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Using data from the Quarterly Workforce Indicators, this brief explores changes in the Los Angeles County labor market and in the working-age population as a plausible explanation for some of the enrollment decline at the county's community college campuses.

Most selective colleges implemented test-optional admissions during the pandemic, making college entrance exam scores optional for applicants. We draw on descriptive, two-way fixed effects, and event study methods to examine variation in test-optional implementation during the pandemic and how implementation relates to selectivity and enrollment. For "test-optional" colleges during the pandemic, we found substantial variation in policy type (e.g., test optional, test free) and whether the policy extended to all applicants and scholarship consideration. Findings suggest test-optional implementation related to increases in Black student enrollment, mostly at moderately selective colleges and when policies extended to all applicants and scholarships. At highly selective colleges, findings suggest test-optional implementation related to an increase in applications but not consistent gains in enrollment.

The Wallace Foundation commissioned Research for Action and McClanahan Associates to study how out-of-school time intermediaries (OSTIs) responded to the COVID-19 pandemic and the role they could play in supporting communities moving forward. Citywide out-of-school time (OST) systems encompass a wide variety of afterschool and summer programs and associated provider organizations, youth participants, and their families. These systems were stretched during the COVID-19 pandemic and the national racial reckoning to respond to community needs in new and more equitable ways. Also impacted were OSTIs that manage OST systems within individual cities. OSTIs operate through various governance structures and perform a range of coordination functions intended to ensure quality, access, and equity in OST systems so that all youth have access to the unique out-of-school resources and opportunities they need to thrive.

As states incorporate measures of college readiness into their accountability systems, school and district leaders need effective strategies to identify and support students at risk of not enrolling in college. Although there is an abundant literature on early warning indicators for high school dropout, fewer studies focus on indicators for college enrollment, especially those that are simple to calculate and easy for practitioners to use. This study explores three potential indicators of college readiness that educational leaders may consider using as part of an early warning system for college enrollment. Using district administrative data, our analysis shows that an indicator based on attendance, grades, and advanced course-taking is slightly more effective at predicting college enrollment than indicators based on course failures or standardized test scores. However, the performance of these indicators varies across different student demographic and socioeconomic subgroups, highlighting the limitations of these measures and pointing to areas where they may need to be supplemented with contextual information. Through event history analysis, we demonstrate that the ninth grade is a particularly challenging year for students, especially those who are male, Black, Hispanic, or economically disadvantaged. These results suggest that educational leaders ought to consider identifying and targeting students at risk of not attending college with additional resources and support during the freshman year of high school.

One of the most challenging problems in the computational study of localization in quantum manybody systems is to capture the effects of rare events, which requires sampling over exponentially many disorder realizations. We implement an efficient procedure on a quantum processor, leveraging quantum parallelism, to efficiently sample over all disorder realizations. We observe localization without disorder in quantum many-body dynamics in one and two dimensions: perturbations do not diffuse even though both the generator of evolution and the initial states are fully translationally invariant. The disorder strength as well as its density can be readily tuned using the initial state. Furthermore, we demonstrate the versatility of our platform by measuring Renyi entropies. Our method could also be extended to higher moments of the physical observables and disorder learning.

We examine star-formation and dust properties for a sample of 660 galaxies at $1.37\leq z\leq 2.61$ in the MOSDEF survey by dividing them into groups with similarly-shaped spectral energy distributions (SEDs). For each group, we combine the galaxy photometry into a finely-sampled composite SED, and stack their spectra. This method enables the study of more complete galaxy samples, including galaxies with very faint emission lines. We fit these composite SEDs with Prospector to measure the stellar attenuation and SED-based star-formation rates (SFRs). We also derive emission-line properties from the spectral stacks, including Balmer decrements, dust-corrected SFRs, and metallicities. We find that stellar attenuation correlates most strongly with mass, while nebular attenuation correlates strongly with both mass and SFR. Furthermore, the excess of nebular compared to stellar attenuation correlates most strongly with SFR. The highest SFR group has 2 mag of excess nebular attenuation. Our results are consistent with a model in which star-forming regions become more dusty as galaxy mass increases. To explain the increasing excess nebular attenuation, we require a progressively larger fraction of star formation to occur in highly-obscured regions with increasing SFR. This highly-obscured star formation could occur in dusty clumps or central starbursts. Additionally, as each galaxy group represents a different evolutionary stage, we study their locations on the UVJ and SFR-mass diagrams. As mass increases, metallicity and dust attenuation increase, while sSFR decreases. However, the most massive group moves towards the quiescent region of the UVJ diagram, while showing less obscuration, potentially indicating removal of dust., Comment: 21 pages, 7 figures, accepted for publication in ApJ

