80,048 results on '"Harrison, P. A."'
Search Results
2. Influences on the Recruitment, Retention, and Advancement of the Child Care and Early Education Workforce. A Conceptual Framework. BASE Knowledge Review Series. OPRE Report 2023-191
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Administration for Children and Families (DHHS), Office of Planning, Research and Evaluation (OPRE), MDRC, MEF Associates, Chapin Hall at the University of Chicago, JoAnn Hsueh, Harrison Taylor, Michelle Maier, and Sydney Roach
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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.
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- 2024
3. Inclusive Approaches for Measuring Demographics of Underrepresented Populations in STEM and Biomedical Research Training Programs
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Stephanie E. Paris, Alexis Dinno, Mollie C. Marr, Aaron Raz Link, Brandy L. Lentz, Angie Setthavongsack, Shanthia N. Espinosa, Gwen Shusterman, Jerian Abel, Kristen M. K. Harrison, James Hook, Teala W. Alvord, Dawn M. Richardson, Kieran Chase, and Lisa K. Marriott
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As federal strategic plans prioritize increasing diversity within the biomedical workforce, and STEM training and outreach programs seek to recruit and retain students from historically underrepresented populations, there is a need for interrogation of traditional demographic descriptors and careful consideration of best practices for obtaining demographic data. To accelerate this work, equity-focused researchers and leaders from STEM programs convened to examine approaches for measuring demographic variables. Gender, race/ethnicity, disability, and disadvantaged background were prioritized given their focus by federal funding agencies. Categories of sex minority, sexual (orientation) minority, and gender minority (SSGM) should be included in demographic measures collected by STEM programs, consistent with recommendations from White House Executive Orders and federal reports. Our manuscript offers operationalized phrasing for demographic questions and recommendations for use across student-serving programs. Inclusive demographics permit the identification of individuals who are being excluded, marginalized, or improperly aggregated, increasing capacity to address inequities in biomedical research training. As trainees do not enter training programs with equal access, accommodations, or preparation, inclusive demographic measures can welcome trainees and inform a nuanced set of program outcomes that facilitate research on intersectionality to support the recruitment and retention of underrepresented students in biomedical research.
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- 2024
4. Autocorrelation properties of temporal networks governed by dynamic node variables
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Hartle, Harrison and Masuda, Naoki
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Physics - Physics and Society - Abstract
We study synthetic temporal networks whose evolution is determined by stochastically evolving node variables - synthetic analogues of, e.g., temporal proximity networks of mobile agents. We quantify the long-timescale correlations of these evolving networks by an autocorrelative measure of edge persistence. Several distinct patterns of autocorrelation arise, including power-law decay and exponential decay, depending on the choice of node-variable dynamics and connection probability function. Our methods are also applicable in wider contexts; our temporal network models are tractable mathematically and in simulation, and our long-term memory quantification is analytically tractable and straightforwardly computable from temporal network data., Comment: 15 pages, 4 figures
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- 2024
5. KASHz+SUPER: Evidence of cold molecular gas depletion in AGN hosts at cosmic noon
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Bertola, E., Circosta, C., Ginolfi, M., Mainieri, V., Vignali, C., Rivera, G. Calistro, Ward, S. R., Lopez, I. E., Pensabene, A., Alexander, D. M., Bischetti, M., Brusa, M., Cappi, M., Comastri, A., Contursi, A., Cicone, C., Cresci, G., Dadina, M., D'Amato, Q., Feltre, A., Harrison, C. M., Kakkad, D., Lamperti, I., Lanzuisi, G., Mannucci, F., Marconi, A., Perna, M., Piconcelli, E., Puglisi, A., Ricci, F., Scholtz, J., Tozzi, G., Vietri, G., Zamorani, G., and Zappacosta, L.
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Astrophysics - Astrophysics of Galaxies - Abstract
The energy released by AGN has the potential to heat or remove the gas of the ISM, thus likely impacting the cold molecular gas reservoir of host galaxies at first, with star formation following on longer timescales. Previous works on high-z galaxies have yielded conflicting results, possibly due to selection biases and other systematics. To provide a reliable benchmark for galaxy evolution models at cosmic noon (z=1-3), two surveys were conceived: SUPER and KASHz, both targeting unbiased X-ray-selected AGN at z>1 that span a wide bolometric luminosity range. In this paper, we assess the effects of AGN feedback on the molecular gas content of host galaxies in a statistically robust, uniformly selected, coherently analyzed sample of AGN at z=1-2.6, drawn from the KASHz and SUPER surveys. By using ALMA data in combination with dedicated SED modeling, we retrieve CO and FIR luminosity as well as $M_*$ of SUPER and KASHz AGN. We selected non-active galaxies from PHIBBS, ASPECS and multiple ALMA/NOEMA surveys of sub-mm galaxies. By matching the samples in z, $M_*$ and $L_{FIR}$, we compared the properties of AGN and non-active galaxies within a Bayesian framework. We find that AGN hosts at given $L_{FIR}$ are on average CO depleted compared to non-active galaxies, confirming what was previously found in the SUPER survey. Moreover, the molecular gas fraction distributions of AGN and non-active galaxies are statistically different, with that of of AGN being skewed to lower values. Our results indicate that AGN can indeed reduce the total cold molecular gas reservoir of their host galaxies. Lastly, by comparing our results with predictions from three cosmological simulations (TNG, Eagle and Simba) filtered to match the observed properties, we confirm already known discrepancies and highlight new ones between observations and simulations.[Abridged], Comment: 26 pages (17 in the main body of the paper and 9 in the appendix), 14 figures (11 in the main body of the paper and 3 in the appendix), 8 tables (2 in the main body of the paper and 6 in the appendix). Accepted for publication in A&A, in press
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- 2024
6. Benchmarking with Supernovae: A Performance Study of the FLASH Code
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Martin, Joshua, Feldman, Catherine, Siegmann, Eva, Curtis, Tony, Carlson, David, Coskun, Firat, Wood, Daniel, Gonzalez, Raul, Harrison, Robert J., and Calder, Alan C.
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Computer Science - Distributed, Parallel, and Cluster Computing ,Astrophysics - Instrumentation and Methods for Astrophysics - Abstract
Astrophysical simulations are computation, memory, and thus energy intensive, thereby requiring new hardware advances for progress. Stony Brook University recently expanded its computing cluster "SeaWulf" with an addition of 94 new nodes featuring Intel Sapphire Rapids Xeon Max series CPUs. We present a performance and power efficiency study of this hardware performed with FLASH: a multi-scale, multi-physics, adaptive mesh-based software instrument. We extend this study to compare performance to that of Stony Brook's Ookami testbed which features ARM-based A64FX-700 processors, and SeaWulf's AMD EPYC Milan and Intel Skylake nodes. Our application is a stellar explosion known as a thermonuclear (Type Ia) supernova and for this 3D problem, FLASH includes operators for hydrodynamics, gravity, and nuclear burning, in addition to routines for the material equation of state. We perform a strong-scaling study with a 220 GB problem size to explore both single- and multi-node performance. Our study explores the performance of different MPI mappings and the distribution of processors across nodes. From these tests, we determined the optimal configuration to balance runtime and energy consumption for our application., Comment: Accepted to PEARC '24 (Practice and Experience in Advanced Research Computing)
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- 2024
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7. Quantifying & Mitigating Satellite Constellation Interference with SatHub
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Rawls, Meredith L., Walker, Constance E., Dadighat, Michelle, Krantz, Harrison, Eggl, Siegfried, and Peel, Mike
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Astrophysics - Instrumentation and Methods for Astrophysics ,Physics - Physics and Society ,Physics - Space Physics - Abstract
This Birds-of-a-Feather (BOF) session on 6 November 2023 was organized by leaders and members of SatHub at the International Astronomical Union Centre for the Protection of the Dark and Quiet Sky from Satellite Constellation Interference (IAU CPS). SatHub is dedicated to observations, data analysis, software, and related activities. The session opened with a talk on the current state of affairs with regards to satellite constellation mitigation, with a focus on optical astronomy, and moved to focused discussion around the top-voted topics. These included tools and techniques for forecasting satellite positions and brightnesses as well as streak detection and masking., Comment: 4 pages, 1 figure, conference proceeding from ADASS 2023
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- 2024
8. Mica: Automated Differential Testing for OCaml Modules
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Ng, Ernest, Goldstein, Harrison, and Pierce, Benjamin C.
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Computer Science - Programming Languages ,Computer Science - Software Engineering - Abstract
Suppose we are given two OCaml modules implementing the same signature. How do we check that they are observationally equivalent -- that is, that they behave the same on all inputs? One established technique is to use a property-based testing (PBT) tool such as QuickCheck. Currently, however, this can require significant amounts of boilerplate code and ad-hoc test harnesses. To address this issue, we present Mica, an automated tool for testing observational equivalence of OCaml modules. Mica is implemented as a PPX compiler extension, allowing users to supply minimal annotations to a module signature. These annotations guide Mica to automatically derive specialized PBT code that checks observational equivalence. We discuss the design of Mica and demonstrate its efficacy as a testing tool on various modules taken from real-world OCaml libraries., Comment: OCaml Workshop 2024
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- 2024
9. EFT Workshop at Notre Dame
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Smith, Nick, Spitzbart, Daniel, Dickinson, Jennet, Wilson, Jon, Gray, Lindsey, Mohrman, Kelci, Bhattacharya, Saptaparna, Piccinelli, Andrea, Roy, Titas, Paspalaki, Garyfallia, Fontes, Duarte, Martin, Adam, Shepherd, William, Cruz, Sergio Sánchez, Goncalves, Dorival, Gritsan, Andrei, Prosper, Harrison, Junk, Tom, Cranmer, Kyle, Peskin, Michael, Gilbert, Andrew, Langford, Jonathon, Petriello, Frank, Mantani, Luca, Wightman, Andrew, Knight, Charlotte, Shyamsundar, Prasanth, Basnet, Aashwin, Boldrini, Giacomo, and Lannon, Kevin
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High Energy Physics - Experiment - Abstract
The LPC EFT workshop was held April 25-26, 2024 at the University of Notre Dame. The workshop was organized into five thematic sessions: "how far beyond linear" discusses issues of truncation and validity in interpretation of results with an eye towards practicality; "reconstruction-level results" visits the question of how best to design analyses directly targeting inference of EFT parameters; "logistics of combining likelihoods" addresses the challenges of bringing a diverse array of measurements into a cohesive whole; "unfolded results" tackles the question of designing fiducial measurements for later use in EFT interpretations, and the benefits and limitations of unfolding; and "building a sample library" addresses how best to generate simulation samples for use in data analysis. This document serves as a summary of presentations, subsequent discussions, and actionable items identified over the course of the workshop.
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- 2024
10. A Comparison of Large Language Model and Human Performance on Random Number Generation Tasks
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Harrison, Rachel M.
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Computer Science - Artificial Intelligence ,Computer Science - Computation and Language ,Quantitative Biology - Neurons and Cognition - Abstract
Random Number Generation Tasks (RNGTs) are used in psychology for examining how humans generate sequences devoid of predictable patterns. By adapting an existing human RNGT for an LLM-compatible environment, this preliminary study tests whether ChatGPT-3.5, a large language model (LLM) trained on human-generated text, exhibits human-like cognitive biases when generating random number sequences. Initial findings indicate that ChatGPT-3.5 more effectively avoids repetitive and sequential patterns compared to humans, with notably lower repeat frequencies and adjacent number frequencies. Continued research into different models, parameters, and prompting methodologies will deepen our understanding of how LLMs can more closely mimic human random generation behaviors, while also broadening their applications in cognitive and behavioral science research.
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- 2024
11. Large Bandgap Observed on the Surfaces of EuZn2As2 Single Crystals
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Kong, Dejia, Karbasizadeh, Siavash, Narasimha, Ganesh, Regmi, Paras, Tao, Chenggang, Mu, Sai, Vasudevan, Rama, Harrison, Ian, Jin, Rongying, and Gai, Zheng
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Condensed Matter - Materials Science - Abstract
EuM2As2 (M = Zn, Cd, In, Sn etc.) is an excellent material system for studying topological properties, which can be easily tuned by magnetism involved. Theoretical calculations predict gapped and flat bands in EuZn2As2 but gapless structure in EuCd2As2. In this work, low-temperature (77 K) cleaved EuZn2As2 crystals are studied using scanning tunneling microscopy/spectroscopy (STM/S) and density functional theory (DFT) calculations. Defects-induced local density of states (LDOS) modification with a triangular shape helps identify the surface terminations: Eu versus AsZn surface. While large bandgaps (~1.5 eV at 77 K) are observed on both pristine surfaces, the bandgap width is found to be very sensitive to local heterogeneity, such as defects and step edges, with the tendency of reduction. Combining experimental data with DFT simulations, we conclude that the modified bandgap in the heterogeneous area arises from Zn vacancies and/or substitution by As atoms. Our investigation offers important information for reevaluating the electron topology of the EuM2As2 family., Comment: 17 pages, 4 figures
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- 2024
12. Anisotropic Diffusion Model of Communication in 2D Biofilm
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Paramalingam, Yanahan, Arjmandi, Hamidreza, Harrison, Freya, Schiller, Tara, and Noel, Adam
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Electrical Engineering and Systems Science - Signal Processing - Abstract
A biofilm is a microbial city. It consists of bacteria embedded in an extracellular polymeric substance (EPS) that functions as a protective barrier. Quorum sensing (QS) is a method of bacterial communication, where autoinducers (AIs) propagate via diffusion through the EPS and water channels within the biofilm. This diffusion process is anisotropic due to varying densities between the EPS and water channels. This study introduces a 2D anisotropic diffusion model for molecular communication (MC) within biofilms, analyzing information propagation between a point-to-point transmitter (TX) and receiver (RX) in bounded space. The channel impulse response is derived using Green's function for concentration (GFC) and is validated with particle-based simulation (PBS). The outcomes reveal similar results for both isotropic and anisotropic diffusion when the TX is centrally located due to symmetry. However, anisotropic conditions lead to greater diffusion peaks when the TX is positioned off-center. Additionally, the propagation of AIs is inversely proportional to both overall biofilm size and and diffusion coefficient values. It is hypothesized that anisotropic diffusion supports faster responses to hostile environmental changes because signals can propagate faster from the edge of the biofilm to the center.
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- 2024
13. Effect of Proton Irradiation in Thin-Film YBa$_2$Cu$_3$O$_{7-\delta}$ Superconductor
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Fogt, Joseph, Weeda, Hope, Harrison, Trevor, Miles, Nolan, and Cho, Kyuil
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Condensed Matter - Superconductivity - Abstract
We investigated the effect of 0.6 MeV proton irradiation on the superconducting and normal state properties of thin-film $\text{YBa}_{2}\text{Cu}_{3}\text{O}_{7-\delta}$ superconductors. A thin-film YBCO superconductor ($\approx$ 567 nm thick) was subject to a series of proton irradiations with a total fluence of $7.6\times10^{16}$ $\text{p/cm}^2$. Upon irradiation, $T_c$ was drastically decreased from 89.3 K towards zero with a corresponding increase in its normal state resistivity above $T_c$. This increase in resistivity which indicates the increase of defects inside the thin-film sample can be converted to the dimensionless scattering rate. We found that the relation between $T_c$ and dimensionless scattering rate obtained during proton irradiation approximates the generalized d-wave Abrikosov-Gor'kov theory better than the previous results obtained from electron irradiations. This is an unexpected result since the electron irradiation is known to be most effective to suppress superconductivity over other heavier ion irradiations such as proton irradiation. It suggests that the type of defects created by proton irradiation evolves from cascade defects (in bulk single crystals) to point-like defects (in thin-film single crystals) as the thickness decreases.
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- 2024
14. Setting the duration of online A/B experiments
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Li, Harrison H. and Yu, Chaoyu
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Statistics - Methodology ,Computer Science - Machine Learning - Abstract
In designing an online A/B experiment, it is crucial to select a sample size and duration that ensure the resulting confidence interval (CI) for the treatment effect is the right width to detect an effect of meaningful magnitude with sufficient statistical power without wasting resources. While the relationship between sample size and CI width is well understood, the effect of experiment duration on CI width remains less clear. This paper provides an analytical formula for the width of a CI based on a ratio treatment effect estimator as a function of both sample size (N) and duration (T). The formula is derived from a mixed effects model with two variance components. One component, referred to as the temporal variance, persists over time for experiments where the same users are kept in the same experiment arm across different days. The remaining error variance component, by contrast, decays to zero as T gets large. The formula we derive introduces a key parameter that we call the user-specific temporal correlation (UTC), which quantifies the relative sizes of the two variance components and can be estimated from historical experiments. Higher UTC indicates a slower decay in CI width over time. On the other hand, when the UTC is 0 -- as for experiments where users shuffle in and out of the experiment across days -- the CI width decays at the standard parametric 1/T rate. We also study how access to pre-period data for the users in the experiment affects the CI width decay. We show our formula closely explains CI widths on real A/B experiments at YouTube.
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- 2024
15. PKS~J0805$-$0111: A Second Owens Valley Radio Observatory Blazar Showing Highly Significant Sinusoidal Radio Variability -- The Tip of the Iceberg
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de la Parra, P. V., Kiehlmann, S., Mroz, P., Readhead, A. C. S., Synani, A., Begelman, M. C., Blandford, R. D., Ding, Y., Harrison, F., Liodakis, I., Max-Moerbeck, W., Pavlidou, V., Reeves, R., Vallisneri, M., Aller, M. F., Graham, M. J., Hovatta, T., Lawrence, C. R., Lazio, T. J. W., Mahabal, A. A., Molina, B., O'Neill, S., Pearson, T. J., Ravi, V., Tassis, K., and Zensus, J. A.
