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Realizing tunable functional materials with built-in nanoscale heat flow directionality represents a significant challenge with the potential to enable novel thermal management strategies. Here we use spatiotemporally-resolved thermoreflectance to visualize lateral thermal transport anisotropy in self-assembled supercrystals of anisotropic Au nanocrystals. Correlative electron and thermoreflectance microscopy reveal that heat predominantly flows along the long-axis of the anisotropic nanocrystals, and does so across grain boundaries and curved assemblies while voids disrupt heat flow. We finely control the anisotropy via the aspect ratio of constituent nanorods, and it exceeds the aspect ratio for nano-bipyramid supercrystals and certain nanorod arrangements. Finite element simulations and effective medium modeling rationalize the emergent anisotropic behavior in terms of a simple series resistance model, further providing a framework for estimating thermal anisotropy as a function of material and structural parameters. Self-assembly of colloidal nanocrystals promises a novel route to direct heat flow in a wide range of applications that utilize this important class of materials.

The ability to create and harness entanglement is crucial to the fields of quantum sensing andsimulation, and ultracold atom-cavity systems offer pristine platforms for this undertaking. Recently, an experiment demonstrated an effective momentum-exchange interaction between atoms in a common cavity mode. Here, we derive this interaction from a general atom-cavity model, and discuss the role of the cavity frequency shift in response to atomic motion. We show the cavity response leads to many different squeezing interactions between the atomic momentum states. Furthermore, when the atoms form a density grating, the collective motion leads to one-axis twisting, a many-body energy gap, and metrologically useful entanglement even in the presence of noise. This system offers a highly tunable, many-body quantum sensor and simulator.

Using Keck Planet Imager and Characterizer (KPIC) high-resolution ($R$~35000) spectroscopy from 2.29-2.49 $\mu$m, we present uniform atmospheric retrievals for eight young substellar companions with masses of ~10-30 $M_\textrm{Jup}$, orbital separations spanning ~50-360 au, and $T_\textrm{eff}$ between ~1500-2600 K. We find that all companions have solar C/O ratios, and metallicities, to within the 1-2$\sigma$ level, with the measurements clustered around solar composition. Stars in the same stellar associations as our systems have near-solar abundances, so these results indicate that this population of companions is consistent with formation via direct gravitational collapse. Alternatively, core accretion outside the CO snowline would be compatible with our measurements, though the high mass ratios of most systems would require rapid core assembly and gas accretion in massive disks. On a population level, our findings can be contrasted with abundance measurements for directly imaged planets with m<10 $M_\textrm{Jup}$, which show tentative atmospheric metal enrichment. In addition, the atmospheric compositions of our sample of companions are distinct from those of hot Jupiters, which most likely form via core accretion. For two companions with $T_\textrm{eff}$~1700-2000 K (kap And b and GSC 6214-210 b), our best-fit models prefer a non-gray cloud model with >3$\sigma$ significance. The cloudy models yield 2-3$\sigma$ lower $T_\textrm{eff}$ for these companions, though the C/O and [C/H] still agree between cloudy and clear models at the $1\sigma$ level. Finally, we constrain 12CO/13CO for three companions with the highest S/N data (GQ Lup b, HIP 79098 b, and DH Tau b), and report $v$sin($i$) and radial velocities for all companions., Comment: Accepted to ApJ, 52 pages, 20 figures

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.

We present a multi-wavelength analysis, from the radio to the X-ray band, of the redshift $z=6.44$ VIK J2318$-$31 radio-loud (RL) quasi stellar object (QSO), one of the most distant currently known in this class. The work is based on newly obtained (uGMRT, ATCA, Chandra) as well as archival (GNIRS and X-Shooter) dedicated observations that have not been published yet. Based on the observed X-ray and radio emission, its relativistic jets are likely young and misaligned from our line of sight. Moreover, we can confirm, with simultaneous observations, the presence of a turnover in the radio spectrum at $\nu_{\rm peak} \sim 650$ MHz which is unlikely to be associated with self-synchrotron absorption. From the NIR spectrum we derived the mass of the central black hole, M$_{\rm BH}=8.1^{+6.8}_{-5.6} \times 10^8 {\rm M_{\odot}}$, and the Eddington ratio, $\lambda_{\rm EDD} = 0.8^{+0.8}_{-0.6}$, using broad emission lines as well as an accretion disc model fit to the continuum emission. Given the high accretion rate, the presence of a $\sim$8$\times$10$^8$ M$_\odot$ black hole at $z=6.44$ can be explained by a seed black hole ($\sim$10$^{4}$ M$_\odot$) that formed at $z\sim25$, assuming a radiative efficiency $\eta_{\rm d}\sim0.1$. However, by assuming $\eta_{\rm d}\sim0.3$, as expected for jetted systems, the mass observed would challenge current theoretical models of black hole formation., Comment: Accepted for publication on A&A the 22nd April 2024

