Search

This brief is a continuation of NWEA's research series examining the impact of the COVID-19 pandemic on student achievement and progress toward academic recovery. Initiated in the early phase of the pandemic, this series has leveraged NWEA's large national sample of longitudinal MAP® Growth™ data to track student performance and compare it to historical trends. The authors have tracked two critical aspects of student performance in the wake of the pandemic: achievement and growth. Achievement data reveals the extent of unfinished learning. The authors refer to the distance between current test scores and prepandemic trends as "achievement gaps." Growth data estimate how much test scores increase over time. They use these data to indicate whether students are making gains that keep pace with prepandemic trends. Understanding and tracking both achievement and growth is important. Achievement gaps quantify how much unfinished learning remains, while growth patterns help gauge the rate at which gaps will close. The system needs accelerated or above-average growth for students to catch up. The data provide insights into how effectively this is happening. The cumulative research shows that the harmful effects of the pandemic on student achievement steadily accumulated over the course of the 2020-21 school year (Lewis, Kuhfeld, Ruzek, & McEachin, 2021). Growth generally returned to, or slightly exceeded, prepandemic trends in the 2021-22 school year (Kuhfeld & Lewis, 2022). Progress stalled in 2022-23 when growth in nearly all grades fell short of prepandemic trends (Lewis & Kuhfeld, 2023). In this analysis, the authors use 2023-24 school year data to examine the current progress toward recovery. They examine test scores from approximately 7.7 million students currently in grades 3-8 in 22,400 public schools who have taken MAP Growth reading and math assessments since the onset of the pandemic. The "COVID sample" consists of six separate cohorts of students followed longitudinally across the last three school years. For instance, current fifth-graders are part of the grade 3-5 cohort; they measure this cohort's achievement across third grade in 2021-22, fourth grade in 2022-23, and fifth grade in 2023-24. The authors compared this COVID sample to a comparable group of 10 million students who tested in grades 3-8 in the pre-COVID school years of 2016-17 through 2018-19.

This study investigates the role of college major choices in labor market outcomes, with a focus on racial minorities and immigrants. Drawing upon research on school-to-work linkages, we examine two measures, linkage, the connection between college majors and specific occupations in the labor market, and match, the alignment of workers' occupations with their college majors. Analyzing data from the American Community Survey, 2013-2017, we show that linkage positively predicts earnings, particularly for workers in matched occupations, and negatively predicts unemployment. Notably, Black, Hispanic, and foreign-born workers in matched occupations benefit more from linkage strength than their White and U.S.-born counterparts. This advantage is more pronounced in states that are popular destinations for immigrants. Our findings suggest that earnings and unemployment disparities experienced among racial minorities and immigrants may diminish if they pursue majors closely tied to jobs in the labor market and secure jobs related to their college majors.

L 98-59 d is a Super-Earth planet orbiting an M-type star. We performed retrievals on the transmission spectrum of L 98-59 d obtained using NIRSpec G395H during a single transit, from JWST Cycle 1 GTO 1224. The wavelength range of this spectrum allows us to detect the presence of several atmospheric species. We found that the spectrum is consistent with a high mean molecular weight atmosphere. The atmospheric spectrum indicates the possible presence of the sulfur-bearing species H$_2$S and SO$_2$, which could hint at active volcanism on this planet if verified by future observations. We also tested for signs of stellar contamination in the spectrum, and found signs of unocculted faculae on the star. The tentative signs of an atmosphere on L 98-59 d presented in this work from just one transit bodes well for possible molecular detections in the future, particularly as it is one of the best targets among small exoplanets for atmospheric characterization using JWST., Comment: Accepted for publication to ApJL

Modern artificial intelligence (AI) systems are powered by foundation models. This paper presents a new set of foundation models, called Llama 3. It is a herd of language models that natively support multilinguality, coding, reasoning, and tool usage. Our largest model is a dense Transformer with 405B parameters and a context window of up to 128K tokens. This paper presents an extensive empirical evaluation of Llama 3. We find that Llama 3 delivers comparable quality to leading language models such as GPT-4 on a plethora of tasks. We publicly release Llama 3, including pre-trained and post-trained versions of the 405B parameter language model and our Llama Guard 3 model for input and output safety. The paper also presents the results of experiments in which we integrate image, video, and speech capabilities into Llama 3 via a compositional approach. We observe this approach performs competitively with the state-of-the-art on image, video, and speech recognition tasks. The resulting models are not yet being broadly released as they are still under development.

