Search

In the last few decades planet search surveys have been focusing on solar type stars, and only recently the high-mass regimes. This is mostly due to challenges arising from the lack of instrumental precision, and more importantly, the inherent active nature of fast rotating massive stars. Here we report NGTS-33b (TOI-6442b), a super-Jupiter planet with mass, radius and orbital period of 3.6 $\pm$ 0.3 M$_{\rm jup}$, 1.64 $\pm$ 0.07 R$_{\rm jup}$ and $2.827972 \pm 0.000001$ days, respectively. The host is a fast rotating ($0.6654 \pm 0.0006$ day) and hot (T$_{\rm eff}$ = 7437 $\pm$ 72 K) A9V type star, with a mass and radius of 1.60 $\pm$ 0.11 M$_{\odot}$ and 1.47 $\pm$ 0.06 R$_{\odot}$, respectively. Planet structure and Gyrochronology models shows that NGTS-33 is also very young with age limits of 10-50 Myr. In addition, membership analysis points towards the star being part of the Vela OB2 association, which has an age of $\sim$ 20-35 Myr, thus providing further evidences about the young nature of NGTS-33. Its low bulk density of 0.19$\pm$0.03 g cm$^{-3}$ is 13$\%$ smaller than expected when compared to transiting hot Jupiters with similar masses. Such cannot be solely explained by its age, where an up to 15$\%$ inflated atmosphere is expected from planet structure models. Finally, we found that its emission spectroscopy metric is similar to JWST community targets, making the planet an interesting target for atmospheric follow-up. Therefore, NGTS-33b's discovery will not only add to the scarce population of young, massive and hot Jupiters, but will also help place further strong constraints on current formation and evolution models for such planetary systems., Comment: 19 pages, 17 figures, 7 tables, accepted for publication in MNRAS

Ensembles of complex symmetric, and complex self dual random matrices are known to exhibit local statistical properties distinct from those of the non-Hermitian Ginibre ensembles. On the other hand, in distinction to the latter, the joint eigenvalue probability density function of these two ensembles are not known. Nonetheless, as carried out in the recent works of Liu and Zhang, Akemann et al.~and Kulkarni et al., by considering averages of products of characteristic polynomials, analytic progress can be made. Here we show that an approach based on the theory of zonal polynomials provides an alternative to the diffusion operator or supersymmetric Grassmann integrations methods of these works. It has the advantage of not being restricted to a Gaussian unitary invariant measure on the matrix spaces. To illustrate this, as an extension, we consider averages of products and powers of characteristic polynomials for complex symmetric, and complex self dual random matrices subject to a spherical measure. In the case of powers, when comparing against the corresponding real Ginibre, respectively quaternion Ginibre averages with a spherical measure, one finds the qualitative feature of a decreasing (increasing) profile as the magnitude of the argument of the characteristic polynomial increases. This is analogous to the findings of the second two of the cited works in the Gaussian case., Comment: 16 pages

We present a new method that successfully predicts the glass transition temperature $T_{\! \textrm{g}}$ of polymers based on their monomer structure. The model combines ideas from Group Additive Properties (GAP) and Quantitative Structure Property Relationship (QSPR) methods, where GAP (or Group Contributions) assumes that sub-monomer motifs contribute additively to $T_{\! \textrm{g}}$, and QSPR links $T_{\! \textrm{g}}$ to the physico-chemical properties of the structure through a set of molecular descriptors. This method yields fast and accurate predictions of $T_{\! \textrm{g}}$ for polymers based on chemical motifs outside the data sample, which resolves the main limitation of the GAP approach. Using a genetic algorithm, we show that only two molecular descriptors are necessary to predict $T_{\! \textrm{g}}$ for PAEK polymers. Our QSPR-GAP method is readily transferred to other physical properties, to measures of activity (QSAR), or to different classes of polymers such as conjugated or bio-polymers., Comment: 12 pages, 4 figures, 1 table; Supplementary Information: 21 pages, 20 figures, 5 tables

Kagome superconductors AV$_{3}$Sb$_{5}$ provide a unique platform for studying the interplay between a variety of electronic orders, including superconductivity, charge density waves, nematic phases and more. Understanding the evolution of the electronic state from the charge density wave to the superconducting transition is essential for unraveling the interplay of charge, spin, and lattice degrees of freedom giving rise to the unusual magnetic properties of these nonmagnetic metals. Previous zero-field and high-field $\mu$SR studies revealed two anomalies in the muon spin relaxation rate, a first change at $T_{CDW} \sim 100$ K and a second steep increase at $T^{*}\sim 40$ K, further enhanced by an applied magnetic field, thus suggesting a contribution of magnetic origin. In this study, we use the avoided level crossing $\mu$SR technique to investigate charge order in near-zero applied field. By tracking the temperature dependence of quadrupolar level-crossing resonances, we examined the evolution of the electric field gradient at V nuclei in the kagome plane. Our results show a significant rearrangement of the charge density starting at $T^{*}$ indicating a transition in the charge distribution, likely electronic in origin, well below $T_{CDW}$. These findings, combined with previous $\mu$SR, STM, and NMR studies, emphasize the intertwined nature of proximate phases in these systems, with the charge rearrangement dominating the additional increase in $\mu$SR relaxation rate below $T^{*}$.

Robust estimation provides essential tools for analyzing data that contain outliers, ensuring that statistical models remain reliable even in the presence of some anomalous data. While robust methods have long been available in R, users of Python have lacked a comprehensive package that offers these methods in a cohesive framework. RobPy addresses this gap by offering a wide range of robust methods in Python, built upon established libraries including NumPy, SciPy, and scikit-learn. This package includes tools for robust preprocessing, univariate estimation, covariance matrices, regression, and principal component analysis, which are able to detect outliers and to mitigate their effect. In addition, RobPy provides specialized diagnostic plots for visualizing casewise and cellwise outliers. This paper presents the structure of the RobPy package, demonstrates its functionality through examples, and compares its features to existing implementations in other statistical software. By bringing robust methods to Python, RobPy enables more users to perform robust data analysis in a modern and versatile programming language.

