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The pivotal role of Algebra in the educational trajectories of U.S. students continues to motivate controversial, high-profile policies focused on when students access the course, their classroom peers, and how the course is taught. This random-assignment partnership study examines an innovative district-level reform--the Algebra I Initiative--that placed 9th-grade students with prior math scores well below grade level into Algebra I classes coupled with teacher training instead of a remedial pre-Algebra class. We find that this reform significantly increased grade-11 math achievement (ES = 0.2 SD) without lowering the achievement of classroom peers eligible for conventional Algebra I classes. This initiative also increased attendance, district retention, and overall math credits. These results suggest that higher expectations for the lowest-performing students coupled with aligned teacher supports is a promising model for realizing students' mathematical potential. [The Stanford Sequoia K-12 Research Collaborative provided support for this paper.]

AI is the workhorse of modern data analytics and omnipresent across many sectors. Large Language Models and multi-modal foundation models are today capable of generating code, charts, visualizations, etc. How will these massive developments of AI in data analytics shape future data visualizations and visual analytics workflows? What is the potential of AI to reshape methodology and design of future visual analytics applications? What will be our role as visualization researchers in the future? What are opportunities, open challenges and threats in the context of an increasingly powerful AI? This Visualization Viewpoint discusses these questions in the special context of biomedical data analytics as an example of a domain in which critical decisions are taken based on complex and sensitive data, with high requirements on transparency, efficiency, and reliability. We map recent trends and developments in AI on the elements of interactive visualization and visual analytics workflows and highlight the potential of AI to transform biomedical visualization as a research field. Given that agency and responsibility have to remain with human experts, we argue that it is helpful to keep the focus on human-centered workflows, and to use visual analytics as a tool for integrating ``AI-in-the-loop''. This is in contrast to the more traditional term ``human-in-the-loop'', which focuses on incorporating human expertise into AI-based systems., Comment: Accepted for publication in IEEE Computer Graphics & Applications

We present observations of ASASSN-22ci (AT2022dbl), a nearby tidal disruption event (TDE) discovered by the All-Sky Automated Survey for Supernovae (ASAS-SN) at a distance of d$_L \simeq 125$ Mpc. Roughly two years after the initial ASAS-SN discovery, a second flare was detected coincident with ASASSN-22ci. UV/optical photometry and optical spectroscopy indicate that both flares are likely powered by TDEs. The striking similarity in flare properties suggests that these flares result from subsequent disruptions of the same star. Each flare rises on a timescale of $\sim$30 days, has a temperature of $\approx$30,000 K, a peak bolometric luminosity of $L_{UV/Opt} = 10^{43.6 - 43.9} \textrm{ erg} \textrm{ s}^{-1}$, and exhibits a blue optical spectrum with broad H, He, and N lines. No X-ray emission is detected during either flare, but X-ray emission with an unabsorbed luminosity of $L_{X} = 3\times10^{41} \textrm{ erg} \textrm{ s}^{-1}$ and $kT = 0.042$ eV is observed between the flares. Pre-discovery survey observations rule out the existence of earlier flares within the past $\approx$6000 days, indicating that the discovery of ASASSN-22ci likely coincides with the first flare. If the observed flare separation of $720 \pm 4.7$ days is the orbital period, the next flare of ASASSN-22ci should occur near MJD 61075 (2026 February 04). Finally, we find that the existing sample of repeating TDE candidates is consistent with Hills capture of a star initially in a binary with a total mass between $\sim$$1 - 4$ M$_{\odot}$ and a separation of $\sim$$0.01 - 0.1$ AU., Comment: 30 pages, 15 figures, 4 tables. Comments welcome

