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The Vera C. Rubin Observatory will generate an unprecedented volume of data, including approximately 60 petabytes of raw data and around 30 trillion observed sources, posing a significant challenge for large-scale and end-user scientific analysis. As part of the LINCC Frameworks Project we are addressing these challenges with the development of the HATS (Hierarchical Adaptive Tiling Scheme) format and analysis package LSDB (Large Scale Database). HATS partitions data adaptively using a hierarchical tiling system to balance the file sizes, enabling efficient parallel analysis. Recent updates include improved metadata consistency, support for incremental updates, and enhanced compatibility with evolving datasets. LSDB complements HATS by providing a scalable, user-friendly interface for large catalog analysis, integrating spatial queries, crossmatching, and time-series tools while utilizing Dask for parallelization. We have successfully demonstrated the use of these tools with datasets such as ZTF and Pan-STARRS data releases on both cluster and cloud environments. We are deeply involved in several ongoing collaborations to ensure alignment with community needs, with future plans for IVOA standardization and support for upcoming Rubin, Euclid and Roman data. We provide our code and materials at lsdb.io., Comment: 4 pages, 2 figures, Proceedings of XXXIV Astronomical Data Analysis Software & Systems (ADASS) conference, November 10-14 2024, Valletta, Malta

We investigate the phenomenon of generalization through the lens of compression. In particular, we study the complexity dynamics of neural networks to explain grokking, where networks suddenly transition from memorizing to generalizing solutions long after over-fitting the training data. To this end we introduce a new measure of intrinsic complexity for neural networks based on the theory of Kolmogorov complexity. Tracking this metric throughout network training, we find a consistent pattern in training dynamics, consisting of a rise and fall in complexity. We demonstrate that this corresponds to memorization followed by generalization. Based on insights from rate--distortion theory and the minimum description length principle, we lay out a principled approach to lossy compression of neural networks, and connect our complexity measure to explicit generalization bounds. Based on a careful analysis of information capacity in neural networks, we propose a new regularization method which encourages networks towards low-rank representations by penalizing their spectral entropy, and find that our regularizer outperforms baselines in total compression of the dataset.

Photometric redshifts will be a key data product for the Rubin Observatory Legacy Survey of Space and Time (LSST) as well as for future ground and space-based surveys. The need for photometric redshifts, or photo-zs, arises from sparse spectroscopic coverage of observed galaxies. LSST is expected to observe billions of objects, making it crucial to have a photo-z estimator that is accurate and efficient. To that end, we present DeepDISC photo-z, a photo-z estimator that is an extension of the DeepDISC framework. The base DeepDISC network simultaneously detects, segments, and classifies objects in multi-band coadded images. We introduce photo-z capabilities to DeepDISC by adding a redshift estimation Region of Interest head, which produces a photo-z probability distribution function for each detected object. On simulated LSST images, DeepDISC photo-z outperforms traditional catalog-based estimators, in both point estimate and probabilistic metrics. We validate DeepDISC by examining dependencies on systematics including galactic extinction, blending and PSF effects. We also examine the impact of the data quality and the size of the training set and model. We find that the biggest factor in DeepDISC photo-z quality is the signal-to-noise of the imaging data, and see a reduction in photo-z scatter approximately proportional to the image data signal-to-noise. Our code is fully public and integrated in the RAIL photo-z package for ease of use and comparison to other codes at https://github.com/LSSTDESC/rail_deepdisc, Comment: 17 pages, 15 figures

We present a study of asteroseismically derived surface gravities, masses, and radii of a sample of red giant stars both with and without confirmed planetary companions using TESS photometric light curves. These red giants were drawn from radial velocity surveys, and their reported properties in the literature rely on more traditional methods using spectroscopy and isochrone fitting. Our asteroseismically derived surface gravities achieved a precision of $\sim$0.01 dex; however, they were on average $\sim$0.1~dex smaller than the literature. The systematic larger gravities of the literature could plausibly present as a systematic overestimation of stellar masses, which would in turn lead to overestimated planetary masses of the companions. We find that the fractional discrepancies between our asteroseismically-determined parameters and those previously found are typically larger for stellar radii ($\sim$10% discrepancy) than for stellar masses ($<5$% discrepancy). However, no evidence of a systematic difference between methods was found for either fundamental parameter. Two stars, HD~100065 and HD~18742, showed significant disagreement with the literature in both mass and radii. We explore the impacts on updated stellar properties on inferred planetary properties and caution that red giant radii may be more poorly constrained than uncertainties suggest., Comment: 17 pages, 9 figures, 6 tables

