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The anomalous Hall effect (AHE), a hallmark of time-reversal symmetry breaking, has been reported in rutile RuO2, a debated metallic altermagnetic candidate. Previously, AHE in RuO2 was observed only in strain-relaxed thick films under extremely high magnetic fields (~50 T). Yet, in ultrathin strained films with distinctive anisotropic electronic structures, there are no reports, likely due to disorder and defects suppressing metallicity thus hindering its detection. Here, we demonstrate that ultrathin, fully-strained 2 nm TiO2/t nm RuO2/TiO2 (110) heterostructures, grown by hybrid molecular beam epitaxy, retain metallicity and exhibit a sizeable AHE at a significantly lower magnetic field (< 9 T). Density functional theory calculations reveal that epitaxial strain stabilizes a non-compensated magnetic ground state and reconfigures magnetic ordering in RuO2 (110) thin films. These findings establish ultrathin RuO2 as a platform for strain-engineered magnetism and underscore the transformative potential of epitaxial design in advancing spintronic technologies., Comment: 23 pages

We employ deep learning (DL) to improve photometric redshifts (photo-$z$s) in the Kilo-Degree Survey Data Release 4 Bright galaxy sample (KiDS-Bright DR4). This dataset, used as a foreground for KiDS lensing and clustering studies, is flux-limited to $r<20$ mag with mean $z=0.23$ and covers 1000 deg$^2$. Its photo-$z$s were previously derived with artificial neural networks from the ANNz2 package, trained on the Galaxy And Mass Assembly (GAMA) spectroscopy. Here we considerably improve over these previous redshift estimations by building a DL model, Hybrid-z, which combines four-band KiDS images with nine-band magnitudes from KiDS+VIKING. The Hybrid-z framework provides photo-$z$s for KiDS-Bright, with negligible mean residuals of O($10^{-4}$) and scatter at the level of $0.014(1+z)$ -- reduction by 20% over the previous nine-band derivations with ANNz2. We check our photo-$z$ model performance on test data drawn from GAMA, as well as from other KiDS-overlapping wide-angle spectroscopic surveys, namely SDSS, 2dFLenS, and 2dFGRS. We find stable behavior and consistent improvement over ANNz2 throughout. We finally apply Hybrid-z trained on GAMA to the entire KiDS-Bright DR4 sample of 1.2 million galaxies. For these final predictions, we design a method of smoothing the input redshift distribution of the training set, to avoid propagation of features present in GAMA, related to its small sky area and large-scale structure imprint in its fields. Our work paves the way towards the best-possible photo-$z$s achievable with machine learning for any galaxy type both for the final KiDS-Bright DR5 data and for future deeper imaging, such as from the Legacy Survey of Space and Time., Comment: 14 pages, 7 figures

Two substantial technological advances have reshaped the public square in recent decades: first with the advent of the internet and second with the recent introduction of large language models (LLMs). LLMs offer opportunities for a paradigm shift towards more decentralized, participatory online spaces that can be used to facilitate deliberative dialogues at scale, but also create risks of exacerbating societal schisms. Here, we explore four applications of LLMs to improve digital public squares: collective dialogue systems, bridging systems, community moderation, and proof-of-humanity systems. Building on the input from over 70 civil society experts and technologists, we argue that LLMs both afford promising opportunities to shift the paradigm for conversations at scale and pose distinct risks for digital public squares. We lay out an agenda for future research and investments in AI that will strengthen digital public squares and safeguard against potential misuses of AI., Comment: 40 pages, 5 figures

Crystal symmetry plays an important role in the Hall effects. Unconventional spin Hall effect (USHE), characterized by Dresselhaus and out-of-plane spins, has been observed in materials with low crystal symmetry. Recently, antisymmetric planar Hall effect (APHE) was discovered in rutile RuO$_2$ and IrO$_2$ (101) thin films, which also exhibit low crystal symmetry. However, the correlation between USHE and APHE remains largely unexplored. In this study, we report the observation of both USHE and APHE in IrO$_2$ (111) films, using spin-torque ferromagnetic resonance (ST-FMR) and harmonic Hall measurements, respectively. Notably, the unconventional spin torque efficiency from Dresselhaus spin was more than double that of a previous report. Additionally, the temperature dependence of APHE suggests that it arises from the Lorentz force, constrained by crystal symmetry. Symmetry analysis confirms the coexistence of USHE and APHE in IrO$_2$ (111), paving the way for a deeper understanding of Hall effects and related physical phenomena.