Science and engineering problems fall in the category of complex conceptual problems that require specific conceptual information (CI) like math/logic -related know-how, process information, or engineering guidelines to solve them. Large Language Models (LLMs) are promising agents to solve such complex conceptual problems due to their implications in advancing engineering and science tasks like assisted problem-solving. But vanilla LLMs, trained on open-world data, lack the necessary CI. In this work, we specifically explore shallow customization methods (SCMs) of LLMs for solving complex conceptual problems. We propose two novel SCM algorithms for LLM, to augment LLMs with CI and enable LLMs to solve complex conceptual problems: Conceptual In-Context Learning (C-ICL) and Chain of Concepts (CoC). The problem tackled in this paper is generation of proprietary data models in the engineering/industry domain based on conceptual information in data modelling guidelines. We evaluate our algorithms on varied sizes of the OpenAI LLMs against four evaluation metrics related to syntactic and semantic correctness, time and cost incurred. The proposed algorithms perform better than currently popular LLM SCMs like In-context Learning (ICL) and Chain of Thoughts (CoT). It was observed that as compared to CoT, response correctness increased by 30.6% and 29.88% for the new SCMs C-ICL and CoC respectively. Qualitative analysis suggests that the proposed new SCMs activate emergent capabilities in LLMs, previously unobserved in the existing SCMs. They make problem-solving processes more transparent and reduce hallucinations and the tendency of model responses to copy examples from prompts (parroting)., Comment: Accepted to 2025 IEEE Symposium on Computational Intelligence in Natural Language Processing and Social Media

Scaling has not yet been convincingly demonstrated for pure self-supervised learning from video. However, prior work has focused evaluations on semantic-related tasks $\unicode{x2013}$ action classification, ImageNet classification, etc. In this paper we focus on evaluating self-supervised learning on non-semantic vision tasks that are more spatial (3D) and temporal (+1D = 4D), such as camera pose estimation, point and object tracking, and depth estimation. We show that by learning from very large video datasets, masked auto-encoding (MAE) with transformer video models actually scales, consistently improving performance on these 4D tasks, as model size increases from 20M all the way to the largest by far reported self-supervised video model $\unicode{x2013}$ 22B parameters. Rigorous apples-to-apples comparison with many recent image and video models demonstrates the benefits of scaling 4D representations.

We present a structural analysis of 521 galaxy candidates at 6.5 < z < 12.5, with $SNR > 10\sigma$ in the F444W filter, taken from the EPOCHS v1 sample, consisting of uniformly reduced deep JWST NIRCam data, covering the CEERS, JADES GOOD-S, NGDEEP, SMACS0723, GLASS and PEARLS surveys. We use standard software to fit single S\'ersic models to each galaxy in the rest-frame optical and extract their parametric structural parameters (S\'ersic index, half-light radius and axis-ratio), and \texttt{Morfometryka} to measure their non-parametric concentration and asymmetry parameters. We find a wide range of sizes for these early galaxies, but with a strong galaxy-size mass correlation up to $z \sim 12$ such that galaxy sizes continue to get progressively smaller in the high-redshift regime, following $R_{e} = 2.74 \pm 0.49 \left( 1 + z \right) ^{-0.79 \pm 0.08}$ kpc. Using non-parametric methods we find that galaxy merger fractions, classified through asymmetry parameters, at these redshifts remain consistent with those in literature, maintaining a value of $f_{m} \sim 0.12 \pm 0.07$ showing little dependence with redshift when combined with literature at $z > 4$. We find that galaxies which are smaller in size also appear rounder, with an excess of high axis-ratio objects. Finally, we artificially redshift a subsample of our objects to determine how robust the observational trends we see are, determining that observed trends are due to real evolutionary effects, rather than being a consequence of redshift effects., Comment: 35 pages, 13 figures. Submitted to ApJ on 19/12/2024. Comments to corresponding author welcome at lewi.westcott@manchester.ac.uk

