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We present an object-centric approach to empower robots to learn vision-based manipulation skills from human videos. We investigate the problem of imitating robot manipulation from a single human video in the open-world setting, where a robot must learn to manipulate novel objects from one video demonstration. We introduce ORION, an algorithm that tackles the problem by extracting an object-centric manipulation plan from a single RGB-D video and deriving a policy that conditions on the extracted plan. Our method enables the robot to learn from videos captured by daily mobile devices such as an iPad and generalize the policies to deployment environments with varying visual backgrounds, camera angles, spatial layouts, and novel object instances. We systematically evaluate our method on both short-horizon and long-horizon tasks, demonstrating the efficacy of ORION in learning from a single human video in the open world. Videos can be found in the project website https://ut-austin-rpl.github.io/ORION-release.

A codimension-two spiral spin-liquid is a correlated paramagnetic state with one-dimensional ground state degeneracy hosted within a three-dimensional lattice. Here, via neutron scattering experiments and numerical simulations, we establish the existence of a codimension-two spiral spin-liquid in the effective honeycomb-lattice compound Cs$_3$Fe$_2$Cl$_9$ and demonstrate the selective visibility of the spiral surface through phase tuning. In the long-range ordered regime, competing spiral and spin density wave orders emerge as a function of applied magnetic field, among which a possible order-by-disorder transition is identified., Comment: 21 pages, 23 figures

Galaxy number counts probe the evolution of galaxies over cosmic time, and serve as a valuable comparison point to theoretical models of galaxy formation. We present new galaxy number counts in eight photometric bands between 5 and 25 $\mu$m from the Systematic Mid-infrared Instrument Legacy Extragalactic Survey (SMILES) and the JWST Advanced Deep Extragalactic Survey (JADES) deep MIRI parallel, extending to unprecedented depth. By combining our new MIRI counts with existing data from Spitzer and AKARI, we achieve counts across 3-5 orders of magnitude in flux in all MIRI bands. Our counts diverge from predictions from recent semi-analytical models of galaxy formation, likely owing to their treatment of mid-infrared aromatic features. Finally, we integrate our combined JWST-Spitzer counts at 8 and 24 $\mu$m to measure the cosmic infrared background (CIB) light at these wavelengths; our measured CIB fluxes are consistent with those from previous mid-infrared surveys, but larger than predicted by some models based on TeV blazar data., Comment: 13 pages, 4 figures, 2 tables. Accepted to ApJ

Optically detected magnetic resonance (ODMR) has become a well-established and powerful technique for measuring the spin state of solid-state quantum emitters, at room temperature. Relying on spin-dependent recombination processes involving the emitters ground, excited and metastable states, ODMR is enabling spin-based quantum sensing of nanoscale electric and magnetic fields, temperature, strain and pressure, as well as imaging of individual electron and nuclear spins. Central to many of these sensing applications is the ability to reliably analyze ODMR data, as the resonance frequencies in these spectra map directly onto target physical quantities acting on the spin sensor. However, this can be onerous, as relatively long integration times -- from milliseconds up to tens of seconds -- are often needed to reach a signal-to-noise level suitable to determine said resonances using traditional fitting methods. Here, we present an algorithm based on data clustering that overcome this limitation and allows determining the resonance frequencies of ODMR spectra with better accuracy (~1.3x factor), higher resolution (~4.7x factor) and/or overall fewer data points (~5x factor) than standard approaches based on statistical inference. The proposed clustering algorithm (CA) is thus a powerful tool for many ODMR-based quantum sensing applications, especially when dealing with noisy and scarce data sets.

Advances in time domain astronomy have produced a growing population of flares from galactic nuclei, including both tidal disruption events (TDEs) and flares in active galactic nuclei (AGN). Because TDEs are uncommon and AGN variability is abundant, large-amplitude AGN flares are usually not categorized as TDEs. While TDEs are normally channelled by the collisional process of two-body scatterings over relaxation timescale, the quadrupole moment of a gas disk alters the stellar orbits, allowing them to collisionlessly approach the central massive black hole (MBH). This leads to an effectively enlarged loss cone, the \emph{loss wedge}. Earlier studies found a moderate enhancement, up to a factor $\sim 2-3$, of TDE rates $\dot{N}_{\rm 2b} $ for a static axisymmetric perturbation. Here we study the loss wedge problem for an evolving AGN disk, which can capture large number of stars into the growing loss wedge over much shorter times. The rates $\dot{N}_{\rm cl}$ of collisionless TDEs produced by these time-evolving disks are much higher than the collisional rates $\dot{N}_{\rm 2b}$ in a static loss wedge. We calculate the response of a stellar population to the axisymmetric potential of an adiabatically growing AGN disk and find that the highest rates of collisionless TDEs are achieved for the largest (i) MBH masses $M_{\bullet}$ and (ii) disk masses $M_{\rm d}$. For $M_{\bullet}\sim 10^7 M_\odot$ and $M_{\rm d} \sim 0.1 M_{\bullet}$, the rate enhancement can be up to a factor $\dot{N}_{\rm cl}/\dot{N}_{\rm 2b} \sim 10$. The orbits of collisionless TDEs sometimes have a preferred orientation in apses, carrying implications for observational signatures of resulting flares., Comment: Submitted to ApJ; 24 pages, 8 figures; comments are welcome

Imitation Learning (IL) strategies are used to generate policies for robot motion planning and navigation by learning from human trajectories. Recently, there has been a lot of excitement in applying IL in social interactions arising in urban environments such as university campuses, restaurants, grocery stores, and hospitals. However, obtaining numerous expert demonstrations in social settings might be expensive, risky, or even impossible. Current approaches therefore, focus only on simulated social interaction scenarios. This raises the question: \textit{How can a robot learn to imitate an expert demonstrator from real world multi-agent social interaction scenarios}? It remains unknown which, if any, IL methods perform well and what assumptions they require. We benchmark representative IL methods in real world social interaction scenarios on a motion planning task, using a novel pedestrian intersection dataset collected at the University of Texas at Austin campus. Our evaluation reveals two key findings: first, learning multi-agent cost functions is required for learning the diverse behavior modes of agents in tightly coupled interactions and second, conditioning the training of IL methods on partial state information or providing global information in simulation can improve imitation learning, especially in real world social interaction scenarios.