Photometric galaxy surveys, despite their limited resolution along the line of sight, encode rich information about the large-scale structure (LSS) of the Universe thanks to the large number density and extensive depth of the data. However, the complicated selection effects in wide and deep surveys will potentially cause significant bias in the angular two-point correlation function (2PCF) measured from those surveys. In this paper, we measure the 2PCF from the newly published KiDS-Legacy sample. Given an $r$-band $5\sigma$ magnitude limit of $24.8$ and survey footprint of $1347$ deg$^2$, it achieves an excellent combination of sky coverage and depth for such a measurement. We find that complex selection effects, primarily induced by varying seeing, introduce over-estimation of the 2PCF by approximately an order of magnitude. To correct for such effects, we apply a machine learning-based method to recover an ``organised random'' (OR) that presents the same selection pattern as the galaxy sample. The basic idea is to find the selection-induced clustering of galaxies using a combination of self-organising maps (SOM) and hierarchical clustering (HC). This unsupervised machine learning method is able to recover complicated selection effects without specifying their functional forms. We validate this ``SOM+HC'' method on mock deep galaxy samples with realistic systematics and selections derived from the KiDS-Legacy catalogue. Using mock data, we demonstrate that the OR delivers unbiased 2PCF cosmological parameter constraints, removing the $27\sigma$ offset in the galaxy bias parameter that is recovered when adopting uniform randoms. Blinded measurements on the real KiDS-Legacy data show that the corrected 2PCF is robust to the SOM+HC configuration near the optimal setup suggested by the mock tests. Our software is open-source for future usage., Comment: 29 pages, 27 figures, 4 tables

We introduce OneCovariance, an open-source software designed to accurately compute covariance matrices for an arbitrary set of two-point summary statistics across a variety of large-scale structure tracers. Utilising the halo model, we estimate the statistical properties of matter and biased tracer fields, incorporating all Gaussian, non-Gaussian, and super-sample covariance terms. The flexible configuration permits user-specific parameters, such as the complexity of survey geometry, the halo occupation distribution employed to define each galaxy sample, or the form of the real-space and/or Fourier space statistics to be analysed. We illustrate the capabilities of OneCovariance within the context of a cosmic shear analysis of the final data release of the Kilo-Degree Survey (KiDS-Legacy). Upon comparing our estimated covariance with measurements from mock data and calculations from independent software, we ascertain that OneCovariance achieves accuracy at the per cent level. When assessing the impact of ignoring complex survey geometry in the cosmic shear covariance computation, we discover misestimations at approximately the $10\%$ level for cosmic variance terms. Nonetheless, these discrepancies do not significantly affect the KiDS-Legacy recovery of cosmological parameters. We derive the cross-covariance between real-space correlation functions, bandpowers, and COSEBIs, facilitating future consistency tests among these three cosmic shear statistics. Additionally, we calculate the covariance matrix of photometric-spectroscopic galaxy clustering measurements, validating Jackknife covariance estimates for calibrating KiDS-Legacy redshift distributions. The OneCovariance can be found on github Hub together with a comprehensive documentation and examples., Comment: 37 pages, 11 figures, to be submitted to A&A, code available at https://github.com/rreischke/OneCovariance

Understanding the origins of massive black hole seeds and their co-evolution with their host galaxy requires studying intermediate-mass black holes (IMBHs) and estimating their mass. However, measuring the mass of these IMBHs is challenging due to the high spatial resolution requirement. A spectrophotometric reverberation monitoring is performed for a low-luminosity Seyfert 1 galaxy NGC 4395 to measure the size of the broad line region (BLR) and black hole mass. The data were collected using the 1.3-m Devasthal fast optical telescope (DFOT) and 3.6-m Devasthal optical telescope (DOT) at ARIES, Nainital, over two consecutive days in March 2022. The analysis revealed strong emission lines in the spectra and light curves of merged 5100{\AA} spectroscopic continuum flux ($f_{\mathrm{5100}}$) with photometric continuum V-band and H$\alpha$, with fractional variabilities of 6.38\% and 6.31\% respectively. In comparison to several previous studies with lag estimation $<$ 90 minutes, our calculated H$\alpha$ lag supersedes by $125.0^{+6.2}_{-6.1}$ minutes using ICCF and {\small JAVELIN} methods. The velocity dispersion ($\sigma_{\mathrm{line}}$) of the broad line clouds is measured to be $544.7^{+22.4}_{-25.1}$ km s$^{-1}$, yielding a black hole mass of $\sim$ $2.2^{+0.2}_{-0.2}\times 10^{4}M_{\mathrm{\odot}}$ and an Eddington ratio of 0.06., Comment: 17 pages, 8 figures, accepted for publication in ApJ