This summary of the second Terrestrial Very-Long-Baseline Atom Interferometry (TVLBAI) Workshop provides a comprehensive overview of our meeting held in London in April 2024, building on the initial discussions during the inaugural workshop held at CERN in March 2023. Like the summary of the first workshop, this document records a critical milestone for the international atom interferometry community. It documents our concerted efforts to evaluate progress, address emerging challenges, and refine strategic directions for future large-scale atom interferometry projects. Our commitment to collaboration is manifested by the integration of diverse expertise and the coordination of international resources, all aimed at advancing the frontiers of atom interferometry physics and technology, as set out in a Memorandum of Understanding signed by over 50 institutions., Comment: Summary of the second Terrestrial Very-Long-Baseline Atom Interferometry Workshop held at Imperial College London: https://indico.cern.ch/event/1369392/

The digital transformation of production requires new methods of data integration and storage, as well as decision making and support systems that work vertically and horizontally throughout the development, production, and use cycle. In this paper, we propose Data-to-Knowledge (and Knowledge-to-Data) pipelines for production as a universal concept building on a network of Digital Shadows (a concept augmenting Digital Twins). We show a proof of concept that builds on and bridges existing infrastructure to 1) capture and semantically annotates trajectory data from multiple similar but independent robots in different organisations and use cases in a data lakehouse and 2) an independent process that dynamically queries matching data for training an inverse dynamic foundation model for robotic control. The article discusses the challenges and benefits of this approach and how Data-to-Knowledge pipelines contribute efficiency gains and industrial scalability in a World Wide Lab as a research outlook., Comment: 15 pages, 6 figures, submitted to CAiSE 2025

The first JWST/MIRI photometric observations of TRAPPIST-1 b allowed for the detection of the thermal emission of the planet at 15 $\mu m$, suggesting that the planet could be a bare rock with a zero albedo and no redistribution of heat. These observations at 15 $\mu m$ were acquired as part of GTO time that included a twin program at 12.8 $\mu m$ in order to have a measurement in and outside the CO$_2$ absorption band. Here we present five new occultations of TRAPPIST-1 b observed with MIRI in an additional photometric band at 12.8 $\mu m$. We perform a global fit of the 10 eclipses and derive a planet-to-star flux ratio and 1-$\sigma$ error of 452 $\pm$ 86 ppm and 775 $\pm$ 90 ppm at 12.8 $\mu m$ and 15 $\mu m$, respectively. We find that two main scenarios emerge. An airless planet model with an unweathered (fresh) ultramafic surface, that could be indicative of relatively recent geological processes fits well the data. Alternatively, a thick, pure-CO2 atmosphere with photochemical hazes that create a temperature inversion and result in the CO2 feature being seen in emission also works, although with some caveats. Our results highlight the challenges in accurately determining a planet's atmospheric or surface nature solely from broadband filter measurements of its emission, but also point towards two very interesting scenarios that will be further investigated with the forthcoming phase curve of TRAPPIST-1 b., Comment: 49 pages, 3 main text figure, 2 extended figures, 10 supplementary figures, accepted for publication in Nature Astronomy on October 29, 2024

Structure determination is essential to a mechanistic understanding of diseases and the development of novel therapeutics. Machine-learning-based structure prediction methods have made significant advancements by computationally predicting protein and bioassembly structures from sequences and molecular topology alone. Despite substantial progress in the field, challenges remain to deliver structure prediction models to real-world drug discovery. Here, we present NeuralPLexer3 -- a physics-inspired flow-based generative model that achieves state-of-the-art prediction accuracy on key biomolecular interaction types and improves training and sampling efficiency compared to its predecessors and alternative methodologies. Examined through newly developed benchmarking strategies, NeuralPLexer3 excels in vital areas that are crucial to structure-based drug design, such as physical validity and ligand-induced conformational changes.

