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TOI-396 is an F6V star ($V\approx6.4$) orbited by three transiting planets. The orbital periods of the two innermost planets are close to the 5:3 commensurability ($P_b \sim3.6$ d and $P_c \sim6.0$ d). To measure the masses of the three planets, refine their radii, and investigate whether planets b and c are in MMR, we carried out HARPS RV observations and retrieved photometric data from TESS. We extracted the RVs via a skew-normal fit onto the HARPS CCFs and performed an MCMC joint analysis of the Doppler measurements and transit photometry, while employing the breakpoint method to remove stellar activity from the RV time series. We also performed a thorough TTV dynamical analysis of the system. Our analysis confirms that the three planets have similar sizes: $R_b=2.004_{-0.047}^{+0.045}R_{\oplus}$; $R_c=1.979_{-0.051}^{+0.054}R_{\oplus}$; $R_d=2.001_{-0.064}^{+0.063}R_{\oplus}$. For the first time, we determine RV masses for TOI-396b and d: $M_b=3.55_{-0.96}^{+0.94}M_{\oplus}$ ($\rho_b=2.44_{-0.68}^{+0.69}$ g cm$^{-3}$) and $M_d=7.1\pm1.6M_{\oplus}$ ($\rho_d=4.9_{-1.1}^{+1.2}$ g cm$^{-3}$). Our results suggest a quite unusual system architecture, with the outermost planet being the densest. The Doppler reflex motion induced by TOI-396c remains undetected in our RV time series, likely due to the proximity of $P_c$ to the star's rotation period ($P_{\mathrm{rot}}=6.7\pm1.3$ d). We also discovered that TOI-396b and c display significant TTVs. While the TTV dynamical analysis returns a formally precise mass for TOI-396c ($M_{c,\mathrm{dyn}}=2.24^{+0.13}_{-0.67}M_{\oplus}$), the result might not be accurate owing to the poor sampling of the TTV phase. We also conclude that TOI-396b and c are close to-, but out of- the 5:3 MMR. Our numerical simulation suggests TTV semi-amplitudes of up to 5 hours over a temporal baseline of $\sim$5.2 years., Comment: 24 pages (6 in the Appendix), 15 Figures (2 in the Appendix), 10 Tables (5 in the Appendix). Accepted for publication in A&A

Mass spectrometry (MS) is essential for proteomics and metabolomics but faces impending challenges in efficiently processing the vast volumes of data. This paper introduces SpecPCM, an in-memory computing (IMC) accelerator designed to achieve substantial improvements in energy and delay efficiency for both MS spectral clustering and database (DB) search. SpecPCM employs analog processing with low-voltage swing and utilizes recently introduced phase change memory (PCM) devices based on superlattice materials, optimized for low-voltage and low-power programming. Our approach integrates contributions across multiple levels: application, algorithm, circuit, device, and instruction sets. We leverage a robust hyperdimensional computing (HD) algorithm with a novel dimension-packing method and develop specialized hardware for the end-to-end MS pipeline to overcome the non-ideal behavior of PCM devices. We further optimize multi-level PCM devices for different tasks by using different materials. We also perform a comprehensive design exploration to improve energy and delay efficiency while maintaining accuracy, exploring various combinations of hardware and software parameters controlled by the instruction set architecture (ISA). SpecPCM, with up to three bits per cell, achieves speedups of up to 82x and 143x for MS clustering and DB search tasks, respectively, along with a four-orders-of-magnitude improvement in energy efficiency compared with state-of-the-art CPU/GPU tools.

We study the wear rate (mass loss per unit sliding distance) of a tire tread rubber compound sliding on concrete paver surfaces under dry and wet conditions, at different nominal contact pressures of $\sigma_0 = 0.12$, $0.29$, and $0.43 \ {\rm MPa}$, and sliding velocities ranging from $v= 1 \ {\rm \mu m/s}$ to $1 \ {\rm cm/s}$. We find that the wear rate is proportional to the normal force and remains independent of the sliding speed. Sliding in water and soapy water results in significantly lower wear rates compared to dry conditions. The experimental data are analyzed using a theory that predicts wear rates and wear particle size distributions consistent with the experimental observations.

The rich diversity of multi-planetary systems and their architectures is greatly contrasted by the uniformity exhibited within many of these systems. Previous studies have shown that compact Kepler systems tend to exhibit a peas-in-a-pod architecture: Planets in the same system tend to have similar sizes and masses and be regularly spaced in orbits with low eccentricities and mutual inclinations. This work extends on previous research and examines a larger and more diverse sample comprising all the systems with a minimum of three confirmed planets, resulting in 282 systems and 991 planets. We investigated the system architectures, focusing on the orbital spacings between adjacent planets as well as their relationships with the planets' sizes and masses. We also quantified the similarities of the sizes, masses, and spacings of planets within each system, conducting both intra- and inter-system analyses. Our results corroborate previous research showing that planets orbiting the same star tend to be regularly spaced and that pairs of adjacent planets with radii<1 R_Earth predominantly have orbital period ratios (PRs)<2. In contrast to other studies, we identified a significant similarity of adjacent orbital spacings not only at PRs<4 but also at 1.17

We analyze data from multiple flybys by the Solar Orbiter, BepiColombo, and Parker Solar Probe (PSP) missions to study the interaction between Venus' plasma environment and the solar wind forming the induced magnetosphere. Through examination of magnetic field and plasma density signatures we characterize the spatial extent and dynamics of Venus' magnetotail, focusing mainly on boundary crossings. Notably, we observe significant differences in boundary crossing location and appearance between flybys, highlighting the dynamic nature of Venus' magnetotail. In particular, during Solar Orbiter's third flyby, extreme solar wind conditions led to significant variations in the magnetosheath plasma density and magnetic field properties, but the increased dynamic pressure did not compress the magnetotail. Instead, it is possible that the increased EUV flux at this time rather caused it to expand in size. Key findings also include the identification of several far downstream bow shock (BS), or bow wave, crossings to at least 60 Rv (1 Rv = 6,052 km is the radius of Venus), and the induced magnetospheric boundary to at least 20 Rv. These crossings provide insight into the extent of the induced magnetosphere. Pre-existing models from Venus Express were only constrained to within ~5 Rv of the planet, and we provide modifications to better fit the far-downstream crossings. The new model BS is now significantly closer to the central tail than previously suggested, by about 10 Rv at 60 Rv downstream.