We present a method to refine photometric redshift galaxy catalogs by comparing their color-space matching with overlapping spectroscopic calibration data. We focus on cases where photometric redshifts (photo-$z$) are estimated empirically. Identifying galaxies that are poorly represented in spectroscopic data is crucial, as their photo-$z$ may be unreliable due to extrapolation beyond the training sample. Our approach uses a self-organizing map (SOM) to project a multi-dimensional parameter space of magnitudes and colors onto a 2-D manifold, allowing us to analyze the resulting patterns as a function of various galaxy properties. Using SOM, we compare the Kilo-Degree Survey bright galaxy sample (KiDS-Bright), limited to $r<20$ mag, with various spectroscopic samples, including the Galaxy And Mass Assembly (GAMA). Our analysis reveals that GAMA under-represents KiDS-Bright at its faintest ($r\gtrsim19.5$) and highest-redshift ($z\gtrsim0.4$) ranges, however no strong trends in color or stellar mass. By incorporating additional spectroscopic data from the SDSS, 2dF, and early DESI, we identify SOM cells where photo-$z$ are estimated suboptimally. We derive a set of SOM-based criteria to refine the photometric sample and improve photo-$z$ statistics. For the KiDS-Bright sample, this improvement is modest: exclusion of the least represented 20% of the sample reduces photo-$z$ scatter by less than 10%. We conclude that GAMA, used for KiDS-Bright photo-$z$ training, is sufficiently representative for reliable redshift estimation across most of the color space. Future spectroscopic data from surveys such as DESI should be better suited for exploiting the full improvement potential of our method., Comment: Published in A&A

With the growing prevalence of large language models, it is increasingly common to annotate datasets for machine learning using pools of crowd raters. However, these raters often work in isolation as individual crowdworkers. In this work, we regard annotation not merely as inexpensive, scalable labor, but rather as a nuanced interpretative effort to discern the meaning of what is being said in a text. We describe a novel, collaborative, and iterative annotator-in-the-loop methodology for annotation, resulting in a 'Bridging Benchmark Dataset' of comments relevant to bridging divides, annotated from 11,973 textual posts in the Civil Comments dataset. The methodology differs from popular anonymous crowd-rating annotation processes due to its use of an in-depth, iterative engagement with seven US-based raters to (1) collaboratively refine the definitions of the to-be-annotated concepts and then (2) iteratively annotate complex social concepts, with check-in meetings and discussions. This approach addresses some shortcomings of current anonymous crowd-based annotation work, and we present empirical evidence of the performance of our annotation process in the form of inter-rater reliability. Our findings indicate that collaborative engagement with annotators can enhance annotation methods, as opposed to relying solely on isolated work conducted remotely. We provide an overview of the input texts, attributes, and annotation process, along with the empirical results and the resulting benchmark dataset, categorized according to the following attributes: Alienation, Compassion, Reasoning, Curiosity, Moral Outrage, and Respect., Comment: Accepted Paper at AAAI/ACM Artificial Intelligence, Ethics, and Society (AIES)

Reservoir computing has been shown to be a useful framework for predicting critical transitions of a dynamical system if the bifurcation parameter is also provided as an input. Its utility is significant because in real-world scenarios, the exact model equations are unknown. This Letter shows how the theory of dynamical system provides the underlying mechanism behind the prediction. Using numerical methods, by considering dynamical systems which show Hopf bifurcation, we demonstrate that the map produced by the reservoir after a successful training undergoes a Neimark-Sacker bifurcation such that the critical point of the map is in immediate proximity to that of the original dynamical system. In addition, we have compared and analyzed different structures in the phase space. Our findings provide insight into the functioning of machine learning algorithms for predicting critical transitions.

Impact of noise in coupled oscillators with pairwise interactions has been extensively explored. Here, we study stochastic second-order coupled Kuramoto oscillators with higher-order interactions, and show that as noise strength increases the critical points associated with synchronization transitions shift toward higher coupling values. By employing the perturbation analysis, we obtain an expression for the forward critical point as a function of inertia and noise strength. Further, for overdamped systems we show that as noise strength increases, the first-order transition switches to second-order even for higher-order couplings. We include a discussion on nature of critical points obtained through Ott-Antonsen ansatz.

We study transfer learning for estimation in latent variable network models. In our setting, the conditional edge probability matrices given the latent variables are represented by $P$ for the source and $Q$ for the target. We wish to estimate $Q$ given two kinds of data: (1) edge data from a subgraph induced by an $o(1)$ fraction of the nodes of $Q$, and (2) edge data from all of $P$. If the source $P$ has no relation to the target $Q$, the estimation error must be $\Omega(1)$. However, we show that if the latent variables are shared, then vanishing error is possible. We give an efficient algorithm that utilizes the ordering of a suitably defined graph distance. Our algorithm achieves $o(1)$ error and does not assume a parametric form on the source or target networks. Next, for the specific case of Stochastic Block Models we prove a minimax lower bound and show that a simple algorithm achieves this rate. Finally, we empirically demonstrate our algorithm's use on real-world and simulated graph transfer problems.

