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Peaked-spectrum (PS) sources, known for their distinct peaked radio spectra, represent a type of radio-loud active galactic nuclei (AGN). Among these, megahertz-peaked spectrum (MPS) sources, which exhibit a spectral peak at a frequency of a hundred megahertz, have emerged as a potential tool for identifying high-redshift candidates. However, the potential evolutionary link between the fraction of these sources and redshift remains unclear and requires further investigation. The recent, high sensitivity Low Frequency Array (LOFAR) surveys enable statistical studies of these objects to ultra-low frequencies (< 150 MHz). In this study, we first use the multiradio data to investigate the evolution of spectral index with redshift for 1,187 quasars from the SDSS 16th quasar catalog. For each quasar, we analyze available data from the LOFAR Low Band Antenna (LBA) at 54 MHz, High Band Antenna (HBA) at 144 MHz, and the Very Large Array (VLA) the Faint Images of the Radio Sky at Twenty cm (FIRST) at 1.4 GHz. We measure the spectral index ($\alpha^{144}_{54}$ and $\alpha^{1400}_{144}$) and find no significant change in their median values with the redshift. Extended sources have steeper spectral indices than compact sources, which is consistent with previous findings. Based on the spectral indices information, we identify MPS sources using these criteria: $\rm \alpha^{144}_{54} >= 0.1$ and $\rm \alpha^{1400}_{144} < 0$, and analyze their properties. We find that the fraction of MPS sources is constant with the redshift ($0.1-4.8$), bolometric luminosity ($\rm 10^{44}-10^{48} erg/s$), and supermassive black hole mass ($\rm 10^{7}-10^{10.5} M_{\odot}$), which suggests that MPS sources have relatively stable physical conditions or formation mechanisms across various evolutionary stages and environments., Comment: 8 pages, 6 figures. Accepted for publication in Astronomy & Astrophysics

We propose an approach based on Fourier analysis to wavenumber explicit sharp estimation of absolute and relative errors of finite difference methods for the Helmholtz equation. We use the approach to analyze the classical centred scheme for the Helmholtz equation with a general smooth source term and Dirichlet boundary conditions in 1D. For the Fourier interpolants of the discrete solution with homogeneous (or inhomogeneous) Dirichlet conditions, we show rigorously that the worst case attainable convergence order of the absolute error is k2h2 (or k3h2) in the L2-norm and k3h2 (or k4h2) in the H1-semi-norm, and that of the relative error is k3h2 in both L2- and H1-semi-norms. Even though the classical centred scheme is well-known, it is the first time that such sharp estimates of absolute and relative errors are obtained. We show also that the Fourier analysis approach can be used as a convenient visual tool for evaluating finite difference schemes in presence of source terms, which is beyond the scope of dispersion analysis., Comment: 30 pages, 21 figures

We combine the deepest X-ray survey from the Chandra Deep Field-South (CDF-S) `7-Ms' survey with the deepest mid-infrared (5.6$ \mu m$) image from the JWST/MIRI Deep Imaging Survey (MIDIS) in the Hubble Ultra-Deep Field (HUDF) to study the infrared counterparts and point-source emission of 31 X-ray sources with a median, intrinsic, rest-frame X-ray luminosity of $\log_{10}(L_{\rm Xc}^{\rm 0.5-7keV})$=42.04$\pm$0.22 erg $\rm s^{-1}$. The sample includes 24 AGN with a redshift range, as set by the X-ray detectability, of $z \simeq 0.5-3$. Through a multi-wavelength morphological decomposition, employing three separate classifications (visual, parametric and non-parametric) we separate (where present) the luminosity of the point-like AGN component from the remainder of the host-galaxy emission. The unprecedented mid-infrared sensitivity and imaging resolution of MIRI allows, in many cases, the direct characterisation of point-like (i.e. unresolved) components in the galaxies' emission. We establish a broad agreement between the three morphological classifications. At least 70% of the X-ray sources, including some classified as galaxies, show unresolved emission in the MIRI images, with the unresolved-to-total flux fraction at rest-frame 2$\mu m$ ranging from $\sim$0.2 to $\sim$0.9. At high X-ray luminosities ($\log_{10}(L_{\rm Xc}$)>43 erg $\rm s^{-1}$) we derive a consistent rest-frame near-infrared 2$ \mu m$ point-source luminosity to that derived for local AGN, whilst at lower X-ray luminosity we identify an excess in the 2$ \mu m$ emission compared to pre-JWST studies. We speculate this offset may be driven by a combination of Compton-thick AGN components and nuclear starburst, merger driven activity. Our observations highlight the complex nature of X-ray sources in the distant Universe and demonstrate the power of JWST/MIRI in quantifying their nuclear infrared emission. (Abridged), Comment: 21 pages, 7 figures. Submitted to A&A

In three-dimensional space an electron moving in the field of a magnetic monopole has no bound states. In this paper we explore the physics when the electron is restricted to a two-dimensional plane adjacent to a magnetic monopole. We find bound states in the classical version of the problem and quasi-bound states in the quantum one, in addition to a continuum of scattering states. We calculate the lifetimes of the quasi-bound states using several complementary approximate methods, which agree well in the cases where the lifetimes are relatively short. The threshold monopole magnetic charge required to realise a single quasi-bound state is approximately $18Q_D$, where $Q_D$ is the magnetic charge of a Dirac monopole. We examine the feasibility of achieving this magnetic charge in currently available monopole analogues: spin ice, artificial spin ice, and magnetic needles., Comment: 26 pages

Mechanical properties of minerals in planetary materials are not only interesting from a fundamental point of view but also critical to the development of future space missions. Here we present nanoindentation experiments to evaluate the hardness and reduced elastic modulus of olivine, (Mg,Fe)2SiO4, in meteorite NWA 12008, a lunar basalt. Our experiments suggest that the olivine grains in this lunaite are softer and more elastic than their terrestrial counterparts. This may be attributed to macroscopic effects, like increased porosity, or even to modifications at the chemical bond scale. We have performed high-pressure X-ray diffraction (HP-XRD) measurements to probe the elastic compressibility properties on this meteorite and, for comparison purposes, on three ordinary chondrites. The HP-XRD results suggest that the axial compressibility of the orthorhombic $b$ lattice parameter of olivine is higher in NWA 12008 and also in the highly-shocked Chelyabinsk meteorite, relative to terrestrial olivine. The origin of the observed differences may be the consequence of a combination of factors reflecting their complex history. The combined study by nanoindentations and HP-XRD of the mechanical and elastic properties of meteorites and returned samples opens up a new avenue to characterize these materials that will be crucial for future extraterrestrial resource utilization purposes., Comment: 14 pages, 8 figures, 1 table

Statistical protocols are often used for decision-making involving multiple parties, each with their own incentives, private information, and ability to influence the distributional properties of the data. We study a game-theoretic version of hypothesis testing in which a statistician, also known as a principal, interacts with strategic agents that can generate data. The statistician seeks to design a testing protocol with controlled error, while the data-generating agents, guided by their utility and prior information, choose whether or not to opt in based on expected utility maximization. This strategic behavior affects the data observed by the statistician and, consequently, the associated testing error. We analyze this problem for general concave and monotonic utility functions and prove an upper bound on the Bayes false discovery rate (FDR). Underlying this bound is a form of prior elicitation: we show how an agent's choice to opt in implies a certain upper bound on their prior null probability. Our FDR bound is unimprovable in a strong sense, achieving equality at a single point for an individual agent and at any countable number of points for a population of agents. We also demonstrate that our testing protocols exhibit a desirable maximin property when the principal's utility is considered. To illustrate the qualitative predictions of our theory, we examine the effects of risk aversion, reward stochasticity, and signal-to-noise ratio, as well as the implications for the Food and Drug Administration's testing protocols.