Lattice gauge theories (LGTs) can be employed to understand a wide range of phenomena, from elementary particle scattering in high-energy physics to effective descriptions of many-body interactions in materials. Studying dynamical properties of emergent phases can be challenging as it requires solving many-body problems that are generally beyond perturbative limits. We investigate the dynamics of local excitations in a $\mathbb{Z}_2$ LGT using a two-dimensional lattice of superconducting qubits. We first construct a simple variational circuit which prepares low-energy states that have a large overlap with the ground state; then we create particles with local gates and simulate their quantum dynamics via a discretized time evolution. As the effective magnetic field is increased, our measurements show signatures of transitioning from deconfined to confined dynamics. For confined excitations, the magnetic field induces a tension in the string connecting them. Our method allows us to experimentally image string dynamics in a (2+1)D LGT from which we uncover two distinct regimes inside the confining phase: for weak confinement the string fluctuates strongly in the transverse direction, while for strong confinement transverse fluctuations are effectively frozen. In addition, we demonstrate a resonance condition at which dynamical string breaking is facilitated. Our LGT implementation on a quantum processor presents a novel set of techniques for investigating emergent particle and string dynamics.

Chalcogenide optical phase change materials (PCMs) have garnered significant interest for their growing applications in programmable photonics, optical analog computing, active metasurfaces, and beyond. Limited endurance or cycling lifetime is however increasingly becoming a bottleneck toward their practical deployment for these applications. To address this issue, we performed a systematic study elucidating the cycling failure mechanisms of Ge$_2$Sb$_2$Se$_4$Te (GSST), a common optical PCM tailored for infrared photonic applications, in an electrothermal switching configuration commensurate with their applications in on-chip photonic devices. We further propose a set of design rules building on insights into the failure mechanisms, and successfully implemented them to boost the endurance of the GSST device to over 67,000 cycles.

This study evaluates the productivity improvements achieved using a generative artificial intelligence personal assistant tool (PAT) developed by Trane Technologies. The PAT, based on OpenAI's GPT 3.5 model, was deployed on Microsoft Azure to ensure secure access and protection of intellectual property. To assess the tool's productivity effectiveness, an experiment was conducted comparing the completion times and content quality of four common office tasks: writing an email, summarizing an article, creating instructions for a simple task, and preparing a presentation outline. Sixty-three (63) participants were randomly divided into a test group using the PAT and a control group performing the tasks manually. Results indicated significant productivity enhancements, particularly for tasks involving summarization and instruction creation, with improvements ranging from 3.3% to 69%. The study further analyzed factors such as the age of users, response word counts, and quality of responses, revealing that the PAT users generated more verbose and higher-quality content. An 'LLM-as-a-judge' method employing GPT-4 was used to grade the quality of responses, which effectively distinguished between high and low-quality outputs. The findings underscore the potential of PATs in enhancing workplace productivity and highlight areas for further research and optimization., Comment: 18 pages, 9 figures

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

Data science and artificial intelligence are playing an increasingly important role in the physical sciences. Unfortunately, in the field of energetic materials data scarcity limits the accuracy and even applicability of ML tools. To address data limitations, we compiled multi-modal data: both experimental and computational results for several properties. We find that multi-task neural networks can learn from multi-modal data and outperform single-task models trained for specific properties. As expected, the improvement is more significant for data-scarce properties. These models are trained using descriptors built from simple molecular information and can be readily applied for large-scale materials screening to explore multiple properties simultaneously. This approach is widely applicable to fields outside energetic materials., Comment: 16 pages, 4 figures, 2 tables

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.

Letters of recommendation from school counselors are required to apply to many selective colleges and universities. Still, relatively little is known about how this non-standardized component may affect equity in admissions. We use cutting-edge natural language processing techniques to algorithmically analyze a national dataset of over 600,000 student applications and counselor recommendation letters submitted via the Common App platform. We examine how the length and topical content of letters (e.g., sentences about Personal Qualities, Athletics, Intellectual Promise, etc.) relate to student self-identified race/ethnicity, sex, and proxies for socioeconomic status. Paired with regression analyses, we explore whether demographic differences in letter characteristics persist when accounting for additional student, school, and counselor characteristics, as well as among letters written by the same counselor and among students with comparably competitive standardized test scores. We ultimately find large and noteworthy naïve differences in letter length and content across nearly all demographic groups, many in alignment with known inequities (e.g., many more sentences about Athletics among White and higher-SES students, longer letters and more sentences on Personal Qualities for private school students). However, these differences vary drastically based on the exact controls and comparison groups included -- demonstrating that the ultimate implications of these letter differences for equity hinges on exactly how and when letters are used in admissions processes (e.g., among which groups of students are they used to "break ties"?). Findings do not point to a clear recommendation whether institutions should keep or discard letter requirements, but reflect the importance of reading letters and overall applications in the context of structural opportunity. We discuss additional implications and possible recommendations for college access and admissions policy/practice.