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Astrophysics - High Energy Astrophysical Phenomena ,Astrophysics - Astrophysics of Galaxies - Abstract
Owens Valley Radio Observatory (OVRO) observations of supermassive black hole binary (SMBHB) candidate PKS~2131$-$021 revealed, for the first time, six likely characteristics of the phenomenology exhibited by SMBHB in blazars, of which the most unexpected and critical is sinusoidal flux density variations. We have now identified a second blazar, PKS~J0805$-$0111, showing significant sinusoidal variations, with an observed period that translates to $1.422 \pm 0.005$ yr in the rest frame of the $z = 1.388$ object. We generate $10^6$ simulated light curves to reproduce the radio variability characteristics of PKS~J0805$-$0111, and show that the global probability, considering the \textit{look-elsewhere effect}, indicates that the observed periodicity can be attributed to the red noise tail of the power spectral density, with a $p_0$ value of $7.8 \times 10^{-5}$ (i.e. 3.78$\sigma$). PKS J0805$-$0111 displays all six characteristics observed in PKS 2131$-$021. Taking into account the well-defined OVRO sample size, the false positive probability $\sim 0.22$, but the rare behavior makes this a strong SMBHB candidate. The discovery of a second SMBHB candidate exhibiting these rare characteristics reveals that PKS~2131$-$021 is not a unique, isolated case. With these two strong cases we are clearly seeing only the tip of the iceberg. We estimate that the number of SMBHB candidates amongst blazars $\sim$ 1 in 100.
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- 2024
16. Enhancing weak lensing redshift distribution characterization by optimizing the Dark Energy Survey Self-Organizing Map Photo-z method
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Campos, A., Yin, B., Dodelson, S., Amon, A., Alarcon, A., Sánchez, C., Bernstein, G. M., Giannini, G., Myles, J., Samuroff, S., Alves, O., Andrade-Oliveira, F., Bechtol, K., Becker, M. R., Blazek, J., Camacho, H., Rosell, A. Carnero, Kind, M. Carrasco, Cawthon, R., Chang, C., Chen, R., Choi, A., Cordero, J., Davis, C., DeRose, J., Diehl, H. T., Doux, C., Drlica-Wagner, A., Eckert, K., Eifler, T. F., Elvin-Poole, J., Everett, S., Fang, X., Ferté, A., Friedrich, O., Gatti, M., Gruen, D., Gruendl, R. A., Harrison, I., Hartley, W. G., Herner, K., Huang, H., Huff, E. M., Jarvis, M., Krause, E., Kuropatkin, N., Leget, P. -F., MacCrann, N., McCullough, J., Navarro-Alsina, A., Pandey, S., Prat, J., Raveri, M., Rollins, R. P., Roodman, A., Rosenfeld, R., Ross, A. J., Rykoff, E. S., Sanchez, J., Secco, L. F., Sevilla-Noarbe, I., Sheldon, E., Shin, T., Troxel, M. A., Tutusaus, I., Varga, T. N., Wechsler, R. H., Yanny, B., Zhang, Y., Zuntz, J., Aguena, M., Annis, J., Bacon, D., Bocquet, S., Brooks, D., Burke, D. L., Carretero, J., Castander, F. J., Costanzi, M., da Costa, L. N., De Vicente, J., Doel, P., Ferrero, I., Flaugher, B., Frieman, J., García-Bellido, J., Gaztanaga, E., Gutierrez, G., Hinton, S. R., Hollowood, D. L., Honscheid, K., James, D. J., Kuehn, K., Lima, M., Lin, H., Marshall, J. L., Mena-Fernández, J., Menanteau, F., Miquel, R., Ogando, R. L. C., Paterno, M., Pereira, M. E. S., Pieres, A., Malagón, A. A. Plazas, Porredon, A., Sanchez, E., Cid, D. Sanchez, Smith, M., Suchyta, E., Swanson, M. E. C., Tarle, G., To, C., Vikram, V., and Weaverdyck, N.
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Astrophysics - Cosmology and Nongalactic Astrophysics ,Astrophysics - Instrumentation and Methods for Astrophysics - Abstract
Characterization of the redshift distribution of ensembles of galaxies is pivotal for large scale structure cosmological studies. In this work, we focus on improving the Self-Organizing Map (SOM) methodology for photometric redshift estimation (SOMPZ), specifically in anticipation of the Dark Energy Survey Year 6 (DES Y6) data. This data set, featuring deeper and fainter galaxies than DES Year 3 (DES Y3), demands adapted techniques to ensure accurate recovery of the underlying redshift distribution. We investigate three strategies for enhancing the existing SOM-based approach used in DES Y3: 1) Replacing the Y3 SOM algorithm with one tailored for redshift estimation challenges; 2) Incorporating $\textit{g}$-band flux information to refine redshift estimates (i.e. using $\textit{griz}$ fluxes as opposed to only $\textit{riz}$); 3) Augmenting redshift data for galaxies where available. These methods are applied to DES Y3 data, and results are compared to the Y3 fiducial ones. Our analysis indicates significant improvements with the first two strategies, notably reducing the overlap between redshift bins. By combining strategies 1 and 2, we have successfully managed to reduce redshift bin overlap in DES Y3 by up to 66$\%$. Conversely, the third strategy, involving the addition of redshift data for selected galaxies as an additional feature in the method, yields inferior results and is abandoned. Our findings contribute to the advancement of weak lensing redshift characterization and lay the groundwork for better redshift characterization in DES Year 6 and future stage IV surveys, like the Rubin Observatory.
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- 2024
17. A comparative study of radio signatures from winds and jets: Modelling synchrotron emission and polarization
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Meenakshi, Moun, Mukherjee, Dipanjan, Bodo, Gianluigi, Rossi, Paola, and Harrison, Chris M.
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Astrophysics - High Energy Astrophysical Phenomena - Abstract
Outflows driven by active galactic nuclei (AGN) are seen in numerous compact sources; however, it has remained unclear how to distinguish between the driving mechanisms, such as winds and jets. Therefore, our study aims to offer observational insights from simulations to aid in this distinction. Specifically, in this paper, we investigate the evolution of wide-angled, moderately relativistic, magnetized winds and analyze their non-thermal radio emission and polarization properties. We find that the evolution of winds varies depending on factors such as power, density, and opening angle, which in turn influence their observable characteristics. Additionally, different viewing angles can lead to varying observations. Furthermore, we note distinctions in the evolution of winds compared to jets, resulting in disparities in their observable features. Jets typically exhibit a thin spine and hotspot(s). Winds manifest broader spines or an "hourglass-shaped" bright emission in the cocoon, which are capped by bright arcs. Both display high polarization coinciding with the bright spine and hotspots/arcs, although these regions are relatively compact and localized in jets when compared to winds. We emphasize the importance of high resolution, as we demonstrate that emission features from both jets and winds can become indistinguishable at lower resolutions. The distribution of polarization is largely unaffected by resolution, though lower polarization becomes more noticeable when the resolution is decreased., Comment: Accepted for publication in MNRAS
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- 2024
18. The Llama 3 Herd of Models
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Dubey, Abhimanyu, Jauhri, Abhinav, Pandey, Abhinav, Kadian, Abhishek, Al-Dahle, Ahmad, Letman, Aiesha, Mathur, Akhil, Schelten, Alan, Yang, Amy, Fan, Angela, Goyal, Anirudh, Hartshorn, Anthony, Yang, Aobo, Mitra, Archi, Sravankumar, Archie, Korenev, Artem, Hinsvark, Arthur, Rao, Arun, Zhang, Aston, Rodriguez, Aurelien, Gregerson, Austen, Spataru, Ava, Roziere, Baptiste, Biron, Bethany, Tang, Binh, Chern, Bobbie, Caucheteux, Charlotte, Nayak, Chaya, Bi, Chloe, Marra, Chris, McConnell, Chris, Keller, Christian, Touret, Christophe, Wu, Chunyang, Wong, Corinne, Ferrer, Cristian Canton, Nikolaidis, Cyrus, Allonsius, Damien, Song, Daniel, Pintz, Danielle, Livshits, Danny, Esiobu, David, Choudhary, Dhruv, Mahajan, Dhruv, Garcia-Olano, Diego, Perino, Diego, Hupkes, Dieuwke, Lakomkin, Egor, AlBadawy, Ehab, Lobanova, Elina, Dinan, Emily, Smith, Eric Michael, Radenovic, Filip, Zhang, Frank, Synnaeve, Gabriel, Lee, Gabrielle, Anderson, Georgia Lewis, Nail, Graeme, Mialon, Gregoire, Pang, Guan, Cucurell, Guillem, Nguyen, Hailey, Korevaar, Hannah, Xu, Hu, Touvron, Hugo, Zarov, Iliyan, Ibarra, Imanol Arrieta, Kloumann, Isabel, Misra, Ishan, Evtimov, Ivan, Copet, Jade, Lee, Jaewon, Geffert, Jan, Vranes, Jana, Park, Jason, Mahadeokar, Jay, Shah, Jeet, van der Linde, Jelmer, Billock, Jennifer, Hong, Jenny, Lee, Jenya, Fu, Jeremy, Chi, Jianfeng, Huang, Jianyu, Liu, Jiawen, Wang, Jie, Yu, Jiecao, Bitton, Joanna, Spisak, Joe, Park, Jongsoo, Rocca, Joseph, Johnstun, Joshua, Saxe, Joshua, Jia, Junteng, Alwala, Kalyan Vasuden, Upasani, Kartikeya, Plawiak, Kate, Li, Ke, Heafield, Kenneth, Stone, Kevin, El-Arini, Khalid, Iyer, Krithika, Malik, Kshitiz, Chiu, Kuenley, Bhalla, Kunal, Rantala-Yeary, Lauren, van der Maaten, Laurens, Chen, Lawrence, Tan, Liang, Jenkins, Liz, Martin, Louis, Madaan, Lovish, Malo, Lubo, Blecher, Lukas, Landzaat, Lukas, de Oliveira, Luke, Muzzi, Madeline, Pasupuleti, Mahesh, Singh, Mannat, Paluri, Manohar, Kardas, Marcin, Oldham, Mathew, Rita, Mathieu, Pavlova, Maya, Kambadur, Melanie, Lewis, Mike, Si, Min, Singh, Mitesh Kumar, Hassan, Mona, Goyal, Naman, Torabi, Narjes, Bashlykov, Nikolay, Bogoychev, Nikolay, Chatterji, Niladri, Duchenne, Olivier, Çelebi, Onur, Alrassy, Patrick, Zhang, Pengchuan, Li, Pengwei, Vasic, Petar, Weng, Peter, Bhargava, Prajjwal, Dubal, Pratik, Krishnan, Praveen, Koura, Punit Singh, Xu, Puxin, He, Qing, Dong, Qingxiao, Srinivasan, Ragavan, Ganapathy, Raj, Calderer, Ramon, Cabral, Ricardo Silveira, Stojnic, Robert, Raileanu, Roberta, Girdhar, Rohit, Patel, Rohit, Sauvestre, Romain, Polidoro, Ronnie, Sumbaly, Roshan, Taylor, Ross, Silva, Ruan, Hou, Rui, Wang, Rui, Hosseini, Saghar, Chennabasappa, Sahana, Singh, Sanjay, Bell, Sean, Kim, Seohyun Sonia, Edunov, Sergey, Nie, Shaoliang, Narang, Sharan, Raparthy, Sharath, Shen, Sheng, Wan, Shengye, Bhosale, Shruti, Zhang, Shun, Vandenhende, Simon, Batra, Soumya, Whitman, Spencer, Sootla, Sten, Collot, Stephane, Gururangan, Suchin, Borodinsky, Sydney, Herman, Tamar, Fowler, Tara, Sheasha, Tarek, Georgiou, Thomas, Scialom, Thomas, Speckbacher, Tobias, Mihaylov, Todor, Xiao, Tong, Karn, Ujjwal, Goswami, Vedanuj, Gupta, Vibhor, Ramanathan, Vignesh, Kerkez, Viktor, Gonguet, Vincent, Do, Virginie, Vogeti, Vish, Petrovic, Vladan, Chu, Weiwei, Xiong, Wenhan, Fu, Wenyin, Meers, Whitney, Martinet, Xavier, Wang, Xiaodong, Tan, Xiaoqing Ellen, Xie, Xinfeng, Jia, Xuchao, Wang, Xuewei, Goldschlag, Yaelle, Gaur, Yashesh, Babaei, Yasmine, Wen, Yi, Song, Yiwen, Zhang, Yuchen, Li, Yue, Mao, Yuning, Coudert, Zacharie Delpierre, Yan, Zheng, Chen, Zhengxing, Papakipos, Zoe, Singh, Aaditya, Grattafiori, Aaron, Jain, Abha, Kelsey, Adam, Shajnfeld, Adam, Gangidi, Adithya, Victoria, Adolfo, Goldstand, Ahuva, Menon, Ajay, Sharma, Ajay, Boesenberg, Alex, Vaughan, Alex, Baevski, Alexei, Feinstein, Allie, Kallet, Amanda, Sangani, Amit, Yunus, Anam, Lupu, Andrei, Alvarado, Andres, Caples, Andrew, Gu, Andrew, Ho, Andrew, Poulton, Andrew, Ryan, Andrew, Ramchandani, Ankit, Franco, Annie, Saraf, Aparajita, Chowdhury, Arkabandhu, Gabriel, Ashley, Bharambe, Ashwin, Eisenman, Assaf, Yazdan, Azadeh, James, Beau, Maurer, Ben, Leonhardi, Benjamin, Huang, Bernie, Loyd, Beth, De Paola, Beto, Paranjape, Bhargavi, Liu, Bing, Wu, Bo, Ni, Boyu, Hancock, Braden, Wasti, Bram, Spence, Brandon, Stojkovic, Brani, Gamido, Brian, Montalvo, Britt, Parker, Carl, Burton, Carly, Mejia, Catalina, Wang, Changhan, Kim, Changkyu, Zhou, Chao, Hu, Chester, Chu, Ching-Hsiang, Cai, Chris, Tindal, Chris, Feichtenhofer, Christoph, Civin, Damon, Beaty, Dana, Kreymer, Daniel, Li, Daniel, Wyatt, Danny, Adkins, David, Xu, David, Testuggine, Davide, David, Delia, Parikh, Devi, Liskovich, Diana, Foss, Didem, Wang, Dingkang, Le, Duc, Holland, Dustin, Dowling, Edward, Jamil, Eissa, Montgomery, Elaine, Presani, Eleonora, Hahn, Emily, Wood, Emily, Brinkman, Erik, Arcaute, Esteban, Dunbar, Evan, Smothers, Evan, Sun, Fei, Kreuk, Felix, Tian, Feng, Ozgenel, Firat, Caggioni, Francesco, Guzmán, Francisco, Kanayet, Frank, Seide, Frank, Florez, Gabriela Medina, Schwarz, Gabriella, Badeer, Gada, Swee, Georgia, Halpern, Gil, Thattai, Govind, Herman, Grant, Sizov, Grigory, Guangyi, Zhang, Lakshminarayanan, Guna, Shojanazeri, Hamid, Zou, Han, Wang, Hannah, Zha, Hanwen, Habeeb, Haroun, Rudolph, Harrison, Suk, Helen, Aspegren, Henry, Goldman, Hunter, Damlaj, Ibrahim, Molybog, Igor, Tufanov, Igor, Veliche, Irina-Elena, Gat, Itai, Weissman, Jake, Geboski, James, Kohli, James, Asher, Japhet, Gaya, Jean-Baptiste, Marcus, Jeff, Tang, Jeff, Chan, Jennifer, Zhen, Jenny, Reizenstein, Jeremy, Teboul, Jeremy, Zhong, Jessica, Jin, Jian, Yang, Jingyi, Cummings, Joe, Carvill, Jon, Shepard, Jon, McPhie, Jonathan, Torres, Jonathan, Ginsburg, Josh, Wang, Junjie, Wu, Kai, U, Kam Hou, Saxena, Karan, Prasad, Karthik, Khandelwal, Kartikay, Zand, Katayoun, Matosich, Kathy, Veeraraghavan, Kaushik, Michelena, Kelly, Li, Keqian, Huang, Kun, Chawla, Kunal, Lakhotia, Kushal, Huang, Kyle, Chen, Lailin, Garg, Lakshya, A, Lavender, Silva, Leandro, Bell, Lee, Zhang, Lei, Guo, Liangpeng, Yu, Licheng, Moshkovich, Liron, Wehrstedt, Luca, Khabsa, Madian, Avalani, Manav, Bhatt, Manish, Tsimpoukelli, Maria, Mankus, Martynas, Hasson, Matan, Lennie, Matthew, Reso, Matthias, Groshev, Maxim, Naumov, Maxim, Lathi, Maya, Keneally, Meghan, Seltzer, Michael L., Valko, Michal, Restrepo, Michelle, Patel, Mihir, Vyatskov, Mik, Samvelyan, Mikayel, Clark, Mike, Macey, Mike, Wang, Mike, Hermoso, Miquel Jubert, Metanat, Mo, Rastegari, Mohammad, Bansal, Munish, Santhanam, Nandhini, Parks, Natascha, White, Natasha, Bawa, Navyata, Singhal, Nayan, Egebo, Nick, Usunier, Nicolas, Laptev, Nikolay Pavlovich, Dong, Ning, Zhang, Ning, Cheng, Norman, Chernoguz, Oleg, Hart, Olivia, Salpekar, Omkar, Kalinli, Ozlem, Kent, Parkin, Parekh, Parth, Saab, Paul, Balaji, Pavan, Rittner, Pedro, Bontrager, Philip, Roux, Pierre, Dollar, Piotr, Zvyagina, Polina, Ratanchandani, Prashant, Yuvraj, Pritish, Liang, Qian, Alao, Rachad, Rodriguez, Rachel, Ayub, Rafi, Murthy, Raghotham, Nayani, Raghu, Mitra, Rahul, Li, Raymond, Hogan, Rebekkah, Battey, Robin, Wang, Rocky, Maheswari, Rohan, Howes, Russ, Rinott, Ruty, Bondu, Sai Jayesh, Datta, Samyak, Chugh, Sara, Hunt, Sara, Dhillon, Sargun, Sidorov, Sasha, Pan, Satadru, Verma, Saurabh, Yamamoto, Seiji, Ramaswamy, Sharadh, Lindsay, Shaun, Feng, Sheng, Lin, Shenghao, Zha, Shengxin Cindy, Shankar, Shiva, Zhang, Shuqiang, Wang, Sinong, Agarwal, Sneha, Sajuyigbe, Soji, Chintala, Soumith, Max, Stephanie, Chen, Stephen, Kehoe, Steve, Satterfield, Steve, Govindaprasad, Sudarshan, Gupta, Sumit, Cho, Sungmin, Virk, Sunny, Subramanian, Suraj, Choudhury, Sy, Goldman, Sydney, Remez, Tal, Glaser, Tamar, Best, Tamara, Kohler, Thilo, Robinson, Thomas, Li, Tianhe, Zhang, Tianjun, Matthews, Tim, Chou, Timothy, Shaked, Tzook, Vontimitta, Varun, Ajayi, Victoria, Montanez, Victoria, Mohan, Vijai, Kumar, Vinay Satish, Mangla, Vishal, Albiero, Vítor, Ionescu, Vlad, Poenaru, Vlad, Mihailescu, Vlad Tiberiu, Ivanov, Vladimir, Li, Wei, Wang, Wenchen, Jiang, Wenwen, Bouaziz, Wes, Constable, Will, Tang, Xiaocheng, Wang, Xiaofang, Wu, Xiaojian, Wang, Xiaolan, Xia, Xide, Wu, Xilun, Gao, Xinbo, Chen, Yanjun, Hu, Ye, Jia, Ye, Qi, Ye, Li, Yenda, Zhang, Yilin, Zhang, Ying, Adi, Yossi, Nam, Youngjin, Yu, Wang, Hao, Yuchen, Qian, Yundi, He, Yuzi, Rait, Zach, DeVito, Zachary, Rosnbrick, Zef, Wen, Zhaoduo, Yang, Zhenyu, and Zhao, Zhiwei
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Computer Science - Artificial Intelligence ,Computer Science - Computation and Language ,Computer Science - Computer Vision and Pattern Recognition - Abstract
Modern artificial intelligence (AI) systems are powered by foundation models. This paper presents a new set of foundation models, called Llama 3. It is a herd of language models that natively support multilinguality, coding, reasoning, and tool usage. Our largest model is a dense Transformer with 405B parameters and a context window of up to 128K tokens. This paper presents an extensive empirical evaluation of Llama 3. We find that Llama 3 delivers comparable quality to leading language models such as GPT-4 on a plethora of tasks. We publicly release Llama 3, including pre-trained and post-trained versions of the 405B parameter language model and our Llama Guard 3 model for input and output safety. The paper also presents the results of experiments in which we integrate image, video, and speech capabilities into Llama 3 via a compositional approach. We observe this approach performs competitively with the state-of-the-art on image, video, and speech recognition tasks. The resulting models are not yet being broadly released as they are still under development.