We summarize the current best polychromatic (10 to 20 % bandwidth) contrast performance demonstrated in the laboratory by different starlight suppression approaches and systems designed to directly characterize exoplanets around nearby stars. We present results obtained by internal coronagraph and external starshade experimental testbeds using entrance apertures equivalent to off-axis or on-axis telescopes, either monolithic or segmented. For a given angular separation and spectral bandwidth, the performance of each starlight suppression system is characterized by the values of raw contrast (before image processing), off-axis (exoplanet) core throughput, and post-calibration contrast (the final 1 sigma detection limit of off-axis point sources, after image processing). To place the current laboratory results in the perspective of the future Habitable Worlds Observatory (HWO) mission, we simulate visible observations of a fiducial Earth/Sun twin system at 12 pc, assuming a 6m (inscribed diameter) collecting aperture and a realistic end-to-end optical throughput. The exposure times required for broadband exoearth detection (20% bandwidth around a wavelength of 0.55 microns) and visible spectroscopic observations (R=70) are then computed assuming various levels of starlight suppression performance, including the values currently demonstrated in the laboratory. Using spectroscopic exposure time as a simple metric, our results point to key starlight suppression system design performance improvements and trades to be conducted in support of HWO exoplanet science capabilities. These trades may be explored via numerical studies, lab experiments, as well as high contrast space-based observations and demonstrations., Comment: 63 pages, 28 pages, submitted to JATIS

The ability to understand and ultimately control the transformations and properties of various nanoscale systems, from proteins to synthetic nanomaterial assemblies, hinges on the ability to directly elucidate their dynamics on their characteristic length and time scales. Here, we use MHz X-ray photon correlation spectroscopy (XPCS) to directly elucidate the characteristic microsecond-dynamics of density fluctuations of semiconductor nanocrystals (NCs), not only in a colloidal dispersion but also in a liquid phase consisting of densely packed, yet mobile, NCs with no long-range order. By carefully disentangling X-ray induced effects, we find the wavevector-dependent fluctuation rates in the liquid phase are suppressed relative to those in the colloidal phase and to those in experiments and hydrodynamic theories of densely packed repulsive particles. We show that the suppressed rates are due to a substantial decrease in the self-diffusion of NCs in the liquid phase, which we attribute to explicit attractive interactions. Via comparison with simulations, we find that the extracted strength of the attractions explains the stability of the liquid phase, in contrast to the gelation observed via XPCS in many other charged colloidal systems. This work opens the door to elucidating fast, condensed phase dynamics in a variety of complex fluids and other nanoscale soft matter systems, such as densely packed proteins and non-equilibrium self-assembly processes., Comment: 15 pages, 4 figures

Bottom-up assembly of nanocrystals (NCs) into ordered arrays, or superlattices (SLs), is a promising route to design materials with new functionalities, but the degree of control over assembly into functional structures remains challenging. Using electrostatics, rather than density, to tune the interactions between semiconductor NCs, we watch self-assembly proceeding through a metastable liquid phase. We systematically investigate the phase behavior as a function of quench conditions in situ and in real time using small angle X-ray scattering (SAXS). Through quantitative fitting to colloid, liquid, and SL models, we extract the time evolution of each phase and the system phase diagram, which we find to be consistent with short-range attractive interactions. Using the phase diagram's predictive power, we establish control of the self-assembly rate over three orders of magnitude, and identify one- and two-step self-assembly regimes, with only the latter implicating the metastable liquid as an intermediate. Importantly, the presence of the metastable liquid increases SL formation rates relative to the equivalent one-step pathway, and SL order counterintuitively increases with the rate, revealing a highly desirable and generalizable kinetic strategy to promote and enhance ordered assembly., Comment: 16 pages, 4 figures