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.

Las Americas Middle School is a newcomer program within Houston Independent School District (HISD) that serves students in Grades 4 through 8 who have been in the U.S. for less than one year. As a non-zoned school of choice, Las Americas has no attendance boundary, meaning that students and families must opt to enroll in the school. This brief analyzes how the trajectories of English acquisition vary among Las Americas newcomer students across different subgroups (economic disadvantage, initial English oral proficiency level, grade level upon arrival in HISD, classification as a student with interrupted formal education (SIFE) and refugee/asylee status). It also estimates the causal effects of attending Las Americas on students' English language acquisition.

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.

Let $(\mathfrak{M},\rho,\mu)$ be a metric space of homogeneous type, $p_0\in (1,\infty)$, and $T(t):L^{p_0}(\mathfrak{M},\mu)\rightarrow L^{p_0}(\mathfrak{M},\mu)$, $t\geq 0$, a strongly continuous semi-group. We provide sufficient conditions under which $T(t)$ is given by integration against an integral kernel satisfying higher-order Gaussian bounds of the form \[ \left| K_t(x,y) \right| \leq C \exp\left( -c \left( \frac{\rho(x,y)^{2\kappa}}{t} \right)^{\frac{1}{2\kappa-1}} \right) \mu\left( B(x,\rho(x,y)+t^{1/2\kappa}) \right)^{-1}. \] We also provide conditions for similar bounds on ``derivatives'' of $K_t(x,y)$ and our results are localizable. If $A$ is the generator of $T(t)$ the main hypothesis is that $\partial_t -A$ and $\partial_t-A^{*}$ satisfy a hypoelliptic estimate at every scale, uniformly in the scale. We present applications to subelliptic PDEs., Comment: 26 pages

We prove that there is a normed barrelled space with dimension $\mathrm{non}(\mathcal M)$, which denotes the smallest cardinality of a non-meager subset of $\mathbb R$. Consequently, it is consistent with $\mathsf{ZFC}$ that there is a normed barrelled space with dimension $<\!\mathfrak{c}$. This answers a question of S\'anchez Ruiz and Saxon. This is a special case of a more general theorem: for every infinite cardinal $\kappa$, every Banach space with density character $\kappa$ contains a barrelled subspace with dimension $\mathrm{cf}[\kappa]^\omega \cdot \mathrm{non}(\mathcal M)$. We also prove that if the dual of a Banach space does not contain $c_0$ or $\ell^p$ for any $p \geq 1$, then that spaces does not have a barrelled subspaces with dimension $<\!\mathrm{cov}(\mathcal N)$, which denotes the smallest cardinality of a collection of Lebesgue null sets covering $\mathbb R$. In particular, it is consistent with $\mathsf{ZFC}$ that no classical Banach spaces contain barrelled subspaces with dimension $\mathfrak{b}$. This partly answers another question of S\'anchez Ruiz and Saxon.

Panoramic image stitching provides a unified, wide-angle view of a scene that extends beyond the camera's field of view. Stitching frames of a panning video into a panoramic photograph is a well-understood problem for stationary scenes, but when objects are moving, a still panorama cannot capture the scene. We present a method for synthesizing a panoramic video from a casually-captured panning video, as if the original video were captured with a wide-angle camera. We pose panorama synthesis as a space-time outpainting problem, where we aim to create a full panoramic video of the same length as the input video. Consistent completion of the space-time volume requires a powerful, realistic prior over video content and motion, for which we adapt generative video models. Existing generative models do not, however, immediately extend to panorama completion, as we show. We instead apply video generation as a component of our panorama synthesis system, and demonstrate how to exploit the strengths of the models while minimizing their limitations. Our system can create video panoramas for a range of in-the-wild scenes including people, vehicles, and flowing water, as well as stationary background features., Comment: Project page at https://vidpanos.github.io/. To appear at SIGGRAPH Asia 2024 (conference track)