Sample Return Capsules (SRCs) entering Earth's atmosphere at hypervelocity from interplanetary space are a valuable resource for studying meteor phenomena. The 24 September 2023 arrival of the OSIRIS-REx (Origins, Spectral Interpretation, Resource Identification, and Security-Regolith Explorer) SRC provided an unprecedented chance for geophysical observations of a well-characterized source with known parameters, including timing and trajectory. A collaborative effort involving researchers from 16 institutions executed a carefully planned geophysical observational campaign at strategically chosen locations, deploying over 400 ground-based sensors encompassing infrasound, seismic, distributed acoustic sensing (DAS), and GPS technologies. Additionally, balloons equipped with infrasound sensors were launched to capture signals at higher altitudes. This campaign (the largest of its kind so far) yielded a wealth of invaluable data anticipated to fuel scientific inquiry for years to come. The success of the observational campaign is evidenced by the near-universal detection of signals across instruments, both proximal and distal. This paper presents a comprehensive overview of the collective scientific effort, field deployment, and preliminary findings. The early findings have the potential to inform future space missions and terrestrial campaigns, contributing to our understanding of meteoroid interactions with planetary atmospheres. Furthermore, the dataset collected during this campaign will improve entry and propagation models as well as augment the study of atmospheric dynamics and shock phenomena generated by meteoroids and similar sources., Comment: 87 pages, 14 figures

This brief examines which students in the Houston Independent School District (HISD) were more likely to choose the STEM endorsement in ninth grade. The study examined STEM endorsement choice among students who began high school in the 2014-2015 and 2015-2016 school years. The analyses showed female students were significantly less likely to choose the STEM endorsement than male students. Furthermore, Asian and Pacific Islander students were more likely to select the STEM endorsement than Black, Hispanic, and White students. Finally, the analyses found a positive relationship between students' scores on the STAAR science test in eighth grade and STEM endorsement choice upon high school entry.

This study examined whether there were gendered patterns in STEM endorsement choice in the Houston Independent School District (HISD) and how those patterns changed over time, in the wake of a policy change to guidance counseling. The first students required to choose high school endorsements were freshmen in 2014-2015 and graduated high school in spring 2018. The second cohort of students required to do so were freshmen in 2015-2016 and graduated in spring 2019. Students in this second cohort met with their guidance counselor during their senior year to check in on their endorsement progress; this meeting was called the Personal Graduation Plan (PGP) check-in. This was a new district policy implemented beginning in fall 2018, which means that the first cohort did not experience the PGP check-in, while the second cohort did. This study reveals gender gaps in STEM endorsement choice among ninth-grade students. For the high school graduating class of 2018, which did not experience the PGP check-in, female students were less likely than male students to choose the STEM endorsement at any point during high school. However, for the high school graduating class of 2019, which did experience the PGP check-in, female students were less likely than male students to choose the STEM endorsement upon high school entry. Importantly, however, this gender gap in STEM endorsement choice nearly disappeared by high school graduation, suggesting that individualized counseling efforts might be a strategy to improve female retention in STEM.

This brief examines which students in the Houston Independent School District (HISD) are more likely to earn the STEM endorsement and whether STEM endorsement completion predicts college enrollment. Analyses show that gender, STEM magnet program enrollment, and cumulative high school grade point average (GPA) predict STEM endorsement completion. While STEM endorsement completion is associated with college choice, the relationship appears to be explained by academic performance measures, particularly SAT scores and GPA. In fact, if STEM and non-STEM students had the same test scores and grades, college enrollment gaps at 2-year-or-less; 4-year, less-selective; and 4-year, more-selective institutions would reduce. Overall, the findings suggest that the STEM endorsement functions, by design or coincidence, as a funneling mechanism for high-performing students into more-selective colleges and universities.

This brief examines where STEM deserts were located within Houston Independent School District (HISD) boundaries and the students most likely to live in a STEM desert. STEM deserts are areas in which students have more limited access to STEM endorsement paths or STEM course offerings. The analyses showed STEM deserts were more common in the southern and eastern parts of HISD and less common in the northern and western parts of the district. Students in lower socioeconomic neighborhoods were more likely to live in a STEM desert than students in higher socioeconomic neighborhoods. Black students were also more likely than White students to live in a STEM desert. The findings suggest areas in which the district may target resources or interventions to increase STEM offerings.

In the early stages of drug discovery, decisions regarding which experiments to pursue can be influenced by computational models. These decisions are critical due to the time-consuming and expensive nature of the experiments. Therefore, it is becoming essential to accurately quantify the uncertainty in machine learning predictions, such that resources can be used optimally and trust in the models improves. While computational methods for drug discovery often suffer from limited data and sparse experimental observations, additional information can exist in the form of censored labels that provide thresholds rather than precise values of observations. However, the standard approaches that quantify uncertainty in machine learning cannot fully utilize censored labels. In this work, we adapt ensemble-based, Bayesian, and Gaussian models with tools to learn from censored labels by using the Tobit model from survival analysis. Our results demonstrate that despite the partial information available in censored labels, they are essential to accurately and reliably model the real pharmaceutical setting.