Magnetic Resonance Fingerprinting (MRF) is an emerging technology with the potential to revolutionize radiology and medical diagnostics. In comparison to traditional magnetic resonance imaging (MRI), MRF enables the rapid, simultaneous, non-invasive acquisition and reconstruction of multiple tissue parameters, paving the way for novel diagnostic techniques. In the original matching approach, reconstruction is based on the search for the best matches between in vivo acquired signals and a dictionary of high-dimensional simulated signals (fingerprints) with known tissue properties. A critical and limiting challenge is that the size of the simulated dictionary increases exponentially with the number of parameters, leading to an extremely costly subsequent matching. In this work, we propose to address this scalability issue by considering probabilistic mixtures of high-dimensional elliptical distributions, to learn more efficient dictionary representations. Mixture components are modelled as flexible ellipitic shapes in low dimensional subspaces. They are exploited to cluster similar signals and reduce their dimension locally cluster-wise to limit information loss. To estimate such a mixture model, we provide a new incremental algorithm capable of handling large numbers of signals, allowing us to go far beyond the hardware limitations encountered by standard implementations. We demonstrate, on simulated and real data, that our method effectively manages large volumes of MRF data with maintained accuracy. It offers a more efficient solution for accurate tissue characterization and significantly reduces the computational burden, making the clinical application of MRF more practical and accessible.

Systems with pronounced spin anisotropy play a pivotal role in advancing magnetization switching and spin-wave generation mechanisms, which are fundamental for spintronic technologies. Quasi-van der Waals ferromagnets, particularly Cr$_{1+\delta}$Te$_2$ compounds, represent seminal materials in this field, renowned for their delicate balance between frustrated layered geometries and magnetism. Despite extensive investigation, the precise nature of their magnetic ground state, typically described as a canted ferromagnet, remains contested, as does the mechanism governing spin reorientation under external magnetic fields and varying temperatures. In this work, we leverage a multimodal approach, integrating complementary techniques, to reveal that Cr$_{1+\delta}$Te$_2$ ($\delta = 0.25 - 0.50$) hosts a previously overlooked magnetic phase, which we term orthogonal-ferromagnetism. This single phase consists of alternating atomically sharp single layers of in-plane and out-of-plane ferromagnetic blocks, coupled via exchange interactions and as such, it differs significantly from crossed magnetism, which can be achieved exclusively by stacking multiple heterostructural elements together. Contrary to earlier reports suggesting a gradual spin reorientation in CrTe$_2$-based systems, we present definitive evidence of abrupt spin-flop-like transitions. This discovery, likely due to the improved crystallinity and lower defect density in our samples, repositions Cr$_{1+\delta}$Te$_2$ compounds as promising candidates for spintronic and orbitronic applications, opening new pathways for device engineering.

The conventional way of generating optical waveforms relies on the in-phase and quadrature (IQ) modulation of a continuous wave (CW) laser tone. In this case, the bandwidth of the resulting optical waveform is limited by the underlying electronic components, in particular by the digital-to-analog converters (DACs) generating the drive signals for the IQ modulator. This bandwidth bottleneck can be overcome by using a concept known as optical arbitrary waveform generation (OAWG), where multiple IQ modulators and DACs are operated in parallel to first synthesize individual spectral slices, which are subsequently combined to form a single ultra-broadband arbitrary optical waveform. However, targeted synthesis of arbitrary optical waveforms from multiple spectral slices has so far been hampered by difficulties to maintain the correct optical phase relationship between the slices. In this paper, we propose and demonstrate spectrally sliced OAWG with active phase stabilization, which permits targeted synthesis of truly arbitrary optical waveforms. We demonstrate the viability of the scheme by synthesizing optical waveforms with record-high bandwidths of up to 325 GHz from four individually generated optical tributaries. In a proof-of-concept experiment, we use the OAWG system to generate 32QAM data signals at symbol rates of up to 320 GBd, which we transmit over 87 km of single-mode fiber and receive by a two-channel non-sliced optical arbitrary waveform measurement (OAWM) system, achieving excellent signal quality. We believe that our scheme can unlock the full potential of OAWG and disrupt a wide range of applications in high-speed optical communications, photonic-electronic digital-to-analog conversion, as well as advanced test and measurement in science and industry.