Photometric classifications of supernova (SN) light curves have become necessary to utilize the full potential of large samples of observations obtained from wide-field photometric surveys, such as the Zwicky Transient Facility (ZTF) and the Vera C. Rubin Observatory. Here, we present a photometric classifier for SN light curves that does not rely on redshift information and still maintains comparable accuracy to redshift-dependent classifiers. Our new package, Superphot+, uses a parametric model to extract meaningful features from multiband SN light curves. We train a gradient-boosted machine with fit parameters from 6,061 ZTF SNe that pass data quality cuts and are spectroscopically classified as one of five classes: SN Ia, SN II, SN Ib/c, SN IIn, and SLSN-I. Without redshift information, our classifier yields a class-averaged F1-score of 0.61 +/- 0.02 and a total accuracy of 0.83 +/- 0.01. Including redshift information improves these metrics to 0.71 +/- 0.02 and 0.88 +/- 0.01, respectively. We assign new class probabilities to 3,558 ZTF transients that show SN-like characteristics (based on the ALeRCE Broker light curve and stamp classifiers), but lack spectroscopic classifications. Finally, we compare our predicted SN labels with those generated by the ALeRCE light curve classifier, finding that the two classifiers agree on photometric labels for 82 +/- 2% of light curves with spectroscopic labels and 72% of light curves without spectroscopic labels. Superphot+ is currently classifying ZTF SNe in real time via the ANTARES Broker, and is designed for simple adaptation to six-band Rubin light curves in the future., Comment: 37 pages, 25 figures. Submitted to AAS Journals

We present a comprehensive x-ray scattering study of spontaneous magnetostriction in hexagonal MnTe, an antiferromagnetic semiconductor with a Neel temperature of $T_{\mathrm{N}} = 307$ K. We observe the largest spontaneous magnetovolume effect known for an antiferromagnet, reaching a volume contraction of $|\Delta V/V| > 7 \times 10^{-3}$. This can be justified semiquantitatively by considering bulk material properties, the spatial dependence of the superexchange interaction, and the geometrical arrangement of magnetic moments in MnTe. The highly unusual linear scaling of the magnetovolume effect with the short-range magnetic correlations, beginning in the paramagnetic state well above $T_{\mathrm{N}}$, points to a novel physical mechanism, which we explain in terms of a trilinear coupling of the elastic strain with superposed distinct domains of the antiferromagnetic order parameter. This novel mechanism for coupling lattice strain to robust short-range magnetic order casts new light on magnetostrictive phenomena and also provides a template by which the exceptional magnetostrictive properties of MnTe might be realized in a wide range of other functional materials., Comment: Submitted May 11, 2023

We propose DITTO, an offline imitation learning algorithm which uses world models and on-policy reinforcement learning to addresses the problem of covariate shift, without access to an oracle or any additional online interactions. We discuss how world models enable offline, on-policy imitation learning, and propose a simple intrinsic reward defined in the world model latent space that induces imitation learning by reinforcement learning. Theoretically, we show that our formulation induces a divergence bound between expert and learner, in turn bounding the difference in reward. We test our method on difficult Atari environments from pixels alone, and achieve state-of-the-art performance in the offline setting.