Tow steering technologies, such as Automated fiber placement, enable the fabrication of composite laminates with curvilinear fiber, tow, or tape paths. Designers may therefore tailor tow orientations locally according to the expected local stress state within a structure, such that strong and stiff orientations of the tow are (for example) optimized to provide maximal mechanical benefit. Tow path optimization can be an effective tool in automating this design process, yet has a tendency to create complex designs that may be challenging to manufacture. In the context of tow steering, these complexities can manifest in defects such as tow wrinkling, gaps, overlaps. In this work, we implement manufacturing constraints within the tow path optimization formulation to restrict the minimum tow turning radius and the maximum density of gaps between and overlaps of tows. This is achieved by bounding the local value of the curl and divergence of the vector field associated with the tow orientations. The resulting local constraints are effectively enforced in the optimization framework through the Augmented Lagrangian method. The resulting optimization methodology is demonstrated by designing 2D and 3D structures with optimized tow orientation paths that maximize stiffness (minimize compliance) considering various levels of manufacturing restrictions. The optimized tow paths are shown to be structurally efficient and to respect imposed manufacturing constraints. As expected, the more geometrical complexity that can be achieved by the feedstock tow and placement technology, the higher the stiffness of the resulting optimized design., Comment: 29 pages, 16 figures

Particle-in-Cell (PIC) method is a powerful plasma simulation tool for investigating high-intensity femtosecond laser-matter interaction. However, its simulation capability at high-density plasmas around the Fermi temperature is considered to be inadequate due, among others, to the necessity of implementing atomic-scale collisions. Here, we performed a one-dimensional with three-velocity space (1D3V) PIC simulation that features the realistic collision frequency around the Fermi temperature and atomic-scale cell size. The results are compared with state-of-the-art experimental results as well as with hydrodynamic simulation. We found that the PIC simulation is capable of simulating the nanoscale dynamics of solid-density plasmas around the Fermi temperature up to $\sim$2~ps driven by a laser pulse at the moderate intensity of $10^{14-15}$~$\mathrm{W/cm^{2}}$, by comparing with the state-of-the-art experimental results. The reliability of the simulation can be further improved in the future by implementing multi-dimensional kinetics and radiation transport.

The VASARI MRI feature set is a quantitative system designed to standardise glioma imaging descriptions. Though effective, deriving VASARI is time-consuming and seldom used in clinical practice. This is a problem that machine learning could plausibly automate. Using glioma data from 1172 patients, we developed VASARI-auto, an automated labelling software applied to both open-source lesion masks and our openly available tumour segmentation model. In parallel, two consultant neuroradiologists independently quantified VASARI features in a subsample of 100 glioblastoma cases. We quantified: 1) agreement across neuroradiologists and VASARI-auto; 2) calibration of performance equity; 3) an economic workforce analysis; and 4) fidelity in predicting patient survival. Tumour segmentation was compatible with the current state of the art and equally performant regardless of age or sex. A modest inter-rater variability between in-house neuroradiologists was comparable to between neuroradiologists and VASARI-auto, with far higher agreement between VASARI-auto methods. The time taken for neuroradiologists to derive VASARI was substantially higher than VASARI-auto (mean time per case 317 vs. 3 seconds). A UK hospital workforce analysis forecast that three years of VASARI featurisation would demand 29,777 consultant neuroradiologist workforce hours ({\pounds}1,574,935), reducible to 332 hours of computing time (and {\pounds}146 of power) with VASARI-auto. The best-performing survival model utilised VASARI-auto features as opposed to those derived by neuroradiologists. VASARI-auto is a highly efficient automated labelling system with equitable performance across patient age or sex, a favourable economic profile if used as a decision support tool, and with non-inferior fidelity in downstream patient survival prediction. Future work should iterate upon and integrate such tools to enhance patient care., Comment: 28 pages, 6 figures, 1 table