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- 2024
19. Measuring the complexity of characterizing $[0, 1]$, $S^1$, and $\mathbb{R}$ up to homeomorphism
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Harrison-Trainor, Matthew and Haydar, Eissa
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Mathematics - Logic - Abstract
In analogy to the study of Scott rank/complexity of countable structures, we initiate the study of the Wadge degrees of the set of homeomorphic copies of topological spaces. One can view our results as saying that the classical characterizations of $[0,1]$ (e.g., as the unique continuum with exactly two non-cut points, and other similar characterizations), appropriated expressed, are the simplest possible characterizations of $[0,1]$. Formally, we show that the set of homeomorphic copies of $[0,1]$ is $\mathbf{\Pi}^0_4$-Wadge-complete. We also show that the set of homeomorphic copies of $S^1$ is $\mathbf{\Pi}^0_4$-Wadge-complete. On the other hand, we show that the set of homeomorphic copies of $\mathbb{R}$ is $\mathbf{\Pi}^1_1$-Wadge-complete. It is the local compactness that cannot be expressed in a Borel way; the set of homeomorphic copies of $\mathbb{R}$ is $\mathbf{\Pi}^0_4$-Wadge-complete within the locally compact spaces.
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- 2024
20. Weak Gravitational Lensing around Low Surface Brightness Galaxies in the DES Year 3 Data
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Chicoine, N., Prat, J., Zacharegkas, G., Chang, C., Tanoglidis, D., Drlica-Wagner, A., Anbajagane, D., Adhikari, S., Amon, A., Wechsler, R. H., Alarcon, A., Bechtol, K., Becker, M. R., Bernstein, G. M., Campos, A., Rosell, A. Carnero, Kind, M. Carrasco, Cawthon, R., Chen, R., Choi, A., Cordero, J., Davis, C., DeRose, J., Dodelson, S., Doux, C., Eckert, K., Elvin-Poole, J., Everett, S., Ferté, A., Gatti, M., Giannini, G., Gruen, D., Gruendl, R. A., Harrison, I., Herner, K., Jarvis, M., Leget, P. -F., MacCrann, N., McCullough, J., Myles, J., Navarro-Alsina, A., Pandey, S., Raveri, M., Rollins, R. P., Roodman, A., Ross, A. J., Rykoff, E. S., Sánchez, C., Secco, L. F., Sevilla-Noarbe, I., Sheldon, E., Shin, T., Troxel, M. A., Tutusaus, I., Varga, T. N., Yanny, B., Yin, B., Zuntz, J., Aguena, M., Alves, O., Bacon, D., Brooks, D., Carretero, J., Castander, F. J., Conselice, C., Desai, S., De Vicente, J., Doel, P., Ferrero, I., Flaugher, B., Frieman, J., García-Bellido, J., Gaztanaga, E., Gutierrez, G., Hinton, S. R., Hollowood, D. L., Honscheid, K., James, D. J., Kuehn, K., Lee, S., Lidman, C., Lima, M., Marshall, J. L., Mena-Fernández, J., Miquel, R., Muir, J., Ogando, R. L. C., Palmese, A., Pereira, M. E. S., Pieres, A., Malagón, A. A. Plazas, Porredon, A., Walker, A. R., Samuroff, S., Sanchez, E., Cid, D. Sanchez, Smith, M., Suchyta, E., Swanson, M. E. C., Tarle, G., To, C., Tucker, D. L., Vikram, V., Weaverdyck, N., and Wiseman, P.
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Astrophysics - Astrophysics of Galaxies - Abstract
We present galaxy-galaxy lensing measurements using a sample of low surface brightness galaxies (LSBGs) drawn from the Dark Energy Survey Year 3 (Y3) data as lenses. LSBGs are diffuse galaxies with a surface brightness dimmer than the ambient night sky. These dark-matter-dominated objects are intriguing due to potentially unusual formation channels that lead to their diffuse stellar component. Given the faintness of LSBGs, using standard observational techniques to characterize their total masses proves challenging. Weak gravitational lensing, which is less sensitive to the stellar component of galaxies, could be a promising avenue to estimate the masses of LSBGs. Our LSBG sample consists of 23,790 galaxies separated into red and blue color types at $g-i\ge 0.60$ and $g-i< 0.60$, respectively. Combined with the DES Y3 shear catalog, we measure the tangential shear around these LSBGs and find signal-to-noise ratios of 6.67 for the red sample, 2.17 for the blue sample, and 5.30 for the full sample. We use the clustering redshifts method to obtain redshift distributions for the red and blue LSBG samples. Assuming all red LSBGs are satellites, we fit a simple model to the measurements and estimate the host halo mass of these LSBGs to be $\log(M_{\rm host}/M_{\odot}) = 12.98 ^{+0.10}_{-0.11}$. We place a 95% upper bound on the subhalo mass at $\log(M_{\rm sub}/M_{\odot})<11.51$. By contrast, we assume the blue LSBGs are centrals, and place a 95% upper bound on the halo mass at $\log(M_\mathrm{host}/M_\odot) < 11.84$. We find that the stellar-to-halo mass ratio of the LSBG samples is consistent with that of the general galaxy population. This work illustrates the viability of using weak gravitational lensing to constrain the halo masses of LSBGs., Comment: 16 pages, 15 figures
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- 2024
21. Is larger always better? Evaluating and prompting large language models for non-generative medical tasks
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Zhu, Yinghao, Gao, Junyi, Wang, Zixiang, Liao, Weibin, Zheng, Xiaochen, Liang, Lifang, Wang, Yasha, Pan, Chengwei, Harrison, Ewen M., and Ma, Liantao
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Computer Science - Computation and Language ,Computer Science - Artificial Intelligence ,Computer Science - Machine Learning - Abstract
The use of Large Language Models (LLMs) in medicine is growing, but their ability to handle both structured Electronic Health Record (EHR) data and unstructured clinical notes is not well-studied. This study benchmarks various models, including GPT-based LLMs, BERT-based models, and traditional clinical predictive models, for non-generative medical tasks utilizing renowned datasets. We assessed 14 language models (9 GPT-based and 5 BERT-based) and 7 traditional predictive models using the MIMIC dataset (ICU patient records) and the TJH dataset (early COVID-19 EHR data), focusing on tasks such as mortality and readmission prediction, disease hierarchy reconstruction, and biomedical sentence matching, comparing both zero-shot and finetuned performance. Results indicated that LLMs exhibited robust zero-shot predictive capabilities on structured EHR data when using well-designed prompting strategies, frequently surpassing traditional models. However, for unstructured medical texts, LLMs did not outperform finetuned BERT models, which excelled in both supervised and unsupervised tasks. Consequently, while LLMs are effective for zero-shot learning on structured data, finetuned BERT models are more suitable for unstructured texts, underscoring the importance of selecting models based on specific task requirements and data characteristics to optimize the application of NLP technology in healthcare., Comment: arXiv admin note: text overlap with arXiv:2402.01713
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- 2024
22. AGN-driven outflows in clumpy media: multiphase structure and scaling relations
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Ward, Samuel Ruthven, Costa, Tiago, Harrison, Chris M., and Mainieri, Vincenzo
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Astrophysics - Astrophysics of Galaxies - Abstract
Small-scale winds driven from accretion discs surrounding active galactic nuclei (AGN) are expected to launch kpc-scale outflows into their host galaxies. However, the ways in which the structure of the interstellar medium (ISM) affects the multiphase content and impact of the outflow remains uncertain. We present a series of numerical experiments featuring a realistic small-scale AGN wind with velocity $5\times 10^3-10^4\ \rm{km/s}$ interacting with an isolated galaxy disc with a manually-controlled clumpy ISM, followed at sub-pc resolution. Our simulations are performed with AREPO and probe a wide range of AGN luminosities ($L=10^{43-47}\ \rm{erg/s}$) and ISM substructures. In homogeneous discs, the AGN wind sweeps up an outflowing, cooling shell, where the emerging cold phase dominates the mass and kinetic energy budgets, reaching a momentum flux $\dot{p} \approx 7\ L/c$. However, when the ISM is clumpy, outflow properties are profoundly different. They contain small, long-lived ($> 5\ \rm{Myr}$), cold ($T<10^{4.5}\ \rm{K}$) cloudlets entrained in the faster, hot outflow phase, which are only present in the outflow if radiative cooling is included in the simulation. While the cold phase dominates the mass of the outflow, most of the kinetic luminosity is now carried by a tenuous, hot phase with $T > 10^7 \ \rm K$. While the hot phases reaches momentum fluxes $\dot{p} \approx (1 - 5)\ L/c$, energy-driven bubbles couple to the cold phase inefficiently, producing modest momentum fluxes $\dot{p} < L/c$ in the fast-outflowing cold gas. These low momentum fluxes could lead to the outflows being misclassified as momentum-driven using common observational diagnostics. We also show predictions for scaling relations between outflow properties and AGN luminosity and discuss the challenges in constraining outflow driving mechanisms and kinetic coupling efficiencies using observed quantities., Comment: Accepted to MNRAS. 23 pages, 14 plots, 1 table. v2: minor update to Figure 11 to include observational fits from Bischetti+19
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- 2024
23. Computable learning of natural hypothesis classes
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Harrison-Trainor, Matthew and Akbari, Syed
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Computer Science - Machine Learning ,Mathematics - Logic - Abstract
This paper is about the recent notion of computably probably approximately correct learning, which lies between the statistical learning theory where there is no computational requirement on the learner and efficient PAC where the learner must be polynomially bounded. Examples have recently been given of hypothesis classes which are PAC learnable but not computably PAC learnable, but these hypothesis classes are unnatural or non-canonical in the sense that they depend on a numbering of proofs, formulas, or programs. We use the on-a-cone machinery from computability theory to prove that, under mild assumptions such as that the hypothesis class can be computably listable, any natural hypothesis class which is learnable must be computably learnable. Thus the counterexamples given previously are necessarily unnatural., Comment: This is a replacement of the earlier submission to just update the funding information
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- 2024
24. Optical alignment of contamination-sensitive Far-Ultraviolet spectrographs for Aspera SmallSat mission
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Khan, Aafaque R., Hamden, Erika, Chung, Haeun, Choi, Heejoo, Kim, Daewook, Melso, Nicole, Hoadley, Keri, Vargas, Carlos J., Truong, Daniel, Garcia, Elijah, Verts, Bill, Coronado, Fernando, Noenickx, Jamison, Corliss, Jason, Tanquary, Hannah, Mcmahon, Tom, Hamara, Dave, Agarwal, Simran, Augustin, Ramona, Behroozi, Peter, Bradley, Harrison, Brendel, Trenton, Burchett, Joe, Castillo, Jasmine Martinez, Chambers, Jacob, Corlies, Lauren, Davis, Greyson, Dettmar, Ralf-Jürgen, Douglas, Ewan, Ghidoli, Giulia, Goodwin, Alfred, Harris, Walter, Hergenrother, Carl, Howk, J. Christopher, Keppler, Miriam, Kerkeser, Nazende Ipek, Kidd Jr., John N., Li, Jessica S., Noriega, Gabe, Park, Sooseong, Pecha, Ryan, Sauve, Cork, Schiminovich, David, Selznick, Sanford, Siegmund, Oswald, Su, Rebecca, Uppnor, Sumedha, Vider, Jacob, Wolcott, Ellie, Yescas, Naomi, and Zaritsky, Dennis
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Astrophysics - Instrumentation and Methods for Astrophysics ,Physics - Instrumentation and Detectors ,Physics - Optics - Abstract
Aspera is a NASA Astrophysics Pioneers SmallSat mission designed to study diffuse OVI emission from the warm-hot phase gas in the halos of nearby galaxies. Its payload consists of two identical Rowland Circle-type long-slit spectrographs, sharing a single MicroChannel plate detector. Each spectrograph channel consists of an off-axis parabola primary mirror and a toroidal diffraction grating optimized for the 1013-1057 Angstroms bandpass. Despite the simple configuration, the optical alignment/integration process for Aspera is challenging due to tight optical alignment tolerances, driven by the compact form factor, and the contamination sensitivity of the Far-Ultraviolet optics and detectors. In this paper, we discuss implementing a novel multi-phase approach to meet these requirements using state-of-the-art optical metrology tools. For coarsely positioning the optics we use a blue-laser 3D scanner while the fine alignment is done with a Zygo interferometer and a custom computer-generated hologram. The detector focus requires iterative in-vacuum alignment using a Vacuum UV collimator. The alignment is done in a controlled cleanroom facility at the University of Arizona., Comment: Manuscript submitted for Proceedings of Astronomical Telescopes + Instrumentation 2024, Paper no. 13093-9
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- 2024
25. Advancing Ultraviolet Detector Technology for future missions: Investigating the dark current plateau in silicon detectors using photon-counting EMCCDs
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Khan, Aafaque R., Hamden, Erika, Kyne, Gillian, Jewell, April D., Henessey, John, Nikzad, Shouleh, Picouet, Vincent, Jones, Olivia, Bradley, Harrison, Kerkeser, Nazende, Lin, Zeren, Parker, Brock, West, Grant, Ford, John, Gacon, Frank, Beaty, Dave, and Vider, Jacob
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Astrophysics - Instrumentation and Methods for Astrophysics ,Physics - Instrumentation and Detectors - Abstract
Understanding the noise characteristics of high quantum efficiency silicon-based ultraviolet detectors, developed by the Microdevices Lab at the Jet Propulsion Laboratory, is critical for current and proposed UV missions using these devices. In this paper, we provide an overview of our detector noise characterization test bench that uses delta-doped, photon counting, Electron-multiplying CCDs (EMCCDs) to understand the fundamental noise properties relevant to all silicon CCDs and CMOS arrays. This work attempts to identify the source of the dark current plateau that has been previously measured with photon-counting EMCCDs and is known to be prevalent in other silicon-based arrays. It is suspected that the plateau could be due to a combination of detectable photons in the tail of blackbody radiation of the ambient instrument, low-level light leaks, and a non-temperature-dependent component that varies with substrate voltage. Our innovative test setup delineates the effect of the ambient environment during dark measurements by independently controlling the temperature of the detector and surrounding environment. We present the design of the test setup and preliminary results., Comment: Submitted for Proceedings of SPIE Astronomical Telescopes+Instrumentation 2024, Paper number: 13093-26
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- 2024
26. Assessing the formation of spin and charge stripes in La$_{3}$Ni$_{2}$O$_{7}$ from first-principles
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LaBollita, Harrison, Pardo, Victor, Norman, Michael R., and Botana, Antia S.