We present an event observed by Parker Solar Probe at $\sim$0.2 au on March 2, 2022 in which imaging and \emph{in situ} measurements coincide. During this event, PSP passed through structures on the flank of a streamer blowout CME including an isolated flux tube in front of the CME, a turbulent sheath, and the CME itself. Imaging observations and \emph{in situ} helicity and principal variance signatures consistently show the presence of flux ropes internal to the CME. In both the sheath, and the CME interval, the distributions are more isotropic, the spectra are softer, and the abundance ratios of Fe/O and He/H are lower than those in the isolated flux tube, and yet elevated relative to typical plasma and SEP abundances. These signatures in the sheath and the CME indicate that both flare populations and those from the plasma are accelerated to form the observed energetic particle enhancements. In contrast, the isolated flux tube shows large streaming, hard spectra and large Fe/O and He/H ratios, indicating flare sources. Energetic particle fluxes are most enhanced within the CME interval from suprathermal through energetic particle energies ($\sim$ keV to $>10$ MeV), indicating particle acceleration, and confinement local to the closed magnetic structure. The flux-rope morphology of the CME helps to enable local modulation and trapping of energetic particles, particularly along helicity channels and other plasma boundaries. Thus, the CME acts to build-up energetic particle populations, allowing them to be fed into subsequent higher energy particle acceleration throughout the inner heliosphere where a compression or shock forms on the CME front., Comment: 41 pages, 19 figures, In Press

The James Webb Space Telescope (JWST) is revolutionizing our view of the Universe through unprecedented sensitivity and resolution in the infrared, with some of the largest gains realized at its longest wavelengths. We present the Systematic Mid-infrared Instrument (MIRI) Legacy Extragalactic Survey (SMILES), an eight-band MIRI survey with Near-Infrared Spectrograph (NIRSpec) spectroscopic follow-up in the GOODS-S/HUDF region. SMILES takes full advantage of MIRI's continuous coverage from $5.6-25.5\,\mu$m over a $\sim34$ arcmin$^2$ area to greatly expand our understanding of the obscured Universe up to cosmic noon and beyond. This work, together with a companion paper by Rieke et al., covers the SMILES science drivers and technical design, early results with SMILES, data reduction, photometric catalog creation, and the first data release. As part of the discussion on early results, we additionally present a high-level science demonstration on how MIRI's wavelength coverage and resolution will advance our understanding of cosmic dust using the full range of polycyclic aromatic hydrocarbon (PAH) emission features from $3.3-18\,\mu$m. Using custom background subtraction, we produce robust reductions of the MIRI imaging that maximize the depths reached with our modest exposure times ($\sim0.6 - 2.2$ ks per filter). Included in our initial data release are (1) eight MIRI imaging mosaics reaching depths of $0.2-18\,\mu$Jy ($5\sigma$) and (2) a $5-25.5\,\mu$m photometric catalog with over 3,000 sources. Building upon the rich legacy of extensive photometric and spectroscopy coverage of GOODS-S/HUDF from the X-ray to the radio, SMILES greatly expands our investigative power in understanding the obscured Universe., Comment: 23 pages, 19 figures, submitted to ApJ. Comments welcome! Data release will go live at https://archive.stsci.edu/hlsp/smiles in the next few weeks

This paper presents a search for high redshift galaxies from the Euclid Early Release Observations program "Magnifying Lens." The 1.5 deg$^2$ area covered by the twin Abell lensing cluster fields is comparable in size to the few other deep near-infrared surveys such as COSMOS, and so provides an opportunity to significantly increase known samples of rare UV-bright galaxies at $z\approx6-8$ ($M_{\rm UV}\lesssim-22$). Beyond their still uncertain role in reionisation, these UV-bright galaxies are ideal laboratories from which to study galaxy formation and constrain the bright-end of the UV luminosity function. Of the 501994 sources detected from a combined $Y_{\rm E}$, $J_{\rm E}$, and $H_{\rm E}$ NISP detection image, 168 do not have any appreciable VIS/$I_{\rm E}$ flux. These objects span a range in spectral colours, separated into two classes: 139 extremely red sources; and 29 Lyman-break galaxy candidates. Best-fit redshifts and spectral templates suggest the former is composed of both $z\gtrsim5$ dusty star-forming galaxies and $z\approx1-3$ quiescent systems. The latter is composed of more homogeneous Lyman break galaxies at $z\approx6-8$. In both cases, contamination by L- and T-type dwarfs cannot be ruled out with Euclid images alone. Additional contamination from instrumental persistence is investigated using a novel time series analysis. This work lays the foundation for future searches within the Euclid Deep Fields, where thousands more $z\gtrsim6$ Lyman break systems and extremely red sources will be identified., Comment: 22 pages, 13 figures, paper submitted as part of the A&A special issue `Euclid on Sky', which contains Euclid key reference papers and first results from the Euclid Early Release Observations

We present the first analysis of the Euclid Early Release Observations (ERO) program that targets fields around two lensing clusters, Abell 2390 and Abell 2764. We use VIS and NISP imaging to produce photometric catalogs for a total of $\sim 500\,000$ objects. The imaging data reach a $5\,\sigma$ typical depth in the range 25.1-25.4 AB in the NISP bands, and 27.1-27.3 AB in the VIS band. Using the Lyman-break method in combination with photometric redshifts, we identify $30$ Lyman-break galaxy (LBG) candidates at $z>6$ and 139 extremely red sources (ERSs), most likely at lower redshift. The deeper VIS imaging compared to NISP means we can routinely identify high-redshift Lyman breaks of the order of $3$ magnitudes, which reduces contamination by brown dwarf stars and low-redshift galaxies. Spectroscopic follow-up campaigns of such bright sources will help constrain both the bright end of the ultraviolet galaxy luminosity function and the quasar luminosity function at $z>6$, and constrain the physical nature of these objects. Additionally, we have performed a combined strong lensing and weak lensing analysis of A2390, and demonstrate how Euclid will contribute to better constraining the virial mass of galaxy clusters. From these data, we also identify optical and near-infrared counterparts of known $z>0.6$ clusters, which exhibit strong lensing features, establishing the ability of Euclid to characterize high-redshift clusters. Finally, we provide a glimpse of Euclid's ability to map the intracluster light out to larger radii than current facilities, enabling a better understanding of the cluster assembly history and mapping of the dark matter distribution. This initial dataset illustrates the diverse spectrum of legacy science that will be enabled by the Euclid survey., Comment: Paper submitted as part of the A&A special issue `Euclid on Sky', which contains Euclid key reference papers and first results from the Euclid Early Release Observations. 17 pages, 12 figures