Recent developments in Multiple-Input-Multiple-Output (MIMO) technology include packing a large number of antenna elements in a compact array to access the bandwidth benefits provided by higher mutual coupling (MC). The resulting super-wideband (SW) systems require a circuit-theoretic framework to handle the MC and channel models which span extremely large bands. Hence, in this paper, we make two key contributions. First, we develop a physically-consistent Rician channel model for use with SW systems. Secondly, we express the circuit-theoretic models in terms of a standard MIMO model, so that insights into the effects of antenna layouts, MC, and bandwidth can be made using standard communication theory. For example, we show the bandwidth widening resulting from the new channel model. In addition, we show that MC distorts line-of-sight paths which has beamforming implications. We also highlight the interaction between spatial correlation and MC and show that tight coupling reduces spatial correlations at low frequencies., Comment: This paper has been submitted to the IEEE for possible publication

We experimentally investigate on-chip control and analysis of spatially multimode nonlinear interactions in silicon nitride waveguide circuits. Using widely different dispersion of transverse supermodes in a strongly-coupled dual-core waveguide section, and using integrated pairs of input and output single-mode waveguides, we enable controlled excitation of nonlinear processes in multiple supermodes, while a basic physical mode decomposition aids the identification of parallel and cascaded processes. Pumping with ultrashort pulses at 1.5-$\mu$m wavelength (around 195-THz light frequency), we observe simultaneous dual-supermode, near-infrared supercontinuum generation having different spectral widths, in parallel with third-harmonic generation at around 515 nm (582 THz). Cascaded four-wave mixing with supercontinuum components upconverts the third-harmonic radiation toward a set of four shorter blue wavelengths emitted in the range between 485 and 450 nm (617 to 661 THz). The approach taken here, i.e., using chip-integrated spatial multiplexing and demultiplexing for excitation and analysis of broadband transverse nonlinear conversion, can be an advanced tool for better understanding and control in multimode nonlinear optics, such as for extending frequency conversion to wider spectral ranges via extra phase matching paths., Comment: 13 pages, 8 figures

This paper makes some preliminary observations towards an extension of current work on graphs defined on groups to simplicial complexes. I define a variety of simplicial complexes on a group which are preserved by automorphisms of the group, and in many cases have a relation to familiar graphs on the group. The ones which seem to reach deepest into the graph structure are two forms of independence complex, and some results on the class of groups for which these two complexes coincide are given. Other examples are treated more briefly., Comment: error in comment corrected

Faster pathfinding in time-dependent transport networks is an important and challenging problem in navigation systems. There are two main types of transport networks: road networks for car driving and public transport route network. The solutions that work well in road networks, such as Time-dependent Contraction Hierarchies and other graph-based approaches, do not usually apply in transport networks. In transport networks, non-graph solutions such as CSA and RAPTOR show the best results compared to graph-based techniques. In our work, we propose a method that advances graph-based approaches by using different optimization techniques from computational geometry to speed up the search process in transport networks. We apply a new pre-computation step, which we call timetable nodes (TTN). Our inspiration comes from an iterative search problem in computational geometry. We implement two versions of the TTN: one uses a Combined Search Tree (TTN-CST), and the second uses Fractional Cascading (TTN-FC). Both of these approaches decrease the asymptotic complexity of reaching new nodes from $O(k\times \log|C|)$ to $O(k + \log(k) + \log(|C|))$, where $k$ is the number of outgoing edges from a node and $|C|$ is the size of the timetable information (total outgoing edges). Our solution suits any other time-dependent networks and can be integrated into other pathfinding algorithms. Our experiments indicate that this pre-computation significantly enhances the performance on high-density graphs. This study showcases how leveraging computational geometry can enhance pathfinding in transport networks, enabling faster pathfinding in scenarios involving large numbers of outgoing edges.

Seamlessly integrating stimulated Brillouin scattering (SBS) in a low-loss and mature photonic integration platform remains a complicated task. Virtually all current approaches fall short in simultaneously achieving strong SBS, low losses, and technological scalability. In this work we incorporate stong SBS into a standard silicon nitride platform by a simple deposition of a tellurium oxide layer, a commonly used material for acousto-optic modulators. In these heterogeneously integrated waveguides, we harness novel SBS interactions actuated by surface acoustic waves (SAWs) leading to more than two orders of magnitude gain enhancement. Three novel applications are demonstrated in this platform: (i) a silicon nitride Brillouin amplifier with 5 dB net optical gain, (ii) a compact intermodal stimulated Brillouin laser (SBL) capable of high purity radio frequency (RF) signal generation with 7 Hz intrinsic linewidth, and (iii) a widely tunable microwave photonic notch filter with ultra-narrow linewidth of 2.2 MHz enabled by Brillouin induced opacity. These advancements can unlock an array of new RF and optical technologies to be directly integrated in silicon nitride.

The use of machine learning (ML) algorithms in molecular simulations has become commonplace in recent years. There now exists, for instance, a multitude of ML force field algorithms that have enabled simulations approaching ab initio level accuracy at time scales and system sizes that significantly exceed what is otherwise possible with traditional methods. Far fewer algorithms exist for predicting rotationally equivariant, tensorial properties such as the electric polarizability. Here, we introduce a kernel ridge regression algorithm for machine learning of the polarizability tensor. This algorithm is based on the bond polarizability model and allows prediction of the tensor components at the cost similar to that of scalar quantities. We subsequently show the utility of this algorithm by simulating gas phase Raman spectra of biphenyl and malonaldehyde using classical molecular dynamics simulations of these systems performed with the recently developed MACE-OFF23 potential. The calculated spectra are shown to agree very well with the experiments and thus confirm the expediency of our algorithm as well as the accuracy of the used force field. More generally, this work demonstrates the potential of physics-informed approaches to yield simple yet effective machine learning algorithms for molecular properties.

