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The scenario of feedback-free starbursts (FFB), which predicts excessively bright galaxies at cosmic dawn as observed using JWST, may provide a natural setting for black hole (BH) growth. This involves the formation of intermediate-mass seed BHs and their runaway mergers into super-massive BHs with high BH-to-stellar mass ratios and low AGN luminosities. We present a scenario of merger-driven BH growth in FFB galaxies and study its feasibility. BH seeds form within the building blocks of the FFB galaxies, namely, thousands of compact star clusters, each starbursting in a free-fall time of a few Myr before the onset of stellar and supernova feedback. The BH seeds form by rapid core collapse in the FFB clusters, in a few free-fall times, sped up by the migration of massive stars due to the young, broad stellar mass function and stimulated by a `gravo-gyro' instability due to internal cluster rotation and flattening. BHs of $10^4 M_\odot$ are expected in $10^6 M_\odot$ FFB clusters within sub-kpc galactic disks at $z \sim 10$. The BHs then migrate to the galaxy center by dynamical friction, hastened by the compact FFB stellar galactic disk configuration. Efficient mergers of the BH seeds will produce $10^{6-8} M_\odot$ BHs with a BH-to-stellar mass ratio $\sim 0.01$ by $z \sim 4-7$, as observed. The growth of the central BH by mergers can overcome the bottleneck introduced by gravitational wave recoils if the BHs inspiral within a relatively cold disk or if the escape velocity from the galaxy is boosted by a wet compaction event. Such events, common in massive galaxies at high redshifts, can also help by speeding up the inward BH migration and by providing central gas to assist with the final parsec problem. The cold disk version of the FFB scenario provides a feasible route for the formation of supermassive BHs., Comment: 24 pages, 14 figures

TOI-1266 is a benchmark system of two temperate ($<$ 450 K) sub-Neptune-sized planets orbiting a nearby M dwarf exhibiting a rare inverted architecture with a larger interior planet. In this study, we characterize transit timing variations (TTVs) in the TOI-1266 system using high-precision ground-based follow-up and new TESS data. We confirm the presence of a third exterior non-transiting planet, TOI-1266 d (P = 32.5 d, $M_d$ = 3.68$^{+1.05}_{-1.11} M_{\oplus}$), and combine the TTVs with archival radial velocity (RV) measurements to improve our knowledge of the planetary masses and radii. We find that, consistent with previous studies, TOI-1266 b ($R_b$ = 2.52 $\pm$ 0.08 $R_{\oplus}$, $M_b$ = 4.46 $\pm$ 0.69 $M_{\oplus}$) has a low bulk density requiring the presence of a hydrogen-rich envelope, while TOI-1266 c ($R_c$ = 1.98 $\pm$ 0.10 $R_{\oplus}$, $M_c$ = 3.17 $\pm$ 0.76 $M_{\oplus}$) has a higher bulk density that can be matched by either a hydrogen-rich or water-rich envelope. Our new dynamical model reveals that this system is arranged in a rare configuration with the inner and outer planets located near the 3:1 period ratio with a non-resonant planet in between them. Our dynamical fits indicate that the inner and outer planet have significantly nonzero eccentricities ($e_b + e_d = 0.076^{+0.029}_{-0.019}$), suggesting that TOI-1266 b may have an inflated envelope due to tidal heating. Finally, we explore the corresponding implications for the formation and long-term evolution of the system, which contains two of the most favorable cool ($<$ 500 K) sub-Neptunes for atmospheric characterization with JWST., Comment: 36 pages, 19 figures, 5 tables, submitted to The Astronomical Journal

We describe AthenaK: a new implementation of the Athena++ block-based adaptive mesh refinement (AMR) framework using the Kokkos programming model. Finite volume methods for Newtonian, special relativistic (SR), and general relativistic (GR) hydrodynamics and magnetohydrodynamics (MHD), and GR-radiation hydrodynamics and MHD, as well as a module for evolving Lagrangian tracer or charged test particles (e.g., cosmic rays) are implemented using the framework. In two companion papers we describe (1) a new solver for the Einstein equations based on the Z4c formalism and (2) a GRMHD solver in dynamical spacetimes also implemented using the framework, enabling new applications in numerical relativity. By adopting Kokkos, the code can be run on virtually any hardware, including CPUs, GPUs from multiple vendors, and emerging ARM processors. AthenaK shows excellent performance and weak scaling, achieving over one billion cell updates per second for hydrodynamics in three-dimensions on a single NVIDIA Grace Hopper processor and with a typical parallel efficiency of 80% on 65536 AMD GPUs on the OLCF Frontier system. Such performance portability enables AthenaK to leverage modern exascale computing systems for challenging applications in astrophysical fluid dynamics, numerical relativity, and multimessenger astrophysics., Comment: Submitted to ApJS