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Condensed Matter - Strongly Correlated Electrons ,Condensed Matter - Superconductivity - Abstract
We employ correlated density-functional theory methods (DFT + Hubbard $U$) to investigate the spin-density wave state of the bilayer Ruddlesden-Popper (RP) nickelate La$_{3}$Ni$_{2}$O$_{7}$ which becomes superconducting under pressure. We predict that the ground state of this bilayer RP material is a single spin-charge stripe phase with in-plane up$^\prime$/up/down$^\prime$/down diagonal stripes with up$^\prime$/down$^\prime$ being low spin (formally Ni$^{3+}$: $d^7$) and up/down being high spin (formally Ni$^{2+}$: $d^8$). The main feature of this solution (that is insulating even at $U=0$) is the dominant role of $d_{x^{2}-y^{2}}$ bands around the Fermi level, which would become doped with the introduction of electrons via oxygen vacancies. In spite of the similarity with cuprates in terms of the dominant role of $d_{x^{2}-y^{2}}$ bands, some differences are apparent in the magnetic ground state of La$_{3}$Ni$_{2}$O$_{7}$: the antiferromagnetic out-of-plane coupling within the bilayer (linked to the $d_{z^2}$ orbitals forming a spin-singlet-like configuration) is found to be the dominant one while in-plane interactions are reduced due to the stripe order of the ground state. With pressure, this striped magnetic ground state remains similar in nature but the increase in bandwidth quickly transitions La$_{3}$Ni$_{2}$O$_{7}$ into a metallic state with all the activity close to the Fermi level involving, to a large extent, $d_{x^2-y^2}$ orbitals. This is reminiscent of the cuprates and may provide key insights into how superconductivity arises in this material under pressure., Comment: 8 pages, 4 figures
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- 2024
27. Observation of exotic $J/\psi\phi$ resonances in diffractive processes in proton-proton collisions
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LHCb collaboration, Aaij, R., Abdelmotteleb, A. S. W., Beteta, C. Abellan, Abudinén, F., Ackernley, T., Adefisoye, A. A., Adeva, B., Adinolfi, M., Adlarson, P., Agapopoulou, C., Aidala, C. A., Ajaltouni, Z., Akar, S., Akiba, K., Albicocco, P., Albrecht, J., Alessio, F., Alexander, M., Aliouche, Z., Cartelle, P. Alvarez, Amalric, R., Amato, S., Amey, J. L., Amhis, Y., An, L., Anderlini, L., Andersson, M., Andreianov, A., Andreola, P., Andreotti, M., Andreou, D., Anelli, A., Ao, D., Archilli, F., Argenton, M., Cuendis, S. Arguedas, Artamonov, A., Artuso, M., Aslanides, E., Atzeni, M., Audurier, B., Bacher, D., Perea, I. Bachiller, Bachmann, S., Bachmayer, M., Back, J. J., Rodriguez, P. Baladron, Balagura, V., Baldini, W., Leite, J. Baptista de Souza, Barbetti, M., Barbosa, I. R., Barlow, R. J., Barsuk, S., Barter, W., Bartolini, M., Bartz, J., Baryshnikov, F., Basels, J. M., Bassi, G., Batsukh, B., Battig, A., Bay, A., Beck, A., Becker, M., Bedeschi, F., Bediaga, I. B., Beiter, A., Belin, S., Bellee, V., Belous, K., Belov, I., Belyaev, I., Benane, G., Bencivenni, G., Ben-Haim, E., Berezhnoy, A., Bernet, R., Andres, S. Bernet, Bertella, C., Bertolin, A., Betancourt, C., Betti, F., Bex, J., Bezshyiko, Ia., Bhom, J., Bieker, M. S., Biesuz, N. V., Billoir, P., Biolchini, A., Birch, M., Bishop, F. C. R., Bitadze, A., Bizzeti, A., Blake, T., Blanc, F., Blank, J. E., Blusk, S., Bocharnikov, V., Boelhauve, J. A., Garcia, O. Boente, Boettcher, T., Bohare, A., Boldyrev, A., Bolognani, C. S., Bolzonella, R., Bondar, N., Borgato, F., Borghi, S., Borsato, M., Borsuk, J. T., Bouchiba, S. A., Bowcock, T. J. V., Boyer, A., Bozzi, C., Bradley, M. J., Rodriguez, A. Brea, Breer, N., Brodzicka, J., Gonzalo, A. Brossa, Brown, J., Brundu, D., Buchanan, E., Buonaura, A., Buonincontri, L., Burke, A. T., Burr, C., Bursche, A., Butkevich, A., Butter, J. S., Buytaert, J., Byczynski, W., Cadeddu, S., Cai, H., Calabrese, R., Calefice, L., Cali, S., Calvi, M., Gomez, M. Calvo, Bouzas, J. I. Cambon, Campana, P., Perez, D. H. Campora, Quezada, A. F. Campoverde, Capelli, S., Capriotti, L., Caravaca-Mora, R., Carbone, A., Salgado, L. Carcedo, Cardinale, R., Cardini, A., Carniti, P., Carus, L., Vidal, A. Casais, Caspary, R., Casse, G., Godinez, J. Castro, Cattaneo, M., Cavallero, G., Cavallini, V., Celani, S., Cerasoli, J., Cervenkov, D., Cesare, S., Chadwick, A. J., Chahrour, I., Charles, M., Charpentier, Ph., Barajas, C. A. Chavez, Chefdeville, M., Chen, C., Chen, S., Chen, Z., Chernov, A., Chernyshenko, S., Chobanova, V., Cholak, S., Chrzaszcz, M., Chubykin, A., Chulikov, V., Ciambrone, P., Vidal, X. Cid, Ciezarek, G., Cifra, P., Clarke, P. E. L., Clemencic, M., Cliff, H. V., Closier, J., Toapaxi, C. Cocha, Coco, V., Cogan, J., Cogneras, E., Cojocariu, L., Collins, P., Colombo, T., Comerma-Montells, A., Congedo, L., Contu, A., Cooke, N., Corredoira, I., Correia, A., Corti, G., Meldrum, J. J. Cottee, Couturier, B., Craik, D. C., Torres, M. Cruz, Rivera, E. Curras, Currie, R., Da Silva, C. L., Dadabaev, S., Dai, L., Dai, X., Dall'Occo, E., Dalseno, J., D'Ambrosio, C., Daniel, J., Danilina, A., d'Argent, P., Davidson, A., Davies, J. E., Davis, A., Francisco, O. De Aguiar, De Angelis, C., De Benedetti, F., de Boer, J., De Bruyn, K., De Capua, S., De Cian, M., Da Graca, U. De Freitas Carneiro, De Lucia, E., De Miranda, J. M., De Paula, L., De Serio, M., De Simone, D., De Simone, P., De Vellis, F., de Vries, J. A., Debernardis, F., Decamp, D., Dedu, V., Del Buono, L., Delaney, B., Dembinski, H. -P., Deng, J., Denysenko, V., Deschamps, O., Dettori, F., Dey, B., Di Nezza, P., Diachkov, I., Didenko, S., Ding, S., Dittmann, L., Dobishuk, V., Docheva, A. D., Dolmatov, A., Dong, C., Donohoe, A. M., Dordei, F., Reis, A. C. dos, Dowling, A. D., Downes, A. G., Duan, W., Duda, P., Dudek, M. W., Dufour, L., Duk, V., Durante, P., Duras, M. M., Durham, J. M., Durmus, O. D., Dziurda, A., Dzyuba, A., Easo, S., Eckstein, E., Egede, U., Egorychev, A., Egorychev, V., Eisenhardt, S., Ejopu, E., Ek-In, S., Eklund, L., Elashri, M., Ellbracht, J., Ely, S., Ene, A., Epple, E., Escher, S., Eschle, J., Esen, S., Evans, T., Fabiano, F., Falcao, L. N., Fan, Y., Fang, B., Fantini, L., Faria, M., Farmer, K., Fazzini, D., Felkowski, L., Feng, M., Feo, M., Gomez, M. Fernandez, Fernez, A. D., Ferrari, F., Rodrigues, F. Ferreira, Sole, S. Ferreres, Ferrillo, M., Ferro-Luzzi, M., Filippov, S., Fini, R. A., Fiorini, M., Fischer, K. M., Fitzgerald, D. S., Fitzpatrick, C., Fleuret, F., Fontana, M., Foreman, L. F., Forty, R., Foulds-Holt, D., Sevilla, M. Franco, Frank, M., Franzoso, E., Frau, G., Frei, C., Friday, D. A., Fu, J., Fuehring, Q., Fujii, Y., Fulghesu, T., Gabriel, E., Galati, G., Galati, M. D., Torreira, A. Gallas, Galli, D., Gambetta, S., Gandelman, M., Gandini, P., Gao, H., Gao, R., Gao, Y., Garau, M., Martin, L. M. Garcia, Moreno, P. Garcia, Pardiñas, J. García, Garg, K. G., Garrido, L., Gaspar, C., Geertsema, R. E., Gerken, L. L., Gersabeck, E., Gersabeck, M., Gershon, T., Ghorbanimoghaddam, Z., Giambastiani, L., Giasemis, F. I., Gibson, V., Giemza, H. K., Gilman, A. L., Giovannetti, M., Gioventù, A., Gironell, P. Gironella, Giugliano, C., Giza, M. A., Gkougkousis, E. L., Glaser, F. C., Gligorov, V. V., Göbel, C., Golobardes, E., Golubkov, D., Golutvin, A., Gomes, A., Fernandez, S. Gomez, Abrantes, F. Goncalves, Goncerz, M., Gong, G., Gooding, J. A., Gorelov, I. V., Gotti, C., Grabowski, J. P., Cardoso, L. A. Granado, Graugés, E., Graverini, E., Grazette, L., Graziani, G., Grecu, A. T., Greeven, L. M., Grieser, N. A., Grillo, L., Gromov, S., Gu, C., Guarise, M., Guittiere, M., Guliaeva, V., Günther, P. A., Guseinov, A. -K., Gushchin, E., Guz, Y., Gys, T., Habermann, K., Hadavizadeh, T., Hadjivasiliou, C., Haefeli, G., Haen, C., Haimberger, J., Hajheidari, M., Halvorsen, M. M., Hamilton, P. M., Hammerich, J., Han, Q., Han, X., Hansmann-Menzemer, S., Hao, L., Harnew, N., Harrison, T., Hartmann, M., He, J., Heijhoff, K., Hemmer, F., Henderson, C., Henderson, R. D. L., Hennequin, A. M., Hennessy, K., Henry, L., Herd, J., Gascon, P. Herrero, Heuel, J., Hicheur, A., Mendizabal, G. Hijano, Hill, D., Hollitt, S. E., Horswill, J., Hou, R., Hou, Y., Howarth, N., Hu, J., Hu, W., Hu, X., Huang, W., Hulsbergen, W., Hunter, R. J., Hushchyn, M., Hutchcroft, D., Ilin, D., Ilten, P., Inglessi, A., Iniukhin, A., Ishteev, A., Ivshin, K., Jacobsson, R., Jage, H., Elles, S. J. Jaimes, Jakobsen, S., Jans, E., Jashal, B. K., Jawahery, A., Jevtic, V., Jiang, E., Jiang, X., Jiang, Y., Jiang, Y. J., John, M., Johnson, D., Jones, C. R., Jones, T. P., Joshi, S., Jost, B., Jurik, N., Juszczak, I., Kaminaris, D., Kandybei, S., Kang, Y., Karacson, M., Karpenkov, D., Kauniskangas, A., Kautz, J. W., Keizer, F., Kenzie, M., Ketel, T., Khanji, B., Kharisova, A., Kholodenko, S., Khreich, G., Kirn, T., Kirsebom, V. S., Kitouni, O., Klaver, S., Kleijne, N., Klimaszewski, K., Kmiec, M. R., Koliiev, S., Kolk, L., Konoplyannikov, A., Kopciewicz, P., Koppenburg, P., Korolev, M., Kostiuk, I., Kot, O., Kotriakhova, S., Kozachuk, A., Kravchenko, P., Kravchuk, L., Kreps, M., Kretzschmar, S., Krokovny, P., Krupa, W., Krzemien, W., Kubat, J., Kubis, S., Kucewicz, W., Kucharczyk, M., Kudryavtsev, V., Kulikova, E., Kupsc, A., Kutsenko, B. K., Lacarrere, D., Lai, A., Lampis, A., Lancierini, D., Gomez, C. Landesa, Lane, J. J., Lane, R., Langenbruch, C., Langer, J., Lantwin, O., Latham, T., Lazzari, F., Lazzeroni, C., Gac, R. Le, Lefèvre, R., Leflat, A., Legotin, S., Lehuraux, M., Cid, E. Lemos, Leroy, O., Lesiak, T., Leverington, B., Li, A., Li, H., Li, K., Li, L., Li, P., Li, P. -R., Li, S., Li, T., Li, Y., Li, Z., Lian, Z., Liang, X., Libralon, S., Lin, C., Lin, T., Lindner, R., Lisovskyi, V., Litvinov, R., Liu, F. L., Liu, G., Liu, K., Liu, Q., Liu, S., Liu, Y., Liu, Y. L., Salvia, A. Lobo, Loi, A., Castro, J. Lomba, Long, T., Lopes, J. H., Huertas, A. Lopez, Soliño, S. López, Lovell, G. H., Lucarelli, C., Lucchesi, D., Luchuk, S., Martinez, M. Lucio, Lukashenko, V., Luo, Y., Lupato, A., Luppi, E., Lynch, K., Lyu, X. -R., Ma, G. M., Ma, R., Maccolini, S., Machefert, F., Maciuc, F., Mack, B., Mackay, I., Mackey, L. M., Mohan, L. R. Madhan, Madurai, M. M., Maevskiy, A., Magdalinski, D., Maisuzenko, D., Majewski, M. W., Malczewski, J. J., Malde, S., Malecki, B., Malentacca, L., Malinin, A., Maltsev, T., Manca, G., Mancinelli, G., Mancuso, C., Escalero, R. Manera, Manuzzi, D., Marangotto, D., Marchand, J. F., Marchevski, R., Marconi, U., Mariani, S., Benito, C. Marin, Marks, J., Marshall, A. M., Marshall, P. J., Martelli, G., Martellotti, G., Martinazzoli, L., Martinelli, M., Santos, D. Martinez, Vidal, F. Martinez, Massafferri, A., Materok, M., Matev, R., Mathad, A., Matiunin, V., Matteuzzi, C., Mattioli, K. R., Mauri, A., Maurice, E., Mauricio, J., Mayencourt, P., Mazurek, M., McCann, M., Mcconnell, L., McGrath, T. H., McHugh, N. T., McNab, A., McNulty, R., Meadows, B., Meier, G., Melnychuk, D., Merk, M., Merli, A., Garcia, L. Meyer, Miao, D., Miao, H., Mikhasenko, M., Milanes, D. A., Minotti, A., Minucci, E., Miralles, T., Mitreska, B., Mitzel, D. S., Modak, A., Mödden, A., Mohammed, R. A., Moise, R. D., Mokhnenko, S., Mombächer, T., Monk, M., Monteil, S., Gomez, A. Morcillo, Morello, G., Morello, M. J., Morgenthaler, M. P., Morris, A. B., Morris, A. G., Mountain, R., Mu, H., Mu, Z. M., Muhammad, E., Muheim, F., Mulder, M., Müller, K., Muñoz-Rojas, F., Murta, R., Naik, P., Nakada, T., Nandakumar, R., Nanut, T., Nasteva, I., Needham, M., Neri, N., Neubert, S., Neufeld, N., Neustroev, P., Nicolini, J., Nicotra, D., Niel, E. M., Nikitin, N., Nogga, P., Nolte, N. S., Normand, C., Fernandez, J. Novoa, Nowak, G., Nunez, C., Nur, H. N., Oblakowska-Mucha, A., Obraztsov, V., Oeser, T., Okamura, S., Okhotnikov, A., Oldeman, R., Oliva, F., Olocco, M., Onderwater, C. J. G., O'Neil, R. H., Goicochea, J. M. Otalora, Owen, P., Oyanguren, A., Ozcelik, O., Padeken, K. O., Pagare, B., Pais, P. R., Pajero, T., Palano, A., Palutan, M., Panshin, G., Paolucci, L., Papanestis, A., Pappagallo, M., Pappalardo, L. L., Pappenheimer, C., Parkes, C., Passalacqua, B., Passaleva, G., Passaro, D., Pastore, A., Patel, M., Patoc, J., Patrignani, C., Pawley, C. J., Pellegrino, A., Altarelli, M. Pepe, Perazzini, S., Pereima, D., Castro, A. Pereiro, Perret, P., Perro, A., Petridis, K., Petrolini, A., Petrucci, S., Pfaller, J. P., Pham, H., Pica, L., Piccini, M., Pietrzyk, B., Pietrzyk, G., Pinci, D., Pisani, F., Pizzichemi, M., Placinta, V., Casasus, M. Plo, Polci, F., Lener, M. Poli, Poluektov, A., Polukhina, N., Polyakov, I., Polycarpo, E., Ponce, S., Popov, D., Poslavskii, S., Prasanth, K., Prouve, C., Pugatch, V., Punzi, G., Qian, W., Qin, N., Qu, S., Quagliani, R., Raab, N. V., Trejo, R. I. Rabadan, Rademacker, J. H., Rama, M., García, M. Ramírez, Pernas, M. Ramos, Rangel, M. S., Ratnikov, F., Raven, G., De Miguel, M. Rebollo, Redi, F., Reich, J., Reiss, F., Ren, Z., Resmi, P. K., Ribatti, R., Ricart, G. R., Riccardi, D., Ricciardi, S., Richardson, K., Richardson-Slipper, M., Rinnert, K., Robbe, P., Robertson, G., Rodrigues, E., Fernandez, E. Rodriguez, Lopez, J. A. Rodriguez, Rodriguez, E. Rodriguez, Rogovskiy, A., Rolf, D. L., Roloff, P., Romanovskiy, V., Lamas, M. Romero, Vidal, A. Romero, Romolini, G., Ronchetti, F., Rotondo, M., Roy, S. R., Rudolph, M. S., Ruf, T., Diaz, M. Ruiz, Fernandez, R. A. Ruiz, Vidal, J. Ruiz, Ryzhikov, A., Ryzka, J., Saavedra-Arias, J. J., Silva, J. J. Saborido, Sadek, R., Sagidova, N., Sahoo, D., Sahoo, N., Saitta, B., Salomoni, M., Gras, C. Sanchez, Sanderswood, I., Santacesaria, R., Rios, C. Santamarina, Santimaria, M., Santoro, L., Santovetti, E., Saputi, A., Saranin, D., Sarpis, G., Sarpis, M., Sarti, A., Satriano, C., Satta, A., Saur, M., Savrina, D., Sazak, H., Smead, L. G. Scantlebury, Scarabotto, A., Schael, S., Scherl, S., Schertz, A. M., Schiller, M., Schindler, H., Schmelling, M., Schmidt, B., Schmitt, S., Schmitz, H., Schneider, O., Schopper, A., Schulte, N., Schulte, S., Schune, M. H., Schwemmer, R., Schwering, G., Sciascia, B., Sciuccati, A., Sellam, S., Semennikov, A., Senger, T., Soares, M. Senghi, Sergi, A., Serra, N., Sestini, L., Seuthe, A., Shang, Y., Shangase, D. M., Shapkin, M., Sharma, R. S., Shchemerov, I., Shchutska, L., Shears, T., Shekhtman, L., Shen, Z., Sheng, S., Shevchenko, V., Shi, B., Shields, E. B., Shimizu, Y., Shmanin, E., Shorkin, R., Shupperd, J. D., Coutinho, R. Silva, Simi, G., Simone, S., Skidmore, N., Skwarnicki, T., Slater, M. W., Smallwood, J. C., Smith, E., Smith, K., Smith, M., Snoch, A., Lavra, L. Soares, Sokoloff, M. D., Soler, F. J. P., Solomin, A., Solovev, A., Solovyev, I., Song, R., Song, Y., Song, Y. S., De Almeida, F. L. Souza, De Paula, B. Souza, Norella, E. Spadaro, Spedicato, E., Speer, J. G., Spiridenkov, E., Spradlin, P., Sriskaran, V., Stagni, F., Stahl, M., Stahl, S., Stanislaus, S., Stein, E. N., Steinkamp, O., Stenyakin, O., Stevens, H., Strekalina, D., Su, Y., Suljik, F., Sun, J., Sun, L., Sun, Y., Sutcliffe, W., Swallow, P. N., Swystun, F., Szabelski, A., Szumlak, T., Tan, Y., Taneja, S., Tat, M. D., Terentev, A., Terzuoli, F., Teubert, F., Thomas, E., Thompson, D. J. D., Tilquin, H., Tisserand, V., T'Jampens, S., Tobin, M., Tomassetti, L., Tonani, G., Tong, X., Machado, D. Torres, Toscano, L., Tou, D. Y., Trippl, C., Tuci, G., Tuning, N., Uecker, L. H., Ukleja, A., Unverzagt, D. J., Ursov, E., Usachov, A., Ustyuzhanin, A., Uwer, U., Vagnoni, V., Valassi, A., Valenti, G., Canudas, N. Valls, Van Hecke, H., van Herwijnen, E., Van Hulse, C. B., Van Laak, R., van Veghel, M., Gomez, R. Vazquez, Regueiro, P. Vazquez, Sierra, C. Vázquez, Vecchi, S., Velthuis, J. J., Veltri, M., Venkateswaran, A., Vesterinen, M., Diaz, M. Vieites, Vilasis-Cardona, X., Figueras, E. Vilella, Villa, A., Vincent, P., Volle, F. C., Bruch, D. vom, Vorobyev, V., Voropaev, N., Vos, K., Vouters, G., Vrahas, C., Wagner, J., Walsh, J., Walton, E. J., Wan, G., Wang, C., Wang, G., Wang, J., Wang, M., Wang, N. W., Wang, R., Wang, X., Wang, X. W., Wang, Y., Wang, Z., Ward, J. A., Waterlaat, M., Watson, N. K., Websdale, D., Wei, Y., Westhenry, B. D. C., White, D. J., Whitehead, M., Wiederhold, A. R., Wiedner, D., Wilkinson, G., Wilkinson, M. K., Williams, M., Williams, M. R. J., Williams, R., Wilson, F. F., Wislicki, W., Witek, M., Witola, L., Wong, C. P., Wormser, G., Wotton, S. A., Wu, H., Wu, J., Wu, Y., Wyllie, K., Xian, S., Xiang, Z., Xie, Y., Xu, A., Xu, J., Xu, L., Xu, M., Xu, Z., Yang, D., Yang, S., Yang, X., Yang, Y., Yang, Z., Yeroshenko, V., Yeung, H., Yin, H., Yu, C. Y., Yu, J., Yuan, X., Zaffaroni, E., Zavertyaev, M., Zdybal, M., Zeng, M., Zhang, C., Zhang, D., Zhang, J., Zhang, L., Zhang, S., Zhang, Y., Zhang, Y. Z., Zhao, Y., Zharkova, A., Zhelezov, A., Zheng, X. Z., Zheng, Y., Zhou, T., Zhou, X., Zhou, Y., Zhovkovska, V., Zhu, L. Z., Zhu, X., Zhukov, V., Zhuo, J., Zou, Q., Zuliani, D., and Zunica, G.