We propose and implement a comprehensive quantum compilation toolkit for solving the maximum independent set (MIS) problem on quantum hardware based on Rydberg atom arrays. Our end-to-end pipeline involves three core components to efficiently map generic MIS instances onto Rydberg arrays with unit-disk connectivity, with modules for graph reduction, hardware compatibility checks, and graph embedding. The first module (reducer) provides hardware-agnostic and deterministic reduction logic that iteratively reduces the problem size via lazy clique removals. We find that real-world networks can typically be reduced by orders of magnitude on sub-second time scales, thus significantly cutting down the eventual load for quantum devices. Moreover, we show that reduction techniques may be an important tool in the ongoing search for potential quantum speedups, given their ability to identify hard problem instances. In particular, for Rydberg-native MIS instances, we observe signatures of an easy-hard-easy transition and quantify a critical degree indicating the onset of a hard problem regime. The second module (compatibility checker) implements a hardware compatibility checker that quickly determines whether or not a given input graph may be compatible with the restrictions imposed by Rydberg quantum hardware. The third module (embedder) describes hardware-efficient graph embedding routines to generate (approximate) encodings with controllable overhead and optimized ancilla placements. We exemplify our pipeline with experiments run on the QuEra Aquila device available on Amazon Braket. In aggregate, our work provides a set of tools that extends the class of problems that can be tackled with near-term Rydberg atom arrays., Comment: Manuscript: 20 pages, 16 figures. Appendix: 1 page, 3 figures

Panel data consists of a collection of $N$ units that are observed over $T$ units of time. A policy or treatment is subject to staggered adoption if different units take on treatment at different times and remains treated (or never at all). Assessing the effectiveness of such a policy requires estimating the treatment effect, corresponding to the difference between outcomes for treated versus untreated units. We develop inference procedures that build upon a computationally efficient matrix estimator for treatment effects in panel data. Our routines return confidence intervals (CIs) both for individual treatment effects, as well as for more general bilinear functionals of treatment effects, with prescribed coverage guarantees. We apply these inferential methods to analyze the effectiveness of Medicaid expansion portion of the Affordable Care Act. Based on our analysis, Medicaid expansion has led to substantial reductions in uninsurance rates, has reduced infant mortality rates, and has had no significant effects on healthcare expenditures.

We study a class of prediction problems in which relatively few observations have associated responses, but all observations include both standard covariates as well as additional "helper" covariates. While the end goal is to make high-quality predictions using only the standard covariates, helper covariates can be exploited during training to improve prediction. Helper covariates arise in many applications, including forecasting in time series; incorporation of biased or mis-calibrated predictions from foundation models; and sharing information in transfer learning. We propose "prediction aided by surrogate training" ($\texttt{PAST}$), a class of methods that exploit labeled data to construct a response estimator based on both the standard and helper covariates; and then use the full dataset with pseudo-responses to train a predictor based only on standard covariates. We establish guarantees on the prediction error of this procedure, with the response estimator allowed to be constructed in an arbitrary way, and the final predictor fit by empirical risk minimization over an arbitrary function class. These upper bounds involve the risk associated with the oracle data set (all responses available), plus an overhead that measures the accuracy of the pseudo-responses. This theory characterizes both regimes in which $\texttt{PAST}$ accuracy is comparable to the oracle accuracy, as well as more challenging regimes where it behaves poorly. We demonstrate its empirical performance across a range of applications, including forecasting of societal ills over time with future covariates as helpers; prediction of cardiovascular risk after heart attacks with prescription data as helpers; and diagnosing pneumonia from chest X-rays using machine-generated predictions as helpers.

In order to simulate the spread of infectious diseases, many epidemiological models use systems of ordinary differential equations (ODEs) to describe the underlying dynamics. These models incorporate the implicit assumption, that the stay time in each disease state follows an exponential distribution. However, a substantial number of epidemiological, data-based studies indicate that this assumption is not plausible. One method to alleviate this limitation is to employ the Linear Chain Trick (LCT) for ODE systems, which realizes the use of Erlang distributed stay times. As indicated by data, this approach allows for more realistic models while maintaining the advantages of using ODEs. In this work, we propose an advanced LCT model incorporating eight infection states with demographic stratification. We review key properties of LCT models and demonstrate that predictions derived from a simple ODE-based model can be significantly distorted, potentially leading to wrong political decisions. Our findings demonstrate that the influence of distribution assumptions on the behavior at change points and on the prediction of epidemic peaks is substantial, while the assumption has no effect on the final size of the epidemic. As the corresponding ODE systems are often solved by adaptive Runge-Kutta methods such as the Cash Karp method, we also study the implications on the time-to-solution using Cash Karp 5(4) for different LCT models. Eventually and for the application side, we highlight the importance of incorporating a demographic stratification by age groups to improve the prediction performance of the model. We validate our model by showing that realistic infection dynamics are better captured by LCT models than by a simple ODE model., Comment: 26 pages, 16 figures

In recent years, there has been increasing collaboration between the fields of quantum computing and high energy physics, including using LHC processes such as top (anti-)quark pair production to perform high energy tests of quantum entanglement. In this proceeding, I will review another interesting property from quantum computing ("magic"), that is needed to make quantum computers with genuine computational advantage over their classical counterparts. How to make and enhance magic in general quantum systems is an open question, such that new insights are always useful. To this end, I will show that the LHC naturally produces magic top quarks, providing a novel playground for further study in this area., Comment: Talk at the 17th International Workshop on Top Quark Physics (Top2024), 22-27 September 2024

