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Extractive summarization plays a pivotal role in natural language processing due to its wide-range applications in summarizing diverse content efficiently, while also being faithful to the original content. Despite significant advancement achieved in extractive summarization by Large Language Models (LLMs), these summaries frequently exhibit incoherence. An important aspect of the coherent summary is its readability for intended users. Although there have been many datasets and benchmarks proposed for creating coherent extractive summaries, none of them currently incorporate user intent to improve coherence in extractive summarization. Motivated by this, we propose a systematically created human-annotated dataset consisting of coherent summaries for five publicly available datasets and natural language user feedback, offering valuable insights into how to improve coherence in extractive summaries. We utilize this dataset for aligning LLMs through supervised fine-tuning with natural language human feedback to enhance the coherence of their generated summaries. Preliminary experiments with Falcon-40B and Llama-2-13B show significant performance improvements (~10% Rouge-L) in terms of producing coherent summaries. We further utilize human feedback to benchmark results over instruction-tuned models such as FLAN-T5 which resulted in several interesting findings. Data and source code are available at https://github.com/Mihir3009/Extract-AI., Comment: 10 pages

In this work we use Lagrangian perturbation theory to analyze the harmonic space galaxy clustering signal of Bright Galaxy Survey (BGS) and Luminous Red Galaxies (LRGs) targeted by the Dark Energy Spectroscopic Instrument (DESI), combined with the galaxy--galaxy lensing signal measured around these galaxies using Dark Energy Survey Year 3 source galaxies. The BGS and LRG galaxies are extremely well characterized by DESI spectroscopy and, as a result, lens galaxy redshift uncertainty and photometric systematics contribute negligibly to the error budget of our ``$2\times2$-point'' analysis. On the modeling side, this work represents the first application of the \texttt{spinosaurus} code, implementing an effective field theory model for galaxy intrinsic alignments, and we additionally introduce a new scheme (\texttt{MAIAR}) for marginalizing over the large uncertainties in the redshift evolution of the intrinsic alignment signal. Furthermore, this is the first application of a hybrid effective field theory (HEFT) model for galaxy bias based on the $\texttt{Aemulus}\, \nu$ simulations. Our main result is a measurement of the amplitude of the lensing signal, $S_8=\sigma_8 \left(\Omega_m/0.3\right)^{0.5} = 0.850^{+0.042}_{-0.050}$, consistent with values of this parameter derived from the primary CMB. This constraint is artificially improved by a factor of $51\%$ if we assume a more standard, but restrictive parameterization for the redshift evolution and sample dependence of the intrinsic alignment signal, and $63\%$ if we additionally assume the nonlinear alignment model. We show that when fixing the cosmological model to the best-fit values from Planck PR4 there is $> 5 \sigma$ evidence for a deviation of the evolution of the intrinsic alignment signal from the functional form that is usually assumed in cosmic shear and galaxy--galaxy lensing studies., Comment: 53 pages, 25 figures, updated to match version accepted by PRD

We infer the growth of large scale structure over the redshift range $0.4\lesssim z \lesssim 1$ from the cross-correlation of spectroscopically calibrated Luminous Red Galaxies (LRGs) selected from the Dark Energy Spectroscopic Instrument (DESI) legacy imaging survey with CMB lensing maps reconstructed from the latest Planck and ACT data. We adopt a hybrid effective field theory (HEFT) model that robustly regulates the cosmological information obtainable from smaller scales, such that our cosmological constraints are reliably derived from the (predominantly) linear regime. We perform an extensive set of bandpower- and parameter-level systematics checks to ensure the robustness of our results and to characterize the uniformity of the LRG sample. We demonstrate that our results are stable to a wide range of modeling assumptions, finding excellent agreement with a linear theory analysis performed on a restricted range of scales. From a tomographic analysis of the four LRG photometric redshift bins we find that the rate of structure growth is consistent with $\Lambda$CDM with an overall amplitude that is $\simeq5-7\%$ lower than predicted by primary CMB measurements with modest $(\sim2\sigma)$ statistical significance. From the combined analysis of all four bins and their cross-correlations with Planck we obtain $S_8 = 0.765\pm0.023$, which is less discrepant with primary CMB measurements than previous DESI LRG cross Planck CMB lensing results. From the cross-correlation with ACT we obtain $S_8 = 0.790^{+0.024}_{-0.027}$, while when jointly analyzing Planck and ACT we find $S_8 = 0.775^{+0.019}_{-0.022}$ from our data alone and $\sigma_8 = 0.772^{+0.020}_{-0.023}$ with the addition of BAO data. These constraints are consistent with the latest Planck primary CMB analyses at the $\simeq 1.6-2.2\sigma$ level, and are in excellent agreement with galaxy lensing surveys., Comment: 60 pages, 26 figures, comments welcome

We present a high-significance cross-correlation of CMB lensing maps from the Atacama Cosmology Telescope (ACT) Data Release 6 (DR6) with spectroscopically calibrated luminous red galaxies (LRGs) from the Dark Energy Spectroscopic Instrument (DESI). We detect this cross-correlation at a significance of 38$\sigma$; combining our measurement with the Planck Public Release 4 (PR4) lensing map, we detect the cross-correlation at 50$\sigma$. Fitting this jointly with the galaxy auto-correlation power spectrum to break the galaxy bias degeneracy with $\sigma_8$, we perform a tomographic analysis in four LRG redshift bins spanning $0.4 \le z \le 1.0$ to constrain the amplitude of matter density fluctuations through the parameter combination $S_8^\times = \sigma_8 \left(\Omega_m / 0.3\right)^{0.4}$. Prior to unblinding, we confirm with extragalactic simulations that foreground biases are negligible and carry out a comprehensive suite of null and consistency tests. Using a hybrid effective field theory (HEFT) model that allows scales as small as $k_{\rm max}=0.6$ $h/{\rm Mpc}$, we obtain a 3.3% constraint on $S_8^\times = \sigma_8 \left(\Omega_m / 0.3\right)^{0.4} = 0.792^{+0.024}_{-0.028}$ from ACT data, as well as constraints on $S_8^\times(z)$ that probe structure formation over cosmic time. Our result is consistent with the early-universe extrapolation from primary CMB anisotropies measured by Planck PR4 within 1.2$\sigma$. Jointly fitting ACT and Planck lensing cross-correlations we obtain a 2.7% constraint of $S_8^\times = 0.776^{+0.019}_{-0.021}$, which is consistent with the Planck early-universe extrapolation within 2.1$\sigma$, with the lowest redshift bin showing the largest difference in mean. The latter may motivate further CMB lensing tomography analyses at $z<0.6$ to assess the impact of potential systematics or the consistency of the $\Lambda$CDM model over cosmic time., Comment: Prepared for submission to JCAP (47 pages, 13 figures)