We introduce a learning-guided motion planning framework that provides initial seed trajectories using a diffusion model for trajectory optimization. Given a workspace, our method approximates the configuration space (C-space) obstacles through a key-configuration representation that consists of a sparse set of task-related key configurations, and uses this as an input to the diffusion model. The diffusion model integrates regularization terms that encourage collision avoidance and smooth trajectories during training, and trajectory optimization refines the generated seed trajectories to further correct any colliding segments. Our experimental results demonstrate that using high-quality trajectory priors, learned through our C-space-grounded diffusion model, enables efficient generation of collision-free trajectories in narrow-passage environments, outperforming prior learning- and planning-based baselines. Videos and additional materials can be found on the project page: https://kiwi-sherbet.github.io/PRESTO., Comment: Submitted to ICRA 2025

In recent years, the Robotics field has initiated several efforts toward building generalist robot policies through large-scale multi-task Behavior Cloning. However, direct deployments of these policies have led to unsatisfactory performance, where the policy struggles with unseen states and tasks. How can we break through the performance plateau of these models and elevate their capabilities to new heights? In this paper, we propose FLaRe, a large-scale Reinforcement Learning fine-tuning framework that integrates robust pre-trained representations, large-scale training, and gradient stabilization techniques. Our method aligns pre-trained policies towards task completion, achieving state-of-the-art (SoTA) performance both on previously demonstrated and on entirely novel tasks and embodiments. Specifically, on a set of long-horizon mobile manipulation tasks, FLaRe achieves an average success rate of 79.5% in unseen environments, with absolute improvements of +23.6% in simulation and +30.7% on real robots over prior SoTA methods. By utilizing only sparse rewards, our approach can enable generalizing to new capabilities beyond the pretraining data with minimal human effort. Moreover, we demonstrate rapid adaptation to new embodiments and behaviors with less than a day of fine-tuning. Videos can be found on the project website at https://robot-flare.github.io/

We report the fabrication and characterisation of a multi-core anti-resonant hollow core fibre with low inter-core coupling. The optical losses were 0.03 and 0.08 dB/m at 620 and 1000 nm respectively, while the novel structure provides new insights into hollow core fibre design and fabrication.

We present a velocity-resolved reverberation mapping analysis of the hypervariable quasar RM160 (SDSS J141041.25+531849.0) at z = 0.359 with 153 spectroscopic epochs of data representing a ten-year baseline (2013-2023). We split the baseline into two regimes based on the 3x flux increase in the light curve: a 'low state' phase during the years 2013-2019 and a 'high state' phase during the years 2022-2023. The velocity-resolved lag profiles (VRLP) indicate that gas with different kinematics dominates the line emission in different states. The H\b{eta} VRLP begins with a signature of inflow onto the BLR in the 'low state', while in the 'high state' it is flatter with less signature of inflow. The H{\alpha} VRLP begins consistent with a virialized BLR in the 'low state', while in the 'high state' shows a signature of inflow. The differences in the kinematics between the Balmer lines and between the 'low state' and the 'high state' suggests complex BLR dynamics. We find that the BLR radius and velocity (both FWHM and {\sigma}) do not obey a constant virial product throughout the monitoring period. We find that BLR lags and continuum luminosity are correlated, consistent with rapid response of the BLR gas to the illuminating continuum. The BLR kinematic profile changes in unpredictable ways that are not related to continuum changes and reverberation lag. Our observations indicate that non-virial kinematics can significantly contribute to observed line profiles, suggesting caution for black-hole mass estimation in luminous and highly varying quasars like RM160., Comment: 23 pages, 17 figures

We introduce an extension to the AthenaK code for general-relativistic magnetohydrodynamics (GRMHD) in dynamical spacetimes using a 3+1 conservative Eulerian formulation. Like the fixed-spacetime GRMHD solver, we use standard finite-volume methods to evolve the fluid and a constrained transport scheme to preserve the divergence-free constraint for the magnetic field. We also utilize a first-order flux correction (FOFC) scheme to reduce the need for an artificial atmosphere and optionally enforce a maximum principle to improve robustness. We demonstrate the accuracy of AthenaK using a set of standard tests in flat and curved spacetimes. Using a SANE accretion disk around a Kerr black hole, we compare the new solver to the existing solver for stationary spacetimes using the so-called "HARM-like" formulation. We find that both formulations converge to similar results. We also include the first published binary neutron star (BNS) mergers performed on graphical processing units (GPUs). Thanks to the FOFC scheme, our BNS mergers maintain a relative error of $\mathcal{O}(10^{-11})$ or better in baryon mass conservation up to collapse. Finally, we perform scaling tests of AthenaK on OLCF Frontier, where we show excellent weak scaling of $\geq 80\%$ efficiency up to 32768 GPUs and $74\%$ up to 65536 GPUs for a GRMHD problem in dynamical spacetimes with six levels of mesh refinement. AthenaK achieves an order-of-magnitude speedup using GPUs compared to CPUs, demonstrating that it is suitable for performing numerical relativity problems on modern exascale resources., Comment: 26 pages, 25 figures; to be submitted to ApJS soon

We present the numerical relativity module within AthenaK, an open source performance-portable astrophysics code designed for exascale computing applications. This module employs the Z4c formulation to solve the Einstein equations. We demonstrate its accuracy through a series of standard numerical relativity tests, including convergence of the gravitational waveform from binary black hole coalescence. Furthermore, we conduct scaling tests on OLCF Frontier and NERSC Perlmutter, where AthenaK exhibits excellent weak scaling efficiency of 80% on up to 65,536 AMD MI250X GPUs on Frontier (relative to 4 GPUs) and strong scaling efficiencies of 84% and 77% on AMD MI250X and NVIDIA A100 GPUs on Frontier and Perlmutter respectively. Additionally, we observe a significant performance boost, with two orders of magnitude speedup ($\gtrsim 200\times$) on a GPU compared to a single CPU core, affirming that AthenaK is well-suited for exascale computing, thereby expanding the potential for breakthroughs in numerical relativity research.

