Search

The progenitor system(s) as well as the explosion mechanism(s) of thermonuclear (Type Ia) supernovae are long-standing issues in astrophysics. Here we present ejecta masses and other physical parameters for 28 recent Type Ia supernovae inferred from multiband photometric and optical spectroscopic data. Our results confirm that the majority of SNe Ia show {\it observable} ejecta masses below the Chandrasekhar-limit (having a mean $M_{\rm ej} \approx 1.1 \pm 0.3$ M$_\odot$), consistent with the predictions of recent sub-M$_{\rm Ch}$ explosion models. They are compatible with models assuming either single- or double-degenerate progenitor configurations. We also recover a sub-sample of supernovae within $1.2 $ M$_\odot$ $< M_{\rm {ej}} < 1.5$ M$_\odot$ that are consistent with near-Chandrasekhar explosions. Taking into account the uncertainties of the inferred ejecta masses, about half of our SNe are compatible with both explosion models. We compare our results with those in previous studies, and discuss the caveats and concerns regarding the applied methodology.

We study zero attractors for polynomials built from partition statistics, complementing earlier work in this direction by Boyer, Goh, Parry, and others. In particular, using analytic methods we establish the zero attractor of partition $t$-hook polynomials for $t \geq 6$, addressing a question of Males with two of the authors. We also discuss some open problems and present data on other polynomial families, including those associated to deformations of Rogers--Ramanujan functions.

Over the last decade, experimental measurements of electrostatic screening lengths in concentrated electrolytes have exceeded theoretical predictions by orders of magnitude. This disagreement has led to a paradigm in which such screening lengths are referred to as 'anomalous underscreening', while others - predominantly those predicted by theory and molecular simulation - are referred to as 'normal underscreening'. Herein we use discrete Fourier analysis of the radial charge density obtained from molecular dynamics simulations to reveal the origin of anomalous underscreening in concentrated electrolytes. Normal underscreening above the Kirkwood point arises from low-frequency decay modes of the electrostatic potential, while anomalous underscreening arises from high-frequency decay modes that are observed only at high concentrations. The screening length associated with a particular decay mode is in turn determined by the degree of short-range interference between ion-ion correlation functions. The long-range decay associated with anomalous underscreening is thus ultimately determined by short range structure in the bulk electrolyte. These results reconcile the disagreement between experimental measurements and theoretical predictions of screening lengths in concentrated electrolytes., Comment: 16 pages, 3 figures

We explore the consequence of generalized symmetries in four-dimensional $\mathcal{N}=1$ superconformal field theories. First, we classify all possible supersymmetric gauge theories with a simple gauge group that have a nontrivial one-form symmetry and flows to a superconformal field theory. Upon identifying unbroken discrete zero-form symmetries from the ABJ anomaly, we find that many of these theories have mixed zero-form/one-form 't Hooft anomalies. Then we classify the relevant deformations of these SCFTs that preserve the anomaly. From this mixed anomaly together with the anomalies of the discrete zero-form symmetries, we find obstructions for the relevant deformations of these SCFTs to flow to a trivially gapped phase. We also study non-Lagrangian SCFTs formed by gauging copies of Argyres-Douglas theories and constrain their deformations. In particular, we explore a new duality between the diagonal gauging of two $\mathcal{D}_3(SU(N))$ theories and $SU(N)$ gauge theory with two adjoints. We also repeat our analysis for a host of non-supersymmetric gauge theories having nontrivial one-form symmetry including examples that appear to flow to Bank-Zaks type CFTs., Comment: 78 pages + references

Quantum error correction provides a path to reach practical quantum computing by combining multiple physical qubits into a logical qubit, where the logical error rate is suppressed exponentially as more qubits are added. However, this exponential suppression only occurs if the physical error rate is below a critical threshold. In this work, we present two surface code memories operating below this threshold: a distance-7 code and a distance-5 code integrated with a real-time decoder. The logical error rate of our larger quantum memory is suppressed by a factor of $\Lambda$ = 2.14 $\pm$ 0.02 when increasing the code distance by two, culminating in a 101-qubit distance-7 code with 0.143% $\pm$ 0.003% error per cycle of error correction. This logical memory is also beyond break-even, exceeding its best physical qubit's lifetime by a factor of 2.4 $\pm$ 0.3. We maintain below-threshold performance when decoding in real time, achieving an average decoder latency of 63 $\mu$s at distance-5 up to a million cycles, with a cycle time of 1.1 $\mu$s. To probe the limits of our error-correction performance, we run repetition codes up to distance-29 and find that logical performance is limited by rare correlated error events occurring approximately once every hour, or 3 $\times$ 10$^9$ cycles. Our results present device performance that, if scaled, could realize the operational requirements of large scale fault-tolerant quantum algorithms., Comment: 10 pages, 4 figures, Supplementary Information