The calcium isotopes are an ideal system to investigate the evolution of shell structure and magic numbers. Although the properties of surface nucleons in calcium have been well studied, probing the structure of deeply bound nucleons remains a challenge. Here, we report on the first measurement of unbound states in $^{53}$Ca and $^{55}$Ca, populated from \ts{54,56}Ca($p,pn$) reactions at a beam energy of around 216 MeV/nucleon at the RIKEN Radioactive Isotopes Beam Factory. The resonance properties, partial cross sections, and momentum distributions of these unbound states were analyzed. Orbital angular momentum $l$ assignments were extracted from momentum distributions based on calculations using the distorted wave impulse approximation (DWIA) reaction model. The resonances at excitation energies of 5516(41)\,keV in $^{53}$Ca and 6000(250)\,keV in $^{55}$Ca indicate a significant $l$\, =\,3 component, providing the first experimental evidence for the $\nu 0f_{7/2}$ single-particle strength of unbound hole states in the neutron-rich Ca isotopes. The observed excitation energies and cross-sections point towards extremely localized and well separated strength distributions, with some fragmentation for the $\nu 0f_{7/2}$ orbital in $^{55}$Ca. These results are in good agreement with predictions from shell-model calculations using the effective GXPF1Bs interaction and \textit{ab initio} calculations and diverge markedly from the experimental distributions in the nickel isotones at $Z=28$., Comment: 13 pages, 7 figures

The CUbesat Solar Polarimeter (CUSP) project is a future CubeSat mission orbiting the Earth aimed to measure the linear polarization of solar flares in the hard X-ray band, by means of a Compton scattering polarimeter. CUSP will allow us to study the magnetic reconnection and particle acceleration in the flaring magnetic structures of our star. The project is in the framework of the Italian Space Agency Alcor Program, which aims to develop new CubeSat missions. CUSP is approved for a Phase B study that will last for 12 months, starting in mid-2024. We report on the current status of the CUSP mission project as the outcome of the Phase A., Comment: Proceeding of SPIE Conference "Astronomical Telescopes+ Instrumentation", Yokohama (Japan), 16-21 June 2024. arXiv admin note: substantial text overlap with arXiv:2208.06211

The CUbesat Solar Polarimeter (CUSP) project is a CubeSat mission orbiting the Earth aimed to measure the linear polarization of solar flares in the hard X-ray band by means of a Compton scattering polarimeter. CUSP will allow the study of the magnetic reconnection and particle acceleration in the flaring magnetic structures of our star. CUSP is a project in the framework of the Alcor Program of the Italian Space Agency aimed at developing new CubeSat missions. It is approved for a Phase B study. In this work, we report on the characterization of the Avalanche Photodiodes (APDs) that will be used as readout sensors of the absorption stage of the Compton polarimeter. We assessed the APDs gain and energy resolution as a function of temperature by irradiating the sensor with a \textsuperscript{55}Fe radioactive source. Moreover, the APDs were also characterized as being coupled to a GAGG scintillator., Comment: Proceeding of SPIE Conference "Astronomical Telescopes+ Instrumentation", Yokohama (Japan), 16-21 June 2024

The CUbesat Solar Polarimeter (CUSP) project aims to develop a constellation of two CubeSats orbiting the Earth to measure the linear polarization of solar flares in the hard X-ray band by means of a Compton scattering polarimeter on board of each satellite. CUSP will allow to study the magnetic reconnection and particle acceleration in the flaring magnetic structures. CUSP is a project approved for a Phase B study by the Italian Space Agency in the framework of the Alcor program aimed to develop CubeSat technologies and missions. In this paper we describe the a method for a multi-physical simulation analysis while analyzing some possible design optimization of the payload design solutions adopted. In particular, we report the mechanical design for each structural component, the results of static and dynamic finite element analysis, the preliminary thermo-mechanical analysis for two specific thermal cases (hot and cold orbit) and a topological optimization of the interface between the platform and the payload., Comment: Proceeding of SPIE Conference "Astronomical Telescopes+ Instrumentation", Yokohama (Japan), 16-21 June 2024

The CUbesat Solar Polarimeter (CUSP) project is a CubeSat mission orbiting the Earth aimed to measure the linear polarization of solar flares in the hard X-ray band by means of a Compton scattering polarimeter. CUSP will allow to study the magnetic reconnection and particle acceleration in the flaring magnetic structures of our star. CUSP is a project in the framework of the Alcor Program of the Italian Space Agency aimed to develop new CubeSat missions. It is approved for a Phase B study. In this work, we report on the accurate simulation of the detector's response to evaluate the scientific performance. A GEANT4 Monte Carlo simulation is used to assess the physical interactions of the source photons with the detector and the passive materials. Using this approach, we implemented a detailed CUSP Mass Model. In this work, we report on the evaluation of the detector's effective area as a function of the beam energy., Comment: Proceeding of SPIE Conference "Astronomical Telescopes+ Instrumentation", Yokohama (Japan), 16-21 June 2024

Large Language Models (LLMs) have been achieving competent performance on a wide range of downstream tasks, yet existing work shows that inference on structured data is challenging for LLMs. This is because LLMs need to either understand long structured data or select the most relevant evidence before inference, and both approaches are not trivial. This paper proposes a framework, Learning to Reduce, that fine-tunes a language model with On-Policy Learning to generate a reduced version of an input structured data. When compared to state-of-the-art LLMs like GPT-4, Learning to Reduce not only achieves outstanding performance in reducing the input, but shows generalizability on different datasets. We further show that the model fine-tuned with our framework helps LLMs better perform on table QA tasks especially when the context is longer., Comment: ICML 2024 Workshop on Long-Context Foundation Models, Vienna, Austria 2024. arXiv admin note: substantial text overlap with arXiv:2402.14195

