Stellar Rotation and Structure of the α Persei Complex: When Does Gyrochronology Start to Work?

On the pre-main sequence, the rotation rates of Sun-like stars are dictated by the interplay between the protostellar disk and the star’s contraction. At ages exceeding 100 Myr, magnetic spindown erases the initial stellar spin rate and enables rotation-based age dating (gyrochronology). The exact time at which the transition between these two regimes occurs depends on stellar mass, and has been challenging to empirically resolve due to a lack of viable calibration clusters. The α Persei open cluster (t ≈ 80 Myr, d ≈ 170 pc) may provide the needed calibrator, but recent analyses of the Gaia data have provided wildly varying views of its age and spatial extent. As such, we analyze a combination of TESS, Gaia, and LAMOST data to calibrate gyrochronology at the age of α Per and to uncover the cluster’s true morphology. By assembling a list of rotationally confirmed α Per members, we provide strong evidence that α Per is part of a larger complex of similarly aged stars. Through kinematic back-integration, we show that the most diffuse components of α Per were five times closer together 50 Myr ago. Finally, we use our stellar rotation periods to derive a relative gyrochronology age for α Per of 67% ± 12% the age of the Pleiades, which yields 86 ± 16 Myr given current knowledge. We show that by this age, stars more massive than ≈0.8 M_⊙ have converged to form a well-defined slow sequence

Southern Ocean Ice‐Covered Eddy Properties From Satellite Altimetry

We investigate statistical properties of surface currents as well as coherent mesoscale eddies in the seasonally ice-covered Southern Ocean. Based on a recent regional Sea Level Anomaly satellite altimetry data set, we compute Eddy Kinetic Energy (EKE) and detect mesoscale eddies. EKE is about one order of magnitude higher in the northern sector of the subpolar basin and over the continental slope, as compared to the middle of the subpolar gyres. An eddy detection methodology reveals that eddies are distributed evenly in the subpolar Southern Ocean, and their amplitude follows the spatial pattern of EKE. In addition to regional circulation variations, sea ice concentration arises as an important driver of eddy properties. Eddies have low amplitude and density in the pack ice, in particular in the middle of the gyres where the background circulation is unfavorable for instabilities. In contrast, the northern part of the Marginal Ice Zone is favorable for mesoscale eddies, especially cyclonic. There, eddies are stronger and their density is higher than in any other region of the ice-covered or ice-free subpolar Southern Ocean. This region is expected to be a site of frontogenesis due to sea ice melt and upwelling generated from interactions between the wind and the sea ice. While many mesoscale eddies will fall below detection level due to the small Rossby radius at high latitudes, these results contribute to understanding the interactions between mesoscale eddies, sea ice, and the background circulation in the subpolar region

Phosphate deprivation‐induced changes in tomato are mediated by an interaction between brassinosteroid signaling and zinc

Inorganic phosphate (Pi) is a necessary macronutrient for basic biological processes. Plants modulate their root system architecture (RSA) and cellular processes to adapt to Pi deprivation albeit with a growth penalty. Excess application of Pi fertilizer, on the contrary, leads to eutrophication and has a negative environmental impact. We compared RSA, root hair elongation, acid phosphatase activity, metal ion accumulation, and brassinosteroid hormone levels of Solanum lycopersicum (tomato) and Solanum pennellii, which is a wild relative of tomato, under Pi sufficiency and deficiency conditions to understand the molecular mechanism of Pi deprivation response in tomato. We showed that S. pennellii is partially insensitive to phosphate deprivation. Furthermore, it mounts a constitutive response under phosphate sufficiency. We demonstrate that activated brassinosteroid signaling through a tomato BZR1 ortholog gives rise to the same constitutive phosphate deficiency response, which is dependent on zinc overaccumulation. Collectively, these results reveal an additional strategy by which plants can adapt to phosphate starvation

Photogenerated Ni(I)-Bipyridine Halide Complexes: Structure-Function Relationships for Competitive C(sp²)-Cl Oxidative Addition and Dimerization Reactivity Pathways