We study the intracluster light (ICL) and intracluster globular clusters (ICGCs) in the nearby Perseus galaxy cluster using Euclid's EROs. By modelling the isophotal and iso-density contours, we mapped the distributions and properties of the ICL and ICGCs out to radii of 200-600 kpc (up to ~1/3 of the virial radius) from the brightest cluster galaxy (BCG). We find that the central 500 kpc hosts 70000$\pm$2800 GCs and $1.7\times10^{12}$ L$_\odot$ of diffuse light from the BCG+ICL in the near-infrared H$_E$. This accounts for 38$\pm$6% of the cluster's total stellar luminosity within this radius. The ICL and ICGCs share a coherent spatial distribution, suggesting a common origin or that a common potential governs their distribution. Their contours on the largest scales (>200 kpc) are offset from the BCG's core westwards by 60 kpc towards several luminous cluster galaxies. This offset is opposite to the displacement observed in the gaseous intracluster medium. The radial surface brightness profile of the BCG+ICL is best described by a double S\'ersic model, with 68$\pm$4% of the H$_E$ light in the extended, outer component. The transition between these components occurs at ~60 kpc, beyond which the isophotes become increasingly elliptical and off-centred. The radial ICGC number density profile closely follows the BCG+ICL profile only beyond this 60 kpc radius, where we find an average of 60-80 GCs per $10^9$ M$_\odot$ of diffuse stellar mass. The BCG+ICL colour becomes increasingly blue with radius, consistent with the stellar populations in the ICL having subsolar metallicities [Fe/H] ~ -0.6 to -1.0. The colour of the ICL, and the specific frequency and luminosity function of the ICGCs suggest that the ICL+ICGCs were tidally stripped from the outskirts of massive satellites with masses of a few $\times10^{10}$ M$_\odot$, with an increasing contribution from dwarf galaxies at large radii., Comment: Paper submitted as part of the A&A special issue `Euclid on Sky', which contains Euclid key reference papers and first results from the Euclid Early Release Observations. 27 pages, 21 figures, 5 tables. Accepted for publication in A&A

We make use of the unprecedented depth, spatial resolution, and field of view of the Euclid Early Release Observations of the Perseus galaxy cluster to detect and characterise the dwarf galaxy population in this massive system. The Euclid high resolution VIS and combined VIS+NIR colour images were visually inspected and dwarf galaxy candidates were identified. Their morphologies, the presence of nuclei, and their globular cluster (GC) richness were visually assessed, complementing an automatic detection of the GC candidates. Structural and photometric parameters, including Euclid filter colours, were extracted from 2-dimensional fitting. Based on this analysis, a total of 1100 dwarf candidates were found across the image, with 638 appearing to be new identifications. The majority (96%) are classified as dwarf ellipticals, 53% are nucleated, 26% are GC-rich, and 6% show disturbed morphologies. A relatively high fraction of galaxies, 8%, are categorised as ultra-diffuse galaxies. The majority of the dwarfs follow the expected scaling relations. Globally, the GC specific frequency, S_N, of the Perseus dwarfs is intermediate between those measured in the Virgo and Coma clusters. While the dwarfs with the largest GC counts are found throughout the Euclid field of view, those located around the east-west strip, where most of the brightest cluster members are found, exhibit larger S_N values, on average. The spatial distribution of the dwarfs, GCs, and intracluster light show a main iso-density/isophotal centre displaced to the west of the bright galaxy light distribution. The ERO imaging of the Perseus cluster demonstrates the unique capability of Euclid to concurrently detect and characterise large samples of dwarfs, their nuclei, and their GC systems, allowing us to construct a detailed picture of the formation and evolution of galaxies over a wide range of mass scales and environments., Comment: 44 pages, 24 figures, 5 tables, paper submitted to A&A as part of the A&A special issue `Euclid on Sky', which contains Euclid key reference papers and first results from the Euclid Early Release Observations

The Euclid ERO programme targeted the Perseus cluster of galaxies, gathering deep data in the central region of the cluster over 0.7 square degree, corresponding to approximately 0.25 r_200. The data set reaches a point-source depth of IE=28.0 (YE, JE, HE = 25.3) AB magnitudes at 5 sigma with a 0.16" and 0.48" FWHM, and a surface brightness limit of 30.1 (29.2) mag per square arcsec. The exceptional depth and spatial resolution of this wide-field multi-band data enable the simultaneous detection and characterisation of both bright and low surface brightness galaxies, along with their globular cluster systems, from the optical to the NIR. This study advances beyond previous analyses of the cluster and enables a range of scientific investigations summarised here. We derive the luminosity and stellar mass functions (LF and SMF) of the Perseus cluster in the Euclid IE band, thanks to supplementary u,g,r,i,z and Halpha data from the CFHT. We adopt a catalogue of 1100 dwarf galaxies, detailed in the corresponding ERO paper. We identify all other sources in the Euclid images and obtain accurate photometric measurements using AutoProf or AstroPhot for 138 bright cluster galaxies, and SourceExtractor for half a million compact sources. Cluster membership for the bright sample is determined by calculating photometric redshifts with Phosphoros. Our LF and SMF are the deepest recorded for the Perseus cluster, highlighting the groundbreaking capabilities of the Euclid telescope. Both the LF and SMF fit a Schechter plus Gaussian model. The LF features a dip at M(IE)=-19 and a faint-end slope of alpha_S = -1.2 to -1.3. The SMF displays a low-mass-end slope of alpha_S = -1.2 to -1.35. These observed slopes are flatter than those predicted for dark matter halos in cosmological simulations, offering significant insights for models of galaxy formation and evolution., Comment: Submitted to A&A, 44 pages, 35 figures, Part of the A&A special issue `Euclid on Sky', which contains Euclid key reference papers and first results from the Euclid Early Release Observations

We present an analysis of Euclid observations of a 0.5 deg$^2$ field in the central region of the Fornax galaxy cluster that were acquired during the performance verification phase. With these data, we investigate the potential of Euclid for identifying GCs at 20 Mpc, and validate the search methods using artificial GCs and known GCs within the field from the literature. Our analysis of artificial GCs injected into the data shows that Euclid's data in $I_{\rm E}$ band is 80% complete at about $I_{\rm E} \sim 26.0$ mag ($M_{V\rm } \sim -5.0$ mag), and resolves GCs as small as $r_{\rm h} = 2.5$ pc. In the $I_{\rm E}$ band, we detect more than 95% of the known GCs from previous spectroscopic surveys and GC candidates of the ACS Fornax Cluster Survey, of which more than 80% are resolved. We identify more than 5000 new GC candidates within the field of view down to $I_{\rm E}$ mag, about 1.5 mag fainter than the typical GC luminosity function turn-over magnitude, and investigate their spatial distribution within the intracluster field. We then focus on the GC candidates around dwarf galaxies and investigate their numbers, stacked luminosity distribution and stacked radial distribution. While the overall GC properties are consistent with those in the literature, an interesting over-representation of relatively bright candidates is found within a small number of relatively GC-rich dwarf galaxies. Our work confirms the capabilities of Euclid data in detecting GCs and separating them from foreground and background contaminants at a distance of 20 Mpc, particularly for low-GC count systems such as dwarf galaxies., Comment: Paper submitted as part of the A&A special issue `Euclid on Sky', which contains Euclid key reference papers and first results from the Euclid Early Release Observations

