Search

From CMB polarization data alone we reconstruct the CMB lensing power spectrum, comparable in overall constraining power to previous temperature-based reconstructions, and an unlensed E-mode power spectrum. The observations, taken in 2019 and 2020 with the South Pole Telescope (SPT) and the SPT-3G camera, cover 1500 deg$^2$ at 95, 150, and 220 GHz with arcminute resolution and roughly 4.9$\mu$K-arcmin coadded noise in polarization. The power spectrum estimates, together with systematic parameter estimates and a joint covariance matrix, follow from a Bayesian analysis using the Marginal Unbiased Score Expansion (MUSE) method. The E-mode spectrum at $\ell>2000$ and lensing spectrum at $L>350$ are the most precise to date. Assuming the $\Lambda$CDM model, and using only these SPT data and priors on $\tau$ and absolute calibration from Planck, we find $H_0=66.81\pm0.81$ km/s/Mpc, comparable in precision to the Planck determination and in 5.4$\sigma$ tension with the most precise $H_0$ inference derived via the distance ladder. We also find $S_8=0.850\pm0.017$, providing further independent evidence of a slight tension with low-redshift structure probes. The $\Lambda$CDM model provides a good simultaneous fit to the combined Planck, ACT, and SPT data, and thus passes a powerful test. Combining these CMB datasets with BAO observations, we find that the effective number of neutrino species, spatial curvature, and primordial helium fraction are consistent with standard model values, and that the 95% confidence upper limit on the neutrino mass sum is 0.075 eV. The SPT data are consistent with the somewhat weak preference for excess lensing power seen in Planck and ACT data relative to predictions of the $\Lambda$CDM model. We also detect at greater than 3$\sigma$ the influence of non-linear evolution in the CMB lensing power spectrum and discuss it in the context of the $S_8$ tension.(abridged), Comment: 28 pages, 21 figures + appendices

We present $24$ cosmological dark matter (DM)--only zoom-in simulations of a Milky Way (MW) analog with initial conditions appropriate for scenarios where non-cold DM is a fraction of the total DM abundance (f-NCDM models), as the second installment of the COZMIC suite. We initialize our simulations using transfer functions, $T_{\mathrm{f-NCDM}}(k)\equiv\sqrt{P_{\mathrm{f-NCDM}}(k)/P_{\mathrm{CDM}}(k)}$ (where $P(k)$ is the linear matter power spectrum), with an initial suppression similar to thermal-relic warm DM (WDM) followed by a constant-amplitude plateau. We simulate suppression wave numbers $[22.8,~ 32.1,~ 41.8,~ 52.0,~ 57.1,~ 95.3]~\mathrm{Mpc}^{-1}$, corresponding to thermal-relic WDM masses $m_{\mathrm{WDM}}\in [3,~ 4,~ 5,~ 6,~ 6.5,~ 10]~\mathrm{keV}$, and plateau amplitudes $\delta\in [0.2,~ 0.4,~ 0.6,~ 0.8]$. We model the subhalo mass function in terms of the suppression wave number and $\delta$. Integrating these models into a forward model of the MW satellite galaxy population yields new limits on f-NCDM scenarios, with suppression wave numbers greater than $46$ and $ 40~\mathrm{Mpc}^{-1}$ for $\delta=0.2$, $0.4$, respectively, at $95\%$ confidence. The current data do not constrain $\delta>0.4$. We map these limits to scenarios where a fraction $f_{\mathrm{WDM}}$ of DM behaves as a thermal relic, which yields the following bounds on cosmologies with a mixture of WDM and CDM: $m_{\mathrm{WDM}}>3.6,~ 4.1,~ 4.6,~ 4.9,~ 5.4~\mathrm{keV}$ for $f_{\mathrm{WDM}}=0.5,~ 0.6,~ 0.7,~ 0.8,~ 0.9$, respectively, at $95\%$ confidence. The current data do not constrain WDM fractions $f_{\mathrm{WDM}}<0.5$. Our results affirm that low-mass halo abundances are sensitive to partial suppression in $P(k)$, indicating the possibility of using galactic substructure to reconstruct $P(k)$ on small scales., Comment: 19 pages, 14 figures, 1 table; comments welcome

The detection of satellite thermal emission at millimeter wavelengths is presented using data from the 3rd-Generation receiver on the South Pole Telescope (SPT-3G). This represents the first reported detection of thermal emission from artificial satellites at millimeter wavelengths. Satellite thermal emission is shown to be detectable at high signal-to-noise on timescales as short as a few tens of milliseconds. An algorithm for downloading orbital information and tracking known satellites given observer constraints and time-ordered observatory pointing is described. Consequences for cosmological surveys and short-duration transient searches are discussed, revealing that the integrated thermal emission from all large satellites does not contribute significantly to the SPT-3G survey intensity map. Measured satellite positions are found to be discrepant from their two-line element (TLE) derived ephemerides up to several arcminutes which may present a difficulty in cross-checking or masking satellites from short-duration transient searches.

