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Human image datasets used to develop and evaluate technology should represent the diversity of human phenotypes, including skin tone. Datasets that include skin tone information frequently rely on manual skin tone ratings based on the Fitzpatrick Skin Type (FST) or the Monk Skin Tone (MST) scales in lieu of the actual measured skin tone of the image dataset subjects. However, perceived skin tone is subject to known biases and skin tone appearance in digital images can vary substantially depending on the capture camera and environment, confounding manual ratings. Surprisingly, the relationship between skin-tone ratings and measured skin tone has not been explored. To close this research gap, we measured the relationship between skin tone ratings from existing scales (FST, MST) and skin tone values measured by a calibrated colorimeter. We also propose and assess a novel Colorimetric Skin Tone (CST) scale developed based on prior colorimetric measurements. Using experiments requiring humans to rate their own skin tone and the skin tone of subjects in images, we show that the new CST scale is more sensitive, consistent, and colorimetrically accurate. While skin tone ratings appeared to correct for some color variation across images, they introduced biases related to race and other factors. These biases must be considered before using manual skin-tone ratings in technology evaluations or for engineering decisions.

Large neutrino liquid argon time projection chamber (LArTPC) experiments can broaden their physics reach by reconstructing and interpreting MeV-scale energy depositions, or blips, present in their data. We demonstrate new calorimetric and particle discrimination capabilities at the MeV energy scale using reconstructed blips in data from the MicroBooNE LArTPC at Fermilab. We observe a concentration of low energy ($<$3 MeV) blips around fiberglass mechanical support struts along the TPC edges with energy spectrum features consistent with the Compton edge of 2.614 MeV $^{208}$Tl decay $\gamma$ rays. These features are used to verify proper calibration of electron energy scales in MicroBooNE's data to few percent precision and to measure the specific activity of $^{208}$Tl in the fiberglass composing these struts, $(11.7 \pm 0.2 ~\text{(stat)} \pm 2.8~\text{(syst)})$ Bq/kg. Cosmogenically-produced blips above 3 MeV in reconstructed energy are used to showcase the ability of large LArTPCs to distinguish between low-energy proton and electron energy depositions. An enriched sample of low-energy protons selected using this new particle discrimination technique is found to be smaller in data than in dedicated CORSIKA cosmic ray simulations, suggesting either incorrect CORSIKA modeling of incident cosmic fluxes or particle transport modeling issues in Geant4., Comment: 19 pages, 15 figures total including the supplementary material section

The theory of swarm control shows promise for controlling multiple objects, however, scalability is hindered by cost constraints, such as hardware and infrastructure. Virtual Reality (VR) can overcome these limitations, but research on swarm interaction in VR is limited. This paper introduces a novel Swarm Manipulation interaction technique and compares it with two baseline techniques: Virtual Hand and Controller (ray-casting). We evaluated these techniques in a user study ($N$ = 12) in three tasks (selection, rotation, and resizing) across five conditions. Our results indicate that Swarm Manipulation yielded superior performance, with significantly faster speeds in most conditions across the three tasks. It notably reduced resizing size deviations but introduced a trade-off between speed and accuracy in the rotation task. Additionally, we conducted a follow-up user study ($N$ = 6) using Swarm Manipulation in two complex VR scenarios and obtained insights through semi-structured interviews, shedding light on optimized swarm control mechanisms and perceptual changes induced by this interaction paradigm. These results demonstrate the potential of the Swarm Manipulation technique to enhance the usability and user experience in VR compared to conventional manipulation techniques. In future studies, we aim to understand and improve swarm interaction via internal swarm particle cooperation., Comment: 15 pages, accepted at Computers & Graphics

Two-dimensional (2D) materials have emerged as promising candidates for next-generation integrated single-photon emitters (SPEs). However, significant variability in the emission energies of 2D SPEs presents a major challenge in producing identical single photons from different SPEs, which may become crucial for various quantum applications including quantum information processing. Although various approaches to dynamically tuning the emission energies of 2D SPEs have been developed to address the issue, the practical solution to matching multiple individual SPEs in a single 2D flake is still scarce. In this work, we demonstrate a precise emission energy tuning of individual SPEs in a WSe2 monolayer. Our approach utilizes localized strain fields near individual SPEs, which we control independently by adjusting the physical volume of an SU-8-based stressor layer via focused laser annealing. This technique allows continuous emission energy tuning of up to 15 meV while maintaining the qualities of SPEs. Additionally, we showcase the precise spectral alignment of three distinct SPEs in a single WSe2 monolayer to the same wavelength. The tunability of 2D SPEs represents a solid step towards the on-chip integrated photonics with 2D materials for quantum technologies.

We investigate the electronic structure of high-density layers of Sb dopants in a silicon host, so-called Si:Sb $\delta$-layers. We show that, in spite of the known challenges in producing highly confined Sb $\delta$-layers, sufficient confinement is created such that the lowest conduction band states ($\Gamma$ states, studied in depth in other silicon $\delta$-layers), become occupied and can be observed using angle-resolved photoemission spectroscopy. The electronic structure of the Si:Sb $\delta$-layers closely resembles that of Si:P systems, where the observed conduction band is near-parabolic and slightly anisotropic in the $\mathbf{k}_\parallel$ plane. The observed $\Gamma$ state extends ~ 1 nm in the out-of-plane direction, which is slightly wider than the 1/3 monolayer thick dopant distribution. This is caused by a small segregation of the dopant layer, which is nevertheless minimal when comparing with earlier published attempts. Our results serve to demonstrate that Sb is still a feasible dopant alternative for use in the semiconductor $\delta$-layer platform, providing similar electronic functionality to Si:P systems. Additionally, it has the advantages of being less expensive, more controllable, safer to handle, and more compatible with industrial patterning techniques. Si:Sb is therefore a viable platform for emerging quantum device applications.