Finite-size systems of Kuramoto model display intricate dynamics, especially in the presence of multi-stability where both coherent and incoherent states coexist. We investigate such scenario in globally coupled populations of Kuramoto phase oscillators with higher-order interactions, and observe that fluctuations inherent to finite-size systems drives the transition to the synchronized state occurring before the critical point in the thermodynamic limit. Using numerical methods, we plot the first exit time distribution of the magnitude of complex order parameter and obtain numerical transition probabilities across various system sizes. Further, we extend this study to a two-population oscillator system, and using velocity field of the associated order parameters, show the emergence of a new fixed point corresponding to a partially synchronized state arising due to the finite-size effect which is absent in the thermodynamics limit.

Binary rutile oxides of 5d metals such as IrO2, stand out as a paradox due to limited experimental studies despite the rich predicted quantum phenomena. Here, we investigate the electrical transport properties of IrO2 by engineering epitaxial thin films grown via hybrid molecular beam epitaxy. Our findings reveal phonon-limited carrier transport and thickness-dependent anisotropic in-plane resistance in IrO2 (110) films, the latter suggesting a complex relationship between strain relaxation and orbital hybridization. Magneto-transport measurements reveal a previously unobserved non-linear Hall effect. A two-carrier analysis of this effect shows the presence of minority carriers with mobility exceeding 3000 cm2/Vs at 1.8 K. These results point towards emergent properties in 5d metal oxides that can be controlled using dimensionality and epitaxial strain., Comment: 16 pages

Water-soluble sacrificial layers based on epitaxially-grown, single crystalline (Ca, Sr, Ba)3Al2O6 layer are widely used for creating free-standing perovskite oxide membranes. However, obtaining these sacrificial layers with intricate stoichiometry remains a challenge, especially for molecular beam epitaxy (MBE). In this study, we demonstrate the hybrid MBE growth of epitaxial, single crystalline SrTiO3 films using a solution processed, amorphous SrCa2Al2O6 sacrificial layer onto SrTiO3 (001) substrates. Prior to the growth, the oxygen plasma exposure was used to first create the crystalline SrCa2Al2O6 layer with well-defined surface crystallinity. Utilizing reflection high energy electron diffraction, x-ray diffraction, and atomic force microscopy, we observe an atomic layer-by-layer growth of epitaxial, single crystalline SrTiO3 film on the SrCa2Al2O6 layer with atomically smooth surfaces. The SrCa2Al2O6 layer was subsequently dissolved in de-ionized water to create free-standing SrTiO3 membranes that were transferred onto a metal-coated Si wafer. Membranes created with Sr-deficiency revealed ferroelectric-like behavior measured using piezo force microscopy whereas stoichiometric films remained paraelectric-like. These findings underscore the viability of using ex-situ deposited amorphous SrCa2Al2O6 for epitaxial, single crystalline growth, as well as the importance of point defects in determining the ferroic properties in membranes., Comment: 16 pages

Exploration and advancements in ultra-wide bandgap (UWBG) semiconductors are pivotal for next-generation high-power electronics and deep-ultraviolet (DUV) optoelectronics. A critical challenge lies in finding a semiconductor that is highly transparent to DUV wavelengths yet conductive with high mobility at room temperature. Here, we achieved both high transparency and high conductivity by employing a thin heterostructure design. The heterostructure facilitated high conductivity by screening phonons using free carriers, while the atomically thin films ensured high transparency. We utilized a heterostructure comprising SrSnO3/La:SrSnO3/GdScO3 (110) and applied electrostatic gating to effectively separate electrons from their dopant atoms. This led to a modulation of carrier density from 1018 cm-3 to 1020 cm-3, with room temperature mobilities ranging from 40 to 140 cm2V-1s-1. The phonon-limited mobility, calculated from first principles, closely matched experimental results, suggesting that room-temperature mobility could be further increased with higher electron density. Additionally, the sample exhibited 85% optical transparency at a 300 nm wavelength. These findings highlight the potential of heterostructure design for transparent UWBG semiconductor applications, especially in deep-ultraviolet regime., Comment: 32 pages

Advances in material fabrication techniques and growth methods have opened up a new chapter for twistronics, in the form of twisted freestanding three-dimensional material membranes. Through first-principles calculations based on density functional theory, we investigate the crystal and electronic structures of twisted bilayer BaTiO$_3$. Our findings reveal that large stacking fault energy leads to chiral in-plane vortex pattern that was recently observed in experiments. Moreover, we also found non-zero out-of-plane local dipole moments, indicating that the strong interlayer interaction might offer promising strategy to stabilize ferroelectric order in the two-dimensional limit. Remarkably, the vortex pattern in the twisted BaTiO$_3$ bilayer support localized electronic states with quasi-flat bands, associated with the interlayer hybridization of oxygen $p_z$ orbitals. We found that the associated band width reaches a minimum at $\sim$19$^{\circ}$ twisting, configuring the largest magic angle in moir\'e systems reported so far. Further, the moir\'e vortex pattern bears a striking resemblance to two interpenetrating Lieb lattices and corresponding tight-binding model provides a comprehensive description of the evolution the moir\'e bands with twist angle and reveals the topological nature of these states., Comment: 8 pages, 5 figures