Training transformer models requires substantial GPU compute and memory resources. In homogeneous clusters, distributed strategies allocate resources evenly, but this approach is inefficient for heterogeneous clusters, where GPUs differ in power and memory. As high-end GPUs are costly and limited in availability, heterogeneous clusters with diverse GPU types are becoming more common. Existing methods attempt to balance compute across GPUs based on capacity but often underutilize compute due to memory constraints. We present Cephalo, a system that optimizes compute and memory usage by decoupling compute distribution from training state assignment. Cephalo outperforms state-of-the-art methods by achieving significantly higher training throughput while supporting larger models and batch sizes.

We provide an accurate forecast of the expected constraining power from the main void statistics -- the void size function and the void-galaxy cross-correlation function -- to be measured by the Roman reference High Latitude Spectroscopic Survey from the Nancy Grace Roman Space Telescope. Relying on a realistic galaxy mock lightcone, covering 2000 square degrees, we find more than $8\times 10^4 $ voids and explore their constraining power in the framework of three different cosmological models: $\Lambda$CDM, $w$CDM, and $w_0 w_{\rm a}$CDM. This work confirms the strong complementarity of different void statistics and showcases the constraining power to be expected from Roman voids thanks to the combination of its high tracer density and large observed volume., Comment: 24 pages, 11 figures, 5 tables. Comments are welcome

The XLZD collaboration is developing a two-phase xenon time projection chamber with an active mass of 60 to 80 t capable of probing the remaining WIMP-nucleon interaction parameter space down to the so-called neutrino fog. In this work we show that, based on the performance of currently operating detectors using the same technology and a realistic reduction of radioactivity in detector materials, such an experiment will also be able to competitively search for neutrinoless double beta decay in $^{136}$Xe using a natural-abundance xenon target. XLZD can reach a 3$\sigma$ discovery potential half-life of 5.7$\times$10$^{27}$ yr (and a 90% CL exclusion of 1.3$\times$10$^{28}$ yr) with 10 years of data taking, corresponding to a Majorana mass range of 7.3-31.3 meV (4.8-20.5 meV). XLZD will thus exclude the inverted neutrino mass ordering parameter space and will start to probe the normal ordering region for most of the nuclear matrix elements commonly considered by the community., Comment: 29 pages, 7 figures

This report describes the experimental strategy and technologies for a next-generation xenon observatory sensitive to dark matter and neutrino physics. The detector will have an active liquid xenon target mass of 60-80 tonnes and is proposed by the XENON-LUX-ZEPLIN-DARWIN (XLZD) collaboration. The design is based on the mature liquid xenon time projection chamber technology of the current-generation experiments, LZ and XENONnT. A baseline design and opportunities for further optimization of the individual detector components are discussed. The experiment envisaged here has the capability to explore parameter space for Weakly Interacting Massive Particle (WIMP) dark matter down to the neutrino fog, with a 3$\sigma$ evidence potential for the spin-independent WIMP-nucleon cross sections as low as $3\times10^{-49}\rm cm^2$ (at 40 GeV/c$^2$ WIMP mass). The observatory is also projected to have a 3$\sigma$ observation potential of neutrinoless double-beta decay of $^{136}$Xe at a half-life of up to $5.7\times 10^{27}$ years. Additionally, it is sensitive to astrophysical neutrinos from the atmosphere, sun, and galactic supernovae., Comment: 32 pages, 14 figures

We report results of a search for nuclear recoils induced by weakly interacting massive particle (WIMP) dark matter using the LUX-ZEPLIN (LZ) two-phase xenon time projection chamber. This analysis uses a total exposure of $4.2\pm0.1$ tonne-years from 280 live days of LZ operation, of which $3.3\pm0.1$ tonne-years and 220 live days are new. A technique to actively tag background electronic recoils from $^{214}$Pb $\beta$ decays is featured for the first time. Enhanced electron-ion recombination is observed in two-neutrino double electron capture decays of $^{124}$Xe, representing a noteworthy new background. After removal of artificial signal-like events injected into the data set to mitigate analyzer bias, we find no evidence for an excess over expected backgrounds. World-leading constraints are placed on spin-independent (SI) and spin-dependent WIMP-nucleon cross sections for masses $\geq$9 GeV/$c^2$. The strongest SI exclusion set is $2.1\times10^{-48}$ cm$^{2}$ at the 90% confidence level at a mass of 36 GeV/$c^2$, and the best SI median sensitivity achieved is $5.0\times10^{-48}$ cm$^{2}$ for a mass of 40 GeV/$c^2$., Comment: 9 pages, 7 figures. See https://www.hepdata.net/record/155182 for a data release related to this paper

We determine the $\tau^n$-torsion in the first 5-lines of the $E_2$ page of the $\mathbb{C}$-motivic Adams spectral sequence using the techniques of Burklund-Xu. In particular, every element in this range is either $\tau^1$-torsion or $\tau$-free. We also show that $\tau^n$-torsion elements can appear only in Adams filtration at least $2n+2$ and give further evidence of a possible $3n$ bound.