Ultrawide bandgap (UWBG) semiconductors are promising for next-generation power electronics, largely attributed to their substantial bandgap and exceptional breakdown electric field. Rutile GeO2 (r-GeO2) emerges as a promising alternative, particularly because of its ambipolar dopability. However, research on r-GeO2 is still in its infancy, and further investigation into its structural properties is essential for enhancing epilayer quality. In our previous work, we identified distinct surface morphologies; square-patterned and smooth regions of epitaxial r-GeO2 films grown on r-TiO2 (001) substrates using metal-organic chemical vapor deposition (MOCVD).This research employs transmission electron microscopy (TEM) to investigate the structural characteristics of the material. The findings indicate that the square-patterned regions are crystalline, whereas the smooth regions exhibit amorphous properties. The measured lattice spacing in the (110) plane is 0.324 nm, slightly exceeding the theoretical value of 0.312 nm. This discrepancy suggests the presence of tensile strain in the r-GeO2 film, resulting from lattice mismatch or thermal expansion differences with the substrate. We also observed a threading dislocation density of 1.83*10^9 cm-2, consisting of 11.76% screw-type, 29.41% edge-type, 55.89% mixed-type dislocations, and 2.94% planar defects. These findings offer valuable insights into the growth mechanisms and defect characteristics of r-GeO2., Comment: 19 pages, 5 figures

Supernova blasts envelop many surrounding stellar systems, transferring kinetic energy to small bodies in the systems. Geologic evidence from $^{60}\rm Fe$ points to recent nearby supernova activity within the past several Myr. Here, we model the transfer of energy and resulting orbital changes from these supernova blasts to the Oort Cloud, the Kuiper belt, and Saturn's Phoebe ring. For the Oort Cloud, an impulse approximation shows that a 50 pc supernova can eject approximately half of all objects less than 1 cm while altering the trajectories of larger ones, depending on their orbital parameters. For stars closest to supernovae, objects up to $\sim$100 m can be ejected. Turning to the explored solar system, we find that supernovae closer than 50 pc may affect Saturn's Phoebe ring and can sweep away Kuiper belt dust. It is also possible that the passage of the solar system through a dense interstellar cloud could have a similar effect; a numerical trajectory simulation shows that the location of the dust grains and the direction of the wind (from a supernova or interstellar cloud) has a significant impact on whether or not the grains will become unbound from their orbit in the Kuiper belt. Overall, nearby supernovae sweep micron-sized dust from the solar system, though whether the grains are ultimately cast towards the Sun or altogether ejected depends on various factors. Evidence of supernova-modified dust grain trajectories may be observed by New Horizons, though further modeling efforts are required., Comment: 7 pages, 4 figures. Published in Astrophysical Journal Letters (ApJL)

Fingerprints, otherwise known as dermatoglyphs, are most commonly thought of in the context of identification, but have myriad other roles in human biology. They are formed by the restricted ability of ridges and furrows of the epidermis to flatten. The patterns these ridges and furrows make can be represented as 2D fingerprints, but also as 3D structures with cross-sectional shapes that may add new levels of detail to identification, forensic, and behavioral uses/studies. Surface metrology techniques better allow for the quantification of these features, though it is unclear what tool and what scale is most appropriate. A Sensofar S Neox white light reflectance confocal microscope and a Gelsight Mobile 2 were used to independently measure the surface roughness of the fingerprints of four individuals from preserved cadaveric remains. Scale-sensitive fractal analyses (SSFA) were performed on the data from the S Neox (a small area), Gelsight (a larger area), and the same Gelsight datasets cropped down to the size of the S Neox scan size. Though fewer SSFA parameters identified differences between individuals from the smaller, extracted Gelsight area, all three forms of measurement found significant differences between some individuals from the study. No significant differences were found that differ between fingers themselves. Though only an initial step, these data suggest that a variety of surface metrology techniques may be useful in differentiating individuals., Comment: 20 pages, 5 figures

We establish a lower bound on the ADM mass of the time slices of $(n + 1)$-dimensional asymptotically flat standard static spacetimes under the timelike convergence condition. This extends the Minkowski inequality for static vacuum spacetimes, which relates the total mass of a time slice to the area and total mean curvature of its boundary. As a corollary, we obtain the Riemannian Penrose inequality in all dimensions and with rigidity for static manifolds under the TCC., Comment: 15 pages, no figures, comments welcome!

A $d$-subgroup of a lattice-ordered group ($\ell$-group) $G$ is a subgroup that contains the principal polars generated by each of its elements. We call $G$ a Martinez $\ell$-group if every convex $\ell$-subgroup of $G$ is a $d$-subgroup (equivalently: $G(a)=a^{\perp \perp}$ for every $a \in G$); known examples include all hyperarchimedean $\ell$-groups and all existentially closed abelian $\ell$-groups. This paper gives new characterizations of the Martinez $\ell$-groups, shows that the abelian Martinez $\ell$-groups form a radical class, investigates a related type of archimedean $\ell$-group called a Yosida $\ell$-group, and uses an analogue of a construction from ring theory, and other methods, to produce new examples of Martinez $\ell$-groups with special properties.