We investigate the dynamical and physical structures of bright-rimmed clouds (BRCs) in a nearby HII region. We focused on carbon- and oxygen-bearing species that trace photon-dominated regions (PDRs) and warm molecular cloud surfaces in order to understand the effect of UV radiation from the exciting stars on the cloud structure. We mapped four regions around the most prominent BRCs at scales of 4--10 arcmin in the HII region IC 1396 in [CII] 158 micron with (up)GREAT on board SOFIA. IC 1396 is predominantly excited by an O6.5V star. Toward IC 1396A, we also observed [OI] 63 micron and 145 micron. We combined these observations with JCMT archive data, which provide the low-J transitions of CO, $^{13}$CO, and C$^{18}$O. All spectra are velocity-resolved. The line profiles show a variety of velocity structures, which we investigated in detail for all observed emission lines. We find no clear sign of photoevaporating flows in the [CII] spectra, although the uncertainty in the location of the BRCs along the line of sight makes this interpretation inconclusive. Our analysis of the [$^{13}$CII] emission in IC 1396A suggests that the [CII] is likely mostly optically thin. The heating efficiency, measured by the ([CII]+[OI] 63 micron)/far-infrared intensity ratio, is higher in the northern part of IC 1396A than in the southern part, which may indicate a difference in the dust properties of the two areas. The complex velocity structures identified in the BRCs of IC 1396, which is apparently a relatively simple HII region, highlight the importance of velocity-resolved data for disentangling different components along the line of sight and thus facilitating a detailed study of the dynamics of the cloud. We also demonstrate that the optically thin [$^{13}$CII] and [OI] 145 micron emission lines are essential for a conclusive interpretation of the [CII] 158 micron and [OI] 63 micron line profiles., Comment: Accepted for publication in A&A, 26 pages including Appendices

We are living in an age of protest. Although we have an excellent understanding of the factors that predict participation in protest, we understand little about the conditions that foster a sustained (versus transient) movement. How do interactions between supporters and authorities combine to influence whether and how people engage (i.e., using conventional or radical tactics)? This paper introduces a novel, theoretically-founded and empirically-informed agent-based model (DIMESim) to address these questions. We model the complex interactions between the psychological attributes of the protester (agents), the authority to whom the protests are targeted, and the environment that allows protesters to coordinate with each other -- over time, and at a population scale. Where an authority is responsive and failure is contested, a modest sized conventional movement endured. Where authorities repeatedly and incontrovertibly fail the movement, the population disengaged from action but evidenced an ongoing commitment to radicalism (latent radicalism)., Comment: Initial submission version of journal paper

Motivated by the design question of additional fuel needed to complete a task in an uncertain environment, this paper introduces metrics to quantify the maximal additional energy used by a control system in the presence of bounded disturbances when compared to a nominal, disturbance-free system. In particular, we consider the task of finite-time stabilization for a linear time-invariant system. We first derive the nominal energy required to achieve this task in a disturbance-free system, and then the worst-case energy over all feasible disturbances. The latter leads to an optimal control problem with a least-squares solution, and then an infinite-dimensional optimization problem where we derive an upper bound on the solution. The comparison of these energies is accomplished using additive and multiplicative metrics, and we derive analytical bounds on these metrics. Simulation examples on an ADMIRE fighter jet model demonstrate the practicability of these metrics, and their variation with the task hardness, a combination of the distance of the initial condition from the origin and the task completion time., Comment: 6 pages, 4 figures. IEEE Conference on Decision and Control

The extra-dimensional axion solves the strong CP problem while largely circumventing the quality problem that plagues its four-dimensional counterparts. Such high quality can be clearly understood in terms of the generalized global symmetries of the higher-dimensional theory. We emphasize that an electric one-form symmetry is entirely responsible for protecting the potential of axions arising from 5D gauge theories and use this to systematically characterize the extra-dimensional axion quality problem. We identify three ways of breaking this one-form symmetry to generate an axion potential: adding electrically charged matter, gauging a magnetic higher-form symmetry, and turning on an ABJ anomaly. In the latter case, we identify new ways of generating an axion potential via extra-dimensional magnetic monopoles. We also discuss how the axion is modified if the protective electric one-form symmetry is itself gauged. Finally, we relate these effects to gravitational expectations for the quality problem via generalized weak gravity conjectures. The clarity that generalized symmetries bring to the extra-dimensional axion quality problem highlights their relevance to particle phenomenology., Comment: 10 pages, 1 table

Transformer-based recommender systems, such as BERT4Rec or SASRec, achieve state-of-the-art results in sequential recommendation. However, it is challenging to use these models in production environments with catalogues of millions of items: scaling Transformers beyond a few thousand items is problematic for several reasons, including high model memory consumption and slow inference. In this respect, RecJPQ is a state-of-the-art method of reducing the models' memory consumption; RecJPQ compresses item catalogues by decomposing item IDs into a small number of shared sub-item IDs. Despite reporting the reduction of memory consumption by a factor of up to 50x, the original RecJPQ paper did not report inference efficiency improvements over the baseline Transformer-based models. Upon analysing RecJPQ's scoring algorithm, we find that its efficiency is limited by its use of score accumulators for each item, which prevents parallelisation. In contrast, LightRec (a non-sequential method that uses a similar idea of sub-ids) reported large inference efficiency improvements using an algorithm we call PQTopK. We show that it is also possible to improve RecJPQ-based models' inference efficiency using the PQTopK algorithm. In particular, we speed up RecJPQ-enhanced SASRec by a factor of 4.5 x compared to the original SASRec's inference method and by a factor of 1.56 x compared to the method implemented in RecJPQ code on a large-scale Gowalla dataset with more than a million items. Further, using simulated data, we show that PQTopK remains efficient with catalogues of up to tens of millions of items, removing one of the last obstacles to using Transformer-based models in production environments with large catalogues., Comment: Accepted by RecSys 2024

