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In real-world applications of mobile robots, collision avoidance is of critical importance. Typically, global motion planning in constrained environments is addressed through high-level control schemes. However, additionally integrating local collision avoidance into robot motion control offers significant advantages. For instance, it reduces the reliance on heuristics and conservatism that can arise from a two-stage approach separating local collision avoidance and control. Moreover, using model predictive control (MPC), a robot's full potential can be harnessed by considering jointly local collision avoidance, the robot's dynamics, and actuation constraints. In this context, the present paper focuses on obstacle avoidance for wheeled mobile robots, where both the robot's and obstacles' occupied volumes are modeled as ellipsoids. To this end, a computationally efficient overlap test, that works for arbitrary ellipsoids, is conducted and novelly integrated into the MPC framework. We propose a particularly efficient implementation tailored to robots moving in the plane. The functionality of the proposed obstacle-avoiding MPC is demonstrated for two exemplary types of kinematics by means of simulations. A hardware experiment using a real-world wheeled mobile robot shows transferability to reality and real-time applicability. The general computational approach to ellipsoidal obstacle avoidance can also be applied to other robotic systems and vehicles as well as three-dimensional scenarios., Comment: 9 pages, 4 figures

Cathodoluminescence (CL) microscopy has emerged as a powerful tool for investigating the optical properties of materials at the nanoscale, offering unique insights into the behavior of photonic and plasmonic materials under electron excitation. We introduce an atlas of bulk CL spectra for a range of materials widely used in photonics and plasmonics. Through a combination of experimental CL spectroscopy and Monte Carlo simulations, we characterize electron penetration depth and energy deposition, offering a foundational reference for interpreting CL spectra and understanding material behavior under electron excitation. By capturing CL signal from a diverse range of materials, this atlas provides insights into the intrinsic emission properties essential for material selection and design in photonic and plasmonic device engineering.

Advances in machine learning and the growing trend towards effortless data generation in real-world systems has led to an increasing interest for data-inferred models and data-based control in robotics. It seems appealing to govern robots solely based on data, bypassing the traditional, more elaborate pipeline of system modeling through first-principles and subsequent controller design. One promising data-driven approach is the Extended Dynamic Mode Decomposition (EDMD) for control-affine systems, a system class which contains many vehicles and machines of immense practical importance including, e.g., typical wheeled mobile robots. EDMD can be highly data-efficient, computationally inexpensive, can deal with nonlinear dynamics as prevalent in robotics and mechanics, and has a sound theoretical foundation rooted in Koopman theory. On this background, this present paper examines how EDMD models can be integrated into predictive controllers for nonholonomic mobile robots. In addition to the conventional kinematic mobile robot, we also cover the complete data-driven control pipeline - from data acquisition to control design - when the robot is not treated in terms of first-order kinematics but in a second-order manner, allowing to account for actuator dynamics. Using only real-world measurement data, it is shown in both simulations and hardware experiments that the surrogate models enable high-precision predictive controllers in the studied cases. However, the findings raise significant concerns about purely data-centric approaches that overlook the underlying geometry of nonholonomic systems, showing that, for nonholonomic systems, some geometric insight seems necessary and cannot be easily compensated for with large amounts of data., Comment: 23 pages, 12 figures

This article describes condensation of the elements and use of condensation temperatures (Tcond) to interpret the volatility trend of the Earth. Major points are: (1) a listing of updated 50% Tcond for all natural elements and Pu at 1e-2 to 1e-8 bar pressure for solar composition matter. (2) The Tcond are mainly controlled by the Gibbs energy of condensation reactions and also by the Gibbs energy of ideal mixing if elements (compounds) condense in a solution. The Gibbs energy change of non-ideal solution (activity coefficients not equal to 1) is a secondary effect. (3) The theoretically correct relationship between Tcond and fraction condensed is derived from mass balance and chemical thermodynamic considerations. (4) The maximum amount of element condensed per 1/T, is at the inflection point in the logistic (sigmoid) curve for an element, which is also at (or close to) the 50% Tcond. (5) Plots of normalized elemental abundances versus 50% Tcond (volatility trends) are qualitative indicators of elemental fractionations due to volatility. (6) Volatility trend plots for average elemental abundances in CM, CO, CV, CR, H, L, LL, EH, EL chondrites show different trends for moderately and highly volatile elements, which may be linear, curved, a step function, or plateau. Comparison of three abundance sets for CM and CV chondrites shows trends depend on which elements are plotted, which data sources are used, and which temperature range is considered. (7) Proposed mechanisms for volatile element depletion in carbonaceous chondrites and the Earth are reviewed. (8) Possible implications of volatile element abundances in the bulk silicate Earth are discussed., Comment: 50 pages, 1 table, 15 figures. Preprint submitted to Space Science Reviews October 2024

