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Light-matter interactions lie at the heart of our exploration of exoplanetary atmospheres. Interpreting data obtained by remote sensing is enabled by meticulous, time- and resource-consuming work aiming at deepening our understanding of such interactions (i.e., opacity models). Recently, \citet{Niraula2022} pointed out that due primarily to limitations on our modeling of broadening and far-wing behaviors, opacity models needed a timely update for exoplanet exploration in the JWST era, and thus argued for a scalable approach. In this Letter, we introduce an end-to-end solution from ab initio calculations to pressure broadening, and use the perturbation framework to identify the need for precision to a level of $\sim$10\%. We focus on the CO$_2$-H$_2$ system as CO$_2$ presents a key absorption feature for exoplanet research (primarily driven by the observation of gas giants) at $\sim$4.3$\mu$m and yet severely lack opacity data. We compute elastic and inelastic cross-sections for the collision of {ortho-}H$_2$ ~with CO$_2$, in the ground vibrational state, and at the coupled-channel fully converged level. For scattering energies above $\sim$20~cm$^{-1}$, moderate precision inter-molecular potentials are indistinguishable from high precision ones in cross-sections. Our calculations agree with the currently available measurement within 7\%, i.e., well beyond the precision requirements. Our proof-of-concept introduces a computationally affordable way to compute full-dimensional interaction potentials and scattering quantum dynamics with a precision sufficient to reduce the model-limited biases originating from the pressure broadening and thus support instrument-limited science with JWST and future missions., Comment: Submitted to ApJL

This document summarizes the context and main outcomes of the discussions that took place during the NSF-UKRI bilateral workshop on Quantum Information Science in Chemistry, held on 12-13 February 2024, in Alexandria, Virginia (US). The workshop was jointly funded by the National Science Foundation (NSF) and UK Research and Innovation (UKRI) through the Engineering and Physical Sciences Research Council (EPSRC). It brought together scientific delegations from the United States of America (US) and the United Kingdom (UK)., Comment: 43 pages, 6 figures

Why humans fight has no easy answer. However, understanding better how humans fight could inform future interventions, hidden shifts and casualty risk. Fusion-fission describes the well-known grouping behavior of fish etc. fighting for survival in the face of strong opponents: they form clusters ('fusion') which provide collective benefits and a cluster scatters when it senses danger ('fission'). Here we show how similar clustering (fusion-fission) of human fighters provides a unified quantitative explanation for complex casualty patterns across decades of Israel-Palestine region violence, as well as the October 7 surprise attack -- and uncovers a hidden post-October 7 shift. State-of-the-art data shows this fighter fusion-fission in action. It also predicts future 'super-shock' attacks that will be more lethal than October 7 and will arrive earlier. It offers a multi-adversary solution. Our results -- which include testable formulae and a plug-and-play simulation -- enable concrete risk assessments of future casualties and policy-making grounded by fighter behavior., Comment: Comments welcome. Working paper

The key difficulty faced by 2D models for planet-disc interaction is in appropriately accounting for the impact of the disc's vertical structure on the dynamics. 3D effects are often mimicked via softening of the planet's potential; however, the planet-induced flow and torques often depend strongly on the choice of softening length. We show that for a linear adiabatic flow perturbing a vertically isothermal disc, there is a particular vertical average of the 3D equations of motion which exactly reproduces 2D fluid equations for arbitrary adiabatic index. There is a strong connection here with the Lubow-Pringle 2D mode of the disc. Correspondingly, we find a simple, general prescription for the consistent treatment of planetary potentials embedded within '2D' discs. The flow induced by a low-mass planet involves large-scale excited spiral density waves which transport angular momentum radially away from the planet, and 'horseshoe streamlines' within the co-orbital region. We derive simple linear equations governing the flow which locally capture both effects faithfully simultaneously. We present an accurate co-orbital flow solution allowing for inexpensive future study of corotation torques, and predict the vertical structure of the co-orbital flow and horseshoe region width for different values of adiabatic index, as well as the vertical dependence of the initial shock location. We find strong agreement with the flow computed in 3D numerical simulations, and with 3D one-sided Lindblad torque estimates, which are a factor of 2 to 3 times lower than values from previous 2D simulations., Comment: Accepted MNRAS, 18 pages, 6 figures

We give a complete characterisation of the cubic graphs with no eigenvalues in the open interval $(-1,1)$. There are two infinite families, one due to Guo and Mohar [Linear Algebra Appl. 449:68--75] the other due to Koll\'ar and Sarnak [Communications of the AMS. 1,1--38], and $14$ "sporadic" graphs on at most $32$ vertices. This allows us to show that $(-1,1)$ is a maximal spectral gap set for cubic graphs. Our techniques including examination of various substructure and an application of the classification of generalized line graphs.