Development of methods to control the directional and spectral characteristics of thermal radiation from metallic surfaces is a critical factor enabling many important thermal management applications. In this paper, we study the thermal emission properties of functionalized aluminum surfaces produced through femtosecond laser surface processing (FLSP). These types of surfaces have recently been found to exhibit near-unity broadband omnidirectional emissivity. However, their ultrabroadband absorption response includes visible and near-infrared (IR) radiation, in addition to the mid-IR range, which limits their use as daytime passive radiative cooling devices. Here, we present ways to solve this problem by demonstrating a new design that uses a dielectric Bragg visible light reflector to accurately control the thermal emission spectra of the FLSP surface with the goal of achieving high performance daytime radiative cooling operation. In addition, we propose other designs based on dielectric multilayer structures to further tailor and control the spectra and thermal emission angles of the FLSP surfaces leading to narrowband and broadband directional thermal radiation. The presented photonic engineering approach combined with FLSP structures will be beneficial to various emerging applications, such as radiative cooling, thermal sensing, and thermophotovoltaics.

In this paper, an application of a 1D deep convolutional neural network (DCNN) and 4x4 1D DCNN Multi-channel Model (DCNN-MCM) was developed to predict the probability of a channel being associated with a given transmitter for each emitter in a 4x4 multi-input multi-output (MIMO) system. Counterintuitively, compared to the traditional approach to emitter association (EA), this research argues for the identification of received RF signals based on channel features (CFs) such as the channel impulse response (CIR) and transfer function (TF). Based on the CFs there are unique properties per transmit and receive pair that can be used to identify the different transmitters. More specifically, CFs are often defined by a wide sense stationary (WSS) stochastic process which gives them unique properties such as, being statistically independent and reciprocal for emitter association. Given these CFs, the received RF signals can be used to measure the clutter and objects surrounding the emitters. Safely assuming the surrounding clutter and objects are unique to each emitter, the estimation and tracking of this clutter provides a way of identifying what emitter is transmitting the observed signal. This method successfully classifies and identifies the emitters at 97.22% and 88.89% accuracy for the DCNN and DCNN-MCM respectively. This method was further compared with the accuracy of previous methods to test the validity of the approach and future improvements.

The layering approach used in fused filament fabrication (FFF) enables creation of complex designs generated by topology optimization. Defects associated with the layer-by-layer process, introduce considerable random variability to the local elastic modulus of the print. The elastic modulus along the fusion layers connecting bulk materials differs from that of the bulk areas. Accurate quantitative measurements of variations in both areas are essential to achieve robust optimized designs. This study aims to quantify the parameters of the random distributions given the surface strain field of the print measured by digital image correlation (DIC). Two statistical properties, mean and standard deviation, are sufficient to characterize the stochastic elastic modulus fields in each region. An efficient neural network model is developed to estimate spatial variations in the local elastic modulus within both bulk and fusion layers. This model is trained on a dataset of synthetic strain fields with known distributions in the elastic modulus fields. It performs well in correlating the elastic modulus with the input strain, as long as the standard deviation is below 60% of the mean of the random field. The predictive accuracy of the model on testing data, measured by the R2 score, is 0.99 and 0.95 for mean and standard deviation in the fusion material. The scores for the bulk material are 0.97 each. The trained model is implemented to predict the elastic modulus distribution of an FFF-printed material at a print speed of 30 mm/s and an extrusion temperature of 493.15 K, based on its DIC-measured surface strain data. The model predicts a mean and standard deviation of 1.2 GPa and 1 GPa for the bulk material and 400 MPa and 430 MPa for the fusion region. Validation of predictions confirms the reliability of this approach in measuring uncertainty in the local properties of the prints.

This study introduces a parameter-efficient Hierarchical Spatial Temporal Network (HiSTN) specifically designed for the task of emotion classification using multi-channel electroencephalogram data. The network incorporates a graph hierarchy constructed from bottom-up at various abstraction levels, offering the dual advantages of enhanced task-relevant deep feature extraction and a lightweight design. The model's effectiveness is further amplified when used in conjunction with a proposed unique label smoothing method. Comprehensive benchmark experiments reveal that this combined approach yields high, balanced performance in terms of both quantitative and qualitative predictions. HiSTN, which has approximately 1,000 parameters, achieves mean F1 scores of 96.82% (valence) and 95.62% (arousal) in subject-dependent tests on the rarely-utilized 5-classification task problem from the DREAMER dataset. In the subject-independent settings, the same model yields mean F1 scores of 78.34% for valence and 81.59% for arousal. The adoption of the Sequential Top-2 Hit Rate (Seq2HR) metric highlights the significant enhancements in terms of the balance between model's quantitative and qualitative for predictions achieved through our approach when compared to training with regular one-hot labels. These improvements surpass 50% in subject-dependent tasks and 30% in subject-independent tasks. The study also includes relevant ablation studies and case explorations to further elucidate the workings of the proposed model and enhance its interpretability., Comment: Draft