We report the facile photochemical generation of a library of Ni(I)–bpy halide complexes (Ni(I)(ᴿbpy)X (R = t-Bu, H, MeOOC; X = Cl, Br, I) and benchmark their relative reactivity toward competitive oxidative addition and off-cycle dimerization pathways. Structure–function relationships between the ligand set and reactivity are developed, with particular emphasis on rationalizing previously uncharacterized ligand-controlled reactivity toward high energy and challenging C(sp²)–Cl bonds. Through a dual Hammett and computational analysis, the mechanism of the formal oxidative addition is found to proceed through an S_(N)Ar-type pathway, consisting of a nucleophilic two-electron transfer between the Ni(I) 3d(z²) orbital and the C_(aryl)–Cl σ* orbital, which contrasts the mechanism previously observed for activation of weaker C(sp²)–Br/I bonds. The bpy substituent provides a strong influence on reactivity, ultimately determining whether oxidative addition or dimerization even occurs. Here, we elucidate the origin of this substituent influence as arising from perturbations to the effective nuclear charge (Z_(eff)) of the Ni(I) center. Electron donation to the metal decreases Z_(eff), which leads to a significant destabilization of the entire 3d orbital manifold. Decreasing the 3d(z²) electron binding energies leads to a powerful two-electron donor to activate strong C(sp²)–Cl bonds. These changes also prove to have an analogous effect on dimerization, with decreases in Z_(eff) leading to more rapid dimerization. Ligand-induced modulation of Z_(eff) and the 3d(z²) orbital energy is thus a tunable target by which the reactivity of Ni(I) complexes can be altered, providing a direct route to stimulate reactivity with even stronger C–X bonds and potentially unveiling new ways to accomplish Ni-mediated photocatalytic cycles

Deep Synoptic Array Science: A Massive Elliptical Host Among Two Galaxy-cluster Fast Radio Bursts

The stellar population environments that are associated with fast radio burst (FRB) sources provide important insights for developing their progenitor theories. We expand the diversity of known FRB host environments by reporting two FRBs in massive galaxy clusters that were discovered by the Deep Synoptic Array (DSA-110) during its commissioning observations. FRB 20220914A has been localized to a star-forming, late-type galaxy at a redshift of 0.1139 with multiple starbursts at lookback times less than ∼3.5 Gyr in the A2310 galaxy cluster. Although the host galaxy of FRB 20220914A is similar to typical FRB hosts, the FRB 20220509G host stands out as a quiescent, early-type galaxy at a redshift of 0.0894 in the A2311 galaxy cluster. The discovery of FRBs in both late- and early-type galaxies adds to the body of evidence that the FRB sources have multiple formation channels. Therefore, even though FRB hosts are typically star-forming, there must exist formation channels that are consistent with old stellar population in galaxies. The varied star formation histories of the two FRB hosts that we report here indicate a wide delay-time distribution of FRB progenitors. Future work in constraining the FRB delay-time distribution, using the methods that we develop herein, will prove crucial in determining the evolutionary histories of FRB sources

Detecting Exoplanets Closer to Stars with Moderate Spectral Resolution Integral-field Spectroscopy

While radial velocity surveys have demonstrated that the population of gas giants peaks around 3 au, the most recent high-contrast imaging surveys have only been sensitive to planets beyond ∼10 au. Sensitivity at small angular separations from stars is currently limited by the variability of the point-spread function. We demonstrate how moderate-resolution integral-field spectrographs can detect planets at smaller separations (≲ 0.3") by detecting the distinct spectral signature of planets compared to the host star. Using OSIRIS (R ≈ 4000) at the W.M. Keck Observatory, we present the results of a planet search via this methodology around 20 young targets in the Ophiuchus and Taurus star-forming regions. We show that OSIRIS can outperform high-contrast coronagraphic instruments equipped with extreme adaptive optics and non-redundant masking in the 0.05"–0.3" regime. As a proof of concept, we present the 34σ detection of a high-contrast M dwarf companion at ≈0.1" with flux ratio of ≈ 0.92% around the field F2 star HD 148352. We developed an open-source Python package, breads, for the analysis of moderate-resolution integral-field spectroscopy data in which the planet and the host star signal are jointly modeled. The diffracted starlight continuum is forward-modeled using a spline model, which removes the need for prior high-pass filtering or continuum normalization. The code allows for analytic marginalization of linear hyperparameters, which simplifies the posterior sampling of other parameters (e.g., radial velocity, effective temperature). This technique could prove very powerful when applied to integral-field spectrographs such as NIRSpec on the JWST and other upcoming first-light instruments on the future Extremely Large Telescopes