Two-dimensional (2D) hybrid organic-inorganic perovskites (HOIPs) are introducing new directions in the 2D materials landscape. The coexistence of ferroelectricity and spin-orbit interactions play a key role in their optoelectronic properties. We perform a detailed study on a recently synthesized ferroelectric 2D-HOIP, (AMP)PbI$_4$ (AMP = 4-aminomethyl-piperidinium). The calculated polarization and Rashba parameter are in excellent agreement with experimental values. We report a striking new effect, i.e., an extraordinarily large Rashba anisotropy that is tunable by ferroelectric polarization: as polarization is reversed, not only the spin texture chirality is inverted, but also the major and minor axes of the Rashba anisotropy ellipse in k-space are interchanged - a pseudo rotation. A $k \cdot p$ model Hamiltonian and symmetry-mode analysis reveal a quadrilinear coupling between the cation-rotation modes responsible for the Rashba ellipse pseudo-rotation, the framework rotation, and the polarization. These findings may provide new avenues for spin-optoelectronic devices such as spin valves or spin FETs., Comment: 19 pages, 5 figures

In the DFT community, it is common practice to use regular k-point grids (Monkhorst-Pack, MP) for Brillioun zone integration. Recently Wisesa et. al.\cite{wisesa2016efficient} and Morgan et. al.\cite{MORGAN2018424} demonstrated that generalized regular (GR) grids offer advantages over traditional MP grids. GR grids have not been widely adopted because one must search through a large number of candidate grids. This work describes an algorithm that can quickly search over GR grids for those that have the most uniform distribution of points and the best symmetry reduction. The grids are ~60% more efficient, on average, than MP grids and can now be generated on the fly in seconds.

The Zwicky Transient Facility is a large optical survey in multiple filters producing hundreds of thousands of transient alerts per night. We describe here various machine learning (ML) implementations and plans to make the maximal use of the large data set by taking advantage of the temporal nature of the data, and further combining it with other data sets. We start with the initial steps of separating bogus candidates from real ones, separating stars and galaxies, and go on to the classification of real objects into various classes. Besides the usual methods (e.g., based on features extracted from light curves) we also describe early plans for alternate methods including the use of domain adaptation, and deep learning. In a similar fashion we describe efforts to detect fast moving asteroids. We also describe the use of the Zooniverse platform for helping with classifications through the creation of training samples, and active learning. Finally we mention the synergistic aspects of ZTF and LSST from the ML perspective., Comment: Published in PASP Focus Issue on the Zwicky Transient Facility (doi: 10.1088/1538-3873/aaf3fa). 14 Pages, 8 Figures

Metal pollution in white dwarf atmospheres may be the accreted remnants of planetary objects. After the discovery of disintegrating planetary objects transiting WD 1145+017 (Vanderburg et al. 2015), undergraduates in the University of Washington's Pre- Major in Astronomy Program (Pre-MAP) were inspired to collect photometry of the brightest white dwarfs to hunt for similar transiting objects around other metal-polluted white dwarfs. Prior surveys have yet to make a detection of a transiting planet orbiting a white dwarf, yet white dwarfs are still an attractive target for searches of small, rocky planetary material. Since a typical white dwarf is Earth-sized, transits of Earth-sized planets could have depths >50%, so even low S/N photometry has a chance at discovering transiting material. We identified bright, northern, metal-polluted white dwarfs in the SDSS DR10 white dwarf catalog, and observed five targets with the Astrophysical Research Consortium Small Aperture Telescope (ARCSAT) 0.5-meter telescope at Apache Point Observatory. The ARCSAT photometry had sufficient precision to detect Moon-sized objects or larger at short orbital periods, though no such planets were detected for these targets. We look forward to surveys which may find planets orbiting white dwarfs, such as NASA's TESS, ESA's PLATO, and the Evryscope., Comment: Accepted to RNAAS

A fabrication method for positioning and embedding a single-walled carbon nanotube (SWNT) across the diameter of a solid state nanopore is presented. Chemical vapor deposition (CVD) is used to grow SWNTs over arrays of focused ion beam (FIB) milled pores in a thin silicon nitride membrane. This typically yields at least one pore whose diameter is centrally crossed by a SWNT. The final diameter of the FIB pore is adjusted to create a nanopore of any desired diameter by atomic layer deposition (ALD), simultaneously embedding and insulating the SWNT everywhere but in the region that crosses the diameter of the final nanopore, where it remains pristine and bare. This nanotube-articulated nanopore is an important step towards the realization of a new type of detector for biomolecule sensing and electronic characterization, including DNA sequencing.