The existence of superconductivity (SC) in graphene appears to be established in both twisted and non-twisted multilayers. However, whether their building block, single-layer graphene (SLG), can also host SC remains an open question. Earlier theoretical works predicted that SLG could become a chiral d-wave superconductor driven by electronic interactions when doped to its van Hove singularity, but questions such as whether the d-wave SC survives the strong band renormalizations seen in experiments, its robustness against the source of doping, or if it will occur at any reasonable critical temperature (Tc) have remained difficult to answer, in part due to uncertainties in model parameters. In this study, we adopt a random-phase approximation framework based on a Kohn-Luttinger-like mechanism to investigate SC in heavily-doped SLG. We predict that robust d+id topological SC could arise in SLG doped by Tb, with a Tc up to 600 mK. We also investigate the possibility of realizing d-wave SC by employing other dopants, such as Li or Cs. The structural models have been derived from angle-resolved photoemission spectroscopy measurements on Tb-doped graphene and first-principles calculations for Cs and Li doping. We find that dopants that change the lattice symmetry of SLG are detrimental to the d-wave state. The stability of the d-wave SC predicted here in Tb-doped SLG could provide a valuable insight for guiding future experimental efforts aimed at exploring topological superconductivity in monolayer graphene., Comment: 14 pages, 6 figures. Comments are very welcome

High-redshift radio(-loud) galaxies (H$z$RGs) are massive galaxies with powerful radio-loud active galactic nuclei (AGNs) and serve as beacons for protocluster identification. However, the interplay between H$z$RGs and the large-scale environment remains unclear. To understand the connection between H$z$RGs and the surrounding obscured star formation, we investigated the overdensity and spatial distribution of submillimeter-bright galaxies (SMGs) in the field of 4C\,23.56, a well-known H$z$RG at $z=2.48$. We used SCUBA-2 data ($\sigma\,{\sim}\,0.6$\,mJy) to estimate the $850\,{\rm \mu m}$ source number counts and examine the radial and azimuthal overdensities of the $850\,{\rm \mu m}$ sources in the vicinity of the H$z$RG. The angular distribution of SMGs is inhomogeneous around the H$z$RG 4C\,23.56, with fewer sources oriented along the radio jet. We also find a significant overdensity of bright SMGs (${\rm S}_{850\rm\,\mu m}\geq5\,$mJy). Faint and bright SMGs exhibit different spatial distributions. The former are concentrated in the core region, while the latter prefer the outskirts of the H$z$RG field. High-resolution observations show that the seven brightest SMGs in our sample are intrinsically bright, suggesting that the overdensity of bright SMGs is less likely due to the source multiplicity., Comment: 19 pages, 17 figures, 5 tables, accepted to A&A

Spin- and charge-lattice interactions are potential key factors in the microscopic mechanism of high-temperature superconductivity in cuprates. Although both interactions can dramatically shape the low-energy electronic structure, their phenomenological roles in superconductivity are usually investigated independently. Employing angle-resolved photoemission spectroscopy, we reveal the spectroscopic fingerprint of short-range antiferromagnetic order in conjunction with enhanced electron-phonon interaction in the electron-doped cuprate superconductor $\mathrm{Nd_{1.85}Ce_{0.15}CuO_4}$. The observed mode coupling exhibits a strong momentum dependence that is in striking contrast to the node-antinode dichotomy previously observed in the hole-doped cuprates. Our results reveal an intimate relationship between electron-phonon coupling and antiferromagnetic fluctuations, which collectively sets the stage for unconventional superconductivity in the electron-doped cuprates.

The left and right diameters of a monoid are topological invariants defined in terms of suprema of lengths of derivation sequences with respect to finite generating sets for the universal left or right congruences. We compute these parameters for the endomorphism monoid $End(C)$ of a chain $C$. Specifically, if $C$ is infinite then the left diameter of $End(C)$ is 2, while the right diameter is either 2 or 3, with the latter equal to 2 precisely when $C$ is a quotient of $C{\setminus}\{z\}$ for some endpoint $z$. If $C$ is finite then so is $End(C),$ in which case the left and right diameters are 1 (if $C$ is non-trivial) or 0., Comment: 17 pages

Bootstrap current in stellarators can be presented as a sum of a collisionless value given by the Shaing-Callen asymptotic formula and an off-set current, which non-trivially depends on plasma collisionality and radial electric field. Using NEO-2 modelling, analytical estimates and semi-analytical studies with help of a propagator method, it is shown that the off-set current in the $1/\nu$ regime does not converge with decreasing collisionality $\nu_\ast$ but rather shows oscillations over $\log\nu_\ast$ with an amplitude of the order of the bootstrap current in an equivalent tokamak. The convergence to the Shaing-Callen limit appears in regimes with significant orbit precession, in particular, due to a finite radial electric field, where the off-set current decreases as $\nu_\ast^{3/5}$. The off-set current strongly increases in case of nearly aligned magnetic field maxima on the field line where it diverges as $\nu_\ast^{-1/2}$ in the $1/\nu$ regime and saturates due to the precession at a level exceeding the equivalent tokamak value by ${v_E^\ast}^{-1/2}$ where $v_E^\ast$ is the perpendicular Mach number. The latter off-set, however, can be minimized by further aligning local magnetic field maxima and by fulfilling an extra integral condition of "equivalent ripples" for the magnetic field. A criterion for the accuracy of this alignment and of ripple equivalence is derived. In addition, the possibility of the bootstrap effect at the magnetic axis caused by the above off-set is also discussed., Comment: 56 pages, 27 figures, talk at European Fusion Theory Conference 2023, Padua