Directed graphs provide more subtle and precise modelling tools for optimization in road networks than simple graphs. In particular, they are more suitable in the context of alternative fuel vehicles and new automotive technologies, like electric vehicles. In this paper, we introduce the new general concept of a reachability digraph associated with a road network to model the placement of refuelling facilities in road networks as k-dominating sets in the reachability digraph. Two new greedy heuristics are designed and experimentally tested to search for small k-dominating sets in two types of digraphs, including the reachability digraphs. Refined greedy strategies are shown to be efficient, capable of finding good quality solutions, and suitable for application in very large digraphs and road networks. Also, a probabilistic method is used to prove a new upper bound on the k-domination number of a digraph, which informs the development of a new randomized heuristic to search for k-dominating sets in the digraph. Generalizing the randomized heuristic ideas, making the heuristic more flexible, tuning and combining it with the greedy strategies allows us to obtain even better results for the reachability digraphs. Computational experiments are conducted for a case study of road networks in the West Midlands (UK)., Comment: 27 pages, 1 figure, 7 tables; preliminary results are presented in a short conference paper and at the International Network Optimization Conference INOC 2024, University College Dublin (Ireland) https://inoc2024.sciencesconf.org/

In the last decade, the first law of binary black hole mechanics played an important unifying role in the gravitational two-body problem. More recently, binary black hole scattering and the application of high-energy physics methods have provided a new avenue into this classical problem. In this Letter, we connect these two themes by extending the first law to the case of scattering orbits. We present derivations based on classical S-matrix, Hamiltonian, and pseudo-Hamiltonian methods, the last of which allows us to include dissipative effects for the first time. Finally, a "boundary to bound" map links this first law to the traditional bound-orbit version. Through this map a little-known observable for scatter orbits, the elapsed proper time, is mapped to the Detweiler redshift for bound orbits., Comment: 5 pages + supplemental material

K-Origins is a neural network layer designed to improve image-based network performances when learning colour, or intensities, is beneficial. Over 250 encoder-decoder convolutional networks are trained and tested on 16-bit synthetic data, demonstrating that K-Origins improves semantic segmentation accuracy in two scenarios: object detection with low signal-to-noise ratios, and segmenting multiple objects that are identical in shape but vary in colour. K-Origins generates output features from the input features, $\textbf{X}$, by the equation $\textbf{Y}_k = \textbf{X}-\textbf{J}\cdot w_k$ for each trainable parameter $w_k$, where $\textbf{J}$ is a matrix of ones. Additionally, networks with varying receptive fields were trained to determine optimal network depths based on the dimensions of target classes, suggesting that receptive field lengths should exceed object sizes. By ensuring a sufficient receptive field length and incorporating K-Origins, we can achieve better semantic network performance., Comment: 16 pages, 13 figures, 1 table

Several different proof translations exist between classical and intuitionistic logic (negative translations), and intuitionistic and linear logic (Girard translations). Our aims in this paper are (1) to show that all these systems can be expressed as extensions of a basic logical system (essentially intuitionistic linear logic), and that (2) with this common logical basis, a common approach to devising and simplifying such proof translations can be formalised. Via this process of ``simplification'' we get the most well-known translations in the literature.

The possibility of observing spectral features in exoplanet atmospheres with space missions like JWST and ARIEL necessitates the accurate modelling of cloud particle opacities. In exoplanet atmospheres, cloud particles can be made from multiple materials and be considerably chemically heterogeneous. Therefore, assumptions on the morphology of cloud particles are required to calculate their opacities. The aim of this work is to analyse how different approaches to calculate the opacities of heterogeneous cloud particles affect cloud particle optical properties. We calculate cloud particle optical properties using seven different mixing treatments: four effective medium theories (EMTs: Bruggeman, Landau-Lifshitz-Looyenga (LLL), Maxwell-Garnett, and Linear), core-shell, and two homogeneous cloud particle approximations. We study the mixing behaviour of 21 commonly considered cloud particle materials for exoplanets. To analyse the impact on observations, we study the transmission spectra of HATS-6b, WASP-39b, WASP-76b, and WASP-107b.Materials with large refractive indices, like iron-bearing species or carbon, can change the optical properties of cloud particles when they comprise less than 1\% of the total particle volume. The mixing treatment of heterogeneous cloud particles also has an observable effect on transmission spectroscopy. Assuming core-shell or homogeneous cloud particles results in less muting of molecular features and retains the cloud spectral features of the individual cloud particle materials. The predicted transit depth for core-shell and homogeneous cloud particle materials are similar for all planets used in this work. If EMTs are used, cloud spectral features are broader and cloud spectral features of the individual cloud particle materials are not retained. Using LLL leads to less molecular features in transmission spectra compared to Bruggeman., Comment: 21 pages, 15 figures, Accepted by A&A