Polymer mixtures fractionate between phases depending on their molecular weight. Consequently, by varying solvent conditions, a polydisperse polymer sample can be separated between phases so as to achieve a particular molecular weight distribution in each phase. In principle, predictive physics-based theories can help guide separation design and interpret experimental fractionation measurements. Even so, applying the standard Flory-Huggins model can present a computational challenge for mixtures with many polymeric components of different length, particularly for scarce components at the tails of a distribution. Here, we apply our recently-derived exact analytical solution of multi-component Flory-Huggins theory for polydisperse polymers to understand the principles of polymer fractionation for common molecular weight distributions. Our method reveals that polymer fractionation is highly sensitive to the shape, and in particular the tails, of this distribution. Our results highlight the need for considering the full molecular weight distribution in phase coexistence calculations.

We analyze the steady viscoelastic fluid flow in slowly varying contracting channels of arbitrary shape and present a theory based on the lubrication approximation for calculating the flow rate-pressure drop relation at low and high Deborah ($De$) numbers. Unlike most prior theoretical studies leveraging the Oldroyd-B model, we describe the fluid viscoelasticity using a FENE-CR model and examine how the polymer chains' finite extensibility impacts the pressure drop. We employ the low-Deborah-number lubrication analysis to provide analytical expressions for the pressure drop up to $O(De^4)$. We further consider the ultra-dilute limit and exploit a one-way coupling between the parabolic velocity and elastic stresses to calculate the pressure drop of the FENE-CR fluid for arbitrary values of the Deborah number. Such an approach allows us to elucidate elastic stress contributions governing the pressure drop variations and the effect of finite extensibility for all $De$. We validate our theoretical predictions with two-dimensional numerical simulations and find excellent agreement. We show that, at low Deborah numbers, the pressure drop of the FENE-CR fluid monotonically decreases with $De$, similar to the previous results for the Oldroyd-B and FENE-P fluids. However, at high Deborah numbers, in contrast to a linear decrease for the Oldroyd-B fluid, the pressure drop of the FENE-CR fluid exhibits a non-monotonic variation due to finite extensibility, first decreasing and then increasing with $De$. Nevertheless, even at sufficiently high Deborah numbers, the pressure drop of the FENE-CR fluid in the ultra-dilute and lubrication limits is lower than the corresponding Newtonian pressure drop.

Over the past two decades, tight correlations between black hole masses ($M_\bullet$) and their host galaxy properties have been firmly established at low-$z$ ($z<1$), indicating coevolution of supermassive black holes and galaxies. However, the situation at high-$z$, especially beyond cosmic noon ($z\gtrsim2.5$), is controversial. With a combination of \emph{JWST} NIRCam/wide field slitless spectroscopy (WFSS) from FRESCO, CONGRESS and deep multi-band NIRCam/image data from JADES in the GOODS fields, we study the black hole to galaxy mass relation at z$\sim$1--4. After identifying 18 broad-line active galactic nuclei (BL AGNs) at $0.92.5$) from the WFSS data, we measure their black hole masses based on broad near-infrared lines (Pa $\alpha$, Pa $\beta$, and He\,I $\lambda$10833\,\AA), and constrain their stellar masses ($M_{*}$) from AGN-galaxy image decomposition or SED decomposition. Taking account of the observational biases, the intrinsic scatter of the $M_{\bullet}-M_{*}$ relation, and the errors in mass measurements, we find no significant difference in the $M_{\bullet}/M_{*}$ ratio for 2.5 $< $ z $ <$ 3.6 compared to that at lower redshifts ($1 < z < 2.5$), suggesting no evolution of the $M_{\bullet} - M_{*}$ relation up to z$\sim$4., Comment: 21 pages, 11 figures, submitted to AAS Journals