Altermagnetism refers to a wide class of compensated magnetic orders featuring magnetic sublattices with opposite spins related by rotational symmetry rather than inversion or translational operations, resulting in non-trivial spin splitting and high-order multipolar orders. Here, by combining theoretical analysis, electrical transport, X-ray and optical spectroscopies, and nonlinear optical measurements, we establish a phase diagram in hybrid molecular beam epitaxy-grown RuO2/TiO2 (110) films, mapping the broken symmetries along the altermagnetic/electronic/structural phase transitions as functions of film thickness and temperature. This phase diagram features a novel altermagnetic metallic polar phase in strained 2 nm samples, extending the concept of multiferroics to altermagnetic systems. These results provide a comprehensive understanding of altermagnetism upon epitaxial heterostructure design for emergent novel phases with multifunctionalities., Comment: 15 pages

Recent generative AI systems have demonstrated more advanced persuasive capabilities and are increasingly permeating areas of life where they can influence decision-making. Generative AI presents a new risk profile of persuasion due the opportunity for reciprocal exchange and prolonged interactions. This has led to growing concerns about harms from AI persuasion and how they can be mitigated, highlighting the need for a systematic study of AI persuasion. The current definitions of AI persuasion are unclear and related harms are insufficiently studied. Existing harm mitigation approaches prioritise harms from the outcome of persuasion over harms from the process of persuasion. In this paper, we lay the groundwork for the systematic study of AI persuasion. We first put forward definitions of persuasive generative AI. We distinguish between rationally persuasive generative AI, which relies on providing relevant facts, sound reasoning, or other forms of trustworthy evidence, and manipulative generative AI, which relies on taking advantage of cognitive biases and heuristics or misrepresenting information. We also put forward a map of harms from AI persuasion, including definitions and examples of economic, physical, environmental, psychological, sociocultural, political, privacy, and autonomy harm. We then introduce a map of mechanisms that contribute to harmful persuasion. Lastly, we provide an overview of approaches that can be used to mitigate against process harms of persuasion, including prompt engineering for manipulation classification and red teaming. Future work will operationalise these mitigations and study the interaction between different types of mechanisms of persuasion.

Online commenting platforms have commonly developed systems to address online harms by removing and down-ranking content. An alternative, under-explored approach is to focus on up-ranking content to proactively prioritize prosocial commentary and set better conversational norms. We present a study with 460 English-speaking US-based news readers to understand the effects of re-ranking comments by constructiveness, curiosity, and personal stories on a variety of outcomes related to willingness to participate and engage, as well as perceived credibility and polarization in a comment section. In our rich-media survey experiment, participants across these four ranking conditions and a control group reviewed prototypes of comment sections of a Politics op-ed and Dining article. We found that outcomes varied significantly by article type. Up-ranking curiosity and constructiveness improved a number of measures for the Politics article, including perceived Respect, Trustworthiness, and Interestingness of the comment section. Constructiveness also increased perceptions that the comments were favorable to Republicans, with no condition worsening perceptions of partisans. Additionally, in the Dining article, personal stories and constructiveness rankings significantly improved the perceived informativeness of the comments. Overall, these findings indicate that incorporating prosocial qualities of speech into ranking could be a promising approach to promote healthier, less polarized dialogue in online comment sections.

The island paradigm asserts that after the Page time the operators in the interior of an AdS2 eternal black hole in equilibrium with a finite temperature non-gravitating bath can not be reconstructed using the operators in the black hole region outside the horizon. In a recent paper, we demonstrated this using the black hole interior reconstruction proposal due to Leutheusser and Liu, based on the half-sided translations. This was done by introducing a notion of the reduced half-sided translations associated with the algebra of operators restricted to the black hole region outside the horizon, and by showing that albeit the reduced half-sided translations translate operators in the black hole region outside the horizon to the black hole interior before the Page time, it fails to do so after the Page time. In this paper, we demonstrate the second assertion of the island paradigm, which states that after the Page time the operators in the black hole interior can be reconstructed using the operators in the bath. We show that even though before the Page time the reduced half-sided translations associated with the algebra of operators restricted to the bath do not translate operators in the bath to the black hole interior, after the Page time they take them to the black hole interior., Comment: 24 pages, 9 figures. arXiv admin note: text overlap with arXiv:2312.11085

