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There is substantial variation in the returns to a college degree. One determinant is whether a worker's employment is "matched" with their education. With a novel education-industry crosswalk and panel data on 295,000 graduates, we provide the first estimates of an education-industry match premium leveraging within-person variation in earnings. We document which majors have the most and least matching, how earnings premia vary across fields and gender, and how premia evolve over time. With robust estimators, we show that workers in industries "matched" with their degree experience an average earnings premium of 7-11%, with variation by degree level and major.

This paper presents a rationale for using professional and continuing education (PaCE) units at post-secondary institutions throughout California to design and implement talent-pipelines, research and development collaborations, and other knowledge ecosystems where emerging and returning professionals can acquire the knowledge, skills, and abilities (KSAs), as well as the experience, they need to address the challenges of the Fourth Industrial Revolution (4IR). The paper provides an analysis of the reasons why PaCE units are uniquely positioned to address the needs of industry and job seekers, and on a timetable that keeps pace with 4IR velocity.

Research for Action (RFA) in partnership with the University of Texas at Austin is engaged in a five-year mixed-methods study of the reforms associated with California AB 705. Over the course of the study, our team will assess the implementation, impact, and cost effectiveness of reforms associated with the law. This second interim report, presented at the conclusion of year three of the study, focuses on gaining a deeper understanding of on-campus implementation through a faculty survey administered to math and English departments across our study sample, an Interrupted Time Series analysis with nine cohorts of FTIC student data, and preliminary data collection for our cost effectiveness study. Collectively, these data highlight significant changes that colleges have made on campus regarding shifting enrollments from developmental education into transfer-level coursework in both English and math, and providing additional supports to students to promote retention and completion. We find that AB 705 has demonstrated notable successes in improving enrollment and completion rates in transfer-level courses, particularly in math, among FTIC students in California's community colleges. While our survey results suggest that faculty believe additional resources and supports would be helpful, most faculty report that implementation supports have been adequate.

Attracting and retaining high-quality teachers is a pressing policy concern. Increasing teacher salaries and creating more attractive compensation packages are often proposed as a potential solution. Signed into law in March 2023, the LEARNS Act increased Arkansas's minimum teacher salary from $36,000 to $50,000, guaranteed all teachers a minimum raise of $2,000, and added flexibility allowing school districts to deviate from seniority-based traditional salary schedules. To study school districts' adjustments to the new legislation, we collected information about districts' teacher compensation policies one year before and the first year of implementation. We also integrated this data with teachers' administrative records to study patterns of teacher retention and mobility. Our results reveal a more equitable distribution of starting teacher salaries across districts, with minimal variation. The LEARNS Act notably increased funding for rural and high-poverty districts, mitigating the negative association between starting salaries and district poverty rates. However, the initial effects on teacher retention and mobility were modest. While some positive trends emerged, such as reduced probabilities of teachers transitioning to non-instructional roles and increased new teacher placement in geographic areas of shortage, broader impacts on retention and mobility were limited in the first year of implementation.

When employees expect evaluation and performance incentives will continue (or begin) in the future, the potential future rewards create an incentive to invest in relevant skills today. Because skills benefit job performance, the effects of evaluation can persist after the rewards end or even anticipate the start of rewards. I provide empirical evidence of these dynamics from a quasi-experiment in Tennessee schools. New performance measures improve teachers' value-added contributions to student achievement. But improvements are twice as large when the teacher also expects future rewards linked to future scores. Value-added remains at the now higher level after performance incentives end.

DarkSide-20k (DS-20k) is a dark matter detection experiment under construction at the Laboratori Nazionali del Gran Sasso (LNGS) in Italy. It utilises ~100 t of low radioactivity argon from an underground source (UAr) in its inner detector, with half serving as target in a dual-phase time projection chamber (TPC). The UAr cryogenics system must maintain stable thermodynamic conditions throughout the experiment's lifetime of >10 years. Continuous removal of impurities and radon from the UAr is essential for maximising signal yield and mitigating background. We are developing an efficient and powerful cryogenics system with a gas purification loop with a target circulation rate of 1000 slpm. Central to its design is a condenser operated with liquid nitrogen which is paired with a gas heat exchanger cascade, delivering a combined cooling power of >8 kW. Here we present the design choices in view of the DS-20k requirements, in particular the condenser's working principle and the cooling control, and we show test results obtained with a dedicated benchmarking platform at CERN and LNGS. We find that the thermal efficiency of the recirculation loop, defined in terms of nitrogen consumption per argon flow rate, is 95 % and the pressure in the test cryostat can be maintained within $\pm$(0.1-0.2) mbar. We further detail a 5-day cool-down procedure of the test cryostat, maintaining a cooling rate typically within -2 K/h, as required for the DS-20k inner detector. Additionally, we assess the circuit's flow resistance, and the heat transfer capabilities of two heat exchanger geometries for argon phase change, used to provide gas for recirculation. We conclude by discussing how our findings influence the finalisation of the system design, including necessary modifications to meet requirements and ongoing testing activities., Comment: 45 pages, 24 figures

Research for Action (RFA) in partnership with the University of Texas at Austin is engaged in a five-year mixed-methods study of the reforms associated with California AB 705. Over the course of the study, our team will assess the implementation, impact, and cost effectiveness of reforms associated with the law. This report first offers a descriptive quantitative analysis of short-term outcome (enrollment and completion) trends in math and English at the state level. This descriptive analysis examines the relationship between AB 705 and course enrollment and completion, which will serve as the basis for the quasi-experimental study in subsequent project years. The second part of the report presents findings from institutional site visits aimed at understanding how institutions have implemented the reforms, who is involved in implementation, and how implementation is experienced by students.

To develop a deeper understanding of who Child Care and Early Education (CCEE) educators are--and what influences impact the entry, retention, turnover, and advancement (that is, the workforce dynamics) in this industry--the Building and Sustaining the Child Care and Early Education Workforce (BASE) research team identified and documented existing literature about the CCEE workforce and strategies that are intended to strengthen it. The team conducted a literature review (among several other research activities) to identify, review, and synthesize relevant literature and the evidence base on both multilevel influences that may shape CCEE workforce dynamics and the effectiveness of strategies that aim to build a sustained, qualified CCEE workforce. The team also conducted an environmental scan--a review to identify strategies currently being implemented to build, advance, and sustain the CCEE workforce. This annotated bibliography contains a comprehensive list of the publications that were formally included in the literature review to provide researchers, practitioners, and policymakers with a quick guide to understanding the recent research landscape of the CCEE workforce. This annotated bibliography details the methods that were used to review the published literature and summarizes elements of the publications.

