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Passive imaging through optical obscurants is a promising application for mm-wave sensing. We have thus developed the Superconducting Kinetic Inductance Passive Radiometer (SKIPR), a 150 GHz polarization-sensitive photometric camera optimized for terrestrial imaging using a focal plane array with 3,840 kinetic inductance detectors (KIDs). We present a full description of the instrument design, with a particular emphasis on the cryogenic system based on a Gifford-McMahon cryocooler with a two-stage Adiabatic Demagnetization Refrigerator and a dedicated 1.59 m crossed Dragone telescope with an altitude/azimuth mount. We include a detailed lab-based characterization of the KIDs, which results in a determination of their superconducting resonator parameters and optical properties. We also present in situ measurements from the telescope, including point-spread functions and noise characterization. In sum, we find that SKIPR performs as expected, providing diffraction-limited imaging with detector noise performance set by the random arrivals of photons from the ambient background. There is minimal variation in detector characteristics over the full SKIPR focal plane array, and the overall detector yield is 92 per cent.

Whilst RISC-V has become popular in fields such as embedded computing, it is yet to find mainstream success in High Performance Computing (HPC). However, the 64-core RISC-V Sophon SG2042 is a potential game changer as it provides a commodity available CPU with much higher core count than existing technologies. In this work we benchmark the SG2042 CPU hosted in an experimental, dual-socket, system to explore the performance properties of the CPU when running a common HPC benchmark suite across sockets. Earlier benchmarks found that, on the Milk-V Pioneer workstation, whilst the SG2042 performs well for compute bound codes, it struggles when pressure is placed on the memory subsystem. The performance results reported here confirm that, even on a different system, these memory performance limitations are still present and hence inherent in the CPU. However, a multi-socket configuration does enable the CPU to scale to a larger number of threads which, in the main, delivers an improvement in performance and-so this is a realistic system configuration for the HPC community., Comment: Preprint of paper submitted to RISC-V for HPC workshop at HPC Asia

We present a transfer function-based method to estimate angular power spectra from filtered maps for cosmic microwave background (CMB) surveys. This is especially relevant for experiments targeting the faint primordial gravitational wave signatures in CMB polarisation at large scales, such as the Simons Observatory (SO) small aperture telescopes. While timestreams can be filtered to mitigate the contamination from low-frequency noise, usual methods that calculate the mode coupling at individual multipoles can be challenging for experiments covering large sky areas or reaching few-arcminute resolution. The method we present here, although approximate, is more practical and faster for larger data volumes. We validate it through the use of simulated observations approximating the first year of SO data, going from half-wave plate-modulated timestreams to maps, and using simulations to estimate the mixing of polarisation modes induced by an example of time-domain filtering. We show its performance through an example null test and with an end-to-end pipeline that performs inference on cosmological parameters, including the tensor-to-scalar ratio $r$. The performance demonstration uses simulated observations at multiple frequency bands. We find that the method can recover unbiased parameters for our simulated noise levels., Comment: 15 figures, 2 tables. Comments are welcome

Given a smooth complex variety $X$, an algebraically skew embedding of $X$ is an embedding of $X$ into a complex projective space $\mathbb{P}^N$ such that for any two points $x,y\in X$, their embedded tangent spaces in $\mathbb{P}^N$ do not intersect. In this work, we establish an upper bound and a lower bound of the minimal dimension $N$ such that there exists an algebraically skew embedding into $\mathbb{P}^N$ in terms of the dimension of the given smooth variety $X$. Then we further classify the algebraic curves in terms of their minimal skew embedding dimensions., Comment: 30 pages. Explains the relation to the Terracini loci, and added references. Comments are welcome

We establish necessary and sufficient conditions for suspension flows over certain families of shift spaces to be topologically mixing. We also show the similarities and differences between this case and the smooth measure theoretic setting on a manifold. Additionally, we show that the set of roof functions defined on a shift space that produce suspension flows that are not topologically mixing is dense in the set of all continuous roof functions., Comment: 35 pages

We present results from a high precision experimental study of the nuclear modification of the longitudinal ($F_L$) to transverse ($F_1$) structure function ratio for bound nucleons in the resonance region. The inclusive electron scattering cross sections were measured in Jefferson Lab Experimental Hall C on carbon and deuterium nuclei for a large range of kinematics, allowing for separations of the longitudinal and transverse structure functions to be performed at a range of four-momentum transfer values $0.5 \le Q^2 \le$ 3.75 GeV$^2$. In contrast to the significant body of measurements of the nuclear modification of the $F_2$ structure function in the deep inelastic scattering region, there is very little on $F_L$ and $R = F_L / 2xF_1$ in the region of the nucleon resonances. In this paper we present measurements of the nuclear effect on $R$ for $^{12}$C ($R_C$) relative to deuterium ($R_D$). These results indicate regions in which in $R_C>R_D$, requiring that the nuclear modifications be different in all three structure functions, $F_2$, $F_1$ and $F_L$., Comment: to be published in PRL