Longitudinal resolution and lateral sensitivity are decisive characteristics that determine the suitability of a nanopore sensor for sequencing a strand of DNA as well as other important polymers. Previous modeling of DNA induced ionic current blockades in single atom thick graphene nanopores has shown these nanopores to have sufficient longitudinal resolution to distinguish individual nucleobases along the length of a DNA molecule. Here we experimentally focus on the sensitivity to small changes in DNA diameter that can be discerned with graphene nanopores. We show that remarkably large sensitivities (0.5 nA/A)are obtained when the nanopore is tailored to have a diameter close to that of the polymer of interest. Our results have been obtained with double-stranded DNA (dsDNA). Smaller graphene nanopores that can be tuned to the diameter of single-stranded DNA (ssDNA) for sequencing have only recently been demonstrated. Our results indicate that nanopore sensors based on such pores will provide excellent resolution and base discrimination, and will be robust competitors to protein nanopores that have recently demonstrated sequencing capability., Comment: 17 pages, 3 figures

Isolated, atomically thin conducting membranes of graphite, called graphene, have recently been the subject of intense research with the hope that practical applications in fields ranging from electronics to energy science will emerge. Here, we show that when immersed in ionic solution, a layer of graphene takes on new electrochemical properties that make it a trans-electrode. The trans-electrode's properties are the consequence of the atomic scale proximity of its two opposing liquid-solid interfaces together with graphene's well known in-plane conductivity. We show that several trans-electrode properties are revealed by ionic conductivity measurements on a CVD grown graphene membrane that separates two aqueous ionic solutions. Despite this membrane being only one to two atomic layers thick, we find it is a remarkable ionic insulator with a very small stable conductivity that depends on the ion species in solution. Electrical measurements on graphene membranes in which a single nanopore has been drilled show that the membrane's effective insulating thickness is less than one nanometer. This small effective thickness makes graphene an ideal substrate for very high-resolution, high throughput nanopore based single molecule detectors. Sensors based on modulation of graphene's in-plane electronic conductivity in response to trans-electrode environments and voltage biases will provide new insights into atomic processes at the electrode surfaces., Comment: Submitted 12 April 2010 to Nature, where it is under review

In phase 1 of this study, development and validation studies of a new assessment for the multiple intelligences were conducted. The second phase of the study was a pilot implementation project during a single academic year in collaboration with several public school teachers. Phase 1 involved a series of activities including initial instrument development, expert content reviews, field testing, pilot validation studies, item analysis, subscale development, instrument revision, and secondary validation studies. The developed instrument, the Multiple Intelligence Development Assessment Scales (MIDAS), was validated through studies involving nearly 3,000 middle school students, approximately 70 high school students, groups of adult and college students, and 400 employed adults. Phase 2 considered how a multiple intelligences (MI) profile might be best used by classroom teachers. Six elementary and secondary school teachers participated. Findings from this study indicated that an MI profile can sensitize teachers to their own weaknesses and help them empathize with students who are struggling. Teachers were able to understand the MI profile as a descriptive narrative of intellectual and creative life. Students of these teachers also appreciated the MI profile and found it encouraging. (Contains 5 tables and 21 references.) (SLD)

The use of a multiple intelligences (MI) assessment to enhance a career exploration program for eighth graders was studied. All of the eighth graders (n=160) in a suburban middle school completed three sets of activities as part of their career exploration program. Students completed a multiple intelligences self-assessment, the Multiple Intelligences Developmental Assessment Scales (MIDAS) (C. Shearer, 1996), and were given interpretive information. They also completed an interest inventory and an 8-hour career shadowing experience. Only 105 students responded to the followup questionnaire at the end of the school year, and 85% of these reported that they had participated in the career shadowing experience. A large majority of students were able to recall the strengths identified on their MI profiles, and they agreed that the profiles described their strengths adequately. Data indicate that most students learned about their MI strengths and were able to use the information to make logical decisions about high school courses they would take and their career shadowing experiences. Data support the value of the Career Exploration Program for these students. An appendix contains a chart of the MI strengths and related career shadowing experiences. (SLD)