Child care and early education (CCEE) are essential resources for families and children across the country. Yet qualified educators are choosing to leave their positions, and young professionals are choosing not to enter the field. This instability has been a long-lasting issue and is thought to be driven largely by structural and systemic forces that shape the everyday experiences of the CCEE workforce. These issues have been exacerbated by the COVID-19 pandemic. This report lays out a conceptual framework to serve as a guide for researchers, policymakers, and administrators who are conducting research on the CCEE workforce and who are designing and implementing strategies to improve entry, retention, turnover, and advancement of the workforce. This report is also intended to inform how the field can work to build and sustain this critical workforce. The conceptual framework consists of three main components that are intended to provide a clear understanding of factors that can disrupt the stability of the CCEE workforce pipeline. By articulating the main components, the conceptual framework encourages researchers, policymakers, and administrators to consider a range of multilevel influences on workforce dynamics when designing strategies and when evaluating whether strategies are working as intended. This framework also aims to underscore that the individuals who make up the workforce--many of whom have been marginalized due to race, ethnicity, social class, and gender--interact with broader social, political, and cultural contexts that shape economic and educational policies, structures, and opportunities.

The provisions in the Every Student Succeeds Act (ESSA) reauthorization of the Elementary and Secondary Education Act (ESEA) include (1) the requirement for states to periodically review resource allocation in local education agencies (LEAs) serving a significant number of schools identified for comprehensive support and improvement (CSI), targeted support and improvement (TSI), and additional targeted support and improvement (ATSI) and (2) the requirement that CSI and ATSI plans both identify and address local resource inequities. ESSA requires states to periodically review resource allocation to support school improvement in schools that qualify for comprehensive and targeted support. In 2019, the Resource Allocation Review Community of Practice (RAR CoP) of the United States Department of Education (the Department) provided a useful foundation. The RAR CoP calls upon state agencies to connect the additional resource inequity provisions outlined in ESSA and align resource allocation reviews with the comprehensive school improvement. Building on the guidance offered by the RAR CoP, Utah, with the support of WestEd's Region 15 Comprehensive Center (R15CC), was among the first states to design and implement an RAR process. This report shares some discoveries and lessons learned during the design and implementation process.

This document provides state education agency (SEA) leaders with a systematized approach to identifying and defining elements, major tasks, and deliverables for conducting a meaningful resource allocation review (RAR). Based on the findings of an intensive four-year design process, field research, and recommendations from the pilot audit of the RAR process conducted by the U.S. Department of Education, this document: (1) offers education leaders at the state and local level with concrete examples of resource inequities; (2) presents considerations for decision-making around resources, and (3) proposes ways to reduce the burden on LEAs and schools by streamlining the RAR completion process.

We propose machine learning (ML) models to predict the electron density -- the fundamental unknown of a material's ground state -- across the composition space of concentrated alloys. From this, other physical properties can be inferred, enabling accelerated exploration. A significant challenge is that the number of sampled compositions and descriptors required to accurately predict fields like the electron density increases rapidly with species. To address this, we employ Bayesian Active Learning (AL), which minimizes training data requirements by leveraging uncertainty quantification capabilities of Bayesian Neural Networks. Compared to strategic tessellation of the composition space, Bayesian-AL reduces the number of training data points by a factor of 2.5 for ternary (SiGeSn) and 1.7 for quaternary (CrFeCoNi) systems. We also introduce easy-to-optimize, body-attached-frame descriptors, which respect physical symmetries and maintain approximately the same descriptor-vector size as alloy elements increase. Our ML models demonstrate high accuracy and generalizability in predicting both electron density and energy across composition space.

Medical image quality assessment (MIQA) is essential for reliable medical image analysis. While deep learning has shown promise in this field, current models could be misled by spurious correlations learned from data and struggle with out-of-distribution (OOD) scenarios. To that end, we propose an MIQA framework based on a concept from causal inference: Probability of Necessity and Sufficiency (PNS). PNS measures how likely a set of features is to be both necessary (always present for an outcome) and sufficient (capable of guaranteeing an outcome) for a particular result. Our approach leverages this concept by learning hidden features from medical images with high PNS values for quality prediction. This encourages models to capture more essential predictive information, enhancing their robustness to OOD scenarios. We evaluate our framework on an Anterior Segment Optical Coherence Tomography (AS-OCT) dataset for the MIQA task and experimental results demonstrate the effectiveness of our framework.

We present a transmission spectrum of the misaligned hot Jupiter WASP-15b from 2.8--5.2 microns observed with JWST's NIRSpec/G395H grating. Our high signal to noise data, which has negligible red noise, reveals significant absorption by H$_2$O ($4.2\sigma$) and CO$_2$ ($8.9\sigma$). From independent data reduction and atmospheric retrieval approaches, we infer that WASP-15b's atmospheric metallicity is super-solar ($\gtrsim 15\times$ solar) and its C/O is consistent with solar, that together imply planetesimal accretion. Our GCM simulations for WASP-15b suggest that the C/O we measure at the limb is likely representative of the entire photosphere due to the mostly uniform spatial distribution of H$_2$O, CO$_2$ and CO. We additionally see evidence for absorption by SO$_2$ and absorption at 4.9$\mu$m, for which the current leading candidate is OCS, albeit with several caveats. If confirmed, this would be the first detection of OCS in an exoplanet atmosphere and point towards complex photochemistry of sulphur-bearing species in the upper atmosphere. These are the first observations from the BOWIE-ALIGN survey which is using JWST's NIRSpec/G395H instrument to compare the atmospheric compositions of aligned/low-obliquity and misaligned/high-obliquity hot Jupiters around F stars above the Kraft break. The goal of our survey is to determine whether the atmospheric composition differs across two populations of planets that have likely undergone different migration histories (disc versus disc-free) as evidenced by their obliquities (aligned versus misaligned)., Comment: 24 pages, 23 figures, 6 tables. Submitted to MNRAS

We introduce a LiDAR inertial odometry (LIO) framework, called LiPO, that enables direct comparisons of different iterative closest point (ICP) point cloud registration methods. The two common ICP methods we compare are point-to-point (P2P) and point-to-feature (P2F). In our experience, within the context of LIO, P2F-ICP results in less drift and improved mapping accuracy when robots move aggressively through challenging environments when compared to P2P-ICP. However, P2F-ICP methods require more hand-tuned hyper-parameters that make P2F-ICP less general across all environments and motions. In real-world field robotics applications where robots are used across different environments, more general P2P-ICP methods may be preferred despite increased drift. In this paper, we seek to better quantify the trade-off between P2P-ICP and P2F-ICP to help inform when each method should be used. To explore this trade-off, we use LiPO to directly compare ICP methods and test on relevant benchmark datasets as well as on our custom unpiloted ground vehicle (UGV). We find that overall, P2F-ICP has reduced drift and improved mapping accuracy, but, P2P-ICP is more consistent across all environments and motions with minimal drift increase., Comment: Submitted to ICRA 2025