Euclid is poised to make significant advances in the study of nearby galaxies in the local Universe. Here we present a first look at 6 galaxies observed for the Nearby Galaxy Showcase as part of the Euclid Early Release Observations acquired between August and November, 2023. These targets, 3 dwarf galaxies (HolmbergII, IC10, NGC6822) and 3 spirals (IC342, NGC2403, NGC6744), range in distance from about 0.5 Mpc to 8.8 Mpc. Our assessment of the surface brightness depths in the stacked Euclid images confirms previous estimates in 100 arcsec^2 regions of 1sigma=30.5 mag/arcsec^2 for VIS, but slightly deeper than previous estimates for NISP with 1sigma=29.2-29.4 mag/arcsec^2. By combining Euclid HE, YE, and IE into RGB images, we illustrate the large field-of-view covered by a single Reference Observing Sequence, together with exquisite detail on parsec scales in these nearby galaxies. Radial surface brightness and color profiles demonstrate galaxy colors in agreement with stellar population synthesis models. Standard stellar photometry selection techniques find approximately 1.3 million stars across the 6 galaxy fields. Euclid's resolved stellar photometry allows us to constrain the star-formation histories of these galaxies, by disentangling the distributions of young stars, as well as asymptotic giant branch and red giant branch stellar populations. We finally examine 2 galaxies individually for surrounding satellite systems. Our analysis of the ensemble of dwarf satellites around NGC6744 reveals a new galaxy, EDwC1, a nucleated dwarf spheroidal at the end of a spiral arm. Our new census of the globular clusters around NGC2403 yields 9 new star-cluster candidates, 8 of which with colors indicative of evolved stellar populations. In summary, our investigation of the 6 Showcase galaxies demonstrates that Euclid is a powerful probe of the anatomy of nearby galaxies [abridged]., Comment: 36 pages; 20 figures in main text; 4 Appendices. Submitted to A&A, as part of the A&A special issue `Euclid on Sky', which contains Euclid key reference papers and first results from the Euclid Early Release Observations

The Euclid ERO showcase Euclid's capabilities in advance of its main mission, targeting 17 astronomical objects, from galaxy clusters, nearby galaxies, globular clusters, to star-forming regions. A total of 24 hours observing time was allocated in the early months of operation, engaging the scientific community through an early public data release. We describe the development of the ERO pipeline to create visually compelling images while simultaneously meeting the scientific demands within months of launch, leveraging a pragmatic, data-driven development strategy. The pipeline's key requirements are to preserve the image quality and to provide flux calibration and photometry for compact and extended sources. The pipeline's five pillars are: removal of instrumental signatures; astrometric calibration; photometric calibration; image stacking; and the production of science-ready catalogues for both the VIS and NISP instruments. We report a PSF with a full width at half maximum of 0.16" in the optical and 0.49" in the three NIR bands. Our VIS mean absolute flux calibration is accurate to about 1%, and 10% for NISP due to a limited calibration set; both instruments have considerable colour terms. The median depth is 25.3 and 23.2 AB mag with a SNR of 10 for galaxies, and 27.1 and 24.5 AB mag at an SNR of 5 for point sources for VIS and NISP, respectively. Euclid's ability to observe diffuse emission is exceptional due to its extended PSF nearly matching a pure diffraction halo, the best ever achieved by a wide-field, high-resolution imaging telescope. Euclid offers unparalleled capabilities for exploring the LSB Universe across all scales, also opening a new observational window in the NIR. Median surface-brightness levels of 29.9 and 28.3 AB mag per square arcsec are achieved for VIS and NISP, respectively, for detecting a 10 arcsec x 10 arcsec extended feature at the 1 sigma level., Comment: Submitted to A&A, 44 pages, 36 figures - Part of the A&A special issue `Euclid on Sky', which contains Euclid key reference papers and first results from the Euclid Early Release Observations

The current standard model of cosmology successfully describes a variety of measurements, but the nature of its main ingredients, dark matter and dark energy, remains unknown. Euclid is a medium-class mission in the Cosmic Vision 2015-2025 programme of the European Space Agency (ESA) that will provide high-resolution optical imaging, as well as near-infrared imaging and spectroscopy, over about 14,000 deg^2 of extragalactic sky. In addition to accurate weak lensing and clustering measurements that probe structure formation over half of the age of the Universe, its primary probes for cosmology, these exquisite data will enable a wide range of science. This paper provides a high-level overview of the mission, summarising the survey characteristics, the various data-processing steps, and data products. We also highlight the main science objectives and expected performance., Comment: Accepted for publication in the A&A special issue`Euclid on Sky'

Point cloud analysis has a wide range of applications in many areas such as computer vision, robotic manipulation, and autonomous driving. While deep learning has achieved remarkable success on image-based tasks, there are many unique challenges faced by deep neural networks in processing massive, unordered, irregular and noisy 3D points. To stimulate future research, this paper analyzes recent progress in deep learning methods employed for point cloud processing and presents challenges and potential directions to advance this field. It serves as a comprehensive review on two major tasks in 3D point cloud processing-- namely, 3D shape classification and semantic segmentation., Comment: Published in Springer Nature (Machine Vision and Applications)