Nickel nanoparticles (Ni NPs), thanks to their peculiar properties, are interesting materials for many applications including catalysis, hydrogen storage, and sensors. In this work, Ni NPs are synthesized in aqueous solution by a simple and rapid procedure with cetyltrimethylammonium bromide (CTAB) as a capping agent, and are extensively characterized by dynamic light scattering (DLS), scanning electron microscopy (SEM), and atomic force microscopy (AFM). We investigated their shape, dimension, and their distribution on the surfaces of SiO2 and epitaxial graphene (EG) samples. Ni NPs have an average diameter of ~11 nm, with a narrow size dispersion, and their arrangement on the surface is strongly dependent on the substrate. EG samples functionalized with Ni NPs are further characterized by X-ray photoelectron spectroscopy (XPS), as made and after thermal annealing above 350{\deg}C to confirm the degradation of CTAB and the presence of metallic Ni(0). Moreover, high resolution scanning tunneling microscopy (STM) topographies reveal the structural stability of the NPs up to 550 {\deg}C.

We present the analysis of the stationary equilibria and their stability in case of an opinion formation process in presence of binary opposite opinions evolving according to majority-like rules on social networks. The starting point is a kinetic Boltzmann-type model derived from microscopic interactions rules for the opinion exchange among individuals holding a certain degree of connectivity. The key idea is to derive from the kinetic model an Allen-Cahn type equation for the fraction of individuals holding one of the two opinions. The latter can be studied by means of a linear stability analysis and by exploiting integral operator analysis. While this is true for ternary interactions, for binary interactions the derived equation of interest is a linear scattering equation, that can be studied by means of General Relative Entropy tools and integral operators.

In this paper, we assess the scientific promise and technology feasibility of distributed instruments for planetary science. A distributed instrument is an instrument designed to collect spatially and temporally correlated data from multiple networked, geographically distributed point sensors. Distributed instruments are ubiquitous in Earth science, where they are routinely employed for weather and climate science, seismic studies and resource prospecting, and detection of industrial emissions. However, to date, their adoption in planetary surface science has been minimal. It is natural to ask whether this lack of adoption is driven by low potential to address high-priority questions in planetary science; immature technology; or both. To address this question, we survey high-priority planetary science questions that are uniquely well-suited to distributed instruments. We identify four areas of research where distributed instruments hold promise to unlock answers that are largely inaccessible to monolithic sensors, namely, weather and climate studies of Mars; localization of seismic events on rocky and icy bodies; localization of trace gas emissions, primarily on Mars; and magnetometry studies of internal composition. Next, we survey enabling technologies for distributed sensors and assess their maturity. We identify sensor placement (including descent and landing on planetary surfaces), power, and instrument autonomy as three key areas requiring further investment to enable future distributed instruments. Overall, this work shows that distributed instruments hold great promise for planetary science, and paves the way for follow-on studies of future distributed instruments for Solar System in-situ science.

Long-text generation is seemingly ubiquitous in real-world applications of large language models such as generating an email or writing a review. Despite the fundamental importance and prevalence of long-text generation in many practical applications, existing work on personalized generation has focused on the generation of very short text. To overcome these limitations, we study the problem of personalized long-text generation, that is, generating long-text that is personalized for a specific user while being practically useful for the vast majority of real-world applications that naturally require the generation of longer text. In this work, we demonstrate the importance of user-specific personalization for long-text generation tasks and develop the Long-text Language Model Personalization (LongLaMP) Benchmark. LongLaMP provides a comprehensive and diverse evaluation framework for personalized long-text generation. Extensive experiments on LongLaMP for zero-shot and fine-tuned language tasks demonstrate the effectiveness of the proposed benchmark and its utility for developing and evaluating techniques for personalized long-text generation across a wide variety of long-text generation tasks. The results highlight the importance of personalization across a wide variety of long-text generation tasks. Finally, we release the benchmark for others to use for this important problem.

Gamma-ray bursts are the most energetic known explosions. Despite fading rapidly, they allow to measure redshift and important properties of their host-galaxies. We report the photometric and spectroscopic study of GRB 160203A and its host-galaxy. Fine-structure absorption lines, detected in the afterglow at different epochs, allow us to investigate variability due to the strong fading background source. We obtained two optical to near-infrared spectra of the afterglow with X-shooter on ESO/VLT, 18 min and 5.7 hrs after the burst, allowing us to investigate temporal changes of fine-structure absorption lines. We measured HI column density log N(HI/cm-2)=21.75+/-0.10, and several heavy-element ions along the GRB sight-line in the host-galaxy: SiII,AlII,AlIII,CII,NiII,SiIV,CIV,ZnII,FeII, and FeII and SiII fine structure transitions from energetic levels excited by the afterglow, at a redshift z=3.518. We measured [M/H]TOT=-0.78+/-0.13 and [Zn/Fe]FIT=0.69+/-0.15, representing the total(dust-corrected) metallicity and dust depletion, respectively. We detected additional intervening systems along the line of sight at z=1.03,z=1.26,z=1.98,z=1.99,z=2.20 and z=2.83. We could not measure significant variability in the fine-structure lines throughout all the observations and determined an upper limit for the GRB distance from the absorber of d<300 pc, adopting the canonical UV pumping scenario. However, we note that the quality of our data is not sufficient to conclusively rule out collisions as an alternative mechanism. GRB 160203A belongs to a growing sample of GRBs with medium resolution spectroscopy, provided by the Swift/X-shooter legacy program, which enables detailed investigation of the interstellar medium in high-redshift GRB host-galaxies. In particular, this host galaxy shows relatively high metal enrichment and dust depletion already in place when the universe was only 1.8 Gyr old., Comment: 16 pages, 9 figures, 2 appendices, A&A accepted