Quantum simulation using synthetic quantum systems offers unique opportunities to explore open questions in many-body physics and a path for the generation of useful entangled states. Nevertheless, so far many quantum simulators have been fundamentally limited in the models they can mimic. Here, we are able to realize an all-to-all interaction with arbitrary quadratic Hamiltonian or effectively an infinite range tunable Heisenberg XYZ model. This is accomplished by engineering cavity-mediated four-photon interactions between 700 rubidium atoms in which we harness a pair of momentum states as the effective pseudo spin or qubit degree of freedom. Using this capability we realize for the first time the so-called two-axis counter-twisting model at the mean-field level. The versatility of our platform to include more than two relevant momentum states, combined with the flexibility of the simulated Hamiltonians by adding cavity tones opens rich opportunities for quantum simulation and quantum sensing in matter-wave interferometers and other quantum sensors such as optical clocks and magnetometers

Transferring the nanocrystals (NCs) from the laboratory environment toward practical applications has raised new challenges. In the case of NCs for display and lightning, the focus was on reduced Auger recombination and maintaining luminescence at high temperatures. When it comes to infrared sensing, narrow band gap materials are required and HgTe appears as the most spectrally tunable platform. Its low-temperature synthesis reduces the growth energy cost yet also favors sintering. As a result, once coupled to a read-out circuit, the Joule effect aggregates the particles leading to a poorly defined optical edge and dramatically large dark current. Here, we demonstrate that CdS shells bring the expected thermal stability (no redshift upon annealing, reduced tendency to form amalgams and preservation of photoconduction after an atomic layer deposition process). The peculiar electronic structure of these confined particles is unveiled using k.p self-consistent simulations showing a significant exciton biding energy at around 200 meV. After shelling, the material displays a p-type behavior that favors the generation of photoconductive gain. The latter is then used to increase the external quantum

We show how a driven-dissipative cavity coupled to a collective ensemble of atoms can dynamically generate metrologically useful spin-squeezed states. In contrast to other dissipative approaches, we do not rely on complex engineered dissipation or input states, nor do we require tuning the system to a critical point. Instead, we utilize a strong symmetry, a special type of symmetry that can occur in open quantum systems and emerges naturally in systems with collective dissipation, such as superradiance. This symmetry preserves coherence and allows for the accumulation of an atom number-dependent Berry phase which in turn creates spin-squeezed states via emergent one-axis twisting dynamics. This work shows that it is possible to generate entanglement in an atom-cavity resonant regime with macroscopic optical excitations of the system, going beyond the typical dispersive regime with negligible optical excitations often utilized in current cavity QED experiments., Comment: 5+14 pages, 3 figures

Solution-phase bottom up self-assembly of nanocrystals into superstructures such as ordered superlattices is an attractive strategy to generate functional materials of increasing complexity, including very recent advances that incorporate strong interparticle electronic coupling. While the self-assembly kinetics in these systems have been elucidated and related to the product characteristics, the weak interparticle bonding interactions suggest the superstructures formed could continue to order within the solution long after the primary nucleation and growth have occurred, even though the mechanism of annealing remains to be elucidated. Here, we use a combination of Bragg coherent diffractive imaging and X-ray photon correlation spectroscopy to create real-space maps of supercrystalline order along with a real-time view of the strain fluctuations in aging strongly coupled nanocrystal superlattices while they remain suspended and immobilized in solution. By combining the results, we deduce that the self-assembled superstructures are polycrystalline, initially comprising multiple nucleation sites, and that shear avalanches at grain boundaries continue to increase crystallinity long after growth has substantially slowed. This multimodal approach should be generalizable to characterize a breadth of materials in situ in their native chemical environments, thus extending the reach of high-resolution coherent X-ray characterization to the benefit of a much wider range of physical systems., Comment: 26 pages, 20 figures