We introduce FLAME, a machine-learning algorithm designed to fit Voigt profiles to HI Lyman-alpha (Ly$\alpha$) absorption lines using deep convolutional neural networks. FLAME integrates two algorithms: the first determines the number of components required to fit Ly$\alpha$ absorption lines, and the second calculates the Doppler parameter $b$, the HI column density N$_{\rm HI}$, and the velocity separation of individual components. For the current version of FLAME, we trained it on low-redshift Ly$\alpha$ forests observed with the far-ultraviolet gratings of the Cosmic Origin Spectrograph (COS) on board the Hubble Space Telescope (HST). Using these data, we trained FLAME on $\sim$ $10^6$ simulated Voigt profiles which we forward-modeled to mimic Ly$\alpha$ absorption lines observed with HST-COS in order to classify lines as either single or double components and then determine Voigt profile-fitting parameters. FLAME shows impressive accuracy on the simulated data, identifying more than 98\% (90\%) of single (double) component lines. It determines $b$ values within $\approx \pm{8}~(15)$ km s$^{-1}$ and log $N_{\rm HI}/ {\rm cm}^2$ values within $\approx \pm 0.3~(0.8)$ for 90\% of the single (double) component lines. However, when applied to real data, FLAME's component classification accuracy drops by $\sim$ 10\%. Nevertheless, there is reasonable agreement between the $b$ and N$_{\rm HI}$ distributions obtained from traditional Voigt profile-fitting methods and FLAME's predictions. Our mock HST-COS data analysis, designed to emulate real data parameters, demonstrates that FLAME is able to achieve consistent accuracy comparable to its performance with simulated data. This finding suggests that the drop in FLAME's accuracy when used on real data primarily arises from the difficulty in replicating the full complexity of real data in the training sample., Comment: Accepted for publication in A&A

In this report, we introduce the Gemini 1.5 family of models, representing the next generation of highly compute-efficient multimodal models capable of recalling and reasoning over fine-grained information from millions of tokens of context, including multiple long documents and hours of video and audio. The family includes two new models: (1) an updated Gemini 1.5 Pro, which exceeds the February version on the great majority of capabilities and benchmarks; (2) Gemini 1.5 Flash, a more lightweight variant designed for efficiency with minimal regression in quality. Gemini 1.5 models achieve near-perfect recall on long-context retrieval tasks across modalities, improve the state-of-the-art in long-document QA, long-video QA and long-context ASR, and match or surpass Gemini 1.0 Ultra's state-of-the-art performance across a broad set of benchmarks. Studying the limits of Gemini 1.5's long-context ability, we find continued improvement in next-token prediction and near-perfect retrieval (>99%) up to at least 10M tokens, a generational leap over existing models such as Claude 3.0 (200k) and GPT-4 Turbo (128k). Finally, we highlight real-world use cases, such as Gemini 1.5 collaborating with professionals on completing their tasks achieving 26 to 75% time savings across 10 different job categories, as well as surprising new capabilities of large language models at the frontier; when given a grammar manual for Kalamang, a language with fewer than 200 speakers worldwide, the model learns to translate English to Kalamang at a similar level to a person who learned from the same content.

The mechanism of superconductivity in materials with aborted ferroelectricity and the emergence of a dilute metallic phase in systems like doped-SrTiO$_3$ are outstanding issues in condensed matter physics. This dilute metal has features both similar and different to those found in the normal state of other unconventional superconductors. We have investigated the optical properties of the dilute metallic phase in doped-SrTiO$_3$ using THz time-domain spectroscopy. At low frequencies the THz response exhibits a Drude-like form as expected for typical metal-like conductivity. We observed the frequency and temperature dependencies to the low energy scattering rate $\Gamma(\omega, T) \propto (\hbar\omega)^2 + (p \pi k_BT)^2 $ expected in a conventional Fermi liquid, despite the fact that densities are too small to allow current decay through electron-electron scattering. However we find the lowest known $p$ values of 0.39-0.72. As $p$ is 2 in a canonical Fermi liquid and existing models based on energy dependent elastic scattering bound $p$ from below to 1, our observation lies outside current explanation. Our data also gives insight into the high temperature regime and shows that the temperature dependence of the resistivity derives in part from strong T dependent mass renormalizations., Comment: 6 pages, 4figures

In network formation games, agents form edges with each other to maximize their utility. Each agent's utility depends on its private beliefs and its edges in the network. Strategic agents can misrepresent their beliefs to get a better resulting network. Most prior works in this area consider honest agents or a single strategic agent. Instead, we propose a model where any subset of agents can be strategic. We provide an efficient algorithm for finding the set of Nash equilibria, if any exist, and certify their nonexistence otherwise. We also show that when several strategic agents are present, their utilities can increase or decrease compared to when they are all honest. Small changes in the inter-agent correlations can cause such shifts. In contrast, the simpler one-strategic-agent setting explored in the literature lacks such complex patterns. Finally, we develop an algorithm by which new agents can learn the information needed for strategic behavior. Our algorithm works even when the (unknown) strategic agents deviate from the Nash-optimal strategies. We verify these results on both simulated networks and a real-world dataset on international trade.

