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The frequent discovery of security vulnerabilities in both open-source and proprietary software underscores the urgent need for earlier detection during the development lifecycle. Initiatives such as DARPA's Artificial Intelligence Cyber Challenge (AIxCC) aim to accelerate Automated Vulnerability Detection (AVD), seeking to address this challenge by autonomously analyzing source code to identify vulnerabilities. This paper addresses two primary research questions: (RQ1) How is current AVD research distributed across its core components? (RQ2) What key areas should future research target to bridge the gap in the practical applicability of AVD throughout software development? To answer these questions, we conduct a systematization over 79 AVD articles and 17 empirical studies, analyzing them across five core components: task formulation and granularity, input programming languages and representations, detection approaches and key solutions, evaluation metrics and datasets, and reported performance. Our systematization reveals that the narrow focus of AVD research-mainly on specific tasks and programming languages-limits its practical impact and overlooks broader areas crucial for effective, real-world vulnerability detection. We identify significant challenges, including the need for diversified problem formulations, varied detection granularities, broader language support, better dataset quality, enhanced reproducibility, and increased practical impact. Based on these findings we identify research directions that will enhance the effectiveness and applicability of AVD solutions in software security.

A localized Zeeman field, intensified at heterostructure interfaces, could play a crucial role in a broad area including spintronics and unconventional superconductors. Conventionally, the generation of a local Zeeman field is achieved through magnetic exchange coupling with a magnetic material. However, magnetic elements often introduce defects, which could weaken or destroy superconductivity. Alternatively, the coupling between a superconductor with strong spin-orbit coupling and a non-magnetic chiral material could serve as a promising approach to generate a spin active interface. In this study, we leverage an interface superconductor, namely induced superconductivity in noble metal surface states, to probe the spin active interface. Our results unveil an enhanced interface Zeeman field, which selectively closes the surface superconducting gap while preserving the bulk superconducting pairing. The chiral material, i.e. trigonal tellurium, also induces Andreev bound states (ABS) exhibiting spin polarization. The field dependence of ABS manifests a substantially enhanced interface Land\'e g-factor (g_eff ~ 12), thereby corroborating the enhanced interface Zeeman energy., Comment: 27 pages, 11 figures

The total energy of a fireball is commonly obtained from optical measurements with an assumed value for luminous efficiency. Acoustic energy measurements offer an independent means of energy estimation. Here we combine optical and acoustic methods to validate the luminous efficiency model of Borovi\v{c}ka et al. (2020). Our goal is to compare these models with acoustic measurements of meteoroid energy deposition. Employing theoretical blast scaling laws following the approach of McFadden et al. (2021), we determine explosive yields for both fireball fragmentation events and cylindrical shocks for four different bright fireballs. We model fireballs using the MetSim software (Vida et al., 2023) and find that the Borovi\v{c}ka et al. (2020) model produces agreement better than a factor of two for our three chondritic fireball case studies. The major exception is an iron meteorite-producing fireball where the luminous efficiency is an order of magnitude higher than model predictions calibrated with stony fireballs. We suggest that large disparities between optical and acoustic energies could be a signature of iron fireballs and hence useful as a discriminant of that population., Comment: Accepted for publication in Icaurs

Increasing the density of superconducting circuits requires compact components, however, superconductor-based capacitors typically perform worse as dimensions are reduced due to loss at surfaces and interfaces. Here, parallel plate capacitors composed of aluminum-contacted, crystalline silicon fins are shown to be a promising technology for use in superconducting circuits by evaluating the performance of lumped element resonators and transmon qubits. High aspect ratio Si-fin capacitors having widths below $300nm$ with an approximate total height of 3$\mu$m are fabricated using anisotropic wet etching of Si(110) substrates followed by aluminum metallization. The single-crystal Si capacitors are incorporated in lumped element resonators and transmons by shunting them with lithographically patterned aluminum inductors and conventional $Al/AlO_x/Al$ Josephson junctions respectively. Microwave characterization of these devices suggests state-of-the-art performance for superconducting parallel plate capacitors with low power internal quality factor of lumped element resonators greater than 500k and qubit $T_1$ times greater than 25$\mu$s. These results suggest that Si-Fins are a promising technology for applications that require low loss, compact, superconductor-based capacitors with minimal stray capacitance.