Data-based methods have gained increasing importance in engineering, especially but not only driven by successes with deep artificial neural networks. Success stories are prevalent, e.g., in areas such as data-driven modeling, control and automation, as well as surrogate modeling for accelerated simulation. Beyond engineering, generative and large-language models are increasingly helping with tasks that, previously, were solely associated with creative human processes. Thus, it seems timely to seek artificial-intelligence-support for engineering design tasks to automate, help with, or accelerate purpose-built designs of engineering systems, e.g., in mechanics and dynamics, where design so far requires a lot of specialized knowledge. However, research-wise, compared to established, predominantly first-principles-based methods, the datasets used for training, validation, and test become an almost inherent part of the overall methodology. Thus, data publishing becomes just as important in (data-driven) engineering science as appropriate descriptions of conventional methodology in publications in the past. This article analyzes the value and challenges of data publishing in mechanics and dynamics, in particular regarding engineering design tasks, showing that the latter raise also challenges and considerations not typical in fields where data-driven methods have been booming originally. Possible ways to deal with these challenges are discussed and a set of examples from across different design problems shows how data publishing can be put into practice. The analysis, discussions, and examples are based on the research experience made in a priority program of the German research foundation focusing on research on artificially intelligent design assistants in mechanics and dynamics., Comment: 25 pages, 10 figures

Floods are among the most common and devastating natural hazards, imposing immense costs on our society and economy due to their disastrous consequences. Recent progress in weather prediction and spaceborne flood mapping demonstrated the feasibility of anticipating extreme events and reliably detecting their catastrophic effects afterwards. However, these efforts are rarely linked to one another and there is a critical lack of datasets and benchmarks to enable the direct forecasting of flood extent. To resolve this issue, we curate a novel dataset enabling a timely prediction of flood extent. Furthermore, we provide a representative evaluation of state-of-the-art methods, structured into two benchmark tracks for forecasting flood inundation maps i) in general and ii) focused on coastal regions. Altogether, our dataset and benchmark provide a comprehensive platform for evaluating flood forecasts, enabling future solutions for this critical challenge. Data, code & models are shared at https://github.com/Multihuntr/GFF under a CC0 license., Comment: Accepted at NeurIPS 2024 Datasets & Benchmarks

Tensor network renormalization group maps study critical points of 2d lattice models like the Ising model by finding the fixed point of the RG map. In a prior work arXiv:2408.10312 we showed that by adding a rotation to the RG map, the Newton method could be implemented to find an extremely accurate fixed point. For a particular RG map (Gilt-TNR) we studied the spectrum of the Jacobian of the RG map at the fixed point and found good agreement between the eigenvalues corresponding to relevant and marginal operators and their known exact values. In this companion work we use two further methods to extract many more scaling dimensions from this Newton method fixed point, and compare the numerical results with the predictions of conformal field theory (CFT). The first method is the well-known transfer matrix. We introduce some extensions of this method that provide spins of the CFT operators modulo an integer. We find good agreement for the scaling dimensions and spins up to $\Delta=3\frac1 8$. The second method we refer to as the lattice dilatation operator (LDO). This lesser-known method obtains good agreement with CFT up to $\Delta=6$. Moreover, the inclusion of a rotation in the RG map makes it possible to extract spins of the CFT operators modulo 4 from this method. Some of the eigenvalues of the Jacobian of the RG map can come from perturbations associated with total derivative interactions and so are not universal. In some past studies (arXiv:2102.08136, arXiv:2305.09899) such non-universal eigenvalues did not appear in the Jacobian. We explain this surprising result by showing that their RG map has the unusual property that the Jacobian is equivalent to the LDO operator., Comment: 25+13 pages, 5 tables, 6 figures, data in ancillary files

Chondritic components such as chondrules and matrix are the key time capsules that can help us understand the evolution and dynamics of the protoplanetary disk from which the Solar System originated. Knowledge of where and how these components formed and to what extent they were transported in the gaseous disk provides major constraints to astrophysical models that investigate planet formation. Here, we explore whether chondrules and matrix are genetically related to each other and formed from single reservoirs per chondrite group or if every chondrite represents a unique proportion of components transported from a small number of formation reservoirs in the disk. These static versus dynamic disk interpretations of cosmochemical data have profound implications for the accretion history of the planets in the Solar System. To fully understand the relationship between chondrules and matrix and their potential complementarity, we dive into the petrological nature and origin of matrix, the chemical and isotopic compositions of chondrules and matrix and evaluate these data considering the effect of secondary alteration observed in chondrites and the potential complexity of chondrule formation. Even though we, the authors, have used different datasets and arrived at differing interpretations of chondrule-matrix relationships in the past, this review provides clarity on the existing data and has given us new directions towards future research that can resolve the complementarity debate., Comment: accepted in Space Science Reviews