This work focuses on model preparation for electrostatic simulations of CAD designs to realize a rapid virtual prototyping concept. We present a boundary element method (BEM) allowing discontinuous fields between surfaces. The corresponding edges of the CAD model are enhanced with the data required to integrate over non-conforming elements. Finally, we generate a mesh for each CAD surface. The approach is verified via numerical experiments and shows excellent agreement with conforming BEM results.

As superconducting kinetic inductance detectors (KIDs) continue to grow in popularity for sensitive sub-mm detection and other applications, there is a drive to advance toward lower loss devices. We present measurements of diagnostic thin film aluminum coplanar waveguide (CPW) resonators designed to inform ongoing KID development at NASA Goddard Space Flight Center. The resonators span $\rm f_0 = 3.5 - 4$\,GHz and include both quarter-wave and half-wave resonators with varying coupling capacitor designs. We present measurements of the device film properties and an analysis of the dominant mechanisms of loss in the resonators measured in a dark environment. We demonstrate quality factors of $\rm Q_i^{-1} \approx 3.64 - 8.57 \times10^{-8}$, and observe enhanced suppression of two-level system (TLS) loss in our devices at high internal microwave power levels before the onset of quasiparticle dissipation from microwave heating. We observe deviations from the standard TLS loss model at low powers and temperatures below 60 mK, and use a modified model to describe this behavior., Comment: 8 pages, 5 figures, submitted to Physical Review Applied Letters

We investigate the nonequilibrium dynamics of a groundstate fermionic many body gas subjected to a quench between parameter regimes of a topologically nontrivial Hamiltonian. By focusing on the role of the chiral edge states inherent to the system, we calculate the many body overlap and show that the characteristic monotonic decay of the orthogonality catastrophe with increasing system size is notably altered. Specifically, we demonstrate that the dynamics are governed not solely by the total particle number but rather by the number of occupied single particle edge states. This behavior is further explained through an analysis of the full work probability distribution, providing a deeper understanding of the system's dynamics., Comment: 9 pages,7 figures

The coordination of vehicles is a crucial element of autonomous driving, as it enhances the efficiency, convenience, and safety of road traffic. In order to fully exploit the capabilities of such coordination, communication with high data rate and low latency is required. It can be reasonably argued that millimeter-wave (mm-wave) vehicle-to-vehicle (V2V) systems are capable of fulfilling the aforementioned requirements. Nevertheless, in order to develop a system that can be deployed in real-world scenarios and to gain an understanding of the various effects of mm-wave propagation, it is necessary to perform radio propagation measurements and to derive radio channel models from them across a range of scenarios and environments. To this end, we have conducted measurement campaigns at 60\,GHz in a variety of situations, including driving in a convoy, driving in opposite direction on a six-lane road, and overtaking. These measurements employ a channel sounder based on ReRoMA, a recently introduced concept that enables the real-time measurement of dynamic double-directional radio channels. The evaluations presented herein encompass key channel parameters, including the path loss (path loss coefficient of approximately 1.9), the root mean square (RMS) delay spread (within a range of 5\,ns to 110\,ns), the angular spreads (in a range of 0.05 to 0.4), the power distribution among multipath components, and the channel stationarity time (multiple seconds)., Comment: 15 pages

The recently launched James Webb Space Telescope (JWST) is opening new observing windows on the distant universe. Among JWST's instruments, the Mid Infrared Instrument (MIRI) offers the unique capability of imaging observations at wavelengths $\lambda > 5\mu$m. This enables unique access to the rest frame near infra-red (NIR, $\lambda \ge 1$\mum) emission from galaxies at redshifts $z>4$ and the visual ($\lambda \gtrsim 5000$\AA) rest frame for $z>9$. We here report on the guaranteed time observations (GTO) from the MIRI European Consortium, of the Hubble Ultra Deep Field (HUDF), forming the MIRI Deep Imaging Survey (MIDIS), consisting of an on source integration time of $\sim41$ hours in the MIRI/F560W (5.6 $\mu$m) filter. To our knowledge, this constitutes the longest single filter exposure obtained with JWST of an extragalactic field as yet., Comment: submitted to A&A on July 30, 2024

