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We propose to measure the weak decay constant $\alpha_-$ for the decay $\Lambda\rightarrow p\pi^-$ using a both circularly and linearly polarized photon beam with the GlueX spectrometer in Hall D. The measurement will take advantage of the fact that a measurement with both linear and circular photon beam polarization results in an over-constrained set of amplitudes which can be fitted to data and used to extract $\alpha_-$ which will be left as a free parameter in the fit. We expect to determine $\alpha_-$ with statistical uncertainties comparable to existing measurements and independent systematic uncertainties. This measurement can be performed alongside GlueX-II running and requires no new hardware or new beam time. The measurement requires that a sufficient fraction of the electron beam polarization be longitudinal in the Hall D tagger., Comment: Submitted to Jefferson Lab PAC52

Discrete-action reinforcement learning algorithms often falter in tasks with high-dimensional discrete action spaces due to the vast number of possible actions. A recent advancement leverages value-decomposition, a concept from multi-agent reinforcement learning, to tackle this challenge. This study delves deep into the effects of this value-decomposition, revealing that whilst it curtails the over-estimation bias inherent to Q-learning algorithms, it amplifies target variance. To counteract this, we present an ensemble of critics to mitigate target variance. Moreover, we introduce a regularisation loss that helps to mitigate the effects that exploratory actions in one dimension can have on the value of optimal actions in other dimensions. Our novel algorithm, REValueD, tested on discretised versions of the DeepMind Control Suite tasks, showcases superior performance, especially in the challenging humanoid and dog tasks. We further dissect the factors influencing REValueD's performance, evaluating the significance of the regularisation loss and the scalability of REValueD with increasing sub-actions per dimension., Comment: ICLR camera ready version

Fast, efficient and accurate triggers are a critical requirement for modern high-energy physics experiments given the increasingly large quantities of data that they produce. The CEBAF Large Acceptance Spectrometer (CLAS12) employs a highly efficient electron trigger to filter the amount of recorded data by requiring at least one electron in each event, at the cost of a low purity in electron identification. Machine learning algorithms are increasingly employed for classification tasks such as particle identification due to their high accuracy and fast processing times. In this article, we show how a convolutional neural network could be deployed as a Level 3 electron trigger at CLAS12. We demonstrate that the AI trigger would achieve a significant data reduction compared to the traditional trigger, whilst preserving a 99.5\% electron identification efficiency. The AI trigger purity as a function of increased luminosity is improved relative to the traditional trigger. As a consequence, this AI trigger can achieve a data recording reduction improvement of 0.33\% per nA when compared to the traditional trigger whilst maintaining an efficiency above 99.5\%. A reduction in data output also reduces storage costs and post-processing times, which in turn reduces the time to the publication of new physics measurements.

Combinatorial Optimisation problems arise in several application domains and are often formulated in terms of graphs. Many of these problems are NP-hard, but exact solutions are not always needed. Several heuristics have been developed to provide near-optimal solutions; however, they do not typically scale well with the size of the graph. We propose a low-complexity approach for identifying a (possibly much smaller) subgraph of the original graph where the heuristics can be run in reasonable time and with a high likelihood of finding a global near-optimal solution. The core component of our approach is LeNSE, a reinforcement learning algorithm that learns how to navigate the space of possible subgraphs using an Euclidean subgraph embedding as its map. To solve CO problems, LeNSE is provided with a discriminative embedding trained using any existing heuristics using only on a small portion of the original graph. When tested on three problems (vertex cover, max-cut and influence maximisation) using real graphs with up to $10$ million edges, LeNSE identifies small subgraphs yielding solutions comparable to those found by running the heuristics on the entire graph, but at a fraction of the total run time., Comment: To appear in ICML 2022

We propose to create a secondary beam of neutral kaons in Hall D at Jefferson Lab to be used with the GlueX experimental setup for strange hadron spectroscopy. The superior CEBAF electron beam will enable a flux on the order of $1\times 10^4~K_L/sec$, which exceeds the flux of that previously attained at SLAC by three orders of magnitude. The use of a deuteron target will provide first measurements ever with neutral kaons on neutrons. The experiment will measure both differential cross sections and self-analyzed polarizations of the produced $\Lambda$, $\Sigma$, $\Xi$, and $\Omega$ hyperons using the GlueX detector at the Jefferson Lab Hall D. The measurements will span CM $\cos\theta$ from $-0.95$ to 0.95 in the range W = 1490 MeV to 2500 MeV. The new data will significantly constrain the partial wave analyses and reduce model-dependent uncertainties in the extraction of the properties and pole positions of the strange hyperon resonances, and establish the orbitally excited multiplets in the spectra of the $\Xi$ and $\Omega$ hyperons. Comparison with the corresponding multiplets in the spectra of the charm and bottom hyperons will provide insight into he accuracy of QCD-based calculations over a large range of masses. The proposed facility will have a defining impact in the strange meson sector through measurements of the final state $K\pi$ system up to 2 GeV invariant mass. This will allow the determination of pole positions and widths of all relevant $K^\ast(K\pi)$ $S$-,$P$-,$D$-,$F$-, and $G$-wave resonances, settle the question of the existence or nonexistence of scalar meson $\kappa/K_0^\ast(700)$ and improve the constrains on their pole parameters. Subsequently improving our knowledge of the low-lying scalar nonet in general., Comment: Final version of the KLF Proposal [C12-19-001] approved by JLab PAC48. The intermediate version of the proposal was posted in arXiv:1707.05284 [hep-ex]. 103 pages, 52 figures, 8 tables, 324 references. Several typos were fixed

We review the last two decades of using photon beams to measure the production of mesons, and in particular the information that can be obtained on the spectrum of light, non-strange baryons. This is a compendium of experimental results, which should be used as a complement to theoretical reviews of the subject. Lists of data sets are given, together with a comprehensive set of references. An indication of the impact of the data is presented with a summary of the results., Comment: Submitted to Progress in Particle and Nuclear Physics

Tomographic imaging techniques using the Coulomb scattering of cosmic-ray muons have been shown previously to successfully identify and characterise low- and high-Z materials within an air matrix using a prototype scintillating-fibre tracker system. Those studies were performed as the first in a series to assess the feasibility of this technology and image reconstruction techniques in characterising the potential high-Z contents of legacy nuclear waste containers for the UK Nuclear Industry. The present work continues the feasibility study and presents the first images reconstructed from experimental data collected using this small-scale prototype system of low- and high-Z materials encapsulated within a concrete-filled stainless-steel container. Clear discrimination is observed between the thick steel casing, the concrete matrix and the sample materials assayed. These reconstructed objects are presented and discussed in detail alongside the implications for future industrial scenarios., Comment: 6 pages, 4 figures