Despite the practical success of Artificial Intelligence (AI), current neural AI algorithms face two significant issues. First, the decisions made by neural architectures are often prone to bias and brittleness. Second, when a chain of reasoning is required, neural systems often perform poorly. Neuro-symbolic artificial intelligence is a promising approach that tackles these (and other) weaknesses by combining the power of neural perception and symbolic reasoning. Meanwhile, the success of AI has made it critical to understand its behaviour, leading to the development of explainable artificial intelligence (XAI). While neuro-symbolic AI systems have important advantages over purely neural AI, we still need to explain their actions, which are obscured by the interactions of the neural and symbolic components. To address the issue, this paper proposes a formal approach to explaining the decisions of neuro-symbolic systems. The approach hinges on the use of formal abductive explanations and on solving the neuro-symbolic explainability problem hierarchically. Namely, it first computes a formal explanation for the symbolic component of the system, which serves to identify a subset of the individual parts of neural information that needs to be explained. This is followed by explaining only those individual neural inputs, independently of each other, which facilitates succinctness of hierarchical formal explanations and helps to increase the overall performance of the approach. Experimental results for a few complex reasoning tasks demonstrate practical efficiency of the proposed approach, in comparison to purely neural systems, from the perspective of explanation size, explanation time, training time, model sizes, and the quality of explanations reported.

Li-ion battery performance is strongly influenced by their cathodes' properties and consequently by the 3D microstructure of the particles the cathodes are comprised of. During calendaring and cycling, cracks develop within cathode particles, which may affect performance in multiple ways. On the one hand, cracks reduce internal connectivity such that electron transport within cathode particles is hindered. On the other hand, intra-particle cracks can increase the cathode reactive surface. Due to these contradictory effects, it is necessary to quantitatively investigate how battery cycling effects cracking and how cracking in-turn influences battery performance. Thus, it is necessary to characterize the 3D particle morphology with structural descriptors and quantitatively correlate them with effective battery properties. Typically, 3D structural characterization is performed using image data. However, informative 3D imaging techniques are time-consuming, costly and rarely available, such that analyses often have to rely on 2D image data. This paper presents a novel stereological approach for generating virtual 3D cathode particles that exhibit crack networks that are statistically equivalent to those observed in 2D sections of experimentally measured particles. Consequently, more easily available 2D image data suffices for deriving a full 3D characterization of cracked cathodes particles. In future research, the virtually generated 3D particles will be used as geometry input for spatially resolved electro-chemo-mechanical simulations, to enhance our understanding of structure-property relationships of cathodes in Li-ion batteries.

We realize a single-Josephson-junction transmon qubit shunted by a simple geometric inductor. We couple it capacitively to a conventional transmon and show that the ZZ interaction between the two qubits is completely suppressed when they are flux-biased to have opposite-sign anharmonicities. Away from the flux sweet spot of the inductively-shunted transmon, we demonstrate fast two-qubit interactions using first-order sideband transitions. The simplicity of this two-qubit-species circuit makes it promising for building large lattices of superconducting qubits with low coherent error and a rich gate set.

Sub-Neptune planets with radii smaller than Neptune (3.9 Re) are the most common type of planet known to exist in The Milky Way, even though they are absent in the Solar System. These planets can potentially have a large diversity of compositions as a result of different mixtures of rocky material, icy material and gas accreted from a protoplanetary disk. However, the bulk density of a sub-Neptune, informed by its mass and radius alone, cannot uniquely constrain its composition; atmospheric spectroscopy is necessary. GJ 1214 b, which hosts an atmosphere that is potentially the most favorable for spectroscopic detection of any sub-Neptune, is instead enshrouded in aerosols (thus showing no spectroscopic features), hiding its composition from view at previously observed wavelengths in its terminator. Here, we present a JWST NIRSpec transmission spectrum from 2.8 to 5.1 um that shows signatures of carbon dioxide and methane, expected at high metallicity. A model containing both these molecules is preferred by 3.3 and 3.6 sigma as compared to a featureless spectrum for two different data analysis pipelines, respectively. Given the low signal-to-noise of the features compared to the continuum, however, more observations are needed to confirm the carbon dioxide and methane signatures and better constrain other diagnostic features in the near-infrared. Further modeling of the planet's atmosphere, interior structure and origins will provide valuable insights about how sub-Neptunes like GJ 1214 b form and evolve., Comment: 22 pages, 11 figures, Accepted in ApJL, Please also see a companion paper Ohno et al. (2024)

We present a transmission spectrum of the misaligned hot Jupiter WASP-15b from 2.8--5.2 microns observed with JWST's NIRSpec/G395H grating. Our high signal to noise data, which has negligible red noise, reveals significant absorption by H$_2$O ($4.2\sigma$) and CO$_2$ ($8.9\sigma$). From independent data reduction and atmospheric retrieval approaches, we infer that WASP-15b's atmospheric metallicity is super-solar ($\gtrsim 15\times$ solar) and its C/O is consistent with solar, that together imply planetesimal accretion. Our GCM simulations for WASP-15b suggest that the C/O we measure at the limb is likely representative of the entire photosphere due to the mostly uniform spatial distribution of H$_2$O, CO$_2$ and CO. We additionally see evidence for absorption by SO$_2$ and absorption at 4.9$\mu$m, for which the current leading candidate is OCS, albeit with several caveats. If confirmed, this would be the first detection of OCS in an exoplanet atmosphere and point towards complex photochemistry of sulphur-bearing species in the upper atmosphere. These are the first observations from the BOWIE-ALIGN survey which is using JWST's NIRSpec/G395H instrument to compare the atmospheric compositions of aligned/low-obliquity and misaligned/high-obliquity hot Jupiters around F stars above the Kraft break. The goal of our survey is to determine whether the atmospheric composition differs across two populations of planets that have likely undergone different migration histories (disc versus disc-free) as evidenced by their obliquities (aligned versus misaligned)., Comment: 24 pages, 23 figures, 6 tables. Submitted to MNRAS