The composition of protoplanetary disks, and hence the initial conditions of planet formation, may be strongly influenced by the infall and thermal processing of material during the protostellar phase. Composition of dust and ice in protostellar envelopes, shaped by energetic processes driven by the protostar, serves as the fundamental building material for planets and complex organic molecules. As part of the JWST GO program, "Investigating Protostellar Accretion" (IPA), we observed an intermediate-mass protostar HOPS 370 (OMC2-FIR3) using NIRSpec/IFU and MIRI/MRS. This study presents the gas and ice phase chemical inventory revealed with the JWST in the spectral range of $\sim$2.9 to 28 $\mu$m and explores the spatial variation of volatile ice species in the protostellar envelope. We find evidence for thermal processing of ice species throughout the inner envelope. We present the first high-spatial resolution ($\sim 80$ au) maps of key volatile ice species H$_{2}$O, CO$_{2}$, $^{13}$CO$_2$, CO, and OCN$^-$, which reveal a highly structured and inhomogeneous density distribution of the protostellar envelope, with a deficiency of ice column density that coincides with the jet/outflow shocked knots. Further, we observe high relative crystallinity of H$_{2}$O ice around the shocked knot seen in the H$_2$ and OH wind/outflow, which can be explained by a lack of outer colder material in the envelope along the line of sight due to the irregular structure of the envelope. These observations show clear evidence of thermal processing of the ices in the inner envelope, close to the outflow cavity walls, heated by the luminous protostar., Comment: Submitted to ApJ. Main text:16 pages with 11 figures

This work presents the measurements of the cosmic muon charge ratio as a function of full azimuthal angle and momentum within the range of 0.8 to 3.0 GeV/c, using the mini-ICAL detector. The detector, comprising 10 layers of RPCs, has collected cosmic muon data since August 2018 till recent time, at an altitude of 160 m above sea level at the Inter-Institutional Center for High Energy Physics in Madurai, India $(9^\circ56'\,N, 78^\circ00'\,E)$. The muon charge identification is achieved through the use of a magnetic field of strength 1.4 T. The analysis shows that the cosmic muon charge ratio, $R_\mu = N_{\mu^+}/N_{\mu^-}$, ranges from 1.1 to 1.2 and has small dependency on the zenith angle. The charge ratio's dependence on momentum and azimuthal angle is thoroughly examined for a wide range of zenith angle upto $50^\circ$. These measurements are compared with the predictions from various combinations of different hadronic models in CORSIKA extensive air shower simulations., Comment: 19 pages, 15 figures

This paper presents an overview of the Burer-Monteiro method (BM), a technique that has been applied to solve robot perception problems to certifiable optimality in real-time. BM is often used to solve semidefinite programming relaxations, which can be used to perform global optimization for non-convex perception problems. Specifically, BM leverages the low-rank structure of typical semidefinite programs to dramatically reduce the computational cost of performing optimization. This paper discusses BM in certifiable perception, with three main objectives: (i) to consolidate information from the literature into a unified presentation, (ii) to elucidate the role of the linear independence constraint qualification (LICQ), a concept not yet well-covered in certifiable perception literature, and (iii) to share practical considerations that are discussed among practitioners but not thoroughly covered in the literature. Our general aim is to offer a practical primer for applying BM towards certifiable perception., Comment: Accepted to 2024 Robotics: Science and Systems (RSS) Safe Autonomy Workshop

Isolated, low-mass galaxies provide the opportunity to assess the impact of reionization on their star formation histories (SFHs) without the ambiguity of environmental processes associated with massive host galaxies. There are very few isolated, low-mass galaxies that are close enough to determine their SFHs from resolved star photometry reaching below the oldest main sequence turnoff. JWST has increased the volume for which this is possible, and here we report on JWST observations of the low-mass, isolated galaxy Leo P. From NIRCam imaging in F090W, F150W, and F277W, we derive a SFH which shows early star formation followed by a pause subsequent to the epoch of reionization which is then later followed by a re-ignition of star formation. This is very similar to the SFHs from previous studies of other dwarf galaxies in the ``transition zone'' between quenched very low-mass galaxies and the more massive galaxies which show no evidence of the impact of reionization on their SFHs; this pattern is rarely produced in simulations of SFHs. The lifetime SFH reveals that Leo P's stellar mass at the epoch of reionization was in the range that is normally associated with being totally quenched. The extended pause in star formation from z~5-1 has important implications for the contribution of low-mass galaxies to the UV photon budget at intermediate redshifts. We also demonstrate that, due to higher sensitivity and angular resolution, observing in two NIRCam short wavelength filters is superior to observing in a combination of a short and a long wavelength filter., Comment: 24 pages, 9 figures, 3 tables

We introduce SeaSplat, a method to enable real-time rendering of underwater scenes leveraging recent advances in 3D radiance fields. Underwater scenes are challenging visual environments, as rendering through a medium such as water introduces both range and color dependent effects on image capture. We constrain 3D Gaussian Splatting (3DGS), a recent advance in radiance fields enabling rapid training and real-time rendering of full 3D scenes, with a physically grounded underwater image formation model. Applying SeaSplat to the real-world scenes from SeaThru-NeRF dataset, a scene collected by an underwater vehicle in the US Virgin Islands, and simulation-degraded real-world scenes, not only do we see increased quantitative performance on rendering novel viewpoints from the scene with the medium present, but are also able to recover the underlying true color of the scene and restore renders to be without the presence of the intervening medium. We show that the underwater image formation helps learn scene structure, with better depth maps, as well as show that our improvements maintain the significant computational improvements afforded by leveraging a 3D Gaussian representation., Comment: Project page here: https://seasplat.github.io

Medical coding is essential for standardizing clinical data and communication but is often time-consuming and prone to errors. Traditional Natural Language Processing (NLP) methods struggle with automating coding due to the large label space, lengthy text inputs, and the absence of supporting evidence annotations that justify code selection. Recent advancements in Generative Artificial Intelligence (AI) offer promising solutions to these challenges. In this work, we introduce MedCodER, a Generative AI framework for automatic medical coding that leverages extraction, retrieval, and re-ranking techniques as core components. MedCodER achieves a micro-F1 score of 0.60 on International Classification of Diseases (ICD) code prediction, significantly outperforming state-of-the-art methods. Additionally, we present a new dataset containing medical records annotated with disease diagnoses, ICD codes, and supporting evidence texts (https://doi.org/10.5281/zenodo.13308316). Ablation tests confirm that MedCodER's performance depends on the integration of each of its aforementioned components, as performance declines when these components are evaluated in isolation.