We present initial results from the Polarisation Sky Survey of the Universe's Magnetism (POSSUM), analysing 22,817 Faraday Rotation Measures (RMs) with median uncertainties of 1.2 rad m^-2 across 1,520 square degrees to study magnetised gas associated with 55 nearby galaxy groups (z less than 0.025) with halo masses between 10^12.5 and 10^14.0 M_sun. We identify two distinct gas phases: the Intragroup Medium (IGrM) within 0-2 splashback radii and the Warm-Hot Intergalactic Medium (WHIM) extending from 2 to 7 splashback radii. These phases enhance the standard deviation of residual (i.e., Galactic foreground RM-subtracted) RMs by 6.9 +/- 1.8 rad m^-2 and 4.2 +/- 1.2 rad m^-2, respectively. Estimated magnetic field strengths are several microGauss within the IGrM and 0.1-1 microGauss in the WHIM. We estimate the plasma beta in both phases and show that magnetic pressure might be more dynamically important than in the ICM of more massive clusters or sparse cosmic web filaments. Our findings indicate that "missing baryons" in the WHIM likely extend beyond the gravitational radii of group-mass halos to Mpc scales, consistent with large-scale, outflow-driven "magnetised bubbles" seen in cosmological simulations. We demonstrate that RM grids are an effective method for detecting magnetised thermal gas at galaxy group interfaces and within the cosmic web. This approach complements X-ray and Sunyaev-Zel'dovich effect methods, and when combined with Fast Radio Burst Dispersion Measures, data from the full POSSUM survey, comprising approximately a million RMs, will allow direct magnetic field measurements to further our understanding of baryon circulation in these environments and the magnetised universe., Comment: 15 pages, 7 figures, 3 tables. Accepted for publication in MNRAS

Many X-ray binaries are transiently accreting. Having statistics on their recurrence times is helpful to address questions related to binary evolution and populations, as well as the physics of binary systems. We compile a catalog of known outbursts of neutron star (identified through bursts or pulsations) low-mass X-ray binaries, until late 2023. Most outbursts are taken from the literature, but we also identify some outbursts from public X-ray monitoring lightcurves. We find 109 outbursts not previously identified in the literature; most are from the frequent transients GRS 1747-312 and the Rapid Burster MXB 1730-335, though we suspect that two outbursts from Liller 1 may be from another transient, besides the Rapid Burster. We also find new outbursts for 10 other systems, and verify substantial quiescent intervals for XMM J174457-2850.3, XMMU J174716.1-281048, and AX J1754.2-2754. Outburst detection has been relatively efficient since 1996 for outbursts above $F_X$(2-10)$=3\times10^{-10}$ ergs/s/cm$^2$. While several systems have many known outbursts, 40 of the 85 systems we track have zero or one recorded outburst between 1996 and 2023. This suggests that faint Galactic Center X-ray binaries may be neutron star X-ray binaries, though we cannot completely rule out the proposition that most neutron star X-ray binaries undergo frequent outbursts below all-sky monitor detection limits., Comment: Submitted to AAS Journals. Comments very welcome

We argue by example that conditionally clean ancillae, recently described by [NZS24], should become a standard tool in the quantum circuit design kit. We use conditionally clean ancillae to reduce the gate counts and depths of several circuit constructions. In particular, we present: (a) n-controlled NOT using 2n Toffolis and O(log n) depth given 2 clean ancillae. (b) n-qubit incrementer using 3n Toffolis given log*(n) clean ancillae. (c) n-qubit quantum-classical comparator using 3n Toffolis given log*(n) clean ancillae. (d) unary iteration over [0, N) using 2.5N Toffolis given 2 clean ancillae. (e) unary iteration via skew tree over [0, N) using 1.25 N Toffolis given n dirty ancillae. We also describe a technique for laddered toggle detection to replace clean ancillae with dirty ancillae in all our constructions with a 2x Toffoli overhead. Our constructions achieve the lowest gate counts to date with sublinear ancilla requirements and should be useful building blocks to optimize circuits in the low-qubit regime of Early Fault Tolerance.

Several Earth system components are at a high risk of undergoing rapid and irreversible qualitative changes or `tipping', due to increasing climate warming. Potential tipping elements include Arctic sea-ice, Atlantic meridional overturning circulation, and tropical coral reefs. Amidst such immediate concerns, it has become necessary to investigate the feasibility of arresting or even reversing the crossing of tipping thresholds using feedback control. In this paper, we study the control of an idealized diffusive energy balance model (EBM) for the Earth's climate; this model has two tipping points due to strong co-albedo feedback. One of these tipping points is a `small icecap' instability responsible for a rapid transition to an ice-free climate state under increasing greenhouse gas (GHG) forcing. We develop an optimal control strategy for the EBM under different climate forcing scenarios with the goal of reversing sea ice loss while minimizing costs. We find that effective control is achievable for such a system, but the cost of reversing sea-ice loss nearly quadruples for an initial state that has just tipped as compared to a state before reaching the tipping point. We also show that thermal inertia may delay tipping leading to an overshoot of the critical GHG forcing threshold. This may offer a short intervention window (overshoot window) during which the control required to reverse sea-ice loss only scales linearly with intervention time. While systems with larger system inertia may have longer overshoot windows, this increased elbow room comes with a steeper rise in the requisite control once the intervention is delayed past this window. Additionally, we find that the requisite control to restore sea-ice is localized in the polar region.

