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Programmers spend a significant amount of time reading code during the software development process. This trend is amplified by the emergence of large language models (LLMs) that automatically generate code. However, little is known about the readability of the LLM-generated code and whether it is still important from practitioners' perspectives in this new era. In this paper, we conduct a survey to explore the practitioners' perspectives on code readability in the age of LLMs and investigate the readability of our LLM-based software development agents framework, HULA, by comparing its generated code with human-written code in real-world scenarios. Overall, the findings underscore that (1) readability remains a critical aspect of software development; (2) the readability of our LLM-generated code is comparable to human-written code, fostering the establishment of appropriate trust and driving the broad adoption of our LLM-powered software development platform., Comment: 6 pages, 2 figures, 5 tables, under review

JWST has enabled the detection of the UV continuum of galaxies at z>10, evidencing a population of extremely blue, potentially dust-free galaxies. Interpreting the UV spectra of galaxies as they redden is complicated by the well-known degeneracy between stellar ages, dust, and nebular continuum. The main goal of this paper is to develop a theoretical model for the relationship between galaxy UV slopes, bursty star formation histories, dust evolution, and the contribution from nebular regions. We accomplish this via cosmological zoom-in simulations, and in specific, build a layered model where we simulate the UV slopes of galaxies with increasingly complex physics. Our main results follow. (i) Unattenuated stellar populations with no nebular emission exhibit a diverse range of intrinsic UV slopes, with values ranging from beta ~ -3 --> -2.2 due to long delays between bursts. This is manifested by an inverse correlation between the intrinsic UV slope and sSFR for early galaxies such that higher sSFR corresponds to bluer UV slopes. (ii) When including dust, our model galaxies demonstrate a rapid rise in dust obscuration between z ~ 8-10. This increase in dust mass is due to high grain-grain shattering rates, and enhanced growth per unit dust mass in very small grains, resulting in UV-detected galaxies at z ~ 12 descending into ALMA-detectable galaxies by z ~ 6. The rapid rise in dust content at z ~ 8-10 leads to a systematic reddening of the UV slopes during this redshift range. (iii) The inclusion of nebular continuum reddens the UV slope by a median factor Delta beta ~ 0.2-0.4. However, when including nebular continuum, our highest redshift galaxies (z~12) are insufficiently blue compared to observations; this may imply an evolving escape fraction from HII regions with redshift., Comment: Submitted to ApJ; comments welcome

Large-scale magnetic fields are observed off the midplanes of disk galaxies, indicating that they harbour magnetised halos. These halos are crucial to studies of galaxy evolution, galactic-scale outflows, and feedback from star formation activity. Identifying the magnetised halo of the Milky Way is challenging because of the potential contamination from foreground emission arising in local spiral arms. Additionally, it is unclear how our magnetic halo is influenced by recently revealed large-scale structures such as the X-ray emitting eROSITA Bubbles, which, according to previous simulations, might be transient structures powered by the Galactic Center or the Galaxy's star-forming ring. Here we report the identification of several kpc-scale magnetised structures based on their polarized radio emission and their gamma-ray counterparts, which can be interpreted as the radiation of relativistic electrons. These non-thermal structures extend far above and below the Galactic plane and are spatially coincident with the thermal X-ray emission from the eROSITA Bubbles. The morphological consistency of these structures suggests a common origin, which can be sustained by Galactic outflows driven by the active star-forming regions located at 3-5 kpc from the Galactic Centre. These results reveal how X-ray-emitting and magnetised halos of spiral galaxies can be related to intense star formation activities and suggest that the X-shaped coherent magnetic structures observed in their halos can stem from galaxy outflows., Comment: Initially submitted on March 2nd, 2024

A muon collider represents a promising candidate for the next generation of particle physics experiments after the expected end of LHC operations in the early 2040s. Rare or hard-to-detect processes at the LHC, such as the production of multiple gauge bosons, become accessible at a TeV muon collider. We present here the prospects of detecting quantum entanglement and the violation of Bell inequalities in H to ZZ to 4l events at a potential future muon collider. We show that the spin density matrix of the Z boson pairs can be reconstructed using the kinematics of the charged leptons from the Z boson decays. Once the density matrix is determined, it is straightforward to obtain the expectation values of various Bell operators and test the quantum entanglement between the Z boson pair. Through a detailed study based on Monte-Carlo simulation, we show that the generalized CGLMP inequality can be maximally violated, and testing Bell inequalities could be established with high significance., Comment: 11 pages, 3 figures, updated version