Highly inclined (edge-on) disk galaxies offer the unique perspective to constrain their intrinsic flattening, $c/a$, where $c$ and $a$ are respectively the vertical and long radial axes of the disk measured at suitable stellar densities. The ratio $c/a$ is a necessary quantity in the assessment of galaxy inclinations, three-dimensional structural reconstructions, total masses, as well as a constraint to galaxy formation models. 3.6 micron maps of 133 edge-on spiral galaxies from the Spitzer Survey of Stellar Structure in Galaxies (S4G) and its early-type galaxy extension are used to revisit the assessment of $c/a$ free from dust extinction and away from the influence of a stellar bulge. We present a simple definition of $c/a$ and explore trends with other galactic physical parameters: total stellar mass, concentration index, total HI mass, mass of the central mass concentration, circular velocity, model-dependent scales, as well as Hubble type. Other than a dependence on early/late Hubble types, and a related trend with light concentration, no other parameters were found to correlate with the intrinsic flattening of spiral galaxies. The latter is mostly constant with $\langle c/a \rangle$ = 0.124 $\pm$ 0.001 (stat) $\pm$ 0.033 (intrinsic/systematic) and greater for earlier types., Comment: 27 full pages, 14 figures, 6 tables, 1 appendix. Submitted to AAS Journals. Comments welcome

In addressing the Department of Energy's April, 2022 announcement of a Bold Decadal Vision for delivering a Fusion Pilot Plant by 2035, associated software tools need to be developed for the integration of real world engineering and supply chain data with advanced science models that are accelerated with Machine Learning. An associated research and development effort has been introduced here with promising early progress on the delivery of a realistic Digital Twin Tokamak that has benefited from accelerated advances by the Princeton University AI Deep Learning innovative near-real-time simulators accompanied by technological capabilities from the NVIDIA Omniverse, an open computing platform for building and operating applications that connect with leading scientific computing visualization software. Working with the CAD files for the GA/DIII-D tokamak including equilibrium evolution as an exemplar tokamak application using Omniverse, the Princeton-NVIDIA collaboration has integrated modern AI/HPC-enabled near-real-time kinetic dynamics to connect and accelerate state-of-the-art, synthetic, HPC simulators to model fusion devices and control systems. The overarching goal is to deliver an interactive scientific digital twin of an advanced MFE tokamak that enables near-real-time simulation workflows built with Omniverse to eventually help open doors to new capabilities for generating clean power for a better future.

The mini proceedings of the "Fourth International Workshop on the Extension Project for the J-PARC Hadron Experimental Facility (HEF-ex 2024) [https://kds.kek.jp/event/46965]" held at J-PARC, February 19-21, 2024, are presented. The workshop was devoted to discussing the physics case that connects both the present and the future Hadron Experimental Facility at J-PARC, covering a wide range of topics in flavor, hadron, and nuclear physics related to both experimental and theoretical activities being conducted at the facility.

Ultralight scalars emerge naturally in several motivated particle physics scenarios and are viable candidates for dark matter. While laboratory detection of such bosons is challenging, their existence in nature can be imprinted on measurable properties of astrophysical black holes (BHs). The phenomenon of superradiance can convert the BH spin kinetic energy into a bound cloud of scalars. In this letter, we propose a new technique for directly measuring the mass of a dark cloud around a spinning BH. We compare the measurement of the BH spin obtained with two independent electromagnetic techniques: continuum fitting and iron K$\alpha$ spectroscopy. Since the former technique depends on a dynamical observation of the BH mass while the latter does not, a mismatch between the two measurements can be used to infer the presence of additional extended mass around the BH. We find that a precision of $\sim 1\%$ on the two spin measurements is required to exclude the null hypothesis of no dark mass around the BH at a 2$\sigma$ confidence level for dark masses about a few percent of the BH mass, as motivated in some superradiance scenarios., Comment: 12 pages, 3 figures, 1 table. Main text 5 pages, 2 figures, 1 table

The jet cross-section and jet-substructure observables in $p$$+$$p$ collisions at $\sqrt{s}=200$ GeV were measured by the PHENIX Collaboration at the Relativistic Heavy Ion Collider (RHIC). Jets are reconstructed from charged-particle tracks and electromagnetic-calorimeter clusters using the anti-$k_{t}$ algorithm with a jet radius $R=0.3$ for jets with transverse momentum within $8.0

Motivated by the study of state opioid policies, we propose a novel approach that uses autoregressive models for causal effect estimation in settings with panel data and staggered treatment adoption. Specifically, we seek to estimate of the impact of key opioid-related policies by quantifying the effects of must access prescription drug monitoring programs (PDMPs), naloxone access laws (NALs), and medical marijuana laws on opioid prescribing. Existing methods, such as differences-in-differences and synthetic controls, are challenging to apply in these types of dynamic policy landscapes where multiple policies are implemented over time and sample sizes are small. Autoregressive models are an alternative strategy that have been used to estimate policy effects in similar settings, but until this paper have lacked formal justification. We outline a set of assumptions that tie these models to causal effects, and we study biases of estimates based on this approach when key causal assumptions are violated. In a set of simulation studies that mirror the structure of our application, we also show that our proposed estimators frequently outperform existing estimators. In short, we justify the use of autoregressive models to provide robust evidence on the effectiveness of four state policies in combating the opioid crisis.

