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RNA is the only known biopolymer that combines genotype and phenotype in a single molecular entity. This has suggested that the flow of genetic information DNA-RNA-proteins already operating in LUCA could have been preceded by a primordial era when RNA was the genetic and catalytic macromolecule. However, understanding how RNA could have polymerized and subsequently replicated in early Earth remains challenging. We present a theoretical and computational framework to model the non-enzymatic polymerization of ribonucleotides and the template-dependent replication of primordial RNA molecules, at the interfaces between the aqueous solution and a clay mineral supplied by its interlayers and channels. Our results demonstrate that efficient polymerization and accurate replication of single-stranded RNA polymers, sufficiently long to fold and acquire basic functions ($>15$ nt), were possible at clay-water interfaces in early Earth, provided the physico-chemical environment exhibited an oscillatory pattern of large amplitude and a period compatible with spring tide dynamics. Interestingly, the theoretical analysis presents rigorous evidence that RNA replication efficiency increases in oscillating environments compared to constant ones. Moreover, the versatility of our framework enables comparisons between different genetic alphabets, showing that a four-letter alphabet -- particularly when allowing non-canonical base pairs, as in current RNA -- represents an optimal balance of replication speed and sequence diversity in the pathway to life., Comment: This file contains the main manuscript (6 figures) and the Supplementary Information (4 sections and 7 Supplementary figures)

Interior compositions are key for our understanding of Earth-like exoplanets. The composition of the core can influence the presence of a magnetic dynamo and the strength of gravity on the planetary surface, both of which heavily impact thermal and possible biological processes and thus the habitability for life and its evolution on the planet. However, detailed measurements of the planetary interiors are extremely challenging for small exoplanets, and existing data suggest a wide diversity in planet compositions. Hitherto, only certain photospheric chemical abundances of the host stars have been considered as tracers to explain the diversity of exoplanet compositions. Here we present a homogeneous analysis of stars hosting rocky exoplanets, with ages between 2 and 14 Gyr, revealing a correlation between rocky exoplanet compositions and the ages of the planetary systems. Denser rocky planets are found around younger stars. This suggests that the compositional diversity of rocky exoplanets can be linked to the ages of their host stars. We interpret this to be a result of chemical evolution of stars in the Milky Way, which modifies the material out of which stars and planets form. The results imply that rocky planets which form today, at similar galactocentric radii, may have different formation conditions, and thus different properties than planets which formed several billion years ago, such as the Earth.

Phase-locked loop (PLL), conceived in 1932 by H. Bellescize, has been the basic electronic component in the development of communication technology from the early analog radio receptors to modern digital civil and military facilities. Traditionally, the analysis is conducted by modeling the dynamical behavior of phase and frequency errors, hence following a phase reduction approach. One of the main goals of the present work is to describe and investigate the dynamics of a PLL node by representing it in full state-space, here called non reductionist model, without the usual design simplifications i.e., considering different input and output frequencies and not neglecting the higher frequencies components generated in the phase detection process. On the one hand, this approach complicates the use of analytical tools but on the other hand it permits an efficient numerical approach that can be used for precise definition of regions in parameters space that show the boundaries between synchronization and non synchronization regimes, even when noise is considered. Results show that the PLL node can be simulated in a more realistic way using the state-space model and that a number of design-relevant aspects can now be investigated numerically., Comment: The paper is not submitted to any journal

We present the notion of complexity $\text{C}(G,H)$ of two graphs $G$ and $H$, along with basic results for this numerical invariant. This was motivated by the Data Migration Problem. This invariant $\text{C}(G,H)$ is a number that measures \aspas{complexity} of the question: when is there a homomorphism $G\to H$? More precisely, $\text{C}(G,H)$ is the minimal number $\ell$ such that there are $\ell$ different subgraphs $G_j$ of $G$ such that $G=G_1\cup\cdots\cup G_\ell$ and for each $G_j$, there is a homomorphism $G_j\to H$. The complexity $\text{C}(-,-)$ is a graph invariant. Additionally, $\text{C}(G,H)$ provides a obstruction to the existence of homomorphisms. We explore the sub-additivity of the complexity $\text{C}(-,-)$ and study the complexity for products. We present a relation between $\text{C}(G,H)$ and the chromatic numbers $\chi(G),\chi(H)$. Specifically, we present a lower and an upper bounds for the complexity in terms of the chromatic number. We compute $\text{C}(K_j,K_i)$ and demonstrate a triangular inequality. Furthermore, we apply our theory to solve an example related to Data Migration. A primary objective of this paper is to present a well-defined methodology that can help manage the complexity of data migration tasks., Comment: 21 pages. Comments are welcome