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High Energy Physics - Experiment - Abstract
The first study of $J/\psi\phi$ production in diffractive processes in proton-proton collisions is presented. The study is based on an LHCb dataset recorded at centre-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 5 fb$^{-1}$. The data disfavour a nonresonant $J/\psi\phi$ production but are consistent with a resonant model including several resonant states observed previously only in $B^+ \to J/\psi\phi K^+$ decays. The $\chi_{c0}(4500)$ state is observed with a significance over $5\sigma$ and the $\chi_{c1}(4274)$ is confirmed with a significance of more than $4\sigma$., Comment: All figures and tables, along with any supplementary material and additional information, are available at: https://lhcbproject.web.cern.ch/Publications/LHCbProjectPublic/LHCb-PAPER-2023-043.html (LHCb public pages)
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- 2024
28. Synthetic Counterfactual Faces
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Ramesh, Guruprasad V, Rosenberg, Harrison, Hooda, Ashish, and Fawaz, Shimaa Ahmed Kassem
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Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Artificial Intelligence ,Computer Science - Machine Learning - Abstract
Computer vision systems have been deployed in various applications involving biometrics like human faces. These systems can identify social media users, search for missing persons, and verify identity of individuals. While computer vision models are often evaluated for accuracy on available benchmarks, more annotated data is necessary to learn about their robustness and fairness against semantic distributional shifts in input data, especially in face data. Among annotated data, counterfactual examples grant strong explainability characteristics. Because collecting natural face data is prohibitively expensive, we put forth a generative AI-based framework to construct targeted, counterfactual, high-quality synthetic face data. Our synthetic data pipeline has many use cases, including face recognition systems sensitivity evaluations and image understanding system probes. The pipeline is validated with multiple user studies. We showcase the efficacy of our face generation pipeline on a leading commercial vision model. We identify facial attributes that cause vision systems to fail., Comment: Paper under review. Full text and results will be updated after acceptance
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- 2024
29. Long-Horizon Planning for Multi-Agent Robots in Partially Observable Environments
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Nayak, Siddharth, Orozco, Adelmo Morrison, Have, Marina Ten, Thirumalai, Vittal, Zhang, Jackson, Chen, Darren, Kapoor, Aditya, Robinson, Eric, Gopalakrishnan, Karthik, Harrison, James, Ichter, Brian, Mahajan, Anuj, and Balakrishnan, Hamsa
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Computer Science - Robotics ,Computer Science - Multiagent Systems - Abstract
The ability of Language Models (LMs) to understand natural language makes them a powerful tool for parsing human instructions into task plans for autonomous robots. Unlike traditional planning methods that rely on domain-specific knowledge and handcrafted rules, LMs generalize from diverse data and adapt to various tasks with minimal tuning, acting as a compressed knowledge base. However, LMs in their standard form face challenges with long-horizon tasks, particularly in partially observable multi-agent settings. We propose an LM-based Long-Horizon Planner for Multi-Agent Robotics (LLaMAR), a cognitive architecture for planning that achieves state-of-the-art results in long-horizon tasks within partially observable environments. LLaMAR employs a plan-act-correct-verify framework, allowing self-correction from action execution feedback without relying on oracles or simulators. Additionally, we present MAP-THOR, a comprehensive test suite encompassing household tasks of varying complexity within the AI2-THOR environment. Experiments show that LLaMAR achieves a 30% higher success rate compared to other state-of-the-art LM-based multi-agent planners., Comment: 27 pages, 4 figures, 5 tables
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- 2024
30. Badminton Birdie-Like Aerodynamic Alignment of Drifting Dust Grains by Subsonic Gaseous Flows in Protoplanetary Disks
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Lin, Zhe-Yu Daniel, Li, Zhi-Yun, Yang, Haifeng, Looney, Leslie W., Stephens, Ian W., Fernández-López, Manuel, and Harrison, Rachel E.
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Astrophysics - Earth and Planetary Astrophysics - Abstract
Recent (sub)millimeter polarization observations of protoplanetary disks reveal toroidally aligned, effectively prolate dust grains large enough (at least ~100 $\mu$m) to efficiently scatter millimeter light. The alignment mechanism for these grains remains unclear. We explore the possibility that gas drag aligns grains through gas-dust relative motion when the grain's center of mass is offset from its geometric center, analogous to a badminton birdie's alignment in flight. A simple grain model of two non-identical spheres illustrates how a grain undergoes damped oscillations from flow-induced restoring torques which align its geometric center in the flow direction relative to its center of mass. Assuming specular reflection and subsonic flow, we derive an analytical equation of motion for spheroids where the center of mass can be shifted away from the spheroid's geometric center. We show that a prolate or an oblate grain can be aligned with the long axis parallel to the gas flow when the center of mass is shifted along that axis. Both scenarios can explain the required effectively prolate grains inferred from observations. Application to a simple disk model shows that the alignment timescales are shorter than or comparable to the orbital time. The grain alignment direction in a disk depends on the disk (sub-)structure and grain Stokes number (St) with azimuthal alignment for large St grains in sub-Keplerian smooth gas disks and for small St grains near the gas pressure extrema, such as rings and gaps., Comment: 21 pages, 12 figures, submitted to MNRAS
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- 2024
31. PKS 2131-021 -- Discovery of Strong Coherent Sinusoidal Variations from Radio to Optical Frequencies: Compelling Evidence for a Blazar Supermassive Black Hole Binary
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Kiehlmann, Sebastian, De La Parra, Philipe Vergara, Sullivan, Andrew, Synani, A., Liodakis, Ioannis, Readhead, Anthony, Graham, Matthew, Begelman, Mitchell, Blandford, Roger, Chatziioannou, Katerina, Ding, Yuanze, Harrison, Fiona, Homan, D., Hovatta, Talvikki, Kulkarni, Shrinivas, Lister, Matthew, Maiolino, Roberto, Max-Moerbeck, Walter, Molina, B., Mroz, Przemyslaw, O'Dea, Christopher, Pavlidou, Vasiliki, Pearson, Timothy J., Aller, Margo, Lawrence, C., Lazio, T. Joseph, O'Neill, S., Prince, Thomas, Ravi, Vikram, Reeves, Rodrigo, Tassis, Konstantinos, Vallisneri, Michele, and Zensus, J.
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Astrophysics - High Energy Astrophysical Phenomena - Abstract
Haystack and Owens Valley Radio Observatory (OVRO) observations recently revealed strong sinusoidal total flux density variations that maintained coherence between 1975 and 2021 in the blazar PKS 2131-021 ($z=1.283)$. This was interpreted as possible evidence of a supermassive black hole binary (SMBHB). Extended observations through 2023 show coherence over 47.9~years, with an observed period $P_\textrm{15 GHz}=(1739.3 \pm 1.2) \, {\rm days}$. We reject, with $p$-value = $5.3 \times 10^{-7}$, the hypothesis that the variations are due to random fluctuations in the red noise tail of the power spectral density. There is clearly a constant-period physical phenomenon in PKS 2131-021 producing coherent intermittent sinusoidal flux density variations. We find the coherent sinusoidal intensity variations extend from below 2.7 GHz to optical frequencies, from which we derive an observed period $P_\textrm{optical}=(1764 \pm 36)$ days. Across this broad frequency range there is a monotonic phase shift in the sinusoidal variations with frequency. The same coherent periodicity is possibly also observed at $\gamma$-ray energies. The importance of well-vetted SMBHB candidates to searches for gravitational waves is pointed out. We estimate the fraction of blazars that are SMBHB candidates to be $>1$ in 100. Thus monitoring programs covering tens of thousands of blazars could discover hundreds of SMBHB candidates., Comment: 23 pages, 17 figures, 5 tables, submitted to ApJ
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- 2024
32. Determination of five-parameter grain boundary characteristics in nanocrystalline Ni-W by Scanning Precession Electron Diffraction Tomography
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Rauch, E. F., Harrison, Patrick, Das, Saurabh Mohan, Goncalves, William, Da Silva, Alessandra, Chen, Xinren, Viganò, Nicola, Liebscher, Christian H., Ludwig, Wolfgang, and Zhou, Xuyang
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Condensed Matter - Materials Science - Abstract
Determining the full five-parameter grain boundary characteristics from experiments is essential for understanding grain boundaries impact on material properties, improving related models, and designing advanced alloys. However, achieving this is generally challenging, in particular at nanoscale, due to their 3D nature. In our study, we successfully determined the grain boundary characteristics of an annealed nickel-tungsten alloy (NiW) nanocrystalline needle-shaped specimen (tip) containing twins using Scanning Precession Electron Diffraction (SPED) Tomography. The presence of annealing twins in this face-centered cubic (fcc) material gives rise to common reflections in the SPED diffraction patterns, which challenges the reconstruction of orientation-specific virtual dark field (VDF) images required for tomographic reconstruction of the 3D grain shapes. To address this, an automated post-processing step identifies and deselects these shared reflections prior to the reconstruction of the VDF images. Combined with appropriate intensity normalization and projection alignment procedures, this approach enables high-fidelity 3D reconstruction of the individual grains contained in the needle-shaped sample volume. To probe the accuracy of the resulting boundary characteristics, the twin boundary surface normal directions were extracted from the 3D voxelated grain boundary map using a 3D Hough transform. For the sub-set of coherent Sigma 3 boundaries, the expected {111} grain boundary plane normals were obtained with an angular error of less than 3{\textdegree} for boundary sizes down to 400 nm${}^2$. This work advances our ability to precisely characterize and understand the complex grain boundaries that govern material properties.
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- 2024
33. Gentrification, Mobility, and Consumption
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De Giorgi, Giacomo, Moretti, Enrico, and Wheeler, Harrison
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Economics - General Economics - Abstract
We study the effect of localized housing price hikes on renters' mobility, consumption, and credit outcomes. Consistent with a spatial equilibrium model, we find that the consumption responses vary greatly for movers and stayers. While movers increase their consumption, purchase homes, and cars, stayers are relatively unaffected.
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- 2024
34. Tilt-to-length coupling in LISA Pathfinder: long-term stability
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Armano, M, Audley, H, Baird, J, Binetruy, P, Born, M, Bortoluzzi, D, Castelli, E, Cavalleri, A, Cesarini, A, Cruise, A M, Danzmann, K, Silva, M de Deus, Diepholz, I, Dixon, G, Dolesi, R, Ferraioli, L, Ferroni, V, Fitzsimons, E D, Freschi, M, Gesa, L, Giardini, D, Gibert, F, Giusteri, R, Grimani, C, Grzymisch, J, Harrison, I, Hartig, M-S, Heinzel, G, Hewitson, M, Hollington, D, Hoyland, D, Hueller, M, Inchauspé, H, Jennrich, O, Jetzer, P, Johann, U, Johlander, B, Karnesis, N, Kaune, B, Killow, C J, Korsakova, N, Lobo, J A, López-Zaragoza, J P, Maarschalkerweerd, R, Mance, D, Martín, V, Martin-Polo, L, Martin-Porqueras, F, Martino, J, McNamara, P W, Mendes, J, Mendes, L, Meshksar, N, Nofrarias, M, Paczkowski, S, Perreur-Lloyd, M, Petiteau, A, Plagnol, E, Ramos-Castro, J, Reiche, J, Rivas, F, Robertson, D I, Russano, G, Sanjuan, J, Slutsky, J, Sopuerta, C F, Sumner, T, Texier, D, Thorpe, J I, Vetrugno, D, Vitale, S, Wanner, G, Ward, H, Wass, P J, Weber, W J, Wissel, L, Wittchen, A, and Zweifel, P
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Astrophysics - Instrumentation and Methods for Astrophysics - Abstract
The tilt-to-length coupling during the LISA Pathfinder mission has been numerically and analytically modeled for particular timespans. In this work, we investigate the long-term stability of the coupling coefficients of this noise. We show that they drifted slowly (by 1\,$\mu$m/rad and 6$\times10^{-6}$ in 100 days) and strongly correlated to temperature changes within the satellite (8\,$\mu$m/rad/K and 30$\times10^{-6}$/K). Based on analytical TTL coupling models, we attribute the temperature-driven coupling changes to rotations of the test masses and small distortions in the optical setup. Particularly, we show that LISA Pathfinder's optical baseplate was bent during the cooldown experiment, which started in late 2016 and lasted several months.
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- 2024
35. Work extraction with feedback control using limited resources
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Hartle, Harrison, Wolpert, David, Stier, Andrew, Kempes, Christopher P., and Manzano, Gonzalo
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Condensed Matter - Statistical Mechanics - Abstract
Many physical, biological, and even social systems are faced with the problem of how to efficiently harvest free energy from any of many possible environmental states, yet only have a limited number of harvesting strategies to choose among. We formalize this general situation within the framework of work extraction from nonequilibirum systems using feedback control. Specifically, we analyze the combined and separate effects of noisy measurements, memory limitations, and the access to only a limited set of possible control operations, quantifying the amount of extractable work under all such constraints. Such analysis allows us to provide a general recipe to construct repertoires of allowed control operations that minimize the expected losses during the feedback protocol, i.e., that minimize expected entropy production. Our results highlight the importance and benefits of feedback control over uninformed (random) actions beyond the information gain under control restrictions and are applied to several situations including uncertain initial distributions., Comment: 13 pages, 1 figure
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- 2024
36. In situ observation of thermally activated and localized Li leaching from lithiated graphite
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Szeto, Harrison, Kumar, Vijay, and Zhu, Yangying
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Condensed Matter - Materials Science - Abstract
Temperature is known to impact Li-ion battery performance and safety, however, understanding its effect on Li-ion batteries has largely been limited to uniform high or low temperatures. While the insights gathered from such research are important, much less information is available on the effects of non-uniform temperatures which more accurately reflect the environments that Li-ion batteries are exposed to in real world applications. In this paper, we characterize the impact of a microscale, temperature hotspot on a Li-ion battery using a combination of in situ micro-Raman spectroscopy, in situ optical microscopy and COMSOL Multiphysics thermal simulations. Our results show that mild temperature heterogeneity induced by the micro-Raman laser can cause lithium to locally leach out from different lithiated graphite phases (LiC6 and LiC12) in the absence of an applied current. The Li metal is found to be largely localized to the region heated by the micro-Raman laser and is not observed upon uniform heating to comparable temperatures suggesting that temperature heterogeneity is uniquely responsible for causing Li to leach out from lithiated graphite phases. A mechanism whereby localized temperature heterogeneity induced by the laser induces heterogeneity in the degree of lithiation across the graphite anode is proposed to explain the localized Li leaching. This study highlights the sensitivity of lithiated graphite phases to minor temperature heterogeneity in the absence of an applied current.