Short-period gas giant planets have been shown to be significantly rarer for host stars less massive than the Sun. We report the discovery of two transiting giant planets - TOI-2379 b and TOI-2384 b - with low-mass (early M) host stars. Both planets were detected using TESS photometry and for both the transit signal was validated using ground based photometric facilities. We confirm the planetary nature of these companions and measure their masses using radial velocity observations. We find that TOI-2379 b has an orbital period of 5.469 d and a mass and radius of $5.76\pm0.20$ M$_{J}$ and $1.046\pm0.023$ R$_{J}$ and TOI-2384 b has an orbital period of 2.136 d and a mass and radius of $1.966\pm0.059$ M$_{J}$ and $1.025\pm0.021$ R$_{J}$. TOI-2379 b and TOI-2384 b have the highest and third highest planet-to-star mass ratios respectively out of all transiting exoplanets with a low-mass host star, placing them uniquely among the population of known exoplanets and making them highly important pieces of the puzzle for understanding the extremes of giant planet formation., Comment: Accepted for publication in MNRAS. 15 pages, 12 figures

This article investigates neighborhoods' sizes in the enhanced power graph (as known as the cyclic graph) associated with a finite group. In particular, we characterize finite $p$-groups with the smallest maximum size for neighborhoods of nontrivial element in its enhanced power graph., Comment: 6 pages

Detecting atmospheres around planets with a radius below 1.6 R$_{\oplus}$, commonly referred to as rocky planets (Rogers_2015, Rogers_2021), has proven to be challenging. However, rocky planets orbiting M-dwarfs are ideal candidates due to their favorable planet-to-star radius ratio. Here, we present one transit observation of the Super-Earth L98-59d (1.58 R$_{\oplus}$, 2.31 M$_{\oplus}$), at the limit of rocky/gas-rich, using the JWST NIRSpec G395H mode covering the 2.8 to 5.1 microns wavelength range. The extracted transit spectrum from a single transit observation deviates from a flat line by 2.6 to 5.6$\sigma$, depending on the data reduction and retrieval setup. The hints of an atmospheric detection are driven by a large absorption feature between 3.3 to 4.8 microns. A stellar contamination retrieval analysis rejected the source of this feature as being due to stellar inhomogeneities, making the best fit an atmospheric model including sulfur-bearing species, suggesting that the atmosphere of L98-59d may not be at equilibrium. This result will need to be confirmed by the analysis of the second NIRSpec G395H visit in addition to the NIRISS SOSS transit observation., Comment: Accepted for publication in the Astrophysical Journal Letters (ApJL), August 25, 2024

Although exoplanetary science was not initially projected to be a substantial part of the Spitzer mission, its exoplanet observations set the stage for current and future surveys with JWST and Ariel. We present a comprehensive reduction and analysis of Spitzer's 4.5 micron phase curves of 29 hot Jupiters on low-eccentricity orbits. The analysis, performed with the Spitzer Phase Curve Analysis (SPCA) pipeline, confirms that BLISS mapping is the best detrending scheme for most, but not all, observations. Visual inspection remains necessary to ensure consistency across detrending methods due to the diversity of phase curve data and systematics. Regardless of the model selection scheme - whether using the lowest-BIC or a uniform detrending approach - we observe the same trends, or lack thereof. We explore phase curve trends as a function of irradiation temperature, orbital period, planetary radius, mass, and stellar effective temperature. We discuss the trends that are robustly detected and provide potential explanations for those that are not observed. While it is almost tautological that planets receiving greater instellation are hotter, we are still far from confirming dynamical theories of heat transport in hot Jupiter atmospheres due to the sample's diversity. Even among planets with similar temperatures, other factors like rotation and metallicity vary significantly. Larger, curated sample sizes and higher-fidelity phase curve measurements from JWST and Ariel are needed to firmly establish the parameters governing day-night heat transport on synchronously rotating planets., Comment: 16 pages, 6 figures, submitted to AAS journal

Financial networks can be constructed using statistical dependencies found within the price series of speculative assets. Across the various methods used to infer these networks, there is a general reliance on predictive modelling to capture cross-correlation effects. These methods usually model the flow of mean-response information, or the propagation of volatility and risk within the market. Such techniques, though insightful, don't fully capture the broader distribution-level causality that is possible within speculative markets. This paper introduces a novel approach, combining quantile regression with a piecewise linear embedding scheme - allowing us to construct causality networks that identify the complex tail interactions inherent to financial markets. Applying this method to 260 cryptocurrency return series, we uncover significant tail-tail causal effects and substantial causal asymmetry. We identify a propensity for coins to be self-influencing, with comparatively sparse cross variable effects. Assessing all link types in conjunction, Bitcoin stands out as the primary influencer - a nuance that is missed in conventional linear mean-response analyses. Our findings introduce a comprehensive framework for modelling distributional causality, paving the way towards more holistic representations of causality in financial markets.