In this study, we assess the effectiveness and robustness of the recently proposed $T'$-expansion scheme for expanding the equation of state of strongly interacting matter to finite density, by comparing its performance relative to the conventional Taylor expansion method in various effective QCD models. We use baryon number density and its susceptibilities to calculate the expansion coefficients in the $T'$-expansion scheme with and without the Stefan-Boltzmann limit correction. Our methodology involves comparing truncation orders to exact solutions to assess the scheme's accuracy. We utilize Ideal, Excluded Volume, and van der Waals formulations of the Hadron Resonance Gas (HRG) model at low temperatures, and the Cluster Expansion Model at higher temperatures. Our findings indicate that the $T'$-expansion scheme offers superior convergence properties near and above the chiral crossover temperature, where the chiral-criticality-inspired scaling $(\partial/ \partial T)_{\mu_B} \sim (\partial^2/\partial \mu_B^2)_T$ holds. However, it shows limited improvement in the HRG models, indicating that it may not be the most suitable choice for describing the hadronic phase., Comment: 11 pages, 4 figures

Attosecond science offers unprecedented precision in probing the initial moments of chemical reactions, revealing the dynamics of molecular electrons that shape reaction pathways. A fundamental question emerges: what role, if any, do quantum coherences between molecular electron states play in photochemical reactions? Answering this question necessitates quantum tomography: the determination of the electronic density matrix from experimental data, where the off-diagonal elements represent these coherences. The Maximal Entropy (MaxEnt) based Quantum State Tomography (QST) approach offers unique advantages in studying molecular dynamics, particularly with partial tomographic data. Here, we explore the application of MaxEnt-based QST on photoexcited ammonia, necessitating the operator form of observables specific to the performed measurements. We present two methodologies for constructing these operators: one leveraging Molecular Angular Distribution Moments (MADMs) which accurately capture the orientation-dependent vibronic dynamics of molecules; and another utilizing Angular Momentum Coherence Operators to construct measurement operators for the full rovibronic density matrix in the symmetric top basis. A key revelation of our study is the direct link between Lagrange multipliers in the MaxEnt formalism and the unique set of MADMs. Furthermore, we achieve a groundbreaking milestone by constructing, for the first time, the entanglement entropy of the electronic subsystem: a metric that was previously inaccessible. The entropy vividly reveals and quantifies the effects of coupling between the excited electron and nuclear degrees of freedom. Consequently, our findings open new avenues for research in ultrafast molecular spectroscopy within the broader domain of quantum information science., Comment: 18 pages, 4 figures

The X$_2$MH$_6$ family, consisting of an electropositive cation X and a main group metal M octahedrally coordinated by hydrogen, has been predicted to hold promise for high-temperature conventional superconductivity. Herein, we analyze the electronic structure of two members of this family, Mg$_2$IrH$_6$ and Ca$_2$IrH$_6$, showing why the former may possess superconducting properties rivaling those of the cuprates, whereas the latter does not. Within Mg$_2$IrH$_6$ the vibrations of the IrH$_6^{4-}$ anions are key for the superconducting mechanism, and they induce coupling in the $e_g^*$ set, which are antibonding between the H 1$s$ and the Ir $d_{x^2-y^2}$ or $d_{z^2}$ orbitals. Because calcium possesses low-lying d-orbitals, $e_g^* \rightarrow$ Ca $d$ back-donation is preferred, quenching the superconductivity. Our analysis explains why high critical temperatures were only predicted for second or third row X metal atoms, and may hold implications for superconductivity in other systems where the antibonding anionic states are filled.

For fast-tracking climate change response, green hydrogen is key for achieving greenhouse gas neutral energy systems. Especially Sub-Saharan Africa can benefit from it enabling an increased access to clean energy through utilizing its beneficial conditions for renewable energies. However, developing green hydrogen strategies for Sub-Saharan Africa requires highly detailed and consistent information ranging from technical, environmental, economic, and social dimensions, which is currently lacking in literature. Therefore, this paper provides a comprehensive novel approach embedding the required range of disciplines to analyze green hydrogen cost-potentials in Sub-Saharan Africa. This approach stretches from a dedicated land eligibility based on local preferences, a location specific renewable energy simulation, locally derived sustainable groundwater limitations under climate change, an optimization of local hydrogen energy systems, and a socio-economic indicator-based impact analysis. The capability of the approach is shown for case study regions in Sub-Saharan Africa highlighting the need for a unified, interdisciplinary approach.