A paper of Beckner, Carbery, Semmes, and Soria proved that the Fourier extension operator associated to the sphere cannot be weak-type bounded at the restriction endpoint $q = 2d/(d-1)$. We generalize their approach to prove that the extension operator associated with any $n$-dimensional quadratic manifold in $\mathbb{R}^d$ cannot be weak-type bounded at $q = 2d/n$. The key step in generalizing the proof of Beckner, Carbery, Semmes, and Soria will be replacing Kakeya sets with what we will call $\mathcal{N}$-Kakeya sets, where $\mathcal{N}$ denotes a closed subset of the Grassmannian $\text{Gr}(d-n,d)$. We define $\mathcal{N}$-Kakeya sets to be subsets of $\mathbb{R}^d$ containing a translate of every $d-n$-plane segment in $\mathcal{N}$. We will prove that if $\mathcal{N}$ is closed and $n$-dimensional, then there exists compact, measure zero $\mathcal{N}$-Kakeya sets, generalizing the same result for standard Kakeya sets.

Radium-225 (nuclear spin $I=1/2$) ions possess electronic hyperfine transitions that are first-order insensitive to magnetic field noise, which is advantageous for optical clocks and quantum information science. We report on laser cooling and trapping of radium-225 ions and hyperfine splitting measurements of the ion's $7s$ $^2S_{1/2}$, $7p$ $^2P_{1/2}$, and $6d$ $^2D_{3/2}$ states. We measured the ground state hyperfine constant, $A(^2S_{1/2}) = -27.684511056(9)\ \mathrm{GHz}$, and the quadratic Zeeman coefficient, $C_2 = 142.3(10)\ \mathrm{Hz\ G}^{-2}$, of the $^2S_{1/2} (F=0, m_F = 0) \leftrightarrow~^2S_{1/2} (F=1, m_{F} = 0)$ transition. We also measured the hyperfine constants of the $^2P_{1/2}$ state, $A(^2P_{1/2}) = -5.447(4)\ \mathrm{GHz}$, and the $^2D_{3/2}$ state, $A(^2D_{3/2}) = -619.7(11)\ \mathrm{MHz}$., Comment: 5 pages, 4 figures

We study a multi-body finite element model of a packing of hydrogel particles using the Flory-Rehner constitutive law to model the deformation of the swollen polymer network. We show that while the dependence of the pressure, $\Pi$, on the effective volume fraction, $\phi$, is virtually identical to a monolithic Flory material, the shear modulus, $\mu$, behaves in a non-trivial way. $\mu$ increases monotonically with $\Pi$ from zero and remains below about $80\%$ of the monolithic Flory value at the largest $\Pi$ we study here. The local shear strain in the particles has a large spatial variation. Local strains near the centers of the particles are all roughly equal to the applied shear strain, but the local strains near the contact facets are much smaller and depend on the orientation of the facet. We show that the slip between particles at the facets depends strongly on the orientation of the facet and is, on average, proportional to the component of the applied shear strain resolved onto the facet orientation. This slip screens the stress transmission and results in a reduction of the shear modulus relative to what one would obtain if the particles were welded together at the facet. Surprisingly, given the reduction in the shear modulus arising from the facet slip, and the spatial variations in the local shear strain inside the particles themselves, the deformation of the particle centroids is rather homogeneous with the strains of the Delaunay triangles having fluctuations of only order $\pm 5\%$. These results should open the way to construction of quantitative estimates of the shear modulus in highly compressed packings via mean-field, effective-medium type approaches., Comment: 9 pages, 12 figures

For navigation of robots, image segmentation is an important component to determining a terrain's traversability. For safe and efficient navigation, it is key to assess the uncertainty of the predicted segments. Current uncertainty estimation methods are limited to a specific choice of model architecture, are costly in terms of training time, require large memory for inference (ensembles), or involve complex model architectures (energy-based, hyperbolic, masking). In this paper, we propose a simple, light-weight module that can be connected to any pretrained image segmentation model, regardless of its architecture, with marginal additional computation cost because it reuses the model's backbone. Our module is based on maximum separation of the segmentation classes by respective prototype vectors. This optimizes the probability that out-of-distribution segments are projected in between the prototype vectors. The uncertainty value in the classification label is obtained from the distance to the nearest prototype. We demonstrate the effectiveness of our module for terrain segmentation., Comment: 10 pages

Galaxies are theorized to form and co-evolve with their dark matter halos, such that their stellar masses and halo masses should be well-correlated. However, it is not known whether other observable galaxy features, such as their morphologies or large-scale environments, can be used to tighten the correlation between galaxy properties and halo masses. In this work, we train a baseline random forest model to predict halo mass using galaxy features from the Illustris TNG50 hydrodynamical simulation, and compare with convolutional neural networks (CNNs) and graph neural networks (GNNs) trained respectively using galaxy image cutouts and galaxy point clouds. The best baseline model has a root mean squared error (RMSE) of 0.310 and mean absolute error (MAE) of 0.220, compared to the CNN (RSME=0.359, MAE=0.238), GNN (RMSE=0.248, MAE=0.158), and a novel combined CNN+GNN (RMSE=0.248, MAE=0.144). The CNN is likely limited by our small data set, and we anticipate that the CNN and CNN+GNN would benefit from training on larger cosmological simulations. We conclude that deep learning models can leverage information from galaxy appearances and environment, beyond commonly used summary statistics, in order to better predict the halo mass., Comment: 11 pages, 3 figures, accepted to ICML 2024 AI4Science Workshop