Plan-view transmission electron microscopy (TEM) samples are key to understand the atomic structure and associated properties of materials along their growth orientation, especially for thin films that are stain-engineered onto different substrates for property tuning. In this work, we present a method to prepare high-quality plan-view samples for analytical STEM study from thin-films using a dual-beam focused ion beam scanning electron microscope (FIB-SEM) system. The samples were prepared from thin films of perovskite oxides and metal oxides ranging from 20-80 nm thicknesses, grown on different substrates using molecular beam epitaxy. A site-specific sample preparation from the area of interest is described, which includes sample attachment and thinning techniques to minimize damage to the final TEM samples. While optimized for the thin film-like geometry, this method can be extended to other site-specific plan-view samples from bulk materials. Aberration-corrected scanning (S)TEM was used to access the quality of the thin film in each sample. This enabled direct visualization of line defects in perovskite BaSnO3 and Ir particle formation and texturing in IrO2 films.

An AdS$_2$ black hole in equilibrium with a finite temperature non-gravitating bath comes with a Hawking-like information paradox. The resolution of this paradox requires introducing an island for the bath after the Page time. Since the island region contains the black hole interior, the consistency of the island paradigm demands the failure of any interior reconstruction proposal that uses only the operators in the AdS$_2$ region outside the black hole horizon after the Page time. In this paper, we investigate the consistency of the island paradigm using the black hole interior reconstruction proposal due to Leutheusser and Liu. They argued that the operators in the interior of a black hole can be reconstructed by the half-sided translations of the operators outside the black hole horizon. However, in order to illustrate the island paradigm we need to modify the Leutheusser-Liu proposal by introducing the notion of the reduced half-sided translations. The reduced half-sided translations, unlike the half-sided translations, have non-trivial action only on the operators in the AdS$_2$ black hole region. As a result, the reconstructed interior operators are expressed only using the operators in the AdS$_2$ region outside the black hole horizon. We demonstrate the consistency of the island paradigm by showing that the reduced half-sided translations which successfully reconstruct the operators in the black hole interior before the Page time become trivial after the Page time, and hence fail to reconstruct the interior operators after the Page time., Comment: 31 pages, 14 figures

This report introduces a new family of multimodal models, Gemini, that exhibit remarkable capabilities across image, audio, video, and text understanding. The Gemini family consists of Ultra, Pro, and Nano sizes, suitable for applications ranging from complex reasoning tasks to on-device memory-constrained use-cases. Evaluation on a broad range of benchmarks shows that our most-capable Gemini Ultra model advances the state of the art in 30 of 32 of these benchmarks - notably being the first model to achieve human-expert performance on the well-studied exam benchmark MMLU, and improving the state of the art in every one of the 20 multimodal benchmarks we examined. We believe that the new capabilities of the Gemini family in cross-modal reasoning and language understanding will enable a wide variety of use cases. We discuss our approach toward post-training and deploying Gemini models responsibly to users through services including Gemini, Gemini Advanced, Google AI Studio, and Cloud Vertex AI.

Gravitational lensing is proven to be one of the most efficient tools for studying the Universe. The spectral confirmation of such sources requires extensive calibration. This paper discusses the spectral extraction technique for the case of multiple source spectra being very near each other. Using the masking technique, we first detect high Signal-to-Noise (S/N) peaks in the CCD spectral image corresponding to the location of the source spectra. This technique computes the cumulative signal using a weighted sum, yielding a reliable approximation for the total counts contributed by each source spectrum. We then proceed with the subtraction of the contaminating spectra. Applying this method, we confirm the nature of 11 lensed quasar candidates., Comment: Accepted for publication in Bulletin de la Soci\'et\'e Royale des Sciences de Li\`ege (BSRSL)

In cosmological analyses, precise redshift determination remains pivotal for understanding cosmic evolution. However, with only a fraction of galaxies having spectroscopic redshifts (spec-$z$s), the challenge lies in estimating redshifts for a larger number. To address this, photometry-based redshift (photo-$z$) estimation, employing machine learning algorithms, is a viable solution. Identifying the limitations of previous methods, this study focuses on implementing deep learning (DL) techniques within the Kilo-Degree Survey (KiDS) Bright Galaxy Sample for more accurate photo-$z$ estimations. Comparing our new DL-based model against prior `shallow' neural networks, we showcase improvements in redshift accuracy. Our model gives mean photo-$z$ bias $\langle \Delta z\rangle= 10^{-3}$ and scatter $\mathrm{SMAD}(\Delta z)=0.016$, where $\Delta z = (z_\mathrm{phot}-z_\mathrm{spec})/(1+z_\mathrm{spec})$. This research highlights the promising role of DL in revolutionizing photo-$z$ estimation., Comment: Proceedings of the XLI Polish Astronomical Society Meeting, 11-15 September 2023, Toru\'n, Poland