We study the effect of geometric frustration on dilational mechanical metamaterial membranes. While shape frustrated elastic plates can only accommodate non-zero Gaussian curvature up to size scales that ultimately vanish with their elastic thickness, we show that frustrated {\it metamembranes} accumulate hyperbolic curvatures up to mesoscopic length scales that are ultimately independent of the size of their microscopic constituents. A continuum elastic theory and discrete numerical model describe the size-dependent shape and internal stresses of axisymmetric, trumpet-like frustrated metamembranes, revealing a non-trivial crossover to a much weaker power-law growth in elastic strain energy with size than in frustrated elastic membranes. We study a consequence of this for the self-limiting assembly thermodynamics of frustrated trumpets, showing a several-fold increase the size range of self-limitation of metamembranes relative to elastic membranes., Comment: 6 pages, 3 figures, supplementary text appendices

The design and development of power electronics converters pose a multitude of challenges. The evaluation of power electronics converters, particularly when operating at high power levels, presents a significant task, offering designers a deeper understanding of the functionality. Several methodologies have been devised to conduct hardware-in-the-loop (HIL) tests, which are classified into two main categories: controller hardware-in-the-loop (CHIL) and power hardware-in-the-loop (PHIL) tests. This paper explores the advantages and drawbacks of these two approaches and introduces a straightforward and cost-effective CHIL method for initial proof of concept and risk-free controller training. This method is based on the interaction between MATLAB/Simulink and Python. To assess the operation of the proposed system, a modeled battery pack (96S1P) is charged using a modeled battery charger converter, employing a non-linear PID controller. In this scenario, the controller benefits from the CC-CV technique for charging the battery pack. The results are presented in the final section., Comment: 2024 IEEE Transportation Electrification Conference & Expo (ITEC 2024) (5 pages, 11 figures)

With the advent of smart grid (SG) systems, electricity networks have been able to ensure greater efficiency and utility by interconnecting their grids through cloud-based technology. As SGs become increasingly complex, a wide range of security challenges arise, threatening the grid's reliability, safety, efficiency, and stability. The security challenges include the potential exposure of personal data due to hackers intercepting the communications between the SG infrastructure and the smart meters. Security awareness plays a vital role in addressing some of these challenges. However, the traditional training programs are no longer efficient for instilling information security culture in organisations or from an individual user perspective. Gamification is a new concept in the field of information security awareness training (SAT) campaigns that can be introduced to fill in this gap by providing employees with a means of practising and learning about many security flaws and risks that exist within the organisation. Thus, this paper examines the effectiveness of gamification in promoting security awareness among smart meter components for smart grid users/operators. A gaming application is developed as part of the study with the aim of training and evaluating the results through three difficulty levels of questionnaires. Furthermore, the results are evaluated for the three difficulty levels as well as the overall flag captured. It can be demonstrated that the scores of participants in the three levels have improved by 40%, 35% and 29%, respectively. This reflects the awareness of learning within our system., Comment: 18 pages, 15 figures and 2 tables

Adapting language models (LMs) to novel domains is often achieved through fine-tuning a pre-trained LM (PLM) on domain-specific data. Fine-tuning introduces new knowledge into an LM, enabling it to comprehend and efficiently perform a target domain task. Fine-tuning can however be inadvertently insensitive if it ignores the wide array of disparities (e.g in word meaning) between source and target domains. For instance, words such as chronic and pressure may be treated lightly in social conversations, however, clinically, these words are usually an expression of concern. To address insensitive fine-tuning, we propose Mask Specific Language Modeling (MSLM), an approach that efficiently acquires target domain knowledge by appropriately weighting the importance of domain-specific terms (DS-terms) during fine-tuning. MSLM jointly masks DS-terms and generic words, then learns mask-specific losses by ensuring LMs incur larger penalties for inaccurately predicting DS-terms compared to generic words. Results of our analysis show that MSLM improves LMs sensitivity and detection of DS-terms. We empirically show that an optimal masking rate not only depends on the LM, but also on the dataset and the length of sequences. Our proposed masking strategy outperforms advanced masking strategies such as span- and PMI-based masking., Comment: Paper alrerady accepted for publishing by the NAACL 2024 conference (main conference paper)