JWST spectroscopy has discovered a population of $z \gtrsim 3.5$ galaxies with broad Balmer emission lines, and narrow forbidden lines, that are consistent with hosting active galactic nuclei (AGN). Many of these systems, now known as ``little red dots" (LRDs), are compact and have unique colors that are very red in the optical/near-infrared and blue in the ultraviolet. The relative contribution of galaxy starlight and AGN to these systems remains uncertain, especially for the galaxies with unusual blue+red spectral energy distributions. In this work, we use Balmer decrements to measure the independent dust attenuation of the broad and narrow emission-line components of a sample of 29 broad-line AGN identified from three public JWST spectroscopy surveys: CEERS, JADES, and RUBIES. Stacking the narrow components from the spectra of 25 sources with broad H$\rm{\alpha}$ and no broad H$\rm{\beta}$ results in a median narrow H$\rm{\alpha}$/H$\rm{\beta}$ = $2.47^{+0.05}_{-0.05}$ (consistent with $A_{v} = 0$) and broad H$\rm{\alpha}$/H$\rm{\beta}$ $> 8.85$ ($A_{v} > 3.63$). The narrow and broad Balmer decrements imply little-to-no attenuation of the narrow emission lines, which are consistent with being powered by star formation and located on larger physical scales. Meanwhile, the lower limit in broad H$\rm{\alpha}$/H$\rm{\beta}$ decrement, with broad H$\rm{\beta}$ undetected in the stacked spectrum of 25 broad-H$\rm{\alpha}$ AGN, implies significant dust attenuation of the broad-line emitting region that is presumably associated with the central AGN. Our results indicate that these systems, on average, are consistent with heavily dust-attenuated AGN powering the red parts of their SED while their blue UV emission is powered by unattenuated star formation in the host galaxy., Comment: 4 figures, 3 tables

In this paper we develop a systematic analysis of the properties of entanglement entropy in curved backgrounds using the replica approach. We explore the analytic $(q-1)$ expansion of R\'enyi entropy $S_q$ and its variations; our setup applies to generic variations, from symmetry transformations to variations of the background metric or entangling region. Our methodology elegantly reproduces and generalises results from the literature on entanglement entropy in different dimensions, backgrounds, and states. We use our analytic expansions to explore the behaviour of entanglement entropy in static black hole backgrounds under specific scaling transformations, and we explain why this behaviour is key to determining whether there are islands of entanglement., Comment: 93 pages, 18 figures

Nongravitational accelerations in the absence of observed activity have recently been identified on NEOs, opening the question of the prevalence of anisotropic mass-loss in the near-Earth environment. Motivated by the necessity of nongravitational accelerations to identify 2010 VL$_{65}$ and 2021 UA$_{12}$ as a single object, we investigate the problem of linking separate apparitions in the presence of nongravitational perturbations. We find that nongravitational accelerations on the order of $10^{-9}$ au/d$^2$ can lead to a change in plane-of-sky positions of $\sim10^3$ arcsec between apparitions. Moreover, we inject synthetic tracklets of hypothetical nongravitationally-accelerating NEOs into the Minor Planet Center orbit identification algorithms. We find that at large nongravitational accelerations ($|A_i|\geq10^{-8}$ au/d$^2$) these algorithms fail to link a significant fraction of these tracklets. We further show that if orbits can be determined for both apparitions, the tracklets will be linked regardless of nongravitational accelerations, although they may be linked to multiple objects. In order to aid in the identification and linkage of nongravitationally accelerating objects, we propose and test a new methodology to search for unlinked pairs. When applied to the current census of NEOs, we recover the previously identified case but identify no new linkages. We conclude that current linking algorithms are generally robust to nongravitational accelerations, but objects with large nongravitational accelerations may potentially be missed. While current algorithms are well-positioned for the anticipated increase in the census population from future survey missions, it may be possible to find objects with large nongravitational accelerations hidden in isolated tracklet pairs., Comment: 16 pages, 5 figures and 5 appendix figures. Accepted to ApJ

Fragmentation dynamics in the Coulomb explosion of hydrocarbons, specifically methane, ethane, propane, and butane, are investigated using time dependent density functional theory (TDDFT) simulations. The goal of this work is to elucidate the distribution of fragments generated under laser-driven Coulomb explosion conditions. Detailed analysis reveals the types of fragments formed, their respective charge states, and the optimal laser intensities required for achieving various fragmentations. Our results indicate distinct fragmentation patterns for each hydrocarbon, correlating with the molecular structure and ionization potential. Additionally, we identify the laser parameters that maximize fragmentation efficiency, providing valuable insights for experimental setups. This research advances our understanding of Coulomb explosion mechanisms and offers a foundation for further studies in controlled molecular fragmentation.

Teasers are an effective tool for promoting content in entertainment, commercial and educational fields. However, creating an effective teaser for long videos is challenging for it requires long-range multimodal modeling on the input videos, while necessitating maintaining audiovisual alignments, managing scene changes and preserving factual accuracy for the output teasers. Due to the lack of a publicly-available dataset, progress along this research direction has been hindered. In this work, we present DocumentaryNet, a collection of 1,269 documentaries paired with their teasers, featuring multimodal data streams of video, speech, music, sound effects and narrations. With DocumentaryNet, we propose a new two-stage system for generating teasers from long documentaries. The proposed TeaserGen system first generates the teaser narration from the transcribed narration of the documentary using a pretrained large language model, and then selects the most relevant visual content to accompany the generated narration through language-vision models. For narration-video matching, we explore two approaches: a pretraining-based model using pretrained contrastive language-vision models and a deep sequential model that learns the mapping between the narrations and visuals. Our experimental results show that the pretraining-based approach is more effective at identifying relevant visual content than directly trained deep autoregressive models.