Emerging holographic display technology offers unique capabilities for next-generation virtual reality systems. Current holographic near-eye displays, however, only support a small \'etendue, which results in a direct tradeoff between achievable field of view and eyebox size. \'Etendue expansion has recently been explored, but existing approaches are either fundamentally limited in the image quality that can be achieved or they require extremely high-speed spatial light modulators. We describe a new \'etendue expansion approach that combines multiple coherent sources with content-adaptive amplitude modulation of the hologram spectrum in the Fourier plane. To generate time-multiplexed phase and amplitude patterns for our spatial light modulators, we devise a pupil-aware gradient-descent-based computer-generated holography algorithm that is supervised by a large-baseline target light field. Compared with relevant baseline approaches, our method demonstrates significant improvements in image quality and \'etendue in simulation and with an experimental holographic display prototype., Comment: 12 pages, 7 figures, to be published in SIGGRAPH Asia 2024. Project website: https://bchao1.github.io/holo_dfm/

Under the Riemann hypothesis and the simplicity of the nontrivial zeros $\rho_{n}=1/2\pm i\gamma_{n}$ of the Riemann zeta function $\zeta(s)$ we show that $$ \frac{1}{\left|\zeta' \left(\rho_{n}\right)\right|} = o\left(\gamma_{n}\right) = o\left(\frac{n}{\log n}\right).$$ This is the first known effective upper bound on $1/\left|\zeta'(\rho)\right|$., Comment: 8 pages; corrections to final steps of proof and main result; comments appreciated

Prime-Cam, a first-generation science instrument for the Atacama-based Fred Young Submillimeter Telescope, is being built by the CCAT Collaboration to observe at millimeter and submillimeter wavelengths using kinetic inductance detectors (KIDs). Prime-Cam's 280 GHz instrument module will deploy with two aluminum-based KID arrays and one titanium nitride-based KID array, totaling approximately 10,000 detectors at the focal plane, all of which have been fabricated and are currently undergoing testing. One complication of fielding large arrays of KIDs under dynamic loading conditions is tuning the detector tone powers to maximize signal-to-noise while avoiding bifurcation due to the nonlinear kinetic inductance. For aluminum-based KIDs, this is further complicated by additional nonlinear effects which couple tone power to resonator quality factors and resonant frequencies. While both nonequilibrium quasiparticle dynamics and two-level system fluctuations have been shown to give rise to qualitatively similar distortions, modeling these effects alongside nonlinear kinetic inductance is inefficient when fitting thousands of resonators on-sky with existing models. For this reason, it is necessary to have a detailed understanding of the nonlinear effects across relevant detector loading conditions, including how they impact on on-sky noise and how to diagnose the detector's relative performance. We present a study of the competing nonlinearities seen in Prime-Cam's 280 GHz aluminum KIDs, with a particular emphasis on the resulting distortions to the resonator line shape and how these impact detector parameter estimation., Comment: 10 pages, 4 figures, Conference proceedings from SPIE Astronomical Telescopes + Instrumentation (AS24)

Axions are a well-motivated dark matter candidate. They may be detectable from radio line emission from their resonant conversion in neutron star magnetospheres. While radio data collection for this signal has begun, further efforts are required to solidify the theoretical predictions for the resulting radio lines. Usually, the flat spacetime Goldreich-Julian model of the neutron star magnetosphere is used, while a Schwarzschild geometry is assumed for the ray tracing. We assess the impact of incorporating the spacetime curvature into the magnetosphere model. We examine a range of neutron star and axion masses and find an average difference of $~26\%$ in radiated power compared to the standard Goldreich-Julian magnetosphere model for a $10\mu$eV mass axion and a $2.2M_\odot$ mass neutron star. A much lesser difference is found for lower-mass neutron stars, as in that case, axion-photon conversion occurs further from the Schwarzschild radius., Comment: 17 pages, 10 figures

In 1999 Wright and Dyson highlighted the fact that large sections of the proteome of all organisms are comprised of protein sequences that lack globular folded structures under physiological conditions. Since then the biophysics community has made significant strides in unraveling the intricate structural and dynamic characteristics of intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs). Unlike crystallographic beamlines and their role in streamlining acquisition of structures for folded proteins, an integrated experimental and computational approach aimed at IDPs/IDRs has emerged. In this Perspective we aim to provide a robust overview of current computational tools for IDPs and IDRs, and most recently their complexes and phase separated states, including statistical models, physics-based approaches, and machine learning methods that permit structural ensemble generation and validation against many solution experimental data types.

Here we show that a Large Language Model (LLM) can serve as a foundation model for a Chemical Language Model (CLM) which performs at or above the level of CLMs trained solely on chemical SMILES string data. Using supervised fine-tuning (SFT) and direct preference optimization (DPO) on the open-source Llama LLM, we demonstrate that we can train an LLM to respond to prompts such as generating molecules with properties of interest to drug development. This overall framework allows an LLM to not just be a chatbot client for chemistry and materials tasks, but can be adapted to speak more directly as a CLM which can generate molecules with user-specified properties.

The following magic trick is at the center of this paper. While the audience writes the first ten terms of a Fibonacci-like sequence (the sequence following the same recursion as the Fibonacci sequence), the magician calculates the sum of these ten terms very fast by multiplying the 7th term by 11. This trick is based on the divisibility properties of partial sums of Fibonacci-like sequences. We find the maximum Fibonacci number that divides the sum of the Fibonacci numbers 1 through $n$. We discuss the generalization of the trick for other second-order recurrences. We show that a similar trick exists for Pell-like sequences and does not exist for Jacobhstal-like sequences., Comment: 26 pages, 9 tables