Modern archaeological methods increasingly utilize 3D virtual representations of objects, computationally intensive analyses, high resolution scanning, large datasets, and machine learning. With higher resolution scans, challenges surrounding computational power, memory, and file storage quickly arise. Processing and analyzing high resolution scans often requires memory-intensive workflows, which are infeasible for most computers and increasingly necessitate the use of super-computers or innovative methods for processing on standard computers. Here we introduce a novel protocol for en-masse micro-CT scanning of small objects with a {\em mostly-automated} processing workflow that functions in memory-limited settings. We scanned 1,112 animal bone fragments using just 10 micro-CT scans, which were post-processed into individual PLY files. Notably, our methods can be applied to any object (with discernible density from the packaging material) making this method applicable to a variety of inquiries and fields including paleontology, geology, electrical engineering, and materials science. Further, our methods may immediately be adopted by scanning institutes to pool customer orders together and offer more affordable scanning. The work presented herein is part of a larger program facilitated by the international and multi-disciplinary research consortium known as Anthropological and Mathematical Analysis of Archaeological and Zooarchaeological Evidence (AMAAZE). AMAAZE unites experts in anthropology, mathematics, and computer science to develop new methods for mass-scale virtual archaeological research. Overall, our new scanning method and processing workflows lay the groundwork and set the standard for future mass-scale, high resolution scanning studies., Comment: 36 pages, 12 figures, 2 tables. Source code available at https://github.com/oneil571/AMAAZE-MCT-Processing

We present an adaptation of the exoplanet transit model code batman, in order to permit the generation of X-ray transits. Our underlying extended coronal model assumes an isothermal plasma that is radially symmetric. While this ignores the effect of bright, active regions, observations of transits in X-rays will require averaging across multiple epochs of data for the foreseeable future, significantly reducing the importance of more complex modelling. Our publicly available code successfully generates the predicted W-shaped transit profile in X-rays due to the optically thin nature of the emission, which concentrates the expected observational emission around the limb of the photospheric stellar disc. We provide some examples based on the best known X-ray transit target, HD 189733b, and examine the effect of varying the planet size, coronal temperature, and impact parameter on the resulting transit profile. We also derived scaling relationships for how the overall transit detectability is affected by changing these parameters. Over most of the parameter space, we find that the detectability scales linearly with the cross-sectional area of the planet in X-rays. The relationship with increasing coronal temperature is less fixed, but averages out to a power law with slope $-1/4$ except when the impact parameter is high. Indeed, varying impact parameter has little effect on detectability at all until it approaches unity., Comment: 16 pages, 8 figures, 2 tables. Accepted for publication in the Astronomical Journal. Code available at https://github.com/georgewking/batmanX-rays

We present a study of a previously identified candidate ``jellyfish'' galaxy in the Abell 2744 cluster, F0083, which showed faint signs of a tidal interaction in archival imaging. We used publicly available, PSF-matched deep photometric data from the Hubble and James Webb Space Telescopes, to infer the spatially-resolved star-formation history of this galaxy. F0083 shows clear signs of ram-pressure stripping (RPS), with a recently enhanced star-formation rate (SFR) orientated towards the South-West quadrant of the stellar disc. The stellar mass surface density is heavily asymmetric, with a variation of nearly 1 dex between the Western spiral arm and the postulated tidal feature. This feature appears to contain a high proportion of older stars, ruling out RPS as the cause of this ``unwinding''. An investigation of nearby galaxies reveals the most probable interaction candidate to be a compact elliptical galaxy, 28171, of mass $\log_{10}(M_*/\rm{M}_{\odot})=8.53\pm0.04$ embedded in the tidal stream along our line-of-sight. The star-formation history of the tidal feature indicates a steep change in SFR at lookback times $t_L\lesssim1\,$Gyr. The most probable formation scenario of F0083 thus indicates a low-speed interaction with 28171, followed by RPS as the combined system approaches pericentre passage. Our results demonstrate the ability of photometric data to distinguish between these consecutive processes., Comment: 18 pages, 14 figures. Submitted to A&A

In order to solve problems of practical importance, quantum computers will likely need to incorporate quantum error correction, where a logical qubit is redundantly encoded in many noisy physical qubits. The large physical-qubit overhead typically associated with error correction motivates the search for more hardware-efficient approaches. Here, using a microfabricated superconducting quantum circuit, we realize a logical qubit memory formed from the concatenation of encoded bosonic cat qubits with an outer repetition code of distance $d=5$. The bosonic cat qubits are passively protected against bit flips using a stabilizing circuit. Cat-qubit phase-flip errors are corrected by the repetition code which uses ancilla transmons for syndrome measurement. We realize a noise-biased CX gate which ensures bit-flip error suppression is maintained during error correction. We study the performance and scaling of the logical qubit memory, finding that the phase-flip correcting repetition code operates below threshold, with logical phase-flip error decreasing with code distance from $d=3$ to $d=5$. Concurrently, the logical bit-flip error is suppressed with increasing cat-qubit mean photon number. The minimum measured logical error per cycle is on average $1.75(2)\%$ for the distance-3 code sections, and $1.65(3)\%$ for the longer distance-5 code, demonstrating the effectiveness of bit-flip error suppression throughout the error correction cycle. These results, where the intrinsic error suppression of the bosonic encodings allows us to use a hardware-efficient outer error correcting code, indicate that concatenated bosonic codes are a compelling paradigm for reaching fault-tolerant quantum computation., Comment: Comments on the manuscript welcome!

Single Transferable Vote (STV) counting, used in several jurisdictions in Australia, is a system for choosing multiple election winners given voters' preferences over candidates. There are a variety of different versions of STV legislated and/or applied across Australia. This paper shows some of the unintuitive properties of some of these systems.