Plasmon polaritons are formed by coupling light with delocalized electrons. The half-light and half-matter nature of plasmon polaritons endows them with unparalleled tunability via a range of parameters, such as dielectric environments and carrier density. Therefore, plasmon polaritons are expected to be tuned when in proximity to polar materials since the carrier density is tuned by an electrostatic potential; conversely, the plasmon polariton response might enable the sensing of polarization. Here, we use infrared nano-imaging and nano-photocurrent measurements to investigate heterostructures composed of graphene and twisted hexagonal boron nitride (t-BN), with alternating polarization in a triangular network of moir\'e stacking domains. We observe that the carrier density and the corresponding plasmonic response of graphene are modulated by polar domains in t-BN. In addition, we demonstrate that the nanometer-wide domain walls of graphene moir\'es superlattices, created by the polar domains of t-BN, provide momenta to assist the plasmonic excitations. Furthermore, our studies establish that the plasmon of graphene could function as a delicate sensor for polarization textures. The evolution of polarization textures in t-BN under uniform electric fields is tomographically examined via plasmonic imaging. Strikingly, no noticeable polarization switching is observed under applied electric fields up to 0.23 V/nm, at variance with transport reports. Our nano-images unambiguously reveal that t-BN with triangular domains acts like a ferrielectric, rather than ferroelectric claimed by many previous studies., Comment: 41 pages, 20 figures

Let $(R,\mathfrak{m})$ be a complete local ring, and $G={\rm gr}_{\mathfrak{m}}(R)$ be its associated graded ring. We introduce a homogenization technique which allows to relate $G$ to the special fiber and $R$ to the generic fiber of a "Gr\"obner-like" deformation. Using this technique we prove sharp results concerning the connectedness of $R$ and $G$. We also construct a family of local domains which fail to satisfy Abhyankar's inequality for the Hilbert-Samuel multiplicity. However, we prove a version of the inequality which holds when $R$ is connected in codimension one.

With the number of supernovae observed expected to drastically increase thanks to large-scale surveys like the Dark Energy Spectroscopic Instrument (DESI), it is necessary that the tools we use to classify these objects keep up with this increase. We previously created Supernova Tagging and Classification (STag) to address this problem by employing machine learning techniques alongside logistic regression in order to assign 'tags' to spectra based on spectral features. STag II is a continuation of this work, which now makes use of model supernova spectra combined with real DESI spectra in order to train STag to better deal with realistic data. We also make use of the rlap score as a trustworthiness cut, making for a more robust and accurate supernova classifier than before., Comment: 27 pages, 7 figures. The STag code is available at https://github.com/wdavison909/STag

Long GRB hosts at z<1 are usually low-mass, low metallicity star-forming galaxies. Here we present the until now most detailed, spatially resolved study of the host of GRB 171205A, a grand-design barred spiral galaxy at z=0.036. Our analysis includes MUSE integral field spectroscopy, complemented by high spatial resolution UV/VIS HST imaging and CO(1-0) and HI 21cm data. The GRB is located in a small star-forming region in a spiral arm of the galaxy at a deprojected distance of ~ 8 kpc from the center. The galaxy shows a smooth negative metallicity gradient and the metallicity at the GRB site is half solar, slightly below the mean metallicity at the corresponding distance from the center. Star formation in this galaxy is concentrated in a few HII regions between 5-7 kpc from the center and at the end of the bar, inwards of the GRB region, however, the HII region hosting the GRB is in the top 10% of regions with highest specific star-formation rate. The stellar population at the GRB site has a very young component (< 5 Myr) contributing a significant part of the light. Ionized and molecular gas show only minor deviations at the end of the bar. A parallel study found an asymmetric HI distribution and some additional gas near the position of the GRB, which might explain the star-forming region of the GRB site. Our study shows that long GRBs can occur in many types of star-forming galaxies, however, the actual GRB sites consistently have low metallicity, high star formation and a young population. Furthermore, gas inflow or interactions triggering the star formation producing the GRB progenitor might not be evident in ionized or even molecular gas but only in HI., Comment: 22 pages, 18 figures, Appendix with additional figures, A&A under revision

The control of a mosquito population using the sterile insect technique is considered. Building on a model-based approach, where the control input is the release rate of sterilized males, we propose a non-negative backstepping control law capable of globally stabilizing the extinction equilibrium of the system. A simulation study supports and validates the theoretical findings, showing the efficacy of the approach both on a reduced model, used for control design, and on a complete model of the mosquito population dynamics.

Measuring Deeply Virtual Compton Scattering on the neutron is one of the necessary steps to understand the structure of the nucleon in terms of Generalized Parton Distributions (GPDs). Neutron targets play a complementary role to transversely polarized proton targets in the determination of the GPD $E$. This poorly known and poorly constrained GPD is essential to obtain the contribution of the quarks' angular momentum to the spin of the nucleon. DVCS on the neutron was measured for the first time selecting the exclusive final state by detecting the neutron, using the Jefferson Lab longitudinally polarized electron beam, with energies up to 10.6 GeV, and the CLAS12 detector. The extracted beam-spin asymmetries, combined with DVCS observables measured on the proton, allow a clean quark-flavor separation of the imaginary parts of the GPDs $H$ and $E$., Comment: 7 pages, 6 figures

We present Occamy, a 432-core RISC-V dual-chiplet 2.5D system for efficient sparse linear algebra and stencil computations on FP64 and narrow (32-, 16-, 8-bit) SIMD FP data. Occamy features 48 clusters of RISC-V cores with custom extensions, two 64-bit host cores, and a latency-tolerant multi-chiplet interconnect and memory system with 32 GiB of HBM2E. It achieves leading-edge utilization on stencils (83 %), sparse-dense (42 %), and sparse-sparse (49 %) matrix multiply., Comment: 2 pages, 7 figures. Accepted at the 2024 IEEE Symposium on VLSI Technology & Circuits