Over the last two decades, spatial light modulators (SLMs) have revolutionised our ability to shape optical fields. They grant independent dynamic control over thousands of degrees-of-freedom within a single light beam. In this work we test a new type of SLM, known as a phase-only light modulator (PLM), that blends the high efficiency of liquid crystal SLMs with the fast switching rates of binary digital micro-mirror devices (DMDs). A PLM has a 2D mega-pixel array of micro-mirrors. The vertical height of each micro-mirror can be independently adjusted with 4-bit precision. Here we provide a concise tutorial on the operation and calibration of a PLM. We demonstrate arbitrary pattern projection, aberration correction, and control of light transport through complex media. We show high-speed wavefront shaping through a multimode optical fibre -- scanning over 2000 points at 1.44 kHz. We make available our custom high-speed PLM control software library developed in C++. As PLMs are based upon micro-electromechanical system (MEMS) technology, they are polarisation agnostic, and possess fundamental switching rate limitations equivalent to that of DMDs -- with operation at up to 10 kHz anticipated in the near future. We expect PLMs will find high-speed light shaping applications across a range of fields including adaptive optics, microscopy, optogenetics and quantum optics., Comment: 15 pages, 5 figures

A $(v,k,\lambda)$-difference set in a group $G$ of order $v$ is a subset $\{d_1, d_2, \ldots,d_k\}$ of $G$ such that $D=\sum d_i$ in the group ring ${\mathbb Z}[G]$ satisfies $$D D^{-1} = n + \lambda G,$$ where $n=k-\lambda$. In other words, the nonzero elements of $G$ all occur exactly $\lambda$ times as differences of elements in $D$. A $(v,k,\lambda,t)$-almost difference set has $t$ nonzero elements of $G$ occurring $\lambda$ times, and the other $v-1-t$ occurring $\lambda+1$ times. When $\lambda=0$, this is equivalent to a modular Golomb ruler. In this paper we investigate existence questions on these objects, and extend previous results constructing almost difference sets by adding or removing an element from a difference set., Comment: 6 pages, 1 figure

Authorship obfuscation, rewriting a text to intentionally obscure the identity of the author, is an important but challenging task. Current methods using large language models (LLMs) lack interpretability and controllability, often ignoring author-specific stylistic features, resulting in less robust performance overall. To address this, we develop StyleRemix, an adaptive and interpretable obfuscation method that perturbs specific, fine-grained style elements of the original input text. StyleRemix uses pre-trained Low Rank Adaptation (LoRA) modules to rewrite an input specifically along various stylistic axes (e.g., formality and length) while maintaining low computational cost. StyleRemix outperforms state-of-the-art baselines and much larger LLMs in a variety of domains as assessed by both automatic and human evaluation. Additionally, we release AuthorMix, a large set of 30K high-quality, long-form texts from a diverse set of 14 authors and 4 domains, and DiSC, a parallel corpus of 1,500 texts spanning seven style axes in 16 unique directions

HMYSOs gain most of their mass in short bursts of accretion. Maser emission is an invaluable tool in discovering and probing accretion bursts. We observed the 22 GHz water maser response induced by the accretion burst in NGC6334I-MM1B and identified the underlying maser variability mechanisms. We report seven epochs of VLBI observations of 22 GHz water masers in NGC6334I with the VERA array, from 2014 to 2016, spanning the onset of the accretion burst in 2015.1. We also report 2019 ALMA observations of 321 GHz water masers and 22 GHz maser monitoring by HartRAO. We analyze variability patterns and use proper motions with the 22 GHz to 321 GHz line ratio to distinguish between masers in C-shocks and J-shocks. We also calculated the burst-to-quiescent variance ratio of the single-dish time series. The constant mean proper motion before and after the burst indicates that maser variability is due to excitation effects from variable radiation rather than jet ejecta. We find that the flux density variance ratio in the single-dish time series can identify maser efficiency variations in 22 GHz masers. The northern region, CM2-W2, is excited in C-shocks and showed long-term flaring with velocity-dependent excitation of new maser features. We propose that radiative heating of H2 due to high-energy radiation from the accretion burst be the mechanism for the flaring in CM2-W2. The southern regions are excited by J-shocks and have short-term flaring and dampening of water masers. We attributed the diverse variability patterns in the southern regions to the radiative transfer of the burst energy in the source. Our results indicate that the effects of source geometry, shock type, and incident radiation spectrum are fundamental factors affecting 22 GHz maser variability. Investigating water masers in irradiated shocks will improve their use as a diagnostic in time-variable radiation environments., Comment: 21 pages, 12 figures, Table 2 in electronic publication. Contact: jakobus.vorster@helsinki.fi

Identification of the breaking point for the chemical bond is essential for our understanding of chemical reactivity. The current consensus is that a point of maximal electron delocalization along the bonding axis separates the different bonding regimes of reactants and products. This maximum transition point has been investigated previously through the total position spread and the bond-parallel components of the static polarizability tensor for describing covalent bond breaking. In this paper, we report that the first-order change of the Wiberg and Mayer bond index with respect to the reaction coordinate, the bond flux, is similarly maximized and is nearly equivalent with the bond breaking points determined by the bond-parallel polarizability. We investigate the similarites and differences between the two bonding metrics for breaking the nitrogen triple bond, twisting around the ethene double bond, and a set of prototypical reactions in the hydrogen combustion reaction network. The Wiberg-Mayer bond flux provides a simpler approach to calculating the point of bond dissociation and formation and can yield greater chemical insight through bond specific information for certain reactions where multiple bond changes are operative.