Let $G$ be a transitive permutation group on $\Omega$. The $G$-invariant partitions form a sublattice of the lattice of all partitions of $\Omega$, having the further property that all its elements are uniform (that is, have all parts of the same size). If, in addition, all the equivalence relations defining the partitions commute, then the relations form an \emph{orthogonal block structure}, a concept from statistics; in this case the lattice is modular. If it is distributive, then we have a \emph{poset block structure}, whose automorphism group is a \emph{generalised wreath product}. We examine permutation groups with these properties, which we call the \emph{OB property} and \emph{PB property} respectively, and in particular investigate when direct and wreath products of groups with these properties also have these properties. A famous theorem on permutation groups asserts that a transitive imprimitive group $G$ is embeddable in the wreath product of two factors obtained from the group (the group induced on a block by its setwise stabiliser, and the group induced on the set of blocks by~$G$). We extend this theorem to groups with the PB property, embeddng them into generalised wreath products. We show that the map from posets to generalised wreath products preserves intersections and inclusions. We have included background and historical material on these concepts., Comment: Embedding theorem strengthened

This paper addresses the problem of autonomous UAV search missions, where a UAV must locate specific Entities of Interest (EOIs) within a time limit, based on brief descriptions in large, hazard-prone environments with keep-out zones. The UAV must perceive, reason, and make decisions with limited and uncertain information. We propose NEUSIS, a compositional neuro-symbolic system designed for interpretable UAV search and navigation in realistic scenarios. NEUSIS integrates neuro-symbolic visual perception, reasoning, and grounding (GRiD) to process raw sensory inputs, maintains a probabilistic world model for environment representation, and uses a hierarchical planning component (SNaC) for efficient path planning. Experimental results from simulated urban search missions using AirSim and Unreal Engine show that NEUSIS outperforms a state-of-the-art (SOTA) vision-language model and a SOTA search planning model in success rate, search efficiency, and 3D localization. These results demonstrate the effectiveness of our compositional neuro-symbolic approach in handling complex, real-world scenarios, making it a promising solution for autonomous UAV systems in search missions.

In this work we demonstrate a NASICON film sintered in situ onto a fused silica substrate. This production method drastically reduces the manufacturing time by combining the use of a spray-coated sol-gel solution and near-infrared (NIR) ultrafast sintering technology. The first demonstration of NIR sintered ceramics at high temperatures (~1000$^\circ$C).

These problems were mostly presented at the problem session at the 30th British Combinatorial Conference at Queen Mary University of London on 4 July 2024. Some were contributed later by conference participants. Thank you to all the contributors. The problems are given here in alphabetical order of presenter. If no originator is given, I assume that the presenter is the originator. Please send corrections to me (\texttt{pjc20@st-andrews.ac.uk}). Solutions should be sent to the presenter; I would appreciate a copy too., Comment: 22 problems from the conference, edited by Peter J. Cameron

Mode-locked lasers are of interest for applications such as biological imaging, non-linear frequency conversion, and single-photon generation. In the infrared, chip-integrated mode-locked lasers have been demonstrated through integration of laser diodes with low-loss photonic circuits. However additional challenges, such as a higher propagation loss and smaller alignment tolerances have prevented the realization of such lasers in the visible range. Here, we demonstrate the first chip-integrated mode-locked diode laser in the visible using an integrated photonic circuit for cavity extension. Based on a gallium arsenide gain chip and a low-loss silicon nitride feedback circuit, the laser is passively mode-locked using a saturable absorber implemented by focused ion beam milling. At a center wavelength of 642 nm, the laser shows an average output power of 3.4 mW, with a spectral bandwidth of 1.5 nm at a repetition rate of 7.84 GHz., Comment: 7 pages, 4 figures

The ensemble inter-relations to be considered are special features of classical cases, where the joint eigenvalue probability density can be computed explicitly. Attention will be focussed too on the consequences of these inter-relations, most often in relation to gap probabilities. A highlight from this viewpoint is an evaluation formula for the gap probability generating function for the circular orthogonal and circular symplectic ensembles (examples of Pfaffian point processes), in terms of the gap probability generating function for real orthogonal matrices chosen with Haar measure ensembles (examples of determinantal point processes). The classes of inter-relations which lead to this result involve the superposition of the eigenvalue point processes of two independent classical ensembles, or consideration of the singular values of the classical ensembles with an evenness symmetry, and the decimation operation of integrating over every second eigenvalue. It turns out that the probability density functions encountered through the consideration of superposition and decimation can in some cases be obtained via the consideration of various rank one matrix perturbations. These allow for different understandings of some of the inter-relations in this class. We make note too of inter-relations -- which we consider generally as an identity or evaluation formula of a statistic linking two distinct random matrix ensemble -- that fall outside of this class, applying to the spectral form factor, and ones relating to discrete determinantal point processes. Not part of our review are the so-called duality relations of random matrix theory. Their consideration warrants a separate discussion., Comment: 24 pages, expository paper prepared for a forthcoming volume in the KIAS Springer Series in Mathematics

The power spectrum is a Fourier series statistic associated with the covariances of the displacement from average positions of the members of an eigen-sequence. When this eigen-sequence has rotational invariance, as for the eigen-angles of Dyson's circular ensembles, recent work of Riser and Kanzieper has uncovered an exact identity expressing the power spectrum in terms of the generating function for the conditioned gap probability of having $k$ eigenvalues in an interval. These authors moreover showed how for the circular unitary ensemble integrability properties of the generating function, via a particular Painlev\'e VI system, imply a computational scheme for the corresponding power spectrum, and allow for the determination of its large $N$ limit. In the present work, these results are extended to the case of the circular orthogonal ensemble and circular symplectic ensemble, where the integrability is expressed through four particular Painlev\'e VI systems for finite $N$, and two Painlev\'e III$'$ systems for the limit $N\to\infty$, and also via corresponding Fredholm determinants. The relation between the limiting power spectrum $S_\infty(\omega)$, where $\omega$ denotes the Fourier variable, and the limiting generating function for the conditioned gap probabilities is particular direct, involving just a single integration over the gap endpoint in the latter. Interpreting this generating function as the characteristic function of a counting statistic allows for it to be shown that $S_\infty(\omega) \mathop{\sim} \limits_{\omega \to 0} {1 \over \pi \beta | \omega|}$, where $\beta$ is the Dyson index., Comment: 26 pages