The time variability and spectra of directly imaged companions provide insight into their physical properties and atmospheric dynamics. We present follow-up R~40 spectrophotometric monitoring of red companion HD 1160 B at 2.8-4.2 $\mu$m using the double-grating 360{\deg} vector Apodizing Phase Plate (dgvAPP360) coronagraph and ALES integral field spectrograph on the Large Binocular Telescope Interferometer. We use the recently developed technique of gvAPP-enabled differential spectrophotometry to produce differential light curves for HD 1160 B. We reproduce the previously reported ~3.2 h periodic variability in archival data, but detect no periodic variability in new observations taken the following night with a similar 3.5% level precision, suggesting rapid evolution in the variability of HD 1160 B. We also extract complementary spectra of HD 1160 B for each night. The two are mostly consistent, but the companion appears fainter on the second night between 3.0-3.2 $\mu$m. Fitting models to these spectra produces different values for physical properties depending on the night considered. We find an effective temperature T$_{\text{eff}}$ = 2794$^{+115}_{-133}$ K on the first night, consistent with the literature, but a cooler T$_{\text{eff}}$ = 2279$^{+79}_{-157}$ K on the next. We estimate the mass of HD 1160 B to be 16-81 M$_{\text{Jup}}$, depending on its age. We also present R = 50,000 high-resolution optical spectroscopy of host star HD 1160 A obtained simultaneously with the PEPSI spectrograph. We reclassify its spectral type to A1 IV-V and measure its projected rotational velocity v sin i = 96$^{+6}_{-4}$ km s$^{-1}$. We thus highlight that gvAPP-enabled differential spectrophotometry can achieve repeatable few percent level precision and does not yet reach a systematic noise floor, suggesting greater precision is achievable with additional data or advanced detrending techniques., Comment: 22 pages, 12 figures, published in MNRAS; typos corrected, references updated

We present three-dimensional magnetohydrodynamic (MHD) simulations of the fueling of supermassive black holes in elliptical galaxies from a turbulent cooling medium on galactic scales, taking M87* as a typical case. We find that the mass accretion rate is increased by a factor of $\sim 10$ compared with analogous hydrodynamic simulations. The scaling of $\dot{M} \sim r^{1/2}$ roughly holds from $\sim 10\,\mathrm{pc}$ to $\sim 10^{-3}\,\mathrm{pc}$ ($\sim 10\, r_\mathrm{g}$) with the accretion rate through the event horizon being $\sim 10^{-2}\, M_\odot\,\mathrm{yr^{-1}}$. The accretion flow on scales $\sim 0.03-3\,\mathrm{kpc}$ takes the form of magnetized filaments. Within $\sim 30\,\mathrm{pc}$, the cold gas circularizes, forming a highly magnetized ($\beta\sim 10^{-3}$) thick disk supported by a primarily toroidal magnetic field. The cold disk is truncated and transitions to a turbulent hot accretion flow at $\sim0.3\,\mathrm{pc}$ ($10^3\,r_\mathrm{g}$). There are strong outflows towards the poles driven by the magnetic field. The outflow energy flux increases with smaller accretor size, reaching $\sim 3\times10^{43}\,\mathrm{erg\,s^{-1}}$ for $r_\mathrm{in}=8\,r_\mathrm{g}$; this corresponds to a nearly constant energy feedback efficiency of $\eta\sim0.05-0.1$ independent of accretor size. The feedback energy is enough to balance the total cooling of the M87/Virgo hot halo out to $\sim 50$ kpc. The accreted magnetic flux at small radii is similar to that in magnetically arrested disk models, consistent with the formation of a powerful jet on horizon scales in M87. Our results motivate a subgrid model for accretion in lower-resolution simulations in which the hot gas accretion rate is suppressed relative to the Bondi rate by $\sim (10r_\mathrm{g}/r_\mathrm{B})^{1/2}$., Comment: 23 pages, 14 figures, Accepted for publication in ApJ

We report the results of an extensive set of simulations exploring the sensitivity of the BlackCAT CubeSat to long-duration gamma-ray bursts (GRBs). BlackCAT is a NASA APRA-funded CubeSat mission for the detection and real-time sub-arcminute localization of high-redshift ($z\gtrsim 3.5$) GRBs. Thanks to their luminous and long-lived afterglow emissions, GRBs are uniquely valuable probes of high-redshift star-forming galaxies and the intergalactic medium. In addition, each detected GRB with a known redshift serves to localize a region of high-redshift star formation in three dimensions, enabling deep follow-on searches for host galaxies and associated local and large-scale structures. We explore two distinct models for the GRB redshift distribution and luminosity function, both consistent with Swift observations. We find that, for either model, BlackCAT is expected to detect a mean of 42 bursts per year on-orbit, with 6.7% to 10% of these at $z>3.5$. BlackCAT bursts will be localized to $r_{90} \lesssim 55^{\prime\prime}$ precision and reported to the community within seconds. Due to the mission orbit and pointing scheme, bursts will be located in the night sky and well-placed for deep multiwavelength follow-up observations. BlackCAT is on schedule to achieve launch readiness in 2025., Comment: 10 pages, 4 figures, 3 tables; Published in ApJ

Using the framework of semi-classical Landau-Lifshitz dynamics (LLD), we conduct a systematic investigation of the temperature-dependent spin dynamics in the S = 1/2 Heisenberg square-lattice antiferromagnet (SqAF). By performing inelastic neutron scattering measurements on Zn2VO(PO4)2 (ZVPO) and corresponding finite-temperature spin dynamics simulations based on LLD, we present a comprehensive analysis that bridges quantum and classical spin dynamics over a broad temperature range. First, a remarkable agreement between experimental data and LLD simulations is found in the paramagnetic phase of ZVPO, demonstrating the capability of LLD in accurately determining the spin Hamiltonian of S = 1/2 systems and capturing the quantum-to-classical crossover of their spin dynamics. Second, by analyzing the discrepancies between the experimental data and the LLD simulations at lower temperatures, we determine the experimental temperature dependence of the quantum effects in the excitation spectrum of the S = 1/2 SqAF: the quantum renormalization factor for the magnon energies and the quantum continuum above the one-magnon bands. Notably, the emergence of each quantum effect is found to correlate with the formation of three-dimensional long-range order. This work demonstrates the utility of LLD in gaining experimental insights into the temperature-induced modifications of quantum spin dynamics and their convergence towards classical expectations at higher temperatures. This motivates further applications to more challenging quantum antiferromagnets dominated by stronger quantum fluctuations., Comment: 8 pages, 4 figures, Supplemental Material can be found on the journal's website

A tidal disruption event (TDE) may occur when a star is torn apart by the tidal force of a black hole (BH). Eventually, an accretion disc is thought to form out of stellar debris falling back towards the BH. If the star's orbital angular momentum vector prior to disruption is not aligned with the BH spin angular momentum vector, the disc will be tilted with respect to the BH equatorial plane. The disc will eventually be drawn into the BH equatorial plane due to a combination of the Bardeen-Petterson effect and internal torques. Here, we analyse the X-ray and UV observations of the TDE AT2020ocn obtained by Swift, XMM-Newton, and NICER. The X-ray light curve shows strong flares during the first $\approx100$ days, while, over the same period, the UV emission decays gradually. We find that the X-ray flares can be explained by a model that also explains the spectral evolution. This model includes a slim disc viewed under a variable inclination plus an inverse-Comptonisation component processing the slim disc emission. A scenario where the ongoing Lense-Thirring precession during the disc alignment process is responsible for the observed inclination variations is consistent with the data. In later observations, we find that the X-ray spectrum of AT2020ocn becomes harder, while the mass accretion rate remains at super-Eddington levels, suggesting the formation of a corona in line with accretion onto other compact objects. We constrain the BH mass to be $(7^{+13}_{-3})\times10^{5}$ M$_\odot$ at the 1$\sigma$ (68%) confidence level., Comment: 14 pages, 8 figures, 5 tables, with supplementary materials. Accepted for publication in ApJ