Context. The recent detection of nitrogen-enhanced, metal-poor galaxies at high redshift by the James Webb Space Telescope has sparked renewed interest in exploring the chemical evolution of carbon, nitrogen, and oxygen (the CNO elements) at early times, prompting fresh inquiries into their origins. Aims. The main goal of this paper is to shed light onto the early evolution of the main CNO isotopes in our Galaxy and in young distant systems, such as GN-z11 at z=10.6. Methods. To this aim, we incorporate a stochastic star-formation component into a chemical evolution model calibrated with high-quality Milky Way (MW) data, focusing on the contribution of Population III (Pop III) stars to the early chemical enrichment. Results. By comparing the model predictions with CNO abundance measurements from high-resolution spectroscopy of an homogeneous sample of Galactic halo stars, we first demonstrate that the scatter observed in the metallicity range -4.5 < [Fe/H] <-1.5 can be explained by pre-enrichment from Pop III stars that explode as supernovae (SNe) with different initial masses and energies. Then, by exploiting the chemical evolution model, we provide testable predictions for log(C/N), log(N/O), and log(C/O) vs. log(O/H)+12 in MW-like galaxies observed at different cosmic epochs/redshifts. Finally, by calibrating the chemical evolution model to replicate the observed properties of GN-z11, we provide an alternative interpretation of its log(N/O) abundance ratio, demonstrating that its high N content can be reproduced through enrichment from high-mass faint Pop III SNe. Conclusions. Stochastic chemical enrichment from primordial stars explains both the observed scatter in CNO abundances in MW halo stars and the exceptionally high N/O ratios in some distant galaxies. These findings emphasize the critical role of Pop III stars in shaping early chemical evolution.

Hypervelocity stars (HVSs) are stars which have been ejected from the Galactic Centre (GC) at velocities of up to a few thousand km/s. They are tracers of the Galactic potential and can be used to infer properties of the GC, such as the initial-mass function and assembly history. HVSs are rare, however, with only about a dozen promising candidates discovered so far. In this work we make use of a novel, highly efficient method to identify new HVS candidates in Gaia. This method uses the nearly radial trajectories of HVSs to infer their distances and velocities based on their position and Gaia proper motion alone. Through comparison of inferred distances with Gaia parallaxes and photometry we identified 600 HVS candidates with G<20 including the previously discovered S5-HVS1, out of which we obtained ground-based follow-up observations for 196 stars. As we found no new HVSs based on their radial velocity, we used detailed HVS ejection simulations to significantly improve previous HVS ejection rate constraints. In particular, the ejection rate of HVSs more massive than 1 $\mathrm{M_\odot}$ cannot be higher than $10^{-5}$ yr$^{-1}$ at $2\sigma$ significance. Additionally, we predict that there are 5-45 unbound HVSs in the complete Gaia catalogue ($1\sigma$ interval), most of which will be main-sequence stars of a few M$_\odot$ at heliocentric distances of tens to hundreds of kpc. By comparing our results to literature HVS candidates, we find an indication of either a time-dependent ejection rate of HVSs or a non-GC origin of previously identified HVS candidates., Comment: 17 pages, 16 figures, accepted for publication in MNRAS

Lead halide perovskite nanocrystals (LHP-NCs) embedded in polymeric hosts are gaining attention as scalable and low-cost scintillation detectors for technologically relevant applications. Despite rapid progress, little is currently known about the scintillation properties and stability of LHP-NCs prepared by the ligand assisted reprecipitation (LARP) method, which allows mass scalability at room temperature unmatched by any other type of nanostructure, and the implications of incorporating LHP-NCs into polyacrylate hosts are still largely debated. Here, we show that LARP-synthesized CsPbBr3 NCs are comparable to particles from hot-injection routes and unravel the dual effect of polyacrylate incorporation, where the partial degradation of LHP-NCs luminescence is counterbalanced by the passivation of electron-poor defects by the host acrylic groups. Experiments on NCs with tailored surface defects show that the balance between such antithetical effects of polymer embedding is determined by the surface defect density of the NCs and provide guidelines for further material optimization.

The elusive properties of the first (Pop III) stars can be indirectly unveiled by uncovering their true descendants. To this aim, we exploit our data-calibrated model for the best-studied ultra-faint dwarf (UFD) galaxy, Bo\"otes I, which tracks the chemical evolution (from carbon to zinc) of individual stars from their formation to the present day. We explore the chemical imprint of Pop III supernovae (SNe), with different explosion energies and masses, showing that they leave distinct chemical signatures in their descendants. We find that UFDs are strongly affected by SNe-driven feedback resulting in a very low fraction of metals retained by their gravitational potential well (< 2.5 %). Furthermore, the higher the Pop III SN explosion energy, the lower the fraction of metals retained. Thus, the probability to find descendants of energetic Pair Instability SNe is extremely low in these systems. Conversely, UFDs are ideal cosmic laboratories to identify the fingerprints of less massive and energetic Pop III SNe through their [X/Fe] abundance ratios. Digging into the literature data of Bo\"otes I, we uncover three hidden Pop III descendants: one mono-enriched and two multi-enriched. These stars show the chemical signature of Pop III SNe in the mass range $[20-60]\rm M_{\odot}$, spanning a wide range in explosion energies $[0.3-5] 10^{51}$ erg. In conclusion, Pop III descendants are hidden in ancient UFDs but those mono-enriched by a single Pop III SN are extremely rare. Thus, self-consistent models such as the one presented here are required to uncover these precious fossils and probe the properties of the first Pop III supernovae., Comment: Submitted to ApJ

Generalised contextuality is the notion of nonclassicality powering up a myriad of quantum tasks, among which is the celebrated case of a two-party information processing task where classical information is compressed in a quantum channel, the parity-oblivious multiplexing (POM) task. The success rate is the standard quantifier of resourcefulness for this task, while robustness-based quantifiers are as operationally motivated and have known general properties. In this work, we leverage analytical and numerical tools to estimate robustness of contextuality in POM scenarios under different types of noise. We conclude that for the 3-to-1 case robustness of contextuality to depolarisation, as well as a minimisation of robustness of contextuality to dephasing over all bases, are good quantifiers for the nonclassical advantage of this scenario. Moreover, we obtain a general relation between robustness of contextuality to depolarisation and the success rate in any $n$-to-1 POM scenario and show how it can be used to bound the number of bits encoded in this task., Comment: 11 pages, 7 figures. Comments are welcome