The precise characterization and mitigation of systematic effects is one of the biggest roadblocks impeding the detection of the fluctuations of cosmological 21cm signals. Missing data in radio cosmological experiments, often due to radio frequency interference (RFI), poses a particular challenge to power spectrum analysis as it could lead to the ringing of bright foreground modes in Fourier space, heavily contaminating the cosmological signals. Here we show that the problem of missing data becomes even more arduous in the presence of systematic effects. Using a realistic numerical simulation, we demonstrate that partially flagged data combined with systematic effects can introduce significant foreground ringing. We show that such an effect can be mitigated through inpainting the missing data. We present a rigorous statistical framework that incorporates the process of inpainting missing data into a quadratic estimator of the 21cm power spectrum. Under this framework, the uncertainties associated with our inpainting method and its impact on power spectrum statistics can be understood. These results are applied to the latest Phase II observations taken by the Hydrogen Epoch of Reionization Array, forming a crucial component in power spectrum analyses as we move toward detecting 21cm signals in the ever more noisy RFI environment., Comment: 25 pages, 11 figures, submitted to ApJ

We explore a family of paraxial beams constructed by the linear superposition of Laguerre-Gaussian beams, representing an optical analogue to generalized $SU(2)$ Lie group coherent states. A single complex parameter controls a smooth transition between Laguerre-Gaussian and Hermite-Gaussian beams, with intermediate beams that merge characteristics of both families. Our beams exhibit propagation-invariant properties, up to a scaling factor, a highly desirable feature for optical applications, validated via holographic experimental results., Comment: 12 pages, 6 figures

We present the mission concept "Mission to Analyze the UltraViolet universE" (MAUVE), a wide-field spectrometer and imager conceived during the inaugural NASA Astrophysics Mission Design School. MAUVE responds to the 2023 Announcement of Opportunity for Probe-class missions, with a budget cap of \$1 billion, and would hypothetically launch in 2031. However, the formulation of MAUVE was an educational exercise and the mission is not being developed further. The Principal Investigator-led science of MAUVE aligns with the priorities outlined in the 2020 Astrophysics Decadal Survey, enabling new characterizations of exoplanet atmospheres, the early-time light curves of some of the universe's most explosive transients, and the poorly-understood extragalactic background light. Because the Principal Investigator science occupies 30% of the observing time available during the mission's 5 yr lifespan, we provide an observing plan that would allow for 70% of the observing time to be used for General Observer programs, with community-solicited proposals. The onboard detector (THISTLE) claims significant heritage from the Space Telescope Imaging Spectrograph on Hubble, but extends its wavelength range down to the extreme UV. We note that MAUVE would be the first satellite in decades with the ability to access this regime of the electromagnetic spectrum. MAUVE has a field of view of 900" x 900" a photometric sensitivity extending to $m_{UV}\leq 24$, and a resolving power of $R\sim1000$. This paper provides full science and mission traceability matrices for this concept, and also outlines cost and scheduling timelines aimed at enabling a within-budget mission and an on-time launch., Comment: 21 pages, 15 figures. Published by the Publications of the Astronomical Society of the Pacific

Precise spatial manipulation of particles via optical forces is essential in many research areas, ranging from biophysics to atomic physics. Central to this effort is the challenge of designing optical systems that are optimized for specific applications. Traditional design methods often rely on trial-and-error methods, or on models that approximate the particle as a point dipole, which only works for particles much smaller than the wavelength of the electromagnetic field. In this work, we present a general inverse design framework based on the Maxwell stress tensor formalism capable of simultaneously designing all components of the system, while being applicable to particles of arbitrary sizes and shapes. Notably, we show that with small modifications to the baseline formulation, it is possible to engineer systems capable of attracting, repelling, accelerating, oscillating, and trapping particles. We demonstrate our method using various case studies where we simultaneously design the particle and its environment, with particular focus on free-space particles and particle-metalens systems.

In this article, we seek to elucidate challenges and opportunities for differential privacy within the federal government setting, as seen by a team of differential privacy researchers, privacy lawyers, and data scientists working closely with the U.S. government. After introducing differential privacy, we highlight three significant challenges which currently restrict the use of differential privacy in the U.S. government. We then provide two examples where differential privacy can enhance the capabilities of government agencies. The first example highlights how the quantitative nature of differential privacy allows policy security officers to release multiple versions of analyses with different levels of privacy. The second example, which we believe is a novel realization, indicates that differential privacy can be used to improve staffing efficiency in classified applications. We hope that this article can serve as a nontechnical resource which can help frame future action from the differential privacy community, privacy regulators, security officers, and lawmakers., Comment: 2nd Workshop on Regulatable ML at NeurIPS 2024