Quantification of microstructures is crucial for understanding processing-structure and structure-property relationships in polycrystalline materials. Delineating grain boundaries in bright-field transmission electron micrographs, however, is challenging due to complex diffraction contrast in images. Conventional edge detection algorithms are inadequate; instead, manual tracing is usually required. This study demonstrates the first successful machine-learning approach for grain-boundary detection in bright-field transmission electron micrographs. The proposed methodology uses a U-Net convolutional neural network trained on carefully constructed data from bright-field images and hand-tracings available from prior studies, combined with targeted post-processing algorithms to preserve fine features of interest. The image processing pipeline accurately estimates grain-boundary positions, avoiding segmentation in regions with intragrain contrast and identifying low-contrast boundaries. Our approach is validated by directly comparing microstructural markers (i.e., grain centroids) identified in U-Net predictions with those identified in hand tracings; furthermore, the grain size distributions obtained from the two techniques show notable overlap when compared using t-, Kolmogorov-Smirnov, and Cramer-von Mises tests. The technique is then successfully applied to interpret new aluminum film microstructures having different image characteristics from the training data, and preliminary results from Pt and Pd microstructures are presented, highlighting the versatility of our approach for grain-boundary identification in bright-field micrographs.

The factorization method of Schrodinger shows us how to determine the energy eigenstates without needing to determine the wavefunctions in position or momentum space. A strategy to convert the energy eigenstates to wavefunctions is well known for the one-dimensional simple harmonic oscillator by employing the Rodrigues formula for the Hermite polynomials in position or momentum space. In this work, we illustrate how to generalize this approach in a representation-independent fashion to find the wavefunctions of other problems in quantum mechanics that can be solved by the factorization method. We examine three problems in detail: (i) the one-dimensional simple harmonic oscillator; (ii) the three-dimensional isotropic harmonic oscillator; and (iii) the three-dimensional Coulomb problem. This approach can be used in either undergraduate or graduate classes in quantum mechanics., Comment: (10 pages, 1 figure, plus supplemental material)

Self-assembly of colloidal nanocrystals (NCs) into superlattices (SLs) is an appealing strategy to design hierarchically organized materials with new functionalities. Mechanistic studies are still needed to uncover the design principles for SL self-assembly, but such studies have been difficult to perform due to the fast time- and short length scales of NC systems. To address this challenge, we developed an apparatus to directly measure the evolving phases \textit{in situ} and in real time of an electrostatically stabilized Au NC solution before, during, and after it is quenched to form SLs using small angle X-ray scattering (SAXS). By developing a quantitative model, we fit the time-dependent scattering patterns to obtain the phase diagram of the system and the kinetics of the colloidal and SL phases as a function of varying quench conditions. The extracted phase diagram is consistent with particles whose interactions are short in range relative to their diameter. We find the degree of SL order is primarily determined by fast (sub-second) initial nucleation and growth kinetics, while coarsening at later times depends non-monotonically on the driving force for self-assembly. We validate these results by direct comparison with simulations and use them to suggest dynamic design principles to optimize crystallinity within a finite time window. The combination of this measurement methodology, quantitative analysis, and simulation should be generalizable to elucidate and better control the microscopic self-assembly pathways of a wide range of bottom-up assembled systems and architectures.

M dwarfs are common host stars to exoplanets but often lack atmospheric abundance measurements. Late-M dwarfs are also good analogs to the youngest substellar companions, which share similar $T_{\rm eff}\sim2300-2800~K$. We present atmospheric analyses for the M7.5 companion HIP 55507 B and its K6V primary star with Keck/KPIC high-resolution ($R\sim35,000$) $K$ band spectroscopy. First, by including KPIC relative radial velocities between the primary and secondary in the orbit fit, we improve the dynamical mass precision by 60% and find $M_B=88.0_{-3.2}^{+3.4}$ $M_{\rm Jup}$, putting HIP 55507 B above the stellar-substellar boundary. We also find that HIP 55507 B orbits its K6V primary star with $a=38^{+4}_{-3}$ AU and $e=0.40\pm0.04$. From atmospheric retrievals of HIP 55507 B, we measure $\rm [C/H]=0.24\pm0.13$, $\rm [O/H]=0.15\pm0.13$, and $\rm C/O=0.67\pm0.04$. Moreover, we strongly detect $\rm ^{13}CO$ ($7.8\sigma$ significance) and tentatively detect $\rm H_2^{18}O$ ($3.7\sigma$ significance) in companion's atmosphere, and measure $\rm ^{12}CO/^{13}CO=98_{-22}^{+28}$ and $\rm H_2^{16}O/H_2^{18}O=240_{-80}^{+145}$ after accounting for systematic errors. From a simplified retrieval analysis of HIP 55507 A, we measure $\rm ^{12}CO/^{13}CO=79_{-16}^{+21}$ and $\rm C^{16}O/C^{18}O=288_{-70}^{+125}$ for the primary star. These results demonstrate that HIP 55507 A and B have consistent $\rm ^{12} C/^{13}C$ and $\rm ^{16}O/^{18}O$ to the $<1\sigma$ level, as expected for a chemically homogeneous binary system. Given the similar flux ratios and separations between HIP 55507 AB and systems with young, substellar companions, our results open the door to systematically measuring $\rm ^{13}CO$ and $\rm H_2^{18}O$ abundances in the atmospheres of substellar or even planetary-mass companions with similar spectral types., Comment: Accepted to ApJ, 28 pages, 14 figures

