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Improving Star Cluster Age Estimates in PHANGS-HST Galaxies and the Impact on Cluster Demographics in NGC 628
No full textA long-standing problem when deriving the physical properties of stellar populations is the degeneracy between age, reddening, and metallicity. When a single metallicity is used for all the star clusters in a galaxy, this degeneracy can result in ‘catastrophic’ errors for old globular clusters. Typically, approximately 10–20 per cent of all clusters detected in spiral galaxies can have ages that are incorrect by a factor of 10 or more. In this paper, we present a pilot study for four galaxies (NGC 628, NGC 1433, NGC 1365, and NGC 3351) from the PHANGS-HST survey. We describe methods to correct the age-dating for old globular clusters, by first identifying candidates using their colours, and then reassigning ages and reddening based on a lower metallicity solution. We find that young ‘Interlopers’ can be identified from their Hα flux. CO (2-1) intensity or the presence of dust can also be used, but our tests show that they do not work as well. Improvements in the success fraction are possible at the ≈15 per cent level (reducing the fraction of catastrophic age-estimates from between 13 and 21 per cent, to between 3 and 8 per cent). A large fraction of the incorrectly age-dated globular clusters are systematically given ages around 100 Myr, polluting the younger populations as well. Incorrectly age-dated globular clusters significantly impact the observed cluster age distribution in NGC 628, which affects the physical interpretation of cluster disruption in this galaxy. For NGC 1365, we also demonstrate how to fix a second major age-dating problem, where very dusty young clusters with E(B − V) > 1.5 mag are assigned old, globular-cluster like ages. Finally, we note the discovery of a dense population of ≈300 Myr clusters around the central region of NGC 1365 and discuss how this results naturally from the dynamics in a barred galaxy
SN 2020qlb: A hydrogen-poor superluminous supernova with well-characterized light curve undulations
No full textContext. SN 2020qlb (ZTF20abobpcb) is a hydrogen-poor superluminous supernova (SLSN-I) that is among the most luminous (maximum M_g = −22.25 mag) and that has one of the longest rise times (77 days from explosion to maximum). We estimate the total radiated energy to be > 2.1 × 10⁵¹ erg. SN 2020qlb has a well-sampled light curve that exhibits clear near and post peak undulations, a phenomenon seen in other SLSNe, whose physical origin is still unknown.
Aims. We discuss the potential power source of this immense explosion as well as the mechanisms behind its observed light curve undulations.
Methods. We analyze photospheric spectra and compare them to other SLSNe-I. We constructed the bolometric light curve using photometry from a large data set of observations from the Zwicky Transient Facility (ZTF), Liverpool Telescope (LT), and Neil Gehrels Swift Observatory and compare it with radioactive, circumstellar interaction and magnetar models. Model residuals and light curve polynomial fit residuals are analyzed to estimate the undulation timescale and amplitude. We also determine host galaxy properties based on imaging and spectroscopy data, including a detection of the [O III]λ4363, auroral line, allowing for a direct metallicity measurement.