The rapid advancement and exploration of open-hardware RISC-V platforms are driving significant changes in sectors like autonomous vehicles, smart-city infrastructure, and medical devices. OpenTitan stands out as a groundbreaking open-source RISC-V design with a comprehensive security toolkit as a standalone system-on-chip (SoC). OpenTitan includes Earl Grey, a fully implemented and silicon-proven SoC, and Darjeeling, announced but not yet fully implemented. Earl Grey targets standalone SoC implementations, while Darjeeling is for integrable implementations. The literature lacks a silicon-ready embedded implementation of an open-source Root of Trust, despite lowRISC's efforts on Darjeeling. We address the limitations of existing implementations by optimizing data transfer latency between memory and cryptographic accelerators to prevent under-utilization and ensure efficient task acceleration. Our contributions include a comprehensive methodology for integrating custom extensions and IPs into the Earl Grey architecture, architectural enhancements for system-level integration, support for varied boot modes, and improved data movement across the platform. These advancements facilitate deploying OpenTitan in broader SoCs, even without specific technology-dependent IPs, providing a deployment-ready research vehicle for the community. We integrated the extended Earl Grey architecture into a reference architecture in a 22nm FDX technology node, benchmarking the enhanced architecture's performance. The results show significant improvements in cryptographic processing speed, achieving up to 2.7x speedup for SHA-256/HMAC and 1.6x for AES accelerators compared to the baseline Earl Grey architecture.

Multi-relational temporal graphs are powerful tools for modeling real-world data, capturing the evolving and interconnected nature of entities over time. Recently, many novel models are proposed for ML on such graphs intensifying the need for robust evaluation and standardized benchmark datasets. However, the availability of such resources remains scarce and evaluation faces added complexity due to reproducibility issues in experimental protocols. To address these challenges, we introduce Temporal Graph Benchmark 2.0 (TGB 2.0), a novel benchmarking framework tailored for evaluating methods for predicting future links on Temporal Knowledge Graphs and Temporal Heterogeneous Graphs with a focus on large-scale datasets, extending the Temporal Graph Benchmark. TGB 2.0 facilitates comprehensive evaluations by presenting eight novel datasets spanning five domains with up to 53 million edges. TGB 2.0 datasets are significantly larger than existing datasets in terms of number of nodes, edges, or timestamps. In addition, TGB 2.0 provides a reproducible and realistic evaluation pipeline for multi-relational temporal graphs. Through extensive experimentation, we observe that 1) leveraging edge-type information is crucial to obtain high performance, 2) simple heuristic baselines are often competitive with more complex methods, 3) most methods fail to run on our largest datasets, highlighting the need for research on more scalable methods., Comment: 29 pages, 8 figures, 11 tables, accepted at NeurIPS 2024 Track on Datasets and Benchmarks

The Dark Energy Spectroscopic Instrument Milky Way Survey (DESI MWS) will explore the assembly history of the Milky Way by characterising remnants of ancient dwarf galaxy accretion events and improving constraints on the distribution of dark matter in the outer halo. We present mock catalogues that reproduce the selection criteria of MWS and the format of the final MWS data set. These catalogues can be used to test methods for quantifying the properties of stellar halo substructure and reconstructing the Milky Way's accretion history with the MWS data, including the effects of halo-to-halo variance. The mock catalogues are based on a phase-space kernel expansion technique applied to star particles in the Auriga suite of six high-resolution $\Lambda$CDM magneto-hydrodynamic zoom-in simulations. They include photometric properties (and associated errors) used in DESI target selection and the outputs of the MWS spectral analysis pipeline (radial velocity, metallicity, surface gravity, and temperature). They also include information from the underlying simulation, such as the total gravitational potential and information on the progenitors of accreted halo stars. We discuss how the subset of halo stars observable by MWS in these simulations corresponds to their true content and properties. These mock Milky Ways have rich accretion histories, resulting in a large number of substructures that span the whole stellar halo out to large distances and have substantial overlap in the space of orbital energy and angular momentum., Comment: Accepted for publication in MNRAS, 31 pages, 27 figues, 7 tables. The mock catalogues are available at https://data.desi.lbl.gov/public/papers/mws/auridesi/v1

This Roadmap provides an overview of the critical role of materials in exploiting spin and topology for next-generation quantum technologies including computing, sensing, information storage and networking devices. We explore the key materials systems that support spin and topological phenomena and discuss their figures of merit. Spin and topology-based quantum technologies have several advantages over their classical, charged-based counterparts, including non-volatility, faster data processing speeds, higher integration densities and lower power consumption. We discuss the main challenges facing the field, identify strategies to overcome them, and provide a realistic outlook on future possibilities of spin-based and topological materials in quantum technology applications., Comment: Roadmap of the UKRI EPSRC Materials for Quantum Network (M4QN) Spin & Topology group. 25 pages, 5 figures, includes supplement. Comments welcome!

We propose a novel technique for guidance of buoyancy-controlled vehicles in uncertain under-ice ocean flows. In-situ melt rate measurements collected at the grounding zone of Antarctic ice shelves, where the ice shelf meets the underlying bedrock, are essential to constrain models of future sea level rise. Buoyancy-controlled vehicles, which control their vertical position in the water column through internal actuation but have no means of horizontal propulsion, offer an affordable and reliable platform for such in-situ data collection. However, reaching the grounding zone requires vehicles to traverse tens of kilometers under the ice shelf, with approximate position knowledge and no means of communication, in highly variable and uncertain ocean currents. To address this challenge, we propose a partially observable MDP approach that exploits model-based knowledge of the under-ice currents and, critically, of their uncertainty, to synthesize effective guidance policies. The approach uses approximate dynamic programming to model uncertainty in the currents, and QMDP to address localization uncertainty. Numerical experiments show that the policy can deliver up to 88.8% of underwater vehicles to the grounding zone -- a 33% improvement compared to state-of-the-art guidance techniques, and a 262% improvement over uncontrolled drifters. Collectively, these results show that model-based under-ice guidance is a highly promising technique for exploration of under-ice cavities, and has the potential to enable cost-effective and scalable access to these challenging and rarely observed environments., Comment: Presented at IROS 2021