We use an ensemble of laser-cooled strontium atoms in a high-finesse cavity to cleanly emulate the technique of rf spectroscopy employed in studies of BEC-BCS physics in fermionic superfluids of degenerate cold gases. Here, we leverage the multilevel internal structure of the atoms to study the physics of Cooper pair breaking in this system. In doing so, we observe and distinguish the properties of two distinct many-body gaps, the BCS pairing gap and the spectral gap, using nondestructive readout techniques. The latter is found to depend on the populations of the internal atomic states, reflecting the chemical potential dependence predicted in fermionic superfluids. This work opens the path for more fully exploiting the rich internal structure of atoms in cavity QED emulators to study both analogous systems and also more exotic states yet to be realized., Comment: Main Text with Supplementary Material, 15 pages, 5 figures

The many initiatives on trustworthy AI result in a confusing and multipolar landscape that organizations operating within the fluid and complex international value chains must navigate in pursuing trustworthy AI. The EU's AI Act will now shift the focus of such organizations toward conformance with the technical requirements for regulatory compliance, for which the Act relies on Harmonized Standards. Though a high-level mapping to the Act's requirements will be part of such harmonization, determining the degree to which standards conformity delivers regulatory compliance with the AI Act remains a complex challenge. Variance and gaps in the definitions of concepts and how they are used in requirements between the Act and harmonized standards may impact the consistency of compliance claims across organizations, sectors, and applications. This may present regulatory uncertainty, especially for SMEs and public sector bodies relying on standards conformance rather than proprietary equivalents for developing and deploying compliant high-risk AI systems. To address this challenge, this paper offers a simple and repeatable mechanism for mapping the terms and requirements relevant to normative statements in regulations and standards, e.g., AI Act and ISO management system standards, texts into open knowledge graphs. This representation is used to assess the adequacy of standards conformance to regulatory compliance and thereby provide a basis for identifying areas where further technical consensus development in trustworthy AI value chains is required to achieve regulatory compliance., Comment: This work was presented at the 9th International Symposium on Language & Knowledge Engineering (LKE 2024) Dublin, Ireland, 4 - 6 June, 2024

The jet cross-section and jet-substructure observables in $p$$+$$p$ collisions at $\sqrt{s}=200$ GeV were measured by the PHENIX Collaboration at the Relativistic Heavy Ion Collider (RHIC). Jets are reconstructed from charged-particle tracks and electromagnetic-calorimeter clusters using the anti-$k_{t}$ algorithm with a jet radius $R=0.3$ for jets with transverse momentum within $8.0

This paper studies the power of the "abstract MAC layer" model in a single-hop asynchronous network. The model captures primitive properties of modern wireless MAC protocols. In this model, Newport [PODC '14] proves that it is impossible to achieve deterministic consensus when nodes may crash. Subsequently, Newport and Robinson [DISC '18] present randomized consensus algorithms that terminate with O(n3 log n) expected broadcasts in a system of n nodes. We are not aware of any results on other fault-tolerant distributed tasks in this model. We first study the computability aspect of the abstract MAC layer. We present a wait-free algorithm that implements an atomic register. Furthermore, we show that in general, k-set consensus is impossible. Second, we aim to minimize storage complexity. Existing algorithms require {\Omega}(n log n) bits. We propose four wait-free consensus algorithms that only need constant storage complexity. (Two approximate consensus and two randomized binary consensus algorithms.) One randomized algorithm terminates with O(n log n) expected broadcasts. All our consensus algorithms are anonymous, meaning that at the algorithm level, nodes do not need to have a unique identifier., Comment: A full version for our DISC24 paper

Quantum sensing based on solid-state spin defects provides a uniquely versatile platform for imaging physical properties at the nanoscale under diverse environmental conditions. Operation of most sensors used to-date is based on projective measurement along a single axis combined with computational extrapolation. Here, we show that the individually addressable carbon-related spin defect in hexagonal boron nitride is a multi-axis spin system for vectorial nanoscale magnetometry. We demonstrate how its low symmetry and strongly spin-selective direct and reverse intersystem crossing dynamics provide sub-$\mu$T/$\sqrt{\text{Hz}}$ magnetic-field sensitivity for both on and off-axis bias magnetic field exceeding 50 mT. Alongside these features, the room-temperature operation and the nanometer-scale proximity enabled by the van der Waals host material further consolidate this system as an exciting quantum sensing platform.

We present Subaru/SCExAO + CHARIS broadband (JHK) integral field spectroscopy of HD 34700 A in polarized light. CHARIS has the unique ability to obtain polarized integral field images at 22 wavelength channels in broadband, as the incoming light is first split into different polarization states before passing though the lenslet array. We recover the transition disk around HD 34700 A in multiband polarized light in our data. We combine our polarized intensity data with previous total intensity data to examine the scattering profiles, scattering phase functions and polarized fraction of the disk at multiple wavelengths. We also carry out 3D Monte Carlo radiative transfer simulations of the disk using MCFOST, and make qualitative comparisons between our models and data to constrain dust grain properties. We find that in addition to micron-sized dust grains, a population of sub-micron grains is needed to match the surface brightness in polarized light and polarized fraction. This could indicate the existence of a population of small grains in the disk, or it could be caused by Mie theory simulations using additional small grains to compensate for sub-micron structures of real dust aggregates. We find models that match the polarized fraction of the data but the models do not apply strong constraints on the dust grain type or compositions. We find no models that can match all observed properties of the disk. More detailed modeling using realistic dust aggregates with irregular surfaces and complex structures is required to further constrain the dust properties.