Quantum error correction provides a path to reach practical quantum computing by combining multiple physical qubits into a logical qubit, where the logical error rate is suppressed exponentially as more qubits are added. However, this exponential suppression only occurs if the physical error rate is below a critical threshold. In this work, we present two surface code memories operating below this threshold: a distance-7 code and a distance-5 code integrated with a real-time decoder. The logical error rate of our larger quantum memory is suppressed by a factor of $\Lambda$ = 2.14 $\pm$ 0.02 when increasing the code distance by two, culminating in a 101-qubit distance-7 code with 0.143% $\pm$ 0.003% error per cycle of error correction. This logical memory is also beyond break-even, exceeding its best physical qubit's lifetime by a factor of 2.4 $\pm$ 0.3. We maintain below-threshold performance when decoding in real time, achieving an average decoder latency of 63 $\mu$s at distance-5 up to a million cycles, with a cycle time of 1.1 $\mu$s. To probe the limits of our error-correction performance, we run repetition codes up to distance-29 and find that logical performance is limited by rare correlated error events occurring approximately once every hour, or 3 $\times$ 10$^9$ cycles. Our results present device performance that, if scaled, could realize the operational requirements of large scale fault-tolerant quantum algorithms., Comment: 10 pages, 4 figures, Supplementary Information

3D immersive scene generation is a challenging yet critical task in computer vision and graphics. A desired virtual 3D scene should 1) exhibit omnidirectional view consistency, and 2) allow for free exploration in complex scene hierarchies. Existing methods either rely on successive scene expansion via inpainting or employ panorama representation to represent large FOV scene environments. However, the generated scene suffers from semantic drift during expansion and is unable to handle occlusion among scene hierarchies. To tackle these challenges, we introduce LayerPano3D, a novel framework for full-view, explorable panoramic 3D scene generation from a single text prompt. Our key insight is to decompose a reference 2D panorama into multiple layers at different depth levels, where each layer reveals the unseen space from the reference views via diffusion prior. LayerPano3D comprises multiple dedicated designs: 1) we introduce a novel text-guided anchor view synthesis pipeline for high-quality, consistent panorama generation. 2) We pioneer the Layered 3D Panorama as underlying representation to manage complex scene hierarchies and lift it into 3D Gaussians to splat detailed 360-degree omnidirectional scenes with unconstrained viewing paths. Extensive experiments demonstrate that our framework generates state-of-the-art 3D panoramic scene in both full view consistency and immersive exploratory experience. We believe that LayerPano3D holds promise for advancing 3D panoramic scene creation with numerous applications., Comment: Project page: https://ys-imtech.github.io/projects/LayerPano3D/

Background: Radiography (X-rays) is the dominant modality in orthopedics, and improving the interpretation of radiographs is clinically relevant. Machine learning (ML) has revolutionized data analysis and has been applied to medicine, with some success, in the form of natural language processing (NLP) and artificial neural networks (ANN). Latent Dirichlet allocation (LDA) is an NLP method that automatically categorizes documents into topics. Successfully applying ML to orthopedic radiography could enable the creation of computer-aided decision systems for use in the clinic. We studied how an automated ML pipeline could classify orthopedic trauma radiographs from radiologist reports. Methods: Wrist and ankle radiographs from Danderyd Hospital in Sweden taken between 2002 and 2015, with radiologist reports. LDA was used to create image labels for radiographs from the radiologist reports. Radiographs and labels were used to train an image recognition ANN. The ANN outcomes were manually reviewed to get an accurate estimate of the method's utility and accuracy. Results: Image Labels generated via LDA could successfully train the ANN. The ANN reached an accuracy between 91% and 60% compared to a gold standard, depending on the label. Conclusions: We found that LDA was unsuited to label orthopedic radiographs from reports with high accuracy. However, despite this, the ANN could learn to detect some features in radiographs with high accuracy. The study also illustrates how ML and ANN can be applied to medical research., Comment: This article is an abridged version of a 2016 master's thesis at the Karolinska Institute. The original is available upon request

We propose sparse regression as an alternative to neural networks for the discovery of parsimonious constitutive models (CMs) from oscillatory shear experiments. Symmetry and frame-invariance are strictly imposed by using tensor basis functions to isolate and describe unknown nonlinear terms in the CMs. We generate synthetic experimental data using the Giesekus and Phan-Thien Tanner CMs, and consider two different scenarios. In the complete information scenario, we assume that the shear stress, along with the first and second normal stress differences, is measured. This leads to a sparse linear regression problem that can be solved efficiently using $l_1$ regularization. In the partial information scenario, we assume that only shear stress data is available. This leads to a more challenging sparse nonlinear regression problem, for which we propose a greedy two-stage algorithm. In both scenarios, the proposed methods fit and interpolate the training data remarkably well. Predictions of the inferred CMs extrapolate satisfactorily beyond the range of training data for oscillatory shear. They also extrapolate reasonably well to flow conditions like startup of steady and uniaxial extension that are not used in the identification of CMs. We discuss ramifications for experimental design, potential algorithmic improvements, and implications of the non-uniqueness of CMs inferred from partial information., Comment: 45 pages, 8 figures

Accurate assessment of lymph node size in 3D CT scans is crucial for cancer staging, therapeutic management, and monitoring treatment response. Existing state-of-the-art segmentation frameworks in medical imaging often rely on fully annotated datasets. However, for lymph node segmentation, these datasets are typically small due to the extensive time and expertise required to annotate the numerous lymph nodes in 3D CT scans. Weakly-supervised learning, which leverages incomplete or noisy annotations, has recently gained interest in the medical imaging community as a potential solution. Despite the variety of weakly-supervised techniques proposed, most have been validated only on private datasets or small publicly available datasets. To address this limitation, the Mediastinal Lymph Node Quantification (LNQ) challenge was organized in conjunction with the 26th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2023). This challenge aimed to advance weakly-supervised segmentation methods by providing a new, partially annotated dataset and a robust evaluation framework. A total of 16 teams from 5 countries submitted predictions to the validation leaderboard, and 6 teams from 3 countries participated in the evaluation phase. The results highlighted both the potential and the current limitations of weakly-supervised approaches. On one hand, weakly-supervised approaches obtained relatively good performance with a median Dice score of $61.0\%$. On the other hand, top-ranked teams, with a median Dice score exceeding $70\%$, boosted their performance by leveraging smaller but fully annotated datasets to combine weak supervision and full supervision. This highlights both the promise of weakly-supervised methods and the ongoing need for high-quality, fully annotated data to achieve higher segmentation performance., Comment: Submitted to MELBA

