Related papers: Data-Driven Predictions for Dark Photon and Millic…
We show that dark matter direct detection experiments are sensitive to the existence of particles with a small effective charge (for instance, via couplings to a kinetically mixed, low-mass dark photon). Our forecasts do not depend on these…
Data-driven methods are widely used to overcome shortcomings of Monte Carlo simulations (lack of statistics, mismodeling of processes, etc.) in experimental high energy physics. A precise description of background processes is crucial to…
With anomalies found in cosmic ray observations and unsolved questions of the Standard Model of particle physics like the discrepancy in the muon's anomalous magnetic moment, the idea of an U(1) extension of the Standard Model arose. This…
Initial development and subsequent calibration of discrete event simulation models for complex systems require accurate identification of dynamically changing process characteristics. Existing data driven change point methods (DD-CPD)…
This paper proposes a method for estimating and detecting optical signals in practical photon-counting receivers. There are two important aspects of non-perfect photon-counting receivers, namely, (i) dead time which results in blocking…
Images are formed by counting how many photons traveling from a given set of directions hit an image sensor during a given time interval. When photons are few and far in between, the concept of `image' breaks down and it is best to consider…
Characteristics of hadron production in diffractive deep-inelastic positron-proton scattering are studied using data collected in 1994 by the H1 experiment at HERA. The following distributions are measured in the centre-of-mass frame of the…
This study proposes a behaviorally-informed multi-factor stock selection framework that integrates short-cycle technical alpha signals with deep learning. We design a dual-task multilayer perceptron (MLP) that jointly predicts five-day…
We study dark sector production in electromagnetic (EM) cascades. This problem requires accurate simulations of Standard Model (SM) and dark sector processes, both of which impact angular and energy distributions of emitted particles that…
This work presents DMPC (Data-and Model-Driven Predictive Control) to solve control problems in which some of the constraints or parts of the objective function are known, while others are entirely unknown to the controller. It is assumed…
Fixed-target proton-beam experiments produce a multitude of charged pions that rescatter in the beam dump. These charged pion scattering events can be an additional irreducible source of exotic particles which couple to photons or hadrons.…
We present a data-driven approach to efficiently approximate nonlinear transient dynamics in solid-state systems. Our proposed machine-learning model combines a dimensionality reduction stage with a nonlinear vector autoregression scheme.…
Particle collisions at the energy frontier can probe the nature of invisible dark matter via production in association with recoiling visible objects. We propose a new potential production mode, in which dark matter is produced by the decay…
In this paper, we present the first complete treatment of incoherent photon-initiated production in ultraperipheral heavy ion collisions, focussing on the dilepton and diphoton final states. In the former case we compare to the ATLAS…
Soft photons produced in heavy ion collisions are an important tool for probing the properties of the quark-gluon plasma. It is therefore crucial to understand the background - soft photons produced in elementary collisions. Low theorem…
Monte Carlo (MC) generators are crucial for analyzing data in particle collider experiments. However, often even a small mismatch between the MC simulations and the measurements can undermine the interpretation of the results. This is…
Direct photon production at large transverse momentum in the coherent diffractive processes at hadron colliders is calculated in the two-gluon exchange model. We find that the amplitude for the production process is related to the…
In this work we analyse the theoretical uncertainties on the predictions for the photoproduction of light vector mesons in coherent pp, pA and AA collisions at the LHC energies using the color dipole approach. In particular, we present our…
Our predictions for particle physics processes are realized in a chain of complex simulators. They allow us to generate high-fidelity simulated data, but they are not well-suited for inference on the theory parameters with observed data. We…
We propose a data-driven tracking model predictive control (MPC) scheme to control unknown discrete-time linear time-invariant systems. The scheme uses a purely data-driven system parametrization to predict future trajectories based on…