Observations of the high-$z$ Universe from JWST have revealed a new population of bright, early galaxies. A robust statistical interpretation of this data requires fast forward models that account for uncertainties in galaxy evolution and incorporate observational systematic effects. We present a probabilistic framework for population synthesis of high-$z$ galaxies and inference of their properties. Our framework is based on the semi-analytic galaxy-formation model Galacticus. To infer the astrophysical parameters governing high-$z$ galaxy evolution, we analyze JWST data from the CEERS and NGDEEP surveys and calculate the likelihood of observing individual objects in apparent magnitude--redshift space, for $z\geq8.5$ galaxy candidates. We include observational selection effects due to limited survey volume and depth, as well as photometric redshift uncertainties. We recover the posterior probability distribution for parameters describing star formation and outflow rates. We place an upper limit on the star formation timescale of $500~\mathrm{Myr}$ at a disk velocity of $50~\mathrm{km\ s}^{-1}$, and we infer a characteristic velocity at which the outflow mass-loading factor is $\sim 1$ of $150^{+280}_{-60}~\mathrm{km\ s}^{-1}$, both at $95\%$ confidence. Marginalizing over our astrophysical model, we find that galaxies in CEERS and NGDEEP data occupy halos with virial masses $10^{10\pm 0.5}~M_{\mathrm{\odot}}$ at $8.5\leq z\leq 12$, at $95\%$ confidence. The star formation timescale preferred by our fit is relatively short compared to typical values at lower redshifts, consistent with previous findings. The modeling and analysis framework presented here can enable systematic tests of high-$z$ galaxies' dust content, initial mass functions, and star formation burstiness in the future., Comment: 14 pages, 10 figures

DNA-Encoded Libraries (DEL) are combinatorial small molecule libraries that offer an efficient way to characterize diverse chemical spaces. Selection experiments using DELs are pivotal to drug discovery efforts, enabling high-throughput screens for hit finding. However, limited availability of public DEL datasets hinders the advancement of computational techniques designed to process such data. To bridge this gap, we present KinDEL, one of the first large, publicly available DEL datasets on two kinases: Mitogen-Activated Protein Kinase 14 (MAPK14) and Discoidin Domain Receptor Tyrosine Kinase 1 (DDR1). Interest in this data modality is growing due to its ability to generate extensive supervised chemical data that densely samples around select molecular structures. Demonstrating one such application of the data, we benchmark different machine learning techniques to develop predictive models for hit identification; in particular, we highlight recent structure-based probabilistic approaches. Finally, we provide biophysical assay data, both on- and off-DNA, to validate our models on a smaller subset of molecules. Data and code for our benchmarks can be found at: https://github.com/insitro/kindel.

The first very long baseline interferometry (VLBI) detections at 870$\mu$m wavelength (345$\,$GHz frequency) are reported, achieving the highest diffraction-limited angular resolution yet obtained from the surface of the Earth, and the highest-frequency example of the VLBI technique to date. These include strong detections for multiple sources observed on inter-continental baselines between telescopes in Chile, Hawaii, and Spain, obtained during observations in October 2018. The longest-baseline detections approach 11$\,$G$\lambda$ corresponding to an angular resolution, or fringe spacing, of 19$\mu$as. The Allan deviation of the visibility phase at 870$\mu$m is comparable to that at 1.3$\,$mm on the relevant integration time scales between 2 and 100$\,$s. The detections confirm that the sensitivity and signal chain stability of stations in the Event Horizon Telescope (EHT) array are suitable for VLBI observations at 870$\mu$m. Operation at this short wavelength, combined with anticipated enhancements of the EHT, will lead to a unique high angular resolution instrument for black hole studies, capable of resolving the event horizons of supermassive black holes in both space and time., Comment: Corresponding author: S. Doeleman

We present $72$ cosmological dark matter (DM)--only N-body zoom-in simulations with initial conditions beyond cold, collisionless dark matter (CDM), as the first installment of the COZMIC suite. We simulate Milky Way (MW) analogs with linear matter power spectra, $P(k)$ for: i) thermal-relic warm dark matter (WDM) with masses $m_{\mathrm{WDM}}\in [3,4,5,6,6.5,10]~\mathrm{keV}$, ii) fuzzy dark matter (FDM) with masses $m_{\mathrm{FDM}}\in [25.9,69.4,113,151,185,490]\times 10^{-22}~\mathrm{eV}$, and iii) interacting dark matter (IDM) with a velocity-dependent elastic proton scattering cross section $\sigma=\sigma_0 v^n$ relative particle velocity scaling $n\in [2,4]$, and DM mass $m_{\mathrm{IDM}}\in[10^{-4},~ 10^{-2},~ 1]~\mathrm{GeV}$. Subhalo mass function (SHMF) suppression is significantly steeper in FDM versus WDM, while dark acoustic oscillations in $P(k)$ can reduce SHMF suppression for IDM. We fit SHMF models to our simulation results and derive new bounds on WDM and FDM from the MW satellite population, obtaining $m_{\mathrm{WDM}}>5.9~\mathrm{keV}$ and $m_{\mathrm{FDM}}>1.4\times 10^{-20}~\mathrm{eV}$ at $95\%$ confidence; these limits are $\approx 10\%$ weaker and $5\times$ stronger than previous constraints due to the updated transfer functions and SHMF models, respectively. We estimate IDM bounds for $n=2$ ($n=4$) and obtain $\sigma_0 < 1.0\times 10^{-27}$, $1.3\times 10^{-24}$, and $3.1\times 10^{-23}~\mathrm{cm}^2$ ($\sigma_0 < 9.9\times 10^{-27}$, $9.8\times 10^{-21}$, and $2.1\times 10^{-17}~\mathrm{cm}^2$) for $m_{\mathrm{IDM}}=10^{-4}$, $10^{-2}$, and $1$ GeV, respectively. Thus, future development of IDM SHMF models can improve IDM cross section bounds by up to a factor of $\sim 20$ with current data. COZMIC presents an important step toward accurate small-scale structure modeling in beyond-CDM cosmologies, critical to upcoming observational searches for DM physics., Comment: 36 pages, 19 figures, 2 tables; comments welcome