Quantum computers must achieve large-scale, fault-tolerant operation to deliver on their promise of transformational processing power [1-4]. This will require thousands or millions of high-fidelity quantum gates and similar numbers of qubits [5]. Demonstrations using neutral-atom qubits trapped and manipulated by lasers have shown that this modality can provide high two-qubit gate (CZ) fidelities and scalable operation [6-10]. However, the gates in these demonstrations are driven by lasers that do not resolve individual qubits, with universal computation enabled by physical mid-circuit shuttling of the qubits. This relatively slow operation will greatly extend runtimes for useful, large-scale computation. Here we demonstrate a universal neutral-atom quantum computer with gate rates limited by optical switching times, rather than shuttling, by individually addressing tightly focused laser beams at an array of single atoms. We achieve CZ fidelity of 99.35(4)% and local single qubit RZ gate fidelity of 99.902(8)%. Moreover, we demonstrate non-destructive readout of alkali-atom qubits with sub-percent loss, which boosts operational speed. This technique also enables us to measure 99.73(3)% CZ fidelity with atom-loss events excluded, which is a record among long lived neutral-atom qubits and highlights the path to higher fidelity and error correction. Our results represent a critical step towards large-scale, fault-tolerant neutral-atom quantum computers that can execute computations on practical timescales.

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

While quiescent galaxies have comparable amounts of cool gas in their outer circumgalactic medium (CGM) compared to star-forming galaxies, they have significantly less interstellar gas. However, open questions remain on the processes causing galaxies to stop forming stars and stay quiescent . Theories suggest dynamical interactions with the hot corona prevent cool gas from reaching the galaxy, therefore predicting the inner regions of quiescent galaxy CGMs are devoid of cool gas. However, there is a lack of understanding of the inner regions of CGMs due to the lack of spatial information in quasar-sightline methods. We present integral-field spectroscopy probing 10--20~kpc (2.4--4.8 R\textsubscript{e}) around a massive quiescent galaxy using a gravitationally lensed star-forming galaxy. We detect absorption from Magnesium (MgII) implying large amounts of cool atomic gas (10\textsuperscript{8.4} -- 10\textsuperscript{9.3} M\textsubscript{$\odot$} with T$\sim$10\textsuperscript{4} Kelvin), in comparable amounts to star-forming galaxies. Lens modeling of Hubble imaging also reveals a diffuse asymmetric component of significant mass consistent with the spatial extent of the MgII absorption, and offset from the galaxy light profile. This study demonstrates the power of galaxy-scale gravitational lenses to not only probe the gas around galaxies, but to also independently probe the mass of the CGM due to it's gravitational effect., Comment: accepted nature communications physics

Transmission spectroscopy is the most widely used technique for studying exoplanet atmospheres. Since the planetary nightside faces the observer during a transit, highly irradiated giant exoplanets with warm nightsides emit thermal radiation that can contaminate transmission spectra. Observations of ultra-hot Jupiters in the near- and mid-infrared with JWST are especially susceptible to nightside contamination. However, nightside thermal emission is generally not considered in atmospheric retrievals of exoplanet transmission spectra. Here, we quantify the potential biases from neglecting nightside thermal emission in multidimensional atmospheric retrievals of an ultra-hot Jupiter. Using simulated JWST transmission spectra of the ultra-hot Jupiter WASP-33b (0.8-12 $\mu$m), we find that transmission spectra retrievals without nightside emission can overestimate molecular abundances by almost an order-of-magnitude and underestimate the dayside temperature by $\gtrsim$ 400 K. We show that a modified retrieval prescription, including both transmitted light and nightside thermal emission, correctly recovers the atmospheric properties and is favored by Bayesian model comparisons. Nightside thermal contamination can be readily implemented in retrieval models via a first-order approximation, and we provide formulae to estimate whether this effect is likely to be significant for a given planet. We recommend that nightside emission should be included as standard practice when interpreting ultra-hot Jupiter transmission spectra with JWST., Comment: 21 pages, 11 figures. Accepted for publication in ApJ

We advocate for further prioritisation of atmospheric characterisation observations of high mass transiting exoplanets and brown dwarfs. This population acts as a unique comparative sample to the directly imaged exoplanet and brown dwarf populations, of which a range of JWST characterisation observations are planned. In contrast, only two observations of transiting exoplanets in this mass regime were performed in Cycle 1, and none are planned for Cycle 2. Such observations will: improve our understanding of how irradiation influences high gravity atmospheres, provide insights towards planetary formation and evolution across this mass regime, and exploit JWST's unique potential to characterise exoplanets across the known population., Comment: 4 pages, 2 figures. This white paper was submitted following a call from the "Working Group on Strategic Exoplanet Initiatives with HST and JWST" (https://sites.google.com/view/exoplanet-strategy-wg, final report in 10.48550/arXiv.2404.02932)

