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We present NodeOP, a novel framework designed to optimize the management of General Node Operators in decentralized networks. By integrating Agent-Based Modeling (ABM) with a Tendermint Byzantine Fault Tolerance (BFT)-based consensus mechanism, NodeOP addresses key challenges in task allocation, consensus formation, and system stability. Through rigorous mathematical modeling and formal optimization, NodeOP ensures stable equilibrium in node task distribution. We validate the framework via convergence analysis and performance metrics such as transaction throughput, system latency, and fault tolerance. We further demonstrate NodeOP's practical utility through two use cases: decentralized sequencer management in Layer 2 networks and off-chain payment validation. These examples underscore how NodeOP enhances validation efficiency and unlocks new revenue opportunities in large-scale decentralized environments. Our results position NodeOP as a scalable and flexible solution, significantly improving operational efficiency and economic sustainability in decentralized systems.

The growing reproducibility crisis in machine learning has brought forward a need for careful examination of research findings. This paper investigates the claims made by Lei et al. (2023) regarding their proposed method, LICO, for enhancing post-hoc interpretability techniques and improving image classification performance. LICO leverages natural language supervision from a vision-language model to enrich feature representations and guide the learning process. We conduct a comprehensive reproducibility study, employing (Wide) ResNets and established interpretability methods like Grad-CAM and RISE. We were mostly unable to reproduce the authors' results. In particular, we did not find that LICO consistently led to improved classification performance or improvements in quantitative and qualitative measures of interpretability. Thus, our findings highlight the importance of rigorous evaluation and transparent reporting in interpretability research., Comment: 15 pages, 2 figures, Machine Learning Reproducibility Challenge 2024

The ISO standard Property Graph model has become increasingly popular for representing complex, interconnected data. However, it lacks native support for querying metadata and reification, which limits its abilities to deal with the demands of modern applications. We introduce the vision of Meta-Property Graphs, a backwards compatible extension of the property graph model addressing these limitations. Our approach enables first-class treatment of labels and properties as queryable objects and supports reification of substructures in a graph. We propose MetaGPML, a backwards compatible extension of the Graph Pattern Matching Language forming the core of the ISO standard GQL, to query these enhanced graphs. We demonstrate how these foundations pave the way for advanced data analytics and governance tasks that are challenging or impossible with current property graph systems.

We investigated two consecutive solar eruption events in the solar active region (AR) 12994 at the solar eastern limb on 2022 April 15. We found that the flare loops formed by the first eruption were involved in the second eruption. During the initial stage of the second flare, the middle part of these flare loops (E-loops) erupted outward along with the flux ropes below, while the parts of the flare loops (I-loops1 and I-loops2) on either side of the E-loops first rose and then contracted. Approximately 1 hour after the eruption, the heights of I-loops1 and I-loops2 decreased by 9 Mm and 45 Mm, respectively, compared to before the eruption. Their maximum descent velocities were 30 km/s and 130 km/s, respectively. The differential emission measure (DEM) results indicate that the plasma above I-loops1 and I-loops2 began to be heated about 23 minutes and 44 minutes after the start of the second flare, respectively. Within 20 minutes, the plasma temperature in these regions increased from ~3 MK to 6 MK. We proposed an adiabatic heating mechanism that magnetic energy would be converted into thermal and kinetic energy when the pre-stretched loops contract. Our calculations show that the magnetic energy required to heat the two high-temperature regions are 10^29-10^30 erg, which correspond to a loss of field strength of 2-3 G., Comment: The paper has been accepted for publication in the ApJ

Empowering resource-limited robots to execute computationally intensive tasks such as locomotion and manipulation is challenging. This project provides a comprehensive design space exploration to determine optimal hardware computation architectures suitable for model-based control algorithms. We profile and optimize representative architectural designs across general-purpose scalar, vector processors, and specialized accelerators. Specifically, we compare CPUs, vector machines, and domain-specialized accelerators with kernel-level benchmarks and end-to-end representative robotic workloads. Our exploration provides a quantitative performance, area, and utilization comparison and analyzes the trade-offs between these representative distinct architectural designs. We demonstrate that architectural modifications, software, and system optimization can alleviate bottlenecks and enhance utilization. Finally, we propose a code generation flow to simplify the engineering work for mapping robotic workloads to specialized architectures., Comment: This submission has been withdrawn following further internal review and discussions with collaborators, as it was determined that the current version does not meet our intended standards, and will not be updated further. This decision aligns with internal changes and agreements that were finalized post-submission