Underwater object-level mapping requires incorporating visual foundation models to handle the uncommon and often previously unseen object classes encountered in marine scenarios. In this work, a metric of semantic uncertainty for open-set object detections produced by visual foundation models is calculated and then incorporated into an object-level uncertainty tracking framework. Object-level uncertainties and geometric relationships between objects are used to enable robust object-level loop closure detection for unknown object classes. The above loop closure detection problem is formulated as a graph-matching problem. While graph matching, in general, is NP-Complete, a solver for an equivalent formulation of the proposed graph matching problem as a graph editing problem is tested on multiple challenging underwater scenes. Results for this solver as well as three other solvers demonstrate that the proposed methods are feasible for real-time use in marine environments for the robust, open-set, multi-object, semantic-uncertainty-aware loop closure detection. Further experimental results on the KITTI dataset demonstrate that the method generalizes to large-scale terrestrial scenes.

The physical processes that produce X-ray Quasi-Periodic Eruptions (QPEs) recently discovered from the nuclei of several low-redshift galaxies are mysterious. Several pieces of observational evidence strongly suggest a link between QPEs and Tidal Disruption Events (TDE). Previous studies also reveal that the morphologies of TDE host galaxies are highly concentrated, with high Sersic indicies, bulge-to-total light (B/T) ratios, and stellar surface mass densities relative to the broader galaxy population. We use these distinctive properties to test the link between QPEs and TDEs, by comparing these parameters of QPE host galaxies to TDE host galaxies. We employ archival Legacy Survey images of a sample of 9 QPE host galaxies and a sample of 13 TDE host galaxies, and model their surface brightness profiles. We show that QPE host galaxies have high Sersic indices of ~3, high B/T ratios of ~0.5, and high surface mass densities of ~10^10 Msun kpc^-2. These properties are similar to TDE host galaxies, but are in strong contrast to a mass- and redshift-matched control sample of galaxies. We also find tentative evidence that the central black holes in both QPE and TDE host galaxies are undermassive relative to their stellar mass. The morphological similarities between QPE and TDE host galaxies at the population level add to the mounting evidence of a physical link between these phenomena, and favor QPE models that also invoke TDEs., Comment: 12 pages, 4 figures, submitted to ApJ

This study investigates the 5$f$-electron-conduction electron hybridization process in the heavy fermion superconductor UPd$_2$Al$_3$ using a combination of angle-resolved photoemission spectroscopy (ARPES) and time-resolved photoemission spectroscopy (tr-PES). ARPES measurements reveal the formation of a hybridization gap at a temperature of approximately 75 K, which becomes more pronounced as the temperature decreases. Notably, the persistence of a flat U 5$f$ band at temperatures well above the hybridization onset challenges conventional understanding. Our findings demonstrate a non-monotonic temperature dependence of the quasiparticle relaxation time, with an anomalous decrease at 20 K, suggesting complex electronic and magnetic interactions. These findings provide detailed insights into the 5$f$-electron hybridization process in UPd$_2$Al$_3$, with significant implications for the understanding of heavy fermion superconductivity and the role of 5$f$-electron hybridization in uranium-based materials., Comment: 5 pages, 4 figures

On-chip thermometry at deep-cryogenic temperatures is vital in quantum computing applications to accurately quantify the effect of increased temperature on qubit performance and to implement real-time thermal management on quantum processors. In this work, we present a sub-1K temperature sensor in CMOS technology based on the temperature dependence of the critical current of a superconducting (SC) thin-film. The sensor is implemented in 22-nm fully depleted silicon on insulator (FDSOI) technology and comprises a 6-nA-resolution current-output digital-to-analog converter (DAC), a transimpedance amplifier (TIA) with a SC thin-film as a gain element, and a voltage comparator. The circuit dissipates 1.5uW and is demonstrated operating at ambient temperatures as low as 15mK, providing a variable temperature resolution reaching sub-10mK., Comment: This work has been submitted to the IEEE for possible publication

We explore the effects of stress on silicon donor bound exciton ($\mathrm{D^0X}$) transitions in bulk silicon and in microfabricated silicon devices. We first study $\mathrm{D^0X}$ transitions in an isotopically purified silicon-28 bulk doped sample under controlled uniaxial stress, confirming the validity of existing models in the low strain ($\lesssim 10^{-5}$) regime. We then demonstrate the localised photoconductive detection of a few thousand donors illuminated by a 1078 nm resonant laser with $4~\mathrm{\mu m}$ spot focused on a microfabricated device consisting of an implanted phosphorus layer between a pair of metallic contacts. We observe local variations in the strained exciton peak splitting from $10~\mathrm{\mu eV}$ to $200~\mathrm{\mu eV}$, and obtain scanning microscopy stress maps in good agreement with finite-element-model thermal stress simulations. Our results suggest a potential use of donor bound excitons for in-situ stress sensing, and demonstrate pathways for the miniaturisation of $\mathrm{D^0X}$ photoconductive detection., Comment: 8 pages, 4 figures