In the tensor network approach to statistical physics, properties of the critical point of a 2D lattice model are encoded by a four-legged tensor which is a fixed point of an RG map. The traditional way to find the fixed point tensor consists in iterating the RG map after having tuned the temperature to criticality. Here we develop a different and more direct technique, which solves the fixed point equation via the Newton method. This is challenging due to the existence of marginal deformations -- linear transformations of the coordinate frame, which parametrize a two-dimensional family of fixed points. We address this challenge by including a 90 degree rotation into the RG map. This flips the sign of the problematic marginal eigenvalues, rendering the fixed point isolated and accessible via the Newton method. We demonstrate the power of this technique via explicit computations for the 2D Ising and 3-state Potts models. Using the Gilt-TNR algorithm at bond dimension $\chi=30$, we find the fixed point tensors with $10^{-9}$ accuracy, much higher than what was previously achieved., Comment: 37+24 pages, 16 figures, 7 tables. Version 4: 3-state Potts model discussion was added; discussions of CFT and RG were extended; discussion of Jacobian approximations was rearranged and extended; many clarifying comments were added

In this paper we show how fully homomorphic encryption (FHE) can be accelerated using a systolic architecture. We begin by analyzing FHE algorithms and then develop systolic or systolic-esque units for each major kernel. Connecting units is challenging due to the different data access and computational patterns of the kernels. We overcome this by proposing a new data tiling technique that we name limb interleaving. Limb interleaving creates a common data input/output pattern across all kernels that allows the entire architecture, named Osiris, to operate in lockstep. Osiris is capable of processing key-switches, bootstrapping, and full neural network inferences with high utilization across a range of FHE parameters. To achieve high performance, we propose a new giant-step centric (GSC) dataflow that efficiently maps state-of-the-art FHE matrix-vector product algorithms onto Osiris by optimizing for reuse and parallelism. Our evaluation of Osiris shows it outperforms the prior state-of-the-art accelerator on all standard benchmarks., Comment: 11 pages, 15 figures, 5 tables, 2 algorithms

Formation of the giant Chicxulub crater off Mexico's Yucatan Peninsula coincided with deposition of the global Ir-rich Cretaceous-Tertiary (K-T) stratigraphic boundary layer at ca. 65 Ma. The boundary is marked most sharply by abundant spherules containing unaltered grains of magnesioferrite spinel. Here we predict for the first time the sequential condensation of solids and liquids from the plume of vaporized rock expected from oblique K-T impacts. We predict highly oxidizing plumes that condense silicate liquid droplets bearing spinel grains whose compositions closely match those marking the actual boundary. Systematic global variations in spinel composition are consistent with higher condensation temperatures for spinels found at Atlantic and European sites than for those in the Pacific., Comment: 24 pages, 3 figures, 1 table, 2 supplemental tables included

Abundances, apparent sizes, and individual chemical compositions of chondrules, refractory inclusions, other objects and surrounding matrix have been determined for Semarkona (LL3.00) and Renazzo (CR2) using consistent methods and criteria on x-ray element intensity maps. These represent the non-carbonaceous (NC, Semarkona) and carbonaceous chondrite (CC, Renazzo) superclans of chondrite types. We compare object and matrix abundances with similar data for CM, CO, K, and CV chondrites. We assess, pixel-by-pixel, the major element abundance in each object and in the entire matrix. We determine the abundance of "metallic chondrules" in LL chondrites. Chondrules with high Mg/Si and low Fe/Si and matrix carrying opposing ratios complement each other to make whole rocks with near-solar major element ratios in Renazzo. Similar Mg/Si and Fe/Si chondrule-matrix relationships are seen in Semarkona, which is within 11% of solar Mg/Si but significantly Fe-depleted. These results provide a robust constraint in support of single-reservoir models for chondrule formation and accretion, ruling out whole classes of astrophysical models and constraining processes of chondrite component formation and accretion into chondrite parent bodies., Comment: 20 pages, 10 figures, 4 tables. Meteoritics and Planetary Sciences (20pp) (2024)

Hurricanes and coastal floods are among the most disastrous natural hazards. Both are intimately related to storm surges, as their causes and effects, respectively. However, the short-term forecasting of storm surges has proven challenging, especially when targeting previously unseen locations or sites without tidal gauges. Furthermore, recent work improved short and medium-term weather forecasting but the handling of raw unassimilated data remains non-trivial. In this paper, we tackle both challenges and demonstrate that neural networks can implicitly assimilate sparse in situ tide gauge data with coarse ocean state reanalysis in order to forecast storm surges. We curate a global dataset to learn and validate the dense prediction of storm surges, building on preceding efforts. Other than prior work limited to known gauges, our approach extends to ungauged sites, paving the way for global storm surge forecasting., Comment: Accepted at CVPR EarthVision 2024