Jupiter's Great Red Spot (GRS) was mapped by the James Webb Space Telescope (JWST)/Mid-Infrared Instrument (4.9-27.9 micron) in July and August 2022. These observations took place alongside a suite of visual and infrared observations from; Hubble, JWST/NIRCam, Very Large Telescope/VISIR and amateur observers which provided both spatial and temporal context across the jovian disc. The stratospheric temperature structure retrieved using the NEMESIS software revealed a series of hot-spots above the GRS. These could be the consequence of GRS-induced wave activity. In the troposphere, the temperature structure was used to derive the thermal wind structure of the GRS vortex. These winds were only consistent with the independently determined wind field by JWST/NIRCam at 240 mbar if the altitude of the Hubble-derived winds were located around 1,200 mbar, considerably deeper than previously assumed. No enhancement in ammonia was found within the GRS but a link between elevated aerosol and phosphine abundances was observed within this region. North-south asymmetries were observed in the retrieved temperature, ammonia, phosphine and aerosol structure, consistent with the GRS tilting in the north-south direction. Finally, a small storm was captured north-west of the GRS that displayed a considerable excess in retrieved phosphine abundance, suggestive of vigorous convection. Despite this, no ammonia ice was detected in this region. The novelty of JWST required us to develop custom-made software to resolve challenges in calibration of the data. This involved the derivation of the "FLT-5" wavelength calibration solution that has subsequently been integrated into the standard calibration pipeline., Comment: 53 pages, 19 figures, 4 tables

The Check tools automate formal memory consistency model and security verification of processors by analyzing abstract models of microarchitectures, called $\mu$SPEC models. Despite the efficacy of this approach, a verification gap between $\mu$SPEC models, which must be manually written, and RTL limits the Check tools' broad adoption. Our prior work, called RTL2$\mu$SPEC, narrows this gap by automatically synthesizing formally verified $\mu$SPEC models from SystemVerilog implementations of simple processors. But, RTL2$\mu$SPEC assumes input designs where an instruction (e.g., a load) cannot exhibit more than one microarchitectural execution path ($\mu$PATH, e.g., a cache hit or miss path) -- its single-execution-path assumption. In this paper, we first propose an automated approach and tool, called RTL2M$\mu$PATH, that resolves RTL2$\mu$SPEC's single-execution-path assumption. Given a SystemVerilog processor design, instruction encodings, and modest design metadata, RTL2M$\mu$PATH finds a complete set of formally verified $\mu$PATHs for each instruction. Next, we make an important observation: an instruction that can exhibit more than one $\mu$PATH strongly indicates the presence of a microarchitectural side channel in the input design. Based on this observation, we then propose an automated approach and tool, called SynthLC, that extends RTL2M$\mu$PATH with a symbolic information flow analysis to support synthesizing a variety of formally verified leakage contracts from SystemVerilog processor designs. Leakage contracts are foundational to state-of-the-art defenses against hardware side-channel attacks. SynthLC is the first automated methodology for formally verifying hardware adherence to them., Comment: Authors' version; to appear in the Proceedings of the 57th Annual IEEE/ACM International Symposium on Microarchitecture 57th (MICRO 2024)

We describe the spectrophotometric calibration of the Mid-Infrared Instrument's (MIRI) Medium Resolution Spectrometer (MRS) aboard the James Webb Space Telescope (JWST). This calibration is complicated by a time-dependent evolution in the effective throughput of the MRS; this evolution is strongest at long wavelengths, approximately a factor of 2 at 25um over the first two years of the mission. We model and correct for this evolution through regular observations of internal calibration lamps. Pixel flatfields are constructed from observations of the infrared-bright planetary nebula NGC 7027, and photometric aperture corrections from a combination of theoretical models and observations of bright standard stars. We tie the 5--18um flux calibration to high signal/noise (S/N; ~ 600-1000) observations of the O9 V star 10 Lacertae, scaled to the average calibration factor of nine other spectrophotometric standards. We calibrate the 18--28um spectral range using a combination of observations of main belt asteroid 515 Athalia and the circumstellar disk around young stellar object SAO 206462. The photometric repeatability is stable to better than 1% in the wavelength range 5--18um, and the S/N ratio of the delivered spectra is consistent between bootstrapped measurements, pipeline estimates, and theoretical predictions. The MRS point-source calibration agrees with that of the MIRI imager to within 1% from 7 to 21um and is approximately 1% fainter than prior Spitzer observations, while the extended source calibration agrees well with prior Cassini/CIRS and Voyager/IRIS observations., Comment: 29 pages, 32 figures. Submitted to AJ