This paper presents a comprehensive survey of AI-driven mini-grid solutions aimed at enhancing sustainable energy access. It emphasises the potential of mini-grids, which can operate independently or in conjunction with national power grids, to provide reliable and affordable electricity to remote communities. Given the inherent unpredictability of renewable energy sources such as solar and wind, the necessity for accurate energy forecasting and management is discussed, highlighting the role of advanced AI techniques in forecasting energy supply and demand, optimising grid operations, and ensuring sustainable energy distribution. This paper reviews various forecasting models, including statistical methods, machine learning algorithms, and hybrid approaches, evaluating their effectiveness for both short-term and long-term predictions. Additionally, it explores public datasets and tools such as Prophet, NeuralProphet, and N-BEATS for model implementation and validation. The survey concludes with recommendations for future research, addressing challenges in model adaptation and optimisation for real-world applications.

The International Muon Collider Collaboration (IMCC) [1] was established in 2020 following the recommendations of the European Strategy for Particle Physics (ESPP) and the implementation of the European Strategy for Particle Physics-Accelerator R&D Roadmap by the Laboratory Directors Group [2], hereinafter referred to as the the European LDG roadmap. The Muon Collider Study (MuC) covers the accelerator complex, detectors and physics for a future muon collider. In 2023, European Commission support was obtained for a design study of a muon collider (MuCol) [3]. This project started on 1st March 2023, with work-packages aligned with the overall muon collider studies. In preparation of and during the 2021-22 U.S. Snowmass process, the muon collider project parameters, technical studies and physics performance studies were performed and presented in great detail. Recently, the P5 panel [4] in the U.S. recommended a muon collider R&D, proposed to join the IMCC and envisages that the U.S. should prepare to host a muon collider, calling this their "muon shot". In the past, the U.S. Muon Accelerator Programme (MAP) [5] has been instrumental in studies of concepts and technologies for a muon collider., Comment: This document summarises the International Muon Collider Collaboration (IMCC) progress and status of the Muon Collider R&D programme

Neural networks -- especially those that use large, pre-trained language models -- have improved search engines in various ways. Most prominently, they can estimate the relevance of a passage or document to a user's query. In this work, we depart from this direction by exploring whether neural networks can effectively predict which of a document's passages are unlikely to be relevant to any query submitted to the search engine. We refer to this query-agnostic estimation of passage relevance as a passage's quality. We find that our novel methods for estimating passage quality allow passage corpora to be pruned considerably while maintaining statistically equivalent effectiveness; our best methods can consistently prune >25% of passages in a corpora, across various retrieval pipelines. Such substantial pruning reduces the operating costs of neural search engines in terms of computing resources, power usage, and carbon footprint -- both when processing queries (thanks to a smaller index size) and when indexing (lightweight models can prune low-quality passages prior to the costly dense or learned sparse encoding step). This work sets the stage for developing more advanced neural "learning-what-to-index" methods., Comment: SIGIR 2024

Let $R$ be a ring. The unitary addition Cayley graph of $R$, denoted $\mathcal{U}(R)$, is the graph with vertex $R$, and two distinct vertices $x$ and $y$ are adjacent if and only if $x+y$ is a unit. We determine a formula for the clique number and chromatic number of such graphs when $R$ is a finite commutative ring. This includes the special case when $R$ is $\mathbb{Z}_n$, the integers modulo $n$, where these parameters had been found under the assumption that $n$ is even, or $n$ is a power of an odd prime. Additionally, we study the achromatic number of $\mathcal{U}( \mathbb{Z}_n )$ in the case that $n$ is the product of two primes. We prove that the achromatic number of $\mathcal{U} ( \mathbb{Z}_{3q})$ is equal to $\frac{3q+1}{2}$ when $q > 3$ is a prime. We also prove a lower bound that applies when $n = pq$ where $p$ and $q$ are distinct odd primes.

We present results from a search for X-ray/gamma-ray counterparts of gravitational-wave (GW) candidates from the third observing run (O3) of the LIGO-Virgo-KAGRA (LVK) network using the Swift Burst Alert Telescope (Swift-BAT). The search includes 636 GW candidates received in low latency, 86 of which have been confirmed by the offline analysis and included in the third cumulative Gravitational-Wave Transient Catalogs (GWTC-3). Targeted searches were carried out on the entire GW sample using the maximum--likelihood NITRATES pipeline on the BAT data made available via the GUANO infrastructure. We do not detect any significant electromagnetic emission that is temporally and spatially coincident with any of the GW candidates. We report flux upper limits in the 15-350 keV band as a function of sky position for all the catalog candidates. For GW candidates where the Swift-BAT false alarm rate is less than 10$^{-3}$ Hz, we compute the GW--BAT joint false alarm rate. Finally, the derived Swift-BAT upper limits are used to infer constraints on the putative electromagnetic emission associated with binary black hole mergers., Comment: 50 pages, 10 figures, 4 tables