Discriminant analysis (DA) is one of the most popular methods for classification due to its conceptual simplicity, low computational cost, and often solid performance. In its standard form, DA uses the arithmetic mean and sample covariance matrix to estimate the center and scatter of each class. We discuss and illustrate how this makes standard DA very sensitive to suspicious data points, such as outliers and mislabeled cases. We then present an overview of techniques for robust DA, which are more reliable in the presence of deviating cases. In particular, we review DA based on robust estimates of location and scatter, along with graphical diagnostic tools for visualizing the results of DA., Comment: Accepted for publication in WIREs Computational Statistics (Wiley Interdisciplinary Reviews)

Principal component analysis (PCA) is a fundamental tool for analyzing multivariate data. Here the focus is on dimension reduction to the principal subspace, characterized by its projection matrix. The classical principal subspace can be strongly affected by the presence of outliers. Traditional robust approaches consider casewise outliers, that is, cases generated by an unspecified outlier distribution that differs from that of the clean cases. But there may also be cellwise outliers, which are suspicious entries that can occur anywhere in the data matrix. Another common issue is that some cells may be missing. This paper proposes a new robust PCA method, called cellPCA, that can simultaneously deal with casewise outliers, cellwise outliers, and missing cells. Its single objective function combines two robust loss functions, that together mitigate the effect of casewise and cellwise outliers. The objective function is minimized by an iteratively reweighted least squares (IRLS) algorithm. Residual cellmaps and enhanced outlier maps are proposed for outlier detection. The casewise and cellwise influence functions of the principal subspace are derived, and its asymptotic distribution is obtained. Extensive simulations and two real data examples illustrate the performance of cellPCA.

Image classification usually requires connectivity and access to the cloud which is often limited in many parts of the world, including hard to reach rural areas. TinyML aims to solve this problem by hosting AI assistants on constrained devices, eliminating connectivity issues by processing data within the device itself, without internet or cloud access. This pilot study explores the use of tinyML to provide healthcare support with low spec devices in low connectivity environments, focusing on diagnosis of skin diseases and the ethical use of AI assistants in a healthcare setting. To investigate this, 10,000 images of skin lesions were used to train a model for classifying visually detectable diseases (VDDs). The model weights were then offloaded to a Raspberry Pi with a webcam attached, to be used for the classification of skin lesions without internet access. It was found that the developed prototype achieved a test accuracy of 78% and a test loss of 1.08., Comment: 6 pages, 5 figures

Mammalian functional architecture flexibly adapts, transitioning from integration where information is distributed across the cortex, to segregation where information is focal in densely connected communities of brain regions. This flexibility in cortical brain networks is hypothesized to be driven by control signals originating from subcortical pathways, with the basal ganglia shifting the cortex towards integrated processing states and the cerebellum towards segregated states. In a sample of healthy human participants (N=242), we used fMRI to measure temporal variation in global brain networks while participants performed two tasks with similar cognitive demands (Stroop and Multi-Source Inference Task (MSIT)). Using the modularity index, we determined cortical networks shifted from integration (low modularity) at rest to high modularity during easier i.e. congruent (segregation). Increased task difficulty (incongruent) resulted in lower modularity in comparison to the easier counterpart indicating more integration of the cortical network. Influence of basal ganglia and cerebellum was measured using eigenvector centrality. Results correlated with decreases and increases in cortical modularity respectively, with only the basal ganglia influence preceding cortical integration. Our results support the theory the basal ganglia shifts cortical networks to integrated states due to environmental demand. Cerebellar influence correlates with shifts to segregated cortical states, though may not play a causal role.

While many capabilities of language models (LMs) improve with increased training budget, the influence of scale on hallucinations is not yet fully understood. Hallucinations come in many forms, and there is no universally accepted definition. We thus focus on studying only those hallucinations where a correct answer appears verbatim in the training set. To fully control the training data content, we construct a knowledge graph (KG)-based dataset, and use it to train a set of increasingly large LMs. We find that for a fixed dataset, larger and longer-trained LMs hallucinate less. However, hallucinating on $\leq5$% of the training data requires an order of magnitude larger model, and thus an order of magnitude more compute, than Hoffmann et al. (2022) reported was optimal. Given this costliness, we study how hallucination detectors depend on scale. While we see detector size improves performance on fixed LM's outputs, we find an inverse relationship between the scale of the LM and the detectability of its hallucinations., Comment: Published at COLM 2024. 16 pages, 11 figures

We present an error mitigation strategy composed of Echo Verification (EV) and Clifford Data Regression (CDR), the combination of which allows one to learn the effect of the quantum noise channel to extract error mitigated estimates for the expectation value of Pauli observables. We analyse the behaviour of the method under the depolarizing channel and derive an estimator for the depolarization rate in terms of the ancilla purity and postselection probability. We also highlight the sensitivity of this probability to noise, a potential bottleneck for the technique. We subsequently consider a more general noise channel consisting of arbitrary Pauli errors, which reveals a linear relationship between the error rates and the estimation of expectation values, suggesting the learnability of noise in EV by regression techniques. Finally, we present a practical demonstration of Echo Verified Clifford Data Regression (EVCDR) on a superconducting quantum computer and observe accurate results for the time evolution of an Ising model over a spin-lattice consisting of up to 35 sites and circuit depths in excess of 1,000., Comment: 15 pages, 13 figures

To enhance the variational quantum eigensolver (VQE), the CAFQA method can utilize classical computational capabilities to identify a better initial state than the Hartree-Fock method. Previous research has demonstrated that the initial state provided by CAFQA recovers more correlation energy than that of the Hartree-Fock method and results in faster convergence. In the present study, we advance the investigation of CAFQA by demonstrating its advantages on a high-fidelity trapped-ion quantum computer located at the Duke Quantum Center -- this is the first experimental demonstration of CAFQA-bootstrapped VQE on a TI device and on any academic quantum device. In our VQE experiment, we use LiH and BeH$_2$ as test cases to show that CAFQA achieves faster convergence and obtains lower energy values within the specified computational budget limits. To ensure the seamless execution of VQE on this academic device, we develop a novel hardware-software interface framework that supports independent software environments for both the circuit and hardware end. This mechanism facilitates the automation of VQE-type job executions as well as mitigates the impact of random hardware interruptions. This framework is versatile and can be applied to a variety of academic quantum devices beyond the trapped-ion quantum computer platform, with support for integration with customized packages.