Controlling free-electron momentum states is of high interest in electron microscopy to achieve momentum and energy resolved probing and manipulation of physical systems. Free-electron and light interactions have emerged as a powerful technique to accomplish this. Here, we demonstrate both longitudinal and transverse phase control of a slow electron wavepacket by extending the Kapitza-Dirac effect to spatially-structured pulsed laser beams. This extension enables both inelastic and elastic stimulated Compton scattering. The interaction reveals the formation of distinct electron transverse momentum orders, each demonstrating a comb-like electron energy spectrum. By exerting complete control over light parameters, including wavelength, field intensity, pulse duration, and spatial mode order, as well as their combinations, it is possible to coherently control the population of these electron energy-momentum states that are separated by a few meV energy and multiple photon momentum orders. This free-space electron-light interaction phenomenon possesses the capability to coherently control the energy and momentum of electron beams in electron microscopes. Moreover, it has the potential to facilitate the selective probing of various material excitations, including plasmons, excitons, and phonons, and performing Talbot-Lau matter-wave interferometry with transversely shaped electron beams.

As the automotive world moves toward higher levels of driving automation, Level 3 automated driving represents a critical juncture. In Level 3 driving, vehicles can drive alone under limited conditions, but drivers are expected to be ready to take over when the system requests. Assisting the driver to maintain an appropriate level of Situation Awareness (SA) in such contexts becomes a critical task. This position paper explores the potential of Attentive User Interfaces (AUIs) powered by generative Artificial Intelligence (AI) to address this need. Rather than relying on overt notifications, we argue that AUIs based on novel AI technologies such as large language models or diffusion models can be used to improve SA in an unconscious and subtle way without negative effects on drivers overall workload. Accordingly, we propose 5 strategies how generative AI s can be used to improve the quality of takeovers and, ultimately, road safety., Comment: MUM 2023 Workshop on Interruptions and Attention Management: Exploring the Potential of Generative AI

Building upon previous $2D$ studies, this research focuses on describing $3D$ tensor renormalisation group (RG) flows for lattice spin systems, such as the Ising model. We present a novel RG map, which operates on tensors with infinite-dimensional legs and does not involve truncations, in contrast to numerical tensor RG maps. To construct this map, we developed new techniques for analysing tensor networks. Our analysis shows that the constructed RG map contracts the region around the tensor $A_*$, corresponding to the high-temperature phase of the $3D$ Ising model. This leads to the iterated RG map convergence in the Hilbert-Schmidt norm to $A_*$ when initialised in the vicinity of $A_*$. This work provides the first steps towards the rigorous understanding of tensor RG maps in $3D$., Comment: Annales Henri Poincar\'e (2024)

We have measured the absolute doubly differential angular sputtering yield for 20 keV Kr+ impacting a polycrystalline Cu slab at an incidence angle of {\theta}i = 45{\deg} relative to the surface normal. Sputtered Cu atoms were captured using collectors mounted on a half dome above the sample, and the sputtering distribution was measured as a function of the sputtering polar, {\theta}s, and azimuthal, phi, angles. Absolute results of the sputtering yield were determined from the mass gain of each collector, the ion dose, and the solid angle subtended, after irradiation to a total fluence of ~ 1 x 10^18 ions/cm^2. Our approach overcomes shortcomings of commonly used methods that only provide relative yields as a function of {\theta}s in the incidence plane (defined by the ion velocity and the surface normal). Our experimental results display an azimuthal variation that increases with increasing {\theta}s and is clearly discrepant with simulations using binary collision theory. We attribute the observed azimuthal anisotropy to ion-induced formation of micro- and nano-scale surface features that suppress the sputtering yield through shadowing and redeposition effects, neither of which are accounted for in the simulations. Our experimental results demonstrate the importance of doubly differential angular sputtering studies to probe ion sputtering processes at a fundamental level and to explore the effect of ion-beam-generated surface roughness., Comment: 29 pages, 9 figures

Fully Homomorphic Encryption (FHE) has the potential to substantially improve privacy and security by enabling computation directly on encrypted data. This is especially true with deep learning, as today, many popular user services are powered by neural networks in the cloud. One of the major challenges facing wide-scale deployment of FHE-secured neural inference is effectively mapping these networks to FHE primitives. FHE poses many programming challenges including packing large vectors, automatically managing noise via bootstrapping, and translating arbitrary and general-purpose programs to the limited instruction set provided by FHE. These challenges make building large FHE neural networks intractable using the tools available today. In this paper we address these challenges with Orion, a fully-automated framework for private neural inference in FHE. Orion accepts deep neural networks written in PyTorch and translates them into efficient FHE programs. We achieve this by proposing a novel single-shot multiplexed packing strategy for arbitrary convolutions and through a new, efficient technique to automate bootstrap placement. We evaluate Orion on common benchmarks used by the FHE deep learning community and outperform state-of-the-art by $2.38 \times$ on ResNet-20, the largest network they report. Orion extends naturally to larger networks. We demonstrate this by evaluating ResNet-50 on ImageNet and present the first high-resolution homomorphic object detection experiments using a YOLO-v1 model with 139 million parameters. Finally, we open-source our framework Orion at the following repository: https://github.com/baahl-nyu/orion, Comment: 12 pages, 13 figures, 4 tables