We study the effects of AGN feedback on the Lyman-$\alpha$ forest 1D flux power spectrum (P1D). Using the Simba cosmological-hydrodynamic simulations, we examine the impact that adding different AGN feedback modes has on the predicted P1D. We find that, for Simba, the impact of AGN feedback is most dramatic at lower redshifts ($z<1$) and that AGN jet feedback plays the most significant role in altering the P1D. The effects of AGN feedback can be seen across a large range of wavenumbers ($1.5\times10^{-3}2.0$), AGN feedback has a $2\%$ effect on the P1D for $k<5\times10^{-2}$ s/km and an $8\%$ effect for $k>5\times10^{-2}$ s/km. We show that the small scale effect is reduced when normalizing the simulation to the observed mean flux. On large scales, the effect of AGN feedback appears via a change in the IGM temperature and is thus unlikely to bias cosmological parameters. The strong AGN jets in the Simba simulation can reproduce the $z>2$ Lyman-$\alpha$ forest. We stress that analyses comparing different AGN feedback models to future higher precision data will be necessary to determine the full extent of this effect., Comment: 17 pages, 5 figures, submitted to ApJ

Despite advances in diffusion-based text-to-music (TTM) methods, efficient, high-quality generation remains a challenge. We introduce Presto!, an approach to inference acceleration for score-based diffusion transformers via reducing both sampling steps and cost per step. To reduce steps, we develop a new score-based distribution matching distillation (DMD) method for the EDM-family of diffusion models, the first GAN-based distillation method for TTM. To reduce the cost per step, we develop a simple, but powerful improvement to a recent layer distillation method that improves learning via better preserving hidden state variance. Finally, we combine our step and layer distillation methods together for a dual-faceted approach. We evaluate our step and layer distillation methods independently and show each yield best-in-class performance. Our combined distillation method can generate high-quality outputs with improved diversity, accelerating our base model by 10-18x (230/435ms latency for 32 second mono/stereo 44.1kHz, 15x faster than comparable SOTA) -- the fastest high-quality TTM to our knowledge. Sound examples can be found at https://presto-music.github.io/web/.

Online communities are important spaces for members of marginalized groups to organize and support one another. To better understand the experiences of fat people -- a group whose marginalization often goes unrecognized -- in online communities, we conducted 12 semi-structured interviews with fat people. Our participants leveraged online communities to engage in consciousness raising around fat identity, learning to locate "the problem of being fat" not within themselves or their own bodies but rather in the oppressive design of the society around them. Participants were then able to use these communities to mitigate everyday experiences of anti-fatness, such as navigating hostile healthcare systems. However, to access these benefits, our participants had to navigate myriad sociotechnical harms, ranging from harassment to discriminatory algorithms. In light of these findings, we suggest that researchers and designers of online communities support selective fat visibility, consider fat people in the design of content moderation systems, and investigate algorithmic discrimination toward fat people. More broadly, we call on researchers and designers to contend with the social and material realities of fat experience, as opposed to the prevailing paradigm of treating fat people as problems to be solved in-and-of-themselves. This requires recognizing fat people as a marginalized social group and actively confronting anti-fatness as it is embedded in the design of technology.

Recent calls for pluralistic alignment emphasize that AI systems should address the diverse needs of all people. Yet, efforts in this space often require sorting people into fixed buckets of pre-specified diversity-defining dimensions (e.g., demographics, personalities, communication styles), risking smoothing out or even stereotyping the rich spectrum of individualistic variations. To achieve an authentic representation of diversity that respects individuality, we propose individualistic alignment. While individualistic alignment can take various forms, in this paper, we introduce IndieValueCatalog, a dataset transformed from the influential World Values Survey (WVS), to study language models (LMs) on the specific challenge of individualistic value reasoning. Specifically, given a sample of an individual's value-expressing statements, models are tasked with predicting their value judgments in novel cases. With IndieValueCatalog, we reveal critical limitations in frontier LMs' abilities to reason about individualistic human values with accuracies, only ranging between 55% to 65%. Moreover, our results highlight that a precise description of individualistic values cannot be approximated only via demographic information. We also identify a partiality of LMs in reasoning about global individualistic values, as measured by our proposed Value Inequity Index ({\sigma}INEQUITY). Finally, we train a series of Individualistic Value Reasoners (IndieValueReasoner) using IndieValueCatalog to enhance models' individualistic value reasoning capability, revealing new patterns and dynamics into global human values. We outline future research challenges and opportunities for advancing individualistic alignment.

We investigate the Lyman-$\alpha$ (Ly$\alpha$) and Lyman continuum (LyC) properties of the Sunburst Arc, a $z=2.37$ gravitationally lensed galaxy with a multiply-imaged, compact region leaking LyC and a triple-peaked Ly$\alpha$ profile indicating direct Ly$\alpha$ escape. Non-LyC-leaking regions show a redshifted Ly$\alpha$ peak, a redshifted and central Ly$\alpha$ peak, or a triple-peaked Ly$\alpha$ profile. We measure the properties of the Ly$\alpha$ profile from different regions of the galaxy using $R\sim5000$ Magellan/MagE spectra. We compare the Ly$\alpha$ spectral properties to LyC and narrowband Ly$\alpha$ maps from Hubble Space Telescope (HST) imaging to explore the subgalactic Ly$\alpha-$LyC connection. We find strong correlations (Pearson correlation coefficient $r>0.6$) between the LyC escape fraction ($f_{\rm esc}^{\rm LyC}$) and Ly$\alpha$ (1) peak separation $v_{\rm{sep}}$, (2) ratio of the minimum flux density between the redshifted and blueshifted Ly$\alpha$ peaks to continuum flux density $f_{\rm{min}}/f_{\rm{cont}}$, and (3) equivalent width. We favor a complex \ion{H}{1} geometry to explain the Ly$\alpha$ profiles from non-LyC-leaking regions and suggest two \ion{H}{1} geometries that could diffuse and/or rescatter the central Ly$\alpha$ peak from the LyC-leaking region into our sightline across transverse distances of several hundred parsecs. Our results emphasize the complexity of Ly$\alpha$ radiative transfer and its sensitivity to the anisotropies of \ion{H}{1} gas on subgalactic scales. Large differences in the physical scales on which we observe spatially variable direct escape Ly$\alpha$, blueshifted Ly$\alpha$, and escaping LyC photons in the Sunburst Arc underscore the importance of resolving the physical scales that govern Ly$\alpha$ and LyC escape., Comment: Submitted to The Astrophysical Journal with revisions from the first referee report. Comments welcome

We prove global existence, boundedness and decay for small data solutions $\psi$ to a general class of quasilinear wave equations on Kerr black hole backgrounds in the full sub-extremal range $|a|