A mechanism is described that addresses the fundamental trade off between media producers who want to increase reach and consumers who provide attention based on the rate of utility received, and where overreach negatively impacts that rate. An optimal solution can be achieved when the media source considers the impact of overreach in a cost function used in determining the optimal distribution of content to maximize individual consumer utility and participation. The result is a Nash equilibrium between producer and consumer that is also Pareto efficient. Comparison with the literature on Recommender systems highlights the advantages of the mechanism, including identifying an optimal content volume for the consumer and improvements for optimizing with multiple objectives. A practical algorithm for generating the optimal distribution for each consumer is provided., Comment: Main Paper: 20 pages, Appendix with proofs and additional material: 26 pages. This version fixes typos

Empirical surface treatments, such as low-temperature baking (LTB) in a gaseous atmosphere or in vacuum, are important for the surface preparation of Nb superconducting radio frequency (SRF) cavities. These treatments inhomogeneously dope the first $\sim$50 nm of Nb's subsurface and are expected to impart depth-dependent characteristics to its Meissner response; however, direct evidence supporting this remains elusive, suggesting the effect is subtle. In this work, we revisit the Meissner profile data for several LTB treatments obtained from low-energy muon spin rotation (LE-$\mu$SR) experiments [A. Romanenko et al., Appl. Phys. Lett. 104, 072601 (2014) and R. M. L. McFadden et al., Phys. Rev. Appl. 19, 044018 (2023)], and search for signatures of inhomogeneous field screening. Using a generalized London expression with a recently proposed empirical model for a depth-dependent magnetic penetration depth $\lambda(z)$, we obtain improved fits to the Meissner data, revealing that the presence of a non-superconducting surface "dead layer" $d \geq 25$ nm is a strong indicator of a reduced supercurrent density at shallow subsurface depths. Our analysis supports the notion that vacuum annealing at 120 $^{\circ}$C for 48 h induces a depth-dependent Meissner response, which has consequences for Nb's ability to maintain a magnetic-flux-free state. Evidence of similar behavior from a "nitrogen infusion" treatment is less compelling. Suggestions for further investigation into the matter are provided., Comment: 7 pages, 4 figures, 1 table

Motivated by recent advancements highlighting Ta as a promising material in low-loss superconducting circuits and showing long coherence times in superconducting qubits, we have explored the effect of cryogenic temperatures on the growth of Ta and its integration in superconducting circuits. Cryogenic growth of Ta using a low temperature molecular beam epitaxy (MBE) system is found to stabilize single phase $\alpha$-Ta on several different substrates, which include Al$\mathrm{_2}$O$\mathrm{_3}$(0001), Si(001), Si(111), SiN${_x}$, and GaAs(001). The substrates are actively cooled down to cryogenic temperatures and remain < 20 K during the Ta deposition. X-ray $\theta$-2$\theta$ diffraction after warming to room temperature indicates the formation of polycrystalline $\alpha$-Ta. The 50 nm $\alpha$-Ta films grown on Al$\mathrm{_2}$O$\mathrm{_3}$(0001) at a substrate manipulator temperature of 7 K have a room temperature resistivity ($\mathrm{\rho _{300 K}}$) of 13.4 $\mathrm{\mu \Omega}$cm, a residual resistivity ratio (RRR) of 17.3 and a superconducting transition temperature (T$_C$) of 4.14 K, which are comparable to bulk values. In addition, atomic force microscopy (AFM) indicates that the film grown at 7 K with an RMS roughness of 0.45 nm was significantly smoother than the one grown at room temperature. Similar properties are found for films grown on other substrates. Results for films grown at higher substrate manipulator temperatures show higher $\mathrm{\rho _{300 K}}$, lower RRR and Tc, and increased $\beta$-Ta content. Coplanar waveguide resonators with a gap width of 3 $\mathrm{\mu}$m fabricated from cryogenically grown Ta on Si(111) and Al$\mathrm{_2}$O$\mathrm{_3}$(0001) show low power Q$_i$ of 1.9 million and 0.7 million, respectively, indicating polycrystalline $\alpha$-Ta films may be promising for superconducting qubit applications even though they are not fully epitaxial.