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- 2024
37. Unraveling Radiomics Complexity: Strategies for Optimal Simplicity in Predictive Modeling
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Loutfi, Mahdi Ait Lhaj, Podasca, Teodora Boblea, Zwanenburg, Alex, Upadhaya, Taman, Barrios, Jorge, Raleigh, David R., Chen, William C., Capaldi, Dante P. I., Zheng, Hong, Gevaert, Olivier, Wu, Jing, Silva, Alvin C., Zhang, Paul J., Bai, Harrison X., Seuntjens, Jan, Löck, Steffen, Richard, Patrick O., Morin, Olivier, Reinhold, Caroline, Lepage, Martin, and Vallières, Martin
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Electrical Engineering and Systems Science - Image and Video Processing ,Computer Science - Computer Vision and Pattern Recognition - Abstract
Background: The high dimensionality of radiomic feature sets, the variability in radiomic feature types and potentially high computational requirements all underscore the need for an effective method to identify the smallest set of predictive features for a given clinical problem. Purpose: Develop a methodology and tools to identify and explain the smallest set of predictive radiomic features. Materials and Methods: 89,714 radiomic features were extracted from five cancer datasets: low-grade glioma, meningioma, non-small cell lung cancer (NSCLC), and two renal cell carcinoma cohorts (n=2104). Features were categorized by computational complexity into morphological, intensity, texture, linear filters, and nonlinear filters. Models were trained and evaluated on each complexity level using the area under the curve (AUC). The most informative features were identified, and their importance was explained. The optimal complexity level and associated most informative features were identified using systematic statistical significance analyses and a false discovery avoidance procedure, respectively. Their predictive importance was explained using a novel tree-based method. Results: MEDimage, a new open-source tool, was developed to facilitate radiomic studies. Morphological features were optimal for MRI-based meningioma (AUC: 0.65) and low-grade glioma (AUC: 0.68). Intensity features were optimal for CECT-based renal cell carcinoma (AUC: 0.82) and CT-based NSCLC (AUC: 0.76). Texture features were optimal for MRI-based renal cell carcinoma (AUC: 0.72). Tuning the Hounsfield unit range improved results for CECT-based renal cell carcinoma (AUC: 0.86). Conclusion: Our proposed methodology and software can estimate the optimal radiomics complexity level for specific medical outcomes, potentially simplifying the use of radiomics in predictive modeling across various contexts.
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- 2024
38. Precision measurements of the magnetic parameters of LISA Pathfinder test masses
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Armano, M, Audley, H, Baird, J, Binetruy, P, Born, M, Bortoluzzi, D, Castelli, E, Cavalleri, A, Cesarini, A, Cruise, A M, Danzmann, K, Silva, M De Deus, Diepholz, I, Dixon, G, Dolesi, R, Ferraioli, L, Ferroni, V, Fitzsimons, E D, Freschi, M, Gesa, L, Giardini, D, Gibert, F, Giusteri, R, Grimani, C, Grzymisch, J, Harrison, I, Hartig, M S, Heinzel, G, Hewitson, M, Hollington, D, Hoyland, D, Hueller, M, Inchauspé, H, Jennrich, O, Jetzer, P, Karnesis, N, Kaune, B, Korsakova, N, Killow, C J, Liu, L, Lobo, J A, López-Zaragoza, J P, Maarschalkerweerd, R, Mance, D, Martín, V, Martino, J, Martin-Polo, L, Martin-Porqueras, F, McNamara, P W, Mendes, J, Mendes, L, Meshksar, N, Nofrarias, M, Paczkowski, S, Perreur-Lloyd, M, Petiteau, A, Pivato, P, Plagnol, E, Ramos-Castro, J, Reiche, J, Rivas, F, Robertson, D I, Russano, G, Serrano, D, Slutsky, J, Sopuerta, C F, Sumner, T, Texier, D, Thorpe, J I, Vetrugno, D, Vitale, S, Wanner, G, Ward, H, Wass, P, Weber, W J, Wissel, L, Wittchen, A, and Zweifel, P
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Astrophysics - Instrumentation and Methods for Astrophysics ,General Relativity and Quantum Cosmology - Abstract
A precise characterization of the magnetic properties of LISA Pathfinder free falling test-masses is of special interest for future gravitational wave observatory in space. Magnetic forces have an important impact on the instrument sensitivity in the low frequency regime below the millihertz. In this paper we report on the magnetic injection experiments performed throughout LISA Pathfinder operations. We show how these experiments allowed a high precision estimate of the instrument magnetic parameters. The remanent magnetic moment was found to have a modulus of $(0.245\pm0.081)\,\rm{nAm}^2$, the x-component of the background magnetic field within the test masses position was measured to be $(414 \pm 74)$ nT and its gradient had a value of $(-7.4\pm 2.1)\,\mu$T/m. Finally, we also measured the test mass magnetic susceptibility to be $(-3.35\pm0.15)\times$10$^{-5}$ in the low frequency regime. All results are in agreement with on-ground estimates.
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- 2024
39. Magnetic-induced force noise in LISA Pathfinder free-falling test masses
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Armano, M, Audley, H, Baird, J, Binetruy, P, Born, M, Bortoluzzi, D, Castelli, E, Cavalleri, A, Cesarini, A, Cruise, A M, Danzmann, K, Silva, M De Deus, Diepholz, I, Dixon, G, Dolesi, R, Ferraioli, L, Ferroni, V, Fitzsimons, E D, Freschi, M, Gesa, L, Giardini, D, Gibert, F, Giusteri, R, Grimani, C, Grzymisch, J, Harrison, I, Hartig, M S, Heinzel, G, Hewitson, M, Hollington, D, Hoyland, D, Hueller, M, Inchauspé, H, Jennrich, O, Jetzer, P, Karnesis, N, Kaune, B, Korsakova, N, Killow, C J, Liu, L, Lobo, J A, López-Zaragoza, J P, Maarschalkerweerd, R, Mance, D, Martín, V, Martino, J, Martin-Polo, L, Martin-Porqueras, F, McNamara, P W, Mendes, J, Mendes, L, Meshksar, N, Nofrarias, M, Paczkowski, S, Perreur-Lloyd, M, Petiteau, A, Pivato, P, Plagnol, E, Ramos-Castro, J, Reiche, J, Rivas, F, Robertson, D I, Russano, G, Serrano, D, Slutsky, J, Sopuerta, C F, Sumner, T, Texier, D, Thorpe, J I, Vetrugno, D, Vitale, S, Wanner, G, Ward, H, Wass, P, Weber, W J, Wissel, L, Wittchen, A, and Zweifel, P
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Astrophysics - Instrumentation and Methods for Astrophysics ,General Relativity and Quantum Cosmology - Abstract
LISA Pathfinder was a mission designed to test key technologies required for gravitational wave detection in space. Magnetically driven forces play a key role in the instrument sensitivity in the low-frequency regime, which corresponds to the measurement band of interest for future space-borne gravitational wave observatories. Magnetic-induced forces couple to the test mass motion, introducing a contribution to the relative acceleration noise between the free falling test masses. In this Letter we present the first complete estimate of this term of the instrument performance model. Our results set the magnetic-induced acceleration noise during the February 2017 noise run of $\rm 0.25_{-0.08}^{+0.15}\,fm\,s^{-2}/\sqrt{Hz}$ at 1 mHz and $\rm 1.01_{-0.24}^{+0.73}\, fm\,s^{-2}/\sqrt{Hz}$ at 0.1 mHz. We also discuss how the non-stationarities of the interplanetary magnetic field can affect these values during extreme space weather conditions.
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- 2024
40. SUPER VIII. Fast and Furious at $z\sim2$: obscured type-2 active nuclei host faster ionised winds than type-1 systems
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Tozzi, G., Cresci, G., Perna, M., Mainieri, V., Mannucci, F., Marconi, A., Kakkad, D., Marasco, A., Brusa, M., Bertola, E., Bischetti, M., Carniani, S., Cicone, C., Circosta, C., Fiore, F., Feruglio, C., Harrison, C. M., Lamperti, I., Netzer, H., Piconcelli, E., Puglisi, A., Scholtz, J., Vietri, G., Vignali, C., and Zamorani, G.
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Astrophysics - Astrophysics of Galaxies - Abstract
We present spatially resolved VLT/SINFONI spectroscopy with adaptive optics of type-2 active galactic nuclei (AGN) from the SINFONI Survey for Unveiling the Physics and Effect of Radiative feedback (SUPER), which targeted X-ray bright ($L_{2-10 keV}\gtrsim10^{42}$ erg s$^{-1}$) AGN at Cosmic Noon ($z\sim2$). Our analysis of the rest-frame optical spectra unveils ionised outflows in all seven examined targets, as traced via [OIII]$\lambda$5007 line emission, moving at $v\gtrsim600$ km s$^{-1}$. In six objects these outflows are clearly spatially resolved and extend on 2-4 kpc scales, whereas marginally resolved in the remaining one. Interestingly, these SUPER type-2 AGN are all heavily obscured sources ($N_{H}\gtrsim10^{23}$ cm$^{-2}$) and host faster ionised outflows than their type-1 counterparts within the same range of bolometric luminosity ($L_{bol} \sim 10^{44.8-46.5}$ erg s$^{-1}$). SUPER has hence provided observational evidence that the type-1/type-2 dichotomy at $z\sim2$ might not be driven simply by projection effects, but might reflect two distinct obscuring life stages of active galaxies, as predicted by evolutionary models. Within this picture, SUPER type-2 AGN might be undergoing the 'blow-out' phase, where the large amount of obscuring material efficiently accelerates large-scale outflows via radiation pressure on dust, eventually unveiling the central active nucleus and signal the start of the bright, unobscured type-1 AGN phase. Moreover, the overall population of ionised outflows detected in SUPER has velocities comparable with the escape speed of their dark matter halos, and in general high enough to reach 30-50 kpc distances from the centre. These outflows are hence likely to sweep away the gas (at least) out of the baryonic disk and/or to heat the host gas reservoir, thus reducing and possibly quenching star formation., Comment: 21 pages, 13 figures. Key figure is 8. Accepted for publication in A&A
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- 2024
41. STRIDE: Simple Type Recognition In Decompiled Executables
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Green, Harrison, Schwartz, Edward J., Goues, Claire Le, and Vasilescu, Bogdan
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Computer Science - Cryptography and Security - Abstract
Decompilers are widely used by security researchers and developers to reverse engineer executable code. While modern decompilers are adept at recovering instructions, control flow, and function boundaries, some useful information from the original source code, such as variable types and names, is lost during the compilation process. Our work aims to predict these variable types and names from the remaining information. We propose STRIDE, a lightweight technique that predicts variable names and types by matching sequences of decompiler tokens to those found in training data. We evaluate it on three benchmark datasets and find that STRIDE achieves comparable performance to state-of-the-art machine learning models for both variable retyping and renaming while being much simpler and faster. We perform a detailed comparison with two recent SOTA transformer-based models in order to understand the specific factors that make our technique effective. We implemented STRIDE in fewer than 1000 lines of Python and have open-sourced it under a permissive license at https://github.com/hgarrereyn/STRIDE.
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- 2024
42. The PLATO Mission
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Rauer, Heike, Aerts, Conny, Cabrera, Juan, Deleuil, Magali, Erikson, Anders, Gizon, Laurent, Goupil, Mariejo, Heras, Ana, Lorenzo-Alvarez, Jose, Marliani, Filippo, Martin-Garcia, Cesar, Mas-Hesse, J. Miguel, O'Rourke, Laurence, Osborn, Hugh, Pagano, Isabella, Piotto, Giampaolo, Pollacco, Don, Ragazzoni, Roberto, Ramsay, Gavin, Udry, Stéphane, Appourchaux, Thierry, Benz, Willy, Brandeker, Alexis, Güdel, Manuel, Janot-Pacheco, Eduardo, Kabath, Petr, Kjeldsen, Hans, Min, Michiel, Santos, Nuno, Smith, Alan, Suarez, Juan-Carlos, Werner, Stephanie C., Aboudan, Alessio, Abreu, Manuel, Acuña, Lorena, Adams, Moritz, Adibekyan, Vardan, Affer, Laura, Agneray, François, Agnor, Craig, Børsen-Koch, Victor Aguirre, Ahmed, Saad, Aigrain, Suzanne, Al-Bahlawan, Ashraf, Gil, M de los Angeles Alcacera, Alei, Eleonora, Alencar, Silvia, Alexander, Richard, Alfonso-Garzón, Julia, Alibert, Yann, Prieto, Carlos Allende, Almeida, Leonardo, Sobrino, Roi Alonso, Altavilla, Giuseppe, Althaus, Christian, Trujillo, Luis Alonso Alvarez, Amarsi, Anish, Eiff, Matthias Ammler-von, Amôres, Eduardo, Andrade, Laerte, Antoniadis-Karnavas, Alexandros, António, Carlos, del Moral, Beatriz Aparicio, Appolloni, Matteo, Arena, Claudio, Armstrong, David, Aliaga, Jose Aroca, Asplund, Martin, Audenaert, Jeroen, Auricchio, Natalia, Avelino, Pedro, Baeke, Ann, Baillié, Kevin, Balado, Ana, Balestra, Andrea, Ball, Warrick, Ballans, Herve, Ballot, Jerome, Barban, Caroline, Barbary, Gaële, Barbieri, Mauro, Forteza, Sebastià Barceló, Barker, Adrian, Barklem, Paul, Barnes, Sydney, Navascues, David Barrado, Barragan, Oscar, Baruteau, Clément, Basu, Sarbani, Baudin, Frederic, Baumeister, Philipp, Bayliss, Daniel, Bazot, Michael, Beck, Paul G., Bedding, Tim, Belkacem, Kevin, Bellinger, Earl, Benatti, Serena, Benomar, Othman, Bérard, Diane, Bergemann, Maria, Bergomi, Maria, Bernardo, Pierre, Biazzo, Katia, Bignamini, Andrea, Bigot, Lionel, Billot, Nicolas, Binet, Martin, Biondi, David, Biondi, Federico, Birch, Aaron C., Bitsch, Bertram, Ceballos, Paz Victoria Bluhm, Bódi, Attila, Bognár, Zsófia, Boisse, Isabelle, Bolmont, Emeline, Bonanno, Alfio, Bonavita, Mariangela, Bonfanti, Andrea, Bonfils, Xavier, Bonito, Rosaria, Bonomo, Aldo Stefano, Börner, Anko, Saikia, Sudeshna Boro, Martín, Elisa Borreguero, Borsa, Francesco, Borsato, Luca, Bossini, Diego, Bouchy, Francois, Boué, Gwenaël, Boufleur, Rodrigo, Boumier, Patrick, Bourrier, Vincent, Bowman, Dominic M., Bozzo, Enrico, Bradley, Louisa, Bray, John, Bressan, Alessandro, Breton, Sylvain, Brienza, Daniele, Brito, Ana, Brogi, Matteo, Brown, Beverly, Brown, David, Brun, Allan Sacha, Bruno, Giovanni, Bruns, Michael, Buchhave, Lars A., Bugnet, Lisa, Buldgen, Gaël, Burgess, Patrick, Busatta, Andrea, Busso, Giorgia, Buzasi, Derek, Caballero, José A., Cabral, Alexandre, Calderone, Flavia, Cameron, Robert, Cameron, Andrew, Campante, Tiago, Martins, Bruno Leonardo Canto, Cara, Christophe, Carone, Ludmila, Carrasco, Josep Manel, Casagrande, Luca, Casewell, Sarah L., Cassisi, Santi, Castellani, Marco, Castro, Matthieu, Catala, Claude, Fernández, Irene Catalán, Catelan, Márcio, Cegla, Heather, Cerruti, Chiara, Cessa, Virginie, Chadid, Merieme, Chaplin, William, Charpinet, Stephane, Chiappini, Cristina, Chiarucci, Simone, Chiavassa, Andrea, Chinellato, Simonetta, Chirulli, Giovanni, Christensen-Dalsgaard, Jorgen, Church, Ross, Claret, Antonio, Clarke, Cathie, Claudi, Riccardo, Clermont, Lionel, Coelho, Hugo, Coelho, Joao, Cogato, Fabrizio, Colomé, Josep, Condamin, Mathieu, Conseil, Simon, Corbard, Thierry, Correia, Alexandre C. M., Corsaro, Enrico, Cosentino, Rosario, Costes, Jean, Cottinelli, Andrea, Covone, Giovanni, Creevey, Orlagh L., Crida, Aurelien, Csizmadia, Szilard, Cunha, Margarida, Curry, Patrick, da Costa, Jefferson, da Silva, Francys, Dalal, Shweta, Damasso, Mario, Damiani, Cilia, Damiani, Francesco, Chagas, Maria Liduina das, Davies, Melvyn, Davies, Guy, Davies, Ben, Davison, Gary, de Almeida, Leandro, de Angeli, Francesca, de Barros, Susana Cristina Cabral, Leão, Izan de Castro, de Freitas, Daniel Brito, de Freitas, Marcia Cristina, De Martino, Domitilla, de Medeiros, José Renan, de Paula, Luiz Alberto, de Plaa, Jelle, De Ridder, Joris, Deal, Morgan, Decin, Leen, Deeg, Hans, Degl'Innocenti, Scilla, Deheuvels, Sebastien, del Burgo, Carlos, Del