Deep Metric Learning (DML) loss functions traditionally aim to control the forces of separability and compactness within an embedding space so that the same class data points are pulled together and different class ones are pushed apart. Within the context of DML, a softmax operation will typically normalize distances into a probability for optimization, thus coupling all the push/pull forces together. This paper proposes a potential new class of loss functions that operate within a euclidean domain and aim to take full advantage of the coupled forces governing embedding space formation under a softmax. These forces of compactness and separability can be boosted or mitigated within controlled locations at will by using a warping function. In this work, we provide a simple example of a warping function and use it to achieve competitive, state-of-the-art results on various metric learning benchmarks., Comment: Preprint

Solid-state defects susceptible of spin manipulation hold great promise for scalable quantum technology. To broaden their utility, operating at room temperature and emitting in the telecom wavelength range are desired, eliminating cryogenic requirements and leveraging existing optical fiber infrastructure for transmitting the quantum information. To that end, we report that telecom single photon emitters (SPEs) in gallium nitride (GaN) exhibit optically detected magnetic resonance (ODMR) at room temperature. The analysis of ODMR as a function of magnetic field orientation enables the determination of the orientation of the spin quantization axis with respect to the GaN crystalline lattice. The optical transitions dynamics are analyzed to gain further insight into the transition rates dominating ODMR. Our findings, coupled with GaN's mature fabrication technology, could facilitate the realization of scalable quantum technology.

Category-level object pose and shape estimation from a single depth image has recently drawn research attention due to its wide applications in robotics and self-driving. The task is particularly challenging because the three unknowns, object pose, object shape, and model-to-measurement correspondences, are compounded together but only a single view of depth measurements is provided. The vast majority of the prior work heavily relies on data-driven approaches to obtain solutions to at least one of the unknowns and typically two, running with the risk of failing to generalize to unseen domains. The shape representations used in the prior work also mainly focus on point cloud and signed distance field (SDF). In stark contrast to the prior work, we approach the problem using an iterative estimation method that does not require learning from any pose-annotated data. In addition, we adopt a novel mesh-based object active shape model that has not been explored by the previous literature. Our algorithm, named ShapeICP, has its foundation in the iterative closest point (ICP) algorithm but is equipped with additional features for the category-level pose and shape estimation task. The results show that even without using any pose-annotated data, ShapeICP surpasses many data-driven approaches that rely on the pose data for training, opening up new solution space for researchers to consider.

Although access to sufficient screen space is crucial to knowledge work, workers often find themselves with limited access to display infrastructure in remote or public settings. While virtual displays can be used to extend the available screen space through extended reality (XR) head-worn displays (HWD), we must better understand the implications of working with them in public settings from both users' and bystanders' viewpoints. To this end, we conducted two user studies. We first explored the usage of a hybrid AR display across real-world settings and tasks. We focused on how users take advantage of virtual displays and what social and environmental factors impact their usage of the system. A second study investigated the differences between working with a laptop, an AR system, or a VR system in public. We focused on a single location and participants performed a predefined task to enable direct comparisons between the conditions while also gathering data from bystanders. The combined results suggest a positive acceptance of XR technology in public settings and show that virtual displays can be used to accompany existing devices. We highlighted some environmental and social factors. We saw that previous XR experience and personality can influence how people perceive the use of XR in public. In addition, we confirmed that using XR in public still makes users stand out and that bystanders are curious about the devices, yet have no clear understanding of how they can be used., Comment: arXiv admin note: substantial text overlap with arXiv:2310.09786

Measurements of the obliquities in exoplanet systems have revealed some remarkable architectures, some of which are very different from the Solar System. Nearly 200 obliquity measurements have been obtained through observations of the Rossiter-McLaughlin (RM) effect. Here we report on observations of 19 planetary systems that led to 17 clear detections of the RM effect and 2 less secure detections. After adding the new measurements to the tally, we use the entire collection of RM measurements to investigate four issues that have arisen in the literature. i) Does the obliquity distribution show a peak at approximately 90$^\circ$? We find tentative evidence that such a peak does exist when restricting attention to the sample of sub-Saturn planets and hot Jupiters orbiting F stars. ii) Are high obliquities associated with high eccentricities? We find the association to be weaker than previously reported, and that a stronger association exists between obliquity and orbital separation, possibly due to tidal obliquity damping at small separations. iii) How low are the lowest known obliquities? Among hot Jupiters around cool stars, we find the dispersion to be $1.4\pm0.7^\circ$, smaller than the 6$^\circ$ obliquity of the Sun, which serves as additional evidence for tidal damping. iv) What are the obliquities of stars with compact and flat systems of multiple planets? We find that they generally have obliquities lower than $10^\circ$, with several remarkable exceptions possibly caused by wide-orbiting stellar or planetary companions., Comment: 47 pages, 43 figures. Accepted for publication in A&A

We report the measurement of the final-state products of negative pion and muon nuclear capture at rest on argon by the LArIAT experiment at the Fermilab Test Beam Facility. We measure a population of isolated MeV-scale energy depositions, or blips, in 296 LArIAT events containing tracks from stopping low-momentum pions and muons. The average numbers of visible blips are measured to be 0.74 $\pm$ 0.19 and 1.86 $\pm$ 0.17 near muon and pion track endpoints, respectively. The 3.6$\sigma$ statistically significant difference in blip content between muons and pions provides the first demonstration of a new method of pion-muon discrimination in neutrino liquid argon time projection chamber experiments. LArIAT Monte Carlo simulations predict substantially higher average blip counts for negative muon (1.22 $\pm$ 0.08) and pion (2.34 $\pm$ 0.09) nuclear captures. We attribute this difference to Geant4's inaccurate simulation of the nuclear capture process.