Homomorphic encryption (HE) is a privacy-preserving computation technique that enables computation on encrypted data. Today, the potential of HE remains largely unrealized as it is impractically slow, preventing it from being used in real applications. A major computational bottleneck in HE is the key-switching operation, accounting for approximately 70% of the overall HE execution time and involving a large amount of data for inputs, intermediates, and keys. Prior research has focused on hardware accelerators to improve HE performance, typically featuring large on-chip SRAMs and high off-chip bandwidth to deal with large scale data. In this paper, we present a novel approach to improve key-switching performance by rigorously analyzing its dataflow. Our primary goal is to optimize data reuse with limited on-chip memory to minimize off-chip data movement. We introduce three distinct dataflows: Max-Parallel (MP), Digit-Centric (DC), and Output-Centric (OC), each with unique scheduling approaches for key-switching computations. Through our analysis, we show how our proposed Output-Centric technique can effectively reuse data by significantly lowering the intermediate key-switching working set and alleviating the need for massive off-chip bandwidth. We thoroughly evaluate the three dataflows using the RPU, a recently published vector processor tailored for ring processing algorithms, which includes HE. This evaluation considers sweeps of bandwidth and computational throughput, and whether keys are buffered on-chip or streamed. With OC, we demonstrate up to 4.16x speedup over the MP dataflow and show how OC can save 12.25x on-chip SRAM by streaming keys for minimal performance penalty.

We provide an axiomatic treatment of Quillen's construction of the model structure on topological spaces to make it applicable to a wider range of settings, including $\Delta$-generated spaces and pseudotopological spaces. We use this axiomatization to construct a model structure on the category of locales., Comment: 31 pages; comments welcome

Djerfisherite is an important carrier of potassium in highly reduced enstatite chondrites, where it occurs in sub-round metal-sulfide nodules. These nodules were once free-floating objects in the protoplanetary nebula. Here, we analyze existing and new data to derive an equation of state (EOS) for djerfisherites of K_{6}(Cu,Fe,Ni)^{B} (Fe,Ni,Cu)^{C}_{24} S_{26}Cl structural formula. We use this EOS to calculate the thermal stability of djerfisherite coexisting in equilibrium with a cooling vapor of solar composition enriched in a dust analogous to anhydrous, chondritic interplanetary dust (C-IDP). We find that condensed mineral assemblages closely match those found in enstatite chondrites, with djerfisherite condensing above 1000 K in C-IDP dust enriched systems. Results may have implications for the volatile budgets of terrestrial planets, and the incorporation of K into early-formed, highly reduced, planetary cores. Previous work links enstatite chondrites to the planet Mercury, where the surface has a terrestrial K/Th ratio, high S/Si ratio, and very low FeO content. Mercury's accretion history may yield insights into Earth's., Comment: 18 pages, 5 figures, 4 tables

We report non-destructive 3-dimensional imaging and analysis techniques for material returned by the Stardust cometary collector. Our technique utilizes 3-dimensional laser scanning confocal microscopy (3D LSCM) to image whole Stardust tracks, in situ, with attainable resolutions <90 nm/pixel edge. LSCM images illustrate track morphology and fragmentation history; image segmentation techniques provide quantifiable volumetric and dynamic measurements. We present a method for multipart image acquisition and registration in 3-D. Additionally, we present a 3D deconvolution method for aerogel, using a theoretically calculated point spread function for first-order corrections of optical aberrations induced by light diffraction and refractive index mismatches. LSCM is a benchtop technique and is an excellent alternative to synchrotron x-ray computed microtomography for optically transparent media. Our technique, developed over the past 2 years, is a non-invasive, rapid technique for fine-scale imaging of high value returned samples from the Stardust mission, as well as various other samples from the geosciences., Comment: 17 pages, 6 figures, 2 tables