The standard cosmological model, which assumes statistical isotropy and parity invariance, predicts the absence of correlations between even-parity and odd-parity observables of the cosmic microwave background (CMB). Contrary to these predictions, large-angle CMB temperature anomalies generically involve correlations between even-$\ell$ and odd-$\ell$ angular power spectrum $C_\ell$, while recent analyses of CMB polarization have revealed non-zero equal-$\ell$ $EB$ correlations. These findings challenge the conventional understanding, suggesting deviations from statistical isotropy, violations of parity, or both. Cosmic topology, which involves changing only the boundary conditions of space relative to standard cosmology, offers a compelling framework to potentially account for such parity-violating observations. Topology inherently breaks statistical isotropy, and can also break homogeneity and parity, providing a natural paradigm for explaining observations of parity-breaking observables without the need to add parity violation to the underlying microphysics. Our investigation delves into the harmonic space implications of topology for CMB correlations, using as an illustrative example $EB$ correlations generated by tensor perturbations under both parity-preserving and parity-violating scenarios. Consequently, these findings not only challenge the foundational assumptions of the standard cosmological model but also open new avenues for exploring the topological structure of the Universe through CMB observations., Comment: 20 pages, 4 figures

The Synthetic Corona Outflow Model (SynCOM), an empirical model, simulates the solar corona's dynamics to match high-resolution observations, providing a useful resource for testing velocity measurement algorithms. SynCOM generates synthetic images depicting radial variability in polarized brightness and includes stochastic elements for plasma outflows and instrumental noise. It employs a predefined flow velocity probability distribution and an adjustable signal-to-noise ratio to evaluate different data analysis methods for coronal flows. By adjusting parameters to match specific coronal and instrumental conditions, SynCOM offers a platform to assess these methods for determining coronal velocity and acceleration. Validating these measurements would help to understand solar wind origins and support missions such as the Polarimeter to Unify the Corona and Heliosphere (PUNCH). In this study, we demonstrate how SynCOM can be employed to assess the precision and performance of two different flow tracking methods. By providing a ground-truth based on observational data, we highlight the importance of SynCOM in confirming observational standards for detecting coronal flows., Comment: 18 pages, 10 figures

The geomagnetic "solar flare effect" (SFE) results from excess ionization in the Earth's ionosphere, famously first detected at the time of the Carrington flare in 1859. This indirect detection of a flare constituted one of the first cases of "multimessenger astronomy," whereby solar ionizing radiation stimulates ionospheric currents. Well-observed SFEs have few-minute time scales and perturbations of >10 nT, with the greatest events reaching above 100 nT. In previously reported cases the SFE time profiles tend to resemble those of solar soft X-ray emission, which ionizes the D-region; there is also a less-well-studied contribution from Lyman-alpha. We report here a specific case, from flare SOL2024-03-10 (M7.4), in which an impulsive SFE deviated from this pattern. This flare contained an "early impulsive" component of exceptionally hard radiation, extending up to gamma-ray energies above 1 MeV, distinctly before the bulk of the flare soft X-ray emission. We can characterize the spectral distribution of this early-impulsive component in detail, thanks to the modern extensive wavelength coverage. A more typical gradual SFE occurred during the flare's main phase. We suggest that events of this type warrant exploration of the solar physics in the "impulse response" limit of very short time scales., Comment: MNRAS to be published

We present the most comprehensive catalog to date of Type I Superluminous Supernovae (SLSNe), a class of stripped envelope supernovae (SNe) characterized by exceptionally high luminosities. We have compiled a sample of 262 SLSNe reported through 2022 December 31. We verified the spectroscopic classification of each SLSN and collated an exhaustive data set of UV, optical and IR photometry from both publicly available data and our own FLEET observational follow-up program, totaling over 30,000 photometric detections. Using these data we derive observational parameters such as the peak absolute magnitudes, rise and decline timescales, as well as bolometric luminosities, temperature and photospheric radius evolution for all SLSNe. Additionally, we model all light curves using a hybrid model that includes contributions from both a magnetar central engine and the radioactive decay of $^{56}$Ni. We explore correlations among various physical and observational parameters, and recover the previously found relation between ejecta mass and magnetar spin, as well as the overall progenitor pre-explosion mass distribution with a peak at $\approx 6.5$ M$_\odot$. We find no significant redshift dependence for any parameter, and no evidence for distinct sub-types of SLSNe. We find that $< 3$\% of SLSNe are best fit with a significant contribution from radioactive decay $\gtrsim 50$\%, representing a set of relatively dim and slowly declining SNe. We provide several analytical tools designed to simulate typical SLSN light curves across a broad range of wavelengths and phases, enabling accurate K-corrections, bolometric scaling calculations, and inclusion of SLSNe in survey simulations or future comparison works. The complete catalog, including all of the photometry, models, and derived parameters, is made available as an open-source resource on GitHub., Comment: 59 pages, 22 Figures, Submitted to MNRAS

This paper presents verification-guided development (VGD), a software engineering process we used to build Cedar, a new policy language for expressive, fast, safe, and analyzable authorization. Developing a system with VGD involves writing an executable model of the system and mechanically proving properties about the model; writing production code for the system and using differential random testing (DRT) to check that the production code matches the model; and using property-based testing (PBT) to check properties of unmodeled parts of the production code. Using VGD for Cedar, we can build fast, idiomatic production code, prove our model correct, and find and fix subtle implementation bugs that evade code reviews and unit testing. While carrying out proofs, we found and fixed 4 bugs in Cedar's policy validator, and DRT and PBT helped us find and fix 21 additional bugs in various parts of Cedar.