The first FASER search for a light, long-lived particle decaying into a pair of photons is reported. The search uses LHC proton-proton collision data at $\sqrt{s}=13.6~\text{TeV}$ collected in 2022 and 2023, corresponding to an integrated luminosity of $57.7\text{fb}^{-1}$. A model with axion-like particles (ALPs) dominantly coupled to weak gauge bosons is the primary target. Signal events are characterised by high-energy deposits in the electromagnetic calorimeter and no signal in the veto scintillators. One event is observed, compared to a background expectation of $0.44 \pm 0.39$ events, which is entirely dominated by neutrino interactions. World-leading constraints on ALPs are obtained for masses up to $300~\text{MeV}$ and couplings to the Standard Model W gauge boson, $g_{aWW}$, around $10^{-4}$ GeV$^{-1}$, testing a previously unexplored region of parameter space. Other new particle models that lead to the same experimental signature, including ALPs coupled to gluons or photons, U(1)$_B$ gauge bosons, up-philic scalars, and a Type-I two-Higgs doublet model, are also considered for interpretation, and new constraints on previously viable parameter space are presented in this paper., Comment: 37 pages, 22 figures

The inherent sensitivity of quantum sensors to their physical environment can make them good reporters of parameters such as temperature, pressure, strain, and electric fields. Here, we present a molecular platform for pressure (P) and temperature (T) sensing using para-terphenyl crystals doped with pentacene. We leverage the optically detected magnetic resonance (ODMR) of the photoexcited triplet electron in the pentacene molecule, that serves as a sensitive probe for lattice changes in the host para-terphenyl due to pressure or temperature variations. We observe maximal ODMR frequency variations of df/dP=1.8 MHz/bar and df/dT=247 kHz/K, which are over 1,200 times and three times greater, respectively, than those seen in nitrogen-vacancy centers in diamond. This results in a >85-fold improvement in pressure sensitivity over best previously reported. The larger variation reflects the weaker nature of the para-terphenyl lattice, with first-principles DFT calculations indicating that even picometer-level shifts in the molecular orbitals due to P, T changes are measurable. The platform offers additional advantages including high levels of sensor doping, narrow ODMR linewidths and high contrasts, and ease of deployment, leveraging the ability for large single crystals at low cost. Overall, this work paves the way for low-cost, optically-interrogated pressure and temperature sensors and lays the foundation for even more versatile sensors enabled by synthetic tunability in designer molecular systems., Comment: 7 pages, 4 figures, 1 table

The electrical response of ferroelectric domain walls is often influenced by their geometry underneath the sample surface. Tomographic imaging in these material systems has therefore become increasingly important for its ability to correlate the surface-level functional response with subsurface domain microstructure. In this context, AFM-based tomography emerges as a compelling choice because of its simplicity, high resolution and robust contrast mechanism. However, to date, the technique has been implemented in a limited number of ferroelectric materials, typically to depths of a few hundred nanometers or on relatively soft materials, resulting in an unclear understanding of its capabilities and limitations. In this work, AFM tomography is carried out in YbMnO3, mapping its complex domain microstructure up to a depth of around 1.8 um along with its current pathways. A model is presented, describing the impact of interconnected domain walls within the network, which act as current dividers and codetermine how currents distribute. Finally, challenges such as tip-blunting and subsurface amorphisation are identified through TEM studies, and strategies to address them are also put forward. This study highlights the potential of AFM tomography and could spur interest within the ferroics community for its use in the investigation of similar material systems.

Kenya, known for its linguistic diversity, faces unique challenges and promising opportunities in advancing Natural Language Processing (NLP) technologies, particularly for its underrepresented indigenous languages. This survey provides a detailed assessment of the current state of NLP in Kenya, emphasizing ongoing efforts in dataset creation, machine translation, sentiment analysis, and speech recognition for local dialects such as Kiswahili, Dholuo, Kikuyu, and Luhya. Despite these advancements, the development of NLP in Kenya remains constrained by limited resources and tools, resulting in the underrepresentation of most indigenous languages in digital spaces. This paper uncovers significant gaps by critically evaluating the available datasets and existing NLP models, most notably the need for large-scale language models and the insufficient digital representation of Indigenous languages. We also analyze key NLP applications: machine translation, information retrieval, and sentiment analysis-examining how they are tailored to address local linguistic needs. Furthermore, the paper explores the governance, policies, and regulations shaping the future of AI and NLP in Kenya and proposes a strategic roadmap to guide future research and development efforts. Our goal is to provide a foundation for accelerating the growth of NLP technologies that meet Kenya's diverse linguistic demands., Comment: 21 pages