The origin of Mercury's anomalous core and low FeO surface mineralogy are outstanding questions in planetary science. Mercury's composition may result from cosmochemical controls on the precursor solids that accreted to form Mercury. High temperatures and enrichment in solid condensates are likely conditions near the midplane of the inner solar protoplanetary disk. Silicate liquids similar to the liquids quenched in ferromagnesian chondrules are thermodynamically stable in oxygen-rich systems that are highly enriched in dust of CI-chondrite composition. In contrast, the solids surviving into the orbit of Mercury's accretion zone were probably similar to highly unequilibrated, anhydrous, interstellar organic- and presolar grain-bearing chondritic, porous interplanetary dust particles (C-IDPs). Chemical systems enriched in an assumed C-IDP composition dust produce condensates (solid + liquid assemblages in equilibrium with vapor) with super-chondritic atomic Fe/Si ratios at high temperatures, approaching 50% of that estimated for bulk Mercury. Sulfur behaves as a refractory element, but at lower temperatures, in these chemical systems. Stable minerals are FeO-poor, and include CaS and MgS, species found in enstatite chondrites. Disk gradients in volatile compositions of planetary and asteroidal precursors can explain Mercury's anomalous composition, as well as enstatite chondrite and aubrite parent body compositions. This model predicts high sulfur content, and very low FeO content of Mercury's surface rocks., Comment: 17 pages, 5 figures, 1 table

User Experience (UX) professionals need to be able to analyze large amounts of usage data on their own to make evidence-based design decisions. However, the design process for In-Vehicle Information Systems (IVIS) lacks data-driven support and effective tools for visualizing and analyzing user interaction data. Therefore, we propose ICEBOAT, an interactive visualization tool tailored to the needs of automotive UX experts to effectively and efficiently evaluate driver interactions with IVISs. ICEBOAT visualizes telematics data collected from production line vehicles, allowing UX experts to perform task-specific analyses. Following a mixed methods User-centered design (UCD) approach, we conducted an interview study (N=4) to extract the domain specific information and interaction needs of automotive UX experts and used a co-design approach (N=4) to develop an interactive analysis tool. Our evaluation (N=12) shows that ICEBOAT enables UX experts to efficiently generate knowledge that facilitates data-driven design decisions., Comment: to be published at the 15th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI '23), September 18--22, 2023, Ingolstadt, Germany

Privacy and security have rapidly emerged as first order design constraints. Users now demand more protection over who can see their data (confidentiality) as well as how it is used (control). Here, existing cryptographic techniques for security fall short: they secure data when stored or communicated but must decrypt it for computation. Fortunately, a new paradigm of computing exists, which we refer to as privacy-preserving computation (PPC). Emerging PPC technologies can be leveraged for secure outsourced computation or to enable two parties to compute without revealing either users' secret data. Despite their phenomenal potential to revolutionize user protection in the digital age, the realization has been limited due to exorbitant computational, communication, and storage overheads. This paper reviews recent efforts on addressing various PPC overheads using private inference (PI) in neural network as a motivating application. First, the problem and various technologies, including homomorphic encryption (HE), secret sharing (SS), garbled circuits (GCs), and oblivious transfer (OT), are introduced. Next, a characterization of their overheads when used to implement PI is covered. The characterization motivates the need for both GCs and HE accelerators. Then two solutions are presented: HAAC for accelerating GCs and RPU for accelerating HE. To conclude, results and effects are shown with a discussion on what future work is needed to overcome the remaining overheads of PI., Comment: Appear in the 20th ACM International Conference on Computing Frontiers

One of the major unresolved problems in cosmochemistry is the origin of chondrules, once molten, spherical silicate droplets with diameters of 0.2 to 2 mm. Chondrules are an essential component of primitive meteorites and perhaps of all early solar system materials including the terrestrial planets. Numerous hypotheses have been proposed for their origin. Many carbonaceous chondrites are composed of about equal amounts of chondrules and fine-grained matrix. Recent data confirm that matrix in carbonaceous chondrites has high Si/Mg and Fe/Mg ratios when compared to bulk carbonaceous chondrites with solar abundance ratios. Chondrules have the opposite signature, low Si/Mg and Fe/Mg ratios. In some carbonaceous chondrites chondrules have low Al/Ti ratios, matrix has the opposite signature and the bulk is chondritic. It is shown in detail that these complementary relationships cannot have evolved on the parent asteroid(s) of carbonaceous chondrites. They reflect preaccretionary processes. Both chondrules and matrix must have formed from a single, solar-like reservoir. Consequences of complementarity for chondrule formation models are discussed. An independent origin and/or random mixing of chondrules and matrix can be excluded. Hence, complementarity is a strong constraint for all astrophysical-cosmochemical models of chondrule formation. Although chondrules and matrix formed from a single reservoir, the chondrule-matrix system was open to the addition of oxygen and other gaseous components., Comment: 27 pages, 8 figures, with supplemental tables

The Stardust mission captured comet Wild 2 particles in aerogel at 6.1 km/sec. We performed high resolution three-dimensional imaging and X-ray fluorescence mapping of whole cometary tracks in aerogel. We present the results of a survey of track structures using Laser Scanning Confocal Microscopy, including measurements of track volumes, entry hole size and cross-sectional profiles. We compare various methods for measuring track parameters. We demonstrate a methodology for discerning hypervelocity particle ablation rates using synchrotron-based X-ray fluorescence, combined with mass and volume estimates of original impactors derived from measured track properties. Finally, we present a rough framework for reconstruction of original impactor size, and volume of volatilized material, using our measured parameters. The bulk of this work is in direct support of non-destructive analysis and identification of cometary grains in whole tracks, and its eventual application to the reconstruction of the size, shape, porosity and chemical composition of whole Stardust impactors., Comment: 21 pages, 10 figures, 3 tables