Jupiter's icy moon Ganymede has a tenuous exosphere produced by sputtering and possibly sublimation of water ice. To date, only atomic hydrogen and oxygen have been directly detected in this exosphere. Here, we present observations of Ganymede's CO$_2$ exosphere obtained with the James Webb Space Telescope. CO$_2$ gas is observed over different terrain types, mainly over those exposed to intense Jovian plasma irradiation, as well as over some bright or dark terrains. Despite warm surface temperatures, the CO$_2$ abundance over equatorial subsolar regions is low. CO$_2$ vapor has the highest abundance over the north polar cap of the leading hemisphere, reaching a surface pressure of 1 pbar. From modeling we show that the local enhancement observed near 12 h local time in this region can be explained by the presence of cold traps enabling CO$_2$ adsorption. However, whether the release mechanism in this high-latitude region is sputtering or sublimation remains unclear. The north polar cap of the leading hemisphere also has unique surface-ice properties, probably linked to the presence of the large atmospheric CO2 excess over this region. These CO2 molecules might have been initially released in the atmosphere after the radiolysis of CO$_2$ precursors, or from the sputtering of CO$_2$ embedded in the H$_2$O ice bedrock. Dark terrains (regiones), more widespread on the north versus south polar regions, possibly harbor CO$_2$ precursors. CO$_2$ molecules would then be redistributed via cold trapping on ice-rich terrains of the polar cap and be diurnally released and redeposited on these terrains. Ganymede's CO$_2$ exosphere highlights the complexity of surface-atmosphere interactions on Jupiter's icy Galilean moons., Comment: 21 pages, 21 figures, Accepted as a Letter in Astronomy and Astrophysics

Inequalities may appear in many models. They can be as simple as assuming a parameter is nonnegative, possibly a regression coefficient or a treatment effect. This paper focuses on the case that there is only one inequality and proposes a confidence interval that is particularly attractive, called the inequality-imposed confidence interval (IICI). The IICI is simple. It does not require simulations or tuning parameters. The IICI is adaptive. It reduces to the usual confidence interval (calculated by adding and subtracting the standard error times the $1 - \alpha/2$ standard normal quantile) when the inequality is sufficiently slack. When the inequality is sufficiently violated, the IICI reduces to an equality-imposed confidence interval (the usual confidence interval for the submodel where the inequality holds with equality). Also, the IICI is uniformly valid and has (weakly) shorter length than the usual confidence interval; it is never longer. The first empirical application considers a linear regression when a coefficient is known to be nonpositive. A second empirical application considers an instrumental variables regression when the endogeneity of a regressor is known to be nonnegative.

X-ray Thomson scattering (XRTS) has emerged as a powerful tool for the diagnostics of matter under extreme conditions. In principle, it gives one access to important system parameters such as the temperature, density, and ionization state, but the interpretation of the measured XRTS intensity usually relies on theoretical models and approximations. In this work, we show that it is possible to extract the Rayleigh weight -- a key property that describes the electronic localization around the ions -- directly from the experimental data without the need for any model calculations or simulations. As a practical application, we consider an experimental measurement of strongly compressed Be at the National Ignition Facility (NIF) [D\"oppner \emph{et al.}, \textit{Nature} \textbf{618}, 270-275 (2023)]. In addition to being interesting in their own right, our results will open up new avenues for diagnostics from \emph{ab initio} simulations, help to further constrain existing chemical models, and constitute a rigorous benchmark for theory and simulations.

The tuning of the Fermi level in tin telluride, a topological crystalline insulator, is essential for accessing its unique surface states and optimizing its electronic properties for applications such as spintronics and quantum computing. In this study, we demonstrate that the Fermi level in tin telluride can be effectively modulated by controlling the tin concentration during chemical vapor deposition synthesis. By introducing tin-rich conditions, we observed a blue shift in the X-ray photoelectron spectroscopy core-level peaks of both tin and tellurium, indicating an upward shift in the Fermi level. This shift is corroborated by a decrease in work function values measured via ultraviolet photoelectron spectroscopy, confirming the suppression of Sn vacancies. Our findings provide a low-cost, scalable method to achieve tunable Fermi levels in tin telluride, offering a significant advancement in the development of materials with tailored electronic properties for next-generation technological applications.

Coronal mass ejections (CMEs) are solar eruptions that involve large-scale changes to the magnetic topology of an active region. There exists a range of models for CME onset which are based on twisted or sheared magnetic field above a polarity inversion line (PIL). We present observational evidence that topological changes at PILs, in the photosphere, form a key part of CME onset, as implied by many models. In particular, we study the onset of 30 CMEs and investigate topological changes in the photosphere by calculating the magnetic winding flux, using the \texttt{ARTop} code. By matching the times and locations of winding signatures with CME observations produced by the \texttt{ALMANAC} code, we confirm that these signatures are indeed associated with CMEs. Therefore, as well as presenting evidence that changes in magnetic topology at the photosphere are a common signature of CME onset, our approach also allows for the finding of the source location of a CME within an active region., Comment: Accepted by MNRAS

Curbs -- the edge of a raised sidewalk at the point where it meets a street -- crucial in urban environments where they help delineate safe pedestrian zones, from dangerous vehicular lanes. However, curbs themselves are significant navigation hazards, particularly for people who are blind or have low vision (pBLV). The challenges faced by pBLV in detecting and properly orientating themselves for these abrupt elevation changes can lead to falls and serious injuries. Despite recent advancements in assistive technologies, the detection and early warning of curbs remains a largely unsolved challenge. This paper aims to tackle this gap by introducing a novel, multi-faceted sensory substitution approach hosted on a smart wearable; the platform leverages an RGB camera and an embedded system to capture and segment curbs in real time and provide early warning and orientation information. The system utilizes YOLO (You Only Look Once) v8 segmentation model, trained on our custom curb dataset for the camera input. The output of the system consists of adaptive auditory beeps, abstract sonification, and speech, conveying information about the relative distance and orientation of curbs. Through human-subjects experimentation, we demonstrate the effectiveness of the system as compared to the white cane. Results show that our system can provide advanced warning through a larger safety window than the cane, while offering nearly identical curb orientation information.