Pruning neural networks, which involves removing a fraction of their weights, can often maintain high accuracy while significantly reducing model complexity, at least up to a certain limit. We present a neural network pruning technique that builds upon the Combinatorial Brain Surgeon, but solves an optimization problem over a subset of the network weights in an iterative, block-wise manner using block coordinate descent. The iterative, block-based nature of this pruning technique, which we dub ``iterative Combinatorial Brain Surgeon'' (iCBS) allows for scalability to very large models, including large language models (LLMs), that may not be feasible with a one-shot combinatorial optimization approach. When applied to large models like Mistral and DeiT, iCBS achieves higher performance metrics at the same density levels compared to existing pruning methods such as Wanda. This demonstrates the effectiveness of this iterative, block-wise pruning method in compressing and optimizing the performance of large deep learning models, even while optimizing over only a small fraction of the weights. Moreover, our approach allows for a quality-time (or cost) tradeoff that is not available when using a one-shot pruning technique alone. The block-wise formulation of the optimization problem enables the use of hardware accelerators, potentially offsetting the increased computational costs compared to one-shot pruning methods like Wanda. In particular, the optimization problem solved for each block is quantum-amenable in that it could, in principle, be solved by a quantum computer., Comment: 16 pages, 6 figures, 5 tables

We report the discovery of three ultracompact binary white dwarf systems hosting accretion disks, with orbital periods of 7.95, 8.68, and 13.15 minutes. This significantly augments the population of mass-transferring binaries at the shortest periods, and provides the first evidence that accretors in ultracompacts can be dense enough to host accretion disks even below 10 minutes (where previously only direct-impact accretors were known). In the two shortest-period systems, we measured changes in the orbital periods driven by the combined effect of gravitational wave emission and mass transfer; we find $\dot{P}$ is negative in one case, and positive in the other. This is only the second system measured with a positive $\dot{P}$, and it the most compact binary known that has survived a period minimum. Using these systems as examples, we show how the measurement of $\dot{P}$ is a powerful tool in constraining the physical properties of binaries, e.g. the mass and mass-radius relation of the donor stars. We find that the chirp masses of ultracompact binaries at these periods seem to cluster around $\mathcal{M}_c \sim 0.3 M_\odot$, perhaps suggesting a common origin for these systems or a selection bias in electromagnetic discoveries. Our new systems are among the highest-amplitude known gravitational wave sources in the millihertz regime, providing exquisite opportunity for multi-messenger study with future space-based observatories such as \textit{LISA} and TianQin; we discuss how such systems provide fascinating laboratories to study the unique regime where the accretion process is mediated by gravitational waves., Comment: Accepted for publication in ApJ

There is a growing realization that neutrinos can be used as a diagnostic tool to better understand the inner workings of a nuclear weapon. Robust estimates demonstrate that an Inverse Beta Decay (IBD) neutrino scintillation detector built at the Nevada Test Site of 1000-ton active target mass at a standoff distance of 500 m would detect thousands of neutrino events per kTe of nuclear yield. This would provide less than 4% statistical error on measured neutrino rate and 5% error on neutrino energy. Extrapolating this to an error on the test device explosive yield requires knowledge from evaluated nuclear databases, non-equilibrium fission rates, and assumptions on internal neutron fluxes. Initial calculations demonstrate that prompt neutrino rates from a short pulse of Pu-239 fission is about a factor of two less than that from a steady state assumption. As well, there are significant energy spectral differences as a function of time after the pulse that needs to be considered. In the absence of nuclear weapons testing, many of the technical and theoretical challenges of a full nuclear test could be mitigated with a low cost smaller scale 20 ton fiducial mass IBD demonstration detector placed near a TRIGA pulsed reactor. The short duty cycle and repeatability of pulses would provide critical real environment testing and the measured neutrino rate as a function of time data would provide unique constraints on fission databases and equilibrium assumptions.

Jets launched by supermassive black holes transport relativistic leptons, magnetic fields, and atomic nuclei from the centres of galaxies to their outskirts and beyond. These outflows embody the most energetic pathway by which galaxies respond to their Cosmic Web environment. Studying black hole feedback is an astrophysical frontier, providing insights on star formation, galaxy cluster stability, and the origin of cosmic rays, magnetism, and heavy elements throughout the Universe. This feedback's cosmological importance is ultimately bounded by the reach of black hole jets, and could be sweeping if jets travel far at early epochs. Here we present the joint LOFAR-uGMRT-Keck discovery of a black hole jet pair extending over $7$ megaparsecs -- the largest galaxy-made structure ever found. The outflow, seen $7.5$ gigayears into the past, spans two-thirds of a typical cosmic void radius, thus penetrating voids at ${\sim}95\%$ probability. This system demonstrates that jets can avoid destruction by magnetohydrodynamical instabilities over cosmological distances, even at epochs when the Universe was 15 to 7 times denser than it is today. Whereas previous record-breaking outflows were powered by radiatively inefficient active galactic nuclei, this outflow is powered by a radiatively efficient active galactic nucleus, a type common at early epochs. If, as implied, a population of early void-penetrating outflows existed, then black hole jets could have overwritten the fields from primordial magnetogenesis. This outflow shows that energy transport from supermassive black holes operates on scales of the Cosmic Web and raises the possibility that cosmic rays and magnetism in the intergalactic medium have a non-local, cross-void origin., Comment: 30 pages, 10 figures, 1 table, published in Nature. This arXiv version pre-dates the peer review process

In magnetic systems, angular momentum is carried by the spin and orbital degrees of freedom. Non-local devices can be used to study angular momentum transport. They consist of parallel heavy-metal nanowires placed on top of magnetic insulators like yttrium iron garnet (YIG), facilitating the transmission of information by magnons, generated by the accumulation of spin at the interface, created via the Spin Hall Effect (SHE) and detected via the inverse SHE (iSHE). It has been demonstrated that these processes have comparable efficiencies when the role of the detector and injector is reversed, which points to reciprocity of the processes. However, we show that by adding Ru as a source of direct and inverse orbital Hall effect (OHE), the system no longer exhibits this reciprocity. Specifically, the generation of magnons via the combination of SHE and OHE and detection via the iSHE is found to be about 35% more efficient than the inverse process for our system.

During the COVID-19 crisis, mechanistic models have been proven fundamental to guide evidence-based decision making. However, time-critical decisions in a dynamically changing environment restrict the time available for modelers to gather supporting evidence. As infectious disease dynamics are often heterogeneous on a spatial or demographic scale, models should be resolved accordingly. In addition, with a large number of potential interventions, all scenarios can barely be computed on time, even when using supercomputing facilities. We suggest to combine complex mechanistic models with data-driven surrogate models to allow for on-the-fly model adaptations by public health experts. We build upon a spatially and demographically resolved infectious disease model and train a graph neural network for data sets representing early phases of the pandemic. The resulting networks reached an execution time of less than a second, a significant speedup compared to the metapopulation approach. The suggested approach yields potential for on-the-fly execution and, thus, integration of disease dynamics models in low-barrier website applications. For the approach to be used with decision-making, datasets with larger variance will have to be considered., Comment: 22 pages, 8 figures