Importance: Many individuals with drug-resistant epilepsy continue to have seizures after resective surgery. Accurate identification of focal brain abnormalities is essential for successful neurosurgical intervention. Current clinical approaches to identify structural abnormalities for surgical targeting in epilepsy do not use diffusion-weighted MRI (dMRI), despite evidence that dMRI abnormalities are present in epilepsy and may relate to the epileptogenic zone. Objective: To investigate whether surgical resection of diffusion abnormalities relates to post-operative seizure freedom. Design: This retrospective case-control study was conducted between 2009 and 2022. Data were acquired at the National Hospital for Neurology and Neurosurgery, UK. Study participants included 200 individuals with drug-resistant focal epilepsy, who underwent resective surgery, and 97 healthy controls used as a normative baseline. Main Outcomes: Spatial overlap between diffusion abnormality clusters and surgical resection masks, and relation to post-surgical outcome. Results: Surgical resections overlapping with the largest abnormal cluster significantly correlated with sustained seizure freedom at 12 months (83% vs 55%; p<0.0001) and over five years (p<0.0001). Notably, resecting only a small proportion of the largest cluster was associated with better seizure outcomes than cases with no resection of this cluster (p=0.008). Furthermore, sparing the largest cluster but resecting other large clusters still improved seizure freedom rates compared to no overlap (p=0.03). Conclusions: Our results suggest that abnormal clusters, identified using dMRI, are integral to the epileptogenic network, and even a partial removal of such an abnormal cluster is sufficient to achieve seizure freedom. The study highlights the potential of incorporating dMRI into pre-surgical planning to improve outcomes in focal epilepsy.

Numerical relativity simulations of merging black holes provide the most accurate description of the binary dynamics and the emitted gravitational wave signal. However, practical considerations such as imperfect initial data and initial parameters mean that achieving target parameters, such as the orbital eccentricity or the black hole spin directions, at the beginning of the usable part of the simulation is challenging. In this paper, we devise a method to produce simulations with specific target parameters, namely the Keplerian orbital parameters - eccentricity, semi-major axis, mean anomaly - and the black hole spin vectors using SpEC. The method is an extension of the current process for achieving vanishing eccentricity and it is based on a parameter control loop that iteratively numerically evolves the system, fits the orbit with analytical post-Newtonian equations, and calculates updated input parameters. Through SpEC numerical simulations, we demonstrate $\lesssim 10^{-3}$ and $O(\rm degree)$ convergence for the orbital eccentricity and the spin directions respectively in $\leq7$ iterations. These tests extend to binaries with mass ratios $q \leq 3$, eccentricities $e \leq 0.65$, and spin magnitudes $|\chi | \leq 0.75$. Our method for controlling the orbital and spin parameters of numerical simulations can be used to produce targeted simulations in sparsely covered regions of the parameter space or study the dynamics of relativistic binaries., Comment: 12 pages, 9 figures, submitted to PRD

Crystalline symmetry can be used to predict bulk and surface properties of topological phases. For non-interacting cases, symmetry-eigenvalue analysis of Bloch states at high symmetry points in the Brillouin zone simplifies the calculation of topological quantities. However, when open boundaries are present, and only the point group part of the symmetry group remains, it is unclear how to utilize crystalline symmetries to diagnose band topology. In this work, we introduce topological crystalline markers to characterize bulk topology in $C_n$-symmetric ($n=2,3,4,6$) crystalline insulators and superconductors with and without translation symmetry. These markers are expressed using a crystalline symmetry operator and the ground state projector, and are defined locally in position space. First, we provide a general method to calculate topological markers in periodic systems with an arbitrary number of unit cells. This includes cases where momentum quantization does not span all necessary high-symmetry points for computing the topological quantities, which we address using twisted boundary conditions. Second, we map these markers to the Chern number, bulk polarization, and sector charge for two-dimensional $C_n$-symmetric insulators in symmetry classes A, AI, AII, and superconductors in class D. Finally, we show how to numerically calculate the markers in finite-size systems with translation-symmetry (and even rotation-symmetry) breaking defects, and how to diagnose the bulk topology from the marker. Our results demonstrate how to compute bulk topological crystalline invariants locally in position space, thereby providing broader scope to diagnosing bulk crystalline topology that works even in inhomogeneous systems where there is no global rotation symmetry., Comment: 29 pages main text + 32 pages supplement

A turn constrained vehicle is initially located inside a polygon region and desires to escape in minimum time. First, the method of characteristics is used to describe the time-optimal strategies for reaching a line of infinite length. Next, the approach is extended to polygons constructed of a series of line segments. Using this construction technique, the min-time path to reach each edge is obtained; the resulting minimum of the set of optimal trajectories is then selected for escaping the polygon., Comment: 7 Pages, 6 Figures, Submitted to IFAC ACC, DISTRIBUTION STATEMENT A. Approved for public release. Distribution is unlimited; AFRL-2024-5262. This work is funded in-part by AFOSR, LRIR 24RQCOR002

Recent years have seen many audio-domain text-to-music generation models that rely on large amounts of text-audio pairs for training. However, symbolic-domain controllable music generation has lagged behind partly due to the lack of a large-scale symbolic music dataset with extensive metadata and captions. In this work, we present MetaScore, a new dataset consisting of 963K musical scores paired with rich metadata, including free-form user-annotated tags, collected from an online music forum. To approach text-to-music generation, we leverage a pretrained large language model (LLM) to generate pseudo natural language captions from the metadata. With the LLM-enhanced MetaScore, we train a text-conditioned music generation model that learns to generate symbolic music from the pseudo captions, allowing control of instruments, genre, composer, complexity and other free-form music descriptors. In addition, we train a tag-conditioned system that supports a predefined set of tags available in MetaScore. Our experimental results show that both the proposed text-to-music and tags-to-music models outperform a baseline text-to-music model in a listening test, while the text-based system offers a more natural interface that allows free-form natural language prompts.