Large widefield surveys make possible the serendipitous discovery of rare sub-classes of pulsars. One such class are "spider"-type pulsar binaries, comprised of a pulsar in a compact orbit with a low-mass (sub)stellar companion. In a search for circularly-polarized radio sources in ASKAP Pilot Survey observations, we discovered highly variable and circularly polarized emission from a radio source within the error region of the $\gamma$-ray source {4FGL}~J1646.5$-$4406. The variability is consistent with the eclipse of a compact, steep-spectrum source behind ablated material from a companion in a $\sim 5.3\,$h binary orbit. Based on the eclipse properties and spatial coincidence with {4FGL} J1646.5$-$4406, we argue that the source is likely a recycled pulsar in a "redback" binary system. Using properties of the eclipses from ASKAP and Murchison Widefield Array observations, we provide broad constraints on the properties of the eclipse medium. We identified a potential optical/infra-red counterpart in archival data consistent with a variable low-mass star. Using the Parkes Radio Telescope "Murriyang" and MeerKAT, we searched extensively for radio pulsations but yielded no viable detections of pulsed emission. We suggest that the non-detection of pulses is due to scattering in the intra-binary material, but scattering from the ISM can also plausibly explain the pulse non-detections if the interstellar dispersion measure exceeds $\sim$600$\,$pc$\,$cm$^{-3}$. Orbital constraints derived from optical observations of the counterpart would be highly valuable for future $\gamma$-ray pulsation searches, which may confirm the source nature as a pulsar., Comment: Submitted to MNRAS. 13 Pages, 10 figures, 3 tables

The Australian SKA Pathfinder (ASKAP) has surveyed the sky at multiple frequencies as part of the Rapid ASKAP Continuum Survey (RACS). The first two RACS observing epochs, at 887.5 (RACS-low) and 1367.5 (RACS-mid) MHz, have been released (McConnell et al., 2020; Duchesne et al., 2023). A catalogue of radio sources from RACS-low has also been released, covering the sky south of declination +30$^\circ$ (Hale et al., 2021). With this paper, we describe and release the first set of catalogues from RACS-mid, covering the sky below declination +49$^\circ$. The catalogues are created in a similar manner to the RACS-low catalogue, and we discuss this process and highlight additional changes. The general purpose primary catalogue covering 36 200 deg$^2$ features a variable angular resolution to maximise sensitivity and sky coverage across the catalogued area, with a median angular resolution of 11.2" times 9.3". The primary catalogue comprises 3 105 668 radio sources, including those in the Galactic Plane (2 861 923 excluding Galactic latitudes of $|b|<5^\circ$) and we estimate the catalogue to be 95% complete for sources above 1.6 mJy. With the primary catalogue, we also provide two auxiliary catalogues. The first is a fixed-resolution, 25-arcsec catalogue approximately matching the sky coverage of the RACS-low catalogue. This 25-arcsec catalogue is constructed identically to the primary catalogue, except images are convolved to a less-sensitive 25-arcsec angular resolution. The second auxiliary catalogue is designed for time-domain science, and is the concatenation of source-lists from the original RACS-mid images with no additional convolution, mosaicking, or de-duplication of source entries to avoid losing time-variable signals. All three RACS-mid catalogues, and all RACS data products, are available through the CSIRO ASKAP Science Data Archive (CASDA)., Comment: Accepted for publication in PASA. Primary catalogues and images available at https://doi.org/10.25919/p524-xb81 and an auxiliary catalogue available at https://doi.org/10.25919/p8ns-da63