The T center in silicon has recently emerged as a promising candidate for scalable quantum technologies, due to its telecommunications band optical transition and microwave addressable ground state spin. The immense promise of the T center is driven by its silicon host material; silicon is by far the most mature, manufacturable semiconductor material for integrated photonic and electronic devices. Here, we present the first study of T-centers in an electrical device. We study an ensemble of T centers coupled to a buried lateral P-I-N diode in silicon, observing the T-center's optical response to static and dynamic electric fields. We utilize the defect's optical response as a probe of device nonlinearity, observing a phase transition of the carrier density into a stable oscillatory regime characteristic of negative differential resistance. These findings provide fundamental insight into the physics of the T-center for improved quantum device performance and open a promising new direction for defect-based local quantum sensing in semiconductor devices.

Contribution: This study presents an evaluation of federally-funded graduate internship outcomes in computational science at a national laboratory. Additionally, we present a survey instrument that may be used for other internship programs with a similar focus. Background: There is ongoing demand for computational scientists to grapple with large-scale problems such as climate change. Internships may help provide additional training and access to greater compute capabilities for graduate students. However, little work has been done to quantify the learning outcomes of such internships. Background: There is ongoing demand for computational scientists to grapple with large-scale problems such as climate change. Internships may help provide additional training and access to greater compute capabilities for graduate students. However, little work has been done to quantify the learning outcomes of such internships. Research Questions: What computational skills, research skills, and professional skills do graduate students improve through their internships at NREL, the national laboratory selected for the study? What sustainability and renewable energy topics do graduate students gain more familiarity with through their internships at NREL? Do graduate students' career interests change after their internships at NREL? Methodology: We developed a survey and collected responses from past participants of five federally-funded internship programs and compare participant ratings of their prior experience to their internship experience. Findings: Our results indicate participants improve their computational skills, familiarity with sustainability and renewable energy topics, and are more interested in working at national labs. Additionally, participants go on to degree programs and positions related to sustainability and renewable energy after their internships., Comment: Submission to IEEE Transactions on Education pending

Core spanners are a class of document spanners that capture the core functionality of IBM's AQL. FC is a logic on strings built around word equations that when extended with constraints for regular languages can be seen as a logic for core spanners. The recently introduced FC-Datalog extends FC with recursion, which allows us to define recursive relations for core spanners. Additionally, as FC-Datalog captures P, it is also a tractable version of Datalog on strings. This presents an opportunity for optimization. We propose a series of FC-Datalog fragments with desirable properties in terms of complexity of model checking, expressive power, and efficiency of checking membership in the fragment. This leads to a range of fragments that all capture LOGSPACE, which we further restrict to obtain linear combined complexity. This gives us a framework to tailor fragments for particular applications. To showcase this, we simulate deterministic regex in a tailored fragment of FC-Datalog.

Generative artificial intelligence (GenAI) holds great promise as a tool to support personalized learning. Teachers need tools to efficiently and effectively enhance content readability of educational texts so that they are matched to individual students reading levels, while retaining key details. Large Language Models (LLMs) show potential to fill this need, but previous research notes multiple shortcomings in current approaches. In this study, we introduced a generalized approach and metrics for the systematic evaluation of the accuracy and consistency in which LLMs, prompting techniques, and a novel multi-agent architecture to simplify sixty informational reading passages, reducing each from the twelfth grade level down to the eighth, sixth, and fourth grade levels. We calculated the degree to which each LLM and prompting technique accurately achieved the targeted grade level for each passage, percentage change in word count, and consistency in maintaining keywords and key phrases (semantic similarity). One-sample t-tests and multiple regression models revealed significant differences in the best performing LLM and prompt technique for each of the four metrics. Both LLMs and prompting techniques demonstrated variable utility in grade level accuracy and consistency of keywords and key phrases when attempting to level content down to the fourth grade reading level. These results demonstrate the promise of the application of LLMs for efficient and precise automated text simplification, the shortcomings of current models and prompting methods in attaining an ideal balance across various evaluation criteria, and a generalizable method to evaluate future systems., Comment: 64 pages, 9 tables, 6 figures, and supplemental materials

In this paper, we contribute a proof that minimum radius balls over metric spaces with the Heine-Borel property are always LP type. Additionally, we prove that weak metric spaces, those without symmetry, also have this property if we fix the direction in which we take their distances from the centers of the balls. We use this to prove that the minimum radius ball problem is LP type in the Hilbert and Thompson metrics and Funk weak metric. In doing so, we contribute a proof that the topology induced by the Thompson metric coincides with the Hilbert. We provide explicit primitives for computing the minimum radius ball in the Hilbert metric.