We examine the energy distribution of the fast radio burst (FRB) population using a well-defined sample of 63 FRBs from the ASKAP radio telescope, 28 of which are localised to a host galaxy. We apply the luminosity-volume ($V/V_{\mathrm{max}}$) test to examine the distribution of these transient sources, accounting for cosmological and instrumental effects, and determine the energy distribution for the sampled population over the redshift range $0.01 \lesssim z \lesssim 1.02$. We find the distribution between $10^{23}$ and $10^{26}$J Hz$^{-1}$ to be consistent with both a pure power-law with differential slope $\gamma=-1.96 \pm 0.15$, and a Schechter function with $\gamma = -1.82 \pm 0.12$ and downturn energy $E_{\rm max} \sim 6.3 \cdot 10^{25}$J Hz$^{-1}$. We identify systematic effects which currently limit our ability to probe the luminosity function outside this range and give a prescription for their treatment. Finally, we find that with the current dataset, we are unable to distinguish between the evolutionary and spectral models considered in this work., Comment: 23 pages, 10 figures, submitted to PASA

We present new JWST observations of the nearby, prototypical edge-on, spiral galaxy NGC 891. The northern half of the disk was observed with NIRCam in its F150W and F277W filters. Absorption is clearly visible in the mid-plane of the F150W image, along with vertical dusty plumes that closely resemble the ones seen in the optical. A $\sim 10 \times 3~{\rm kpc}^2$ area of the lower circumgalactic medium (CGM) was mapped with MIRI F770W at 12 pc scales. Thanks to the sensitivity and resolution of JWST, we detect dust emission out to $\sim 4$ kpc from the disk, in the form of filaments, arcs, and super-bubbles. Some of these filaments can be traced back to regions with recent star formation activity, suggesting that feedback-driven galactic winds play an important role in regulating baryonic cycling. The presence of dust at these altitudes raises questions about the transport mechanisms at play and suggests that small dust grains are able to survive for several tens of million years after having been ejected by galactic winds in the disk-halo interface. We lay out several scenarios that could explain this emission: dust grains may be shielded in the outer layers of cool dense clouds expelled from the galaxy disk, and/or the emission comes from the mixing layers around these cool clumps where material from the hot gas is able to cool down and mix with these cool cloudlets. This first set of data and upcoming spectroscopy will be very helpful to understand the survival of dust grains in energetic environments, and their contribution to recycling baryonic material in the mid-plane of galaxies., Comment: Accepted for publication in Astronomy & Astrophysics; 16 pages, 8 figures

Trained on vast corpora, Large Language Models (LLMs) have the potential to encode visualization design knowledge and best practices. However, if they fail to do so, they might provide unreliable visualization recommendations. What visualization design preferences, then, have LLMs learned? We contribute DracoGPT, a method for extracting, modeling, and assessing visualization design preferences from LLMs. To assess varied tasks, we develop two pipelines--DracoGPT-Rank and DracoGPT-Recommend--to model LLMs prompted to either rank or recommend visual encoding specifications. We use Draco as a shared knowledge base in which to represent LLM design preferences and compare them to best practices from empirical research. We demonstrate that DracoGPT can accurately model the preferences expressed by LLMs, enabling analysis in terms of Draco design constraints. Across a suite of backing LLMs, we find that DracoGPT-Rank and DracoGPT-Recommend moderately agree with each other, but both substantially diverge from guidelines drawn from human subjects experiments. Future work can build on our approach to expand Draco's knowledge base to model a richer set of preferences and to provide a robust and cost-effective stand-in for LLMs., Comment: IEEE Transactions on Visualization and Computer Graphics (Proc. VIS 2024)

The First Large Absorption Survey in HI (FLASH) is a large-area radio survey for neutral hydrogen in the redshift range 0.41$, and appear to be a mixture of intervening and associated systems. The overall detection rate for HI absorption lines in the Pilot Surveys (0.3 to 0.5 lines per ASKAP field) is a factor of two below the expected value. There are several possible reasons for this, but one likely factor is the presence of a range of spectral-line artefacts in the Pilot Survey data that have now been mitigated and are not expected to recur in the full FLASH survey. A future paper will discuss the host galaxies of the HI absorption systems identified here., Comment: 46 pages, 25 figures, 10 tables. Submitted to PASA