Arthroscopy is a minimally invasive surgical procedure used to diagnose and treat joint problems. The clinical workflow of arthroscopy typically involves inserting an arthroscope into the joint through a small incision, during which surgeons navigate and operate largely by relying on their visual assessment through the arthroscope. However, the arthroscope's restricted field of view and lack of depth perception pose challenges in navigating complex articular structures and achieving surgical precision during procedures. Aiming at enhancing intraoperative awareness, we present a robust pipeline that incorporates simultaneous localization and mapping, depth estimation, and 3D Gaussian splatting to realistically reconstruct intra-articular structures solely based on monocular arthroscope video. Extending 3D reconstruction to Augmented Reality (AR) applications, our solution offers AR assistance for articular notch measurement and annotation anchoring in a human-in-the-loop manner. Compared to traditional Structure-from-Motion and Neural Radiance Field-based methods, our pipeline achieves dense 3D reconstruction and competitive rendering fidelity with explicit 3D representation in 7 minutes on average. When evaluated on four phantom datasets, our method achieves RMSE = 2.21mm reconstruction error, PSNR = 32.86 and SSIM = 0.89 on average. Because our pipeline enables AR reconstruction and guidance directly from monocular arthroscopy without any additional data and/or hardware, our solution may hold the potential for enhancing intraoperative awareness and facilitating surgical precision in arthroscopy. Our AR measurement tool achieves accuracy within 1.59 +/- 1.81mm and the AR annotation tool achieves a mIoU of 0.721., Comment: 8 pages, with 2 additional pages as the supplementary. Accepted by AE-CAI 2024

In percutaneous pelvic trauma surgery, accurate placement of Kirschner wires (K-wires) is crucial to ensure effective fracture fixation and avoid complications due to breaching the cortical bone along an unsuitable trajectory. Surgical navigation via mixed reality (MR) can help achieve precise wire placement in a low-profile form factor. Current approaches in this domain are as yet unsuitable for real-world deployment because they fall short of guaranteeing accurate visual feedback due to uncontrolled bending of the wire. To ensure accurate feedback, we introduce StraightTrack, an MR navigation system designed for percutaneous wire placement in complex anatomy. StraightTrack features a marker body equipped with a rigid access cannula that mitigates wire bending due to interactions with soft tissue and a covered bony surface. Integrated with an Optical See-Through Head-Mounted Display (OST HMD) capable of tracking the cannula body, StraightTrack offers real-time 3D visualization and guidance without external trackers, which are prone to losing line-of-sight. In phantom experiments with two experienced orthopedic surgeons, StraightTrack improves wire placement accuracy, achieving the ideal trajectory within $5.26 \pm 2.29$ mm and $2.88 \pm 1.49$ degree, compared to over 12.08 mm and 4.07 degree for comparable methods. As MR navigation systems continue to mature, StraightTrack realizes their potential for internal fracture fixation and other percutaneous orthopedic procedures.

Measurements of galaxy clustering are affected by RSD. Peculiar velocities, gravitational lensing, and other light-cone projection effects modify the observed redshifts, fluxes, and sky positions of distant light sources. We determine which of these effects leave a detectable imprint on several 2-point clustering statistics extracted from the EWSS on large scales. We generate 140 mock galaxy catalogues with the survey geometry and selection function of the EWSS and make use of the LIGER method to account for a variable number of relativistic RSD to linear order in the cosmological perturbations. We estimate different 2-point clustering statistics from the mocks and use the likelihood-ratio test to calculate the statistical significance with which the EWSS could reject the null hypothesis that certain relativistic projection effects can be neglected in the theoretical models. We find that the combined effects of lensing magnification and convergence imprint characteristic signatures on several clustering observables. Their S/N ranges between 2.5 and 6 (depending on the adopted summary statistic) for the highest-redshift galaxies in the EWSS. The corresponding feature due to the peculiar velocity of the Sun is measured with a S/N of order one or two. The $P_{\ell}(k)$ from the catalogues that include all relativistic effects reject the null hypothesis that RSD are only generated by the variation of the peculiar velocity along the line of sight with a significance of 2.9 standard deviations. As a byproduct of our study, we demonstrate that the mixing-matrix formalism to model finite-volume effects in the $P_{\ell}(k)$ can be robustly applied to surveys made of several disconnected patches. Our results indicate that relativistic RSD, the contribution from weak gravitational lensing in particular, cannot be disregarded when modelling 2-point clustering statistics extracted from the EWSS., Comment: 23 pages, 14 figures

JWST has now revealed a population of broad-line AGN at $z>4$ characterized by a distinctive SED shape, with very red rest-frame optical and very blue rest-frame UV continuum. While the optical continuum is thought to originate from the accretion disk, the origin of the UV continuum has been largely unclear. We report the detection of the strong rest-frame UV emission lines of CIII]$\lambda\lambda$1907,1909 and CIV$\lambda\lambda$1549,1551 in a "little red dot" AGN, COS-66964. Spectroscopically confirmed at $z=7.0371$, COS-66964 exhibits broad H$\alpha$ emission (FWHM $\sim 2000$ km s$^{-1}$), and weak broad H$\beta$, implying significant dust attenuation to the BLR ($A_V = 3.9^{+1.7}_{-0.9}$). The H$\alpha$ line width implies a central SMBH mass of $M_{\rm BH} = \left(1.9^{+1.6}_{-0.7}\right)\times10^{7}$ M$_\odot$, and an Eddington ratio $\lambda\sim0.3$-$0.5$. While marginal HeII$\lambda4687$ and [FeX]$\lambda6376$ detections further indicate that the AGN dominates in the rest-frame optical, the non-detection of HeII$\lambda1640$ in the UV despite high EW CIII] and CIV ($\sim 35$ {\AA}) is more consistent with photoionization by massive stars. The non-detection of MgII$\lambda\lambda$2800 is similarly inconsistent with an AGN scattered light interpretation. Assuming the rest-frame UV is dominated by stellar light, we derive a stellar mass of $\log M_\star/M_\odot\sim8.5$, implying an elevated $M_{\rm BH}/M_\star$ ratio $\sim2$ orders of magnitude above the local relation, but consistent with other high-$z$ AGN discovered by JWST. The source is unresolved in all bands, implying a very compact size $\lesssim200$ pc in the UV. This suggests that the simultaneous buildup of compact stellar populations (i.e., galaxy bulges) and the central SMBH is ongoing even at $z>7$., Comment: 14 pages, 6 figures; submitted to ApJL

Due to the dynamic nature of the semantic web, ontology version control is required to capture time-varying information, most importantly for widely-used ontologies. Despite the long-standing recognition of ontology versioning (OV) as a crucial component for efficient ontology management, the growing size of ontologies and accumulating errors caused by manual labour overwhelm current OV approaches. In this paper, we propose yet another approach to performing OV using existing ontology matching (OM) techniques and systems. We introduce a unified OM4OV pipeline. From an OM perspective, we reconstruct a new task formulation, performance measurement, and dataset construction for OV tasks. Reusing the prior alignment(s) from OM, we also propose a cross-reference mechanism to effectively reduce the matching candidature and improve overall OV performance. We experimentally validate the OM4OV pipeline and its cross-reference mechanism using three datasets from the Alignment Evaluation Initiative (OAEI) and exploit insights on OM used for OV tasks., Comment: 7 pages, 7 figures, 1 table