Background Advancements in Large Language Models (LLMs) hold transformative potential in healthcare, however, recent work has raised concern about the tendency of these models to produce outputs that display racial or gender biases. Although training data is a likely source of such biases, exploration of disease and demographic associations in text data at scale has been limited. Methods We conducted a large-scale textual analysis using a dataset comprising diverse web sources, including Arxiv, Wikipedia, and Common Crawl. The study analyzed the context in which various diseases are discussed alongside markers of race and gender. Given that LLMs are pre-trained on similar datasets, this approach allowed us to examine the potential biases that LLMs may learn and internalize. We compared these findings with actual demographic disease prevalence as well as GPT-4 outputs in order to evaluate the extent of bias representation. Results Our findings indicate that demographic terms are disproportionately associated with specific disease concepts in online texts. gender terms are prominently associated with disease concepts, while racial terms are much less frequently associated. We find widespread disparities in the associations of specific racial and gender terms with the 18 diseases analyzed. Most prominently, we see an overall significant overrepresentation of Black race mentions in comparison to population proportions. Conclusions Our results highlight the need for critical examination and transparent reporting of biases in LLM pretraining datasets. Our study suggests the need to develop mitigation strategies to counteract the influence of biased training data in LLMs, particularly in sensitive domains such as healthcare.

Self-centred regular graphs which are Ollivier-Ricci Bonnet-Myers sharp have been completely classified. When the conditions of self-centeredness and regularity are removed it is an open problem on what the classification is. We present a complete classification of Bonnet-Myers sharp graphs with a diameter 2 and show that there exists Bonnet-Myers sharp graphs of diameter 3, 4 and 6 that belong to a family of graphs called symmetrical antitees.

Reinforcement learning (RL) presents a promising framework to learn policies through environment interaction, but often requires an infeasible amount of interaction data to solve complex tasks from sparse rewards. One direction includes augmenting RL with offline data demonstrating desired tasks, but past work often require a lot of high-quality demonstration data that is difficult to obtain, especially for domains such as robotics. Our approach consists of a reverse curriculum followed by a forward curriculum. Unique to our approach compared to past work is the ability to efficiently leverage more than one demonstration via a per-demonstration reverse curriculum generated via state resets. The result of our reverse curriculum is an initial policy that performs well on a narrow initial state distribution and helps overcome difficult exploration problems. A forward curriculum is then used to accelerate the training of the initial policy to perform well on the full initial state distribution of the task and improve demonstration and sample efficiency. We show how the combination of a reverse curriculum and forward curriculum in our method, RFCL, enables significant improvements in demonstration and sample efficiency compared against various state-of-the-art learning-from-demonstration baselines, even solving previously unsolvable tasks that require high precision and control., Comment: Accepted at The Twelfth International Conference on Learning Representations (ICLR 2024). Website: https://reverseforward-cl.github.io/

Reinforcement Learning is a promising tool for learning complex policies even in fast-moving and object-interactive domains where human teleoperation or hard-coded policies might fail. To effectively reflect this challenging category of tasks, we introduce a dynamic, interactive RL testbed based on robot air hockey. By augmenting air hockey with a large family of tasks ranging from easy tasks like reaching, to challenging ones like pushing a block by hitting it with a puck, as well as goal-based and human-interactive tasks, our testbed allows a varied assessment of RL capabilities. The robot air hockey testbed also supports sim-to-real transfer with three domains: two simulators of increasing fidelity and a real robot system. Using a dataset of demonstration data gathered through two teleoperation systems: a virtualized control environment, and human shadowing, we assess the testbed with behavior cloning, offline RL, and RL from scratch.

Vaccination campaigns have both direct and indirect effects that act to control an infectious disease as it spreads through a population. Indirect effects arise when vaccinated individuals block disease transmission in any infection chains they are part of, and this in turn can benefit both vaccinated and unvaccinated individuals. Indirect effects are difficult to quantify in practice, but here, working with the Susceptible-Infected-Recovered (SIR) model, they are analytically calculated in important cases, through pivoting on the Final Size formula for epidemics. Their relationship to herd immunity is also clarified. Furthermore, we identify the important distinction between quantifying indirect effects of vaccination at the "population level" versus the "per capita" individual level, which often results in radically different conclusions. As an important example, the analysis unpacks why population-level indirect effect can appear significantly larger than its per capita analogue. In addition, we consider a recently proposed epidemiological non-pharamaceutical intervention used over COVID-19, referred to as "shielding", and study its impact in our mathematical analysis. The shielding scheme is extended by inclusion of limited vaccination.

Integrated frequency combs promise transformation of lab-based metrology into disruptive real-world applications. These microcombs are, however, sensitive to stochastic thermal fluctuations of the integrated cavity refractive index, with its impact becoming more significant as the cavity size becomes smaller. This tradeoff between microcomb noise performance and footprint stands as a prominent obstacle to realizing applications beyond a controlled lab environment. Here, we demonstrate that small footprint and low noise become compatible through the all-optical Kerr-induced synchronization (KIS) method. Our study unveils that the phase-locking nature of the synchronization between the cavity soliton and the injected reference pump laser enables the microcomb to no longer be limited by internal noise sources. Instead, the microcomb noise is mostly limited by external sources, namely, the frequency noise of the two pumps that doubly pin the microcomb. First, we theoretically and experimentally show that the individual comb tooth linewidths of an octave-spanning microcomb remain within the same order-of-magnitude as the pump lasers, contrary to the single-pumped case that exhibits a more than two order-of-magnitude increase from the pump to the comb edge. Second, we theoretically show that intrinsic noise sources such as thermorefractive noise in KIS are quenched at the cavity decay rate, greatly decreasing its impact. Experimentally, we show that even with free-running lasers, the KIS microcomb can exhibit better repetition rate noise performance than the predicted thermorefractive noise limitation in absence of KIS.