People with blindness and low vision (pBLV) face challenges in navigating. Mobility aids are crucial for enhancing independence and safety. This paper presents an electronic travel aid that leverages a haptic-based, higher-order sensory substitution approach called Virtual Whiskers, designed to help pBLV negotiate obstacles effectively, efficiently, and safely. Virtual Whiskers is equipped with a plurality of modular vibration units that operate independently to deliver haptic feedback to users. Virtual Whiskers features two navigation modes: open path mode and depth mode, each addressing obstacle negotiation from different perspectives. The open path mode detects and delineate a traversable area within an analyzed field of view. Then, it guides the user through to the traversable direction adaptive vibratory feedback. The depth mode assists users in negotiating obstacles by highlighting spatial areas with prominent obstacles via haptic feedback. We recruited 10 participants with blindness or low vision to participate in user testing for Virtual Whiskers. Results show that the device significantly reduces idle periods and decreases the number of cane contacts. Virtual Whiskers is a promising obstacle negotiation strategy that demonstrating great potential to assist with pBLV navigation.

Green's functions are highly useful in analyzing the dynamical behavior of polynomials in their escaping set. The aim of this paper is to construct an analogue of Green's functions for planar quasiregular mappings of degree two and constant complex dilatation. These Green's functions are dynamically natural, in that they semi-conjugate our quasiregular mappings to the real squaring map. However, they do not share the same regularity properties as Green's functions of polynomials. We use these Green's functions to investigate properties of the boundary of the escaping set and give several examples to illustrate behavior that does not occur for the dynamics of quadratic polynomials., Comment: 23 pages, 6 figures

This paper presents a study on the growing threat of "sleeper social bots," AI-driven social bots in the political landscape, created to spread disinformation and manipulate public opinion. We based the name sleeper social bots on their ability to pass as humans on social platforms, where they're embedded like political "sleeper" agents, making them harder to detect and more disruptive. To illustrate the threat these bots pose, our research team at the University of Southern California constructed a demonstration using a private Mastodon server, where ChatGPT-driven bots, programmed with distinct personalities and political viewpoints, engaged in discussions with human participants about a fictional electoral proposition. Our preliminary findings suggest these bots can convincingly pass as human users, actively participate in conversations, and effectively disseminate disinformation. Moreover, they can adapt their arguments based on the responses of human interlocutors, showcasing their dynamic and persuasive capabilities. College students participating in initial experiments failed to identify our bots, underscoring the urgent need for increased awareness and education about the dangers of AI-driven disinformation, and in particular, disinformation spread by bots. The implications of our research point to the significant challenges posed by social bots in the upcoming 2024 U.S. presidential election and beyond.

The number of citations received by papers often exhibits imbalances in terms of author attributes such as country of affiliation and gender. While recent studies have quantified citation imbalance in terms of the authors' gender in journal papers, the computer science discipline, where researchers frequently present their work at conferences, may exhibit unique patterns in gendered citation imbalance. Additionally, understanding how network properties in citations influence citation imbalances remains challenging due to a lack of suitable reference models. In this paper, we develop a family of reference models for citation networks and investigate gender imbalance in citations between papers published in computer science conferences. By deploying these reference models, we found that homophily in citations is strongly associated with gendered citation imbalance in computer science, whereas heterogeneity in the number of citations received per paper has a relatively minor association with it. Furthermore, we found that the gendered citation imbalance is most pronounced in papers published in the highest-ranked conferences, is present across different subfields, and extends to citation-based rankings of papers. Our study provides a framework for investigating associations between network properties and citation imbalances, aiming to enhance our understanding of the structure and dynamics of citations between research publications., Comment: 14 pages, 6 figures, and 7 tables. This work has been accepted as a full paper in the AAAI/ACM conference on Artificial Intelligence, Ethics and Society (AIES) 2024

In this paper, we give for the first time a systematic study of the variance of the distance to the boundary for arbitrary bounded convex domains in $\mathbb{R}^2$ and $\mathbb{R}^3$. In dimension two, we show that this function is strictly convex, which leads to a new notion of the centre of such a domain, called the variocentre. In dimension three, we investigate the relationship between the variance and the distance to the boundary, which mathematically justifies claims made for a recently developed algorithm for classifying interior and exterior points with applications in biology., Comment: 26 pages, 6 figures