Leveraging the advanced manufacturing capabilities of the semiconductor industry promises to help scale up silicon-based quantum processors by increasing yield, uniformity and integration. Recent studies of quantum dots fabricated on 300 mm wafer metal-oxide-semiconductor (MOS) processes have shown control and readout of individual spin qubits, yet quantum processors require two-qubit interactions to operate. Here, we use a 300 mm wafer MOS process customized for spin qubits and demonstrate coherent control of two electron spins using the spin-spin exchange interaction, forming the basis of an entangling gate such as $\sqrt{\text{SWAP}}$. We observe gate dephasing times of up to $T_2^{*}\approx500$ ns and a gate quality factor of 10. We further extend the coherence by up to an order of magnitude using an echo sequence. For readout, we introduce a dispersive readout technique, the radiofrequency electron cascade, that amplifies the signal while retaining the spin-projective nature of dispersive measurements. Our results demonstrate an industrial grade platform for two-qubit operations, alongside integration with dispersive sensing techniques.

We present the results of the ALMA Large Program Early Planet Formation in Embedded disks observations of the Class 0 protostar GSS30 IRS3. Our observations included 1.3 mm continuum with a resolution of 0.''05 (7.8 au) and several molecular species including $^{12}$CO, $^{13}$CO, C$^{18}$O, H$_{2}$CO and c-C$_{3}$H$_{2}$. The dust continuum analysis unveiled a disk-shaped structure with a major axis size of $\sim$200 au. We observed an asymmetry in the minor axis of the continuum emission suggesting that the emission is optically thick and the disk is flared. On the other hand, we identified two prominent bumps along the major axis located at distances of 26 and 50 au from the central protostar. The origin of the bumps remains uncertain and might be due to an embedded substructure within the disk or the result of the temperature distribution instead of surface density due to optically thick continuum emission. The $^{12}$CO emission reveals a molecular outflow consisting of three distinct components: a collimated one, an intermediate velocity component exhibiting an hourglass shape, and a wider angle low-velocity component. We associate these components with the coexistence of a jet and a disk-wind. The C$^{18}$O emission traces both a Keplerian rotating circumstellar disk and the infall of the rotating envelope. We measured a stellar dynamical mass of 0.35$\pm$0.09 M$_{\odot}$., Comment: 25 pages, 19 figures. Accepted for publication in A&A

We present Atacama Large Millimeter/submillimeter Array (ALMA) observations of the binary Class 0 protostellar system BHR 71 IRS1 and IRS2 as part of the Early Planet Formation in Embedded Disks (eDisk) ALMA Large Program. We describe the $^{12}$CO ($J$=2--1), $^{13}$CO ($J$=2--1), C$^{18}$O ($J$=2--1), H$_2$CO ($J=3_{2,1}$--$2_{2,0}$), and SiO ($J$=5--4) molecular lines along with the 1.3 mm continuum at high spatial resolution ($\sim$0.08" or $\sim$5 au). Dust continuum emission is detected toward BHR 71 IRS1 and IRS2, with a central compact component and extended continuum emission. The compact components are smooth and show no sign of substructures such as spirals, rings or gaps. However, there is a brightness asymmetry along the minor axis of the presumed disk in IRS1, possibly indicative of an inclined geometrically and optically thick disk-like component. Using a position-velocity diagram analysis of the C$^{18}$O line, clear Keplerian motions were not detected toward either source. If Keplerian rotationally-supported disks are present, they are likely deeply embedded in their envelope. However, we can set upper limits of the central protostellar mass of 0.46 M$_\odot$ and 0.26 M$_\odot$ for BHR 71 IRS1 and BHR 71 IRS2, respectively. Outflows traced by $^{12}$CO and SiO are detected in both sources. The outflows can be divided into two components, a wide-angle outflow and a jet. In IRS1, the jet exhibits a double helical structure, reflecting the removal of angular momentum from the system. In IRS2, the jet is very collimated and shows a chain of knots, suggesting episodic accretion events., Comment: 38 pages, 29 figures, accepted in ApJ

Secure methods for identifying the host galaxies of individual massive black hole (MBH) binaries and mergers detected by gravitational wave experiments such as LISA and Pulsar Timing Arrays are currently lacking, but will be critical to a variety of science goals. Recently in Bardati et al. (2024, Paper I), we used the Romulus25 cosmological simulation to show that MBH merger host galaxies have unique morphologies in imaging, due to their stronger bulges. Here, we use the same sample of simulated MBH merger host galaxies to investigate their stellar kinematics, as probed by optical integral field unit (IFU) spectroscopy. We perform stellar population synthesis and dust radiative transfer to generate synthetic 3D optical spectral datacubes of each simulated galaxy, and produce mock stellar kinematic maps. Based on a linear discriminant analysis of a combination of kinematic parameters derived from these maps, we show that this approach can identify MBH binary and merger host galaxies with accuracies that increase with chirp mass and mass ratio. For mergers with high chirp masses (>10^8.2 Msun) and high mass ratios (>0.5), the accuracies reach >85%, and their host galaxies are uniquely characterized by slower rotation and stronger stellar kinematic misalignments. These kinematic properties are commonly associated with massive early-type galaxies that have experienced major mergers, and naturally act as signposts for MBH binaries and mergers with high chirp masses and mass ratios. These results suggest that IFU spectroscopy should also play a role in telescope follow-up of future MBH binaries and mergers detected in gravitational waves, Comment: 18 pages, 7 figures. Submitted to ApJ

Transit functions were introduced as models of betweenness on undirected structures. Here we introduce directed transit function as the directed analogue on directed structures such as posets and directed graphs. We first show that betweenness in posets can be expressed by means of a simple set of first order axioms. Similar characterizations can be obtained for graphs with natural partial orders, in particular, forests, trees, and mangroves. Relaxing the acyclicity conditions leads to a generalization of the well-known geometric transit function to the directed structures. Moreover, we discuss some properties of the directed analogues of prominent transit functions, including the all-paths, induced paths, and shortest paths (or interval) transit functions. Finally we point out some open questions and directions for future work.