The ongoing revolution in application domains targeting autonomous navigation, first and foremost automotive "zonalization", has increased the importance of certain off-chip communication interfaces, particularly Ethernet. The latter will play an essential role in next-generation vehicle architectures as the backbone connecting simultaneously and instantaneously the zonal/domain controllers. There is thereby an incumbent need to introduce a performant Ethernet controller in the open-source HW community, to be used as a proxy for architectural explorations and prototyping of mixed-criticality systems (MCSs). Driven by this trend, in this work, we propose a fully open-source, DMA-enhanced, technology-agnostic Gigabit Ethernet architecture that overcomes the limitations of existing open-source architectures, such as Lowrisc's Ethernet, often tied to FPGA implementation, performance-bound by sub-optimal design choices such as large memory buffers, and in general not mature enough to bridge the gap between academia and industry. Besides the area advantage, the proposed design increases packet transmission speed up to almost 3x compared to Lowrisc's and is validated through implementation and FPGA prototyping into two open-source, heterogeneous MCSs., Comment: 4 pages,4 figures, 21st ACM International Conference on Computing Frontiers Workshops and Special Sessions

When measuring the Baryon Acoustic Oscillations (BAO) scale from galaxy surveys, one typically assumes a fiducial cosmology when converting redshift measurements into comoving distances and also when defining input parameters for the reconstruction algorithm. A parameterised template for the model to be fitted is also created based on a (possibly different) fiducial cosmology. This model reliance can be considered a form of data compression, and the data is then analysed allowing that the true answer is different from the fiducial cosmology assumed. In this study, we evaluate the impact of the fiducial cosmology assumed in the BAO analysis of the Dark Energy Spectroscopic Instrument (DESI) survey Data Release 1 (DR1) on the final measurements in DESI 2024 III. We utilise a suite of mock galaxy catalogues with survey realism that mirrors the DESI DR1 tracers: the bright galaxy sample (BGS), the luminous red galaxies (LRG), the emission line galaxies (ELG) and the quasars (QSO), spanning a redshift range from 0.1 to 2.1. We compare the four secondary AbacusSummit cosmologies against DESI's fiducial cosmology (Planck 2018). The secondary cosmologies explored include a lower cold dark matter density, a thawing dark energy universe, a higher number of effective species, and a lower amplitude of matter clustering. The mocks are processed through the BAO pipeline by consistently iterating the grid, template, and reconstruction reference cosmologies. We determine a conservative systematic contribution to the error of $0.1\%$ for both the isotropic and anisotropic dilation parameters $\alpha_{\rm iso}$ and $\alpha_{\rm AP}$. We then directly test the impact of the fiducial cosmology on DESI DR1 data., Comment: Supporting publication of DESI 2024 III: Baryon Acoustic Oscillations from Galaxies and Quasars

Large Generative Models (LGMs) such as GPT, Stable Diffusion, Sora, and Suno are trained on a huge amount of language corpus, images, videos, and audio that are extremely diverse from numerous domains. This training paradigm over diverse well-curated data lies at the heart of generating creative and sensible content. However, all previous graph generative models (e.g., GraphRNN, MDVAE, MoFlow, GDSS, and DiGress) have been trained only on one dataset each time, which cannot replicate the revolutionary success achieved by LGMs in other fields. To remedy this crucial gap, we propose a new class of graph generative model called Large Graph Generative Model (LGGM) that is trained on a large corpus of graphs (over 5000 graphs) from 13 different domains. We empirically demonstrate that the pre-trained LGGM has superior zero-shot generative capability to existing graph generative models. Furthermore, our pre-trained LGGM can be easily fine-tuned with graphs from target domains and demonstrate even better performance than those directly trained from scratch, behaving as a solid starting point for real-world customization. Inspired by Stable Diffusion, we further equip LGGM with the capability to generate graphs given text prompts (Text-to-Graph), such as the description of the network name and domain (i.e., "The power-1138-bus graph represents a network of buses in a power distribution system."), and network statistics (i.e., "The graph has a low average degree, suitable for modeling social media interactions."). This Text-to-Graph capability integrates the extensive world knowledge in the underlying language model, offering users fine-grained control of the generated graphs. We release the code, the model checkpoint, and the datasets at https://lggm-lg.github.io/.

We present a method to mitigate the effects of fiber assignment incompleteness in two-point power spectrum and correlation function measurements from galaxy spectroscopic surveys, by truncating small angular scales from estimators. We derive the corresponding modified correlation function and power spectrum windows to account for the small angular scale truncation in the theory prediction. We validate this approach on simulations reproducing the Dark Energy Spectroscopic Instrument (DESI) Data Release 1 (DR1) with and without fiber assignment. We show that we recover unbiased cosmological constraints using small angular scale truncated estimators from simulations with fiber assignment incompleteness, with respect to standard estimators from complete simulations. Additionally, we present an approach to remove the sensitivity of the fits to high $k$ modes in the theoretical power spectrum, by applying a transformation to the data vector and window matrix. We find that our method efficiently mitigates the effect of fiber assignment incompleteness in two-point correlation function and power spectrum measurements, at low computational cost and with little statistical loss., Comment: 36 pages, 23 figures, typos corrected, clarifications added

Atomically thin materials offer multiple opportunities for layer-by-layer control of their electronic properties. While monolayer graphene (MLG) is a zero-gap system, Bernal-stacked bilayer graphene (BLG) acquires a finite band gap when the symmetry between the layers' potential energy is broken, usually, via a large electric field applied in double-gate devices. Here, we introduce an asymmetric twistronic stack comprising both MLG and BLG, synthesized via low-pressure chemical vapor deposition (LP-CVD) on Cu. Although a large ($\sim30^{\circ}$) twist angle decouples the MLG and BLG electronic bands near Fermi level, we find that the layer degeneracy in the BLG subsystem is lifted, producing a gap in the absence of external fields. The built-in interlayer asymmetry originates from proximity-induced energy shifts in the outermost layers and requires a displacement field of $0.14$ V/nm to be compensated. The latter corresponds to a $\sim10$ meV intrinsic BLG gap, a value confirmed by our thermal-activation measurements. The present results highlight the role of structural asymmetry and encapsulating environment, expanding the engineering toolbox for monolithically-grown graphene multilayers., Comment: 23 pages, 4 figures and supporting information