We theoretically investigate the out-of-equilibrium dynamics of irregular one- and two-dimensional arrays of Rydberg dipoles featuring spatially anisotropic interactions. Starting from a collectively polarized initial state, we map out the dynamical phase diagram and identify a crossover between regimes of regular and anomalously slow relaxation of the initial collective order, that strongly depends on both the degree of interaction disorder and anisotropy. In addition, we find the regime of slow relaxation is characterized by a sub-ballistic propagation of correlations that remained confined to short distances even at long times. To explain our findings we develop an analytic model based on decoupled clusters of interacting dipoles that goes beyond prior theoretical works and enables us to identify multiple relaxation timescales. Our findings can be relevant for a wide variety of quantum science platforms naturally featuring disordered dipolar interactions, including polar molecules, frozen Rydberg gases and NV centers., Comment: 13 pages and 8 figures

Current methods for verifying quantum computers are predominately based on interactive or automatic theorem provers. Considering that quantum computers are dynamical in nature, this paper employs and extends the concepts from the verification of dynamical systems to verify properties of quantum circuits. Our main contribution is to propose k-inductive barrier certificates over complex variables and show how to compute them using Hermitian Sum of Squares optimization. We apply this new technique to verify properties of different quantum circuits., Comment: 20 pages, 6 figures

The success of Large Language Models (LLMs) in multicultural environments hinges on their ability to understand users' diverse cultural backgrounds. We measure this capability by having an LLM simulate human profiles representing various nationalities within the scope of a questionnaire-style psychological experiment. Specifically, we employ GPT-3.5 to reproduce reactions to persuasive news articles of 7,286 participants from 15 countries; comparing the results with a dataset of real participants sharing the same demographic traits. Our analysis shows that specifying a person's country of residence improves GPT-3.5's alignment with their responses. In contrast, using native language prompting introduces shifts that significantly reduce overall alignment, with some languages particularly impairing performance. These findings suggest that while direct nationality information enhances the model's cultural adaptability, native language cues do not reliably improve simulation fidelity and can detract from the model's effectiveness., Comment: 18 pages, 8 figures, Published as a conference paper at COLM 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

In this paper, we construct a Real equivariant version of the B\"okstedt spectral sequence which takes inputs in the theory of Real Hochschild homology developed by Angelini-Knoll, Gerhardt, and Hill and converges to the equivariant homology of Real topological Hochschild homology, $\text{THR}$. We also show that when $A$ is a commutative $C_2$-ring spectrum, $\text{THR}(A)$ has the structure of an $A$-Hopf algebroid in the $C_2$-equivariant stable homotopy category.

Variational analysis presents a unified theory encompassing in particular both smoothness and convexity. In a Euclidean space, convex sets and smooth manifolds both have straightforward local geometry. However, in the most basic hybrid case of feasible regions consisting of pre-images of convex sets under maps that are once (but not necessarily twice) continuously differentiable, the geometry is less transparent. We define a new approximate convexity property, that holds both for such feasible regions and also for all prox-regular sets. This new property requires that nearby points can always be joined by smooth feasible paths that are almost straight. In particular, in the terminology of real algebraic geometry, such feasible regions are locally normally embedded in the Euclidean space.

In physics, density matrices are used to represent mixed states, i.e. probabilistic mixtures of pure states. This concept has previously been used to model lexical ambiguity. In this paper, we consider metaphor as a type of lexical ambiguity, and examine whether metaphorical meaning can be effectively modelled using mixtures of word senses. We find that modelling metaphor is significantly more difficult than other kinds of lexical ambiguity, but that our best-performing density matrix method outperforms simple baselines as well as some neural language models., Comment: In Proceedings QPL 2024, arXiv:2408.05113

Purpose: Estimation of multi-compartment intravoxel flow in fD in ml/100g/min with multi-b-value diffusion weighted imaging and a multi-Gaussian model in the kidneys. Theory and Methods: A multi-Gaussian model of intravoxel flow using water transport time to quantify fD is presented and simulated. Multi-compartment anisotropic DWI signal is simulated analyzed with (1) a rigid bi-exponential, (2) a rigid tri-exponential, and (3) diffusion spectrum imaging model of intravoxel incoherent motion (spectral diffusion). The application is demonstrated in a two-center study of 54 kidney allografts with 9 b-value advanced DWI that were split by function (CKD-EPI 2021 eGFR<45ml/min/1.73m2) and fibrosis (Banff 2017 interstitial fibrosis and tubular atrophy score 0-6). Results: Spectral diffusion demonstrated strong correlation to truth for simulated three-compartment anisotropic diffusion (y=1.08x+0.1, R2=0.71) and two-compartment anisotropic diffusion (y=0.91x+0.6, R2=0.74), outperforming rigid models in cases of variable compartment number. Use of a fixed regularization parameter set to {\lambda}=0.1 increased computation up to 208-fold and agreed with voxel-wise cross-validated regularization (concordance correlation coefficient=0.99). Spectral diffusion of renal allografts showed significant increase in tissue parenchyma compartment fD (f-stat=3.86, p=0.02). Tubular fD was significantly decreased in allografts with impaired function (Mann-Whitney Utest t-stat=-2.14, p=0.04). Conclusions: Quantitative multi-compartment intravoxel flow can be estimated in ml/100g/min with fD from multi-Gaussian diffusion, even with moderate anisotropy such as in kidneys. The use of spectral diffusion with a multi-Gaussian model and a fixed regularization parameter shows promise in organs such as the kidney with variable numbers of physiologic compartments.