The unpredictability of random numbers is fundamental to both digital security and applications that fairly distribute resources. However, existing random number generators have limitations-the generation processes cannot be fully traced, audited, and certified to be unpredictable. The algorithmic steps used in pseudorandom number generators are auditable, but they cannot guarantee that their outputs were a priori unpredictable given knowledge of the initial seed. Device-independent quantum random number generators can ensure that the source of randomness was unknown beforehand, but the steps used to extract the randomness are vulnerable to tampering. Here, for the first time, we demonstrate a fully traceable random number generation protocol based on device-independent techniques. Our protocol extracts randomness from unpredictable non-local quantum correlations, and uses distributed intertwined hash chains to cryptographically trace and verify the extraction process. This protocol is at the heart of a public traceable and certifiable quantum randomness beacon that we have launched. Over the first 40 days of operation, we completed the protocol 7434 out of 7454 attempts -- a success rate of 99.7%. Each time the protocol succeeded, the beacon emitted a pulse of 512 bits of traceable randomness. The bits are certified to be uniform with error times actual success probability bounded by $2^{-64}$. The generation of certifiable and traceable randomness represents one of the first public services that operates with an entanglement-derived advantage over comparable classical approaches., Comment: 40 pages, 4 main figures, 10 supplementary figures

This paper presents the Random-Key Optimizer (RKO), a versatile and efficient stochastic local search method tailored for combinatorial optimization problems. Using the random-key concept, RKO encodes solutions as vectors of random keys that are subsequently decoded into feasible solutions via problem-specific decoders. The RKO framework is able to combine a plethora of classic metaheuristics, each capable of operating independently or in parallel, with solution sharing facilitated through an elite solution pool. This modular approach allows for the adaptation of various metaheuristics, including simulated annealing, iterated local search, and greedy randomized adaptive search procedures, among others. The efficacy of the RKO framework, implemented in C++, is demonstrated through its application to three NP-hard combinatorial optimization problems: the alpha-neighborhood p-median problem, the tree of hubs location problem, and the node-capacitated graph partitioning problem. The results highlight the framework's ability to produce high-quality solutions across diverse problem domains, underscoring its potential as a robust tool for combinatorial optimization., Comment: 54 pages, 16 figures, 8 tables

We consider the quantum magic in systems of dense neutrinos undergoing coherent flavor transformations, relevant for supernova and neutron-star binary mergers. Mapping the three-flavor-neutrino system to qutrits, the evolution of quantum magic is explored in the single scattering angle limit for a selection of initial tensor-product pure states for $N_\nu \le 8$ neutrinos. For $|\nu_e\rangle^{\otimes N_\nu}$ initial states, the magic, as measured by the $\alpha=2$ stabilizer Renyi entropy $M_2$, is found to decrease with radial distance from the neutrino sphere, reaching a value that lies below the maximum for tensor-product qutrit states. Further, the asymptotic magic per neutrino, $M_2/N_\nu$, decreases with increasing $N_\nu$. In contrast, the magic evolving from states containing all three flavors reaches values only possible with entanglement, with the asymptotic $M_2/N_\nu$ increasing with $N_\nu$. These results highlight the connection between the complexity in simulating quantum physical systems and the parameters of the Standard Model., Comment: 15 pages, 8 figures

Future cosmic microwave background (CMB) experiments are primarily targeting a detection of the primordial $B$-mode polarisation. The faintness of this signal requires exquisite control of systematic effects which may bias the measurements. In this work, we derive requirements on the relative calibration accuracy of the overall polarisation gain ($\Delta g_\nu$) for LiteBIRD experiment, through the application of the blind Needlet Internal Linear Combination (NILC) foreground-cleaning method. We find that minimum variance techniques, as NILC, are less affected by gain calibration uncertainties than a parametric approach, which requires a proper modelling of these instrumental effects. The tightest constraints are obtained for frequency channels where the CMB signal is relatively brighter (166 GHz channel, $\Delta {g}_\nu \approx 0.16 \%$), while, with a parametric approach, the strictest requirements were on foreground-dominated channels. We then propagate gain calibration uncertainties, corresponding to the derived requirements, into all frequency channels simultaneously. We find that the overall impact on the estimated $r$ is lower than the required budget for LiteBIRD by almost a factor $5$. The adopted procedure to derive requirements assumes a simple Galactic model. We therefore assess the robustness of obtained results against more realistic scenarios by injecting the gain calibration uncertainties, according to the requirements, into LiteBIRD simulated maps and assuming intermediate- and high-complexity sky models. In this case, we employ the so-called Multi-Clustering NILC (MC-NILC) foreground-cleaning pipeline and obtain that the impact of gain calibration uncertainties on $r$ is lower than the LiteBIRD gain systematics budget for the intermediate-complexity sky model. For the high-complexity case, instead, it would be necessary to tighten the requirements by a factor $1.8$., Comment: 29 pages, 11 figures

We introduce a toluene-filled fiber platform for two-photon absorption measurements. By confining both the light and molecular sample inside the 5 $\mu$m hollow core of the fiber, we increase the distance over which the nonlinear light-matter interaction occurs. With only a 7.3 nL excitation volume, we measure classical two-photon absorption (C2PA) at an average laser power as low as 1.75 nW, which is a 45-fold improvement over a conventional free-space technique. We use this platform to attempt to measure entangled two-photon absorption (E2PA), a process with a limited regime where the quantum advantage is large. This regime arises due to a crossover from linear to quadratic scaling with photon flux as photon flux is increased. Recently, several teams of researchers have reported that E2PA cross-sections are much smaller than previously claimed. As a result, the linear scaling dominates at photon fluxes so low that it is extremely difficult or impossible to measure using conventional free-space techniques. In this report, we implement the first E2PA measurement using a waveguide. We see no evidence of E2PA, and we set an upper bound on the cross-section consistent with these recent reports.

We present a compendium of HI 21-cm line observations of circumstellar envelopes (CSEs) of 290 evolved stars, mostly (~84%) on the asymptotic giant branch (AGB), made with the 100m-class, single-dish Nancay Radio Telescope. The observational and data reduction procedures were optimised for separating genuine CSE HI emission from surrounding Galactic line features. For most targets (254) the results have not been previously published. Clear detections were made of 34 objects, for 33 of which the total HI flux and the size of the CSE could be determined. Possible detections were made of 21 objects, and upper limits could be determined for 95 undetected targets, while for 140 objects confusion from Galactic HI emission along the line-of-sight precluded meaningful upper limits. The collective results of this survey can provide guidance on detectability of circumstellar HI gas for future mapping and imaging studies.