Fabrication of semiconductor heterostructures is now so precise that metrology has become a key challenge for progress in science and applications. It is now relatively straightforward to characterize classic III-V and group IV heterostructures consisting of slabs of different semiconductor alloys with thicknesses of $\sim$5 nm and greater using sophisticated tools such as X-ray diffraction, high energy X-ray photoemission spectroscopy, and secondary ion mass spectrometry. However, profiling thin layers with nm or sub-nm thickness, e.g. atomically thin dopant layers ($\delta$-layers), of impurities required for modulation doping and spin-based quantum and classical information technologies is more challenging. Here, we present theory and experiment showing how resonant-contrast X-ray reflectometry meets this challenge. The technique takes advantage of the change in the scattering factor of atoms as their core level resonances are scanned by varying the X-ray energy. We demonstrate the capability of the resulting element-selective, non-destructive profilometry for single arsenic $\delta$-layers within silicon, and show that the sub-nm electronic thickness of the $\delta$-layers corresponds to sub-nm chemical thickness. In combination with X-ray fluorescence imaging, this enables non-destructive three-dimensional characterization of nano-structured quantum devices. Due to the strong resonances at soft X-ray wavelengths, the technique is also ideally suited to characterize layered quantum materials, such as cuprates or the topical infinite-layer nickelates.

In the third APOKASC catalog, we present data for the complete sample of 15,808 evolved stars with APOGEE spectroscopic parameters and Kepler asteroseismology. We used ten independent asteroseismic analysis techniques and anchor our system on fundamental radii derived from Gaia $L$ and spectroscopic $T_{\rm eff}$. We provide evolutionary state, asteroseismic surface gravity, mass, radius, age, and the spectroscopic and asteroseismic measurements used to derive them for 12,418 stars. This includes 10,036 exceptionally precise measurements, with median fractional uncertainties in \nmax, \dnu, mass, radius and age of 0.6\%, 0.6\%, 3.8\%, 1.8\%, and 11.1\% respectively. We provide more limited data for 1,624 additional stars which either have lower quality data or are outside of our primary calibration domain. Using lower red giant branch (RGB) stars, we find a median age for the chemical thick disk of $9.14 \pm 0.05 ({\rm ran}) \pm 0.9 ({\rm sys})$ Gyr with an age dispersion of 1.1 Gyr, consistent with our error model. We calibrate our red clump (RC) mass loss to derive an age consistent with the lower RGB and provide asymptotic GB and RGB ages for luminous stars. We also find a sharp upper age boundary in the chemical thin disk. We find that scaling relations are precise and accurate on the lower RGB and RC, but they become more model dependent for more luminous giants and break down at the tip of the RGB. We recommend the usage of multiple methods, calibration to a fundamental scale, and the usage of stellar models to interpret frequency spacings., Comment: 43 pages, 25 figures, submitted ApJSupp. Comments welcome. Data tables available on request from pinsonneault.1@osu.edu

We define Ford Spheres $\mathcal{P}$ in hyperbolic $n$-space associated to Clifford-Bianchi groups $PSL_2(O)$ for $O$ orders in rational Clifford algebras associated to positive definite, integral, primitive quadratic forms. For $\mathcal{H}^2$ and $\mathcal{H}^3$ these spheres correspond to the classical Ford circles and Ford spheres (these are non-maximal subsets of classical Apollonian packings). We prove the Ford spheres are integral, have disjoint interiors, and intersect tangentially when they do intersect. If we assume that $O$ is Clifford-Euclidean then $\mathcal{P}$ is also connected. We also give connections to Dirichlet's Theorem and Farey fractions. In a discussion section, we pose some questions related to existing packings in the literature.

Faults on power lines and other electric equipment are known to cause wildfire ignitions. To mitigate the threat of wildfire ignitions from electric power infrastructure, many utilities preemptively de-energize power lines, which may result in power shutoffs. Data regarding wildfire ignition risks are key inputs for effective planning of power line de-energizations. However, there are multiple ways to formulate risk metrics that spatially aggregate wildfire risk map data, and there are different ways of leveraging this data to make decisions. The key contribution of this paper is to define and compare the results of employing six metrics for quantifying the wildfire ignition risks of power lines from risk maps, considering both threshold- and optimization-based methods for planning power line de-energizations. The numeric results use the California Test System (CATS), a large-scale synthetic grid model with power line corridors accurately representing California infrastructure, in combination with real Wildland Fire Potential Index data for a full year. This is the first application of optimal power shutoff planning on such a large and realistic test case. Our results show that the choice of risk metric significantly impacts the lines that are de-energized and the resulting load shed. We find that the optimization-based method results in significantly less load shed than the threshold-based method while achieving the same risk reduction.

Attempts to probe the atmospheres of rocky planets around M dwarfs present both promise and peril. While their favorable planet-to-star radius ratios enable searches for even thin secondary atmospheres, their high activity levels and high-energy outputs threaten atmosphere survival. Here, we present the 0.6--2.85$\mu$m transmission spectrum of the 1.1 Earth-radius, ~340K rocky planet TRAPPIST-1c obtained over two JWST NIRISS/SOSS transit observations. Each of the two spectra displays 100--500 ppm signatures of stellar contamination. Despite being separated by 367 days, the retrieved spot and faculae properties are consistent between the two visits, resulting in nearly identical transmission spectra. Jointly retrieving for stellar contamination and a planetary atmosphere rules out with high confidence (>3-$\sigma$) not only clear hydrogen-dominated atmospheres, but even thin, 1-bar high-mean molecular weight atmospheres rich in H$_2$O, NH$_3$, or CO (at the 2-$\sigma$ level). We find that the only atmosphere scenarios which our spectrum cannot rule out are CH$_4$- or CO$_2$-rich atmospheres, which are both unlikely to be retained when considering the photodestruction of CH$_4$ and the susceptibility of even a CO$_2$-rich atmosphere to escape given the cumulative high-energy irradiation experienced by the planet. Our results further stress the importance of robustly accounting for stellar contamination when analyzing JWST observations of exo-Earths around M dwarfs, as well as the need for high-fidelity stellar models to search for the potential signals of thin secondary atmospheres., Comment: Minor typo corrections and figure axis adjustments compared to previous version

In fragile watermarking, a sensitive watermark is embedded in an object in a manner such that the watermark breaks upon tampering. This fragile process can be used to ensure the integrity and source of watermarked objects. While fragile watermarking for model integrity has been studied in classification models, image transformation/generation models have yet to be explored. We introduce a novel, trigger-based fragile model watermarking system for image transformation/generation networks that takes advantage of properties inherent to image outputs. For example, manifesting watermarks as specific visual patterns, styles, or anomalies in the generated content when particular trigger inputs are used. Our approach, distinct from robust watermarking, effectively verifies the model's source and integrity across various datasets and attacks, outperforming baselines by 94%. We conduct additional experiments to analyze the security of this approach, the flexibility of the trigger and resulting watermark, and the sensitivity of the watermarking loss on performance. We also demonstrate the applicability of this approach on two different tasks (1 immediate task and 1 downstream task). This is the first work to consider fragile model watermarking for image transformation/generation networks.