Computed Tomography (CT) reconstruction of objects with cylindrical symmetry can be performed with a single projection. When the measured rays are parallel, and the axis of symmetry is perpendicular to the optical axis, the data can be modeled with the so-called Abel Transform. The Abel Transform has been extensively studied and many methods exist for accurate reconstruction. However, most CT geometries are cone-beam rather than parallel-beam. Using Abel methods for reconstruction in these cases can lead to distortions and reconstruction artifacts. Here, we develop analytic and model-based iterative reconstruction (MBIR) methods to reconstruct symmetric objects with an arbitrary axis of symmetry from a cone-beam geometry. The MBIR methods demonstrate superior results relative to the analytic inversion methods by mitigating artifacts and reducing noise while retaining fine image features. We demonstrate the efficacy of our methods using simulated and experimentally-acquired x-ray and neutron projections.

Simulations of the cosmic-ray (CR) anisotropy down to TeV energies are presented, using turbulence parameters consistent with those inferred from observations of the interstellar medium. We compute the angular power spectra $C_{\ell}$ of the CR anisotropy obtained from the simulations. We demonstrate that the amplitude of the large scale gradient in the CR density profile affects only the overall normalisation of the $C_{\ell}$s, without affecting the shape of the angular power spectrum. We show that the power spectrum depends on CR energy, and that it is sensitive to the location of the observer at small $\ell$. It is found to flatten at large $\ell$, and can be modelled by a broken power-law, exhibiting a break at $\ell \approx 4$. Our computed power spectrum at $\sim 10\,$TeV fits well HAWC and IceCube measurements. Moreover, we calculate all coefficients of the spherical harmonics and compute the component of the angular power spectrum projected onto the direction of the local magnetic field line. We find that deviations from gyrotropy become increasingly important at higher CR energies and larger values of $\ell$., Comment: 14 pages, 11 figures

The Central Molecular Zone (CMZ) of the Milky Way is fed by gas inflows from the Galactic disk along almost radial trajectories aligned with the major axis of the Galactic bar. However, despite being fundamental to all processes in the nucleus of the galaxy, these inflows have been studied significantly less than the CMZ itself. We present observations of various molecular lines between 215 and 230 GHz for 20 clouds with $|\ell| < 10^\circ$, which are candidates for clouds in the Galactic bar due to their warm temperatures and broad lines relative to typical Galactic disk clouds, using the Atacama Large Millimeter/submillimeter Array (ALMA) Atacama Compact Array (ACA). We measure gas temperatures, shocks, star formation rates, turbulent Mach numbers, and masses for these clouds. Although some clouds may be in the Galactic disk despite their atypical properties, nine clouds are likely associated with regions in the Galactic bar, and in these clouds, turbulent pressure is suppressing star formation. In clouds with no detected star formation, turbulence is the dominant heating mechanism, whereas photo-electric processes heat the star-forming clouds. We find that the ammonia (NH3) and formaldehyde (H2CO) temperatures probe different gas components, and in general each transition appears to trace different molecular gas phases within the clouds. We also measure the CO-to-H2 X-factor in the bar to be an order of magnitude lower than the typical Galactic value. These observations provide evidence that molecular clouds achieve CMZ-like properties before reaching the CMZ, Comment: 43 pages, 22 figures. Accepted to ApJ

Lubricated contacts in soft materials are important in various engineering systems and natural settings. Three major lubrication regimes are boundary (BL), mixed (ML), and elasto-hydrodynamic (EHL) lubrication, where the contact region is dry, partially wetted, or fully wetted, respectively. The transition between these regimes is insufficiently understood, especially for soft contacts, which impedes desired control of lubricated sliding friction. Here, we report on the role of solid wettability and adhesion on these transitions. Wettability of glycerol on polydimethylsiloxane (PDMS) surface, and adhesion between a glass indenter and PDMS, were varied by exposure of the PDMS to an ultraviolet light-ozone (UV-Ozone) cleaner. By combining friction tests and visualization, we demonstrate that the transition from ML to BL regime is dominated by the wettability of the lubricant; increasing wettability of glycerol makes removal of liquid from the contact region more difficult. Transition from EHL to ML is related to a series of events with increasing normal load, which are thinning of the lubricant layer, sudden jump to contact between the glass indenter and solid substrate across a gap of tens to a few hundreds of nanometers, and attendant elastic instabilities such as wrinkling and stick-slip. These results provide a deeper understanding of transitions in lubricated frictional behavior of soft materials which govern the maximum and minimum friction achievable.

