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The continuous advancement of experimental techniques and investigations has led to observations of various exotic states in particle physics. Each addition to this family of states not only raises expectations for future discoveries but also focuses attention on such potential new states. Building upon this motivation and inspired by recent observations of various traditional and exotic particles containing an increased number of heavy quarks, our study provides a spectroscopic search for potential pentaquark states with spin-parity $\frac{3}{2}^-$ and composed entirely of charm or bottom quarks. We predict the masses for full-charm and full-bottom pentaquark states as $m = 7628 \pm 112$~MeV and $m = 21982 \pm 144$~MeV, respectively. We also compute the current couplings of these states to vacuum, which are main inputs in investigations of their various possible decays., Comment: 9 Pages, 4 Figures and 2 Tables

We investigate the light quarkonium hybrid mesons of various spin-parities in QCD. Considering different interpolating currents made of the valence light quarks and single gluon, we calculate the mass and current coupling of the strange and nonstrange members of light hybrid mesons by including into computations the nonperturbative quark and gluon condensates up to ten dimensions in order to increase the accuracy of the results. The obtained results may be useful for future experimental searches of these hypothetical states. They can also be used in the calculations of different parameters related to the decays/interactions of light hybrid mesons to/with other states., Comment: 12 Pages, 3 Figures and 9 Tables

Time-series with volatility clustering pose a unique challenge to uncertainty quantification (UQ) for returns forecasts. Methods for UQ such as Deep Evidential regression offer a simple way of quantifying return forecast uncertainty without the costs of a full Bayesian treatment. However, the Normal-Inverse-Gamma (NIG) prior adopted by Deep Evidential regression is prone to miscalibration as the NIG prior is assigned to latent mean and variance parameters in a hierarchical structure. Moreover, it also overparameterizes the marginal data distribution. These limitations may affect the accurate delineation of epistemic (model) and aleatoric (data) uncertainties. We propose a Scale Mixture Distribution as a simpler alternative which can provide favorable complexity-accuracy trade-off and assign separate subnetworks to each model parameter. To illustrate the performance of our proposed method, we apply it to two sets of financial time-series exhibiting volatility clustering: cryptocurrencies and U.S. equities and test the performance in some ablation studies., Comment: 44 pages

We study the triply heavy spin-1/2 baryons with quark contents $ ccb $ and $ bbc $, and calculate their mass and residue using QCD sum rules. In the calculations, we consider the ground (1S), first orbitally excited (1P) and first radially excited (2S) states. Aiming to achieve higher accuracies in the results, we perform the computations by taking into account the non-perturbative operators up to eight mass dimensions. We compare our results with the predictions of other theoretical studies existing in the literature. The obtained results may help experimental groups in their search for these yet unseen, but previously predicted by the quark model, interesting particles., Comment: 36 Pages, 7 Figures and 6 Tables

This paper addresses the gap between the capabilities and utilisation of robotics and automation in laboratory settings and builds upon the concept of Self Driving Labs (SDL). %to significantly impact laboratory operations. We introduce an innovative approach to the temporal characterisation of materials. The article discusses the challenges posed by manual methods involving established laboratory equipment and presents an automated hyperspectral characterisation station. This station integrates robot-aided hyperspectral imaging, complex material characterisation modeling, and automated data analysis, offering a non-destructive and comprehensive approach. This work explains how the proposed assembly can automatically measure the half-life of biodegradable polymers with higher throughput and accuracy than manual methods. The investigation explores the effect of pH, number of average molecular weight (Mn), end groups, and blends on the degradation rate of polylactic acid (PLA). The contributions of the paper lie in introducing an adaptable classification station for novel characterisation methods and presenting an innovative methodology for polymer degradation rate measurement. The proposed system has the potential to accelerate the development of high-throughput screening and characterisation methods in material and chemistry laboratories., Comment: 11 pages, 12 figures

As Vision Transformers (ViTs) increasingly set new benchmarks in computer vision, their practical deployment on inference engines is often hindered by their significant memory bandwidth and (on-chip) memory footprint requirements. This paper addresses this memory limitation by introducing an activation-aware model compression methodology that uses selective low-rank weight tensor approximations of different layers to reduce the parameter count of ViTs. The key idea is to decompose the weight tensors into a sum of two parameter-efficient tensors while minimizing the error between the product of the input activations with the original weight tensor and the product of the input activations with the approximate tensor sum. This approximation is further refined by adopting an efficient layer-wise error compensation technique that uses the gradient of the layer's output loss. The combination of these techniques achieves excellent results while it avoids being trapped in a shallow local minimum early in the optimization process and strikes a good balance between the model compression and output accuracy. Notably, the presented method significantly reduces the parameter count of DeiT-B by 60% with less than 1% accuracy drop on the ImageNet dataset, overcoming the usual accuracy degradation seen in low-rank approximations. In addition to this, the presented compression technique can compress large DeiT/ViT models to have about the same model size as smaller DeiT/ViT variants while yielding up to 1.8% accuracy gain. These results highlight the efficacy of our approach, presenting a viable solution for embedding ViTs in memory-constrained environments without compromising their performance.