We propose an architecture for bit flip error correction of Andreev spins that is protected by Kramers' degeneracy. Specifically, we show that a coupling network of linear inductors results in a static Hamiltonian composed of the stabilizers of a bit flip code. Thereby, without detuning from the Kramers' point, reflectometry off a single coupled resonator accomplishes a projective measurement of multiple stabilizers. We further show how circuit-mediated spin couplings enable error correction operations and a complete set of logical quantum gates. The concept is experimentally feasible., Comment: Additional references and discussion

The surface states of intrinsic higher order topological phases are protected by the spatial symmetries of a finite sample. This property makes the existing scattering theory of topological invariants inapplicable because the scattering geometry is either incompatible with the symmetry or does not probe the bulk topology. We resolve this obstacle by using a symmetric scattering geometry that probes transport from the inside to the outside of the sample. We demonstrate that the intrinsic higher order topology is captured by the flux dependence of the reflection matrix. Our finding follows from identifying the spectral flow of a flux line as a signature of higher order topology. We show how this scattering approach applies to several examples of higher order topological insulators and superconductors. Our theory provides an alternative approach for proving bulk--edge correspondence in intrinsic higher order topological phases, especially in presence of disorder.

We consider the problem of how a trusted, but computationally bounded agent (a 'verifier') can learn to interact with one or more powerful but untrusted agents ('provers') in order to solve a given task. More specifically, we study the case in which agents are represented using neural networks and refer to solutions of this problem as neural interactive proofs. First we introduce a unifying framework based on prover-verifier games, which generalises previously proposed interaction protocols. We then describe several new protocols for generating neural interactive proofs, and provide a theoretical comparison of both new and existing approaches. Finally, we support this theory with experiments in two domains: a toy graph isomorphism problem that illustrates the key ideas, and a code validation task using large language models. In so doing, we aim to create a foundation for future work on neural interactive proofs and their application in building safer AI systems., Comment: 42 pages, 17 figures

The Simons Observatory (SO) is a cosmic microwave background (CMB) survey experiment located in the Atacama Desert in Chile at an elevation of 5200 meters, nominally consisting of an array of three 0.42-meter small aperture telescopes (SATs) and one 6-meter large aperture telescope (LAT). SO will make accurate measurements of the CMB temperature and polarization spanning six frequency bands ranging from 27 to 280 GHz, fielding a total of $\sim$68,000 detectors covering angular scales between one arcminute to tens of degrees. In this paper, we focus on the SATs, which are tailored to search for primordial gravitational waves, with the primary science goal of measuring the primordial tensor-to-scalar ratio \textit{r} at a target level of $\sigma(r) \approx 0.003$. We discuss the design drivers, scientific impact, and current deployment status of the three SATs, which are scheduled to start taking data in the coming year. The SATs aim to map 10\% of the sky at a 2 $\mu$K-arcmin noise level observing at mid-frequencies (93/145 GHz), with additional ultra-high-frequency (225/280 GHz) and low-frequency (27/39 GHz) targets to yield galactic foreground-subtracted measurements.

Alloy is a well-known, formal, declarative language for modelling systems early in the software development process. Currently, it uses the Kodkod library as a back-end for finite model finding. Kodkod translates the model to a SAT problem; however, this method can often handle only problems of fairly low-size sets and is inherently finite. We present Portus, a method for translating Alloy into an equivalent many-sorted first-order logic problem (MSFOL). Once in MSFOL, the problem can be evaluated by an SMT-based finite model finding method implemented in the Fortress library, creating an alternative back-end for the Alloy Analyzer. Fortress converts the MSFOL finite model finding problem into the logic of uninterpreted functions with equality (EUF), a decidable fragment of first-order logic that is well-supported in many SMT solvers. We compare the performance of Portus with Kodkod on a corpus of 49 expert Alloy models. Our method is fully integrated into the Alloy Analyzer.