Cu$_2$IrO$_3$ has attracted recent interest due to its proximity to the Kitaev quantum spin liquid state and the complex structural response observed at high pressures. We use x-ray spectroscopy and scattering as well as electrical transport techniques to unveil the electronic structure of Cu$_2$IrO$_3$ at ambient and high pressures. Despite featuring a $\mathrm{Ir^{4+}}$ $J_{\rm{eff}}=1/2$ state at ambient pressure, Ir $L_{3}$ edge resonant inelastic x-ray scattering reveals broadened electronic excitations that point to the importance of Ir $5d$-Cu $3d$ interaction. High pressure first drives an Ir-Ir dimer state with collapsed $\langle \mathbf{L} \cdot \mathbf{S} \rangle$ and $\langle L_z \rangle/\langle S_z \rangle$, signaling the formation of $5d$ molecular orbitals. A novel $\mathrm{Cu \to Ir}$ charge transfer is observed at the onset of phase 5 above 30 GPa at low temperatures, leading to an approximate $\mathrm{Ir^{3+}}$ and $\mathrm{Cu^{1.5+}}$ valence, with persistent insulating electrical transport seemingly driven by charge segregation of Cu 1+/2+ ions into distinct sites. Concomitant x-ray spectroscopy and scattering measurements through different thermodynamic paths demonstrate a strong electron-lattice coupling, with $J_{\rm{eff}}=1/2$ and $\mathrm{Ir^{3+}}$/$\mathrm{Cu^{1.5+}}$ electronic states occurring only in phases 1 and 5, respectively. Remarkably, the charge-transferred state can only be reached if Cu$_2$IrO$_3$ is pressurized at low temperature, suggesting that phonons play an important role in the stability of this phase. These results point to the choice of thermodynamic path across interplanar collapse transition as a key route to access novel states in intercalated iridates., Comment: 8 pages, 4 figures, see ancillary file for Supplemental Material

Interactions between active individuals in animal collectives lead to emergent responses that remain elusive in synthetic soft matter. Here, shape-morphing polymers are used to create bio-inspired transient solids that self-assemble with controlled mechanical properties and disassemble on demand. Dilute-suspensions of magnetic, heat-responsive liquid crystal elastomer ribbons mechanically interlock, inducing reversible aggregation. A mathematical model is developed that sheds light on the role of topological mechanisms in aggregation. Aggregation was favored for ribbons with moderate curvature at 25C above crosslinking temperature as compared to flat ribbons or higher curvature ribbons at higher temperatures. The ribbon suspensions reversibly transition between fluid- and solid-like states, exhibiting up to 6 orders-of-magnitude increase in the storage moduli of the entangled aggregates compared with the liquid dispersions. Controlled dissociation is induced by imparting kinetic energy to the individual ribbons at high magnetic field rotation speeds (> 200 RPM). Ribbon shape and the medium in which dissociation occurs were shown to govern disassembly. Imparting dynamic collective behaviors into synthetic systems may enable a range of potential applications from bio-inspired soft robotics to injectable biomaterials., Comment: 16 pages, 6 figures

The interaction of multiple fluids through a heterogeneous pore space leads to complex pore-scale flow dynamics, such as intermittent pathway flow. The non-local nature of these dynamics, and the size of the 4D datasets acquired to capture them, presents challenges in identifying key fluctuations controlling fluid connectivity. To address these challenges, this work employs Dynamic Mode Decomposition (DMD), a data-driven algorithm that decomposes complex nonlinear systems into dominant spatio-temporal structures without relying on prior system assumptions. We present a workflow that identifies critical spatio-temporal regions exhibiting intermittent flow dynamics. This workflow is validated through three test cases, each exploring the impact of viscosity ratio on flow dynamics while maintaining a constant capillary number. Our findings demonstrate DMD's potential in analyzing extensive experimental datasets and identifying crucial intermittent flow structures, offering a powerful tool for understanding complex fluid behaviors in heterogeneous pore spaces. Using our method, we can quickly identify the timescales and locations of interest in an objective manner, providing a valuable diagnostic tool for analysing large synchrotron datasets.