The tidal disruption event (TDE) AT2018fyk has unusual X-ray, UV, and optical light curves that decay over the first $\sim$600d, rebrighten, and decay again around 1200d. We explain this behavior as a one-off TDE associated with a massive black hole (BH) \emph{binary}. The sharp drop-offs from $t^{-5/3}$ power laws at around 600d naturally arise when one BH interrupts the debris fallback onto the other BH. The BH mass $M_\bullet$ derived from fitting X-ray spectra with a slim disk accretion model and, independently, from fitting the early UV/optical light curves, is smaller by two orders of magnitude than predicted from the $M_\bullet$--$\sigma_*$ host galaxy relation, suggesting that the debris is accreted onto the secondary, with fallback cut off by the primary. Furthermore, if the rebrightening were associated with the primary, it should occur around 5000d, not the observed 1200d. The secondary's mass and dimensionless spin is $M_{\bullet,{\rm s}}=2.7^{+0.5}_{-1.5} \times 10^5 M_\odot$ and $a_{\bullet,{\rm s}}>0.3$ (X-ray spectral fitting), while the primary's mass is $M_{\bullet,{\rm p}}=10^{7.7\pm0.4}M_\odot$ ($M_\bullet$-$\sigma_*$ relation). An intermediate mass BH secondary is consistent with the observed UV/optical light curve decay, i.e., the secondary's outer accretion disk is too faint to produce a detectable emission floor. The time of the first accretion cutoff constrains the binary separation to be $(6.7\pm 1.2) \times 10^{-3}~{\rm pc}$. X-ray spectral fitting and timing analysis indicate that the hard X-rays arise from a corona above the secondary's disk. The early UV/optical emission, suggesting a super-Eddington phase for the secondary, possibly originates from shocks arising from debris circularization., Comment: 5 tables, 7 figures

In multi-agent reinforcement learning (MARL), coordination plays a crucial role in enhancing agents' performance beyond what they could achieve through cooperation alone. The interdependence of agents' actions, coupled with the need for communication, leads to a domain where effective coordination is crucial. In this paper, we introduce and define $\textit{Multi-Agent Synchronization Tasks}$ (MSTs), a novel subset of multi-agent tasks. We describe one MST, that we call $\textit{Synchronized Predator-Prey}$, offering a detailed description that will serve as the basis for evaluating a selection of recent state-of-the-art (SOTA) MARL algorithms explicitly designed to address coordination challenges through the use of communication strategies. Furthermore, we present empirical evidence that reveals the limitations of the algorithms assessed to solve MSTs, demonstrating their inability to scale effectively beyond 2-agent coordination tasks in scenarios where communication is a requisite component. Finally, the results raise questions about the applicability of recent SOTA approaches for complex coordination tasks (i.e. MSTs) and prompt further exploration into the underlying causes of their limitations in this context., Comment: Adaptive Learning Agents Workshop at AAMAS 2024

The Flory-Huggins theory describes the phase separation of solutions containing polymers. Although it finds widespread application from polymer physics to materials science to biology, the concentrations that coexist in separate phases at equilibrium have not been determined analytically, and numerical techniques are required that restrict the theory's ease of application. In this work, we derive an implicit analytical solution to the Flory-Huggins theory of one polymer in a solvent by applying a procedure that we call the implicit substitution method. While the solutions are implicit and in the form of composite variables, they can be mapped explicitly to a phase diagram in composition space. We apply the same formalism to multicomponent polymeric systems, where we find analytical solutions for polydisperse mixtures of polymers of one type. Finally, while complete analytical solutions are not possible for arbitrary mixtures, we propose computationally efficient strategies to map out coexistence curves for systems with many components of different polymer types.

Progress in machine learning and artificial intelligence has spurred the widespread adoption of automated decision systems (ADS). An extensive literature explores what conditions must be met for these systems' decisions to be fair. However, questions of legitimacy -- why those in control of ADS are entitled to make such decisions -- have received comparatively little attention. This paper shows that when such questions are raised theorists often incorrectly conflate legitimacy with either public acceptance or other substantive values such as fairness, accuracy, expertise or efficiency. In search of better theories, we conduct a critical analysis of the philosophical literature on the legitimacy of the state, focusing on consent, public reason, and democratic authorisation. This analysis reveals that the prevailing understanding of legitimacy in analytical political philosophy is also ill-suited to the task of establishing whether and when ADS are legitimate. The paper thus clarifies expectations for theories of ADS legitimacy and charts a path for a future research programme on the topic., Comment: Non-archival submission accepted to the ACM Conference on Fairness, Accountability, and Transparency 2024

The end of supernova remnant (SNR) evolution is characterized by a so-called "radiative" stage, in which efficient cooling of the hot bubble inside the forward shock slows expansion, leading to eventual shock breakup. Understanding SNR evolution at this stage is vital for predicting feedback in galaxies, since SNRs are expected to deposit their energy and momentum into the interstellar medium at the ends of their lives. A key prediction of SNR evolutionary models is the formation at the onset of the radiative stage of a cold, dense shell behind the forward shock. However, searches for these shells via their neutral hydrogen emission have had limited success. We instead introduce an independent observational signal of shell formation arising from the interaction between nonthermal particles accelerated by the SNR forward shock (cosmic rays) and the dense shell. Using a semi-analytic model of particle acceleration based on state-of-the-art simulations coupled with a high-resolution hydrodynamic model of SNR evolution, we predict the nonthermal emission that arises from this interaction. We demonstrate that the onset of the radiative stage leads to nonthermal signatures from radio to $\gamma$-rays, including radio and $\gamma$-ray brightening by nearly two orders of magnitude. Such a signature may be detectable with current instruments, and will be resolvable with the next generation of gamma-ray telescopes (namely, the Cherenkov Telescope Array)., Comment: 13 pages, 6 figures, accepted to ApJ

Nonlinear microresonators can convert light from chip-integrated sources into new wavelengths within the visible and near-infrared spectrum. For most applications, such as the interrogation of quantum systems with specific transition wavelengths, tuning the frequency of converted light is critical. Nonetheless, demonstrations of wavelength conversion have mostly overlooked this metric. Here, we apply efficient integrated heaters to tune the idler frequency produced by Kerr optical parametric oscillation in a silicon-nitride microring across a continuous 1.5 terahertz range. Finally, we suppress idler frequency noise between DC and 5 kHz by several orders of magnitude using feedback to the heater drive.