Agent-based models have proven to be useful tools in supporting decision-making processes in different application domains. The advent of modern computers and supercomputers has enabled these bottom-up approaches to realistically model human mobility and contact behavior. The COVID-19 pandemic showcased the urgent need for detailed and informative models that can answer research questions on transmission dynamics. We present a sophisticated agent-based model to simulate the spread of respiratory diseases. The model is highly modularized and can be used on various scales, from a small collection of buildings up to cities or countries. Although not being the focus of this paper, the model has undergone performance engineering on a single core and provides an efficient intra- and inter-simulation parallelization for time-critical decision-making processes. In order to allow answering research questions on individual level resolution, nonpharmaceutical intervention strategies such as face masks or venue closures can be implemented for particular locations or agents. In particular, we allow for sophisticated testing and isolation strategies to study the effects of minimal-invasive infectious disease mitigation. With realistic human mobility patterns for the region of Brunswick, Germany, we study the effects of different interventions between March 1st and May 30, 2021 in the SARS-CoV-2 pandemic. Our analyses suggest that symptom-independent testing has limited impact on the mitigation of disease dynamics if the dark figure in symptomatic cases is high. Furthermore, we found that quarantine length is more important than quarantine efficiency but that, with sufficient symptomatic control, also short quarantines can have a substantial effect., Comment: 35 pages, 13 figures, to be submitted to Elsevier

Recent breakthroughs in natural language processing and computer vision, driven by efficient pre-training on large datasets, have enabled foundation models to excel on a wide range of tasks. However, this potential has not yet been fully realised in time series analysis, as existing methods fail to address the heterogeneity in large time series corpora. Prevalent in domains ranging from medicine to finance, time series vary substantially in characteristics such as variate count, inter-variate relationships, temporal patterns, and sampling frequency. To address this, we introduce a novel pre-training paradigm specifically designed to handle time series heterogeneity. We propose a tokeniser with learnable domain signatures, a dual masking strategy, and a normalised cross-correlation loss, enabling our open model for general time series analysis (OTiS) to efficiently learn from large time series corpora. Extensive benchmarking on diverse tasks, such as classification, regression, and forecasting, demonstrates that OTiS outperforms state-of-the-art baselines. Our code and pre-trained weights are available at https://github.com/oetu/otis.

We provide a non-asymptotic analysis of the linear instrumental variable estimator allowing for the presence of exogeneous covariates. In addition, we introduce a novel measure of the strength of an instrument that can be used to derive non-asymptotic confidence intervals. For strong instruments, these non-asymptotic intervals match the asymptotic ones exactly up to higher order corrections; for weaker instruments, our intervals involve adaptive adjustments to the instrument strength, and thus remain valid even when asymptotic predictions break down. We illustrate our results via an analysis of the effect of PM2.5 pollution on various health conditions, using wildfire smoke exposure as an instrument. Our analysis shows that exposure to PM2.5 pollution leads to statistically significant increases in incidence of health conditions such as asthma, heart disease, and strokes.

Kinetic inductance detectors (KIDs) have been proven as reliable systems for astrophysical observations, especially in the millimetre range. Their compact size enables to optimally fill the focal plane, thus boosting sensitivity. The KISS (KIDs Interferometric Spectral Surveyor) instrument is a millimetre camera that consists of two KID arrays of 316 pixels each coupled to a Martin-Puplett interferometer (MPI). The addition of the MPI grants the KIDs camera the ability to provide spectral information in the 100 and 300 GHz range. In this paper we report the main properties of the KISS instrument and its observations. We also describe the calibration and data analysis procedures used. We present a complete model of the observed data including the sky signal and several identified systematics. We have developed a full photometric and spectroscopic data analysis pipeline that translates our observations into science-ready products. We show examples of the results of this pipeline on selected sources: Moon, Jupiter and Venus. We note the presence of a deficit of response with respect to expectations and laboratory measurements. The detectors noise level is consistent with values obtained during laboratory measurements, pointing to a sub-optimal coupling between the instrument and the telescope as the most probable origin for the problem. This deficit is large enough as to prevent the detection of galaxy clusters, which were KISS main scientific objective. Nevertheless, we have demonstrated the feasibility of this kind of instrument, in the prospect for other KID interferometers (such as the CONCERTO instrument). As this regard, we have developed key instrumental technologies such as optical conception, readout electronics and raw calibration procedures, as well as, adapted data analysis procedures., Comment: 23 pages, 15 figures. Accepted for publication in Publications of the Astronomical Society of the Pacific

A search for proton decay into $e^+/\mu^+$ and a $\eta$ meson has been performed using data from a 0.373 Mton$\cdot$year exposure (6050.3 live days) of Super-Kamiokande. Compared to previous searches this work introduces an improved model of the intranuclear $\eta$ interaction cross section, resulting in a factor of two reduction in uncertainties from this source and $\sim$10\% increase in signal efficiency. No significant data excess was found above the expected number of atmospheric neutrino background events resulting in no indication of proton decay into either mode. Lower limits on the proton partial lifetime of $1.4\times\mathrm{10^{34}~years}$ for $p\rightarrow e^+\eta$ and $7.3\times\mathrm{10^{33}~years}$ for $p\rightarrow \mu^+\eta$ at the 90$\%$ C.L. were set. These limits are around 1.5 times longer than our previous study and are the most stringent to date.

Erbium ions in crystals show considerable promise for the technologies that will form the backbone of future networked quantum information technology. Despite advances in leveraging erbium's fibre-compatible infrared transition for classical and quantum applications, the transitions are, in general, not well understood. We present detailed absorption and laser site-selective spectroscopy of the C$_{\rm 3v}$(O$^{2-}$) centre in CaF$_2$:Er$^{3+}$ as an interesting erbium site case study. The $^{4}$I$_{15/2}$Z$_1 \rightarrow {^{4}}$I$_{13/2}$Y$_1$ transition has a low-temperature inhomogeneous linewidth of 1 GHz with hyperfine structure observable from the $^{167}$Er isotope. A parametrized crystal-field Hamiltonian is fitted to 34 energy levels and the two ground state magnetic splitting factors. The wavefunctions are used to perform a transition intensity analysis and electric-dipole parameters are fitted to absorption oscillator strengths. Simulated spectra for the $^{4}$I$_{11/2}\rightarrow {^{4}}$I$_{15/2}$ and $^{4}$I$_{13/2} \rightarrow {^{4}}$I$_{15/2}$ inter-multiplet transitions are in excellent agreement with the experimentally measured spectra. The $^{4}$I$_{13/2}$ excited state lifetime is 25.0\,ms and the intensity calculation is in excellent agreement with this value.