We present the preliminary design of GMagAO-X, the first-light high-contrast imager planned for the Giant Magellan Telescope. GMagAO-X will realize the revolutionary increase in spatial resolution and sensitivity provided by the 25 m GMT. It will enable, for the first time, the spectroscopic characterization of nearby potentially habitable terrestrial exoplanets orbiting late-type stars. Additional science cases include: reflected light characterization of mature giant planets; measurement of young extrasolar giant planet variability; characterization of circumstellar disks at unprecedented spatial resolution; characterization of benchmark stellar atmospheres at high spectral resolution; and mapping of resolved objects such as giant stars and asteroids. These, and many more, science cases will be enabled by a 21,000 actuator extreme adaptive optics system, a coronagraphic wavefront control system, and a suite of imagers and spectrographs. We will review the science-driven performance requirements for GMagAO-X, which include achieving a Strehl ratio of 70% at 800 nm on 8th mag and brighter stars, and post-processed characterization at astrophysical flux-ratios of 1e-7 at 4 lambda/D (26 mas at 800 nm) separation. We will provide an overview of the resulting mechanical, optical, and software designs optimized to deliver this performance. We will also discuss the interfaces to the GMT itself, and the concept of operations. We will present an overview of our end-to-end performance modeling and simulations, including the control of segment phasing, as well as an overview of prototype lab demonstrations. Finally, we will review the results of Preliminary Design Review held in February, 2024., Comment: Presented at SPIE Astronomical Telescopes

With high equilibrium temperatures and tidally locked rotation, ultra-hot Jupiters (UHJs) are unique laboratories within which to probe extreme atmospheric physics and chemistry. In this paper, we present high-resolution dayside spectroscopy of the UHJ WASP-189b obtained with the new Gemini High-resolution Optical SpecTrograph (GHOST) at the Gemini South Observatory. The observations, which cover three hours of post-eclipse orbital phases, were obtained during the instrument's System Verification run. We detect the planet's atmosphere via the Doppler cross-correlation technique, and recover a detection of neutral iron in the planet's dayside atmosphere at a significance of 7.5$\sigma$ in the red-arm of the data, verifying the presence of a thermal inversion. We also investigate the presence of other species in the atmosphere and discuss the implications of model injection/recovery tests. These results represent the first atmospheric characterization of an exoplanet with GHOST's high-resolution mode, and demonstrate the potential of this new instrument in detecting and studying ultra-hot exoplanet atmospheres., Comment: 21 pages, 12 figures, 3 tables. Accepted for publication in The Astronomical Journal

The geomagnetic "solar flare effect" (SFE) results from excess ionization in the Earth's ionosphere, famously first detected at the time of the Carrington flare in 1859. This indirect detection of a flare constituted one of the first cases of "multimessenger astronomy," whereby solar ionizing radiation stimulates ionospheric currents. Well-observed SFEs have few-minute time scales and perturbations of >10 nT, with the greatest events reaching above 100 nT. In previously reported cases the SFE time profiles tend to resemble those of solar soft X-ray emission, which ionizes the D-region; there is also a less-well-studied contribution from Lyman-alpha. We report here a specific case, from flare SOL2024-03-10 (M7.4), in which an impulsive SFE deviated from this pattern. This flare contained an "early impulsive" component of exceptionally hard radiation, extending up to gamma-ray energies above 1 MeV, distinctly before the bulk of the flare soft X-ray emission. We can characterize the spectral distribution of this early-impulsive component in detail, thanks to the modern extensive wavelength coverage. A more typical gradual SFE occurred during the flare's main phase. We suggest that events of this type warrant exploration of the solar physics in the "impulse response" limit of very short time scales., Comment: MNRAS to be published

In recent years, deep reinforcement learning (DRL) approaches have generated highly successful controllers for a myriad of complex domains. However, the opaque nature of these models limits their applicability in aerospace systems and safety-critical domains, in which a single mistake can have dire consequences. In this paper, we present novel advancements in both the training and verification of DRL controllers, which can help ensure their safe behavior. We showcase a design-for-verification approach utilizing k-induction and demonstrate its use in verifying liveness properties. In addition, we also give a brief overview of neural Lyapunov Barrier certificates and summarize their capabilities on a case study. Finally, we describe several other novel reachability-based approaches which, despite failing to provide guarantees of interest, could be effective for verification of other DRL systems, and could be of further interest to the community., Comment: 10 pages, 3 figures