We consider the projected normal distribution, with isotropic variance, on the 2-sphere using intrinsic statistics. We show that in this case, the expectation commutes with the projection and that the covariance of the normal variable has a 1-1 correspondence with the intrinsic covariance of the projected normal distribution. This allows to estimate, after model identification, the parameters of the underlying normal distribution that generates the data.

Navigating complex environments requires Unmanned Aerial Vehicles (UAVs) and autonomous systems to perform trajectory tracking and obstacle avoidance in real-time. While many control strategies have effectively utilized linear approximations, addressing the non-linear dynamics of UAV, especially in obstacle-dense environments, remains a key challenge that requires further research. This paper introduces a Non-linear Model Predictive Control (NMPC) framework for the DJI Matrice 100, addressing these challenges by using a dynamic model and B-spline interpolation for smooth reference trajectories, ensuring minimal deviation while respecting safety constraints. The framework supports various trajectory types and employs a penalty-based cost function for control accuracy in tight maneuvers. The framework utilizes CasADi for efficient real-time optimization, enabling the UAV to maintain robust operation even under tight computational constraints. Simulation and real-world indoor and outdoor experiments demonstrated the NMPC ability to adapt to disturbances, resulting in smooth, collision-free navigation., Comment: This manuscript has 7 pages and 8 figures, detailing NMPC for UAV obstacle avoidance using DJI UAVs. It features simulations, experimental results, and uses CasADi for optimization with ROS integration. Code and media at https://github.com/larasupernovae/nmpc_flash_multi_obstacle

We report on the discovery and spectroscopic confirmation of TOI-2458 b, a transiting mini-Neptune around an F-type star leaving the main-sequence with a mass of $M_\star=1.05 \pm 0.03$ M$_{\odot}$, a radius of $R_\star=1.31 \pm 0.03$ R$_{\odot}$, an effective temperature of $T_{\rm eff}=6005\pm50$ K, and a metallicity of $-0.10\pm0.05$ dex. By combining TESS photometry with high-resolution spectra acquired with the HARPS spectrograph, we found that the transiting planet has an orbital period of $\sim$3.74 days, a mass of $M_p=13.31\pm0.99$ M$_{\oplus}$ and a radius of $R_p=2.83\pm0.20$ R$_{\oplus}$. The host star TOI-2458 shows a short activity cycle of $\sim$54 days revealed in the HARPS S-index and H$\alpha$ times series. We took the opportunity to investigate other F stars showing activity cycle periods comparable to that of TOI-2458 and found that they have shorter rotation periods than would be expected based on the gyrochronology predictions. In addition, we determined TOI-2458's stellar inclination angle to be $i_\star\,=\,10.6_{-10.6}^{+13.3}$ degrees. We discuss that both phenomena (fast stellar rotation and planet orbit inclination) could be explained by in situ formation of a hot Jupiter interior to TOI-2458 b. It is plausible that this hot Jupiter was recently engulfed by the star. Analysis of HARPS spectra has identified the presence of another planet with a period of $P\,=\,16.55\pm0.06$ days and a minimum mass of $M_p \sin i=10.22\pm1.90$ M$_{\oplus}$. Using dynamical stability analysis, we constrained the mass of this planet to the range $M_{c} \simeq (10, 25)$ M$_{\oplus}$., Comment: 25 pages, 20 figures, accepted for publication in Astronomy & Astrophysics

Advances in lithium-metal anodes have inspired interest in discovery of Li-free cathodes, most of which are natively found in their charged state. This is in contrast to today's commercial lithium-ion battery cathodes, which are more stable in their discharged state. In this study, we combine calculated cathode voltage information from both categories of cathode materials, covering 5577 and 2423 total unique structure pairs, respectively. The resulting voltage distributions with respect to the redox pairs and anion types for both classes of compounds emphasize design principles for high-voltage cathodes, which favor later Period 4 transition metals in their higher oxidation states and more electronegative anions like fluorine or polyaion groups. Generally, cathodes that are found in their charged, delithiated state are shown to exhibit voltages lower than those that are most stable in their lithiated state, in agreement with thermodynamic expectations. Deviations from this trend are found to originate from different anion distributions between redox pairs. In addition, a machine learning model for voltage prediction based on chemical formulae is constructed, and shows state-of-the-art performance when compared to two established composition-based ML models for materials properties predictions, Roost and CrabNet.

I study the influence of temperature and the crack-tip velocity of the bond breaking at the crack tip in rubber-like materials. The bond breaking is considered as a stress-aided thermally activated process and result in an effective crack propagation energy which increases strongly with decreasing temperature or increasing crack-tip speed. This effect is particular important for adhesive (interfacial) crack propagation but less important for cohesive crack propagation owing to the much larger bond-breaking energies in the latter case. For adhesive cracks the theory results are consistent with adhesion measurements for silicone (PDMS) rubber in contact with silica glass surfaces. For cohesive cracks the theory agree well with experimental results PDMS films chemically bound to silinized glass.