Starshade is one of the technologies that will enable the observation and characterization of small planets around nearby stars through direct imaging. The Starshade Exoplanetary Data Challenge (SEDC) was designed to validate starshade-imaging's noise budget and evaluate the capabilities of image-processing techniques, by inviting community participating teams to analyze >1000 simulated images of hypothetical exoplanetary systems observed through a starshade. Because the starshade would suppress the starlight so well, the dominant noise source and the main challenge for the planet detection becomes the exozodiacal disks and their structures. In this paper, we summarize the techniques used by the participating teams and compare their findings with the truth. With an independent component analysis to remove the background, about 70% of the inner planets (close to the inner working angle) have been detected and ~40% of the outer planet (fainter than the inner counterparts) have been identified. Planet detection becomes more difficult in the cases of higher disk inclination, as the false negative and false positive counts increase. Interestingly, we found little difference in the planet detection ability between 1e-10 and 1e-9 instrument contrast, confirming that the dominant limitations are from the astrophysical background and not due to the performance of the starshade. Finally, we find that a non-parametric background calibration scheme, such as the independent component analysis reported here, results in a mean residual of 10% the background brightness. This background estimation error leads to substantial false positives and negatives and systematic bias in the planet flux estimation, and should be included in the estimation of the planet detection signal-to-noise ratio for imaging using a starshade and also a coronagraph that delivers exozodi-limited imaging., Comment: Accepted for publication in Journal of Astronomical Telescopes, Instruments, and Systems

We propose a resource-constrained heuristic for instances of Max-SAT that iteratively decomposes a larger problem into smaller subcomponents that can be solved by optimized solvers and hardware. The unconstrained outer loop maintains the state space of a given problem and selects a subset of the SAT variables for optimization independent of previous calls. The resource-constrained inner loop maximizes the number of satisfiable clauses in the "sub-SAT" problem. Our outer loop is agnostic to the mechanisms of the inner loop, allowing for the use of traditional solvers for the optimization step. However, we can also transform the selected "sub-SAT" problem into a quadratic unconstrained binary optimization (QUBO) one and use specialized hardware for optimization. In contrast to existing solutions that convert a SAT instance into a QUBO one before decomposition, we choose a subset of the SAT variables before QUBO optimization. We analyze a set of variable selection methods, including a novel graph-based method that exploits the structure of a given SAT instance. The number of QUBO variables needed to encode a (sub-)SAT problem varies, so we additionally learn a model that predicts the size of sub-SAT problems that will fit a fixed-size QUBO solver. We empirically demonstrate our results on a set of randomly generated Max-SAT instances as well as real world examples from the Max-SAT evaluation benchmarks and outperform existing QUBO decomposer solutions.

Dust from core-collapse supernovae (CCSNe), specifically Type IIP SNe, has been suggested to be a significant source of the dust observed in high-redshift galaxies. CCSNe eject large amounts of newly formed heavy elements, which can condense into dust grains in the cooling ejecta. However, infrared (IR) observations of typical CCSNe generally measure dust masses that are too small to account for the dust production needed at high redshifts. Type IIn SNe, classified by their dense circumstellar medium (CSM), are also known to exhibit strong IR emission from warm dust, but the dust origin and heating mechanism have generally remained unconstrained because of limited observational capabilities in the mid-IR. Here, we present a JWST/MIRI Medium Resolution Spectrograph (MRS) spectrum of the Type IIn SN 2005ip nearly 17 years post-explosion. The Type IIn SN 2005ip is one of the longest-lasting and most well-studied SNe observed to date. Combined with a Spitzer mid-IR spectrum of SN 2005ip obtained in 2008, this data set provides a rare 15-year baseline, allowing for a unique investigation of the evolution of dust. The JWST spectrum shows a new high-mass dust component ($\gtrsim0.08$ M$_{\odot}$) that is not present in the earlier Spitzer spectrum. Our analysis shows dust likely formed over the past 15 years in the cold, dense shell (CDS), between the forward and reverse shocks. There is also a smaller mass of carbonaceous dust ($\gtrsim0.005$ M$_{\odot}$) in the ejecta. These observations provide new insights into the role of SN dust production, particularly within the CDS, and its potential contribution to the rapid dust enrichment of the early Universe.