Explosive transient events occur throughout the solar atmosphere. The differing manifestations range from coronal mass ejections to Ellerman bombs. The former may have negligible signatures in the lower atmosphere, and the latter may have negligible nonthermal emissions such as hard X-radiation. A solar flare generally involves a broad range of emission signatures. Using a suite of four space-borne telescopes, we report a solar event that combines aspects of simple UV bursts and hard X-ray emitting flares at the same time. The event is a compact C-class flare in active region AR11861, SOL2013-10-12T00:30. By fitting a combined isothermal and nonthermal model to the hard X-ray spectrum, we inferred plasma temperatures in excess of 15\,MK and a nonthermal power of about $3\times10^{27}$\,erg\,s$^{-1}$ in this event. Despite these high temperatures and evidence for nonthermal particles, the flare was mostly confined to the chromosphere. However, the event lacked clear signatures of UV spectral lines, such as the Fe\,{\sc xii} 1349\,\AA\ and Fe\,{\sc xxi} 1354\,\AA\ emission lines, which are characteristic of emission from hotter plasma with a temperature over 1\,MK. Moreover, the event exhibited very limited signatures in the extreme-UV wavelengths. Our study indicates that a UV burst -- hard X-ray flare hybrid phenomenon exists in the low solar atmosphere. Plasma that heats to high temperatures coupled with particle acceleration by magnetic energy that is released directly in the lower atmosphere sheds light on the nature of active region core heating and on inferences of flare signatures., Comment: Publication in the Astronomy & Astrophysics Letters

Submillimeter and millimeter wavelengths provide a unique view of the Universe, from the gas and dust that fills and surrounds galaxies to the chromosphere of our own Sun. Current single-dish facilities have presented a tantalising view of the brightest (sub-)mm sources, and interferometers have provided the exquisite resolution necessary to analyse the details in small fields, but there are still many open questions that cannot be answered with current facilities. In this report we summarise the science that is guiding the design of the Atacama Large Aperture Submillimeter Telescope (AtLAST). We demonstrate how tranformational advances in topics including star formation in high redshift galaxies, the diffuse circumgalactic medium, Galactic ecology, cometary compositions and solar flares motivate the need for a 50m, single-dish telescope with a 1-2 degree field of view and a new generation of highly multiplexed continuum and spectral cameras. AtLAST will have the resolution to drastically lower the confusion limit compared to current single-dish facilities, whilst also being able to rapidly map large areas of the sky and detect extended, diffuse structures. Its high sensitivity and large field of view will open up the field of submillimeter transient science by increasing the probability of serendipitous detections. Finally, the science cases listed here motivate the need for a highly flexible operations model capable of short observations of individual targets, large surveys, monitoring programmes, target of opportunity observations and coordinated observations with other observatories. AtLAST aims to be a sustainable, upgradeable, multipurpose facility that will deliver orders of magnitude increases in sensitivity and mapping speeds over current and planned submillimeter observatories., Comment: 47 pages, 12 figures. For further details on AtLAST see https://atlast.uio.no

In Explainable AI, rule extraction translates model knowledge into logical rules, such as IF-THEN statements, crucial for understanding patterns learned by black-box models. This could significantly aid in fields like disease diagnosis, disease progression estimation, or drug discovery. However, such application domains often contain imbalanced data, with the class of interest underrepresented. Existing methods inevitably compromise the performance of rules for the minor class to maximise the overall performance. As the first attempt in this field, we propose a model-agnostic approach for extracting rules from specific subgroups of data, featuring automatic rule generation for numerical features. This method enhances the regional explainability of machine learning models and offers wider applicability compared to existing methods. We additionally introduce a new method for selecting features to compose rules, reducing computational costs in high-dimensional spaces. Experiments across various datasets and models demonstrate the effectiveness of our methods.

Solar flares are powerful particle accelerators, and in the accepted standard flare model most of the flare energy is transported from a coronal energy-release region by accelerated electrons which stop collisionally in the chromosphere, heating and ionising the plasma, producing a broadband enhancement to the solar radiative output. We present a time-delay analysis of the infrared emission from two chromospheric sources in the flare SOL2014-09-24T17:50 taken at the McMath-Pierce telescope. By cross-correlating the intensity signals, measured with 1s cadence, from the two spatially resolved infrared sources we find a delay of 0.75 $\pm$ 0.07 s at 8.2 $\mu$m, where the uncertainties are quantified by a Monte Carlo analysis. The sources correlate well in brightness but have a time lag larger than can be reasonably explained by the energy transport dominated by non-thermal electrons precipitating from a single acceleration site in the corona. If interpreted as a time-of-flight difference between electrons traveling to each footpoint, we estimate time delays between 0.14 s and 0.42 s, for a reconnection site at the interior quasi-separatrix layer or at the null-point of the spine-fan topology inferred for this event. We employed modelling of electron transport via time-dependent Fokker-Planck and radiative hydrodynamic simulations to evaluate other possible sources of time-delay in the generation of the IR emission, such as differing ionisation timescales under different chromospheric conditions. Our results demonstrate that they are also unable to account for this discrepancy. This flare appears to require energy transport by some means other than electron beams originating in the corona., Comment: 15 pages, 12 figures, accepted for publication (MNRAS)