Two-dimensional materials (2DMs) have been widely investigated because of their potential for heterogeneous integration with modern electronics. However, several major challenges remain, such as the deposition of high-quality dielectrics on 2DMs and the tuning of the 2DM doping levels. Here, we report a scalable plasma-enhanced atomic layer deposition (PEALD) process for direct deposition of a nonstoichiometric aluminum oxide (AlOX) dielectric, overcoming the damage issues associated with conventional methods. Furthermore, we control the thickness of the dielectric layer to systematically tune the doping level of 2DMs. The experimental results demonstrate successful deposition without detectable damage, as confirmed by Raman spectroscopy and electrical measurements. Our method enables tuning of the Dirac and threshold voltages of back-gated graphene and MoS${_2}$ field-effect transistors (FETs), respectively, while also increasing the charge carrier mobility in both device types. We further demonstrate the method in top-gated MoS${_2}$ FETs with double-stack dielectric layers (AlOX+Al${_2}$O${_3}$), achieving critical breakdown field strengths of 7 MV/cm and improved mobility compared with the back gate configuration. In summary, we present a PEALD process that offers a scalable and low-damage solution for dielectric deposition on 2DMs, opening new possibilities for precise tuning of device characteristics in heterogeneous electronic circuits., Comment: 28 pages

Pd$_3$Bi$_2$Se$_2$ is a rare realization of a superconducting metal with a non-zero $Z_2$ topological invariant. We report the growth of high-quality single crystals of layered Pd$_3$Bi$_2$Se$_2$ with a superconducting transition at $T_c$ ~ 0.80 K and upper critical fields of ~10 mT and ~5 mT for the in-plane and out-of-plane directions, respectively. Our density functional theory (DFT) calculations reveal three pairs of doubly degenerate bands crossing the Fermi level, all displaying clear three-dimensional dispersion consistent with the overall low electronic anisotropy (<2). The multiband electronic nature of Pd$_3$Bi$_2$Se$_2$ is evident in magneto-transport measurements, yielding a sign-changing Hall resistivity at low temperatures. The magnetoresistance is non-saturating and follows Kohler's scaling rule. We interpret the magneto-transport data in terms of open orbits that are revealed in the DFT-calculated Fermi surface. de Haas-van Alphen (dHvA) oscillation measurements using torque magnetometry on single crystals yield four frequencies for out-of-plane fields: $F_\alpha = (150 \pm 26)$T, $F_\beta = (293 \pm 10)$T, $F_\gamma = (375 \pm 20)$T, and $F_\eta = (1017 \pm 12)$T, with the low frequency dominating the spectrum. Through the measurement of angular dependent dHvA oscillations and DFT calculations, we identify the $F_\alpha$ frequency with an approximately ellipsoidal electron pocket centered on the $L_2$ point of the Brillouin zone. Lifshitz-Kosevich analysis of the dHvA oscillations reveals a small cyclotron effective mass: $m^* = (0.11 \pm 0.02) m_0$ and a nontrivial Berry phase for the dominant orbit. The presence of nontrivial topology in a bulk superconductor positions Pd$_3$Bi$_2$Se$_2$ as a potential candidate for exploring topological superconductivity., Comment: 30 pages, 5 figures

Exploratory testing, known for its flexibility and ability to uncover unexpected issues, often faces challenges in maintaining systematic coverage and producing reproducible results. To address these challenges, we investigate whether gamification of testing directly in the Integrated Development Environment (IDE) can guide exploratory testing. We therefore show challenges and quests generated by the Gamekins gamification system to make testing more engaging and seamlessly blend it with regular coding tasks. In a 60-minute experiment, we evaluated Gamekins' impact on test suite quality and bug detection. The results show that participants actively interacted with the tool, achieving nearly 90% line coverage and detecting 11 out of 14 bugs. Additionally, participants reported enjoying the experience, indicating that gamification can enhance developer participation in testing and improve software quality.

Fast radio burst (FRB) science primarily revolves around two facets: the origin of these bursts and their use in cosmological studies. This work follows from previous redshift-dispersion measure ($z$-DM) analyses in which we model instrumental biases and simultaneously fit population parameters and cosmological parameters to the observed population of FRBs. This sheds light on both the progenitors of FRBs and cosmological questions. Previously, we have completed similar analyses with data from the Australian Square Kilometer Array Pathfinder (ASKAP) and the Murriyang (Parkes) Multibeam system. With this manuscript, we additionally incorporate data from the Deep Synoptic Array (DSA) and the Five-hundred-meter Aperture Spherical Telescope (FAST), invoke a Markov chain Monte Carlo (MCMC) sampler and implement uncertainty in the Galactic DM contributions. The latter leads to larger uncertainties in derived model parameters than previous estimates despite the additional data. We provide refined constraints on FRB population parameters and derive a new constraint on the minimum FRB energy of log$\,E_{\mathrm{min}}$(erg)=39.49$^{+0.39}_{-1.48}$ which is significantly higher than bursts detected from strong repeaters. This result may indicate a low-energy turnover in the luminosity function or may suggest that strong repeaters have a different luminosity function to single bursts. We also predict that FAST will detect 25-41% of their FRBs at $z \gtrsim 2$ and DSA will detect 2-12% of their FRBs at $z \gtrsim 1$., Comment: 17 pages, 7 figures, submitted to PASA

A hybrid of the critical three dimensional Gross-Neveu and Thirring models deformed by explicit parity breaking operators is studied in the large N expansion and using the renormalization group. Two stable solutions are found. One solution is a stable charge-gapped phase with a massless photon-like vector field, massive fermions and a parametrically light scalar field which acts as a dilaton for a spontaneously broken approximate scale invariance. A second solution is a conformal window where the fermion spectrum is not gapped and the theory flows between infrared and ultraviolet fixed points, becoming a conformal field theory at the infrared fixed point. The latter is an analog of the Wilson-Fisher fixed point and it supports a novel parity and time reversal violating three dimensional conformal field theory with scalar, spinor and vector fields.