A trivial automorphism of the Boolean algebra $\mathcal P(\mathbb N) / \mathrm{Fin}$ is an automorphism induced by the action of some function $\mathbb N \rightarrow \mathbb N$. In models of forcing axioms all automorphisms are trivial, and therefore two trivial automorphisms are conjugate if and only if they have the same (modulo finite) cycle structure. We show that the Continuum Hypothesis implies that two trivial automorphisms are conjugate if and only if there are neither first-order obstructions nor index obstructions for their conjugacy. This is equivalent to given trivial automorphisms being conugate in some forcing extension of the universe. To each automorphism $\alpha$ of $\mathcal P(\mathbb N) / \mathrm{Fin}$ we associate the first-order structure $\mathfrak{A}_\alpha=(\mathcal P(\mathbb N) / \mathrm{Fin},\alpha)$ and compute the existential theories of these structures. These results are applied to resolve a question of Braga, Farah, and Vignati and prove that there are coarse metric spaces $X$ and $Y$ such that the isomorphism between their uniform Roe coronas is independent from $\mathsf{ZFC}$., Comment: Minor touches. 33 pages

Rapid search and rescue is critical to maximizing survival rates following natural disasters. However, these efforts are challenged by the need to search large disaster zones, lack of reliability in the communications infrastructure, and a priori unknown numbers of objects of interest (OOIs), such as injured survivors. Aerial robots are increasingly being deployed for search and rescue due to their high mobility, but there remains a gap in deploying multi-robot autonomous aerial systems for methodical search of large environments. Prior works have relied on preprogrammed paths from human operators or are evaluated only in simulation. We bridge these gaps in the state of the art by developing and demonstrating a decentralized active search system, which biases its trajectories to take additional views of uncertain OOIs. The methodology leverages stochasticity for rapid coverage in communication denied scenarios. When communications are available, robots share poses, goals, and OOI information to accelerate the rate of search. Extensive simulations and hardware experiments in Bloomingdale, OH, are conducted to validate the approach. The results demonstrate the active search approach outperforms greedy coverage-based planning in communication-denied scenarios while maintaining comparable performance in communication-enabled scenarios.

We present multi-epoch optical spectropolarimetric and imaging polarimetric observations of the nearby Type II supernova (SN) 2023ixf discovered in M101 at a distance of 6.85 Mpc. The first imaging polarimetric observations were taken +2.33 days (60085.08 MJD) after the explosion, while the last imaging polarimetric data points (+73.19 and +76.19 days) were acquired after the fall from the light curve plateau. At +2.33 days there is strong evidence of circumstellar material (CSM) interaction in the spectra and the light curve. A significant level of polarization $P_r = 0.88\pm 0.06 \% $ seen during this phase indicates that this CSM is aspherical. We find that the polarization evolves with time toward the interstellar polarization level ($0.35\%$) during the photospheric phase, which suggests that the recombination photosphere is spherically symmetric. There is a jump in polarization ($P_r =0.65 \pm 0.08 \% $) at +73.19 days when the light curve falls from the plateau. This is a phase where polarimetric data is sensitive to non-spherical inner ejecta or a decrease in optical depth into the single scattering regime. We also present spectropolarimetric data that reveal line (de)polarization during most of the observed epochs. In addition, at +14.50 days we see an "inverse P Cygn" profile in the H and He line polarization, which clearly indicates the presence of asymmetrically distributed material overlying the photosphere. The overall temporal evolution of polarization is typical for Type II SNe, but the high level of polarization during the rising phase has only been observed in SN 2023ixf., Comment: 14 pages, 7 figures, submitted to ApJL, comments welcome

Given a supermanifold equipped with an odd distribution of maximal dimension and constant symbol, we construct the formal moduli problem of deformations of the distribution. This moduli problem is described by a local super dg Lie algebra that provides both a resolution of the structure-preserving vector fields on superspace and a derived enhancement of superconformal symmetry. Applying our construction in standard physical examples returns the conformal supergravity multiplet in every known example, in any dimension and with any amount of supersymmetry$\unicode{x2014}$whether or not a superconformal algebra exists. We discuss new examples related to twisted supergravity, higher Virasoro algebras, and exceptional super Lie algebras. The compatibility of our techniques with twisting also leads to a computation of every twist of the stress tensor multiplet of a superconformal theory, including universal operator product expansions. Our approach uses a derived model for the space of functions constant along the distribution, which is applicable even when the distribution is non-involutive; we construct other natural multiplets, such as K\"ahler differentials, that appear naturally through this lens on superspace geometry., Comment: 68 pages, 7 tables. Comments welcome! v2: updated funding information

For a locally finite, connected graph $\Gamma$, let $\operatorname{Map}(\Gamma)$ denote the group of proper homotopy equivalences of $\Gamma$ up to proper homotopy. Excluding sporadic cases, we show $\operatorname{Aut}(S(M_\Gamma)) \cong \operatorname{Map}(\Gamma)$, where $\mathcal{S}(M_\Gamma)$ is the sphere complex of the doubled handlebody $M_\Gamma$ associated to $\Gamma$. We also construct an exhaustion of $S(M_\Gamma)$ by finite strongly rigid sets when $\Gamma$ has finite rank and finitely many rays, and an appropriate generalization otherwise., Comment: 34 pages, 16 figures. Comments welcome