Results. We rule out the Arnett ⁵⁶Ni decay model for SN 2020qlb’s light curve due to unphysical parameter results. Our most favored power source is the magnetic dipole spin-down energy deposition of a magnetar. Two to three near peak oscillations, intriguingly similar to those of SN 2015bn, were found in the magnetar model residuals with a timescale of 32 ± 6 days and an amplitude of 6% of peak luminosity. We rule out centrally located undulation sources due to timescale considerations; and we favor the result of ejecta interactions with circumstellar material (CSM) density fluctuations as the source of the undulations
Seismo-VLAB: An open-source finite element software for seismic meso-scale simulations
No full textWe present Seismo-VLAB (SVL), a new open-source, object-oriented finite element software designed to optimize meso-scale simulations in the context of structural and geotechnical engineering. To this end, state-of-the-art tools and parallel computing capabilities required for efficient modeling of soil–structure interaction and wave propagation in heterogeneous half-spaces are included. For example, perfectly matched layer, domain reduction method, dynamic nonlinear solvers, cutting edge parallel linear system solvers, domain decomposition method, and a series of plasticity models are some of the features available in SVL. In this work, we present the numerical implementation and software structure so enthusiastic developers can contribute to this open-source project and showcase some software capabilities using an illustrative example
UGC 4211: A Confirmed Dual Active Galactic Nucleus in the Local Universe at 230 pc Nuclear Separation
No full textWe present multiwavelength high-spatial resolution (∼0".1, 70 pc) observations of UGC 4211 at z = 0.03474, a late-stage major galaxy merger at the closest nuclear separation yet found in near-IR imaging (0".32, ∼230 pc projected separation). Using Hubble Space Telescope/Space Telescope Imaging Spectrograph, Very Large Telescope/MUSE+AO, Keck/OSIRIS+AO spectroscopy, and the Atacama Large Millimeter/submillimeter Array (ALMA) observations, we show that the spatial distribution, optical and near-infrared emission lines, and millimeter continuum emission are all consistent with both nuclei being powered by accreting supermassive black holes (SMBHs). Our data, combined with common black hole mass prescriptions, suggest that both SMBHs have similar masses, log(M_(BH)/M_⊙) ∼ 8.1 (south) and log(M_(BH)/M_⊙) ∼ 8.3 (north), respectively. The projected separation of 230 pc (∼6× the black hole sphere of influence) represents the closest-separation dual active galactic nuclei (AGN) studied to date with multiwavelength resolved spectroscopy and shows the potential of nuclear (<50 pc) continuum observations with ALMA to discover hidden growing SMBH pairs. While the exact occurrence rate of close-separation dual AGN is not yet known, it may be surprisingly high, given that UGC 4211 was found within a small, volume-limited sample of nearby hard X-ray detected AGN. Observations of dual SMBH binaries in the subkiloparsec regime at the final stages of dynamical friction provide important constraints for future gravitational wave observatories
Deep learning-enhanced ensemble-based data assimilation for high-dimensional nonlinear dynamical systems
No full textData assimilation (DA) is a key component of many forecasting models in science and engineering. DA allows one to estimate better initial conditions using an imperfect dynamical model of the system and noisy/sparse observations available from the system. Ensemble Kalman filter (EnKF) is a DA algorithm that is widely used in applications involving high-dimensional nonlinear dynamical systems. However, EnKF requires evolving large ensembles of forecasts using the dynamical model of the system. This often becomes computationally intractable, especially when the number of states of the system is very large, e.g., for weather prediction. With small ensembles, the estimated background error covariance matrix in the EnKF algorithm suffers from sampling error, leading to an erroneous estimate of the analysis state (initial condition for the next forecast cycle). In this work, we propose hybrid ensemble Kalman filter (H-EnKF), which is applied to a two-layer quasi-geostrophic turbulent flow as a test case. This framework utilizes a pre-trained deep learning-based data-driven surrogate that inexpensively generates and evolves a large data-driven ensemble of the states to accurately compute the background error covariance matrix with smaller sampling errors. The H-EnKF framework outperforms EnKF with only dynamical model or only the data-driven surrogate, and estimates a better initial condition without the need for any ad-hoc localization strategies. H-EnKF can be extended to any ensemble-based DA algorithm, e.g., particle filters, which are currently too expensive to use for high-dimensional systems
Variational quantum one-class classifier