Condensation models describe the equilibrium distribution of elements between coexisting mineral solid solutions, silicate liquid, and vapor in a closed chemical system, vapor phase always present, using equations of state of the phases involved at a fixed total P (< 1 bar) and temperature T. The VAPORS code uses a CaO-MgO-Al$_2$O$_3$-SiO$_2$ liquid model at T above the stability field of olivine and the MELTS algorithm at lower T. Quenched high-T crystal + liquid assemblages are preserved in meteorites as Type B Ca-, Al-rich inclusions (CAIs) and olivine-rich ferromagnesian chondrules. Experimental tests of compositional regions may clarify the nature of the phases present, the phase boundaries, and the partition of trace elements among these phases. Twenty-three Pt-loop equilibrium experiments in seven phase fields on twelve bulk compositions at specific T and dust enrichment factors tested the predicted stability fields of forsteritic olivine (Mg$_2$SiO$_4$), enstatite (MgSiO$_3$), Cr-bearing spinel (MgAl$_2$O$_4$), perovskite (CaTiO$_3$), melilite (Ca$_2$Al$_2$SiO$_7$ - Ca$_2$Mg$_2$Si$_2$O$_7$) and/or grossite (CaAl4O7) crystallizing from liquid. Experimental results for forsterite, enstatite, and grossite are in very good agreement with predictions, both in chemistry and phase abundances. On the other hand, the stability of spinel with olivine, and stability of perovskite and gehlenite are quite different from predictions. Perovskite is absent in all experiments. Even at low oxygen fugacity (IW-3.4), the most TiO$_2$-rich experiments do not crystallize Al-, Ti-bearing calcic pyroxene. The stability of spinel and olivine together is limited to a smaller phase field than is predicted. The melilite stability field is much larger than predicted, indicating a deficiency of current liquid or melilite activity models. In that respect, these experiments contribute to improving the data for calibrating thermodynamic models including MELTS., Comment: 17 pages, 5 figures, 5 tables

Full chemical equilibrium calculations of the sequence of condensation of the elements from cosmic gases made by total vaporization of dust-enriched systems were performed to investigate the oxidation state of the resulting condensates. Computations included 23 elements and 374 gas species over a range of -3=log10(total P) to -6 bar and for enrichments to 1000x in dust of C1 chondritic composition relative to a system of solar composition. Because liquids are stable condensates in these systems, the MELTS non-ideal solution model for silicate liquids was used. Condensation at logP=-3 bar and dust enrichments of 100x, 500x and 1000x occurs at oxygen fugacities of IW-3.1, IW-1.7 and IW-1.2, respectively, and, at the temperature of cessation of direct condensation of olivine from the vapor, yields X(fayalite) of 0.019, 0.088 and 0.164, respectively. Silicate liquid is a stable condensate at dust enrichments >~12.5x at logP=-3. At 1000x, the Na and K oxide contents of the last liquid reach 10.1 and 1.3 wt%, respectively, at logP=-3 bar. At logP=-3 bar, iron sulfide liquids are stable condensates at dust enrichments at least as low as 500x, and the predicted distribution of Fe between metal, silicate and sulfide at 1310K and a dust enrichment of 560x matches that found in H chondrites, and at 1330K and 675x matches that of L chondrites prior to metal loss. With some exceptions, many chondrule glass compositions fall along bulk composition trajectories for liquids in equilibrium with cosmic gases at logP=-3 bar and dust enrichments between 600x and 1000x. If these chondrules formed by secondary melting of mixtures of condensates that formed at different T, nebular regions with characteristics such as these would have been necessary to prevent loss of Na by evaporation and FeO by reduction from the liquid precursors, assuming that liquids and gas were hot for enough time to have equilibrated., Comment: 58 pages, 19 figures, 8 tables

Volatility-dependent fractionation of the rock-forming elements at high temperatures is an early, widespread process during formation of the earliest solids in protoplanetary disks. Equilibrium condensation calculations allow prediction of the identities and compositions of mineral and liquid phases coexisting with gas under presumed bulk chemical, pressure and temperature conditions. A graphical survey of such results is presented for systems of solar and non-solar bulk composition. Chemical equilibrium was approached to varying degrees in the local regions where meteoritic chondrules, Ca-Al-rich inclusions, matrix and other components formed. Early, repeated vapor-solid cycling and homogenization, followed by hierarchical accretion in dust-rich regions, is hypothesized for meteoritic inclusions. Disequilibrium chemical effects appear to have been common at all temperatures, but increasingly so in less refractory meteoritic components. Work is needed to better model high-temperature solid solutions, indicators of these processes., Comment: 43 pages, 4 color plates, 2 figures