Faced with a dangerous epidemic humans will spontaneously social distance to reduce their risk of infection at a socio-economic cost. Compartmentalised epidemic models have been extended to include this endogenous decision making: Individuals choose their behaviour to optimise a utility function, self-consistently giving rise to population behaviour. Here we study the properties of the resulting Nash equilibria, in which no member of the population can gain an advantage by unilaterally adopting different behaviour. We leverage a new analytic solution to obtain, (1) a simple relationship between rational social distancing behaviour and the current number of infections; (2) new scaling results for how the infection peak and number of total cases depend on the cost of contracting the disease; (3) characteristic infection costs that divide regimes of strong and weak behavioural response and depend only on the basic reproduction number of the disease; (4) a closed form expression for the value of the utility. We discuss how these analytic results provide a deep and intuitive understanding into the disease dynamics, useful for both individuals and policymakers. In particular the relationship between social distancing and infections represents a heuristic that could be communicated to the population to encourage, or "bootstrap", rational behaviour.

Accurately modeling the dynamics of high-density ratio ($\mathcal{O}(10^5)$) two-phase flows is important for many applications in material science and manufacturing. In this work, we consider numerical simulations of molten metal undergoing microgravity oscillations. Accurate simulation of the oscillation dynamics allows us to characterize the interplay between the two fluids' surface tension and density ratio, which is an important consideration for terrestrial manufacturing applications. We present a projection-based computational framework for solving a thermodynamically-consistent Cahn-Hilliard Navier-Stokes equations for two-phase flows under these large density ratios. A modified version of the pressure-decoupled solver based on the Helmholtz-Hodge decomposition presented in Khanwale et al. [{\it A projection-based, semi-implicit time-stepping approach for the Cahn-Hilliard Navier-Stokes equations on adaptive octree meshes.}, Journal of Computational Physics 475 (2023): 111874] is used. We validate our numerical method on several canonical problems including the method of manufactured solutions. We also present a comprehensive convergence study to investigate the effect of mesh resolution, time-step, and interfacial thickness on droplet-shape oscillations. We deploy our framework to predict the oscillation behavior of three physical systems exhibiting very large density ratios ($10^4-10^5:1$) that have previously never been performed.

We present ALMA Band 7 molecular line observations of the protostars within the VLA 1623 system. We map C$^{17}$O (3 - 2) in the circumbinary disk around VLA 1623A and the outflow cavity walls of the collimated outflow. We further detect red-shifted and blue-shifted velocity gradients in the circumstellar disks around VLA 1623B and VLA 1623W that are consistent with Keplerian rotation. We use the radiative transfer modeling code, pdspy, and simple flared disk models to measure stellar masses of $0.27 \pm 0.03$ M$_\odot$, $1.9^{+0.3}_{-0.2}$ M$_\odot$, and $0.64 \pm 0.06$ M$_\odot$ for the VLA 1623A binary, VLA 1623B, and VLA 1623W, respectively. These results represent the strongest constraints on stellar mass for both VLA 1623B and VLA 1623W, and the first measurement of mass for all stellar components using the same tracer and methodology. We use these masses to discuss the relationship between the young stellar objects (YSOs) in the VLA 1623 system. We find that VLA 1623W is unlikely to be an ejected YSO, as has been previously proposed. While we cannot rule out that VLA 1623W is a unrelated YSO, we propose that it is a true companion star to the VLA 1623A/B system and that the these stars formed in situ through turbulent fragmentation and have had only some dynamical interactions since their inception., Comment: Accepted to A&A; 16 pages, 12 figures

The front-end electronics of silicon detectors are typically designed to ensure optimal noise performance for the expected input charge. A combination of preamplifiers and shaper circuits result in a nontrivial response of the front-end to injected charge, and the magnitude of the response may be sizeable in readout windows subsequent to that in which the charge was initially injected. The modulation of the discriminator threshold due to the superposition of the front-end response across multiple readout windows is coined "threshold bounce". In this paper, we report a measurement of threshold bounce using silicon modules built for the Phase-II Upgrade of the ATLAS detector at the Large Hadron Collider. These modules utilize ATLAS Binary Chips for their hit readout. The measurement was performed using a micro-focused 15 keV photon beam at the Diamond Light Source synchrotron. The effect of the choice of photon flux and discriminator threshold on the magnitude of the threshold bounce is studied. A Monte Carlo simulation which accounts for the front-end behaviour of the silicon modules is developed, and its predicted hit efficiency is found to be in good agreement with the measured hit efficiency., Comment: 22 pages; accepted to JINST

A significant challenge in measurements of neutrino oscillations is reconstructing the incoming neutrino energies. While modern fully-active tracking calorimeters such as liquid argon time projection chambers in principle allow the measurement of all final state particles above some detection threshold, undetected neutrons remain a considerable source of missing energy with little to no data constraining their production rates and kinematics. We present the first demonstration of tagging neutrino-induced neutrons in liquid argon time projection chambers using secondary protons emitted from neutron-argon interactions in the MicroBooNE detector. We describe the method developed to identify neutrino-induced neutrons and demonstrate its performance using neutrons produced in muon-neutrino charged current interactions. The method is validated using a small subset of MicroBooNE's total dataset. The selection yields a sample with $60\%$ of selected tracks corresponding to neutron-induced secondary protons.