The nonlinear matter power spectrum in cosmology describes how matter density fluctuations vary with scale in the universe, providing critical insights into large-scale structure formation. The matter power spectrum includes both smooth regions and highly oscillatory features. Cosmologists rely on noisy, multi-resolution realizations of large N-body simulations to study these phenomena, which require appropriate smoothing techniques to learn about underlying structures. We introduce a Bayesian Deep Process Convolution (DPC) model that flexibly adapts its smoothness parameter across the input space, enabling it to capture both smooth and variable structure within a single framework. The DPC model leverages common patterns across related functions to improve estimation in regions with sparse data. Compared to existing methods, the DPC model offers superior accuracy and uncertainty quantification in simulated data, and qualitatively superior performance with the cosmological data. This methodology will be useful in cosmology and other fields requiring flexible modeling of smooth nonstationary surfaces.

Promises made by politicians, corporate leaders, and public figures have a significant impact on public perception, trust, and institutional reputation. However, the complexity and volume of such commitments, coupled with difficulties in verifying their fulfillment, necessitate innovative methods for assessing their credibility. This paper introduces the concept of Promise Verification, a systematic approach involving steps such as promise identification, evidence assessment, and the evaluation of timing for verification. We propose the first multilingual dataset, ML-Promise, which includes English, French, Chinese, Japanese, and Korean, aimed at facilitating in-depth verification of promises, particularly in the context of Environmental, Social, and Governance (ESG) reports. Given the growing emphasis on corporate environmental contributions, this dataset addresses the challenge of evaluating corporate promises, especially in light of practices like greenwashing. Our findings also explore textual and image-based baselines, with promising results from retrieval-augmented generation (RAG) approaches. This work aims to foster further discourse on the accountability of public commitments across multiple languages and domains., Comment: 6 pages

Organic molecular ferroelectrics, including organic proton-transfer ferroelectrics and antiferroelectrics, are potentially attractive in organic electronics and have significant chemical tunability. Among these, acid-base proton transfer (PT) salts stand out due to their low coercive fields and the possibility to tune their properties with different acid-base combinations. Using crystal structure prediction, combining small acid and base organic molecular species, we here predict three novel acid-base PT ferroelectric salts with higher polarization than existing materials. We also report two combinations that form antiferroelectric crystal structures. However, some combinations also result in unfavorable packing or the formation of co-crystal or in one case a divalent salt. The protonation state is found to be highly linked to the crystal structure, with cases where salt crystal structures have the same energetic preferability as co-crystals with a different crystalline packing.

Future far-infrared (IR) observatories require compact and cost efficient optical linear variable bandpass filters (LVBFs) to define their instrument spectral bands. We have designed novel far-IR LVBFs that consist of metal-mesh bandpass filters comprised of a gold film with cross-slots of varying sizes along a silicon (Si) substrate with anti-reflection (AR) coatings. We present our work on the simulated and measured transmission of non-AR coated and AR coated LVBFs for bandpass peaks from wavelengths of 24 to 36 $\mu$m with a resolving power ($R=\lambda_0/\Delta\lambda$) of R$\approx$6 for non-AR coated LVBFs and R$\approx$4 for AR coated LVBFs. We also present a method to decrease the effects of out-of-band high frequency transmission exhibited by metal-mesh filters by depositing a thin layer of hydrogenated amorphous silicon (a-Si:H) on the metal-mesh of the LVBF. We have fabricated and measured the LVBFs at room temperature and cryogenic temperatures (5 K). We measure a high peak transmission of $\sim$80-90 \% for the AR coated LVBF at 5 K and demonstrate that the a-Si:H LVBF is a promising method to address out-of-band high frequency transmission., Comment: 8 pages, 10 figures, accepted to Applied Optics

Nucleon structure functions, as measured in lepton-nucleon scattering, have historically provided a critical observable in the study of partonic dynamics within the nucleon. However, at very large parton momenta it is both experimentally and theoretically challenging to extract parton distributions due to the probable onset of non-perturbative contributions and the unavailability of high precision data at critical kinematics. Extraction of the neutron structure and the d-quark distribution have been further challenging due to the necessity of applying nuclear corrections when utilizing scattering data from a deuteron target to extract free neutron structure. However, a program of experiments has been carried out recently at the energy-upgraded Jefferson Lab electron accelerator aimed at significantly reducing the nuclear correction uncertainties on the d-quark distribution function at large partonic momentum. This allows leveraging the vast body of deuterium data covering a large kinematic range to be utilized for d-quark parton distribution function extraction. We present new data from experiment E12-10-002 carried out in Jefferson Lab Hall C on the deuteron to proton cross-section ratio at large BJorken-x. These results significantly improve the precision of existing data, and provide a first look at the expected impact on quark distributions extracted from global parton distribution function fits.