Attention for transformers is a critical workload that has recently received significant "attention" as a target for custom acceleration. Yet, while prior work succeeds in reducing attention's memory-bandwidth requirements, it creates load imbalance between attention operators (resulting in severe compute under-utilization) and requires on-chip memory that scales with sequence length (which is expected to grow over time). This paper ameliorates these issues, enabling attention with nearly 100% compute utilization, no off-chip memory traffic bottlenecks, and on-chip buffer size requirements that are independent of sequence length. The main conceptual contribution is to use a recently proposed abstraction -- the cascade of Einsums -- to describe, formalize and taxonomize the space of attention algorithms that appear in the literature. In particular, we show how Einsum cascades can be used to infer non-trivial lower bounds on the number of passes a kernel must take through its input data, which has implications for either required on-chip buffer capacity or memory traffic. We show how this notion can be used to meaningfully divide the space of attention algorithms into several categories and use these categories to inform our design process. Based on the above characterization, we propose FuseMax -- a novel mapping of attention onto a spatial array-style architecture. On attention, in an iso-area comparison, FuseMax achieves an average $6.7\times$ speedup over the prior state-of-the-art FLAT while using $79\%$ of the energy. Similarly, on the full end-to-end transformer inference, FuseMax achieves an average $5.3\times$ speedup over FLAT using $83\%$ of the energy., Comment: 15 pages, 10 figures

Jupiters south polar region was observed by JWST Mid Infrared Instrument in December 2022. We used the Medium Resolution Spectrometer mode to provide new information about Jupiters South Polar stratosphere. The southern auroral region was visible and influenced the atmosphere in several ways. 1: In the interior of the southern auroral oval, we retrieved peak temperatures at two distinct pressure levels near 0.01 and 1 mbar, with warmer temperatures with respect to non auroral regions of 12 pm 2 K and 37 pm 4 K respectively. A cold polar vortex is centered at 65S at 10 mbar. 2: We found that the homopause is elevated to 590+25-118 km above the 1-bar pressure level inside the auroral oval compared to 460+60-50 km at neighboring latitudes and with an upper altitude of 350 km in regions not affected by auroral precipitation. 3: The retrieved abundance of C2H2 shows an increase within the auroral oval, and it exhibits high abundances throughout the polar region. The retrieved abundance of C2H6 increases towards the pole, without being localized in the auroral oval, in contrast with previous analysis. We determined that the warming at 0.01 mbar and the elevated homopause might be caused by the flux of charged particles depositing their energy in the South Polar Region. The 1 mbar hotspot may arise from adiabatic heating resulting from auroral driven downwelling. The cold region at 10 mbar may be caused by radiative cooling by stratospheric aerosols. The differences in spatial distribution seem to indicate that the hydrocarbons analyzed are affected differently by auroral precipitation.

Curbs serve as vital borders that delineate safe pedestrian zones from potential vehicular traffic hazards. Curbs also represent a primary spatial hazard during dynamic navigation with significant stumbling potential. Such vulnerabilities are particularly exacerbated for persons with blindness and low vision (PBLV). Accurate visual-based discrimination of curbs is paramount for assistive technologies that aid PBLV with safe navigation in urban environments. Herein, we investigate the efficacy of curb segmentation for foundation models. We introduce the largest curb segmentation dataset to-date to benchmark leading foundation models. Our results show that state-of-the-art foundation models face significant challenges in curb segmentation. This is due to their high false-positive rates (up to 95%) with poor performance distinguishing curbs from curb-like objects or non-curb areas, such as sidewalks. In addition, the best-performing model averaged a 3.70-second inference time, underscoring problems in providing real-time assistance. In response, we propose solutions including filtered bounding box selections to achieve more accurate curb segmentation. Overall, despite the immediate flexibility of foundation models, their application for practical assistive technology applications still requires refinement. This research highlights the critical need for specialized datasets and tailored model training to address navigation challenges for PBLV and underscores implicit weaknesses in foundation models., Comment: 21 pages, 8 figures, submitted to Assistive Technology

We study the optimization of navigational graph queries, i.e., queries which combine recursive and pattern-matching fragments. Current approaches to their evaluation are not effective in practice. Towards addressing this, we present a number of novel powerful optimization techniques which aim to constrain the intermediate results during query evaluation. We show how these techniques can be planned effectively and executed efficiently towards the first practical evaluation solution for complex navigational queries on real-world workloads. Indeed, our experimental results show several orders of magnitude improvement in query evaluation performance over state-of-the-art techniques on a wide range of queries on diverse datasets.

We give an efficient algorithm for Centroid-Linkage Hierarchical Agglomerative Clustering (HAC), which computes a $c$-approximate clustering in roughly $n^{1+O(1/c^2)}$ time. We obtain our result by combining a new Centroid-Linkage HAC algorithm with a novel fully dynamic data structure for nearest neighbor search which works under adaptive updates. We also evaluate our algorithm empirically. By leveraging a state-of-the-art nearest-neighbor search library, we obtain a fast and accurate Centroid-Linkage HAC algorithm. Compared to an existing state-of-the-art exact baseline, our implementation maintains the clustering quality while delivering up to a $36\times$ speedup due to performing fewer distance comparisons.