Background: Open Source Software (OSS) is often seen as an option to mitigate risks of lock-ins. Yet, single-vendor OSS can still result in soft lock-ins due to knowledge asymmetries and technical barriers. Aim: This study explores actors that render such soft lock-ins. Research design: We conduct a qualitative case study of an E-service Platform (ESP) used by over 190+ municipalities. Results: User-driven lock-in factors emerged as a significant category, including limited and non-transparent communication, restrictive qualification requirements in procurement, confusion on maintainership, and comfort in the status quo. Technical lock-in factors include inadequate documentation, dependency management issues, and limited test coverage. Conclusions: Strong leadership and continuous training is needed to address presence of comfort and conservative culture among municipalities. Open Source Stewards, i.e., neutral hosts for OSS projects, can support municipalities in these tasks while also helping to foster an open, competitive collaboration that can enable a broader supplier ecosystem., Comment: Accepted for publication at the 57th Hawaii International Conference on System Sciences 2024 (HICSS-57)

We point out an inconsistency in the theoretical treatment of Bosetti and collaborators (Crystal Growth & Design, 2021, 22.1: 87-97), and then proceed to prove that for monomers interacting by two-body potentials, the presence of an infinite, flat, attractive crystal surface may not induce an increased propensity for cluster formation (that is, secondary nucleation) of the type envisioned by these authors., Comment: 6 typeset pages (achemso class), 1 double-panel figure, rejected by Crystal Growth \& Design

Measurements of the obliquities in exoplanet systems have revealed some remarkable architectures, some of which are very different from the Solar System. Nearly 200 obliquity measurements have been obtained through observations of the Rossiter-McLaughlin (RM) effect. Here we report on observations of 19 planetary systems that led to 17 clear detections of the RM effect and 2 less secure detections. After adding the new measurements to the tally, we use the entire collection of RM measurements to investigate four issues that have arisen in the literature. i) Does the obliquity distribution show a peak at approximately 90$^\circ$? We find tentative evidence that such a peak does exist when restricting attention to the sample of sub-Saturn planets and hot Jupiters orbiting F stars. ii) Are high obliquities associated with high eccentricities? We find the association to be weaker than previously reported, and that a stronger association exists between obliquity and orbital separation, possibly due to tidal obliquity damping at small separations. iii) How low are the lowest known obliquities? Among hot Jupiters around cool stars, we find the dispersion to be $1.4\pm0.7^\circ$, smaller than the 6$^\circ$ obliquity of the Sun, which serves as additional evidence for tidal damping. iv) What are the obliquities of stars with compact and flat systems of multiple planets? We find that they generally have obliquities lower than $10^\circ$, with several remarkable exceptions possibly caused by wide-orbiting stellar or planetary companions., Comment: 47 pages, 43 figures. Accepted for publication in A&A

Integrated population models (IPMs) are a promising approach to test ecological theories and assess wildlife populations in dynamic and uncertain conditions. By combining multiple data sources into a single, unified model, they enable the parametrization of versatile, mechanistic models that can predict population dynamics in novel circumstances. Here, we present a Bayesian IPM for the ringed seal (Pusa hispida botnica) population inhabiting the Bothnian Bay in the Baltic Sea. Despite the availability of long-term monitoring data, traditional assessment methods have faltered due to dynamic environmental conditions, varying reproductive rates, and the recently re-introduced hunting, thus limiting the quality of information available to managers. We fit our model to census and various demographic, reproductive and harvest data from 1988 to 2023 to provide a comprehensive assessment of past population trends, and predict population response to alternative hunting scenarios. We estimated that 20,000 to 36,000 ringed seals inhabit the Bothnian Bay, and the population is increasing 3% to 6% per year. Reproductive rates have increased since 1988, leading to a substantial increase in the growth rate up until 2015. However, the re-introduction of hunting has since reduced the growth rate, and even minor quota increases are likely to reduce it further. Our results also support the hypothesis that a greater proportion of seals haul-out under lower ice cover circumstances, leading to higher aerial survey counts in such years. In general, our study demonstrates the value of IPMs for monitoring natural populations under changing environments, and supporting science-based management decisions.

Precise space-based photometry from the Transiting Exoplanet Survey Satellite results in a huge number of exoplanetary candidates. However, the masses of these objects are unknown and must be determined by ground-based spectroscopic follow-up observations, frequently revealing the companions to be low-mass stars rather than exoplanets. We present the first orbital and stellar parameter solutions for five such eclipsing binary-star systems using radial-velocity follow-up measurements together with spectral-energy-distribution solutions. TOI-416 and TOI-1143 are totally eclipsing F+M star systems with well-determined secondary masses, radii, and temperatures. TOI-416 is a circular system with an F6 primary and a secondary with a mass of $M_2={0.131(8)}{M_\odot}$. TOI-1143 consists of an F6 primary with an $M_2={0.142(3)}{M_\odot}$ secondary on an eccentric orbit with a third companion. With respect to the other systems, TOI-1153 shows ellipsoidal variations, TOI-1615 contains a pulsating primary, and TOI-1788 has a spotted primary, while all have moderate mass ratios of 0.2-0.4. However, these systems are in a grazing configuration, which limits their full description. The parameters of TOI-416B and TOI-1143B are suitable for the calibration of the radius-mass relation for dwarf stars., Comment: A&A accepted on 06/06/2024