Temporal cavity solitons, or dissipative Kerr solitons (DKS) in integrated microresonators, are essential for deployable metrology technologies. Such applications favor the lowest noise state, typically the single-DKS state where one soliton is in the resonator. Other multi-DKS states can also be reached, offering better conversion efficiency and thermal stability, potentially simplifying DKS-based technologies. Yet they exhibit more noise due to relative soliton jitter, and are usually not compatible with targeted applications. We demonstrate that Kerr-induced synchronization, an all-optical trapping technique, can azimuthally pin the multi-DKS state to a common reference field. This method ensures repetition rate noise independent of the number of solitons, making a multi-DKS state indistinguishable from a single-DKS state in that regard, akin to trapped-soliton molecule behavior. Supported by theoretical analysis and experimental demonstration in an integrated microresonator, this approach provides metrological capacity regardless of the number of cavity solitons, benefiting numerous DKS-based metrology applications.

Training a neural network is a monolithic endeavor, akin to carving knowledge into stone: once the process is completed, editing the knowledge in a network is nearly impossible, since all information is distributed across the network's weights. We here explore a simple, compelling alternative by marrying the representational power of deep neural networks with the flexibility of a database. Decomposing the task of image classification into image similarity (from a pre-trained embedding) and search (via fast nearest neighbor retrieval from a knowledge database), we build a simple and flexible visual memory that has the following key capabilities: (1.) The ability to flexibly add data across scales: from individual samples all the way to entire classes and billion-scale data; (2.) The ability to remove data through unlearning and memory pruning; (3.) An interpretable decision-mechanism on which we can intervene to control its behavior. Taken together, these capabilities comprehensively demonstrate the benefits of an explicit visual memory. We hope that it might contribute to a conversation on how knowledge should be represented in deep vision models -- beyond carving it in "stone" weights., Comment: Adding link to code at https://github.com/google-deepmind/visual-memory

We introduce Imagen 3, a latent diffusion model that generates high quality images from text prompts. We describe our quality and responsibility evaluations. Imagen 3 is preferred over other state-of-the-art (SOTA) models at the time of evaluation. In addition, we discuss issues around safety and representation, as well as methods we used to minimize the potential harm of our models.

We investigate the ability of the Euclid telescope to detect galaxy-scale gravitational lenses. To do so, we perform a systematic visual inspection of the $0.7\,\rm{deg}^2$ Euclid ERO data towards the Perseus cluster using both the high-resolution VIS $I_{\scriptscriptstyle\rm E}$ band, and the lower resolution NISP bands. We inspect every extended source brighter than magnitude $23$ in $I_{\scriptscriptstyle\rm E}$ with $41$ expert human classifiers. This amounts to $12\,086$ stamps of $10^{\prime\prime}\,\times\,10^{\prime\prime}$. We find $3$ grade A and $13$ grade B candidates. We assess the validity of these $16$ candidates by modelling them and checking that they are consistent with a single source lensed by a plausible mass distribution. Five of the candidates pass this check, five others are rejected by the modelling and six are inconclusive. Extrapolating from the five successfully modelled candidates, we infer that the full $14\,000\,{\rm deg}^2$ of the Euclid Wide Survey should contain $100\,000^{+70\,000}_{-30\,000}$ galaxy-galaxy lenses that are both discoverable through visual inspection and have valid lens models. This is consistent with theoretical forecasts of $170\,000$ discoverable galaxy-galaxy lenses in Euclid. Our five modelled lenses have Einstein radii in the range $0.\!\!^{\prime\prime}68\,<\,\theta_\mathrm{E}\,<1.\!\!^{\prime\prime}24$, but their Einstein radius distribution is on the higher side when compared to theoretical forecasts. This suggests that our methodology is likely missing small Einstein radius systems. Whilst it is implausible to visually inspect the full Euclid data set, our results corroborate the promise that Euclid will ultimately deliver a sample of around $10^5$ galaxy-scale lenses., Comment: 21 pages, 20 figures, submitted to A&A

We present dynamical modeling of the broad-line region (BLR) for the highly variable AGN SDSS J141041.25+531849.0 ($z = 0.359$) using photometric and spectroscopic monitoring data from the Sloan Digital Sky Survey Reverberation Mapping project and the SDSS-V Black Hole Mapper program, spanning from early 2013 to early 2023. We model the geometry and kinematics of the BLR in the H$\beta$, H$\alpha$, and MgII, emission lines for three different time periods to measure the potential change of structure within the BLR across time and line species. We consistently find a moderately edge-on $(i_{\rm full-state} = 53.29^{\circ} \,{}^{+7.29}_{-6.55})$ thick-disk $(\theta_{\rm opn, \; full-state} = 54.86^{\circ} \,{}^{+5.83}_{-4.74})$ geometry for all BLRs, with a joint estimate for the mass of the supermassive black hole (SMBH) for each of three time periods, yielding $\log_{10}(M_{\rm BH} / M_{\odot}) = 7.66^{+0.12}_{-0.13}$ when using the full dataset. The inferred individual virial factor $f$ $\sim 1$ is significantly smaller than the average factor for a local sample of dynamically modeled AGNs. There is strong evidence for non-virial motion, with over $80\%$ of clouds on inflowing/outflowing orbits. We analyze the change in model parameters across emission lines, finding the radii of BLRs for the emission lines are consistent with the following relative sizes $R_{\rm H\beta} \lesssim R_{\rm MgII } \lesssim R_{\rm H\alpha}$. Comparing results across time, we find $R_{\rm low-state} \lesssim R_{\rm high-state}$, with the change in BLR size for H$\beta$, being more significant than for the other two lines. The data also reveal complex, time-evolving, and potentially transient dynamics of the BLR gas over decade-long timescales, encouraging for future dynamical modeling of fine-scale BLR kinematics., Comment: 32 pages, 16 figures, 4 tables. Submitted to ApJ