Mosaic crystals, with their high integrated reflectivities, are widely-employed in spectrometers used to diagnose high energy density systems. X-ray Thomson scattering (XRTS) has emerged as a powerful diagnostic tool of these systems, providing in principle direct access to important properties such as the temperature via detailed balance. However, the measured XRTS spectrum is broadened by the spectrometer instrument function (IF), and without careful consideration of the IF one risks misdiagnosing system conditions. Here, we consider in detail the IF of 40 $\mu$m and 100 $\mu$m mosaic HAPG crystals, and how the broadening varies across the spectrometer in an energy range of 6.7-8.6 keV. Notably, we find a strong asymmetry in the shape of the IF towards higher energies. As an example, we consider the effect of the asymmetry in the IF on the temperature inferred via XRTS for simulated 80 eV CH plasmas, and find that the temperature can be overestimated if an approximate symmetric IF is used. We therefore expect a detailed consideration of the full IF will have an important impact on system properties inferred via XRTS in both forward modelling and model-free approaches., Comment: 19 pages, 13 figures

Deep reinforcement learning (DRL) is a powerful machine learning paradigm for generating agents that control autonomous systems. However, the ``black box'' nature of DRL agents limits their deployment in real-world safety-critical applications. A promising approach for providing strong guarantees on an agent's behavior is to use Neural Lyapunov Barrier (NLB) certificates, which are learned functions over the system whose properties indirectly imply that an agent behaves as desired. However, NLB-based certificates are typically difficult to learn and even more difficult to verify, especially for complex systems. In this work, we present a novel method for training and verifying NLB-based certificates for discrete-time systems. Specifically, we introduce a technique for certificate composition, which simplifies the verification of highly-complex systems by strategically designing a sequence of certificates. When jointly verified with neural network verification engines, these certificates provide a formal guarantee that a DRL agent both achieves its goals and avoids unsafe behavior. Furthermore, we introduce a technique for certificate filtering, which significantly simplifies the process of producing formally verified certificates. We demonstrate the merits of our approach with a case study on providing safety and liveness guarantees for a DRL-controlled spacecraft., Comment: To appear in FMCAD 2024

Last-level cache side-channel attacks have been mostly demonstrated in highly-controlled, quiescent local environments. Hence, it is unclear whether such attacks are feasible in a production cloud environment. In the cloud, side channels are flooded with noise from activities of other tenants and, in Function-as-a-Service (FaaS) workloads, the attacker has a very limited time window to mount the attack. In this paper, we show that such attacks are feasible in practice, although they require new techniques. We present an end-to-end, cross-tenant attack on a vulnerable ECDSA implementation in the public FaaS Google Cloud Run environment. We introduce several new techniques to improve every step of the attack. First, to speed-up the generation of eviction sets, we introduce L2-driven candidate address filtering and a Binary Search-based algorithm for address pruning. Second, to monitor victim memory accesses with high time resolution, we introduce Parallel Probing. Finally, we leverage power spectral density from signal processing to easily identify the victim's target cache set in the frequency domain. Overall, using these mechanisms, we extract a median value of 81% of the secret ECDSA nonce bits from a victim container in 19 seconds on average.

Since the COVID-19 pandemic disrupted in-person learning, fears about children's learning loss remain a primary concern for parents, teachers, and policymakers. These concerns, combined with longstanding issues of inequity regarding children's access to learning opportunities have sparked widespread discussion about how to reimagine education. While much focus has been on the classroom, children spend 80 percent of their waking time outside of school. Playful Learning Landscapes (PLL) capitalizes on the "other 80 percent" by infusing everyday spaces with engaging learning opportunities that are fun and interactive while reaching children and families most affected by the pandemic. Playful Learning Landscapes (PLL) uses discoveries from scientific research regarding "how" people learn best to inform the design of public spaces, including sidewalks, libraries, school yards, parks, and beyond. PLL installations range from games painted on sidewalks, to signage placed in grocery stores, to large physical designs integrated into bus stops. They are designed to foster actively engaged, meaningful, socially interactive, iterative, and joyful experiences for children and families. As a placemaking activity, PLL projects typically involve the community in their design, implementation, and evaluation processes--utilizing a participatory design approach that honors community values, ideas, and input. This ensures that the installations are accessible to all and that historically marginalized populations are centered in ownership of the designs. In this brief, the authors present findings from a rigorous analysis, providing evidence of the effectiveness of PLLs to date by synthesizing evaluations across a variety of PLL projects. The analysis examines data from 12 PLL projects in five locations to determine impacts on caregiver-child interaction and caregiver behavior and child behavior individually. The analysis also identifies moderating factors influencing effectiveness, such as the type of PLL and the extent of community involvement. Determining the factors that lead to increased effectiveness can help maximize impact and inform the implementation of PLLs. Thus, the authors close with a discussion of what this analysis tells about how local leaders can promote PLL uptake and integration in their communities and how they can create beautiful playful learning environments that build more child-friendly cities.