We develop new conformal inference methods for obtaining validity guarantees on the output of large language models (LLMs). Prior work in conformal language modeling identifies a subset of the text that satisfies a high-probability guarantee of correctness. These methods work by filtering claims from the LLM's original response if a scoring function evaluated on the claim fails to exceed a threshold calibrated via split conformal prediction. Existing methods in this area suffer from two deficiencies. First, the guarantee stated is not conditionally valid. The trustworthiness of the filtering step may vary based on the topic of the response. Second, because the scoring function is imperfect, the filtering step can remove many valuable and accurate claims. We address both of these challenges via two new conformal methods. First, we generalize the conditional conformal procedure of Gibbs et al. (2023) in order to adaptively issue weaker guarantees when they are required to preserve the utility of the output. Second, we show how to systematically improve the quality of the scoring function via a novel algorithm for differentiating through the conditional conformal procedure. We demonstrate the efficacy of our approach on biography and medical question-answering datasets., Comment: 24 pages, 14 figures, NeurIPS

We present a deep learning-based method for estimating the neutrino energy of charged-current neutrino-argon interactions. We employ a recurrent neural network (RNN) architecture for neutrino energy estimation in the MicroBooNE experiment, utilizing liquid argon time projection chamber (LArTPC) detector technology. Traditional energy estimation approaches in LArTPCs, which largely rely on reconstructing and summing visible energies, often experience sizable biases and resolution smearing because of the complex nature of neutrino interactions and the detector response. The estimation of neutrino energy can be improved after considering the kinematics information of reconstructed final-state particles. Utilizing kinematic information of reconstructed particles, the deep learning-based approach shows improved resolution and reduced bias for the muon neutrino Monte Carlo simulation sample compared to the traditional approach. In order to address the common concern about the effectiveness of this method on experimental data, the RNN-based energy estimator is further examined and validated with dedicated data-simulation consistency tests using MicroBooNE data. We also assess its potential impact on a neutrino oscillation study after accounting for all statistical and systematic uncertainties and show that it enhances physics sensitivity. This method has good potential to improve the performance of other physics analyses.

In this paper, we analyze the properties of the recently proposed real-time equation-of-motion coupled-cluster (RT-EOM-CC) cumulant Green's function approach [J. Chem. Phys. 2020, 152, 174113]. We specifically focus on identifying the limitations of the original time-dependent coupled cluster (TDCC) ansatz and propose an enhanced double TDCC ansatz ensuring the exactness in the expansion limit. Additionally, we introduce a practical cluster-analysis-based approach for characterizing the peaks in the computed spectral function from the RT-EOM-CC cumulant Green's function approach, which is particularly useful for the assignments of satellite peaks when many-body effects dominate the spectra. Our preliminary numerical tests focus on reproducing, approximating, and characterizing the exact impurity Green's function of the three-site and four-site single impurity Anderson models using the RT-EOM-CC cumulant Green's function approach. The numerical tests allow us to have a direct comparison between the RT-EOM-CC cumulant Green's function approach and other Green's function approaches in the numerical exact limit.

X-ray spectroscopy has been a key method to determine ground and excited state properties of quantum materials with atomic specificity. Now, new x-ray facilities are opening the door to the study of pump-probe x-ray spectroscopy - specifically time-resolved x-ray absorption (trXAS) and time-resolved resonant inelastic x-ray scattering (trRIXS). In this paper we will present simulations of each of these spectroscopies using a time-domain full atomic multiplet, charge transfer Hamiltonian, adapted to study the properties of a generalized cluster model including a central transition metal ion caged by ligand atoms in a planar geometry. The numerically evaluated trXAS and trRIXS cross-sections for representative electron configurations $3d^9$ and $3d^8$ demonstrate the insights that can be obtained from charge transfer pumping, and how this nonequilibrium process affects ground and excited state properties. The straightforward characterization of the excitations in these systems, based on our analysis of the simulations, can serve as a benchmark for future experiments, as access to these time-resolved spectroscopic techniques becomes more widely available.

The low carbon content of Earth and primitive meteorites compared to the Sun and interstellar grains suggests that carbon-rich grains were destroyed in the inner few astronomical units of the young solar system. A promising mechanism to selectively destroy carbonaceous grains is thermal sublimation within the soot line at $\gtrsim$ 300 K. To address whether such hot conditions are common amongst low-mass protostars, we observe CH$_3$CN transitions at 1, 2 and 3 mm with the NOrthern Extended Millimeter Array (NOEMA) toward seven low-mass and one intermediate-mass protostar ($L_{\rm{bol}} \sim2-300 L_\odot$), as CH$_3$CN is an excellent temperature tracer. We find $>$ 300 K gas toward all sources, indicating that hot gas may be prevalent. Moreover, the excitation temperature for CH$_3$OH obtained with the same observations is always lower ($\sim$135-250 K), suggesting that CH$_3$CN and CH$_3$OH have a different spatial distribution. A comparison of the column densities at 1 and 3 mm shows a stronger increase at 3 mm for CH$_3$CN than for CH$_3$OH. Since the dust opacity is lower at longer wavelengths, this indicates that CH$_3$CN is enhanced in the hot gas compared to CH$_3$OH. If this CH$_3$CN enhancement is the result of carbon-grain sublimation, these results suggests that Earth's initial formation conditions may not be rare., Comment: 19 pages, 9 figures, 4 tables (plus 13 pages appendix with 10 figures, 4 tables). Accepted for publication in ApJ

We simulate the dynamics, including laser cooling, of 3D ion crystals confined in a Penning trap using a newly developed molecular dynamics-like code. The numerical integration of the ions' equations of motion is accelerated using the fast multipole method to calculate the Coulomb interaction between ions, which allows us to efficiently study large ion crystals with thousands of ions. In particular, we show that the simulation time scales linearly with ion number, rather than with the square of the ion number. By treating the ions' absorption of photons as a Poisson process, we simulate individual photon scattering events to study laser cooling of 3D ellipsoidal ion crystals. Initial simulations suggest that these crystals can be efficiently cooled to ultracold temperatures, aided by the mixing of the easily cooled axial motional modes with the low frequency planar modes. In our simulations of a spherical crystal of 1,000 ions, the planar kinetic energy is cooled to several millikelvin in a few milliseconds while the axial kinetic energy and total potential energy are cooled even further. This suggests that 3D ion crystals could be well-suited as platforms for future quantum science experiments., Comment: 23 pages, 6 figures