Reinforcement learning (RL), particularly its combination with deep neural networks referred to as deep RL (DRL), has shown tremendous promise across a wide range of applications, suggesting its potential for enabling the development of sophisticated robotic behaviors. Robotics problems, however, pose fundamental difficulties for the application of RL, stemming from the complexity and cost of interacting with the physical world. This article provides a modern survey of DRL for robotics, with a particular focus on evaluating the real-world successes achieved with DRL in realizing several key robotic competencies. Our analysis aims to identify the key factors underlying those exciting successes, reveal underexplored areas, and provide an overall characterization of the status of DRL in robotics. We highlight several important avenues for future work, emphasizing the need for stable and sample-efficient real-world RL paradigms, holistic approaches for discovering and integrating various competencies to tackle complex long-horizon, open-world tasks, and principled development and evaluation procedures. This survey is designed to offer insights for both RL practitioners and roboticists toward harnessing RL's power to create generally capable real-world robotic systems., Comment: The first three authors contributed equally. Accepted to Annual Review of Control, Robotics, and Autonomous Systems

Molecular rotors form twisted conformations upon photoexcitation, with their fluorescent relaxation time serving as a measure of viscosity. They have been used to assess membrane viscosities but yield higher values compared to other methods. Here, we show that the rotor's relaxation time is influenced by a combination of membrane viscosity and interleaflet friction. We present a theory for the relaxation time and obtain a correction factor that accounts for the discrepancy. If the membrane's viscosity is known, molecular rotors may enable the extraction of the elusive interleaflet friction.

Modern artificial intelligence (AI) systems are powered by foundation models. This paper presents a new set of foundation models, called Llama 3. It is a herd of language models that natively support multilinguality, coding, reasoning, and tool usage. Our largest model is a dense Transformer with 405B parameters and a context window of up to 128K tokens. This paper presents an extensive empirical evaluation of Llama 3. We find that Llama 3 delivers comparable quality to leading language models such as GPT-4 on a plethora of tasks. We publicly release Llama 3, including pre-trained and post-trained versions of the 405B parameter language model and our Llama Guard 3 model for input and output safety. The paper also presents the results of experiments in which we integrate image, video, and speech capabilities into Llama 3 via a compositional approach. We observe this approach performs competitively with the state-of-the-art on image, video, and speech recognition tasks. The resulting models are not yet being broadly released as they are still under development.

Visualization linters are end-user facing evaluators that automatically identify potential chart issues. These spell-checker like systems offer a blend of interpretability and customization that is not found in other forms of automated assistance. However, existing linters do not model context and have primarily targeted users who do not need assistance, resulting in obvious -- even annoying -- advice. We investigate these issues within the domain of color palette design, which serves as a microcosm of visualization design concerns. We contribute a GUI-based color palette linter as a design probe that covers perception, accessibility, context, and other design criteria, and use it to explore visual explanations, integrated fixes, and user defined linting rules. Through a formative interview study and theory-driven analysis, we find that linters can be meaningfully integrated into graphical contexts thereby addressing many of their core issues. We discuss implications for integrating linters into visualization tools, developing improved assertion languages, and supporting end-user tunable advice -- all laying the groundwork for more effective visualization linters in any context., Comment: To appear at VIS2024

We have observed unexpected spectral attenuation of ultraviolet light in freshly drawn hollow core optical fibres. When the fibre ends are left open to atmosphere, this loss feature dissipates over time. The loss matches the absorption spectrum of gaseous (molecular) chlorine and, given enough time, the transmission spectrum of the fibre recovers to that expected from the morphological structure of the fibre. Our measurements indicate an initial chlorine concentration of 0.45 $\mu$ mol/cm$^{3}$ in the hollow core, equivalent to 1.1 mol% Cl$_{2}$ at atmospheric pressure.

Bayesian inference for inverse problems hinges critically on the choice of priors. In the absence of specific prior information, population-level distributions can serve as effective priors for parameters of interest. With the advent of machine learning, the use of data-driven population-level distributions (encoded, e.g., in a trained deep neural network) as priors is emerging as an appealing alternative to simple parametric priors in a variety of inverse problems. However, in many astrophysical applications, it is often difficult or even impossible to acquire independent and identically distributed samples from the underlying data-generating process of interest to train these models. In these cases, corrupted data or a surrogate, e.g. a simulator, is often used to produce training samples, meaning that there is a risk of obtaining misspecified priors. This, in turn, can bias the inferred posteriors in ways that are difficult to quantify, which limits the potential applicability of these models in real-world scenarios. In this work, we propose addressing this issue by iteratively updating the population-level distributions by retraining the model with posterior samples from different sets of observations and showcase the potential of this method on the problem of background image reconstruction in strong gravitational lensing when score-based models are used as data-driven priors. We show that starting from a misspecified prior distribution, the updated distribution becomes progressively closer to the underlying population-level distribution, and the resulting posterior samples exhibit reduced bias after several updates., Comment: 17 pages, 15 figures, Submitted to The Astrophysical Journal