Hot and warm Jupiters might have undergone the same formation and evolution path, but the two populations exhibit different distributions of orbital parameters, challenging our understanding on their actual origin. The present work, which is the results of our warm Jupiters survey carried out with the CHIRON spectrograph within the KESPRINT collaboration, aims to address this challenge by studying two planets that could help bridge the gap between the two populations. We report the confirmation and mass determination of a hot Jupiter (orbital period shorter than 10 days), TOI-2420\,b, and a warm Jupiter, TOI-2485\,b. We performed a joint analysis using a wide variety of spectral and photometric data in order to characterize these planetary systems. We found that TOI-2420\,b has an orbital period of P$_{\rm b}$=5.8 days, a mass of M$_{\rm b}$=0.9 M$_{\rm J}$ and a radius of R$_{\rm b}$=1.3 R$_{\rm J}$, with a planetary density of 0.477 \gc; while TOI-2485\,b has an orbital period of P$_{\rm b}$=11.2 days, a mass of M$_{\rm b}$=2.4 M$_{\rm J}$ and a radius of R$_{\rm b}$=1.1 R$_{\rm J}$ with density 2.36 \gc. With current parameters, the migration history for TOI-2420\,b and TOI-2485\,b is unclear: the high-eccentricity migration scenarios cannot be ruled out, and TOI-2485\,b's characteristics may rather support this scenario.

Analytical contact mechanics theories depend on surface roughness through the surface roughness power spectrum. In the present study, we evaluated the usability of various experimental methods for studying surface roughness. Our findings indicated that height data obtained from optical methods often lack accuracy and should not be utilized for calculating surface roughness power spectra. Conversely, engineering stylus instruments and atomic force microscopy (AFM) typically yield reliable results that are consistent across the overlapping roughness length scale region. For surfaces with isotropic roughness, the two-dimensional (2D) power spectrum can be derived from the one-dimensional (1D) power spectrum using several approaches, which we explored in this paper.

Inelastic neutron scattering technique is employed to investigate the paramagnetic spin dynamics in a single crystalline sample of the magnetocaloric compound MnFe$_4$Si$_3$. In the investigated temperature range, 1.033$\times T_{C}$ to 1.5$\times T_{C}$, where $T_C$ is the Curie temperature, the spin fluctuations are well described by the ferromagnetic Heisenberg model predictions. Apart from the Heisenberg exchange, additional pseudo-dipolar interactions manifest through a finite long-wavelength relaxation rate that vanishes at the transition temperature ($T_C = 305$\,K). Based on the characteristic extend of spin fluctuations in wave-vector and energy space we determine that the nature of magnetism in MnFe$_4$Si$_3$ is localized above room temperature. This contrasts with the most celebrated Mn and Fe based magnetocaloric materials that are considered as itinerant magnets.

When the solar wind interacts with the ionosphere of an unmagnetized planet, it induces currents that form an induced magnetosphere. These currents and their associated magnetic fields play a pivotal role in controlling the movement of charged particles, which is essential for understanding the escape of planetary ions. Unlike the well-documented magnetospheric current systems, the ionospheric current systems on unmagnetized planets remain less understood, which constrains the quantification of electrodynamic energy transfer from stars to these planets. Here, utilizing eight years of data from the Mars Atmosphere and Volatile EvolutioN (MAVEN) mission, we investigate the global distribution of ionospheric currents on Mars. We have identified two distinct current systems in the ionosphere: one aligns with the solar wind electric field yet exhibits hemispheric asymmetry perpendicular to the electric field direction; the other corresponds to the flow pattern of annually-averaged neutral winds. We propose that these two current systems are driven by the solar wind and atmospheric neutral winds, respectively. Our findings reveal that Martian ionospheric dynamics are influenced by the neutral winds from below and the solar wind from above, highlighting the complex and intriguing nature of current systems on unmagnetized planets., Comment: 20 pages, 6 figures

New computational tools for solid-state synthesis recipe design are needed in order to accelerate the experimental realization of novel functional materials proposed by high-throughput materials discovery workflows. This work contributes a cellular automaton simulation framework (ReactCA) for predicting the time-dependent evolution of intermediate and product phases during solid-state reactions as a function of precursor choice and amount, reaction atmosphere, and heating profile. The simulation captures rudimentary kinetic effects, the effects of reactant particle spatial distribution, particle melting and reaction atmosphere. It achieves conservation of mass using a stochastic, asynchronous evolution rule and estimates reaction rates using density functional theory data from the Materials Project [1] and machine learning estimators for the the melting point [2] and the vibrational entropy component of the Gibbs free energy [3]. The resulting simulation framework allows for the prediction of the likely outcome of a reaction recipe before any experiments are performed. We analyze five experimental solid-state recipes for BaTiO$_3$, CaZrN$_2$ and YMnO$_3$ found in the literature to illustrate the performance of the model in capturing reaction pathways as a function of temperature, reaction selectivity and the effect of precursor choice. Our approach allows for straightforward comparison of predicted mass fractions of intermediates and products with experimental results. This simulation framework presents a step toward $\textit{in silico}$ synthesis recipe design and an easier way to optimize existing recipes, aid in the identification of intermediates and identify effective recipes for yet unrealized inorganic solids.