The present study provides spectroscopic investigations of spin-$\frac{3}{2}$ $\Lambda$ baryons with both positive and negative parities. The analysis mainly focuses on three states, namely $1P$, $2P$, and $2S$, and corresponding masses are calculated using the QCD sum rule method. To implement the method, we apply two types of interpolating currents with octet and singlet quantum numbers and compare the corresponding results with the reported masses of experimentally observed states. From the comparisons, it is extracted that the results of interpolating current with octet quantum numbers are in good agreement with the experimentally measured masses. The masses obtained with this interpolating current are $m=1513.64\pm 8.76$ MeV for $1P$ state with $J^P=\frac{3}{2}^-$, $m'=1687.91\pm 0.31$ MeV for $2P$ state with $J^P=\frac{3}{2}^-$ and $\tilde{m}=1882.37 \pm 11.95$ MeV for $2S$ state with $J^P=\frac{3}{2}^+$ and they are consistent with the experimental masses of $\Lambda(1520)$, $\Lambda(1690)$ and $\Lambda(1890)$, respectively, which confirm their spin-parity quantum numbers. Besides, we calculate the corresponding current coupling constants, which are utilized as inputs in the calculations of different form factors defining the widths of the states under study., Comment: 11 Pages, 6 Figures and 3 Tables

We determine the masses and residues of the ground and excited spin-$\frac {1}{2} $ baryons consist of two heavy b or c quark utilizing the QCD sum rule formalism. In the calculations, we consider the nonperturbative operators up to ten mass dimensions in order to increase the accuracy compared to the previous calculations. We report the obtained results for both the symmetric and anti-symmetric currents defining the doubly heavy baryons of the ground state (1S), first orbitally excited state (1P) and first radially excited state (2S). We compare our results with the predictions of other nonperturbative approaches as well as existing experimental data which is available only for the ground state of $ \Xi_{cc}$ channel. These predictions can help the experimental groups in their searches for all members of the doubly heavy baryons in their ground and exited states., Comment: 18 Pages, 5 Figures and 9 Tables

At the heart of medicine lies the physician-patient dialogue, where skillful history-taking paves the way for accurate diagnosis, effective management, and enduring trust. Artificial Intelligence (AI) systems capable of diagnostic dialogue could increase accessibility, consistency, and quality of care. However, approximating clinicians' expertise is an outstanding grand challenge. Here, we introduce AMIE (Articulate Medical Intelligence Explorer), a Large Language Model (LLM) based AI system optimized for diagnostic dialogue. AMIE uses a novel self-play based simulated environment with automated feedback mechanisms for scaling learning across diverse disease conditions, specialties, and contexts. We designed a framework for evaluating clinically-meaningful axes of performance including history-taking, diagnostic accuracy, management reasoning, communication skills, and empathy. We compared AMIE's performance to that of primary care physicians (PCPs) in a randomized, double-blind crossover study of text-based consultations with validated patient actors in the style of an Objective Structured Clinical Examination (OSCE). The study included 149 case scenarios from clinical providers in Canada, the UK, and India, 20 PCPs for comparison with AMIE, and evaluations by specialist physicians and patient actors. AMIE demonstrated greater diagnostic accuracy and superior performance on 28 of 32 axes according to specialist physicians and 24 of 26 axes according to patient actors. Our research has several limitations and should be interpreted with appropriate caution. Clinicians were limited to unfamiliar synchronous text-chat which permits large-scale LLM-patient interactions but is not representative of usual clinical practice. While further research is required before AMIE could be translated to real-world settings, the results represent a milestone towards conversational diagnostic AI., Comment: 46 pages, 5 figures in main text, 19 figures in appendix