In this work, a non-linear controller designed using non-linear transformation linearization and feedback is proposed for an inverter connected to a weak grid through a single-stage inductive filter. The proposed strategy is self-synchronized, so that it is not necessary to have a voltage sensor at the Point of Common Coupling (PCC). The strategy allows to robustify, in the presence of a weak grid, a strategy that has already been demonstrated to allow a significant reduction in the size of the DC-link capacitor of the converter. For this purpose, a state observer is designed that allows estimating the voltage at the PCC from the measurement of the output inductor current. A start-up controller is also included, which allows synchronization even in the case of system start-up. Simulation results are presented for different operating cases, including start-up, normal operation, and grid-voltage sags and swells. In all these cases, it is considered that the exact parameters of the grid to which the inverter is connected are unknown., Comment: 8 pages, 5 figures

The reader will learn how digital images are edited using linear algebra and calculus. Starting from the concept of filter towards machine learning techniques such as convolutional neural networks., Comment: 23 pages

Artificial intelligence (AI) has demonstrated significant potential in ECG analysis and cardiovascular disease assessment. Recently, foundation models have played a remarkable role in advancing medical AI. The development of an ECG foundation model holds the promise of elevating AI-ECG research to new heights. However, building such a model faces several challenges, including insufficient database sample sizes and inadequate generalization across multiple domains. Additionally, there is a notable performance gap between single-lead and multi-lead ECG analyses. We introduced an ECG Foundation Model (ECGFounder), a general-purpose model that leverages real-world ECG annotations from cardiology experts to broaden the diagnostic capabilities of ECG analysis. ECGFounder was trained on over 10 million ECGs with 150 label categories from the Harvard-Emory ECG Database, enabling comprehensive cardiovascular disease diagnosis through ECG analysis. The model is designed to be both an effective out-of-the-box solution, and a to be fine-tunable for downstream tasks, maximizing usability. Importantly, we extended its application to lower rank ECGs, and arbitrary single-lead ECGs in particular. ECGFounder is applicable to supporting various downstream tasks in mobile monitoring scenarios. Experimental results demonstrate that ECGFounder achieves expert-level performance on internal validation sets, with AUROC exceeding 0.95 for eighty diagnoses. It also shows strong classification performance and generalization across various diagnoses on external validation sets. When fine-tuned, ECGFounder outperforms baseline models in demographic analysis, clinical event detection, and cross-modality cardiac rhythm diagnosis. The trained model and data will be publicly released upon publication through the bdsp.io. Our code is available at https://github.com/bdsp-core/ECGFounder, Comment: working in progress

The teaching innovation project SpaceRaceEdu: development of an educational multiplayer video game for self-study and self-assessment has been carried out under the INNOVA call of the Autonomous University of Madrid during the 2022-2023 academic year. In this project, a functional prototype of SpaceRaceEdu has been developed: a multiplayer video game with a social and educational nature, which can be used both by teachers as a training and evaluation activity and by students as a tool for study and evaluation. In SpaceRaceEdu, several student teams try to launch a rocket before everyone else. To meet this objective, they must gather a series of resources by going through a scenario and answering questions of different types. The teachers can introduce these questions according to the contents of their subject. The videogame balances competition and cooperation to promote participation and learning. Competition occurs between teams who strive to answer all their questions correctly before their rivals. In contrast, cooperation occurs between students on the same team who can organize and support each other to be more effective., Comment: 8 pages, in Spanish language, 3 figures

A successful detection of the cosmological 21-cm signal from intensity mapping experiments (for example, during the Epoch of Reioinization or Cosmic Dawn) is contingent on the suppression of subtle systematic effects in the data. Some of these systematic effects, with mutual coupling a major concern in interferometric data, manifest with temporal variability distinct from that of the cosmological signal. Fringe-rate filtering -- a time-based Fourier filtering technique -- is a powerful tool for mitigating these effects; however, fringe-rate filters also attenuate the cosmological signal. Analyses that employ fringe-rate filters must therefore be supplemented by careful accounting of the signal loss incurred by the filters. In this paper, we present a generalized formalism for characterizing how the cosmological 21-cm signal is attenuated by linear time-based filters applied to interferometric visibilities from drift-scanning telescopes. Our formalism primarily relies on analytic calculations and therefore has a greatly reduced computational cost relative to traditional Monte Carlo signal loss analyses. We apply our signal loss formalism to a filtering strategy used by the Hydrogen Epoch of Reionization Array (HERA) and compare our analytic predictions against signal loss estimates obtained through a Monte Carlo analysis. We find excellent agreement between the analytic predictions and Monte Carlo estimates and therefore conclude that HERA, as well as any other drift-scanning interferometric experiment, should use our signal loss formalism when applying linear, time-based filters to the visibilities., Comment: 27 pages, 11 figures, submitted to ApJ