Crop biomass, a critical indicator of plant growth, health, and productivity, is invaluable for crop breeding programs and agronomic research. However, the accurate and scalable quantification of crop biomass remains inaccessible due to limitations in existing measurement methods. One of the obstacles impeding the advancement of current crop biomass prediction methodologies is the scarcity of publicly available datasets. Addressing this gap, we introduce a new dataset in this domain, i.e. Multi-modality dataset for crop biomass estimation (MMCBE). Comprising 216 sets of multi-view drone images, coupled with LiDAR point clouds, and hand-labelled ground truth, MMCBE represents the first multi-modality one in the field. This dataset aims to establish benchmark methods for crop biomass quantification and foster the development of vision-based approaches. We have rigorously evaluated state-of-the-art crop biomass estimation methods using MMCBE and ventured into additional potential applications, such as 3D crop reconstruction from drone imagery and novel-view rendering. With this publication, we are making our comprehensive dataset available to the broader community., Comment: 10 pages, 10 figures, 3 tables

Current approaches to learning cooperative multi-agent behaviors assume relatively restrictive settings. In standard fully cooperative multi-agent reinforcement learning, the learning algorithm controls $\textit{all}$ agents in the scenario, while in ad hoc teamwork, the learning algorithm usually assumes control over only a $\textit{single}$ agent in the scenario. However, many cooperative settings in the real world are much less restrictive. For example, in an autonomous driving scenario, a company might train its cars with the same learning algorithm, yet once on the road, these cars must cooperate with cars from another company. Towards expanding the class of scenarios that cooperative learning methods may optimally address, we introduce $N$-agent ad hoc teamwork (NAHT), where a set of autonomous agents must interact and cooperate with dynamically varying numbers and types of teammates. This paper formalizes the problem, and proposes the Policy Optimization with Agent Modelling (POAM) algorithm. POAM is a policy gradient, multi-agent reinforcement learning approach to the NAHT problem, that enables adaptation to diverse teammate behaviors by learning representations of teammate behaviors. Empirical evaluation on tasks from the multi-agent particle environment and StarCraft II shows that POAM improves cooperative task returns compared to baseline approaches, and enables out-of-distribution generalization to unseen teammates.

Two-body relaxation may drive stars onto near-radial orbits around a massive black hole, resulting in a tidal disruption event (TDE). In some circumstances, stars are unlikely to undergo a single terminal disruption, but rather to have a sequence of many grazing encounters with the black hole. It has long been unclear what is the physical outcome of this sequence: each of these encounters can only liberate a small amount of stellar mass, but may significantly alter the orbit of the star. We study the phenomenon of repeating partial tidal disruptions (pTDEs) by building a semi-analytical model that accounts for mass loss and tidal excitation. In the empty loss cone regime, where two-body relaxation is weak, we estimate the number of consecutive partial disruptions that a star can undergo, on average, before being significantly affected by two-body encounters. We find that in this empty loss cone regime, a star will be destroyed in a sequence of weak pTDEs, possibly explaining the tension between the low observed TDE rate and its higher theoretical estimates., Comment: Open Journal of Astrophysics, accepted for publication

Advances in artificial intelligence (AI) will transform many aspects of our lives and society, bringing immense opportunities but also posing significant risks and challenges. The next several decades may well be a turning point for humanity, comparable to the industrial revolution. We write to share a set of recommendations for moving forward from the perspective of the founder and leaders of the One Hundred Year Study on AI. Launched a decade ago, the project is committed to a perpetual series of studies by multidisciplinary experts to evaluate the immediate, longer-term, and far-reaching effects of AI on people and society, and to make recommendations about AI research, policy, and practice. As we witness new capabilities emerging from neural models, it is crucial that we engage in efforts to advance our scientific understanding of these models and their behaviors. We must address the impact of AI on people and society through technical, social, and sociotechnical lenses, incorporating insights from a diverse range of experts including voices from engineering, social, behavioral, and economic disciplines. By fostering dialogue, collaboration, and action among various stakeholders, we can strategically guide the development and deployment of AI in ways that maximize its potential for contributing to human flourishing. Despite the growing divide in the field between focusing on short-term versus long-term implications, we think both are of critical importance. As Alan Turing, one of the pioneers of AI, wrote in 1950, "We can only see a short distance ahead, but we can see plenty there that needs to be done." We offer ten recommendations for action that collectively address both the short- and long-term potential impacts of AI technologies., Comment: Four pages. To appear in Communications of the Association for Computing Machinery (CACM), June 2024

As Artificial Intelligence (AI) making advancements in medical decision-making, there is a growing need to ensure doctors develop appropriate reliance on AI to avoid adverse outcomes. However, existing methods in enabling appropriate AI reliance might encounter challenges while being applied in the medical domain. With this regard, this work employs and provides the validation of an alternative approach -- majority voting -- to facilitate appropriate reliance on AI in medical decision-making. This is achieved by a multi-institutional user study involving 32 medical professionals with various backgrounds, focusing on the pathology task of visually detecting a pattern, mitoses, in tumor images. Here, the majority voting process was conducted by synthesizing decisions under AI assistance from a group of pathology doctors (pathologists). Two metrics were used to evaluate the appropriateness of AI reliance: Relative AI Reliance (RAIR) and Relative Self-Reliance (RSR). Results showed that even with groups of three pathologists, majority-voted decisions significantly increased both RAIR and RSR -- by approximately 9% and 31%, respectively -- compared to decisions made by one pathologist collaborating with AI. This increased appropriateness resulted in better precision and recall in the detection of mitoses. While our study is centered on pathology, we believe these insights can be extended to general high-stakes decision-making processes involving similar visual tasks., Comment: 46 pages, 11 figures. Accepted International Journal of Human-Computer Studies

We report field-dependent high-resolution inelastic neutron scattering (INS) measurements on the honeycomb lattice magnet, CoTiO$_3$, to study the evolution of its magnon excitations across a spin reorientation transition driven by an in-plane magnetic field. By carrying out elastic neutron scattering in a magnetic field, we show that the sample transitions from a collinear antiferromagnetic state with multiple magnetic domains at a low field to a mono-domain state with a canted magnetic structure at a high field. Concurrent with this transition, we observed significant changes in both the energy and the width of the zone center magnon peak. The observed width change is argued to be consistent with an unusual zero-field state with extended domain walls. On the other hand, the magnon spectra near the $\mathbf{K}$ point of the Brillouin zone boundary are found to be largely insensitive to the changes in the ordered moment directions and the domain configuration. We argue that this observation is difficult to explain within the framework of the bond-dependent model proposed in a recent INS study [Elliot \textit{et\,al}, Nat. Commun., \textbf{12}, 3936 (2021)]. Our study therefore calls for alternative explanations for the observed $\mathbf{K}$-point gap in CoTiO$_3$., Comment: 15 pages, 9 figures, Supplemental Materials available upon request