(abridged) Characterizing duty cycles of recurrent phases of dormancy and activity in supermassive black holes in active galactic nuclei is crucial in understanding impact of energy released on host galaxies and their evolution. However, identifying sources in quiescent and restarted phases is challenging. Our goal is to identify and characterize a substantial sample of radio galaxies in restarted phase and explore core prominence as a signature of this activity. We expand our prior study from a $30\,\mathrm{deg^2}$ area in Lockman Hole to a larger $424\,\mathrm{deg^2}$ region in Hobby-Eberly Telescope Dark Energy Experiment (HETDEX) field using visually selected core-dominated radio galaxies. We used 144 MHz LOFAR survey images to identify galaxies with restarting jets. By applying selection criteria, including radio core dominance, low surface brightness extended emission, spectral index properties, and morphology, we found 69 candidate restarted radio galaxies. These candidates show diverse intrinsic morphology, spanning FRI, FRII, core-with-halo, and asymmetric forms, suggesting different progenitors. Among these, nine galaxies exhibit ultra-steep spectrum extended emission combined with high radio core prominence, representing previous and current epochs of jet activity. This subset supports a model where the switch-on and switch-off mechanism occurs with fast duty cycle. The restarted candidates span radio luminosities from log$_{10}$(L$_\mathrm{144 MHz}$/$\mathrm{WHz^{-1}}$) = 23.24 to 26.80, with sizes between 88 and 1659 kpc, including 16 giant radio galaxies. Their total stellar content aligns with massive elliptical galaxies. Our findings at $z<0.4$ suggest that many restarting galaxies are not found in rich cluster environments, consistent with broader radio-galaxy population. This study confirms core prominence as an effective parameter for selecting restarted radio sources., Comment: 28 pages, 18 figures, 7 tables, accepted for publication in A&A

We study a class of structured Markov Decision Processes (MDPs) known as Exo-MDPs. They are characterized by a partition of the state space into two components: the exogenous states evolve stochastically in a manner not affected by the agent's actions, whereas the endogenous states can be affected by actions, and evolve according to deterministic dynamics involving both the endogenous and exogenous states. Exo-MDPs provide a natural model for various applications, including inventory control, portfolio management, power systems, and ride-sharing, among others. While seemingly restrictive on the surface, our first result establishes that any discrete MDP can be represented as an Exo-MDP. The underlying argument reveals how transition and reward dynamics can be written as linear functions of the exogenous state distribution, showing how Exo-MDPs are instances of linear mixture MDPs, thereby showing a representational equivalence between discrete MDPs, Exo-MDPs, and linear mixture MDPs. The connection between Exo-MDPs and linear mixture MDPs leads to algorithms that are near sample-optimal, with regret guarantees scaling with the (effective) size of the exogenous state space $d$, independent of the sizes of the endogenous state and action spaces, even when the exogenous state is {\em unobserved}. When the exogenous state is unobserved, we establish a regret upper bound of $O(H^{3/2}d\sqrt{K})$ with $K$ trajectories of horizon $H$ and unobserved exogenous state of dimension $d$. We also establish a matching regret lower bound of $\Omega(H^{3/2}d\sqrt{K})$ for non-stationary Exo-MDPs and a lower bound of $\Omega(Hd\sqrt{K})$ for stationary Exo-MDPs. We complement our theoretical findings with an experimental study on inventory control problems., Comment: 32 pages

In this paper, we demonstrate the integration of photonic devices on sapphire substrates using multi-layer depressed cladding waveguides at both 780 nm and 1550 nm. The devices are up to 10-cm long and written at depths down to 400 um. The propagation losses for single-mode guiding are ~ 0.6 dB/cm at 780 nm and ~ 0.7 dB/cm at 1550 nm. A number of structures have been fabricated with simultaneous single-mode and polarization independent operation: evanescently coupled waveguide arrays, Y-branch splitters, Mach-Zehnder interferometers, and a 2x2 directional-coupler. All the devices were fabricated using adaptive optics-assisted femtosecond laser direct writing with a customized laser writing algorithm. This work enables the integration of single-mode sapphire photonics devices in a scalable manner, enabling many applications in communications, imaging, computing, and sensing.

Motivated by the Gottesman-Knill theorem, we present a detailed study of the quantum complexity of $p$-shell and $sd$-shell nuclei. Valence-space nuclear shell-model wavefunctions generated by the BIGSTICK code are mapped to qubit registers using the Jordan-Wigner mapping (12 qubits for the $p$-shell and 24 qubits for the $sd$-shell), from which measures of the many-body entanglement ($n$-tangles) and magic (non-stabilizerness) are determined. While exact evaluations of these measures are possible for nuclei with a modest number of active nucleons, Monte Carlo simulations are required for the more complex nuclei. The broadly-applicable Pauli-String $IZ$ exact (PSIZe-) MCMC technique is introduced to accelerate the evaluation of measures of magic in deformed nuclei (with hierarchical wavefunctions), by factors of $\sim 8$ for some nuclei. Significant multi-nucleon entanglement is found in the $sd$-shell, dominated by proton-neutron configurations, along with significant measures of magic. This is evident not only for the deformed states, but also for nuclei on the path to instability via regions of shape coexistence and level inversion. These results indicate that quantum-computing resources will accelerate precision simulations of such nuclei and beyond., Comment: 36 pages, 13 figures

Industrially relevant constrained optimization problems, such as portfolio optimization and portfolio rebalancing, are often intractable or difficult to solve exactly. In this work, we propose and benchmark a decomposition pipeline targeting portfolio optimization and rebalancing problems with constraints. The pipeline decomposes the optimization problem into constrained subproblems, which are then solved separately and aggregated to give a final result. Our pipeline includes three main components: preprocessing of correlation matrices based on random matrix theory, modified spectral clustering based on Newman's algorithm, and risk rebalancing. Our empirical results show that our pipeline consistently decomposes real-world portfolio optimization problems into subproblems with a size reduction of approximately 80%. Since subproblems are then solved independently, our pipeline drastically reduces the total computation time for state-of-the-art solvers. Moreover, by decomposing large problems into several smaller subproblems, the pipeline enables the use of near-term quantum devices as solvers, providing a path toward practical utility of quantum computers in portfolio optimization.

Within the RoadMap project we investigated the microphysical aspects of particle collisions during saltation on the Martian surface in laboratory experiments. Following the size distribution of ejected particles, their aerodynamic properties and aggregation status upon ejection, we now focus on the electrification and charge distribution of ejected particles. We analyzed rebound and ejection trajectories of grains in a vacuum setup with a strong electric field of 100 kV/m and deduced particle charges from their acceleration. The ejected particles have sizes of about 10 to 100 microns. They carry charges up to $10^5$ e or charge densities up to $> 10^7$ e/mm$^2$. Within the given size range, we find a small bias towards positive charges., Comment: Preprint, 7 pages, 3 figures