We present a novel construction of the QCD equation of state (EoS) at finite baryon density. Our work combines a recently proposed resummation scheme for lattice QCD results with the universal critical behavior at the QCD critical point. This allows us to obtain a family of equations of state in the range $0 \leq \mu_B \leq 700$ MeV and 25 MeV $\leq T \leq 800$ MeV, which match lattice QCD results near $\mu_B=0$ while featuring a critical point in the 3D Ising model universality class. The position of the critical point can be chosen within the range accessible to beam-energy scan heavy-ion collision experiments. The strength of the singularity and the shape of the critical region are parameterized using a standard parameter set. We impose stability and causality constraints and discuss the available ranges of critical point parameter choices, finding that they extend beyond earlier parametric QCD EoS proposals. We present thermodynamic observables, including baryon density, pressure, entropy density, energy density, baryon susceptibility and speed of sound, that cover a wide range in the QCD phase diagram relevant for experimental exploration., Comment: 16 pages, 18 figures

The Modulation Transfer Function (MTF) is an important image quality metric typically used in the automotive domain. However, despite the fact that optical quality has an impact on the performance of computer vision in vehicle automation, for many public datasets, this metric is unknown. Additionally, wide field-of-view (FOV) cameras have become increasingly popular, particularly for low-speed vehicle automation applications. To investigate image quality in datasets, this paper proposes an adaptation of the Natural Scenes Spatial Frequency Response (NS-SFR) algorithm to suit cameras with a wide field-of-view., Comment: Accepted for publication in the Electronic Imagine Autonomous Vehicles and Machines (EI-AVM) Conference 2024

The Internet of Things (IoT) technology uses small and cost-effective sensors for various applications, such as Industrial IoT. However, these sensor nodes are powered by fixed-size batteries, which creates a trade-off between network performance and long-term sustainability. Moreover, some applications require the network to provide a certain level of service, such as a lower delay for critical data, while ensuring the operational reliability of sensor nodes. To address this energy challenge, external energy harvesting sources, such as solar and wind, offer promising and eco-friendly solutions. However, the available energy from a single energy source is insufficient to meet these requirements. This drives the utilization of a hybrid energy harvesting approach, such as the integration of solar and wind energy harvesters, to increase the amount of harvested energy. Nevertheless, to fully utilize the available energy, which is dynamic in nature, the sensor node must adapt its operation to ensure sustainable operation and enhanced network performance. Therefore, this paper proposes a hybrid energy harvesting-based energy neutral operation (ENO) medium access control (MAC) protocol, called HENO-MAC, that allows the receiver node to harvest energy from the solar-wind harvesters and adapt its duty cycle accordingly. The performance of the proposed HENO-MAC was evaluated using the latest realistic solar and wind data for two consecutive days in GreenCastalia. The simulation results demonstrate that the duty cycle mechanism of HENO-MAC effectively utilizes the harvested energy to achieve ENO and uses the available energy resources efficiently to reduce the packet delay for all packets and the highest priority packet by up to 28.5% and 27.3%, respectively, when compared with other existing MAC protocols., Comment: This paper has been accepted for presentation at the IEEE Wireless Communications and Networking Conference (WCNC) 2024

The BEST Collaboration equation of state combining lattice data with the 3D Ising critical point encounters limitations due to the truncated Taylor expansion up to $\frac{\mu_B}{T} \sim 2.5$. This truncation consequently restricts its applicability at high densities. Through a resummation scheme, the lattice results have been extended to $\frac{\mu_B}{T} = 3.5$. In this article, we amalgamate these ideas with the 3D-Ising model, yielding a family of equations of state valid up to $\mu_B=700 \text{MeV}$ with the correct critical behavior. Our equations of state feature tunable parameters, providing a stable and causal framework-a crucial tool for hydrodynamics simulations., Comment: 4 pages, 2 figures, Contribution to Quark Matter2023 (Houston, TX, 3-9 Sep. 2023)

The complexity and scale of IT systems are increasing dramatically, posing many challenges to real-world anomaly detection. Deep learning anomaly detection has emerged, aiming at feature learning and anomaly scoring, which has gained tremendous success. However, little work has been done on the thresholding problem despite it being a critical factor for the effectiveness of anomaly detection. In this paper, we model thresholding in anomaly detection as a Markov Decision Process and propose an agent-based dynamic thresholding (ADT) framework based on a deep Q-network. The proposed method can be integrated into many systems that require dynamic thresholding. An auto-encoder is utilized in this study to obtain feature representations and produce anomaly scores for complex input data. ADT can adjust thresholds adaptively by utilizing the anomaly scores from the auto-encoder and significantly improve anomaly detection performance. The properties of ADT are studied through experiments on three real-world datasets and compared with benchmarks, hence demonstrating its thresholding capability, data-efficient learning, stability, and robustness. Our study validates the effectiveness of reinforcement learning in optimal thresholding control in anomaly detection.