We propose shortcut to adiabaticity protocols for Bose-Einstein condensates trapped in generalized anisotropic harmonic traps in three dimensions. These protocols enable high-fidelity tuning of trap geometries on time scales much faster than those required for adiabatic processes and are robust across a wide range of interaction strengths, from weakly interacting regimes to the Thomas-Fermi limit. Using the same approach, we also design STA paths to rapidly drive interaction strengths in both isotropic and anisotropic traps. Comparisons with standard linear ramps of system parameters demonstrate significant improvements in performance. Finally, we apply these STA techniques to a unitary engine cycle with a BEC as the working medium. The STA methods significantly enhance the engine's power output without reducing efficiency and remain highly effective even after multiple consecutive cycles., Comment: 10 pages, 5 figures

High-Performance Computing (HPC) systems are among the most energy-intensive scientific facilities, with electric power consumption reaching and often exceeding 20 megawatts per installation. Unlike other major scientific infrastructures such as particle accelerators or high-intensity light sources, which are few around the world, the number and size of supercomputers are continuously increasing. Even if every new system generation is more energy efficient than the previous one, the overall growth in size of the HPC infrastructure, driven by a rising demand for computational capacity across all scientific disciplines, and especially by artificial intelligence workloads (AI), rapidly drives up the energy demand. This challenge is particularly significant for HPC centers in Germany, where high electricity costs, stringent national energy policies, and a strong commitment to environmental sustainability are key factors. This paper describes various state-of-the-art strategies and innovations employed to enhance the energy efficiency of HPC systems within the national context. Case studies from leading German HPC facilities illustrate the implementation of novel heterogeneous hardware architectures, advanced monitoring infrastructures, high-temperature cooling solutions, energy-aware scheduling, and dynamic power management, among other optimizations. By reviewing best practices and ongoing research, this paper aims to share valuable insight with the global HPC community, motivating the pursuit of more sustainable and energy-efficient HPC operations., Comment: 30 pages, 3 figures, 4 tables

Sub-Neptunes - volatile-rich exoplanets smaller than Neptune - are intrinsically the most common type of planet known. However, the formation and nature of these objects, as well as the distinctions between sub-classes (if any), remain unclear. Two powerful tools to tease out the secrets of these worlds are measurements of (i) atmospheric composition and structure revealed by transit and/or eclipse spectroscopy, and (ii) mass, radius, and density revealed by transit photometry and Doppler spectroscopy. Here we present OrCAS, a survey to better elucidate the origins, compositions, and atmospheres of sub-Neptunes. This radial velocity survey uses a repeatable, quantifiable metric to select targets suitable for subsequent transmission spectroscopy and address key science themes about the atmospheric & internal compositions and architectures of these systems. Our survey targets 26 systems with transiting sub-Neptune planet candidates, with the overarching goal of increasing the sample of such planets suitable for subsequent atmospheric characterization. This paper lays out our survey's science goals, defines our target prioritization metric, and performs light-curve fits and statistical validation using existing TESS photometry and ground-based follow-up observations. Our survey serves to continue expanding the sample of small exoplanets with well-measured properties orbiting nearby bright stars, ensuring fruitful studies of these systems for many years to come., Comment: 20 pages, 4 figures, 4 tables, 26 sub-Neptunes, 31 TOIs. Accepted to AJ

Spectroscopic techniques are essential for studying material properties, but the small cross-sections of some methods may result in low signal-to-noise ratios (SNRs) in the collected spectra. In this article we present methods, based on combining Bragg spectroscopy with photon counting and deconvolution algorithms, which increase the SNRs, making the spectra better suited to further analysis. We aim to provide a comprehensive guide for constructing spectra from camera images. The efficacy of these methods is validated on synthetic and experimental data, the latter coming from the field of high-energy density (HED) science, where x-ray spectroscopy is essential for the understanding of materials under extreme thermodynamic conditions.