We analyze JWST MIRI/MRS IFU observations of three Seyferts and showcase the intriguing polycyclic aromatic hydrocarbon (PAH) emission characteristics in regions of $\sim 500\,\rm pc$ scales over or around their active galactic nuclei (AGN). Combining the model predictions and the measurements of PAH features and other infrared emission lines, we find that the central regions containing a high fraction of neutral PAHs with small sizes, e.g., those in ESO137-G034, are in highly heated environments, due to collisional shock heating, with hard and moderately intense radiation fields. Such environments are proposed to be associated with inhibited growth or preferential erosion of PAHs, decreasing the average PAH size and the overall abundance of PAHs. We additionally find that the central regions containing a high fraction of ionized PAHs with large sizes, e.g., those in MCG-05-23-016, are likely experiencing severe photo-ionization because of the radiative effects from the radiative shock precursor besides the AGN. The severe photo-ionization can contribute to the ionization of all PAHs and further destruction of small PAHs. Overall, different Seyferts, even different regions in the same galaxy, e.g., those in NGC\,3081, can contain PAH populations of different properties. Specifically, Seyferts that exhibit similar PAH characteristics to ESO137-G034 and MCG-05-23-016 also tend to have similar emission line properties to them, suggesting that the explanations for PAH characteristics of ESO137-G034 and MCG-05-23-016 may also apply generally. These results have promising application in the era of JWST, especially in diagnosing different (i.e., radiative, and kinetic) AGN feedback modes., Comment: ApJL accepted on September 26th, title slightly modified in accordance with ApJL standards, Fig. 2 updated with additional labels

Utilizing JWST MIRI/MRS IFU observations of the kiloparsec scale central regions, we showcase the diversity of ionized gas distributions and kinematics in six nearby Seyfert galaxies included in the GATOS survey. Specifically, we present spatially resolved flux distribution and velocity field maps of six ionized emission lines covering a large range of ionization potentials ($15.8-97.1$ eV). Based on these maps, we showcase the evidence of ionized gas outflows in the six targets, and find some highly disturbed regions in NGC\,5728, NGC\,5506, and ESO137-G034. We propose AGN-driven radio jets plausibly play an important role in triggering these highly disturbed regions. With the outflow rates estimated based on [Ne~{\footnotesize V}] emission, we find the six targets tend to have ionized outflow rates converged to a narrower range than previous finding. These results have important implication for the outflow properties in AGN of comparable luminosity., Comment: 34 pages (11 pages in the appendix), 18 figures in the main text, ApJ in press (accepted on July 26th)

X-ray reverberation mapping is a powerful technique for probing the innermost accretion disk, whereas continuum reverberation mapping in the UV, optical, and infrared (UVOIR) reveals reprocessing by the rest of the accretion disk and broad-line region (BLR). We present the time lags of Mrk 817 as a function of temporal frequency measured from 14 months of high-cadence monitoring from Swift and ground-based telescopes, in addition to an XMM-Newton observation, as part of the AGN STORM 2 campaign. The XMM-Newton lags reveal the first detection of a soft lag in this source, consistent with reverberation from the innermost accretion flow. These results mark the first simultaneous measurement of X-ray reverberation and UVOIR disk reprocessing lags$\unicode{x2013}$effectively allowing us to map the entire accretion disk surrounding the black hole. Similar to previous continuum reverberation mapping campaigns, the UVOIR time lags arising at low temporal frequencies are longer than those expected from standard disk reprocessing by a factor of 2-3. The lags agree with the anticipated disk reverberation lags when isolating short-timescale variability, namely timescales shorter than the H$\beta$ lag. Modeling the lags requires additional reprocessing constrained at a radius consistent with the BLR size scale inferred from contemporaneous H$\beta$-lag measurements. When we divide the campaign light curves, the UVOIR lags show substantial variations, with longer lags measured when obscuration from an ionized outflow is greatest. We suggest that, when the obscurer is strongest, reprocessing by the BLR elongates the lags most significantly. As the wind weakens, the lags are dominated by shorter accretion disk lags., Comment: 28 pages, 11 figures, 3 tables. Accepted for publication in the Astrophysical Journal

Scientists increasingly recognize the importance of providing rich, standards-adherent metadata to describe their experimental results. Despite the availability of sophisticated tools to assist in the process of data annotation, investigators generally seem to prefer to use spreadsheets when supplying metadata, despite the limitations of spreadsheets in ensuring metadata consistency and compliance with formal specifications. In this paper, we describe an end-to-end approach that supports spreadsheet-based entry of metadata, while ensuring rigorous adherence to community-based metadata standards and providing quality control. Our methods employ several key components, including customizable templates that capture metadata standards and that can inform the spreadsheets that investigators use to author metadata, controlled terminologies and ontologies for defining metadata values that can be accessed directly from a spreadsheet, and an interactive Web-based tool that allows users to rapidly identify and fix errors in their spreadsheet-based metadata. We demonstrate how this approach is being deployed in a biomedical consortium known as HuBMAP to define and collect metadata about a wide range of biological assays.

This work focuses on the study of the AME, an important emission mechanism between 10 and 60 GHz whose polarization properties are not yet fully understood, and is therefore a potential contaminant for future CMB polarization observations. We use new QUIJOTE-MFI maps 11, 13, 17 and 19 GHz, together with other public ancillary data including WMAP and Planck, to study the polarization properties of the AME in three Galactic regions: rho-Ophiuchi, Perseus and W43. We have obtained the SEDs for those three regions over the frequency range 0.4-3000 GHz, both in intensity and polarization. The intensity SEDs are well described by a combination of free-free emission, thermal dust, AME and CMB anisotropies. In polarization, we extracted the flux densities using all available data between 11 and 353 GHz. We implemented an improved intensity-to-polarization leakage correction that has allowed for the first time to derive reliable polarization constraints well below the 1% level from Planck-LFI data. A frequency stacking of maps in the range 10-60 GHz has allowed us to reduce the statistical noise and to push the upper limits on the AME polarization level. We have obtained upper limits on the AME polarization fraction of order <1% (95% confidence level) for the three regions. In particular we get Pi_AME < 1.1% (at 28.4 GHz), Pi_AME < 1.1% (at 22.8 GHz) and Pi_AME < 0.28% (at 33 GHz) in rho-Ophiuchi, Perseus and W43 respectively. At the QUIJOTE 17 GHz frequency band, we get Pi_AME< 5.1% for rho-Ophiuchi, Pi_AME< 3.5% for Perseus and Pi_AME< 0.85% for W43. Our final upper limits derived using the stacking procedure are Pi_AME < 0.58% for rho-Ophiuchi, Pi_AME < 1.64% for Perseus and Pi_AME < 0.31% for W43. Altogether, these are the most stringent constraints to date on the AME polarization fraction of these three star-forming regions., Comment: 26 pages. 15 figures. Submitted to A&A. Comments welcome

The Parareal algorithm was invented in 2001 in order to parallelize the solution of evolution problems in the time direction. It is based on parallel fine time propagators called F and sequential coarse time propagators called G, which alternatingly solve the evolution problem and iteratively converge to the fine solution. The coarse propagator G is a very important component of Parareal, as one sees in the convergence analyses. We present here for the first time a Parareal algorithm without coarse propagator, and explain why this can work very well for parabolic problems. We give a new convergence proof for coarse propagators approximating in space, in contrast to the more classical coarse propagators which are approximations in time, and our proof also applies in the absence of the coarse propagator. We illustrate our theoretical results with numerical experiments, and also explain why this approach can not work for hyperbolic problems.