A systematic construction for supersymmetric negative (non-local) flows for mKdV and KdV based on $sl(2,1)$ with a principal gradation is proposed in this paper. We show that smKdV and sKdV can be mapped onto each other through a gauge super Miura transformation, together with an additional condition for the negative flows, which ensure the supersymmetry of the negative sKdV flow. In addition, we classify both smKdV and sKdV flows with respect to the vacuum (boundary) solutions accepted for each flow, whether zero or non-zero. Each vacuum is used to derive both soliton solutions and the Heisenberg subalgebra for the smKdV hierarchy, where we present novel vertex operators and solutions for non-zero bosonic and fermionic vacuum. Finally, the gauge Miura transformation is used to obtain the sKdV solutions, which exhibit a rich degeneracy due to both multiple gauge super Miura transformations and multiple vacuum possibilities., Comment: 49 pages, 2 figures

Quorum sensing orchestrates bacterial communication, which is vital for bacteria's population behaviour. We propose a mathematical model that unveils chaotic dynamics within quorum sensing networks, challenging predictability. The model considers the interaction between autoinducers (molecular signalling) and two subtypes of bacteria. We analyze the different dynamical scenarios to find parameter regimes for long-term steady-state behaviour, periodic oscillations, and even chaos. In the latter case, we find that the complicated dynamics can be explained by the presence of homoclinic Shilnikov bifurcations., Comment: 20 pages, 9 figures

A crucial question in analyzing a concurrent system is to determine its long-run behaviour, and in particular, whether there are irreversible choices in its evolution, leading into parts of the reachability space from which there is no return to other parts. Casting this problem in the unifying framework of safe Petri nets, our previous work has provided techniques for identifying attractors, i.e. terminal strongly connected components of the reachability space. What we aim at is to determine the attraction basins associated to those attractors; that is, those states from where all infinite runs are doomed to end in the given attractor, as opposed to those that are free to evolve differently. Here, we provide a solution for the case of safe Petri nets. Our algorithm uses net unfoldings and provides a map of all of those configurations (concurrent executions of the system) that lead onto cliff-edges, i.e. any maximal extension for those configurations lies in some basin that is considered fatal., Comment: Will be submitted to a journal. arXiv admin note: substantial text overlap with arXiv:2209.10323

We theoretically investigate the magnetic response on a three-dimensional superconducting nanobridge system, which is compound of two parallel parallelepiped (samples) connected through a nanobridge of size $\mathbf{L}$ and thickness $\mathbf{x}$, which mediates interactions between them. This study is conducted in the presence of a magnetic field $\mathbf{H}$ and the transport of a direct current $\mathbf{J}$. We use the well-know time dependent Ginzburg-Landau theory ($\mathbf{TDGL}$) for analyzed the possible effects on the density Gibbs free energy $\mathbf{F}$, magnetization $\mathbf{M}$, and superconducting electronic Cooper pair density $|\psi|^{2}$. We are interested in studying two cases: varying the $\mathbf{L}$ and $\mathbf{x}$ of the nanobridge in the absence of induced $\mathbf{J}$, and including the induction of external $\mathbf{J}$ for fixed $\mathbf{L}$ and $\mathbf{x}$. We find that $\mathbf{L}$ and $\mathbf{x}$ play an essential role in stabilizing (controlling) vortex states in the nanobridge, and the presence of induced $\mathbf{J}$ ($\mathbf{J}>0$ and $\mathbf{J}<0$), with a fixed $\mathbf{L}$ and $\mathbf{x}$, causes the movement of vortex states in the nanobridge just when $\mathbf{J}$ is induced at both faces of superconducting nanobridge system., Comment: 11 pages, 10 figures

A study of the dynamical and thermodynamical stability of a charged thin-shell wormhole built by gluing two Reissner-Nordstr\"{o}m geometries is presented. The charge on the shell is linearly related to the matter content. For the dynamical stability, a concise inequality is obtained, valid for any barotropic equation of state that relates the pressure with the energy density at the throat. A thermodynamical description of the system is introduced, which leads to the temperature and the electric potentials. Adopting a linear equation of state for the pressure and a definite form for the entropy function, the set of equilibrium configurations that are both dynamically and thermodynamically stable is found., Comment: 27 pages, 3 figures; v3: corrected typos in references

Let $\mathbb{F}_{q}$ be the finite field with $q$ elements. In this paper we will describe the dynamics of the map $f(X)=X(X^{q-1}-c)^{q+1},$ with $c\in\mathbb{F}_{q}^{\ast},$ over the finite field $\mathbb{F}_{q^2}$.