High-transition-temperature superconductivity arises in copper oxides when holes or electrons are doped into the CuO2 planes of their insulating parent compounds. While hole-doping quickly induces metallic behavior and superconductivity in many cuprates, electron-doping alone is insufficient in materials such as R2CuO4 (R is Nd, Pr, La, Ce, etc.), where it is necessary to anneal an as-grown sample in a low-oxygen environment to remove a tiny amount of oxygen in order to induce superconductivity. Here we show that the microscopic process of oxygen reduction repairs Cu deficiencies in the as-grown materials and creates oxygen vacancies in the stoichiometric CuO2 planes, effectively reducing disorder and providing itinerant carriers for superconductivity. The resolution of this long-standing materials issue suggests that the fundamental mechanism for superconductivity is the same for electron- and hole-doped copper oxides., Comment: 23 pages, 3 figures, accepted for publication in Nature Materials

"The Multiple Intelligences Developmental Assessment Scales" (MIDAS) is a self- (or other-) completed instrument which is based upon the theory of multiple intelligences. The validity, reliability, and utility data regarding the MIDAS are reported here. The measure consists of 7 main scales and 24 subscales which summarize a person's intellectual disposition. It is appropriate for adolescents and adults and may be group administered via self-completion, or administered individually as a structured interview. The questions inquire about activities of everyday life that require cognitive ability, involvement, and judgment. This paper reviews the test's applications, its development, its reliability and validity, and its applicability in career exploration. Next, a study that involved 98 college students who were enrolled in career exploration classes is described. Results show that a strong majority of the students reported that the MIDAS Profile was beneficial and almost three-fourths of the students reported that they learned new information about their skills and abilities from the Profile. It is reported that the MIDAS provides information that is useful for increasing self-awareness especially regarding skills and abilities. The MIDAS possessed adequate reliability and validity as a self-report measure of a person's multiple intelligences disposition. Contains 16 references, a description of multiple intelligence scales, and 17 tables. (RJM)

Since Howard Gardner proposed the theory of multiple intelligences as an alternative to the unitary concept of general intelligence, educators have been searching for an acceptable method of assessment. To help with this search, three studies that describe the development and validation of a self- (and parent-) report measure of children's multiple intelligence disposition ("The Multiple Intelligence Developmental Assessment Scales for Children") (MIDAS-for-KIDS) are reported. In the first study, a preliminary version of the instrument was administered to 49 children and 74 parents. In the second study, 170 elementary school children and parents were used to examine item response patterns and scale consistency; in-depth interviews were conducted with 13 children. The third validation study involved over 2,100 children in grades K-8 from 5 states and across a range of socioeconomic levels. Exploratory factor analysis of the final 80-item version identified an appropriate 7-factor solution. This factor structure was confirmed on the other half of the sample. Findings indicate high internal consistency estimates, inter-rater ratings, and test-retest statistics. For the most part, scale scores also correlated in expected ways with appropriate criterion variables. Multiple intelligence definitions and tentative subscales, representative MIDAS items, lists of student activities as well as schools and programs, and seven tables are appended. (RJM)

We studied the unzipping kinetics of single molecules of double-stranded DNA by pulling one of their two strands through a narrow protein pore. PCR analysis yielded the first direct proof of DNA unzipping in such a system. The time to unzip each molecule was inferred from the ionic current signature of DNA traversal. The distribution of times to unzip under various experimental conditions fit a simple kinetic model. Using this model, we estimated the enthalpy barriers to unzipping and the effective charge of a nucleotide in the pore, which was considerably smaller than previously assumed., Comment: 10 pages, 5 figures, Accepted: Physics Review Letters

Howard Gardner's multiple intelligence (MI) theory is an alternative to the unitary concept of general intelligence, but it lacks a practical, reliable, and valid method of assessment. The Hillside Assessment of Perceived Intelligences (HAPI) is an attempt to measure the seven constructs of MI theory with an objective, psychometrically sound instrument. Previous investigations have shown that the HAPI provides a reliable profile, but it has not been clear how much validity this profile holds. This investigation into the concurrent validity of the HAPI with other instruments found the patterns of correlation coefficients to be generally supportive of the HAPI scales. Subjects were 338 undergraduate and graduate students and 45 adults from adult education or community volunteers. However, an examination of the construct validity of the scales using contrasted groups produced mixed results. Appendixes list the core components of MI theory and HAPI scale definitions. Four tables are included. (Contains 20 references.) (Author/SLD)