By leveraging the Variational Quantum Eigensolver (VQE), the ``quantum equation of motion" (qEOM) method established itself as a promising tool for quantum chemistry on near term quantum computers, and has been used extensively to estimate molecular excited states. Here, we explore a novel application of this method, employing it to compute thermal averages of quantum systems, specifically molecules like ethylene and butadiene. A drawback of qEOM is that it requires measuring the expectation values of a large number of observables on the ground state of the system, and the number of necessary measurements can become a bottleneck of the method. In this work we focus on measurements through informationally complete positive operator-valued measures (IC-POVMs) to achieve a reduction in the measurements overheads. We show with numerical simulations that the qEOM combined with IC-POVM measurements ensures a satisfactory accuracy in the reconstruction of the thermal state with a reasonable number of shots., Comment: 7 pages, 9 figures

Hyperspectral image segmentation is crucial for many fields such as agriculture, remote sensing, biomedical imaging, battlefield sensing and astronomy. However, the challenge of hyper and multi spectral imaging is its large data footprint. We propose both a novel camera design and a vision transformer-based (ViT) algorithm that alleviate both the captured data footprint and the computational load for hyperspectral segmentation. Our camera is able to adaptively sample image regions or patches at different resolutions, instead of capturing the entire hyperspectral cube at one high resolution. Our segmentation algorithm works in concert with the camera, applying ViT-based segmentation only to adaptively selected patches. We show results both in simulation and on a real hardware platform demonstrating both accurate segmentation results and reduced computational burden.

We propose an innovative statistical method, called Ordinal Mixed-Effect Random Forest (OMERF), that extends the use of random forest to the analysis of hierarchical data and ordinal responses. The model preserves the flexibility and ability of modeling complex patterns of both categorical and continuous variables, typical of tree-based ensemble methods, and, at the same time, takes into account the structure of hierarchical data, modeling the dependence structure induced by the grouping and allowing statistical inference at all data levels. A simulation study is conducted to validate the performance of the proposed method and to compare it to the one of other state-of-the art models. The application of OMERF is exemplified in a case study focusing on predicting students performances using data from the Programme for International Student Assessment (PISA) 2022. The model identifies discriminating student characteristics and estimates the school-effect.

A zero-magnetic-field Josephson diode effect (JDE) is observed in an asymmetric superconducting quantum interference device (SQUID) mediated by Dirac semimetal Cd3As2. We argue that a phase coupling between the surface and bulk superconducting channels, a unique phenomenon recently identified in the observations of fractional Josephson effect and Leggett modes in Cd3As2, can break time reversal symmetry and therefore give rise to the zero-field JDE. Our results are anticipated to have important implications in superconducting electronic circuit applications.

Partially Observable Markov Decision Processes (POMDPs) are powerful models for sequential decision making under transition and observation uncertainties. This paper studies the challenging yet important problem in POMDPs known as the (indefinite-horizon) Maximal Reachability Probability Problem (MRPP), where the goal is to maximize the probability of reaching some target states. This is also a core problem in model checking with logical specifications and is naturally undiscounted (discount factor is one). Inspired by the success of point-based methods developed for discounted problems, we study their extensions to MRPP. Specifically, we focus on trial-based heuristic search value iteration techniques and present a novel algorithm that leverages the strengths of these techniques for efficient exploration of the belief space (informed search via value bounds) while addressing their drawbacks in handling loops for indefinite-horizon problems. The algorithm produces policies with two-sided bounds on optimal reachability probabilities. We prove convergence to an optimal policy from below under certain conditions. Experimental evaluations on a suite of benchmarks show that our algorithm outperforms existing methods in almost all cases in both probability guarantees and computation time., Comment: Accepted to the Conference on Uncertainty in Artificial Intelligence (UAI) 2024

What can we learn from the classics of Finnish literature by using computational emotion analysis? This article tries to answer this question by examining how computational methods of sentiment analysis can be used in the study of literary works in conjunction with a qualitative or more 'traditional' approach to literature and affect. We present and develop a simple but robust computational approach of affect analysis that uses a carefully curated emotion lexicon adapted to Finnish turn-of-the-century literary texts combined with word embeddings to map out the semantic emotional spaces of seminal works of Finnish literature. We focus our qualitative analysis on selected case studies: four works by Juhani Aho, Minna Canth, Maria Jotuni, and F. E. Sillanp\"a\"a, but provide emotion arcs for a total of 975 Finnish novels. We argue that a computational analysis of a text's lexicon can be valuable in evaluating the large distribution of the emotional valence in a text and provide guidelines to help other researchers replicate our findings. We show that computational approaches have a place in traditional studies on affect in literature as a support tool for close-reading-based analyses, but also allowing for large-scale comparison between, for example, genres or national canons., Comment: Accepted in Scandinavian Studies Journal, issue 97.3 (2025)

We measure the clustering of Lyman Alpha Emitting galaxies (LAEs) selected from the One-hundred-square-degree DECam Imaging in Narrowbands (ODIN) survey, with spectroscopic follow-up from Dark Energy Spectroscopic Instrument (DESI). We use DESI spectroscopy to optimize our selection and to constrain the interloper fraction and redshift distribution of our narrow-band selected sources. We select samples of 4000 LAEs at z=2.45 and 3.1 in 9 sq.deg. centered on the COSMOS field with median LyA fluxes of 10^{-16}erg/s/cm2. Covariances and cosmological inferences are obtained from a series of mock catalogs built upon high-resolution N-body simulations that match the footprint, number density, redshift distribution and observed clustering of the sample. We find that both samples have a correlation length of r_0=(3.0\pm 0.2)Mpc/h. Within our fiducial cosmology these correspond to 3D number densities of 10^{-3} h^3/Mpc^3 and, from our mock catalogs, biases of 1.7 and 2.0 at z=2.45 and 3.1, respectively. We discuss the implications of these measurements for the use of LAEs as large-scale structure tracers for high-redshift cosmology., Comment: 26 pages, 13 figures; minor revisions to match version accepted by JCAP