Constructive type theory combines logic and programming in one language. This is useful both for reasoning about programs written in type theory, as well as for reasoning about other programming languages inside type theory. It is well-known that it is challenging to extend these applications to languages with recursion and computational effects such as probabilistic choice, because these features are not easily represented in constructive type theory. We show how to define and reason about a programming language with probabilistic choice and recursive types, in guarded type theory. We use higher inductive types to represent finite distributions and guarded recursion to model recursion. We define both operational and denotational semantics, as well as a relation between the two. The relation can be used to prove adequacy, but we also show how to use it to reason about programs up to contextual equivalence., Comment: 61 pages

Our study demonstrates that strong cationic segregation can occur in amorphous complex oxide memristors during electrical operation. With the help of analytic techniques, we observed that switching the electrical stimulation from voltage to current significantly prevents structural changes and cation segregation at the nanoscale, improving also the device cycle-to-cycle variability. These findings could contribute to the design of more reliable oxide-based memristors and underscore the crucial effect that has the type of electrical stimulation applied to the devices on their integrity and reliability., Comment: 15 pages, 5 figures

The 21 cm transition from neutral Hydrogen promises to be the best observational probe of the Epoch of Reionisation (EoR). This has led to the construction of low-frequency radio interferometric arrays, such as the Hydrogen Epoch of Reionization Array (HERA), aimed at systematically mapping this emission for the first time. Precision calibration, however, is a requirement in 21 cm radio observations. Due to the spatial compactness of HERA, the array is prone to the effects of mutual coupling, which inevitably lead to non-smooth calibration errors that contaminate the data. When unsmooth gains are used in calibration, intrinsically spectrally-smooth foreground emission begins to contaminate the data in a way that can prohibit a clean detection of the cosmological EoR signal. In this paper, we show that the effects of mutual coupling on calibration quality can be reduced by applying custom time-domain filters to the data prior to calibration. We find that more robust calibration solutions are derived when filtering in this way, which reduces the observed foreground power leakage. Specifically, we find a reduction of foreground power leakage by 2 orders of magnitude at k=0.5.

Very metal-poor stars ([Fe/H]<-2) are important laboratories for testing stellar models and reconstructing the formation history of our galaxy. Asteroseismology is a powerful tool to probe stellar interiors and measure ages, but few asteroseismic detections are known in very metal-poor stars and none have allowed detailed modeling of oscillation frequencies. We report the discovery of a low-luminosity Kepler red giant (KIC 8144907) with high S/N oscillations, [Fe/H]=-2.66+/-0.08 and [alpha/Fe]=0.38+/-0.06, making it by far the most metal-poor star to date for which detailed asteroseismic modeling is possible. By combining the oscillation spectrum from Kepler with high-resolution spectroscopy we measure an asteroseismic mass and age of 0.79+/-0.02(ran)+/-0.01(sys) Msun and 12.0+/-0.6(ran)+/-0.4(sys) Gyr, with remarkable agreement across different codes and input physics, demonstrating that stellar models and asteroseismology are reliable for very metal-poor stars when individual frequencies are used. The results also provide a direct age anchor for the early formation of the Milky Way, implying that substantial star formation did not commence until redshift z~3 (if the star formed in-situ) or that the Milky Way has undergone merger events for at least ~12 Gyr (if the star was accreted by a dwarf satellite merger such as Gaia Enceladus)., Comment: 10 pages, 4 figures, accepted for publication in ApJ

We report on the effects of cosmic ray interactions with the Kinetic Inductance Detector (KID) based focal plane array for the Terahertz Intensity Mapper (TIM). TIM is a NASA-funded balloon-borne experiment designed to probe the peak of the star formation in the Universe. It employs two spectroscopic bands, each equipped with a focal plane of four $\sim\,$900-pixel, KID-based array chips. Measurements of an 864-pixel TIM array shows 791 resonators in a 0.5$\,$GHz bandwidth. We discuss challenges with resonator calibration caused by this high multiplexing density. We robustly identify the physical positions of 788 (99.6$\,$%) detectors using a custom LED-based identification scheme. Using this information we show that cosmic ray events occur at a rate of 2.1$\,\mathrm{events/min/cm^2}$ in our array. 66$\,$% of the events affect a single pixel, and another 33$\,$% affect $<\,$5 KIDs per event spread over a 0.66$\,\mathrm{cm^2}$ region (2 pixel pitches in radius). We observe a total cosmic ray dead fraction of 0.0011$\,$%, and predict that the maximum possible in-flight dead fraction is $\sim\,$0.165$\,$%, which demonstrates our design will be robust against these high-energy events., Comment: 14 pages, 5 figures. Accepted for the publication in Journal of Low Temperature Physics (2024)