The JWST and ALMA have detected emission lines from the ionized interstellar medium (ISM), including [OII], [OIII], and hydrogen Balmer series lines, in some of the first galaxies at z>6. These measurements present an opportunity to better understand galaxy assembly histories and may allow important tests of state-of-the-art galaxy formation simulations. It is challenging, however, to model these lines in their proper cosmological context given the huge dynamic range in spatial scales involved. In order to meet this challenge, we introduce a novel sub-grid line emission modeling framework. The framework uses the high-z zoom-in simulation suite from the Feedback in Realistic Environments (FIRE) collaboration. The line emission signals from HII regions within each simulated FIRE galaxy are modeled using the semi-analytic HIILines code. A machine learning, Mixture Density Network, approach is then used to determine the conditional probability distribution for the line luminosity to stellar-mass ratio from the HII regions around each simulated stellar particle given its age, metallicity, and its galaxy's total stellar mass. This conditional probability distribution can then be applied to predict the line luminosities around stellar particles in lower resolution, yet larger volume cosmological simulations. As an example, we apply this approach to the Illustris-TNG simulations at z=6. The resulting predictions for the [OII], [OIII], and Balmer line luminosities as a function of star-formation rate agree well with current observations. Our predictions differ, however, from related work in the literature which lack detailed sub-grid ISM models. This highlights the importance of our multi-scale simulation modeling framework. Finally, we provide forecasts for future line luminosity function measurements from the JWST and quantify the cosmic variance in such surveys., Comment: 19 pages, 12 figures

In this paper, we study the oriented diameter of power graphs of groups. We show that a $2$-edge connected power graph of a finite group has oriented diameter at most $4$. We prove that the power graph of the cyclic group of order $n$ has oriented diameter $2$ for all $n\neq 1,2,4,6$. For non-cyclic finite nilpotent groups, we show that the oriented diameter of corresponding power graphs is at least $3$. Moreover, we provide necessary and sufficient conditions for the oriented diameter of $2$-edge connected power graphs of finite non-cyclic nilpotent groups to be either $3$ or $4$. This, in turn, gives an algorithm for computing the oriented diameter of the power graph of a given nilpotent group that runs in time polynomial in the size of the group., Comment: 25 pages, Corrected typos and references, and Revised some statements

Low-mass galaxies provide a powerful tool with which to investigate departures from the standard cosmological paradigm in models that suppress the abundance of small dark matter structures. One of the simplest metrics that can be used to compare different models is the abundance of satellite galaxies in the Milky Way. Viable dark matter models must produce enough substructure to host the observed number of Galactic satellites. Here, we scrutinize the predictions of the neutrino Minimal Standard Model ($\nu{\rm MSM}$), a well-motivated extension of the Standard Model of particle physics in which the production of sterile neutrino dark matter is resonantly enhanced by a lepton asymmetry in the primordial plasma. This process enables the model to evade current constraints associated with non-resonantly produced dark matter. Independently of assumptions about galaxy formation physics we rule out, with at least 95 per cent confidence, all parameterizations of the $\nu{\rm MSM}$ with sterile neutrino rest mass, $M_{\rm s} \leq 1.4\, {\rm keV}$. Incorporating physically motivated prescriptions of baryonic processes and modelling the effects of reionization strengthen our constraints, and we exclude all $\nu{\rm MSM}$ parameterizations with $M_{\rm s} \leq 4\, {\rm keV}$. Unlike other literature, our fiducial constraints do not rule out the putative 3.55 keV X-ray line, if it is indeed produced by the decay of a sterile neutrino; however, some of the most favoured parameter space is excluded. If the Milky Way satellite count is higher than we assume, or if the Milky Way halo is less massive than $M^{\rm MW}_{200} = 8 \times 10^{11}\, {\rm M_\odot}$, we rule out the $\nu{\rm MSM}$ as the origin of the 3.55 keV excess. In contrast with other work, we find that the constraints from satellite counts are substantially weaker than those reported from X-ray non-detections., Comment: 14 pages, six figures, two appendices. A repository of reduced scripts and data will be made available at https://github.com/Musical-Neutron/nuMSM_constraints. Submitted, comments welcome!