We report the discovery and characterization of a small planet, TOI-1408 c, on a 2.2-day orbit located interior to a previously known hot Jupiter, TOI-1408 b ($P=4.42$ d, $M=1.86\pm0.02\,M_\mathrm{Jup}$, $R=2.4\pm0.5\,R_\mathrm{Jup}$) that exhibits grazing transits. The two planets are near 2:1 period commensurability, resulting in significant transit timing variations (TTVs) for both planets and transit duration variations (TDVs) for the inner planet. The TTV amplitude for TOI-1408 c is 15% of the planet's orbital period, marking the largest TTV amplitude relative to the orbital period measured to date. Photodynamical modeling of ground-based radial velocity (RV) observations and transit light curves obtained with the Transiting Exoplanet Survey Satellite (TESS) and ground-based facilities leads to an inner planet radius of $2.22\pm0.06\,R_\oplus$ and mass of $7.6\pm0.2\,M_\oplus$ that locates the planet into the Sub-Neptune regime. The proximity to the 2:1 period commensurability leads to the libration of the resonant argument of the inner planet. The RV measurements support the existence of a third body with an orbital period of several thousand days. This discovery places the system among the rare systems featuring a hot Jupiter accompanied by an inner low-mass planet., Comment: Accepted to ApJL, 17 pages, 6 figures, 4 tables

Protostellar multiplicity is common at all stages and mass ranges. However, the factors that determine the multiplicity of protostellar systems have not been systematically characterized through their molecular gas. Nobeyama 45m Radio Observatory OTF maps of HCN, HNC, HCO$^+$, and N$_2$H$^+$ (J = 1--0) toward five subregions in Perseus, complemented with single pointing APEX observations of HNC (J = 4--3) are used to derive physical parameters of the dense gas. Both observations have angular resolutions of $\sim$18", equivalent to $\sim$5000 AU scales at the distance of Perseus. Kinetic gas temperature is derived from the $I$(HCN)/$I$(HNC) J = 1--0 ratio, and H$_2$ density is obtained from the HNC J=4--3/J=1--0 ratio. These parameters are used to obtain the N$_2$H$^+$ and HCO$^+$ gas masses. The inferred and derived parameters are compared to source parameters. Inferred mean kinetic gas temperature ($I$(HCN)/$I$(HNC) J=1--0 ratio; ranging between 15 and 26 K), and H$_2$ volumetric density (HNC J=4--3/J=1--0; 10$^5$ -- 10$^6$ cm$^{-3}$) do not show correlations with multiplicity in Perseus. The derived gas and dust masses, 1.3 to 16 $\times~10^{-9}$ M$_{\odot}$ for the N$_2$H$^+$ gas mass, 0.1 to 25 M$_{\odot}$ for envelope dust masses (850 $\mu$m), and 0.8 to 10 $\times~10^{-10}$ M$_{\odot}$ for the HCO$^+$ gas mass, are correlated to multiplicity and number of protostellar components. The warm gas masses are a factor of 16 lower than the cold gas masses. This work shows that gas and dust mass is correlated to multiplicity at $\sim$5000 AU scales in Perseus. Higher order multiples tend to have higher gas and dust masses in general, while close binaries (separations $\leq$7") and single protostars have similar gas and dust mass distributions. On the other hand, H$_2$ density and kinetic gas temperature do not show any correlation with multiplicity., Comment: 25 pages, 12 figures, 3 appendices. Accepted for publication in A&A. The abstract has been modified to comply with arXiv's character limit

The nature of the close-in rocky planet 55 Cnc e is puzzling despite having been observed extensively. Its optical and infrared occultation depths show temporal variability, in addition to a phase curve variability observed in the optical. We wish to explore the possibility that the variability originates from the planet being in a 3:2 spin-orbit resonance, thus showing different sides during occultations. We proposed and were awarded Cycle 1 time at the James Webb Space Telescope (JWST) to test this hypothesis. JWST/NIRCam observed five occultations (secondary eclipses), of which four were observed within a week, of the planet simultaneously at 2.1 and 4.5 {\mu}m. While the former gives band-integrated photometry, the latter provides a spectrum between 3.9-5.0 {\mu}m. We find that the occultation depths in both bandpasses are highly variable and change between a non-detection (-5 +/- 6 ppm and 7 +/- 9 ppm) to 96 +/- 8 ppm and 119 (+34) (-19) ppm at 2.1 {\mu}m and 4.5 {\mu}m, respectively. Interestingly, the variations in both bandpasses are not correlated and do not support the 3:2 spin-orbit resonance explanation. The measured brightness temperature at 4.5 {\mu}m varies between 873-2256 K and is lower than the expected dayside temperature of bare rock with no heat re-distribution (2500 K) which is indicative of an atmosphere. Our atmospheric retrieval analysis of occultation depth spectra at 4.5 {\mu}m finds that different visits statistically favour various atmospheric scenarios including a thin outgassed CO/CO2 atmosphere and a silicate rock vapour atmosphere. Some visits even support a flat line model. The observed variability could be explained by stochastic outgassing of CO/CO2, which is also hinted by retrievals. Alternatively, the variability, observed at both 2.1 and 4.5 {\mu}m, could be the result of a circumstellar patchy dust torus generated by volcanism on the planet., Comment: 32 pages, 10 + 15 figures, 3+2 tables, accepted for publication in A&A