This thesis is dedicated to analysing the general structure of two- and three-point correlation functions of conserved currents of arbitrary integer or half-integer spins in three- and four-dimensional (super)conformal field theory., Comment: PhD Thesis, 207 pages. Based on arXiv:2102.04827, arXiv:2108.01865, arXiv:2204.04899, arXiv:2210.13135, arXiv:2302.00593, arXiv:2305.02233 and arXiv:2307.11435

We analyse the general structure of the three-point functions involving conserved higher-spin ``vector-like" supercurrents $J_{s}(z) := J_{\alpha(s) \dot{\alpha}(s)}(z)$ in four-dimensional $\mathcal{N}=1$ superconformal field theory. Using the constraints of superconformal symmetry and superfield conservation equations, we utilise a computational approach to analyse the general structure of the three-point function $\langle J^{}_{s_{1}}(z_{1}) \, J'_{s_{2}}(z_{2}) \, J''_{s_{3}}(z_{3}) \rangle$ and provide a general classification of the results. We demonstrate that the three-point function is fixed up to $2 \min (s_{i}) + 2$ independent conserved structures, which we propose to hold for arbitrary superspins. In addition, we show that the conserved structures can be classified as parity-even or parity-odd in superspace based on their transformation properties under superinversion., Comment: 65 pages; v2: moved some content to Appendix A, accepted for publication in Physical Review D

The most fundamental capability of modern AI methods such as Large Language Models (LLMs) is the ability to predict the next token in a long sequence of tokens, known as ``sequence modeling." Although the Transformers model is the current dominant approach to sequence modeling, its quadratic computational cost with respect to sequence length is a significant drawback. State-space models (SSMs) offer a promising alternative due to their linear decoding efficiency and high parallelizability during training. However, existing SSMs often rely on seemingly ad hoc linear recurrence designs. In this work, we explore SSM design through the lens of online learning, conceptualizing SSMs as meta-modules for specific online learning problems. This approach links SSM design to formulating precise online learning objectives, with state transition rules derived from optimizing these objectives. Based on this insight, we introduce a novel deep SSM architecture based on the implicit update for optimizing an online regression objective. Our experimental results show that our models outperform state-of-the-art SSMs, including the Mamba model, on standard sequence modeling benchmarks and language modeling tasks.

The volumetric rate of tidal disruption events (TDEs) encodes information on the still-unknown demographics of central massive black holes (MBHs) in low-mass galaxies ($\lesssim 10^9$~M$_\odot$). Theoretical TDE rates from model galaxy samples can extract this information, but this requires accurately defining the nuclear stellar density structures. This region is typically dominated by nuclear star clusters (NSCs), which have been shown to increase TDE rates by orders of magnitude. Thus, we assemble the largest available sample of pc-scale 3-D density profiles that include NSC components. We deproject the PSF-deconvolved surface brightness profiles of 91 nearby galaxies of varying morphology and combine these with nuclear mass-to-light ratios estimated from measured colors or spectral synthesis to create 3-D mass density profiles. We fit the inner 3-D density profile to find the best-fit power-law density profile in each galaxy. We compile this information as a function of galaxy stellar mass to fit new empirical density scaling relations. These fits reveal positive correlations between galaxy stellar mass and central stellar density in both early- and late-type galaxies. We find that early-type galaxies have somewhat higher densities and shallower profiles relative to late-type galaxies at the same mass. We also use the density profiles to estimate the influence radius of each galaxy's MBH and find that the sphere of influence was likely resolved in most cases. These new relations will be used in future works to build mock galaxy samples for dynamical TDE rate calculations, with the aim of constraining MBH demographics in low-mass galaxies., Comment: 18 pages, 6 figures, 1 table. Accepted by AAS Journals

We present selected examples demonstrating an alternative approach to contour deformation for numerically computing loop integrals in the Minkowski regime. This method focuses on identifying singular hypersurfaces (varieties of the $\mathscr{F}$ polynomial) and mapping them to known points which can then be resolved by employing blow-ups/sector decomposition techniques, thereby avoiding the need for contour deformation. Using this technique, we achieve improved convergence properties without the need for contour deformation, which is known to significantly increase the complexity of the integrand by introducing, for example, derivatives of the $\mathscr{F}$ polynomial and complicated Jacobians. We highlight that while we have only tested the approach on selected one-, two- and three-loop massless and one-loop massive examples, it shows promise for practical applications, offering potential benefits over the traditional approach. Evaluation times are compared with existing contour deformation implementations to illustrate the performance of this alternative method., Comment: Contribution to proceedings of the Loops and Legs in Quantum Field Theory conference (LL2024)