Reverberation as supervision (RAS) is a framework that allows for training monaural speech separation models from multi-channel mixtures in an unsupervised manner. In RAS, models are trained so that sources predicted from a mixture at an input channel can be mapped to reconstruct a mixture at a target channel. However, stable unsupervised training has so far only been achieved in over-determined source-channel conditions, leaving the key determined case unsolved. This work proposes enhanced RAS (ERAS) for solving this problem. Through qualitative analysis, we found that stable training can be achieved by leveraging the loss term to alleviate the frequency-permutation problem. Separation performance is also boosted by adding a novel loss term where separated signals mapped back to their own input mixture are used as pseudo-targets for the signals separated from other channels and mapped to the same channel. Experimental results demonstrate high stability and performance of ERAS., Comment: Accepted to Interspeech 2024

Time-frequency (TF) domain dual-path models achieve high-fidelity speech separation. While some previous state-of-the-art (SoTA) models rely on RNNs, this reliance means they lack the parallelizability, scalability, and versatility of Transformer blocks. Given the wide-ranging success of pure Transformer-based architectures in other fields, in this work we focus on removing the RNN from TF-domain dual-path models, while maintaining SoTA performance. This work presents TF-Locoformer, a Transformer-based model with LOcal-modeling by COnvolution. The model uses feed-forward networks (FFNs) with convolution layers, instead of linear layers, to capture local information, letting the self-attention focus on capturing global patterns. We place two such FFNs before and after self-attention to enhance the local-modeling capability. We also introduce a novel normalization for TF-domain dual-path models. Experiments on separation and enhancement datasets show that the proposed model meets or exceeds SoTA in multiple benchmarks with an RNN-free architecture., Comment: Accepted to IWAENC 2024

Stochastic multi-agent multi-armed bandits typically assume that the rewards from each arm follow a fixed distribution, regardless of which agent pulls the arm. However, in many real-world settings, rewards can depend on the sensitivity of each agent to their environment. In medical screening, disease detection rates can vary by test type; in preference matching, rewards can depend on user preferences; and in environmental sensing, observation quality can vary across sensors. Since past work does not specify how to allocate agents of heterogeneous but known sensitivity of these types in a stochastic bandit setting, we introduce a UCB-style algorithm, Min-Width, which aggregates information from diverse agents. In doing so, we address the joint challenges of (i) aggregating the rewards, which follow different distributions for each agent-arm pair, and (ii) coordinating the assignments of agents to arms. Min-Width facilitates efficient collaboration among heterogeneous agents, exploiting the known structure in the agents' reward functions to weight their rewards accordingly. We analyze the regret of Min-Width and conduct pseudo-synthetic and fully synthetic experiments to study the performance of different levels of information sharing. Our results confirm that the gains to modeling agent heterogeneity tend to be greater when the sensitivities are more varied across agents, while combining more information does not always improve performance., Comment: 19 pages, 6 figures, to be published in ECAI 2024

With wide-field phased array feed technology, the Australian Square Kilometre Array Pathfinder (ASKAP) is ideally suited to search for seemingly rare radio transient sources. The Commensal Real-time ASKAP Fast Transient (CRAFT) Survey Science Project has developed instrumentation to continuously search for fast radio transients (duration $\lesssim$ 1 second) with ASKAP, with a particular focus on finding and localising Fast Radio Bursts (FRBs). Of particular interest are Fast Radio Bursts (FRBs). Since 2018, the CRAFT survey has been searching for FRBs and other fast transients by incoherently adding the intensities received by individual ASKAP antennas, and then correcting for the impact of frequency dispersion on these short-duration signals in the resultant incoherent sum (ICS) in real-time. This low-latency detection enables the triggering of voltage buffers, which facilitates the localisation of the transient source and the study spectro-polarimetric properties at high time resolution. Here we report the sample of 43 FRBs discovered in this CRAFT/ICS survey to date. This includes 22 FRBs that had not previously been reported: 16 FRBs localised by ASKAP to $\lesssim$ 1 arcsec and 6 FRBs localised to approximately 10 arcmin. Of the new arcsecond-localised FRBs, we have identified and characterised host galaxies (and measured redshifts) for 11. The median of all 30 measured host redshifts from the survey to date is z = 0.23. We summarise results from the searches, in particular those contributing to our understanding of the burst progenitors and emission mechanisms, and on the use of bursts as probes of intervening media. We conclude by foreshadowing future FRB surveys with ASKAP using a coherent detection system that is currently being commissioned., Comment: 37 pages, 23 Figures, 7 Tables. Submitted for publication in PASA

We explore the Steklov eigenvalue problem on convex polygons, focusing mainly on the inverse Steklov problem. Our primary finding reveals that, for almost all convex polygonal domains, there exist at most finitely many non-congruent domains with the same Steklov spectrum. Moreover, we obtain explicit upper bounds for the maximum number of mutually Steklov isospectral non-congruent polygonal domains. Along the way, we obtain isoperimetric bounds for the Steklov eigenvalues of a convex polygon in terms of the minimal interior angle of the polygon., Comment: 24 pages, 10 figures

Using very long baseline interferometry data for the sources that comprise the third International Celestial Reference Frame (ICRF3), we examine the quality of the formal source position uncertainties of ICRF3 by determining the excess astrometric variability (unexplained variance) for each source as a function of time. We also quantify multiple qualitatively distinct aspects of astrometric variability seen in the data, using a variety of metrics. Average position offsets, statistical dispersion measures, and coherent trends over time as explored by smoothing the data are combined to characterize the most and least positionally stable ICRF3 sources. We find a notable dependence of the excess variance and statistical variability measures on declination, as is expected for unmodeled ionospheric delay errors and the northern hemisphere dominated network geometries of most astrometric and geodetic observing campaigns., Comment: Accepted for publication in ApJS. 22 pages, 14 figures

In this work, we introduce Gemma 2, a new addition to the Gemma family of lightweight, state-of-the-art open models, ranging in scale from 2 billion to 27 billion parameters. In this new version, we apply several known technical modifications to the Transformer architecture, such as interleaving local-global attentions (Beltagy et al., 2020a) and group-query attention (Ainslie et al., 2023). We also train the 2B and 9B models with knowledge distillation (Hinton et al., 2015) instead of next token prediction. The resulting models deliver the best performance for their size, and even offer competitive alternatives to models that are 2-3 times bigger. We release all our models to the community.