Among the thousands of exoplanets discovered to date, approximately a few hundred gas giants on short-period orbits are classified as "lonely" and only a few are in a multi-planet system with a smaller companion on a close orbit. The processes that formed multi-planet systems hosting gas giants on close orbits are poorly understood, and only a few examples of this kind of system have been observed and well characterised. Within the contest of multi-planet system hosting gas-giant on short orbits, we characterise TOI-1130 system by measuring masses and orbital parameters. This is a 2-transiting planet system with a Jupiter-like planet (c) on a 8.35 days orbit and a Neptune-like planet (b) on an inner (4.07 days) orbit. Both planets show strong anti-correlated transit timing variations (TTVs). Furthermore, radial velocity (RV) analysis showed an additional linear trend, a possible hint of a non-transiting candidate planet on a far outer orbit. Since 2019, extensive transit and radial velocity observations of the TOI-1130 have been acquired using TESS and various ground-based facilities. We present a new photo-dynamical analysis of all available transit and RV data, with the addition of new CHEOPS and ASTEP+ data that achieve the best precision to date on the planetary radii and masses and on the timings of each transit. We were able to model interior structure of planet b constraining the presence of a gaseous envelope of H/He, while it was not possible to assess the possible water content. Furthermore, we analysed the resonant state of the two transiting planets, and we found that they lie just outside the resonant region. This could be the result of the tidal evolution that the system underwent. We obtained both masses of the planets with a precision less than 1.5%, and radii with a precision of about 1% and 3% for planet b and c, respectively., Comment: 22 pages, 10 figures, Accepted for publication by Astronomy and Astrophysics

We describe a randomized algorithm for producing a near-optimal hierarchical off-diagonal low-rank (HODLR) approximation to an $n\times n$ matrix $\mathbf{A}$, accessible only though matrix-vector products with $\mathbf{A}$ and $\mathbf{A}^{\mathsf{T}}$. We prove that, for the rank-$k$ HODLR approximation problem, our method achieves a $(1+\beta)^{\log(n)}$-optimal approximation in expected Frobenius norm using $O(k\log(n)/\beta^3)$ matrix-vector products. In particular, the algorithm obtains a $(1+\varepsilon)$-optimal approximation with $O(k\log^4(n)/\varepsilon^3)$ matrix-vector products, and for any constant $c$, an $n^c$-optimal approximation with $O(k \log(n))$ matrix-vector products. Apart from matrix-vector products, the additional computational cost of our method is just $O(n \operatorname{poly}(\log(n), k, \beta))$. We complement the upper bound with a lower bound, which shows that any matrix-vector query algorithm requires at least $\Omega(k\log(n) + k/\varepsilon)$ queries to obtain a $(1+\varepsilon)$-optimal approximation. Our algorithm can be viewed as a robust version of widely used "peeling" methods for recovering HODLR matrices and is, to the best of our knowledge, the first matrix-vector query algorithm to enjoy theoretical worst-case guarantees for approximation by any hierarchical matrix class. To control the propagation of error between levels of hierarchical approximation, we introduce a new perturbation bound for low-rank approximation, which shows that the widely used Generalized Nystr\"om method enjoys inherent stability when implemented with noisy matrix-vector products. We also introduce a novel randomly perforated matrix sketching method to further control the error in the peeling algorithm.

Large language models (LLMs) present an enormous evolution in the strategic potential of conversational recommender systems (CRS). Yet to date, research has predominantly focused upon technical frameworks to implement LLM-driven CRS, rather than end-user evaluations or strategic implications for firms, particularly from the perspective of a small to medium enterprises (SME) that makeup the bedrock of the global economy. In the current paper, we detail the design of an LLM-driven CRS in an SME setting, and its subsequent performance in the field using both objective system metrics and subjective user evaluations. While doing so, we additionally outline a short-form revised ResQue model for evaluating LLM-driven CRS, enabling replicability in a rapidly evolving field. Our results reveal good system performance from a user experience perspective (85.5% recommendation accuracy) but underscore latency, cost, and quality issues challenging business viability. Notably, with a median cost of $0.04 per interaction and a latency of 5.7s, cost-effectiveness and response time emerge as crucial areas for achieving a more user-friendly and economically viable LLM-driven CRS for SME settings. One major driver of these costs is the use of an advanced LLM as a ranker within the retrieval-augmented generation (RAG) technique. Our results additionally indicate that relying solely on approaches such as Prompt-based learning with ChatGPT as the underlying LLM makes it challenging to achieve satisfying quality in a production environment. Strategic considerations for SMEs deploying an LLM-driven CRS are outlined, particularly considering trade-offs in the current technical landscape., Comment: 27 pages, 3 tables, 5 figures, pre-print manuscript, updated version of manuscript due to typo (previous version, Figure 5 was incorrectly named Figure 6)

We have studied the fluctuation (noise) in the position of sliding blocks under constant driving forces on different substrate surfaces. The experimental data are complemented by simulations using a simple spring-block model where the asperity contact regions are modeled by miniblocks connected to the big block by viscoelastic springs. The miniblocks experience forces that fluctuate randomly with the lateral position, simulating the interaction between asperities on the block and the substrate. The theoretical model provides displacement power spectra that agree well with the experimental results.

The differentiable programming paradigm is a cornerstone of modern scientific computing. It refers to numerical methods for computing the gradient of a numerical model's output. Many scientific models are based on differential equations, where differentiable programming plays a crucial role in calculating model sensitivities, inverting model parameters, and training hybrid models that combine differential equations with data-driven approaches. Furthermore, recognizing the strong synergies between inverse methods and machine learning offers the opportunity to establish a coherent framework applicable to both fields. Differentiating functions based on the numerical solution of differential equations is non-trivial. Numerous methods based on a wide variety of paradigms have been proposed in the literature, each with pros and cons specific to the type of problem investigated. Here, we provide a comprehensive review of existing techniques to compute derivatives of numerical solutions of differential equations. We first discuss the importance of gradients of solutions of differential equations in a variety of scientific domains. Second, we lay out the mathematical foundations of the various approaches and compare them with each other. Third, we cover the computational considerations and explore the solutions available in modern scientific software. Last but not least, we provide best-practices and recommendations for practitioners. We hope that this work accelerates the fusion of scientific models and data, and fosters a modern approach to scientific modelling.