On May 24th, 2023, the Advanced Laser Interferometer Gravitational-Wave Observatory (LIGO), joined by the Advanced Virgo and KAGRA detectors, began the fourth observing run for a two-year-long dedicated search for gravitational waves. The LIGO Hanford and Livingston detectors have achieved an unprecedented sensitivity to gravitational waves, with an angle-averaged median range to binary neutron star mergers of 152 Mpc and 160 Mpc, and duty cycles of 65.0% and 71.2%, respectively, with a coincident duty cycle of 52.6%. The maximum range achieved by the LIGO Hanford detector is 165 Mpc and the LIGO Livingston detector 177 Mpc, both achieved during the second part of the fourth observing run. For the fourth run, the quantum-limited sensitivity of the detectors was increased significantly due to the higher intracavity power from laser system upgrades and replacement of core optics, and from the addition of a 300 m filter cavity to provide the squeezed light with a frequency-dependent squeezing angle, part of the A+ upgrade program. Altogether, the A+ upgrades led to reduced detector-wide losses for the squeezed vacuum states of light which, alongside the filter cavity, enabled broadband quantum noise reduction of up to 5.2 dB at the Hanford observatory and 6.1 dB at the Livingston observatory. Improvements to sensors and actuators as well as significant controls commissioning increased low frequency sensitivity. This paper details these instrumental upgrades, analyzes the noise sources that limit detector sensitivity, and describes the commissioning challenges of the fourth observing run., Comment: 26 pages, 18 figures

It is widely assumed that dust opacities in molecular clouds follow a power-law profile with an index, $\beta$. Recent studies of the Orion Molecular Cloud (OMC) 2/3 complex, however, show a flattening in the spectral energy distribution (SED) at $ \lambda > 2$ mm implying non-constant indices on scales $\gtrsim$ 0.08 pc. The origin of this flattening is not yet known but it may be due to the intrinsic properties of the dust grains or contamination from other sources of emission. We investigate the SED slopes in OMC 2/3 further using observations of six protostellar cores with NOEMA from 2.9 mm to 3.6 mm and ALMA-ACA in Band 4 (1.9 -- 2.1 mm) and Band 5 (1.6 -- 1.8 mm) on core and envelope scales of $\sim 0.02 - 0.08$ pc. We confirm flattened opacity indices between 2.9 mm and 3.6 mm for the six cores with $\beta \approx -0.16 - 1.45$, which are notably lower than the $\beta$ values of $> 1.3$ measured for these sources on $0.08$ pc scales from single-dish data. Four sources have consistent SED slopes between the ALMA data and the NOEMA data. We propose that these sources may have a significant fraction of emission coming from large dust grains in embedded disks, which biases the emission more at longer wavelengths. Two sources, however, had inconsistent slopes between the ALMA and NOEMA data, indicating different origins of emission. These results highlight how care is needed when combining multi-scale observations or extrapolating single-band observations to other wavelengths., Comment: Accepted to ApJ, 18 pages, 4 figures, 6 Tables

We elaborate and validate a generalization of the renowned transition-path-sampling algorithm for a paradigmatic model of active particles, namely the Run-and-Tumble particles. Notwithstanding the non-equilibrium character of these particles, we show how the consequent lack of the microscopical reversibility property, which is usually required by transition-path sampling, can be circumvented by identifying reasonable backward dynamics with a well-defined path-probability density. Our method is then applied to characterize the structure and kinetics of rare transition pathways undergone by Run-and-Tumble particles having to cross a potential barrier in order to find a target., Comment: 16 pages, 7 figures

