Related papers: Towards Designing and Exploiting Generative Networ…
Neural networks transform high-dimensional data into compact, structured representations, often modeled as elements of a lower dimensional latent space. In this paper, we present an alternative interpretation of neural models as dynamical…
By sampling from the latent space of an autoencoder and decoding the latent space samples to the original data space, any autoencoder can simply be turned into a generative model. For this to work, it is necessary to model the autoencoder's…
The LCTPC collaboration is developing a time projection chamber (TPC) for a future linear collider. In the ILD concept for an ILC detector a TPC is foreseen as main tracking device. In order to get measurable signals on the anode, the…
We present a new technology for the shaping of the electric field in Time Projection Chambers (TPCs) using a carbon-loaded polyimide foil. This technology allows for the minimisation of passive material near the active volume of the TPC and…
The Deep Underground Neutrino Experiment (DUNE) is a 40-kton underground liquid argon time-projection-chamber (LAr TPC) detector, for long-baseline neutrino oscillation studies and for neutrino astrophysics and nucleon decay searches.…
Neural Radiance Fields (NeRFs) have proven to be powerful 3D representations, capable of high quality novel view synthesis of complex scenes. While NeRFs have been applied to graphics, vision, and robotics, problems with slow rendering…
The Cryogenic Apparatus for Precision Tests of Argon Interactions with Neutrinos (CAPTAIN) is being built at Los Alamos National Laboratory. A hexagonal time projection chamber (TPC) with a 1 m drift length will be constructed inside a…
We present the multiple particle identification (MPID) network, a convolutional neural network (CNN) for multiple object classification, developed by MicroBooNE. MPID provides the probabilities of $e^-$, $\gamma$, $\mu^-$, $\pi^\pm$, and…
The single-phase liquid argon time projection chamber (LArTPC) provides a large amount of detailed information in the form of fine-grained drifted ionization charge from particle traces. To fully utilize this information, the deposited…
Generative models have demonstrated strong performance in conditional settings and can be viewed as a form of data compression, where the condition serves as a compact representation. However, their limited controllability and…
We report the first measurement of the flux-integrated cross section of $\nu_{\mu}$ charged-current single $\pi^{0}$ production on argon. This measurement is performed with the MicroBooNE detector, an 85 ton active mass liquid argon time…
This paper reports on the capabilities in reconstructing and identifying atmospheric neutrino interactions in one of the Deep Underground Neutrino Experiment's (DUNE) far detector modules, a liquid argon time projection chamber (LArTPC)…
The integration of neutral atoms with nanophotonic structures offer significant potential as a versatile platform to explore fundamental light-matter interactions as well as realizing novel quantum-optical devices. Here, we investigate the…
The current focus of the CERN program is the Large Hadron Collider (LHC), however, CERN is engaged in long baseline neutrino physics with the CNGS project and supports T2K as recognized CERN RE13, and for good reasons: a number of observed…
For a large liquid argon time projection chamber (LArTPC) operating on or near the Earth's surface to detect neutrino interactions, the rejection of cosmogenic background is a critical and challenging task because of the large cosmic ray…
ArgoNeuT (Argon Neutrino Test), a NSF/DOE project at Fermilab, is the first LArTPC to go in a low energy neutrino beam and just the second LArTPC to go in a neutrino beam ever. ArgoNeuT sits just upstream of the on-axis MINOS near detector…
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…
In the majority of GAN architectures, the latent space is defined as a set of vectors of given dimensionality. Such representations are not easily interpretable and do not capture spatial information of image content directly. In this work,…
The Deep Underground Neutrino Experiment (DUNE) Far Detector (FD) will be formed by four 10-kton Liquid Argon (LAr) Time Projection Chambers (TPC) using both single and dual-phase technology. The dual-phase technology foreseen the charge…
We present a novel artificial cognitive mapping system using generative deep neural networks, called variational autoencoder/generative adversarial network (VAE/GAN), which can map input images to latent vectors and generate temporal…