The architecture of the brain is too complex to be intuitively surveyable without the use of compressed representations that project its variation into a compact, navigable space. The task is especially challenging with high-dimensional data, such as gene expression, where the joint complexity of anatomical and transcriptional patterns demands maximum compression. Established practice is to use standard principal component analysis (PCA), whose computational felicity is offset by limited expressivity, especially at great compression ratios. Employing whole-brain, voxel-wise Allen Brain Atlas transcription data, here we systematically compare compressed representations based on the most widely supported linear and non-linear methods-PCA, kernel PCA, non-negative matrix factorization (NMF), t-stochastic neighbour embedding (t-SNE), uniform manifold approximation and projection (UMAP), and deep auto-encoding-quantifying reconstruction fidelity, anatomical coherence, and predictive utility with respect to signalling, microstructural, and metabolic targets. We show that deep auto-encoders yield superior representations across all metrics of performance and target domains, supporting their use as the reference standard for representing transcription patterns in the human brain., Comment: 22 pages, 5 main figures, 1 supplementary figure

We study the combined effects of measurements and unitary evolution on the preparation of spin squeezing in an ensemble of atoms interacting with a single electromagnetic field mode inside a cavity. We derive simple criteria that determine the conditions at which measurement based entanglement generation overperforms unitary protocols. We include all relevant sources of decoherence and study both their effect on the optimal spin squeezing and the overall size of the measurement noise, which limits the dynamical range of quantum-enhanced phase measurements. Our conclusions are relevant for state-of-the-art atomic clocks that aim to operate below the standard quantum limit., Comment: 6 + 10 pages, 4 + 1 figures

Our knowledge of the organisation of the human brain at the population-level is yet to translate into power to predict functional differences at the individual-level, limiting clinical applications, and casting doubt on the generalisability of inferred mechanisms. It remains unknown whether the difficulty arises from the absence of individuating biological patterns within the brain, or from limited power to access them with the models and compute at our disposal. Here we comprehensively investigate the resolvability of such patterns with data and compute at unprecedented scale. Across 23 810 unique participants from UK Biobank, we systematically evaluate the predictability of 25 individual biological characteristics, from all available combinations of structural and functional neuroimaging data. Over 4526 GPU hours of computation, we train, optimize, and evaluate out-of-sample 700 individual predictive models, including fully-connected feed-forward neural networks of demographic, psychological, serological, chronic disease, and functional connectivity characteristics, and both uni- and multi-modal 3D convolutional neural network models of macro- and micro-structural brain imaging. We find a marked discrepancy between the high predictability of sex (balanced accuracy 99.7%), age (mean absolute error 2.048 years, R2 0.859), and weight (mean absolute error 2.609Kg, R2 0.625), for which we set new state-of-the-art performance, and the surprisingly low predictability of other characteristics. Neither structural nor functional imaging predicted psychology better than the coincidence of chronic disease (p<0.05). Serology predicted chronic disease (p<0.05) and was best predicted by it (p<0.001), followed by structural neuroimaging (p<0.05). Our findings suggest either more informative imaging or more powerful models are needed to decipher individual level characteristics from the human brain., Comment: 38 pages, 6 figures, 1 table, 2 supplementary figures, 1 supplementary table

This work introduces a moving anchor acceleration technique to extragradient algorithms for smooth structured minimax problems. The moving anchor is introduced as a generalization of the original algorithmic anchoring framework, i.e. the EAG method introduced in [32], in hope of further acceleration. We show that the optimal order of convergence in terms of worst-case complexity on the squared gradient, O(1/k2), is achieved by our new method (where k is the number of iterations). We have also extended our algorithm to a more general nonconvex-nonconcave class of saddle point problems using the framework of [14], which slightly generalizes [32]. We obtain similar order-optimal complexity results in this extended case. In both problem settings, numerical results illustrate the efficacy of our moving anchor algorithm variants, in particular by attaining the theoretical optimal convergence rate for first order methods, as well as suggesting a better optimized constant in the big O notation which surpasses the traditional fixed anchor methods in many cases. A proximal-point preconditioned version of our algorithms is also introduced and analyzed to match optimal theoretical convergence rates., Comment: 21 pages, 6 figures