PLATO (PLAnetary Transits and Oscillations of stars) is ESA's M3 mission designed to detect and characterise extrasolar planets and perform asteroseismic monitoring of a large number of stars. PLATO will detect small planets (down to <2 R_(Earth)) around bright stars (<11 mag), including terrestrial planets in the habitable zone of solar-like stars. With the complement of radial velocity observations from the ground, planets will be characterised for their radius, mass, and age with high accuracy (5 %, 10 %, 10 % for an Earth-Sun combination respectively). PLATO will provide us with a large-scale catalogue of well-characterised small planets up to intermediate orbital periods, relevant for a meaningful comparison to planet formation theories and to better understand planet evolution. It will make possible comparative exoplanetology to place our Solar System planets in a broader context. In parallel, PLATO will study (host) stars using asteroseismology, allowing us to determine the stellar properties with high accuracy, substantially enhancing our knowledge of stellar structure and evolution. The payload instrument consists of 26 cameras with 12cm aperture each. For at least four years, the mission will perform high-precision photometric measurements. Here we review the science objectives, present PLATO's target samples and fields, provide an overview of expected core science performance as well as a description of the instrument and the mission profile at the beginning of the serial production of the flight cameras. PLATO is scheduled for a launch date end 2026. This overview therefore provides a summary of the mission to the community in preparation of the upcoming operational phases.

We develop a technique for predicting the Curie temperature of magnetic materials using density functional theory calculations suitable to include in high-throughput frameworks. We apply four different models, including physically relevant observables and assess numerical constants by studying 32 ferro- and ferrimagnets. With the best-performing model, the Curie temperature can be predicted with a mean absolute error of approximately 126 K. As predictive factors, the models consider either the energy differences between the magnetic ground state and a magnetically disordered paramagnetic state, or the average constraining fields acting on magnetic moments in a disordered local moments calculation. Additionally, the energy differences are refined by incorporating the magnetic entropy of the paramagnetic state and the number of nearest magnetic neighbors of the magnetic atoms. The most advanced model is found to extend well into Fe$_{1-x}$Co$_x$ alloys, indicating the potential efficacy of utilizing our model in designing materials with tailored Curie temperatures by altering alloy compositions. This examination can illuminate the factors influencing magnetic transition temperatures in magnetic materials and provide insights into how they can be employed to make quantitative predictions of Curie temperatures. Our approach is not restricted to specific crystal structures or chemical compositions. It offers a more cost-effective alternative, in terms of human time and need for hands-on oversight, to other density functional theory methods for predicting the Curie temperature. As a result, it provides a practical strategy for conducting high-throughput screening for new technologically applicable magnetic materials. Alternatively, it can complement ML-based screening of magnetic materials by integrating physical principles into such approaches, thereby enhancing their prediction accuracy.

Designing effective reward functions is crucial to training reinforcement learning (RL) algorithms. However, this design is non-trivial, even for domain experts, due to the subjective nature of certain tasks that are hard to quantify explicitly. In recent works, large language models (LLMs) have been used for reward generation from natural language task descriptions, leveraging their extensive instruction tuning and commonsense understanding of human behavior. In this work, we hypothesize that LLMs, guided by human feedback, can be used to formulate reward functions that reflect human implicit knowledge. We study this in three challenging settings -- autonomous driving, humanoid locomotion, and dexterous manipulation -- wherein notions of ``good" behavior are tacit and hard to quantify. To this end, we introduce REvolve, a truly evolutionary framework that uses LLMs for reward design in RL. REvolve generates and refines reward functions by utilizing human feedback to guide the evolution process, effectively translating implicit human knowledge into explicit reward functions for training (deep) RL agents. Experimentally, we demonstrate that agents trained on REvolve-designed rewards outperform other state-of-the-art baselines., Comment: project page: https://rishihazra.github.io/REvolve. updated title, added experiments

Understanding the nature of the luminous 1991T-like supernovae is of great importance to supernova cosmology as they are likely to have been more common in the early universe. In this paper we explore the observational properties of 1991T-like supernovae to study their relationship to other luminous, slow-declining Type~Ia supernovae (SNe Ia). From the spectroscopic and photometric criteria defined in Phillips et al. (1992), we identify 17 1991T-like supernovae from the literature. Combining these objects with ten 1991T-like supernovae from the Carnegie Supernova Project-II, the spectra, light curves, and colors of these events, along with their host galaxy properties, are examined in detail. We conclude that 1991T-like supernovae are closely related in essentially all of their UV, optical, and near-infrared properties -- as well as their host galaxy parameters -- to the slow-declining subset of Branch core-normal supernovae and to the intermediate 1999aa-like events, forming a continuum of luminous SNe Ia. The overriding difference between these three subgroups appears to be the extent to which $^{56}$Ni mixes into the ejecta, producing the pre-maximum spectra dominated by Fe III absorption, the broader UV light curves, and the higher luminosities that characterize the 1991T-like events. Nevertheless, the association of 1991T-like SNe with the rare Type Ia CSM supernovae would seem to run counter to this hypothesis, in which case 1991T-like events may form a separate subclass of SNe Ia, possibly arising from single-degenerate progenitor systems., Comment: Accepted for publication in ApJS

In this paper we present and prove some new results concerning approximation properties of $T$ means with respect to the Vilenkin system in Lebesgue spaces and Lipschitz classes for any $1\leq p<\infty$. As applications, we obtain extension of some known approximation inequalities.