The magnetic field of a molecular cloud core may play a role in the formation of circumstellar disks in the core. We present magnetic field morphologies in protostellar cores of 16 targets in the Atacama Large Millimeter/submillimeter Array large program "Early Planet Formation in Embedded Disks (eDisk)", which resolved their disks with 7 au resolutions. The 0.1-pc scale magnetic field morphologies were inferred from the James Clerk Maxwell Telescope (JCMT) POL-2 observations. The mean orientations and angular dispersions of the magnetic fields in the dense cores are measured and compared with the radii of the 1.3 mm continuum disks and the dynamically determined protostellar masses from the eDisk program. We observe a significant correlation between the disk radii and the stellar masses. We do not find any statistically significant dependence of the disk radii on the projected misalignment angles between the rotational axes of the disks and the magnetic fields in the dense cores, nor on the angular dispersions of the magnetic fields within these cores. However, when considering the projection effect, we cannot rule out a positive correlation between disk radii and misalignment angles in three-dimensional space. Our results suggest that the morphologies of magnetic fields in dense cores do not play a dominant role in the disk formation process. Instead, the sizes of protostellar disks may be more strongly affected by the amount of mass that has been accreted onto star+disk systems, and possibly other parameters, for example, magnetic field strength, core rotation, and magnetic diffusivity., Comment: 14 pages, 4 figures, accepted by ApJ

Quantum processing units will be modules of larger information processing systems containing also digital and analog electronics modules. Silicon-based quantum computing offers the enticing opportunity to manufacture all the modules using the same technology platform. Here, we present a cryogenic multi-module assembly for multiplexed readout of silicon quantum devices where all modules have been fabricated using the same fully-depleted silicon-on-insulator (FDSOI) CMOS process. The assembly is constituted by three chiplets: (i) a low-noise amplifier (LNA), (ii) a single-pole eight-throw switch (SP8T), and (iii) a silicon quantum dot (QD) array. We integrate the chiplets into modules and show respectively, (i) a peak gain over 35dB with a 3dB bandwidth from 709MHz to 827MHz and an average noise temperature of 6.2K (minimum 4.2K), (ii) an insertion loss smaller than 1.1dB and a noise temperature less than 1.1K over the 0-2GHz range, and (iii) single-electron box (SEB) charge sensors. Finally, we combine all modules into a single demonstration showing time-domain radio-frequency multiplexing of two SEBs paving the way to an all-silicon quantum computing system., Comment: This work has been submitted to the IEEE for possible publication

This work aims to utilize the increased sensitivity and resolution of the JWST to quantify the HDO/H$_{2}$O ratio in ices toward young stellar objects (YSOs) and to determine if the HDO/H$_{2}$O ratios measured in the gas phase toward massive YSOs (MYSOs) are representative of the ratios in their ice envelopes. Two protostars observed in the Investigating Protostellar Accretion (IPA) program using JWST NIRSpec were analyzed: HOPS 370, an intermediate-mass YSO (IMYSO), and IRAS 20126+4104, a MYSO. The HDO ice toward these sources was detected above the 3$\sigma$ level and quantified via its 4.1 $\mu$m band. The contributions from the CH$_{3}$OH combination modes to the observed optical depth in this spectral region were constrained via the CH$_{3}$OH 3.53 $\mu$m band to ensure that the integrated optical depth of the HDO feature was not overestimated. H$_{2}$O ice was quantified via its 3 $\mu$m band. From these fits, ice HDO/H$_{2}$O abundance ratios of 4.6$\pm$1.8$\times$10$^{-3}$ and 2.6$\pm$1.2$\times$10$^{-3}$ are obtained for HOPS 370 and IRAS 20126+4104, respectively. The simultaneous detections of both crystalline HDO and crystalline H$_{2}$O corroborate the assignment of the observed feature at 4.1 $\mu$m to HDO ice. The ice HDO/H$_{2}$O ratios are similar to the highest reported gas HDO/H$_{2}$O ratios measured toward MYSOs as well as the hot inner regions of isolated low-mass protostars, suggesting that at least some of the gas HDO/H$_{2}$O ratios measured toward massive hot cores are representative of the HDO/H$_{2}$O ratios in ices. The need for an H$_{2}$O-rich CH$_{3}$OH component in the CH$_{3}$OH ice analysis supports recent experimental and observational results that indicate that some CH$_{3}$OH ice may form prior to the CO freeze-out stage in H$_{2}$O-rich ice layers., Comment: Accepted for publication in A&A. 23 pages, 17 figures, 10 tables

We present an approach for automatically generating and testing, in silico, social scientific hypotheses. This automation is made possible by recent advances in large language models (LLM), but the key feature of the approach is the use of structural causal models. Structural causal models provide a language to state hypotheses, a blueprint for constructing LLM-based agents, an experimental design, and a plan for data analysis. The fitted structural causal model becomes an object available for prediction or the planning of follow-on experiments. We demonstrate the approach with several scenarios: a negotiation, a bail hearing, a job interview, and an auction. In each case, causal relationships are both proposed and tested by the system, finding evidence for some and not others. We provide evidence that the insights from these simulations of social interactions are not available to the LLM purely through direct elicitation. When given its proposed structural causal model for each scenario, the LLM is good at predicting the signs of estimated effects, but it cannot reliably predict the magnitudes of those estimates. In the auction experiment, the in silico simulation results closely match the predictions of auction theory, but elicited predictions of the clearing prices from the LLM are inaccurate. However, the LLM's predictions are dramatically improved if the model can condition on the fitted structural causal model. In short, the LLM knows more than it can (immediately) tell.