Sordo, Fabio, Delgado-Mena, Elisa, Demangeon, Olivier, Denk, Tilmann, Derekas, Aliz, Desidera, Silvano, Dexet, Marc, Di Criscienzo, Marcella, Di Giorgio, Anna Maria, Di Mauro, Maria Pia, Rial, Federico Jose Diaz, Díaz-García, José-Javier, Dima, Marco, Dinuzzi, Giacomo, Dionatos, Odysseas, Distefano, Elisa, Nascimento Jr., Jose-Dias do, Domingo, Albert, D'Orazi, Valentina, Dorn, Caroline, Doyle, Lauren, Duarte, Elena, Ducellier, Florent, Dumaye, Luc, Dumusque, Xavier, Dupret, Marc-Antoine, Eggenberger, Patrick, Ehrenreich, David, Eigmüller, Philipp, Eising, Johannes, Emilio, Marcelo, Eriksson, Kjell, Ermocida, Marco, Giribaldi, Riano Isidoro Escate, Eschen, Yoshi, Estrela, Inês, Evans, Dafydd Wyn, Fabbian, Damian, Fabrizio, Michele, Faria, João Pedro, Farina, Maria, Farinato, Jacopo, Feliz, Dax, Feltzing, Sofia, Fenouillet, Thomas, Ferrari, Lorenza, Ferraz-Mello, Sylvio, Fialho, Fabio, Fienga, Agnes, Figueira, Pedro, Fiori, Laura, Flaccomio, Ettore, Focardi, Mauro, Foley, Steve, Fontignie, Jean, Ford, Dominic, Fornazier, Karin, Forveille, Thierry, Fossati, Luca, Franca, Rodrigo de Marca, da Silva, Lucas Franco, Frasca, Antonio, Fridlund, Malcolm, Furlan, Marco, Gabler, Sarah-Maria, Gaido, Marco, Gallagher, Andrew, Galli, Emanuele, Garcia, Rafael A., Hernández, Antonio García, Munoz, Antonio Garcia, García-Vázquez, Hugo, Haba, Rafael Garrido, Gaulme, Patrick, Gauthier, Nicolas, Gehan, Charlotte, Gent, Matthew, Georgieva, Iskra, Ghigo, Mauro, Giana, Edoardo, Gill, Samuel, Girardi, Leo, Winter, Silvia Giuliatti, Giusi, Giovanni, da Silva, João Gomes, Zazo, Luis Jorge Gómez, Gomez-Lopez, Juan Manuel, Hernández, Jonay Isai González, Murillo, Kevin Gonzalez, Gorius, Nicolas, Gouel, Pierre-Vincent, Goulty, Duncan, Granata, Valentina, Grenfell, John Lee, Grießbach, Denis, Grolleau, Emmanuel, Grouffal, Salomé, Grziwa, Sascha, Guarcello, Mario Giuseppe, Gueguen, Loïc, Guenther, Eike Wolf, Guilhem, Terrasa, Guillerot, Lucas, Guiot, Pierre, Guterman, Pascal, Gutiérrez, Antonio, Gutiérrez-Canales, Fernando, Hagelberg, Janis, Haldemann, Jonas, Hall, Cassandra, Handberg, Rasmus, Harrison, Ian, Harrison, Diana L., Hasiba, Johann, Haswell, Carole A., Hatalova, Petra, Hatzes, Artie, Haywood, Raphaelle, Hébrard, Guillaume, Heckes, Frank, Heiter, Ulrike, Hekker, Saskia, Heller, René, Helling, Christiane, Helminiak, Krzysztof, Hemsley, Simon, Heng, Kevin, Hermans, Aline, Hermes, JJ, Torres, Nadia Hidalgo, Hinkel, Natalie, Hobbs, David, Hodgkin, Simon, Hofmann, Karl, Hojjatpanah, Saeed, Houdek, Günter, Huber, Daniel, Huesler, Joseph, Hui-Bon-Hoa, Alain, Huygen, Rik, Huynh, Duc-Dat, Iro, Nicolas, Irwin, Jonathan, Irwin, Mike, Izidoro, André, Jacquinod, Sophie, Jannsen, Nicholas Emborg, Janson, Markus, Jeszenszky, Harald, Jiang, Chen, Mancebo, Antonio José Jimenez, Jofre, Paula, Johansen, Anders, Johnston, Cole, Jones, Geraint, Kallinger, Thomas, Kálmán, Szilárd, Kanitz, Thomas, Karjalainen, Marie, Karjalainen, Raine, Karoff, Christoffer, Kawaler, Steven, Kawata, Daisuke, Keereman, Arnoud, Keiderling, David, Kennedy, Tom, Kenworthy, Matthew, Kerschbaum, Franz, Kidger, Mark, Kiefer, Flavien, Kintziger, Christian, Kislyakova, Kristina, Kiss, László, Klagyivik, Peter, Klahr, Hubert, Klevas, Jonas, Kochukhov, Oleg, Köhler, Ulrich, Kolb, Ulrich, Koncz, Alexander, Korth, Judith, Kostogryz, Nadiia, Kovács, Gábor, Kovács, József, Kozhura, Oleg, Krivova, Natalie, Kučinskas, Arunas, Kuhlemann, Ilyas, Kupka, Friedrich, Laauwen, Wouter, Labiano, Alvaro, Lagarde, Nadege, Laget, Philippe, Laky, Gunter, Lam, Kristine Wai Fun, Lambrechts, Michiel, Lammer, Helmut, Lanza, Antonino Francesco, Lanzafame, Alessandro, Martiz, Mariel Lares, Laskar, Jacques, Latter, Henrik, Lavanant, Tony, Lawrenson, Alastair, Lazzoni, Cecilia, Lebre, Agnes, Lebreton, Yveline, Etangs, Alain Lecavelier des, Leinhardt, Zoe, Leleu, Adrien, Lendl, Monika, Leto, Giuseppe, Levillain, Yves, Libert, Anne-Sophie, Lichtenberg, Tim, Ligi, Roxanne, Lignieres, Francois, Lillo-Box, Jorge, Linsky, Jeffrey, Liu, John Scige, Loidolt, Dominik, Longval, Yuying, Lopes, Ilídio, Lorenzani, Andrea, Ludwig, Hans-Guenter, Lund, Mikkel, Lundkvist, Mia Sloth, Luri, Xavier, Maceroni, Carla, Madden, Sean, Madhusudhan, Nikku, Maggio, Antonio, Magliano, Christian, Magrin, Demetrio, Mahy, Laurent, Maibaum, Olaf, Malac-Allain, LeeRoy, Malapert, Jean-Christophe, Malavolta, Luca, Maldonado, Jesus, Mamonova, Elena, Manchon, Louis, Mann, Andrew, Mantovan, Giacomo, Marafatto, Luca, Marconi, Marcella, Mardling, Rosemary, Marigo, Paola, Marinoni, Silvia, Marques, Érico, Marques, Joao Pedro, Marrese, Paola Maria, Marshall, Douglas, Perales, Silvia Martínez, Mary, David, Marzari, Francesco, Masana, Eduard, Mascher, Andrina, Mathis, Stéphane, Mathur, Savita, Figueiredo, Ana Carolina Mattiuci, Maxted, Pierre F. L., Mazeh, Tsevi, Mazevet, Stephane, Mazzei, Francesco, McCormac, James, McMillan, Paul, Menou, Lucas, Merle, Thibault, Meru, Farzana, Mesa, Dino, Messina, Sergio, Mészáros, Szabolcs, Meunier, Nadége, Meunier, Jean-Charles, Micela, Giuseppina, Michaelis, Harald, Michel, Eric, Michielsen, Mathias, Michtchenko, Tatiana, Miglio, Andrea, Miguel, Yamila, Milligan, David, Mirouh, Giovanni, Mitchell, Morgan, Moedas, Nuno, Molendini, Francesca, Molnár, László, Mombarg, Joey, Montalban, Josefina, Montalto, Marco, Monteiro, Mário J. P. F. G., Morales, Juan Carlos, Morales-Calderon, Maria, Morbidelli, Alessandro, Mordasini, Christoph, Moreau, Chrystel, Morel, Thierry, Morello, Guiseppe, Morin, Julien, Mortier, Annelies, Mosser, Benoît, Mourard, Denis, Mousis, Olivier, Moutou, Claire, Mowlavi, Nami, Moya, Andrés, Muehlmann, Prisca, Muirhead, Philip, Munari, Matteo, Musella, Ilaria, Mustill, Alexander James, Nardetto, Nicolas, Nardiello, Domenico, Narita, Norio, Nascimbeni, Valerio, Nash, Anna, Neiner, Coralie, Nelson, Richard P., Nettelmann, Nadine, Nicolini, Gianalfredo, Nielsen, Martin, Niemi, Sami-Matias, Noack, Lena, Noels-Grotsch, Arlette, Noll, Anthony, Norazman, Azib, Norton, Andrew J., Nsamba, Benard, Ofir, Aviv, Ogilvie, Gordon, Olander, Terese, Olivetto, Christian, Olofsson, Göran, Ong, Joel, Ortolani, Sergio, Oshagh, Mahmoudreza, Ottacher, Harald, Ottensamer, Roland, Ouazzani, Rhita-Maria, Paardekooper, Sijme-Jan, Pace, Emanuele, Pajas, Miriam, Palacios, Ana, Palandri, Gaelle, Palle, Enric, Paproth, Carsten, Parro, Vanderlei, Parviainen, Hannu, Granado, Javier Pascual, Passegger, Vera Maria, Pastor-Morales, Carmen, Pätzold, Martin, Pedersen, May Gade, Hidalgo, David Pena, Pepe, Francesco, Pereira, Filipe, Persson, Carina M., Pertenais, Martin, Peter, Gisbert, Petit, Antoine C., Petit, Pascal, Pezzuto, Stefano, Pichierri, Gabriele, Pietrinferni, Adriano, Pinheiro, Fernando, Pinsonneault, Marc, Plachy, Emese, Plasson, Philippe, Plez, Bertrand, Poppenhaeger, Katja, Poretti, Ennio, Portaluri, Elisa, Portell, Jordi, de Mello, Gustavo Frederico Porto, Poyatos, Julien, Pozuelos, Francisco J., Moroni, Pier Giorgio Prada, Pricopi, Dumitru, Prisinzano, Loredana, Quade, Matthias, Quirrenbach160, ndreas, Reina6, Julio Arturo Rabanal, Soares, Maria Cristina Rabello, Raimondo, Gabriella, Rainer, Monica, Rodón, Jose Ramón, Ramón-Ballesta, Alejandro, Zapata, Gonzalo Ramos, Rätz, Stefanie, Rauterberg, Christoph, Redman, Bob, Redmer, Ronald, Reese, Daniel, Regibo, Sara, Reiners, Ansgar, Reinhold, Timo, Renie, Christian, Ribas, Ignasi, Ribeiro, Sergio, Ricciardi, Thiago Pereira, Rice, Ken, Richard, Olivier, Riello, Marco, Rieutord, Michel, Ripepi, Vincenzo, Rixon, Guy, Rockstein, Steve, Rodríguez, María Teresa Rodrigo, Díaz, Luisa Fernanda Rodríguez, Garcia, Juan Pablo Rodriguez, Rodriguez-Gomez, Julio, Roehlly, Yannick, Roig, Fernando, Rojas-Ayala, Bárbara, Rolf, Tobias, Rørsted, Jakob Lysgaard, Rosado, Hugo, Rosotti, Giovanni, Roth, Olivier, Roth, Markus, Rousseau, Alex, Roxburgh, Ian, Roy, Fabrice, Royer, Pierre, Ruane, Kirk, Mastropasqua, Sergio Rufini, de Galarreta, Claudia Ruiz, Russi, Andrea, Saar, Steven, Saillenfest, Melaine, Salaris, Maurizio, Salmon, Sebastien, Saltas, Ippocratis, Samadi, Réza, Samadi, Aunia, Samra, Dominic, da Silva, Tiago Sanches, Carrasco, Miguel Andrés Sánchez, Santerne, Alexandre, Santoli, Francesco, Santos, Ângela R. G., Mesa, Rosario Sanz, Sarro, Luis Manuel, Scandariato, Gaetano, Schäfer, Martin, Schlafly, Edward, Schmider, François-Xavier, Schneider, Jean, Schou, Jesper, Schunker, Hannah, Schwarzkopf, Gabriel Jörg, Serenelli, Aldo, Seynaeve, Dries, Shan, Yutong, Shapiro, Alexander, Shipman, Russel, Sicilia, Daniela, Sanmartin, Maria Angeles Sierra, Sigot, Axelle, Silliman, Kyle, Silvotti, Roberto, Simon, Attila E., Napoli, Ricardo Simoyama, Skarka, Marek, Smalley, Barry, Smiljanic, Rodolfo, Smit, Samuel, Smith, Alexis, Smith, Leigh, Snellen, Ignas, Sódor, Ádám, Sohl, Frank, Solanki, Sami K., Sortino, Francesca, Sousa, Sérgio, Southworth, John, Souto, Diogo, Sozzetti, Alessandro, Stamatellos, Dimitris, Stassun, Keivan, Steller, Manfred, Stello, Dennis, Stelzer, Beate, Stiebeler, Ulrike, Stokholm, Amalie, Storelvmo, Trude, Strassmeier, Klaus, Strøm, Paul Anthony, Strugarek, Antoine, Sulis, Sophia, Švanda, Michal, Szabados, László, Szabó, Róbert, Szabó, Gyula M., Szuszkiewicz, Ewa, Talens, Geert Jan, Teti, Daniele, Theisen, Tom, Thévenin, Frédéric, Thoul, Anne, Tiphene, Didier, Titz-Weider, Ruth, Tkachenko, Andrew, Tomecki, Daniel, Tonfat, Jorge, Tosi, Nicola, Trampedach, Regner, Traven, Gregor, Triaud, Amaury, Trønnes, Reidar, Tsantaki, Maria, Tschentscher, Matthias, Turin, Arnaud, Tvaruzka, Adam, Ulmer, Bernd, Ulmer-Moll, Solène, Ulusoy, Ceren, Umbriaco, Gabriele, Valencia, Diana, Valentini, Marica, Valio, Adriana, Guijarro, Ángel Luis Valverde, Van Eylen, Vincent, Van Grootel, Valerie, van Kempen, Tim A., Van Reeth, Timothy, Van Zelst, Iris, Vandenbussche, Bart, Vasiliou, Konstantinos, Vasilyev, Valeriy, de Mascarenhas, David Vaz, Vazan, Allona, Nunez, Marina Vela, Velloso, Eduardo Nunes, Ventura, Rita, Ventura, Paolo, Venturini, Julia, Trallero, Isabel Vera, Veras, Dimitri, Verdugo, Eva, Verma, Kuldeep, Vibert, Didier, Martinez, Tobias Vicanek, Vida, Krisztián, Vigan, Arthur, Villacorta, Antonio, Villaver, Eva, Aparicio, Marcos Villaverde, Viotto, Valentina, Vorobyov, Eduard, Vorontsov, Sergey, Wagner, Frank W., Walloschek, Thomas, Walton, Nicholas, Walton, Dave, Wang, Haiyang, Waters, Rens, Watson, Christopher, Wedemeyer, Sven, Weeks, Angharad, Weingril, Jörg, Weiss, Annita, Wendler, Belinda, West, Richard, Westerdorff, Karsten, Westphal, Pierre-Amaury, Wheatley, Peter, White, Tim, Whittaker, Amadou, Wickhusen, Kai, Wilson, Thomas, Windsor, James, Winter, Othon, Winther, Mark Lykke, Winton, Alistair, Witteck, Ulrike, Witzke, Veronika, Woitke, Peter, Wolter, David, Wuchterl, Günther, Wyatt, Mark, Yang, Dan, Yu, Jie, Sanchez, Ricardo Zanmar, Osorio, María Rosa Zapatero, Zechmeister, Mathias, Zhou, Yixiao, Ziemke, Claas, and Zwintz, Konstanze
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Astrophysics - Instrumentation and Methods for Astrophysics ,Astrophysics - Earth and Planetary Astrophysics ,Astrophysics - Solar and Stellar Astrophysics - Abstract
PLATO (PLAnetary Transits and Oscillations of stars) is ESA's M3 mission designed to detect and characterise extrasolar planets and perform asteroseismic monitoring of a large number of stars. PLATO will detect small planets (down to <2 R_(Earth)) around bright stars (<11 mag), including terrestrial planets in the habitable zone of solar-like stars. With the complement of radial velocity observations from the ground, planets will be characterised for their radius, mass, and age with high accuracy (5 %, 10 %, 10 % for an Earth-Sun combination respectively). PLATO will provide us with a large-scale catalogue of well-characterised small planets up to intermediate orbital periods, relevant for a meaningful comparison to planet formation theories and to better understand planet evolution. It will make possible comparative exoplanetology to place our Solar System planets in a broader context. In parallel, PLATO will study (host) stars using asteroseismology, allowing us to determine the stellar properties with high accuracy, substantially enhancing our knowledge of stellar structure and evolution. The payload instrument consists of 26 cameras with 12cm aperture each. For at least four years, the mission will perform high-precision photometric measurements. Here we review the science objectives, present PLATO's target samples and fields, provide an overview of expected core science performance as well as a description of the instrument and the mission profile at the beginning of the serial production of the flight cameras. PLATO is scheduled for a launch date end 2026. This overview therefore provides a summary of the mission to the community in preparation of the upcoming operational phases.
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- 2024
43. Checks and Balances: Built-In Data Routines Monitor the Impact of Boston's Teacher Leader Program
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Berg, Jill Harrison, Bosch, Christina A., Lessin-Joseph, Nina, and Souvanna, Phomdaen
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This article describes the Boston Teacher Leadership Certificate program created to expand teachers' capacity for teacher leadership roles. The professional learning was designed to strengthen teachers' leadership skills while also paying attention to whether and under what conditions they were more successful in their roles. To monitor the program's impact, the Boston Teacher Leadership Certificate program used four data routines: comparing pre-and post-course surveys, analyzing exit slips, reviewing online discussions, and looking together at student work. These routines supported collaborative inquiry, shared ownership for the quality of the work, and learning at all levels. At the end of the professional learning, 95% of course participants indicated that the course would improve their ability to have a positive impact on others' teaching practice, and 91% felt that the course would have a positive impact on their own teaching practice.
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- 2024
44. Supporting Safe Swallowing of Care Home Residents with Dysphagia: How Does the Care Delivered Compare with Guidance from Speech and Language Therapists?
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Hannah Griffin, Jennie Wilson, Alison Tingle, Anke Görzig, Kirsty Harrison, Celia Harding, Sukhpreet Aujla, Elizabeth Barley, and Heather Loveday
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Introduction: Dysphagia affects up to 70% of care home residents, increasing morbidity and hospital admissions. Speech and language therapists make recommendations to support safe nutrition but have limited capacity to offer ongoing guidance. This study aimed to understand if recommendations made to support safe and effective care are implemented and how these relate to the actual care delivered. Methods: Eleven mealtimes with residents with dysphagia were observed during 2020 using a tool capturing 12 elements of expected practice. Staff actions during mealtimes were compared with adherence to residents' care plans and speech and language therapist recommendations. Results: Written recommendations predominantly focused on food and fluid modification. Observations (n = 66) revealed food texture, posture, and alertness were adhered to on 90% of occasions, but alternating food and drink, prompting and ensuring swallow completed adherence was less than 60%. Thickened fluids frequently did not align with required International Dysphagia Diet Standardisation Initiative levels. Nutrition care provided in the dining room was less safe due to a lack of designated supervision. Conclusion: Care homes need to be supported to establish a safe swallowing culture to improve residents' safety and care experience.