We report direct measurements of the magnetic field screening at the limits of the Meissner phase for two superconducting Nb samples. The samples are processed with two different surface treatments that have been developed for superconducting radio-frequency cavity applications -- a "baseline" treatment and an oxygen-doping ("O-doping") treatment. The measurements show: 1) that the screening length is significantly longer in the "O-doping" sample compared to the "baseline" sample; 2) that the screening length near the limits of the Meissner phase increases with applied field; 3) the evolution of the screening profile as the material transitions from the Meissner phase to the mixed phase; and 4) a demonstration of the absence of any screening profile for the highest applied field, indicative of the full flux entering the sample. Measurements are performed utilizing the $\beta$-detected nuclear magnetic resonance ($\beta$-NMR) technique that allows depth resolved studies of the local magnetic field within the first 100 nm of the surface. The study takes advantage of the $\beta$-SRF beamline, a new facility at TRIUMF, Canada, where field levels up to 200 mT are available parallel to the sample surface to replicate radio frequency (RF) fields near the Meissner breakdown limits of Nb.

Superconducting Nb thin films have recently attracted significant attention due to their utility for quantum information technologies. In the processing of Nb thin films, fluoride-based chemical etchants are commonly used to remove surface oxides that are known to affect superconducting quantum devices adversely. However, these same etchants can also introduce hydrogen to form Nb hydrides, potentially negatively impacting microwave loss performance. Here, we present comprehensive materials characterization of Nb hydrides formed in Nb thin films as a function of fluoride chemical treatments. In particular, secondary-ion mass spectrometry, X-ray scattering, and transmission electron microscopy reveal the spatial distribution and phase transformation of Nb hydrides. The rate of hydride formation is determined by the fluoride solution acidity and the etch rate of Nb2O5, which acts as a diffusion barrier for hydrogen into Nb. The resulting Nb hydrides are detrimental to Nb superconducting properties and lead to increased power-independent microwave loss in coplanar waveguide resonators. However, Nb hydrides do not correlate with two-level system loss or device aging mechanisms. Overall, this work provides insight into the formation of Nb hydrides and their role in microwave loss, thus guiding ongoing efforts to maximize coherence time in superconducting quantum devices.

We report measurements of the first-flux-penetration field in surface-treated and coated Nb samples using muon spin rotation ($\mu$SR). Using thin Ag foils as energy moderators for the implanted muon spin-probes, we "profile" the vortex penetration field $\mu_{0} H_{\mathrm{vp}}$ at sub-surface depths on the order of $\sim 10$ $\mathrm{\mu}$m to $\sim 100$ $\mathrm{\mu}$m. In a coated sample [Nb$_3$Sn(2 $\mathrm{\mu}$m)/Nb], we find that $\mu_{0} H_{\mathrm{vp}}$ is depth-independent with a value of 234.5(35) mT, consistent with Nb's metastable superheating field and suggestive of surface energy barrier for flux penetration. Conversely, in a surface-treated sample [Nb baked in vacuum at 120 $^{\circ}$C for 48 h], vortex penetration onsets close to pure Nb's lower critical field $\mu_{0}H_\mathrm{c1} \approx 170$ mT, but increases with increasing implantation depth, consistent with flux-pinning localized at the surface. The implication of these results for technical applications of superconducting Nb, such as superconducting radio frequency (SRF) cavities, is discussed., Comment: 10 pages, 6 figures

Machine learning (ML) plays a pivotal role in detecting malicious software. Despite the high F1-scores reported in numerous studies reaching upwards of 0.99, the issue is not completely solved. Malware detectors often experience performance decay due to constantly evolving operating systems and attack methods, which can render previously learned knowledge insufficient for accurate decision-making on new inputs. This paper argues that commonly reported results are inflated due to two pervasive sources of experimental bias in the detection task: spatial bias caused by data distributions that are not representative of a real-world deployment; and temporal bias caused by incorrect time splits of data, leading to unrealistic configurations. To address these biases, we introduce a set of constraints for fair experiment design, and propose a new metric, AUT, for classifier robustness in real-world settings. We additionally propose an algorithm designed to tune training data to enhance classifier performance. Finally, we present TESSERACT, an open-source framework for realistic classifier comparison. Our evaluation encompasses both traditional ML and deep learning methods, examining published works on an extensive Android dataset with 259,230 samples over a five-year span. Additionally, we conduct case studies in the Windows PE and PDF domains. Our findings identify the existence of biases in previous studies and reveal that significant performance enhancements are possible through appropriate, periodic tuning. We explore how mitigation strategies may support in achieving a more stable and better performance over time by employing multiple strategies to delay performance decay., Comment: 35 pages, submitted to ACM ToPS, under reviewing. arXiv admin note: text overlap with arXiv:1807.07838