We report the discovery of the most eccentric transiting brown dwarf in the brown dwarf desert, TOI02490b. The brown dwarf desert is the lack of brown dwarfs around main sequence stars within $\sim3$~AU and is thought to be caused by differences in formation mechanisms between a star and planet. To date, only $\sim40$ transiting brown dwarfs have been confirmed. \systemt is a $73.6\pm2.4$ \mjupnospace, $1.00\pm0.02$ \rjup brown dwarf orbiting a $1.004_{-0.022}^{+0.031}$ \msunnospace, $1.105_{-0.012}^{+0.012}$ \rsun sun-like star on a 60.33~d orbit with an eccentricity of $0.77989\pm0.00049$. The discovery was detected within \tess sectors 5 (30 minute cadence) and 32 (2 minute and 20 second cadence). It was then confirmed with 31 radial velocity measurements with \feros by the WINE collaboration and photometric observations with the Next Generation Transit Survey. Stellar modelling of the host star estimates an age of $\sim8$~Gyr, which is supported by estimations from kinematics likely placing the object within the thin disc. However, this is not consistent with model brown dwarf isochrones for the system age suggesting an inflated radius. Only one other transiting brown dwarf with an eccentricity higher than 0.6 is currently known in the brown dwarf desert. Demographic studies of brown dwarfs have suggested such high eccentricity is indicative of stellar formation mechanisms., Comment: Accepted for publication in MNRAS, 18 pages, 14 figures

Let $G$ be a group. Associate a graph $\mathcal{E}_G$ (called the co-Engel graph of $G$) with $G$ whose vertex set is $G$ and two distinct vertices $x$ and $y$ are adjacent if $[x, {}_k y] \neq 1$ and $[y, {}_k x] \neq 1$ for all positive integer $k$. This graph, under the name ``Engel graph'', was introduced by Abdollahi. Let $L(G)$ be the set of all left Engel elements of $G$. In this paper, we realize the induced subgraph of co-Engel graphs of certain finite non-Engel groups $G$ induced by $G \setminus L(G)$. We write $\mathcal{E}^-(G)$ to denote the subgraph of $\mathcal{E}_G$ induced by $G \setminus L(G)$. We also compute genus, various spectra, energies and Zagreb indices of $\mathcal{E}^-(G)$ for those groups. As a consequence, we determine (up to isomorphism) all finite non-Engel group $G$ such that the clique number is at most $4$ and $\mathcal{E}^-$ is toroidal or projective. Further, we show that $\coeng{G}$ is super integral and satisfies the E-LE conjecture and the Hansen--Vuki{\v{c}}evi{\'c} conjecture for the groups considered in this paper.

Since the first demonstration of optical refrigeration in a rare-earth-doped glass nearly 30 years ago, the nascent field of laser cooling solids has progressed significantly. It is now possible to demonstrate payload cooling to ~91 K using laser-excited ytterbium-doped fluoride crystals. Realizing lower temperatures, however, requires achieving ultrahigh purities in existing rare earth-doped crystals or establishing new cooling media. For the latter, semiconductors are an obvious choice given higher cooling power densities and predicted cooling floors as low as 10 K. This has stimulated a race to demonstrate the optical refrigeration of a semiconductor. It is therefore timely to systematize the necessary and sufficient experimental minimum criteria for reporting optical refrigeration results to elevate the reliability and reproducibility of current and future optical refrigeration claims. We distill an optical refrigeration Experimental Minimum (EM) that we propose will standardize the reporting of new cooling results. EM tenets fall into the following categories: demonstrations of explicit heating vs cooling, optical cooling metrics, thermodynamic consistency, and reliable temperature measurements. All optical refrigeration claims should demonstrate the above four criteria to ensure their reliability and verifiability. We further propose that the EM serve as a guide for reviewing literature claims in the field.

The gas-phase velocity dispersions in disk galaxies, which trace turbulence in the interstellar medium, are observed to increase with lookback time. However, the mechanisms that set this rise in turbulence are observationally poorly constrained. To address this, we combine kiloparsec-scale ALMA observations of CO(3-2) and CO(4-3) with HST observations of H$\alpha$ to characterize the molecular gas and star formation properties of seven local analogues of main sequence galaxies at $z \sim 1-2$, drawn from the DYNAMO sample. Investigating the ''molecular gas main sequence'' on kpc-scales, we find that galaxies in our sample are more gas-rich than local star-forming galaxies at all disk positions. We measure beam smearing corrected molecular gas velocity dispersions and relate them to the molecular gas and star formation rate surface densities. Despite being relatively nearby ($z \sim 0.1$), DYNAMO galaxies exhibit high velocity dispersions and gas and star formation rate surface densities throughout their disks, when compared to local star forming samples. Comparing these measurements to predictions from star formation theory, we find very good agreements with the latest feedback-regulated star formation models. However, we find that theories which combine gravitational energy dissipation from radial gas transport with feedback over-estimate the observed molecular gas velocity dispersions., Comment: 24 pages, 12 figures, 2 tables, accepted for publication in The Astrophysical Journal

We apply a Bayesian agent-based framework inspired by QBism to iterations of two quantum games, the CHSH game and the quantum prisoners' dilemma. In each two-player game, players hold beliefs about an amount of shared entanglement and about the actions or beliefs of the other player. Each takes actions which maximize their expected utility and revises their beliefs with the classical Bayes rule between rounds. We simulate iterated play to see if and how players can learn about the presence of shared entanglement and to explore how their performance, their beliefs, and the game's structure interrelate. In the CHSH game, we find that players can learn that entanglement is present and use this to achieve quantum advantage. We find that they can only do so if they also believe the other player will act correctly to exploit the entanglement. In the case of low or zero entanglement in the CHSH game, the players cannot achieve quantum advantage, even in the case where they believe the entanglement is higher than it is. For the prisoners dilemma, we show that assuming 1-fold rational players (rational players who believe the other player is also rational) reduces the quantum extension [Eisert, Wilkens, and Lewenstein, Phys. Rev. Lett. 83, 3077 (1999)] of the prisoners dilemma to a game with only two strategies, one of which (defect) is dominant for low entanglement, and the other (the quantum strategy Q) is dominant for high entanglement. For intermediate entanglement, neither strategy is dominant. We again show that players can learn entanglement in iterated play. We also show that strong belief in entanglement causes optimal play even in the absence of entanglement -- showing that belief in entanglement is acting as a proxy for the players trusting each other. Our work points to possible future applications in resource detection and quantum algorithm design., Comment: 18 pages, 5 figures

