the literature. In particula...
Approximate message passing (AMP) is a low-cost iterative parameter-estimation technique for certain high-dimensional linear systems with non-Gaussian distributions. AMP only applies to independent identically distributed (IID) transform matrices, bu...
Perhaps the most noteworthy of recent findings in extragalactic globular cluster (GC) research are the multimodal GC metallicity distributions seen in massive early-type galaxies. We explore the origin of these distinct GC populations, the implicat...
Most work interpreting reasoning models studies only a single chain-of-thought (CoT), yet these models define distributions over many possible CoTs. We argue that studying a single sample is inadequate for understanding causal influence and the under...
Normalisation in probability theory turns a subdistribution into a proper distribution. It is a partial operation, since it is undefined for the zero subdistribution. This partiality makes it hard to reason equationally about normalisation. A novel d...
Factor models are widely used for dimension reduction in the analysis of multivariate data. This is achieved through decomposition of a p x p covariance matrix into the sum of two components. Through a latent factor representation, they can be interp...
We present photometric multiband spectral energy distributions for the GRB host galaxies: GRB 971214, GRB 970508, GRB 980613, GRB 980703 and GRB 990123 obtained with the 6-m telescope of SAO RAS. Using SEDs for the starburst galaxies, we made estim...
In this paper, we propose a new data poisoning attack and apply it to deep reinforcement learning agents. Our attack centers on what we call in-distribution triggers, which are triggers native to the data distributions the model will be trained on an...