We introduce a compact, two-camera laparoscope that combines active stereo depth estimation and speckle-illumination spatial frequency domain imaging (si-SFDI) to map profile-corrected, pixel-level absorption and reduced scattering optical properties in tissues with complex geometries. Our approach uses multimode fiber-coupled laser illumination to generate high-contrast speckle patterns, requiring only two images for optical property estimation. We demonstrate 3D profilometry using active stereo from low-coherence RGB laser flood illumination, which corrects for measured intensity variations caused by object height and surface angle differences. Validation against conventional SFDI in phantoms and an in-vivo human finger study showed good agreement, with profile-correction improving accuracy for complex geometries. This stereo-laparoscopic implementation of si-SFDI provides a simple method to obtain accurate optical property maps through a laparoscope, potentially offering quantitative endogenous contrast for minimally invasive surgical guidance.

Interactions between active individuals in animal collectives lead to emergent responses that remain elusive in synthetic soft matter. Here, shape-morphing polymers are used to create bio-inspired transient solids that self-assemble with controlled mechanical properties and disassemble on demand. Dilute-suspensions of magnetic, heat-responsive liquid crystal elastomer ribbons mechanically interlock, inducing reversible aggregation. A mathematical model is developed that sheds light on the role of topological mechanisms in aggregation. Aggregation was favored for ribbons with moderate curvature at 25C above crosslinking temperature as compared to flat ribbons or higher curvature ribbons at higher temperatures. The ribbon suspensions reversibly transition between fluid- and solid-like states, exhibiting up to 6 orders-of-magnitude increase in the storage moduli of the entangled aggregates compared with the liquid dispersions. Controlled dissociation is induced by imparting kinetic energy to the individual ribbons at high magnetic field rotation speeds (> 200 RPM). Ribbon shape and the medium in which dissociation occurs were shown to govern disassembly. Imparting dynamic collective behaviors into synthetic systems may enable a range of potential applications from bio-inspired soft robotics to injectable biomaterials., Comment: 16 pages, 6 figures

The Beryllium Electron capture in Superconducting Tunnel junctions (BeEST) experiment searches for evidence of heavy neutrino mass eigenstates in the nuclear electron capture decay of $^7$Be by precisely measuring the recoil energy of the $^7$Li daughter. In Phase-III, the BeEST experiment has been scaled from a single superconducting tunnel junction (STJ) sensor to a 36-pixel array to increase sensitivity and mitigate gamma-induced backgrounds. Phase-III also uses a new continuous data acquisition system that greatly increases the flexibility for signal processing and data cleaning. We have developed procedures for signal processing and spectral fitting that are sufficiently robust to be automated for large data sets. This article presents the optimized procedures before unblinding the majority of the Phase-III data set to search for physics beyond the standard model.

We investigate the effect of a constant static bias force on the dynamically induced shape morphing of a pre-buckled bistable beam, focusing on the beam's ability to change its vibration to be near different stable states under harmonic excitation. Our study explores four categories of oscillatory motions: switching, reverting, vacillating, and intra-well in the parameter space. We aim to achieve transitions between stable states of the pre-buckled bistable beam with minimal excitation amplitude. Our findings demonstrate the synergistic effects between dynamic excitation and static bias force, showing a broadening of the non-fractal region for switching behavior (i.e., switching from the first stable state to the second stable state) in the parameter space. This study advances the understanding of the dynamics of key structural components for multi-stable mechanical metamaterials, offering new possibilities for novel designs in adaptive applications.

We present cosmological parameter forecasts for the Euclid 6x2pt statistics, which include the galaxy clustering and weak lensing main probes together with previously neglected cross-covariance and cross-correlation signals between imaging/photometric and spectroscopic data. The aim is understanding the impact of such terms on the Euclid performance. We produce 6x2pt cosmological forecasts, considering two different techniques: the so-called harmonic and hybrid approaches, respectively. In the first, we treat all the different Euclid probes in the same way, i.e. we consider only angular 2pt-statistics for spectroscopic and photometric clustering, as well as for weak lensing, analysing all their possible cross-covariances and cross-correlations in the spherical harmonic domain. In the second, we do not account for negligible cross-covariances between the 3D and 2D data, but consider the combination of their cross-correlation with the auto-correlation signals. We find that both cross-covariances and cross-correlation signals, have a negligible impact on the cosmological parameter constraints and, therefore, on the Euclid performance. In the case of the hybrid approach, we attribute this result to the effect of the cross-correlation between weak lensing and photometric data, which is dominant with respect to other cross-correlation signals. In the case of the 2D harmonic approach, we attribute this result to two main theoretical limitations of the 2D projected statistics implemented in this work according to the analysis of official Euclid forecasts: the high shot noise and the limited redshift range of the spectroscopic sample, together with the loss of radial information from subleading terms such as redshift-space distortions and lensing magnification. Our analysis suggests that 2D and 3D Euclid data can be safely treated as independent, with a great saving in computational resources., Comment: 32 pages, 20 figures. Comments are welcome

We report on the first measurement of $J/\psi$ photoproduction from nuclei in the photon energy range of $7$ to $10.8$ GeV, extending above and below the photoproduction threshold in the free proton of $\sim8.2$ GeV. The experiment used a tagged photon beam incident on deuterium, helium, and carbon, and the GlueX detector at Jefferson Lab to measure the semi-inclusive $A(\gamma,e^+e^-p)$ reaction with a dilepton invariant mass $M(e^+e^-)\sim m_{J/\psi}=3.1$ GeV. The incoherent $J/\psi$ photoproduction cross sections in the measured nuclei are extracted as a function of the incident photon energy, momentum transfer, and proton reconstructed missing light-cone momentum fraction. Comparisons with theoretical predictions suggest an excess of the measured cross section for sub-threshold production and for interactions with high missing light-cone momentum fraction protons. The measured enhancement can be explained by modified gluon structure for high-virtuality bound-protons.