Unification of Thermal and Quantum Noises in Gravitational-Wave Detectors

Contemporary gravitational-wave detectors are fundamentally limited by thermal noise—due to dissipation in the mechanical elements of the test mass—and quantum noise—from the vacuum fluctuations of the optical field used to probe the test-mass position. Two other fundamental noises can in principle also limit sensitivity: test-mass quantization noise due to the zero-point fluctuation of its mechanical modes and thermal excitation of the optical field. We use the quantum fluctuation-dissipation theorem to unify all four noises. This unified picture shows precisely when test-mass quantization noise and optical thermal noise can be ignored

Value restructures the organization of free recall

A large body of research illustrates the prioritization of goal-relevant information in memory; however, it is unclear how reward-related memories are organized. Using a rewarded free recall paradigm, we investigated how reward motivation structures the organization of memory around temporal and higher-order contexts. To better understand these processes, we simulated our findings using a reward-modulated variant of the Context Maintenance and Retrieval Model (CMR; Polyn et al., 2009). In the first study, we found that reward did not influence temporal clustering, but instead shifted the organization of memory based on reward category. Further, we showed that a reward-modulated learning rate and source features of CMR most accurately depict reward's enhancement on memory and clustering by value. In a second study, we showed that reward-memory effects can exist in both extended periods of sustained motivation and frequent changes in motivation, by showing equivalent reward effects using mixed- and pure-list motivation manipulations. However, we showed that a reward-modulated learning rate in isolation can support reward's enhancement of memory in pure-list contexts. Overall, we conclude that reward-related memories are adaptively organized by higher-order value information, and contextual binding to value contexts may only be necessary when rewards are intermittent versus sustained

Multiview Compressive Coding for 3D Reconstruction

A central goal of visual recognition is to understand objects and scenes from a single image. 2D recognition has witnessed tremendous progress thanks to large-scale learning and general-purpose representations. Comparatively, 3D poses new challenges stemming from occlusions not depicted in the image. Prior works try to overcome these by inferring from multiple views or rely on scarce CAD models and category-specific priors which hinder scaling to novel settings. In this work, we explore single-view 3D reconstruction by learning generalizable representations inspired by advances in self-supervised learning. We introduce a simple framework that operates on 3D points of single objects or whole scenes coupled with category-agnostic large-scale training from diverse RGB-D videos. Our model, Multiview Compressive Coding (MCC), learns to compress the input appearance and geometry to predict the 3D structure by querying a 3D-aware decoder. MCC's generality and efficiency allow it to learn from large-scale and diverse data sources with strong generalization to novel objects imagined by DALL⋅E 2 or captured in-the-wild with an iPhone

Single-shot 3D photoacoustic tomography using a single-element detector for ultrafast imaging of hemodynamics

Imaging hemodynamics is crucial for the diagnosis, treatment, and prevention of vascular diseases. However, current imaging techniques are limited due to the use of ionizing radiation or contrast agents, short penetration depth, or complex and expensive data acquisition systems. Photoacoustic tomography shows promise as a solution to these issues. However, existing photoacoustic tomography methods collect signals either sequentially or through numerous detector elements, leading to either low imaging speed or high system complexity and cost. To address these issues, here we introduce a method to capture a 3D photoacoustic image of vasculature using a single laser pulse and a single-element detector that functions as 6,400 virtual ones. Our method enables ultrafast volumetric imaging of hemodynamics in the human body at up to 1 kHz and requires only a single calibration for different objects and for long-term operations. We demonstrate 3D imaging of hemodynamics at depth in humans and small animals, capturing the variability in blood flow speeds. This concept can inspire other imaging technologies and find applications such as home-care monitoring, biometrics, point-of-care testing, and wearable monitoring