Latching techniques are widely used to enhance readout of qubits. These methods require precise tuning of multiple tunnel rates, which can be challenging to achieve under realistic experimental conditions, such as when a qubit is coupled to a single reservoir. Here, we present a method for single-shot measurement of a quantum dot qubit with a single reservoir using a latched-readout scheme. Our approach involves pulsing a barrier gate to dynamically control qubit-to-reservoir tunnel rates, a method that is readily applicable to the latched readout of various spin-based qubits. We use this method to enable qubit state latching and to reduce the qubit reset time in measurements of coherent Larmor oscillations of a Si/SiGe quantum dot hybrid qubit., Comment: 6 pages, including supplemental materials

Accurately describing the distribution of CO$_2$ in the atmosphere with atmospheric tracer transport models is essential for greenhouse gas monitoring and verification support systems to aid implementation of international climate agreements. Large deep neural networks are poised to revolutionize weather prediction, which requires 3D modeling of the atmosphere. While similar in this regard, atmospheric transport modeling is subject to new challenges. Both, stable predictions for longer time horizons and mass conservation throughout need to be achieved, while IO plays a larger role compared to computational costs. In this study we explore four different deep neural networks (UNet, GraphCast, Spherical Fourier Neural Operator and SwinTransformer) which have proven as state-of-the-art in weather prediction to assess their usefulness for atmospheric tracer transport modeling. For this, we assemble the CarbonBench dataset, a systematic benchmark tailored for machine learning emulators of Eulerian atmospheric transport. Through architectural adjustments, we decouple the performance of our emulators from the distribution shift caused by a steady rise in atmospheric CO$_2$. More specifically, we center CO$_2$ input fields to zero mean and then use an explicit flux scheme and a mass fixer to assure mass balance. This design enables stable and mass conserving transport for over 6 months with all four neural network architectures. In our study, the SwinTransformer displays particularly strong emulation skill (90-day $R^2 > 0.99$), with physically plausible emulation even for forward runs of multiple years. This work paves the way forward towards high resolution forward and inverse modeling of inert trace gases with neural networks., Comment: Code: https://github.com/vitusbenson/carbonbench

The nilCoxeter algebra $\mathcal{N}S_n$ of the symmetric group $S_n$ is the algebra over $\mathbb{Z}$ with generators $Y_i$ ($1\leqslant i\leqslant n-1$), satisfying the braid relations $Y_iY_{i+1}Y_i=Y_{i+1}Y_iY_{i+1}$, $Y_iY_j=Y_jY_i$ ($|j-i|\geqslant 2$), together with the relations $Y_i^2=0$. We describe an explicit presentation for the cohomology ring $Z\cong\mathsf{Ext}^*_{\mathcal{N}S_n}(\mathbb{Z},\mathbb{Z})$, with $n-i$ new generators in degree $i$ for $0< i

We present the detection and characterization of fluctuations in linearly polarized emission from the atmosphere above the South Pole. These measurements make use of Austral winter survey data from the SPT-3G receiver on the South Pole Telescope in three frequency bands centered at 95, 150, and 220 GHz. We use the cross-correlation between detectors to produce an unbiased estimate of the power in Stokes I, Q, and U parameters on large angular scales. Our results are consistent with the polarized signal being produced by the combination of Rayleigh scattering of thermal radiation from the ground and thermal emission from a population of horizontally aligned ice crystals with an anisotropic distribution described by Kolmogorov turbulence. The signal is most significant at large angular scales, high observing frequency, and low elevation angle. Polarized atmospheric emission has the potential to significantly impact observations on the large angular scales being targeted by searches for inflationary B-mode CMB polarization. We present the distribution of measured angular power spectrum amplitudes in Stokes Q and I for 4 years of winter observations, which can be used to simulate the impact of atmospheric polarization and intensity fluctuations at the South Pole on a specified experiment and observation strategy. For the SPT-3G data, downweighting the small fraction of significantly contaminated observations is an effective mitigation strategy. In addition, we present a strategy for further improving sensitivity on large angular scales where maps made in the 220 GHz band are used to measure and subtract the polarized atmosphere signal from the 150 GHz band maps. In observations with the SPT-3G instrument at the South Pole, the polarized atmospheric signal is a well-understood and sub-dominant contribution to the measured noise after implementing the mitigation strategies described here., Comment: 32 pages, 28 figures

Generative artificial intelligence (AI), exemplified by the release of GPT-3.5 in 2022, has significantly advanced the potential applications of large language models (LLMs), including in the realms of ontology development and knowledge graph creation. Ontologies, which are structured frameworks for organizing information, and knowledge graphs, which combine ontologies with actual data, are essential for enabling interoperability and automated reasoning. However, current research has largely overlooked the generation of ontologies extending from established upper-level frameworks like the Basic Formal Ontology (BFO), risking the creation of non-integrable ontology silos. This study explores the extent to which LLMs, particularly GPT-4, can support ontologists trained in BFO. Through iterative development of a specialized GPT model named "My Ontologist," we aimed to generate BFO-conformant ontologies. Initial versions faced challenges in maintaining definition conventions and leveraging foundational texts effectively. My Ontologist 3.0 showed promise by adhering to structured rules and modular ontology suites, yet the release of GPT-4o disrupted this progress by altering the model's behavior. Our findings underscore the importance of aligning LLM-generated ontologies with top-level standards and highlight the complexities of integrating evolving AI capabilities in ontology engineering.