Infectious diseases, transmitted directly or indirectly, are among the leading causes of epidemics and pandemics. Consequently, several open challenges exist in predicting epidemic outbreaks, detecting variants, tracing contacts, discovering new drugs, and fighting misinformation. Artificial Intelligence (AI) can provide tools to deal with these scenarios, demonstrating promising results in the fight against the COVID-19 pandemic. AI is becoming increasingly integrated into various aspects of society. However, ensuring that AI benefits are distributed equitably and that they are used responsibly is crucial. Multiple countries are creating regulations to address these concerns, but the borderless nature of AI requires global cooperation to define regulatory and guideline consensus. Considering this, The Global South AI for Pandemic & Epidemic Preparedness & Response Network (AI4PEP) has developed an initiative comprising 16 projects across 16 countries in the Global South, seeking to strengthen equitable and responsive public health systems that leverage Southern-led responsible AI solutions to improve prevention, preparedness, and response to emerging and re-emerging infectious disease outbreaks. This opinion introduces our branches in Latin American and Caribbean (LAC) countries and discusses AI governance in LAC in the light of biotechnology. Our network in LAC has high potential to help fight infectious diseases, particularly in low- and middle-income countries, generating opportunities for the widespread use of AI techniques to improve the health and well-being of their communities.

We determine necessary and sufficient conditions for unicritical polynomials to be dynamically irreducible over finite fields. This result extends the results of Boston-Jones and Hamblen-Jones-Madhu regarding the dynamical irreducibility of particular families of unicritical polynomials. We also investigate dynamical irreducibility conditions for cubic and shifted linearized polynomials.

Periodic laser driving, known as Floquet engineering, is a powerful tool to manipulate the properties of quantum materials. Using circularly polarized light, artificial magnetic fields, called Berry curvature, can be created in the photon-dressed Floquet-Bloch states that form. This mechanism, when applied to 3D Dirac and Weyl systems, is predicted to lead to photon-dressed movement of Weyl nodes which should be detectable in the transport sector. The transport response of such a topological light-matter hybrid, however, remains experimentally unknown. Here, we report on the transport properties of the type-II Weyl semimetal T$\mathrm{_d}$-MoTe$_\mathrm{2}$ illuminated by a femtosecond pulse of circularly polarized light. Using an ultrafast optoelectronic device architecture, we observed injection currents and a helicity-dependent anomalous Hall effect whose scaling with laser field strongly deviate from the perturbative laws of nonlinear optics. We show using Floquet theory that this discovery corresponds to the formation of a magnetic Floquet-Weyl semimetal state. Numerical ab initio simulations support this interpretation, indicating that the light-induced motion of the Weyl nodes contributes substantially to the measured transport signals. This work demonstrates the ability to generate large effective magnetic fields ($>$ 30T) with light, which can be used to manipulate the magnetic and topological properties of a range of quantum materials.

The Next-generation Extended Wavelength-MUltiband Sub/millimeter Inductance Camera (NEW-MUSIC) on the Leighton Chajnantor Telescope (LCT) will be a first-of-its-kind, six-band, transmillimeter-wave ("trans-mm") polarimeter covering 2.4 octaves of spectral bandwidth to open a new window on the trans-mm time-domain frontier, in particular new frontiers in energy, density, time, and magnetic field. NEW-MUSIC's broad spectral coverage will also enable the use of the Sunyaev-Zeldovich effects to study accretion, feedback, and dust content in the hot gaseous haloes of galaxies and galaxy clusters. Six-band spectral energy distributions, with polarization information, will yield new insights into stellar and planetary nurseries. NEW-MUSIC will employ hierarchical, phased arrays of polarization-sensitive superconducting slot-dipole antennas, coupled to photolithographic bandpass filters, to nearly optimally populate LCT's 14' field-of-view with six spectral bands over 80-420 GHz (1:5.25 spectral dynamic range; 2.4 octaves). Light will be routed to Al or AlMn microstripline-coupled, parallel-plate capacitor, lumped-element kinetic inductance detectors (MS-PPC-LEKIDs), an entirely new KID architecture that substantially enhances design flexibility while providing background-limited performance. Innovative, wide-bandwidth, etched silicon structures will be used to antireflection-treat the back-illuminated focal plane. NEW-MUSIC will cost-effectively reuse much of the MUSIC instrument, initially deploying a quarter-scale focal plane capable of the bulk of NEW-MUSIC science followed later by a full-FoV focal plane needed for NEW-MUSIC wide-area survey science., Comment: 42 pages, 16 figures. This version includes minor corrections relative to the version published at the SPIE website. Versions 2 and 3 include only affiliation corrections