Representing and quantifying Minimal Residual Disease (MRD) in Acute Myeloid Leukemia (AML), a type of cancer that affects the blood and bone marrow, is essential in the prognosis and follow-up of AML patients. As traditional cytological analysis cannot detect leukemia cells below 5\%, the analysis of flow cytometry dataset is expected to provide more reliable results. In this paper, we explore statistical learning methods based on optimal transport (OT) to achieve a relevant low-dimensional representation of multi-patient flow cytometry measurements (FCM) datasets considered as high-dimensional probability distributions. Using the framework of OT, we justify the use of the K-means algorithm for dimensionality reduction of multiple large-scale point clouds through mean measure quantization by merging all the data into a single point cloud. After this quantization step, the visualization of the intra and inter-patients FCM variability is carried out by embedding low-dimensional quantized probability measures into a linear space using either Wasserstein Principal Component Analysis (PCA) through linearized OT or log-ratio PCA of compositional data. Using a publicly available FCM dataset and a FCM dataset from Bordeaux University Hospital, we demonstrate the benefits of our approach over the popular kernel mean embedding technique for statistical learning from multiple high-dimensional probability distributions. We also highlight the usefulness of our methodology for low-dimensional projection and clustering patient measurements according to their level of MRD in AML from FCM. In particular, our OT-based approach allows a relevant and informative two-dimensional representation of the results of the FlowSom algorithm, a state-of-the-art method for the detection of MRD in AML using multi-patient FCM.

Properties such as provable security and correctness for randomized programs are naturally expressed relationally as approximate equivalences. As a result, a number of relational program logics have been developed to reason about such approximate equivalences of probabilistic programs. However, existing approximate relational logics are mostly restricted to first-order programs without general state. In this paper we develop Approxis, a higher-order approximate relational separation logic for reasoning about approximate equivalence of programs written in an expressive ML-like language with discrete probabilistic sampling, higher-order functions, and higher-order state. The Approxis logic recasts the concept of error credits in the relational setting to reason about relational approximation, which allows for expressive notions of modularity and composition, a range of new approximate relational rules, and an internalization of a standard limiting argument for showing exact probabilistic equivalences by approximation. We also use Approxis to develop a logical relation model that quantifies over error credits, which can be used to prove exact contextual equivalence. We demonstrate the flexibility of our approach on a range of examples, including the PRP/PRF switching lemma, IND\$-CPA security of an encryption scheme, and a collection of rejection samplers. All of the results have been mechanized in the Coq proof assistant and the Iris separation logic framework., Comment: Camera-ready POPL submission including additional appendix

The technological development of increasingly larger quantum processors on different quantum platforms raises the problem of how to fairly compare their performance, known as quantum benchmarking of quantum processors. This is a challenge that computer scientists have already faced when comparing classical processors, leading to the development of various mathematical tools to address it, but also to the identification of the limits of this problem. In this work, we briefly review the most important aspects of both classical processor benchmarks and the metrics comprising them, providing precise definitions and analyzing the quality attributes that they should exhibit. Subsequently, we analyze the intrinsic properties that characterize the paradigm of quantum computing and hinder the naive transfer of strategies from classical benchmarking. However, we can still leverage some of the lessons learned such as the quality attributes of a \textit{good} benchmark. Additionally, we review some of the most important metrics and benchmarks for quantum processors proposed in the literature, assessing what quality attributes they fulfill. Finally, we propose general guidelines for quantum benchmarking. These guidelines aim to pave the way for establishing a roadmap towards standardizing the performance evaluation of quantum devices, ultimately leading to the creation of an organization akin to the Standard Performance Evaluation Corporation (SPEC)., Comment: 24 pages, 4 figures

Interferometric experiments designed to detect the highly redshifted 21-cm signal from neutral hydrogen are producing increasingly stringent constraints on the 21-cm power spectrum, but some k-modes remain systematics-dominated. Mutual coupling is a major systematic that must be overcome in order to detect the 21-cm signal, and simulations that reproduce effects seen in the data can guide strategies for mitigating mutual coupling. In this paper, we analyse 12 nights of data from the Hydrogen Epoch of Reionization Array and compare the data against simulations that include a computationally efficient and physically motivated semi-analytic treatment of mutual coupling. We find that simulated coupling features qualitatively agree with coupling features in the data; however, coupling features in the data are brighter than the simulated features, indicating the presence of additional coupling mechanisms not captured by our model. We explore the use of fringe-rate filters as mutual coupling mitigation tools and use our simulations to investigate the effects of mutual coupling on a simulated cosmological 21-cm power spectrum in a "worst case" scenario where the foregrounds are particularly bright. We find that mutual coupling contaminates a large portion of the "EoR Window", and the contamination is several orders-of-magnitude larger than our simulated cosmic signal across a wide range of cosmological Fourier modes. While our fiducial fringe-rate filtering strategy reduces mutual coupling by roughly a factor of 100 in power, a non-negligible amount of coupling cannot be excised with fringe-rate filters, so more sophisticated mitigation strategies are required., Comment: 19 pages, 12 figures, submitted to MNRAS

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.