We introduce the concept of half-closed nodes for nodal discontinuous Galerkin (DG) discretisations. Unlike more commonly used closed nodes in DG, where on every element nodes are placed on all of its boundaries, half-closed nodes only require nodes to be placed on a subset of the element's boundaries. The effect of using different nodes on DG operator sparsity is studied and we find in particular for there to be no difference in the sparsity pattern of the Laplace operator whether closed or half-closed nodes are used. On quadrilateral/hexahedral elements we use the Gauss-Radau points as the half-closed nodes of choice, which we demonstrate is able to speed up DG operator assembly in addition to leverage previously known superconvergence results. We also discuss in this work some linear solver techniques commonly used for Finite Element or discontinuous Galerkin methods such as static condensation and block-based methods, and how they can be applied to half-closed DG discretisations.

Machine learning interatomic potentials (MLIPs) have introduced a new paradigm for atomic simulations. Recent advancements have seen the emergence of universal MLIPs (uMLIPs) that are pre-trained on diverse materials datasets, providing opportunities for both ready-to-use universal force fields and robust foundations for downstream machine learning refinements. However, their performance in extrapolating to out-of-distribution complex atomic environments remains unclear. In this study, we highlight a consistent potential energy surface (PES) softening effect in three uMLIPs: M3GNet, CHGNet, and MACE-MP-0, which is characterized by energy and force under-prediction in a series of atomic-modeling benchmarks including surfaces, defects, solid-solution energetics, phonon vibration modes, ion migration barriers, and general high-energy states. We find that the PES softening behavior originates from a systematic underprediction error of the PES curvature, which derives from the biased sampling of near-equilibrium atomic arrangements in uMLIP pre-training datasets. We demonstrate that the PES softening issue can be effectively rectified by fine-tuning with a single additional data point. Our findings suggest that a considerable fraction of uMLIP errors are highly systematic, and can therefore be efficiently corrected. This result rationalizes the data-efficient fine-tuning performance boost commonly observed with foundational MLIPs. We argue for the importance of a comprehensive materials dataset with improved PES sampling for next-generation foundational MLIPs.

Let $A$ be an invertible $d\times d$ matrix with integer elements. Then $A$ determines a self-map $T$ of the $d$-dimensional torus $\mathbb{T}^d=\mathbb{R}^d/\mathbb{Z}^d$. Given a real number $\tau>0$, and a sequence $\{z_n\}$ of points in $\mathbb{T}^d$, let $W_\tau$ be the set of points $x\in\mathbb{T}^d$ such that $T^n(x)\in B(z_n,e^{-n\tau})$ for infinitely many $n\in\mathbb{N}$. The Hausdorff dimension of $W_\tau$ has previously been studied by Hill--Velani and Li--Liao--Velani--Zorin. We provide complete results on the Hausdorff dimension of $W_\tau$ for any expanding matrix. For hyperbolic matrices, we compute the dimension of $W_\tau$ only when $A$ is a $2 \times 2$ matrix. We give counterexamples to a natural candidate for a dimension formula for general dimension $d$., Comment: 24 pages, 3 figures

We present the second and final release of optical spectroscopy of Type Ia Supernovae (SNe Ia) obtained during the first and second phases of the Carnegie Supernova Project (CSP-I and CSP-II). The newly released data consist of 148 spectra of 30 SNe Ia observed in the course of the CSP-I, and 234 spectra of 127 SNe Ia obtained during the CSP-II. We also present 216 optical spectra of 46 historical SNe Ia, including 53 spectra of 30 SNe Ia observed by the Cal\'an/Tololo Supernova Survey. We combine these observations with previously published CSP data and publicly-available spectra to compile a large sample of measurements of spectroscopic parameters at maximum light, consisting of pseudo-equivalent widths and expansion velocities of selected features, for 232 CSP and historical SNe Ia (including more than 1000 spectra). Finally, we review some of the strongest correlations between spectroscopic and photometric properties of SNe Ia. Specifically, we define two samples: one consisting of SNe Ia discovered by targeted searches (most of them CSP-I objects) and the other composed of SNe Ia discovered by untargeted searches, which includes most of the CSP-II objects. The analysed correlations are similar for both samples. We find a larger incidence of SNe Ia belonging to the Cool (CL)and Broad Line (BL) Branch subtypes among the events discovered by targeted searches, Shallow Silicon (SS) SNe Ia are present with similar frequencies in both samples, while Core Normal (CN) SNe Ia are more frequent in untargeted searches., Comment: 59 pages, 16 figures, accepted for publication in The Astrophysical Journal. May 7, 2024: LaTex file updated: corrected one missing comma and an extraneous space in Table 2

The randomized singular value decomposition (SVD) has become a popular approach to computing cheap, yet accurate, low-rank approximations to matrices due to its efficiency and strong theoretical guarantees. Recent work by Boull\'e and Townsend (FoCM, 2023) presents an infinite-dimensional analog of the randomized SVD to approximate Hilbert-Schmidt operators. However, many applications involve computing low-rank approximations to symmetric positive semi-definite matrices. In this setting, it is well-established that the randomized Nystr{\"o}m approximation is usually preferred over the randomized SVD. This paper explores an infinite-dimensional analog of the Nystr{\"o}m approximation to compute low-rank approximations to non-negative self-adjoint trace-class operators. We present an analysis of the method and, along the way, improve the existing infinite-dimensional bounds for the randomized SVD. Our analysis yields bounds on the expected value and tail bounds for the Nystr{\"o}m approximation error in the operator, trace, and Hilbert-Schmidt norms. Numerical experiments for simple integral operators validate the proposed framework.