Prime-Cam is a first-generation science instrument for the CCAT Observatory's six-meter aperture Fred Young Submillimeter Telescope (FYST). FYST's crossed-Dragone design provides high optical throughput to take advantage of its unique site at 5600 m on Cerro Chajnantor in Chile's Atacama Desert to reach mapping speeds over ten times greater than current and near-term submillimeter experiments. Housing up to seven independent instrument modules in its 1.8-meter diameter cryostat, Prime-Cam will combine broadband polarization-sensitive modules and spectrometer modules designed for observations in several frequency windows between 210 GHz and 850 GHz to study a wide range of astrophysical questions from Big Bang cosmology to the formation of stars and galaxies in the Epoch of Reionization and beyond. In order to cover this range of frequencies and observation modes, each of the modules contains a set of cold reimaging optics that is optimized for the science goals of that module. These optical setups include several filters, three or four anti-reflection-coated silicon lenses, and a Lyot stop to control the field of view and illumination of the primary mirror, satisfy a series of mechanical constraints, and maximize optical performance within each passband. We summarize the design considerations and trade-offs for the optics in these modules and provide a status update on the fabrication of the Prime-Cam receiver and the design of its 1 K and 100 mK thermal BUSs., Comment: 10 pages, 6 figures, presented at SPIE Millimeter, Submillimeter, and Far-Infrared Detectors and Instrumentation for Astronomy XII

Image environments and noisy labels hinder deep learning-based inference models in structural damage detection. Post-detection, there is the challenge of reliance on manual assessments of detected damages. As a result, Guided-DetNet, characterized by Generative Attention Module (GAM), Hierarchical Elimination Algorithm (HEA), and Volumetric Contour Visual Assessment (VCVA), is proposed to mitigate complex image environments, noisy labeling, and post-detection manual assessment of structural damages. GAM leverages cross-horizontal and cross-vertical patch merging and cross foreground-background feature fusion to generate varied features to mitigate complex image environments. HEA addresses noisy labeling using hierarchical relationships among classes to refine instances given an image by eliminating unlikely class categories. VCVA assesses the severity of detected damages via volumetric representation and quantification leveraging the Dirac delta distribution. A comprehensive quantitative study, two robustness tests, and an application scenario based on the PEER Hub Image-Net dataset substantiate Guided-DetNet's promising performances. Guided-DetNet outperformed the best-compared models in a triple classification task by a difference of not less than 3% and not less than 2% in a dual detection task under varying metrics.

Large language models (LLMs) with billions of parameters excel at predicting the next token in a sequence. Recent work computes non-vacuous compression-based generalization bounds for LLMs, but these bounds are vacuous for large models at the billion-parameter scale. Moreover, these bounds are obtained through restrictive compression techniques, bounding compressed models that generate low-quality text. Additionally, the tightness of these existing bounds depends on the number of IID documents in a training set rather than the much larger number of non-IID constituent tokens, leaving untapped potential for tighter bounds. In this work, we instead use properties of martingales to derive generalization bounds that benefit from the vast number of tokens in LLM training sets. Since a dataset contains far more tokens than documents, our generalization bounds not only tolerate but actually benefit from far less restrictive compression schemes. With Monarch matrices, Kronecker factorizations, and post-training quantization, we achieve non-vacuous generalization bounds for LLMs as large as LLaMA2-70B. Unlike previous approaches, our work achieves the first non-vacuous bounds for models that are deployed in practice and generate high-quality text.

High energy electrons carry much of a solar flare's energy. Therefore, understanding changes in electron beam distributions during their propagation is crucial. A key focus of this paper is how the co-spatial return current reduces the energy flux carried by these accelerated electrons. We systematically compute this reduction for various beam and plasma parameters relevant to solar flares. Our 1D model accounts for collisions between beam and plasma electrons, return current electric-field deceleration, thermalization in a warm target approximation, and runaway electron contributions. The results focus on the classical (Spitzer) regime, offering a valuable benchmark for energy flux reduction and its extent. Return current losses are only negligible for the lowest nonthermal fluxes. We calculate the conditions for return current losses to become significant and estimate the extent of the modification to the beam's energy flux density. We also calculate two additional conditions which occur for higher injected fluxes: (1) where runaway electrons become significant, and (2) where current-driven instabilities might become significant, requiring a model that self-consistently accounts for them. Condition (2) is relaxed and the energy flux losses are reduced in the presence of runaway electrons. All results are dependent on beam and co-spatial plasma parameters. We also examine the importance of the reflection of beam electrons by the return-current electric field. We show that the interpretation of a number of flares needs to be reviewed to account for the effects of return currents., Comment: 22 pages, 11 figures, Submitted to ApJ