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- 2024
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45. Genomic data provide insights into the classification of extant termites.
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Hellemans, Simon, Rocha, Mauricio, Wang, Menglin, Romero Arias, Johanna, Aanen, Duur, Bagnères, Anne-Geneviève, Buček, Aleš, Carrijo, Tiago, Chouvenc, Thomas, Cuezzo, Carolina, Constantini, Joice, Constantino, Reginaldo, Dedeine, Franck, Deligne, Jean, Eggleton, Paul, Evans, Theodore, Hanus, Robert, Harrison, Mark, Harry, Myriam, Josens, Guy, Jouault, Corentin, Kalleshwaraswamy, Chicknayakanahalli, Kaymak, Esra, Korb, Judith, Lee, Chow-Yang, Legendre, Frédéric, Li, Hou-Feng, Lo, Nathan, Lu, Tomer, Matsuura, Kenji, Maekawa, Kiyoto, McMahon, Dino, Mizumoto, Nobuaki, Oliveira, Danilo, Poulsen, Michael, Sillam-Dussès, David, Su, Nan-Yao, Tokuda, Gaku, Vargo, Edward, Ware, Jessica, Šobotník, Jan, Scheffrahn, Rudolf, Cancello, Eliana, Roisin, Yves, Engel, Michael, and Bourguignon, Thomas
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Isoptera ,Animals ,Phylogeny ,Genomics ,Genome ,Insect - Abstract
The higher classification of termites requires substantial revision as the Neoisoptera, the most diverse termite lineage, comprise many paraphyletic and polyphyletic higher taxa. Here, we produce an updated termite classification using genomic-scale analyses. We reconstruct phylogenies under diverse substitution models with ultraconserved elements analyzed as concatenated matrices or within the multi-species coalescence framework. Our classification is further supported by analyses controlling for rogue loci and taxa, and topological tests. We show that the Neoisoptera are composed of seven family-level monophyletic lineages, including the Heterotermitidae Froggatt, Psammotermitidae Holmgren, and Termitogetonidae Holmgren, raised from subfamilial rank. The species-rich Termitidae are composed of 18 subfamily-level monophyletic lineages, including the new subfamilies Crepititermitinae, Cylindrotermitinae, Forficulitermitinae, Neocapritermitinae, Protohamitermitinae, and Promirotermitinae; and the revived Amitermitinae Kemner, Microcerotermitinae Holmgren, and Mirocapritermitinae Kemner. Building an updated taxonomic classification on the foundation of unambiguously supported monophyletic lineages makes it highly resilient to potential destabilization caused by the future availability of novel phylogenetic markers and methods. The taxonomic stability is further guaranteed by the modularity of the new termite classification, designed to accommodate as-yet undescribed species with uncertain affinities to the herein delimited monophyletic lineages in the form of new families or subfamilies.
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- 2024
46. Climate change and Californias terrestrial biodiversity.
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Harrison, Susan, Franklin, Janet, Hernandez, Rebecca, Ikegami, Makihiko, Safford, Hugh, and Thorne, James
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California ,biodiversity ,climate change ,solar energy ,terrestrial ,Biodiversity ,California ,Climate Change ,Conservation of Natural Resources ,Humans ,Fires ,Introduced Species ,Plants ,Animals - Abstract
In this review and synthesis, we argue that California is an important test case for the nation and world because terrestrial biodiversity is very high, present and anticipated threats to biodiversity from climate change and other interacting stressors are severe, and innovative approaches to protecting biodiversity in the context of climate change are being developed and tested. We first review salient dimensions of Californias terrestrial physical, biological, and human diversity. Next, we examine four facets of the threat to their sustainability of these dimensions posed by climate change: direct impacts, illustrated by a new analysis of shifting diversity hotspots for plants; interactive effects involving invasive species, land-use change, and other stressors; the impacts of changing fire regimes; and the impacts of land-based renewable energy development. We examine recent policy responses in each of these areas, representing attempts to better protect biodiversity while advancing climate adaptation and mitigation. We conclude that Californias ambitious 30 × 30 Initiative and its efforts to harmonize biodiversity conservation with renewable energy development are important areas of progress. Adapting traditional suppression-oriented fire policies to the reality of new fire regimes is an area in which much progress remains to be made.
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- 2024
47. Characterizing Long COVID in Children and Adolescents
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Gross, Rachel S, Thaweethai, Tanayott, Kleinman, Lawrence C, Snowden, Jessica N, Rosenzweig, Erika B, Milner, Joshua D, Tantisira, Kelan G, Rhee, Kyung E, Jernigan, Terry L, Kinser, Patricia A, Salisbury, Amy L, Warburton, David, Mohandas, Sindhu, Wood, John C, Newburger, Jane W, Truong, Dongngan T, Flaherman, Valerie J, Metz, Torri D, Karlson, Elizabeth W, Chibnik, Lori B, Pant, Deepti B, Krishnamoorthy, Aparna, Gallagher, Richard, Lamendola-Essel, Michelle F, Hasson, Denise C, Katz, Stuart D, Yin, Shonna, Dreyer, Benard P, Carmilani, Megan, Coombs, K, Fitzgerald, Megan L, Güthe, Nick, Hornig, Mady, Letts, Rebecca J, Peddie, Aimee K, Taylor, Brittany D, Foulkes, Andrea S, Stockwell, Melissa S, Balaraman, Venkataraman, Bogie, Amanda, Bukulmez, Hulya, Dozor, Allen J, Eckrich, Daniel, Elliott, Amy J, Evans, Danielle N, Farkas, Jonathan S, Faustino, E Vincent S, Fischer, Laura, Gaur, Sunanda, Harahsheh, Ashraf S, Hasan, Uzma N, Hsia, Daniel S, Huerta-Montanez, Gredia, Hummel, Kathy D, Kadish, Matt P, Kaelber, David C, Krishnan, Sankaran, Kosut, Jessica S, Larrabee, Jerry, Lim, Peter Paul C, Michelow, Ian C, Oliveira, Carlos R, Raissy, Hengameh, Rosario-Pabon, Zaira, Ross, Judith L, Sato, Alice I, Stevenson, Michelle D, Talavera-Barber, Maria M, Teufel, Ronald J, Weakley, Kathryn E, Zimmerman, Emily, Bind, Marie-Abele C, Chan, James, Guan, Zoe, Morse, Richard E, Reeder, Harrison T, Akshoomoff, Natascha, Aschner, Judy L, Bhattacharjee, Rakesh, Cottrell, Lesley A, Cowan, Kelly, D'Sa, Viren A, Fiks, Alexander G, Gennaro, Maria L, Irby, Katherine, Khare, Manaswitha, Landeo Guttierrez, Jeremy, McCulloh, Russell J, Narang, Shalu, Ness- Cochinwala, Manette, Nolan, Sheila, Palumbo, Paul, Ryu, Julie, Salazar, Juan C, Selvarangan, Rangaraj, Stein, Cheryl R, Werzberger, Alan, Zempsky, William T, Aupperle, Robin, and Baker, Fiona C
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Biomedical and Clinical Sciences ,Clinical Sciences ,Health Sciences ,Emerging Infectious Diseases ,Neurosciences ,Coronaviruses ,Infectious Diseases ,Pediatric ,Minority Health ,Pain Research ,Infection ,Good Health and Well Being ,RECOVER-Pediatrics Consortium ,RECOVER-Pediatrics Group Authors ,Medical and Health Sciences ,General & Internal Medicine ,Biomedical and clinical sciences ,Health sciences - Abstract
ImportanceMost research to understand postacute sequelae of SARS-CoV-2 infection (PASC), or long COVID, has focused on adults, with less known about this complex condition in children. Research is needed to characterize pediatric PASC to enable studies of underlying mechanisms that will guide future treatment.ObjectiveTo identify the most common prolonged symptoms experienced by children (aged 6 to 17 years) after SARS-CoV-2 infection, how these symptoms differ by age (school-age [6-11 years] vs adolescents [12-17 years]), how they cluster into distinct phenotypes, and what symptoms in combination could be used as an empirically derived index to assist researchers to study the likely presence of PASC.Design, setting, and participantsMulticenter longitudinal observational cohort study with participants recruited from more than 60 US health care and community settings between March 2022 and December 2023, including school-age children and adolescents with and without SARS-CoV-2 infection history.ExposureSARS-CoV-2 infection.Main outcomes and measuresPASC and 89 prolonged symptoms across 9 symptom domains.ResultsA total of 898 school-age children (751 with previous SARS-CoV-2 infection [referred to as infected] and 147 without [referred to as uninfected]; mean age, 8.6 years; 49% female; 11% were Black or African American, 34% were Hispanic, Latino, or Spanish, and 60% were White) and 4469 adolescents (3109 infected and 1360 uninfected; mean age, 14.8 years; 48% female; 13% were Black or African American, 21% were Hispanic, Latino, or Spanish, and 73% were White) were included. Median time between first infection and symptom survey was 506 days for school-age children and 556 days for adolescents. In models adjusted for sex and race and ethnicity, 14 symptoms in both school-age children and adolescents were more common in those with SARS-CoV-2 infection history compared with those without infection history, with 4 additional symptoms in school-age children only and 3 in adolescents only. These symptoms affected almost every organ system. Combinations of symptoms most associated with infection history were identified to form a PASC research index for each age group; these indices correlated with poorer overall health and quality of life. The index emphasizes neurocognitive, pain, and gastrointestinal symptoms in school-age children but change or loss in smell or taste, pain, and fatigue/malaise-related symptoms in adolescents. Clustering analyses identified 4 PASC symptom phenotypes in school-age children and 3 in adolescents.Conclusions and relevanceThis study developed research indices for characterizing PASC in children and adolescents. Symptom patterns were similar but distinguishable between the 2 groups, highlighting the importance of characterizing PASC separately for these age ranges.
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- 2024
48. Brain‐age prediction: Systematic evaluation of site effects, and sample age range and size
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Yu, Yuetong, Cui, Hao‐Qi, Haas, Shalaila S, New, Faye, Sanford, Nicole, Yu, Kevin, Zhan, Denghuang, Yang, Guoyuan, Gao, Jia‐Hong, Wei, Dongtao, Qiu, Jiang, Banaj, Nerisa, Boomsma, Dorret I, Breier, Alan, Brodaty, Henry, Buckner, Randy L, Buitelaar, Jan K, Cannon, Dara M, Caseras, Xavier, Clark, Vincent P, Conrod, Patricia J, Crivello, Fabrice, Crone, Eveline A, Dannlowski, Udo, Davey, Christopher G, de Haan, Lieuwe, de Zubicaray, Greig I, Di Giorgio, Annabella, Fisch, Lukas, Fisher, Simon E, Franke, Barbara, Glahn, David C, Grotegerd, Dominik, Gruber, Oliver, Gur, Raquel E, Gur, Ruben C, Hahn, Tim, Harrison, Ben J, Hatton, Sean, Hickie, Ian B, Pol, Hilleke E Hulshoff, Jamieson, Alec J, Jernigan, Terry L, Jiang, Jiyang, Kalnin, Andrew J, Kang, Sim, Kochan, Nicole A, Kraus, Anna, Lagopoulos, Jim, Lazaro, Luisa, McDonald, Brenna C, McDonald, Colm, McMahon, Katie L, Mwangi, Benson, Piras, Fabrizio, Rodriguez‐Cruces, Raul, Royer, Jessica, Sachdev, Perminder S, Satterthwaite, Theodore D, Saykin, Andrew J, Schumann, Gunter, Sevaggi, Pierluigi, Smoller, Jordan W, Soares, Jair C, Spalletta, Gianfranco, Tamnes, Christian K, Trollor, Julian N, Ent, Dennis Van't, Vecchio, Daniela, Walter, Henrik, Wang, Yang, Weber, Bernd, Wen, Wei, Wierenga, Lara M, Williams, Steven CR, Wu, Mon‐Ju, Zunta‐Soares, Giovana B, Bernhardt, Boris, Thompson, Paul, Frangou, Sophia, Ge, Ruiyang, and Group, ENIGMA‐Lifespan Working
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Biological Psychology ,Psychology ,Aging ,Clinical Research ,Neurosciences ,Neurological ,Mental health ,Humans ,Adolescent ,Female ,Aged ,Adult ,Child ,Young Adult ,Male ,Brain ,Aged ,80 and over ,Child ,Preschool ,Middle Aged ,Magnetic Resonance Imaging ,Neuroimaging ,Sample Size ,benchmarking ,brain aging ,brainAGE ,ENIGMA‐Lifespan Working Group ,Cognitive Sciences ,Experimental Psychology ,Biological psychology ,Cognitive and computational psychology - Abstract
Structural neuroimaging data have been used to compute an estimate of the biological age of the brain (brain-age) which has been associated with other biologically and behaviorally meaningful measures of brain development and aging. The ongoing research interest in brain-age has highlighted the need for robust and publicly available brain-age models pre-trained on data from large samples of healthy individuals. To address this need we have previously released a developmental brain-age model. Here we expand this work to develop, empirically validate, and disseminate a pre-trained brain-age model to cover most of the human lifespan. To achieve this, we selected the best-performing model after systematically examining the impact of seven site harmonization strategies, age range, and sample size on brain-age prediction in a discovery sample of brain morphometric measures from 35,683 healthy individuals (age range: 5-90 years; 53.59% female). The pre-trained models were tested for cross-dataset generalizability in an independent sample comprising 2101 healthy individuals (age range: 8-80 years; 55.35% female) and for longitudinal consistency in a further sample comprising 377 healthy individuals (age range: 9-25 years; 49.87% female). This empirical examination yielded the following findings: (1) the accuracy of age prediction from morphometry data was higher when no site harmonization was applied; (2) dividing the discovery sample into two age-bins (5-40 and 40-90 years) provided a better balance between model accuracy and explained age variance than other alternatives; (3) model accuracy for brain-age prediction plateaued at a sample size exceeding 1600 participants. These findings have been incorporated into CentileBrain (https://centilebrain.org/#/brainAGE2), an open-science, web-based platform for individualized neuroimaging metrics.
- Published
- 2024
49. Use of Muscle Relaxants After Surgery in Traditional Medicare Part D Enrollees.
- Author
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Bongiovanni, Tasce, Gan, Siqi, Finlayson, Emily, Ross, Joseph, Harrison, James, Boscardin, John, and Steinman, Michael
- Subjects
Humans ,Aged ,Medicare Part D ,Male ,United States ,Female ,Pain ,Postoperative ,Aged ,80 and over ,Retrospective Studies ,Practice Patterns ,Physicians ,Drug Prescriptions - Abstract
BACKGROUND: Surgeons have come under increased scrutiny for postoperative pain management, particularly for opioid prescribing. To decrease opioid use but still provide pain control, nonopioid medications such as muscle relaxants are being used, which can be harmful in older adults. However, the prevalence of muscle relaxant prescribing, trends in use over time, and risk of prolonged use are unknown. STUDY DESIGN: Using a 20% representative Medicare sample, we conducted a retrospective analysis of muscle relaxant prescribing to patients ≥ 65 years of age. We merged patient data from Medicare Carrier, MedPAR, and Outpatient Files with Medicare Part D for the years 2013-2018. A total of 14 surgical procedures were included to represent a wide range of anatomic regions and specialties. RESULTS: The study cohort included 543,929 patients. Of the cohort, 8111 (1.5%) received a new muscle relaxant prescription at discharge. Spine procedures accounted for 12% of all procedures but 56% of postoperative prescribing. Overall, the rate of prescribing increased over the time period (1.4-2.0%, p < 0.001), with increases in prescribing primarily in the spine (7-9.6%, p < 0.0001) and orthopedic procedure groups (0.9-1.4%, p < 0.0001). Of patients discharged with a new muscle relaxant prescription, 10.7% had prolonged use. CONCLUSIONS: The use of muscle relaxants in the postoperative period for older adults is low, but increasing over time, especially in ortho and spine procedures. While pain control after surgery is crucial, surgeons should carefully consider the risks of muscle relaxant use, especially for older adults who are at higher risk for medication-related problems.
- Published
- 2024
50. Implementation of a Booster Sexual Health Education Curriculum for Older Adolescents in Rural Communities.
- Author
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Berglas, Nancy, Harrison, Salish, Romero, Julio, Borgen, Natasha, and Decker, Martha
- Subjects
adolescents ,mental health ,school health ,sex education ,sexual health ,youth voice ,Humans ,Adolescent ,Rural Population ,Female ,Male ,Curriculum ,Sex Education ,Sexual Health ,Health Promotion ,Health Knowledge ,Attitudes ,Practice - Abstract
Ongoing education on sexual health and other health promotion topics is critical as young people transition into adulthood. A booster round of education may be an effective strategy to reinforce information previously taught and expand to additional topics relevant later in adolescence. In partnership with a Youth Advisory Council, we co-designed READY, Set, Go!, a booster curriculum for older adolescents with modules covering adult preparation skills, sexual identity, relationships, reproductive health, and mental health. From November 2021 to January 2023, we provided the curriculum to 21 cohorts of 12th grade students (N = 433) in rural communities of Fresno County, CA, and conducted an implementation evaluation to assess its feasibility in school settings, acceptability by participants, and changes in short-term outcomes. Health educators completed implementation logs to track program adaptations. Youth completed pretest/posttest surveys to assess changes in outcomes and participant satisfaction. We used descriptive statistics to examine program adaptations and satisfaction. We used multivariable regression models to examine changes in outcomes, adjusted for sociodemographic characteristics. Health educators completed most activities as planned, with adaptations occurring in response to youth needs and scheduling limitations. Sexual health knowledge, confidence in adult preparation skills, awareness of local sexual and mental health services, and willingness to seek health services all increased significantly from pretest to posttest. Youth feedback was strongly positive. We conclude that booster sexual health education is a promising strategy to address critical knowledge gaps and support health promotion, especially in rural and other under-resourced communities.
- Published
- 2024
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