We formulate a renormalisation procedure for IR divergences of tree-level in-in late-time de Sitter correlators. These divergences are due to the infinite volume of spacetime and are analogous to the divergences that appear in AdS dealt with by holographic renormalisation. Regulating the theory using dimensional regularisation, we show that one can remove all infinities by adding local counterterms at the future boundary of dS in the Schwinger-Keldysh path integral. The counterterms amount to renormalising the late-time bulk field. We frame the discussion in terms of bulk scalar fields in dS, using tree-level correlators of massless and conformal scalars for illustration. The relation to AdS via analytic continuation is discussed, and we show that different versions of the analytic continuation appearing in the literature are equivalent to each other. In AdS, one needs to add counterterms that are related to conformal anomalies, and also to renormalise the source part of the bulk field. The analytic continuation to dS projects out the traditional AdS counterterms, and links the renormalisation of the sources to the renormalisation of the late-time bulk field. We use these results to establish holographic formulae that relate tree-level dS in-in correlators to CFT correlators at up to four points, and we provide two proofs: one using the connection between the dS wavefunction and the partition function of the dual CFT, and a second by direct evaluation of the in-in correlators using the Schwinger-Keldysh formalism. The renormalisation of the bulk IR divergences is mapped by these formulae to UV renormalisation of the dual CFT via local counterterms, providing structural support for a possible duality. We also recast the regulated holographic formulae in terms of the AdS amplitudes of shadow fields, but show that this relation breaks down when renormalisation is required., Comment: 88 pages; v2: published version

Both Feynman integrals and holographic Witten diagrams can be represented as multivariable hypergeometric functions of a class studied by Gel'fand, Kapranov & Zelevinsky known as GKZ or $\mathcal{A}$-hypergeometric functions. Among other advantages, this formalism enables the systematic construction of highly non-trivial weight-shifting operators known as 'creation' operators. We derive these operators from a physics perspective, highlighting their close relation to the spectral singularities of the integral as encoded by the facets of the Newton polytope. Many examples for Feynman and Witten diagrams are given, including novel weight-shifting operators for holographic contact diagrams. These in turn allow momentum-space exchange diagrams of different operator dimensions to be related while keeping the spacetime dimension fixed. In contrast to previous constructions, only non-derivative vertices are involved., Comment: 73 pp; 15 figs

Probing small main-belt asteroids provides insight into their formation and evolution through multiple dynamical and collisional processes. These asteroids also overlap in size with the potentially hazardous near-earth object population and supply the majority of these objects. The Lucy mission will provide an opportunity for study of a small main-belt asteroid, (152830) Dinkinesh. The spacecraft will perform a flyby of this object on November 1, 2023, in preparation for its mission to the Jupiter Trojan asteroids. We employed aperture photometry on stacked frames of Dinkinesh obtained by the Wide-field-Infrared Survey Explorer and performed thermal modeling on a detection at 12 $\mu$m to compute diameter and albedo values. Through this method, we determined Dinkinesh has an effective spherical diameter of $0.76^{+0.11}_{-0.21}$ km and a visual geometric albedo of $0.27^{+0.25}_{-0.06}$ at the 16th and 84th percentiles. This albedo is consistent with typical stony (S-type) asteroids., Comment: Submitted to Astrophysical Journal Letters

Compensating for slip and skid is crucial for mobile robots navigating outdoor terrains. In these challenging environments, slipping and skidding introduce uncertainties into trajectory tracking systems, potentially compromising the safety of the vehicle. Despite research in this field, having a real-world feasible online slip and skid compensation remains challenging due to the complexity of wheel-terrain interaction in outdoor environments. This paper proposes a novel trajectory tracking technique featuring real-world feasible online slip and skid compensation at the vehicle level for skid-steering mobile robots operating outdoors. The approach employs sliding-mode control to design a robust trajectory tracking system, accounting for the inherent uncertainties in this type of robot. To estimate the robot's slipping and undesired skidding and compensate for them in real-time, two previously developed deep learning models are integrated into the control-feedback loop. The main advantages of the proposed technique are that it (1) considers two slip-related parameters for the entire robot, as opposed to the conventional approach involving two slip components for each wheel along with the robot's skidding, and (2) has an online real-world feasible slip and skid compensator, reducing the tracking errors in unforeseen environments. Experimental results demonstrate a significant improvement, enhancing the trajectory tracking system's performance by over 27%.