Let A be a graph type and B an equivalence relation on a group $G$. Let $[g]$ be the equivalence class of $g$ with respect to the equivalence relation B. The B superA graph of $G$ is an undirected graph whose vertex set is $G$ and two distinct vertices $g, h \in G$ are adjacent if $[g] = [h]$ or there exist $x \in [g]$ and $y \in [h]$ such that $x$ and $y$ are adjacent in the A graph of $G$. In this paper, we compute spectrum of equality/conjugacy supercommuting graphs of dihedral/dicyclic groups and show that these graphs are not integral.

Let $k$ be a field that is finitely generated over its prime field. In Grothendieck's anabelian letter to Faltings, he conjectured that sending a $k$-scheme to its \'{e}tale topos defines a fully faithful functor from the localization of the category of finite type $k$-schemes at the universal homeomorphisms to a category of topoi. We prove Grothendieck's conjecture for infinite fields of arbitrary characteristic. In characteristic $0$, this shows that seminormal finite type $k$-schemes can be reconstructed from their \'{e}tale topoi, generalizing work of Voevodsky. In positive characteristic, this shows that perfections of finite type $k$-schemes can be reconstructed from their \'{e}tale topoi., Comment: Comments very welcome. 39 pages

AWAIRE is one of two extant methods for conducting risk-limiting audits of instant-runoff voting (IRV) elections. In principle AWAIRE can audit IRV contests with any number of candidates, but the original implementation incurred memory and computation costs that grew superexponentially with the number of candidates. This paper improves the algorithmic implementation of AWAIRE in three ways that make it practical to audit IRV contests with 55 candidates, compared to the previous 6 candidates. First, rather than trying from the start to rule out all candidate elimination orders that produce a different winner, the algorithm starts by considering only the final round, testing statistically whether each candidate could have won that round. For those candidates who cannot be ruled out at that stage, it expands to consider earlier and earlier rounds until either it provides strong evidence that the reported winner really won or a full hand count is conducted, revealing who really won. Second, it tests a richer collection of conditions, some of which can rule out many elimination orders at once. Third, it exploits relationships among those conditions, allowing it to abandon testing those that are unlikely to help. We provide real-world examples with up to 36 candidates and synthetic examples with up to 55 candidates, showing how audit sample size depends on the margins and on the tuning parameters. An open-source Python implementation is publicly available., Comment: 16 pages, 4 figures, accepted for E-Vote-ID 2024

Lack of standardization and various intrinsic parameters for magnetic resonance (MR) image acquisition results in heterogeneous images across different sites and devices, which adversely affects the generalization of deep neural networks. To alleviate this issue, this work proposes a novel unsupervised harmonization framework that leverages normalizing flows to align MR images, thereby emulating the distribution of a source domain. The proposed strategy comprises three key steps. Initially, a normalizing flow network is trained to capture the distribution characteristics of the source domain. Then, we train a shallow harmonizer network to reconstruct images from the source domain via their augmented counterparts. Finally, during inference, the harmonizer network is updated to ensure that the output images conform to the learned source domain distribution, as modeled by the normalizing flow network. Our approach, which is unsupervised, source-free, and task-agnostic is assessed in the context of both adults and neonatal cross-domain brain MRI segmentation, as well as neonatal brain age estimation, demonstrating its generalizability across tasks and population demographics. The results underscore its superior performance compared to existing methodologies. The code is available at https://github.com/farzad-bz/Harmonizing-Flows

A fundamental challenge in endoscopy is how to fabricate a small fiber-optic probe that can achieve comparable function to probes with large, complicated optics (e.g., high resolution and extended depth of focus). To achieve high resolution over an extended depth of focus (DOF), the application of needle-like beams has been proposed. However, existing methods using miniaturized needle beam designs fail to adequately correct astigmatism and other monochromatic aberrations, limiting the resolution of at least one axis. Here, we describe a novel approach to realize freeform beam-shaping endoscopic probes via two-photon direct laser writing, also known as micro 3D-printing. We present a design achieving approximately 8-micron resolution with a DOF of >0.8 mm at a central wavelength of 1310 nm. The probe has a diameter of 0.25 mm (without the catheter sheaths) and is fabricated using a single printing step directly on the optical fiber. We demonstrate our device in intravascular imaging of living atherosclerotic pigs at multiple time points, as well as human arteries with plaques ex vivo. This is the first step to enable beam-tailoring endoscopic probes which achieve diffraction-limited resolution over a large DOF.

Closed quantum systems follow a unitary time evolution that can be simulated on quantum computers. By incorporating non-unitary effects via, e.g., measurements on ancilla qubits, these algorithms can be extended to open-system dynamics, such as Markovian processes described by the Lindblad master equation. In this paper, we analyze the convergence criteria and the convergence speed of a Markovian, purely dissipative quantum random walk on an unstructured search space. We analytically derive the mixing time for continuous- and discrete-time processes for different coupling regimes that control the random walk. Then, we map the results onto an actual implementation to correctly estimate the potential and show that it is no more efficient than classical search. Despite this, we highlight the connections between the classical random walks and open quantum random walks and demonstrate how to recover a quadratic speedup in the unitary limit. Moreover, the study of the Grover problem reveals how the hyperparameters affect the cost of implementation. This helps us refine the complexity analysis of the investigated algorithm to simulate the Lindblad equation., Comment: 32 pages, 4 figures, submitted to Quantum Journal