Machine learning (ML) applied to routine patient monitoring within intensive care units (ICUs) has the potential to improve care by providing clinicians with novel insights into each patient's health and expected response to interventions. This paper applies deep learning to a large volume of unlabeled electrocardiogram (ECG) telemetry signals, which are commonly used for continuous patient monitoring in hospitals but have important differences from the standard, single time-point 12-lead ECG used in many prior machine learning studies. We applied self-supervised learning to pretrain a spectrum of deep networks on approximately 147,000 hours of ECG telemetry data. Our approach leverages this dataset to train models that significantly improve performance on four distinct downstream tasks compared with direct supervised learning using labeled data. These pretrained models enable medically useful predictions and estimates in smaller patient cohorts that are typically limited by the scarcity of labels. Notably, we demonstrate that our pretrained networks can continuously annotate ECG telemetry signals, thereby providing monitoring capabilities that are often unavailable due to the requirement for specialized expertise and time-consuming professional annotations., Comment: 17 pages, 9 figures

Chance constrained stochastic model predictive controllers (CC-SMPC) trade off full constraint satisfaction for economical plant performance under uncertainty. Previous CC-SMPC works are over-conservative in constraint violations leading to worse economic performance. Other past works require a-priori information about the uncertainty set, limiting their application. This paper considers a discrete LTI system with hard constraints on inputs and chance constraints on states, with unknown uncertainty distribution, statistics, or samples. This work proposes a novel adaptive online update rule to relax the state constraints based on the time-average of past constraint violations, to achieve reduced conservativeness in closed-loop. Under an ideal control policy assumption, it is proven that the time-average of constraint violations asymptotically converges to the maximum allowed violation probability. The method is applied for optimal battery energy storage system (BESS) dispatch in a grid connected microgrid with PV generation and load demand, with chance constraints on BESS state-of-charge (SOC). Realistic simulations show the superior electricity cost saving potential of the proposed method as compared to the traditional economic MPC without chance constraints, and a state-of-the-art approach with chance constraints. We satisfy the chance constraints non-conservatively in closed-loop, effectively trading off increased cost savings with minimal adverse effects on BESS lifetime., Comment: 16 pages, 3 figures, 3 tables, Submitted to IEEE Transactions on Control Systems Technology

As frontier AI models advance, policy proposals for safe AI development are gaining increasing attention from researchers and policymakers. This paper explores the current integration in the AI supply chain, focusing on vertical relationships and strategic partnerships among AI labs, cloud providers, chip manufacturers, and lithography companies. It aims to lay the groundwork for a deeper understanding of the implications of various governance interventions, including antitrust measures. The study has two main contributions. First, it profiles 25 leading companies in the AI supply chain, analyzing 300 relationships and noting 80 significant mergers and acquisitions along with 40 antitrust cases. Second, we discuss potential market definitions and the integration drivers based on the observed trends. The analysis reveals predominant horizontal integration through natural growth rather than acquisitions and notable trends of backward vertical integration in the semiconductor supply chain. Strategic partnerships are also significant downstream, especially between AI companies and cloud providers, with large tech companies often pursuing conglomerate integration by acquiring specialized AI startups or forming alliances with frontier AI labs. To further understand the strategic partnerships in the industry, we provide three brief case studies featuring companies like OpenAI and Nvidia. We conclude by posing open research questions on market dynamics and possible governance interventions, such as licensing and safety audits., Comment: This is a preliminary version of the paper. Comments are welcome. E-mail: t6aguirre@gmail.com

We provide a detailed exposition of our computational framework designed for the accurate calculation of real-frequency dynamical correlation functions of the single-impurity Anderson model (AM) in the regime of weak to intermediate coupling. Using quantum field theory within the Keldysh formalism to directly access the self-energy and dynamical susceptibilities in real frequencies, as detailed in our recent publication (https://doi.org/10.1103/PhysRevB.109.115128), the primary computational challenge is the full three-dimensional real-frequency dependence of the four-point vertex. Our codebase provides a fully MPI+OpenMP parallelized implementation of the functional renormalization group (fRG) and the self-consistent parquet equations within the parquet approximation. It leverages vectorization to handle the additional complexity imposed by the Keldysh formalism, using optimized data structures and highly performant integration routines. Going beyond the results shown in the previous publication, the code includes functionality to perform fRG calculations in the multiloop framework, at arbitrary loop order, including self-consistent self-energy iterations. Moreover, implementations of various regulators, such as hybridization, interaction, frequency, and temperature are supplied., Comment: 22 pages, 7 figures, 2 tables

We present Tachis, a higher-order separation logic to reason about the expected cost of probabilistic programs. Inspired by the uses of time credits for reasoning about the running time of deterministic programs, we introduce a novel notion of probabilistic cost credit. Probabilistic cost credits are a separation logic resource that can be used to pay for the cost of operations in programs, and that can be distributed across all possible branches of sampling instructions according to their weight, thus enabling us to reason about expected cost. The representation of cost credits as separation logic resources gives Tachis a great deal of flexibility and expressivity. In particular, it permits reasoning about amortized expected cost by storing excess credits as potential into data structures to pay for future operations. Tachis further supports a range of cost models, including running time and entropy usage. We showcase the versatility of this approach by applying our techniques to prove upper bounds on the expected cost of a variety of probabilistic algorithms and data structures, including randomized quicksort, hash tables, and meldable heaps. All of our results have been mechanized using Coq, Iris, and the Coquelicot real analysis library.