Wavefront shaping has become a powerful tool for manipulating light propagation in various complex media undergoing linear scattering. Controlling nonlinear optical interactions with spatial degrees of freedom is a relatively recent but growing area of research. A wavefront-shaping-based approach can be used to suppress nonlinear stimulated Brillouin scattering (SBS) and transverse mode instability (TMI), which are the two main limitations to power scaling in high-power narrowband fiber amplifiers. Here we formulate both SBS and TMI suppression as optimization problems with respect to coherent multimode input excitation in a given multimode fiber. We develop an efficient method for finding the globally optimal input excitation for SBS and TMI suppression using linear programming. We theoretically show that optimally exciting a standard multimode fiber leads to roughly an order of magnitude enhancement in output power limited by SBS and TMI, compared to fundamental-mode-only excitation. We find that the optimal mode content is robust to small perturbations and our approach works even in the presence of mode dependent loss and gain. Optimal mode content can be excited in real experiments using spatial light modulators, creating a novel platform for instability-free ultrahigh-power fiber lasers., Comment: 13 pages, 7 figures

We refine the classical Cauchy--Schwartz inequality $\|X\|_{1} \leq \|X\|_{2}$ by demonstrating that for any $p$ and $q$ with $q>p>2$, there exists a constant $C=C(p,q)$ such that $\|X\|_1 \leq 1 - C \Big{(}\|X\|_p^p - 1\Big{)}^{\frac{q-2}{q-p}}\Big{(}\|X\|_q^q - 1\Big{)}^{\frac{2-p}{q-p}}$ holds true for all Borel measurable random variables $X$ with $\|X\|_{2}=1$ and $\|X\|_{p}<\infty$. We illustrate two applications of this result: one for biased Rademacher sums and another for exponential sums.

We present results for the Yukawa-enhanced and Higgs self-coupling type electroweak corrections to di-Higgs production in gluon fusion. The calculation of the corresponding four-scale, two-loop amplitude is carried out retaining the exact symbolic dependence on all masses and scales during the reduction to master integrals. The resulting integrals are then evaluated at high precision using both the series expansion of the differential equations and sector decomposition. Differential cross sections for the di-Higgs invariant mass and the transverse momentum of a Higgs boson are shown, where we find that the corrections are most pronounced at low invariant mass and transverse momentum., Comment: 33 pages, 7 figures, 4 tables

We analyse, using new analytical models and numerical general relativistic magnetohydrodynamic simulations, the three-dimensional properties of accretion flows inside the plunging region of black hole spacetimes (i.e., at radii smaller than the innermost stable circular orbit). These simulations are of thick discs, with aspect ratios of order unity $h/r \sim 1$, and with a magnetic field geometry given by the standard low-magnetization "SANE" configuration. This work represents the first step in a wider analysis of this highly relativistic region. We show that analytical expressions derived in the "thin disc" limit describe the numerical results remarkably well, despite the large aspect ratio of the flow. We further demonstrate that accretion within this region is typically mediated via spiral arms, and that the geometric properties of these spiral structures can be understood with a simple analytical model. These results highlight how accretion within the plunging region is fundamentally two dimensional in character, which may have a number of observational implications. We derive a modified theoretical description of the pressure within the plunging region which accounts for turbulent heating and may be of use to black hole image modelling., Comment: 21 pages, 16 figures. Accepted for publication in MNRAS

The 3rd BARN (Benchmark Autonomous Robot Navigation) Challenge took place at the 2024 IEEE International Conference on Robotics and Automation (ICRA 2024) in Yokohama, Japan and continued to evaluate the performance of state-of-the-art autonomous ground navigation systems in highly constrained environments. Similar to the trend in The 1st and 2nd BARN Challenge at ICRA 2022 and 2023 in Philadelphia (North America) and London (Europe), The 3rd BARN Challenge in Yokohama (Asia) became more regional, i.e., mostly Asian teams participated. The size of the competition has slightly shrunk (six simulation teams, four of which were invited to the physical competition). The competition results, compared to last two years, suggest that the field has adopted new machine learning approaches while at the same time slightly converged to a few common practices. However, the regional nature of the physical participants suggests a challenge to promote wider participation all over the world and provide more resources to travel to the venue. In this article, we discuss the challenge, the approaches used by the three winning teams, and lessons learned to direct future research and competitions., Comment: arXiv admin note: text overlap with arXiv:2308.03205

This study explores the efficacy of thermal splicing conditions between silica and zirconium-fluoride fibers, focusing on achieving mechanical strength between the two fibers. A comprehensive characterization of the thermal profile in the hot zone of the filament splicer was conducted using a fiber Bragg grating, providing valuable insights into its stability and overall performance. Results demonstrate mechanically strong joints and suggest a very narrow temperature window to achieve strong connection between the two materials. Moreover, we characterize the surface composition of the ZrF4 fiber using energy dispersive spectroscopy following splicing at ideal temperatures, as well as at higher and lower temperatures. This work paves the way towards future implementation of silica and fluoride fibers splicing using alternative splicing solutions such as CO2 laser system while raising interesting facts for further studies in the specific field., Comment: * Authors contributed equally