Sparse autoencoders (SAEs) are an unsupervised method for learning a sparse decomposition of a neural network's latent representations into seemingly interpretable features. Despite recent excitement about their potential, research applications outside of industry are limited by the high cost of training a comprehensive suite of SAEs. In this work, we introduce Gemma Scope, an open suite of JumpReLU SAEs trained on all layers and sub-layers of Gemma 2 2B and 9B and select layers of Gemma 2 27B base models. We primarily train SAEs on the Gemma 2 pre-trained models, but additionally release SAEs trained on instruction-tuned Gemma 2 9B for comparison. We evaluate the quality of each SAE on standard metrics and release these results. We hope that by releasing these SAE weights, we can help make more ambitious safety and interpretability research easier for the community. Weights and a tutorial can be found at https://huggingface.co/google/gemma-scope and an interactive demo can be found at https://www.neuronpedia.org/gemma-scope, Comment: 12 main text pages, and 14 pages of acknowledgements, references and appendices

This visual narrative is a first-person reflection of the previous pictorial at the 1st International Workshop on Explainable AI for the Arts (XAIxArts) at ACM Creativity and Cognition 2023. The initial workshop pictorial explored a relationship between researcher and artificial intelligence, navigating creative challenges throughout the 2023 teaching block. It concluded by raising crucial questions regarding attribution transparency, the ethical dimensions of the creative process, and the delicate balance between inspiration and plagiarism. Subsequent discussions at the workshop yielded valuable insights, particularly concerning interpreting the creative journey. This follow-up visual narrative reflects the enduring impact of Makayla Lewis's interaction with AI. A self-portrait that delves into the interplay of creativity and introspection., Comment: 6 Pages, 7 Figures, Explainable AI for the Arts Workshop 2024 (XAIxArts 2024)

Axions are a well-motivated dark matter candidate particle. Haloscopes aim to detect axions in the galactic halo by measuring the photon signal resulting from axions interacting with a strong magnetic field. Existing haloscopes are primarily targeting axion masses which produce microwave-range photons and rely on microwave resonators to enhance the signal power. Only a limited subset of resonator modes are useful for this process, and current cylindrical-style cavities suffer from mode mixing and crowding from other fundamental modes. The majority of these modes can be eliminated by using photonic band gap (PBG) resonators. The band gap behavior of these structures allows for a resonator with mode selectivity based on frequency. We present results from the first tunable PBG resonator, a proof-of-concept design with a footprint compatible with axion haloscopes. We have thoroughly characterized the tuning range of two versions of the structure and report the successful confinement of the operating TM$_{010}$ mode and the elimination of all TE modes within the tuning range., Comment: 7 pages, 8 figures

We present the atmospheric characterization of the substellar companion HD 19467 B as part of the pioneering JWST GTO program to obtain moderate resolution spectra (R$\sim$2,700, 3-5$\mu$m) of a high-contrast companion with the NIRSpec IFU. HD 19467 B is an old, $\sim$9 Gyr, companion to a Solar-type star with multiple measured dynamical masses. The spectra show detections of CO, CO$_2$, CH$_4$, and H$_2$O. We forward model the spectra using Markov Chain Monte Carlo methods and atmospheric model grids to constrain the effective temperature and surface gravity. We then use NEWERA-PHOENIX grids to constrain non-equilibrium chemistry parameterized by $K_{zz}$ and explore molecular abundance ratios of the detected molecules. We find an effective temperature of 1103 K, with a probable range from 1000--1200 K, a surface gravity of 4.50 dex, with a range of 4.14--5.00, and deep vertical mixing, log$_{10}$($K_{zz}$), of 5.03, with a range of 5.00--5.44. All molecular mixing ratios are approximately Solar, leading to a C/O $\sim$0.55, which is expected from a T5.5 brown dwarf. Finally, we calculate an updated dynamical mass of HD 19467 B using newly derived NIRCam astrometry which we find to be $71.6^{+5.3}_{-4.6} M_{\rm{Jup}}$, in agreement with the mass range we derive from evolutionary models, which we find to be 63-75 $M_{\rm{Jup}}$.These observations demonstrate the excellent capabilities of the NIRSpec IFU to achieve detailed spectral characterization of substellar companions at high-contrast close to bright host stars, in this case at a separation of $\sim$1.6\arcsec with a contrast of 10$^{-4}$ in the 3-5 $\mu$m range., Comment: 35 pages, 20 figures