We discuss the notion of resonance, as well as the existence and uniqueness of periodic solutions for a forced simple harmonic oscillator. While this topic is elementary, and well-studied for sinusoidal forcing, this does not seem to be the case when the forcing function is general (perhaps discontinuous). Clear statements of theorems and proofs do not readily appear in standard textbooks or online. For that reason, we provide a characterization of resonant solutions, written in terms of the relationship between the forcing and natural frequencies, as well as a condition on a particular Fourier mode. While our discussions involve some notions from $L^2$-spaces, our proofs are elementary, using this the variation of parameters formula; the main theorem and its proof should be readable by students who have completed a differential equations course and have some experience with analysis. We provide several examples, and give various constructions of resonant solutions. Additionally, we connect our discussion to notions of resonance in systems of partial differential equations, including fluid-structure interactions and partially damped systems., Comment: 36 pages, 21 figures

We prove that the intermediate Jacobian of the Klein quartic $3$-fold $X$ is not isomorphic, as a principally polarized abelian variety, to a product of Jacobians of curves. As corollaries we deduce (using a criterion of Clemens-Griffiths) that $X$, as well as the general smooth quartic $3$-fold, is irrational. These corollaries were known: Iskovskih-Manin \cite{IM} proved that every smooth quartic $3$-fold is irrational. However, the method of proof here is different than that of \cite{IM} and is significantly simpler.

In this paper we explore several applications of the recently introduced spaces of functions of bounded $\beta$-dimensional mean oscillation for $\beta \in (0,n]$ to regularity theory of critical exponent elliptic equations. We first show that functions with gradient in weak-$L^n$ are in $BMO^\beta$ for any $\beta \in (0,n]$, improving the classical result $\nabla u\in L^n$ implies $u\in BMO$. We apply this result to the Poisson equation $-\Delta u = \operatorname*{div} F$ with zero boundary conditions in a bounded $C^1$ domain to show that $u\in BMO^{\beta}$ when $F$ is in weak-$L^n$. Next, we consider the $n$-Laplace equation \begin{align*} -\operatorname*{div}( |\nabla U|^{n-2} \nabla U) &= F \text{ in } \Omega, \newline U &=0 \text{ on }\partial \Omega. \end{align*} with $F\in L^1(\Omega)$ and show that the classical result $u\in BMO$ can be improved to $u\in BMO^\beta$. Finally, we consider the $n$-Laplace equation in the case when $F \in L^1$, $\operatorname*{div} F=0$ and prove that for smooth domains $\Omega$ we have the estimate \begin{align*} \|\nabla U \|_{L^n} \mathbb \leq C \, \|F\|^{1/(n-1)}_{L^1}, \end{align*} where the constant $C$ is independent of $F$., Comment: 18 pages, 1 figure

Algebras defined over fields of characteristic zero and positive characteristic usually do not behave the same way. However, for certain algebras, for example the group algebras, they behave the same way as the characteristic zero case at good enough prime. In this paper, we initiate the study of this topic by imposing increasingly strong hypotheses on basic algebras. When the algebras satisfy the right hypotheses, we have equalities of the dimensions of their cohomology groups between simple modules and equalities of graded Cartan numbers. The examples include the Solomon descent algebras of finite Coxeter groups at large enough primes, nil-Coxeter algebra, and certain finite semigroup algebras at an arbitrary prime.

In this paper, we study $\beta$-dimensional sharp maximal operator defined as \begin{align*} \mathcal{M}^{\#} _\beta f(x) := \sup_{Q} \inf_{c \in \mathbb{R}} \chi_{Q}(x) \frac{1}{\ell(Q)^\beta} \int_Q |f-c| \; d \mathcal{H}^{\beta}_\infty, \end{align*} where the supremum is taken over all cubes in $\mathbb{R}^d$ with sides pararell to the coordinate axes, $\ell(Q)$ is the length side of $Q$ and $\mathcal{H}^{\beta}_\infty$ is the Hausdorff content. In particular, we prove Fefferman-Stein inequality for $\mathcal{M}^{\#} _\beta f$ by giving a good lambda estimate for $\beta$-dimensional sharp maximal operator in the context of Hausdorff content. Additionally, we prove the Muckenhoupt-Wheeden inequality in this framework by establishing a good lambda inequality of independent interest., Comment: 28 pages

With climate extremes' rising frequency and intensity, robust analytical tools are crucial to predict their impacts on terrestrial ecosystems. Machine learning techniques show promise but require well-structured, high-quality, and curated analysis-ready datasets. Earth observation datasets comprehensively monitor ecosystem dynamics and responses to climatic extremes, yet the data complexity can challenge the effectiveness of machine learning models. Despite recent progress in deep learning to ecosystem monitoring, there is a need for datasets specifically designed to analyse compound heatwave and drought extreme impact. Here, we introduce the DeepExtremeCubes database, tailored to map around these extremes, focusing on persistent natural vegetation. It comprises over 40,000 spatially sampled small data cubes (i.e. minicubes) globally, with a spatial coverage of 2.5 by 2.5 km. Each minicube includes (i) Sentinel-2 L2A images, (ii) ERA5-Land variables and generated extreme event cube covering 2016 to 2022, and (iii) ancillary land cover and topography maps. The paper aims to (1) streamline data accessibility, structuring, pre-processing, and enhance scientific reproducibility, and (2) facilitate biosphere dynamics forecasting in response to compound extremes.