The fully heavy axial-vector diquark-antidiquark structures $bb\overline{c} \overline{c}$ are explored by means of the QCD sum rule method. They are modeled as four-quark mesons $T_{\mathrm{1}}$ and $T_{\mathrm{2}}$ composed of $b^{T}C\sigma _{\mu \nu }\gamma _{5}b$, $\overline{c}\gamma ^{\nu }C \overline{c}^{T}$ and $b^{T}C\gamma _{\mu }\gamma _{5}b$, $\overline{c}C \overline{c}^{T}$ diquarks, respectively. The spectroscopic parameters of the tetraquarks $T_{\mathrm{1}}$ and $T_{\mathrm{2}}$ are determined in the context of the QCD two-point sum rule method. Results obtained for masses of these states $m_{1} =(12715\pm 86)~\mathrm{MeV}$ and $m_{2}=(13383\pm 92)~ \mathrm{MeV}$ are used to fix their strong decay channels. The full width $ \Gamma (T_{\mathrm{1}})$ of the diquark-antidiquark state $T_{\mathrm{1}}$ is estimated by considering the processes $T_{\mathrm{1}} \to B_{c}^{-}B_{c}^{\ast -}$ and $T_{\mathrm{1}} \to B_{c}^{\ast -}B_{c}^{\ast -} $. The decays to mesons $B_{c}^{-}B_{c}^{\ast -}$, $B_{c}^{-}(2S)B_{c}^{ \ast -}$ and $B_{c}^{\ast -}B_{c}^{\ast -}$ are employed to evaluate $\Gamma (T_{\mathrm{2}})$. Results obtained for the widths $\Gamma (T_{\mathrm{1} })=(44.3\pm 8.8)~\mathrm{MeV}$ and $\Gamma (T_{\mathrm{2}})=(82.5\pm 13.7)~ \mathrm{MeV}$ of these tetraquarks in conjunction with their masses are useful for future experimental studies of fully heavy resonances., Comment: 9 Pages and 5 Figures

We conduct a systematic study of the electromagnetic properties of multiquark systems with undetermined internal structures. Motivated by the recent observation of the $T_{cc}^+$ state, we apply the light-cone version of the QCD sum rule method to extract the magnetic dipole moments of several possible doubly-charmed vector tetraquark states. When analyzing the magnetic dipole moment of these states, they are modeled to have the diquark-antidiquark configurations. The magnetic dipole moments for the members are extracted as $ \mu_{T_{cc \bar{u} \bar{d}}} = 1.17^{+0.44}_{-0.32} \, \mu_N$, $ \mu_{T_{cc \bar{u} \bar{s}}} = 1.35^{+0.50}_{-0.37} \, \mu_N$, $ \mu_{T_{cc \bar{d} \bar{s}}} = -2.69^{+1.02}_{-0.75} \, \mu_N$, $ \mu_{T_{cc \bar{u} \bar{u}}} = 1.33^{+0.56}_{-0.40} \, \mu_N$, $ \mu_{T_{cc \bar{d} \bar{d}}} = 1.41^{+0.57}_{-0.43} \, \mu_N$ and $ \mu_{T_{cc \bar{s} \bar{s}}} = 1.44^{+0.53}_{-0.41} \, \mu_N$. Comparing the results obtained for the magnetic dipole moments of the $T_{cc \bar{u} \bar{d}}$ state with the $T_{cc \bar{u} \bar{s}}$ state, the $U$-symmetry is seen to be broken at about $\%15$, while for the $T_{cc \bar{d} \bar{d}}$ and $T_{cc \bar{s} \bar{s}}$ states, this symmetry is minimally broken. The obtained results may be useful to determine the true nature of these new interesting states., Comment: 13 Pages, 1 Figure and 1 Table

We introduced a new framework to detect perceptual bugs using a Long Short-Term Memory (LSTM) network, which detects bugs in video games as anomalies. The detected buggy frames are then clustered to determine the category of the occurred bug. The framework was evaluated on two First Person Shooter (FPS) games. Results show the effectiveness of the framework., Comment: IEEE Conference on Games 2023

This paper presents a mixed-computation neural network processing approach for edge applications that incorporates low-precision (low-width) Posit and low-precision fixed point (FixP) number systems. This mixed-computation approach employs 4-bit Posit (Posit4), which has higher precision around zero, for representing weights with high sensitivity, while it uses 4-bit FixP (FixP4) for representing other weights. A heuristic for analyzing the importance and the quantization error of the weights is presented to assign the proper number system to different weights. Additionally, a gradient approximation for Posit representation is introduced to improve the quality of weight updates in the backpropagation process. Due to the high energy consumption of the fully Posit-based computations, neural network operations are carried out in FixP or Posit/FixP. An efficient hardware implementation of a MAC operation with a first Posit operand and FixP for a second operand and accumulator is presented. The efficacy of the proposed low-precision mixed-computation approach is extensively assessed on vision and language models. The results show that, on average, the accuracy of the mixed-computation is about 1.5% higher than that of FixP with a cost of 0.19% energy overhead.