The dimension of a quantum state is traditionally seen as the number of superposed distinguishable states in a given basis. We propose an absolute, i.e.~basis-independent, notion of dimensionality for ensembles of quantum states. It is based on whether a quantum ensemble can be simulated with states confined to arbitrary lower-dimensional subspaces and classical postprocessing. In order to determine the absolute dimension of quantum ensembles, we develop both analytical witness criteria and a semidefinite programming criterion based on the ensemble's information capacity. Furthermore, we construct explicit simulation models for arbitrary ensembles of pure quantum states subject to white noise, and in natural cases we prove their optimality. Also, efficient numerical methods are provided for simulating generic ensembles. Finally, we discuss the role of absolute dimensionality in high-dimensional quantum information processing.

Ordinary differential equations (ODE) are a popular tool to model the spread of infectious diseases, yet they implicitly assume an exponential distribution to describe the flow from one infection state to another. However, scientific experience yields more plausible distributions where the likelihood of disease progression or recovery changes accordingly with the duration spent in a particular state of the disease. Furthermore, transmission dynamics depend heavily on the infectiousness of individuals. The corresponding nonlinear variation with the time individuals have already spent in an infectious state requires more realistic models. The previously mentioned items are particularly crucial when modeling dynamics at change points such as the implementation of nonpharmaceutical interventions. In order to capture these aspects and to enhance the accuracy of simulations, integro-differential equations (IDE) can be used. In this paper, we propose a generalized model based on integro-differential equations with eight infection states. The model allows for variable stay time distributions and generalizes the concept of ODE-based models as well as IDE-based age-of-infection models. In this, we include particular infection states for severe and critical cases to allow for surveillance of the clinical sector, avoiding bottlenecks and overloads in critical epidemic situations. We will extend a recently introduced nonstandard numerical scheme to solve a simpler IDE-based model. This scheme is adapted to our more advanced model and we prove important mathematical and biological properties for the numerical solution. Furthermore, we validate our approach numerically by demonstrating the convergence rate. Eventually, we also show that our novel model is intrinsically capable of better assessing disease dynamics upon the introduction of nonpharmaceutical interventions.

We study best-response type learning dynamics for two player zero-sum matrix games. We consider two settings that are distinguished by the type of information that each player has about the game and their opponent's strategy. The first setting is the full information case, in which each player knows their own and the opponent's payoff matrices and observes the opponent's mixed strategy. The second setting is the minimal information case, where players do not observe the opponent's strategy and are not aware of either of the payoff matrices (instead they only observe their realized payoffs). For this setting, also known as the radically uncoupled case in the learning in games literature, we study a two-timescale learning dynamics that combine smoothed best-response type updates for strategy estimates with a TD-learning update to estimate a local payoff function. For these dynamics, without additional exploration, we provide polynomial-time finite-sample guarantees for convergence to an $\epsilon$-Nash equilibrium., Comment: 36 pages; under review

We assess the capabilities of the LiteBIRD mission to map the hot gas distribution in the Universe through the thermal Sunyaev-Zeldovich (SZ) effect. Our analysis relies on comprehensive simulations incorporating various sources of Galactic and extragalactic foreground emission, while accounting for specific instrumental characteristics of LiteBIRD, such as detector sensitivities, frequency-dependent beam convolution, inhomogeneous sky scanning, and $1/f$ noise. We implement a tailored component-separation pipeline to map the thermal SZ Compton $y$-parameter over 98% of the sky. Despite lower angular resolution for galaxy cluster science, LiteBIRD provides full-sky coverage and, compared to the Planck satellite, enhanced sensitivity, as well as more frequency bands to enable the construction of an all-sky $y$-map, with reduced foreground contamination at large and intermediate angular scales. By combining LiteBIRD and Planck channels in the component-separation pipeline, we obtain an optimal $y$-map that leverages the advantages of both experiments, with the higher angular resolution of the Planck channels enabling the recovery of compact clusters beyond the LiteBIRD beam limitations, and the numerous sensitive LiteBIRD channels further mitigating foregrounds. The added value of LiteBIRD is highlighted through the examination of maps, power spectra, and one-point statistics of the various sky components. After component separation, the $1/f$ noise from LiteBIRD is effectively mitigated below the thermal SZ signal at all multipoles. Cosmological constraints on $S_8=\sigma_8\left(\Omega_{\rm m}/0.3\right)^{0.5}$ obtained from the LiteBIRD-Planck combined $y$-map power spectrum exhibits a 15% reduction in uncertainty compared to constraints from Planck alone. This improvement can be attributed to the increased portion of uncontaminated sky available in the LiteBIRD-Planck combined $y$-map., Comment: 38 pages, 13 figures, abstract shortened. Updated to match version accepted by JCAP

The Gravitational-wave Optical Transient Observer (GOTO) is a project dedicated to identifying optical counter-parts to gravitational-wave detections using a network of dedicated, wide-field telescopes. After almost a decade of design, construction, and commissioning work, the GOTO network is now fully operational with two antipodal sites: La Palma in the Canary Islands and Siding Spring in Australia. Both sites host two independent robotic mounts, each with a field-of-view of 44 square degrees formed by an array of eight 40 cm telescopes, resulting in an instantaneous 88 square degree field-of-view per site. All four telescopes operate as a single integrated network, with the ultimate aim of surveying the entire sky every 2-3 days and allowing near-24-hour response to transient events within a minute of their detection. In the modern era of transient astronomy, automated telescopes like GOTO form a vital link between multi-messenger discovery facilities and in-depth follow-up by larger telescopes. GOTO is already producing a wide range of scientific results, assisted by an efficient discovery pipeline and a successful citizen science project: Kilonova Seekers., Comment: 8 pages, 5 figures, submitted to SPIE Astronomical Telescopes + Instrumentation 2024

Despite recent advances in human pose estimation (HPE), poor generalization to out-of-distribution (OOD) data remains a difficult problem. While previous works have proposed Test-Time Adaptation (TTA) to bridge the train-test domain gap by refining network parameters at inference, the absence of ground-truth annotations makes it highly challenging and existing methods typically increase inference times by one or more orders of magnitude. We observe that 1) not every test time sample is OOD, and 2) HPE errors are significantly larger on distal keypoints (wrist, ankle). To this end, we propose ESCAPE: a lightweight correction and selective adaptation framework which applies a fast, forward-pass correction on most data while reserving costly TTA for OOD data. The free energy function is introduced to separate OOD samples from incoming data and a correction network is trained to estimate the errors of pretrained backbone HPE predictions on the distal keypoints. For OOD samples, we propose a novel self-consistency adaptation loss to update the correction network by leveraging the constraining relationship between distal keypoints and proximal keypoints (shoulders, hips), via a second ``reverse" network. ESCAPE improves the distal MPJPE of five popular HPE models by up to 7% on unseen data, achieves state-of-the-art results on two popular HPE benchmarks, and is significantly faster than existing adaptation methods., Comment: 32 pages, 8 figures