The quantification of cognitive powers rests on identifying a behavioural task that depends on them. Such dependence cannot be assured, for the powers a task invokes cannot be experimentally controlled or constrained a priori, resulting in unknown vulnerability to failure of specificity and generalisability. Evaluating a compact version of Raven's Advanced Progressive Matrices (RAPM), a widely used clinical test of fluid intelligence, we show that LaMa, a self-supervised artificial neural network trained solely on the completion of partially masked images of natural environmental scenes, achieves human-level test scores a prima vista, without any task-specific inductive bias or training. Compared with cohorts of healthy and focally lesioned participants, LaMa exhibits human-like variation with item difficulty, and produces errors characteristic of right frontal lobe damage under degradation of its ability to integrate global spatial patterns. LaMa's narrow training and limited capacity -- comparable to the nervous system of the fruit fly -- suggest RAPM may be open to computationally simple solutions that need not necessarily invoke abstract reasoning., Comment: 26 pages, 5 figures

The Tidal Disruption Event (TDE) AT 2018hyz exhibited a delayed radio flare almost three years after the stellar disruption. Here we report new radio observations of the TDE AT 2018hyz with the AMI-LA and ATCA spanning from a month to more than four years after the optical discovery and 200 days since the last reported radio observation. We detected no radio detection from 30-220 days after the optical discovery in our observations at 15.5 GHz down to a $3\sigma$ level of < 0.14 mJy. The fast-rising, delayed, radio flare is observed in our radio data set and continues to rise almost ~1580 days after the optical discovery. We find that the delayed radio emission, first detected $972$ days after optical discovery, evolves as $t^{4.2 \pm 0.9}$, at 15.5 GHz. Here, we present an off-axis jet model that can explain the full set of radio observations. In the context of this model, we require a powerful narrow jet with an isotropic equivalent kinetic energy $E_{\rm k,iso} \sim 10^{55}$ erg, an opening angle of $ \rm \sim 7^{\circ}$, and a relatively large viewing angle of $ \rm \sim 42^{\circ}$, launched at the time of the stellar disruption. Within our framework, we find that the minimal collimated energy possible for an off-axis jet from AT 2018hyz is $E_k \geq 3 \times 10^{52}$ erg. Finally, we provide predictions based on our model for the light curve turnover time, and for the proper motion of the radio emitting source., Comment: 8 pages, 6 figures, submitted to MNRAS

We present the detection of 661 known pulsars observed with the Australian SKA Pathfinder (ASKAP) telescope at 888 MHz as a part of the Rapid ASKAP Continuum Survey (RACS). Detections were made through astrometric coincidence and we estimate the false alarm rate of our sample to be ~0.5%. Using archival data at 400 and 1400 MHz, we estimate the power law spectral indices for the pulsars in our sample and find that the mean spectral index is -1.78 +/- 0.6. However, we also find that a single power law is inadequate to model all the observed spectra. With the addition of the flux densities between 150 MHz and 3 GHz from various imaging surveys, we find that up to 40% of our sample shows deviations from a simple power law model. Using Stokes V measurements from the RACS data, we measured the circular polarization fraction for 9% of our sample and find that the mean polarization fraction is ~10% (consistent between detections and upper limits). Using the dispersion measure (DM) derived distance we estimate the pseudo luminosity of the pulsars and do not find any strong evidence for a correlation with the pulsars' intrinsic properties., Comment: Accepted for publication in ApJ (18 pages, 16 figures), comments are welcome

The Landau-Zener problem, where a minimum energy separation is passed with constant rate in a two-state quantum-mechanical system, is an excellent model quantum system for a computational project. It requires a low-level computational effort, but has a number of complex numerical and algorithmic issues that can be resolved through dedicated work. It can be used to teach computational concepts such as accuracy, discretization, and extrapolation, and it reinforces quantum concepts of time-evolution via a time-ordered product and of extrapolation to infinite time via time-dependent perturbation theory. In addition, we discuss the concept of compression algorithms, which are employed in many advanced quantum computing strategies, and easy to illustrate with the Landau-Zener problem., Comment: (9 pages, accepted for publication in the American Journal of Physics)