Epitaxially grown RuO2 films on TiO2 (110) exhibit significant in-plane strain anisotropy, with a compressive strain of - 4.7% along the [001] crystalline direction and a tensile strain of +2.3% along [1-10]. As the film thickness increases, anisotropic strain relaxation is expected. By fabricating Hall bar devices with current channels along two in-plane directions <001> and <1-10>, we revealed anisotropic in-plane transport in RuO2/TiO2 (110) films grown via solid-source metal-organic molecular beam epitaxy approach. For film thicknesses (t_film) < 3.6 nm, the resistivity along <001> exceeds that along <1-10> direction at all temperatures. With further decrease in film thicknesses, we uncover a transition from metallic to insulating behavior at t_film <2.1 nm. Our combined temperature- and magnetic field-dependent electrical transport measurements reveal that this transition from metallic to insulating behavior is driven by electron-electron interactions., Comment: 15 pages

The advancement in thin-film exfoliation for synthesizing oxide membranes has opened up new possibilities for creating artificially-assembled heterostructures with structurally and chemically incompatible materials. The sacrificial layer method is a promising approach to exfoliate as-grown films from a compatible material system, allowing their integration with dissimilar materials. Nonetheless, the conventional sacrificial layers often possess intricate stoichiometry, thereby constraining their practicality and adaptability, particularly when considering techniques like Molecular Beam Epitaxy (MBE). This is where easy-to-grow binary alkaline earth metal oxides with a rock salt crystal structure are useful. These oxides, which include (Mg, Ca, Sr, Ba)O, can be used as a sacrificial layer covering a much broader range of lattice parameters compared to conventional sacrificial layers and are easily dissolvable in deionized water. In this study, we show the epitaxial growth of single-crystalline perovskite SrTiO3 (STO) on sacrificial layers consisting of crystalline SrO, BaO, and Ba1-xCaxO films, employing a hybrid MBE method. Our results highlight the rapid (< 5 minutes) dissolution of the sacrificial layer when immersed in deionized water, facilitating the fabrication of millimeter-sized STO membranes. Using high-resolution x-ray diffraction, atomic-force microscopy, scanning transmission electron microscopy, impedance spectroscopy, and scattering-type near-field optical microscopy (SNOM), we demonstrate epitaxial STO membranes with bulk-like intrinsic dielectric properties. The employment of alkaline earth metal oxides as sacrificial layers is likely to simplify membrane synthesis, particularly with MBE, thus expanding research possibilities., Comment: 36 pages, 4 figures

Explosive synchronization refers to an abrupt (first order) transition to non-zero phase order parameter in oscillatory networks, underpinned by the bistability of synchronous and asynchronous states. Growing evidence suggests that this phenomenon might be no less general then the celebrated Kuramoto scenario that belongs to the second order universality class. Importantly, the recent examples demonstrate that explosive synchronization can occur for certain network topologies and coupling types, like the global higher-order coupling, without specific requirements on the individial oscillator dynamics or dynamics-network correlations. Here we demonstrate a rich picture of explosive synchronization and desynchronization transitions in multiplex networks, where it is sufficient to have a single random sparsly connected layer with higher-order coupling terms (and not necessarily in the synchronization regime on its own), the other layer being a regular lattice without own phase transitions at all. Moreover, explosive synchronization emerges even when the random layer has only low-order pairwise coupling, althoug the hysteresis interval becomes narrow and explosive desynchronization is no longer observed. The relevance to the normal and pathological dynamics of neural-glial networks is pointed out., Comment: 8 pages, 6 figures

We present radio observations of 24 confirmed and candidate strongly lensed quasars identified by the Gaia Gravitational Lenses (GraL) working group. We detect radio emission from 8 systems in 5.5 and 9 GHz observations with the Australia Telescope Compact Array (ATCA), and 12 systems in 6 GHz observations with the Karl G. Jansky Very Large Array (VLA). The resolution of our ATCA observations is insufficient to resolve the radio emission into multiple lensed images, but we do detect multiple images from 11 VLA targets. We have analysed these systems using our observations in conjunction with existing optical measurements, including measuring offsets between the radio and optical positions, for each image and building updated lens models. These observations significantly expand the existing sample of lensed radio quasars, suggest that most lensed systems are detectable at radio wavelengths with targeted observations, and demonstrate the feasibility of population studies with high resolution radio imaging.

We prove the generalized second law (GSL) for higher curvature gravity theories when the matter sector is non-minimally coupled. The validity of our proof is in the regime of linearized fluctuations about equilibrium black holes, which is the same regime as considered in the previous proofs by Wall and Sarkar. These proofs were provided in different gravity theories - for instance, Lovelock theory and higher curvature gravity - but the matter sector was always taken to be minimally coupled. In this article, we describe how to generalize the proof of linearized semi-classical GSL when the matter sector comes with non-minimal couplings. The proof proceeds by suitably evaluating the matter path integral in the stress tensor expectation value by treating the higher derivative couplings in an effective field theory setting. We use the recently established result of the linearized second law for such theories., Comment: 21 pages