No full textOne-class classification (OCC) is a fundamental problem in pattern recognition with a wide range of applications. This work presents a semi-supervised quantum machine learning algorithm for such a problem, which we call a variational quantum one-class classifier (VQOCC). The algorithm is suitable for noisy intermediate-scale quantum computing because the VQOCC trains a fully-parameterized quantum autoencoder with a normal dataset and does not require decoding. The performance of the VQOCC is compared with that of the one-class support vector machine (OC-SVM), the kernel principal component analysis (PCA), and the deep convolutional autoencoder (DCAE) using handwritten digit and Fashion-MNIST datasets. The numerical experiment examined various structures of VQOCC by varying data encoding, the number of parameterized quantum circuit layers, and the size of the latent feature space. The benchmark shows that the classification performance of VQOCC is comparable to that of OC-SVM and PCA, although the number of model parameters grows only logarithmically with the data size. The quantum algorithm outperformed DCAE in most cases under similar training conditions. Therefore, our algorithm constitutes an extremely compact and effective machine learning model for OCC
Lineage tracing reveals fate bias and transcriptional memory in human B cells
No full textWe combined single-cell transcriptomics and lineage tracing to understand fate choice in human B cells. Using the antibody sequences of B cells, we tracked clones during in vitro differentiation. Clonal analysis revealed a subset of IgM+ B cells which were more proliferative than other B-cell types. Whereas the population of B cells adopted diverse states during differentiation, clones had a restricted set of fates available to them; there were two times more single-fate clones than expected given population-level cell-type diversity. This implicated a molecular memory of initial cell states that was propagated through differentiation. We then identified the genes which had strongest coherence within clones. These genes significantly overlapped known B-cell fate determination programs, suggesting the genes which determine cell identity are most robustly controlled on a clonal level. Persistent clonal identities were also observed in human plasma cells from bone marrow, indicating that these transcriptional programs maintain long-term cell identities in vivo. Thus, we show how cell-intrinsic fate bias influences differentiation outcomes in vitro and in vivo
Topological Defect Network Representations of Fracton Stabilizer Codes
No full textA topological defect network (TDN) is formed by a network of topological defects embedded within a topological quantum field theory (TQFT). TDNs were introduced recently for the purpose of describing fracton topological phases of matter using the framework of defect TQFT. Their effectiveness has been demonstrated through numerous examples, yet a systematic construction was lacking. Here we solve this problem by formulating a method to construct TDNs for a wide range of lattice Hamiltonians. Our method takes a lattice Hamiltonian as input, applies an ungauging procedure, then creates a refined lattice within each unit cell, followed by regauging the system to produce a TDN as output. For topological Calderbank-Shor-Steane (CSS) Pauli stabilizer models, this procedure is guaranteed to produce a phase-equivalent TDN. This provides TDN representations of canonical fracton models for which no such construction was previously known, including Haah’s cubic code and Yoshida’s infinite family of fractal spin liquid models. We demonstrate the applicability of our method beyond CSS stabilizer models by constructing TDNs for non-CSS models including Chamon’s model and the semionic X-cube model
Real-time monitoring of tumor-homing bacteria and tumor cells in vivo using ultrasound
No full textBy screening natural prokaryotic gas vesicle gene clusters, we found and engineered new acoustic reporter genes (ARGs) that give bacteria and mammalian cells brighter ultrasound contrast for real-time noninvasive imaging. Expressing these ARGs in engineered cells enabled us to image tumor-homing bacteria and perform genetically guided tumor biopsies in vivo
Parker Solar Probe Encounters the Leg of a Coronal Mass Ejection at 14 Solar Radii
No full textWe use Parker Solar Probe (PSP) observations to report the first direct measurements of the particle and field environments while crossing the leg of a coronal mass ejection (CME) very close to the Sun (∼14 Rs). An analysis that combines imaging from 1 au and PSP with a CME model, predicts an encounter time and duration that correspond to an unusual, complete dropout in low-energy solar energetic ions from H–Fe, observed by the Integrated Science Investigation of the Sun (IS⊙IS). The surrounding regions are populated with low-intensity protons and heavy ions from 10s to 100 keV, typical of some quiet times close in to the Sun. In contrast, the magnetic field and solar wind plasma show no similarly abrupt changes at the boundaries of the dropout. Together, the IS⊙IS energetic particle observations, combined with remote sensing of the CME and a dearth of other "typical" CME signatures, indicate that this CME leg is significantly different from the magnetic and plasma structure normally assumed for CMEs near the Sun and observed in interplanetary CMEs farther out in the solar wind. The dropout in low-energy energetic ions may be due to the cooling of suprathermal ions at the base of the CME leg flux tube, owing to the rapid outward expansion during the release of the CME