We determined the mineral-melt partition coefficients (Di's) and the compositional and/or temperature dependency between grossite, melilite, hibonite, olivine and Ca-, Al-inclusion (CAI)-type liquids for a number of light (LE), high field strength (HFSE), large ion lithophile (LILE), and rare earth (REE) elements including Li, Be, B, Sr, Zr, Nb, Ba, La, Ce, Eu, Dy, Ho, Yb, Hf, Ta, Th. A series of isothermal crystallization experiments was conducted at 5 kbar pressure and IW+1 in graphite capsules. The starting compositions were selected based on the calculated and experimentally confirmed phase relations during condensation in CI dust-enriched systems (Ebel and Grossman, 2000; Ebel, 2006; Ustunisik et al., 2014). Partition coefficients between melt and gehlenite, hibonite, and grossite show that the trace element budget of igneous CAIs is controlled by these three major Al-bearing phases in addition to pyroxene. In general, LE, LILE, REE, and HFSE partition coefficients (by mass) decrease in the order of Di(Gehlenite-Melt) > Di(Hibonite-Melt) > Di(Grossite-Melt). Results suggest that Di(Gehlenite-Melt) vary by a factor of 2-3 in different melt compositions at the same T (~1500 C). Increased melt Al and Ca, relative to earlier work, increases the compatibility of Di(Gehlenite-Melt), and also the compatibility of Di(Hibonite-Melt), especially for La and Ce. Olivine partitioning experiments confirm that olivine contribution to the trace element budget of CAIs is small due to the low Di(Olivine-Melt) at a range of temperatures while D-Eu, Yb(Olivine-Melt) are sensitive to changes in T and oxygen fugacity. The development of a predictive model for partitioning in CAI-type systems would require more experimental data and the use of analytical instruments capable of obtaining single phase analyses for crystals < 5 micron., Comment: 23 pages, 15 figures, 5 tables

The bulk volatile contents of chondritic meteorites provide clues to their origins. Matrix and chondrules carry differing abundances of moderately volatile elements, with chondrules carrying a refractory signature. At the high temperatures of chondrule formation and the low pressures of the solar nebula, many elements, including Na and Fe, should have been volatile. Yet the evidence is that even at peak temperatures, at or near the liquidus, Na and Fe (as FeO and Fe-metal) were present in about their current abundances in molten chondrules. This seems to require very high solid densities during chondrule formation to prevent significant evaporation. Evaporation should also be accompanied by isotopic mass fractionation. Evidence from a wide range of isotopic systems indicates only slight isotopic mass fractionations of moderately vola-tile elements, further supporting high solid densities. However, olivine-rich, FeO-poor chondrules commonly have pyroxene-dominated outer zones that have been interpreted as the prod-ucts of late condensation of SiO2 into chondrule melts. Late condensation of more refractory SiO2 is inconsistent with the apparent abundances of more volatile Na, FeO and Fe-metal in many chondrules. Despite significant recent experimental work bearing on this problem, the conditions under which chondrules behaved as open systems remain enigmatic.

The relative abundances and chemical compositions of the macroscopic components or "inclusions" (chondrules and refractory inclusions) and fine-grained mineral matrix in chondritic meteorites provide constraints on astrophysical theories of inclusion formation and chondrite accretion. We present new techniques for analysis of low count per pixel Si, Mg, Ca, Al, Ti and Fe x-ray intensity maps of rock sections, and apply them to large areas of CO and CV chondrites, and the ungrouped Acfer 094 chondrite. For many thousands of manually segmented and type-identified inclusions, we are able to assess, pixel-by-pixel, the major element content of each inclusion. We quantify the total fraction of those elements accounted for by various types of inclusion and matrix. Among CO chondrites, both matrix and inclusion Mg to Si ratios approach the solar (and bulk CO) ratio with increasing petrologic grade, but Si remains enriched in inclusions relative to matrix. The oxidized CV chondrites with higher matrix-inclusion ratios exhibit more severe aqueous alteration (oxidation), and their excess matrix accounts for their higher porosity relative to reduced CV chondrites. Porosity could accommodate an original ice component of matrix as the direct cause of local alteration of oxidized CV chondrites. We confirm that major element abundances among inclusions differ greatly, across a wide range of CO and CV chondrites. These abundances in all cases add up to near-chondritic (solar) bulk abundance ratios in these chondrites, despite wide variations in matrix-inclusion ratios and inclusion sizes: chondrite components are complementary. This "complementarity" provides a robust meteoritic constraint for astrophysical disk models., Comment: 72 pages, 18 figures, 8 tables, with supplementary tables (2) and figues (12). Extended digital supplement available