We present the design and validation of a variable temperature cryogenic blackbody source, hereinafter called a cold load, that will be used to characterize detectors to be deployed by CMB-S4, the next-generation ground-based cosmic microwave background (CMB) experiment. Although cold loads have been used for detector characterization by previous CMB experiments, this cold load has three novel design features: (1) the ability to operate from the 1 K stage of a dilution refrigerator (DR), (2) a 3He gas-gap heat switch to reduce cooling time, and (3) the ability to couple small external optical signals to measure detector optical time constants under low optical loading. The efficacy of this design was validated using a 150 GHz detector array previously deployed by the Spider experiment. Thermal tests showed that the cold load can be heated to temperatures required for characterizing CMB-S4's detectors without significantly impacting the temperatures of other cryogenic stages when mounted to the DR's 1 K stage. Additionally, optical tests demonstrated that external signals can be coupled to a detector array through the cold load without imparting a significant optical load on the detectors, which will enable measurements of the CMB-S4 detectors' optical time constants.

CMB-S4, the next-generation CMB observatory, will deploy hundreds of thousands of detectors to enable mapping the millimeter-wavelength sky with unprecedented speed. The large aperture telescopes for CMB-S4 consist of six-meter diameter crossed Dragone designs and a five-meter diameter three-mirror anastigmat. The two-mirror crossed Dragone design requires astigmatism corrections in the refractive optics to achieve diffraction-limited performance. We present biconic lens corrections for the CMB-S4 crossed Dragone camera optics and compare these designs to the camera optics for the three mirror anastigmat, as the optical designs of the cameras for these telescopes are being prototyped.

Stellar streams, long thin streams of stars, have been used as sensitive probes of dark matter substructure for over two decades. Gravitational interactions between dark matter substructures and streams lead to the formation of low density "gaps" in streams, with any given stream typically containing no more than a few such gaps. Prior models for the statistics of such gaps have relied on several simplifying assumptions for the properties of the subhalo population in the cold dark matter scenario. With the expected forthcoming increase in the number of streams, and gaps, observed, in this work we develop a more detailed model for the statistics of subhalos interacting with streams, and test some of the assumptions made in prior works. Instead of using simple fits to N-body estimates of subhalo population statistics at z = 0 as in previous work, we make use of realizations of time-dependent subhalo populations generated from a fully physical model, incorporating structure formation, and subhalo orbital evolution, including tidal heating and stripping physics, which has been carefully calibrated to match results of cosmological N-body simulations. We find that this model predicts up to 60% more gaps on average in Pal-5-like streams than prior works., Comment: 11 pages, 7 figures, 1 table

The theory of products of random matrices and Lyapunov exponents have been widely studied and applied in the fields of biology, dynamical systems, economics, engineering and statistical physics. We consider the product of an i.i.d. sequence of $2\times 2$ random non-invertible matrices with real entries. Given some mild moment assumptions we prove an explicit formula for the Lyapunov exponent and prove a central limit theorem with an explicit formula for the variance in terms of the entries of the matrices. We also give examples where exact values for the Lyapunov exponent and variance are computed. An important example where non-invertible matrices are essential is the random Hill's equation, which has numerous physical applications, including the astrophysical orbit problem., Comment: 11 pages

We construct stationary, rotating black binaries in general relativity with a positive cosmological constant. We consider identical black holes with either aligned or anti-aligned spins. Both cases have less entropy than the corresponding single Kerr/Schwarzschild de Sitter black hole with the same total angular momentum and cosmological horizon entropy. Our solutions establish continuous non-uniqueness in general relativity without matter. They also provide initial data for the spinning binary merger problem (when orbital angular momentum is added)., Comment: 15 pages, 11 figures. arXiv admin note: text overlap with arXiv:2303.07361

Ensuring that machine learning (ML) models are safe, effective, and equitable across all patient groups is essential for clinical decision-making and for preventing the reinforcement of existing health disparities. This review examines notions of fairness used in ML for health, including a review of why ML models can be unfair and how fairness has been quantified in a wide range of real-world examples. We provide an overview of commonly used fairness metrics and supplement our discussion with a case-study of an openly available electronic health record (EHR) dataset. We also discuss the outlook for future research, highlighting current challenges and opportunities in defining fairness in health.

Weakly interacting massive particles (WIMPs) may interact with a virtual pion that is exchanged between nucleons. This interaction channel is important to consider in models where the spin-independent isoscalar channel is suppressed. Using data from the first science run of the LUX-ZEPLIN dark matter experiment, containing 60 live days of data in a 5.5~tonne fiducial mass of liquid xenon, we report the results on a search for WIMP-pion interactions. We observe no significant excess and set an upper limit of $1.5\times10^{-46}$~cm$^2$ at a 90\% confidence level for a WIMP mass of 33~GeV/c$^2$ for this interaction.