Transitioning from quantum computation on physical qubits to quantum computation on encoded, logical qubits can improve the error rate of operations, and will be essential for realizing valuable quantum computational advantages. Using a neutral atom quantum processor with 256 qubits, each an individual Ytterbium atom, we demonstrate the entanglement of 24 logical qubits using the distance-two [[4,2,2]] code, simultaneously detecting errors and correcting for lost qubits. We also implement the Bernstein-Vazirani algorithm with up to 28 logical qubits encoded in the [[4,1,2]] code, showing better-than-physical error rates. We demonstrate fault-tolerant quantum computation in our approach, guided by the proposal of Gottesman (2016), by performing repeated loss correction for both structured and random circuits encoded in the [[4,2,2]] code. Finally, since distance-two codes can correct qubit loss, but not other errors, we show repeated loss and error correction using the distance-three [[9,1,3]] Bacon-Shor code. These results begin to clear a path for achieving scientific quantum advantage with a programmable neutral atom quantum processor., Comment: 17 pages, 16 figures

Multimodal learning, which involves integrating information from various modalities such as text, images, audio, and video, is pivotal for numerous complex tasks like visual question answering, cross-modal retrieval, and caption generation. Traditional approaches rely on modality-specific encoders and late fusion techniques, which can hinder scalability and flexibility when adapting to new tasks or modalities. To address these limitations, we introduce a novel framework that extends the concept of task reformulation beyond natural language processing (NLP) to multimodal learning. We propose to reformulate diverse multimodal tasks into a unified next-frame prediction problem, allowing a single model to handle different modalities without modality-specific components. This method treats all inputs and outputs as sequential frames in a video, enabling seamless integration of modalities and effective knowledge transfer across tasks. Our approach is evaluated on a range of tasks, including text-to-text, image-to-text, video-to-video, video-to-text, and audio-to-text, demonstrating the model's ability to generalize across modalities with minimal adaptation. We show that task reformulation can significantly simplify multimodal model design across various tasks, laying the groundwork for more generalized multimodal foundation models., Comment: 10 pages, 10 figures

A sharp step on a chaotic potential can enhance primordial curvature fluctuations on smaller scales to the $\mathcal{O}(10^{-2})$ to form primordial black holes (PBHs). The present study discusses an inflationary potential with a sharp step that results in the formation of PBHs in four distinct mass ranges. Also this inflationary model allows the separate consideration of observable parameters $n_s$ and $r$ on the CMB scale from the physics at small scales, where PBHs formation occur. In this work we computed the fractional abundance of PBHs ($f_{PBH}$) using the GLMS approximation of peak theory and also the Press-Schechter (PS) formalism. In the two typical mass windows, $10^{-13}M_\odot$ and $10^{-11}M_\odot$, $f_{PBH}$ calculated using the GLMS approximation is nearly equal to 1 and that calculated via PS is of $10^{-3}$. In the other two mass windows $1M_\odot$ and $6M_\odot$, $f_{PBH}$ obtained using GLMS approximation is 0.01 and 0.001 respectively, while $f_{PBH}$ calculated via PS formalism yields $10^{-5}$ and $10^{-6}$. The results obtained via GLMS approximation are found to be consistent with observational constraints. A comparative analysis of $f_{PBH}$ obtained using the GLMS perspective and the PS formalism is also included.

In adaptive clinical trials, the conventional confidence interval (CI) for a treatment effect is prone to undesirable properties such as undercoverage and potential inconsistency with the final hypothesis testing decision. Accordingly, as is stated in recent regulatory guidance on adaptive designs, there is the need for caution in the interpretation of CIs constructed during and after an adaptive clinical trial. However, it may be unclear which of the available CIs in the literature are preferable. This paper is the second in a two-part series that explores CIs for adaptive trials. Part I provided a methodological review of approaches to construct CIs for adaptive designs. In this paper (part II), we present an extended case study based around a two-stage group sequential trial, including a comprehensive simulation study of the proposed CIs for this setting. This facilitates an expanded description of considerations around what makes for an effective CI procedure following an adaptive trial. We show that the CIs can have notably different properties. Finally, we propose a set of guidelines for researchers around the choice of CIs and the reporting of CIs following an adaptive design., Comment: 40 pages