The KEYSTONE project aims to enhance our understanding of solar-like oscillators by delivering a catalogue of global asteroseismic parameters (${\Delta\nu}$ and ${\nu_{\rm max}}$) for 173 stars, comprising mainly dwarfs and subgiants, observed by the K2 mission in its short-cadence mode during campaigns 6-19. We derive atmospheric parameters and luminosities using spectroscopic data from TRES, astrometric data from $\textit{Gaia}$, and the infrared flux method (IRFM) for a comprehensive stellar characterisation. Asteroseismic parameters are robustly extracted using three independent methods, complemented by an iterative refinement of the spectroscopic analyses using seismic ${\log g}$ values to enhance parameter accuracy. Our analysis identifies new detections of solar-like oscillations in 159 stars, providing an important complement to already published results from previous campaigns. The catalogue provides homogeneously derived atmospheric parameters and luminosities for the majority of the sample. Comparison between spectroscopic ${T_{\rm eff}}$ and those obtained from the IRFM demonstrates excellent agreement. The iterative approach to spectroscopic analysis significantly enhances the accuracy of the stellar properties derived., Comment: 22 pages, 18 figures, accepted for publication in Astronomy & Astrophysics (A&A)

The Super-Kamiokande and T2K collaborations present a joint measurement of neutrino oscillation parameters from their atmospheric and beam neutrino data. It uses a common interaction model for events overlapping in neutrino energy and correlated detector systematic uncertainties between the two datasets, which are found to be compatible. Using 3244.4 days of atmospheric data and a beam exposure of $19.7(16.3) \times 10^{20}$ protons on target in (anti)neutrino mode, the analysis finds a 1.9$\sigma$ exclusion of CP-conservation (defined as $J_{CP}=0$) and a preference for the normal mass ordering., Comment: 12 pages, 4 figures

Stellar spin down is a critical yet poorly understood component of stellar evolution. In particular, results from the Kepler Mission imply that mature age, solar-type stars have inefficient magnetic braking, resulting in a stalled spin down rate. However, a large number of precise asteroseismic ages are needed for mature ($\geq$ 3Gyr) stars in order to probe the regime where traditional and stalled spin-down models differ. In this paper, we present a new asteroseismic benchmark star for gyrochronology discovered using reprocessed Kepler short cadence data. KIC 11029516 (Papayu) is a bright ($K_{p}$ = 9.6 mag) solar-type star with well-measured rotation period (21.1$\pm$0.8 days) from spot modulation using 4 years of Kepler long cadence data. We combine asteroseismology and spectroscopy to obtain $T_{eff}=5888\pm100$ K, $\rm{[Fe/H]} = 0.30 \pm 0.06\,$ dex, $M = 1.24 \pm 0.05 M_{\odot}$, $R = 1.34 \pm 0.02 R_{\odot}$ and age of 4.0 $\pm$ 0.4 Gyr, making Papayu one of the most similar stars to the Sun in terms of temperature and radius with an asteroseismic age and a rotation period measured from spot modulation. We find that Papayu sits at the transition of where traditional and weakened spin-down models diverge. A comparison with stars of similar zero-age main-sequence temperatures supports previous findings that weakened spin-down models are required to explain the ages and rotation periods of old solar-type stars.

Context: Traditional one-dimensional (1D) hydrostatic model atmospheres introduce systematic modelling errors into spectroscopic analyses of FGK-type stars. Aims: We present an updated version of the STAGGER-grid of 3D model atmospheres, and explore the accuracy of post-processing methods in preparation for spectral synthesis. Methods: New and old models were (re)computed following an updated workflow, including an updated opacity binning technique. Spectroscopic tests were performed in 3D LTE for a grid of 216 fictitious Fe I lines, spanning a wide range in oscillator strength, excitation potential and central wavelength, and eight model atmospheres that cover the stellar atmospheric parameter range (Teff, log g, [Fe/H]) of FGK-type stars. Using this grid, the impact of vertical and horizontal resolution, and temporal sampling of model atmospheres on spectroscopic diagnostics was tested. Results: We find that downsampling the horizontal mesh from its original size of 240 x 240 grid cells to 80 x 80 cells, i.e. sampling every third grid cell, introduces minimal errors on the equivalent width and normalized line flux across the line and stellar parameter space. Regarding temporal sampling, we find that sampling ten statistically independent snapshots is sufficient to accurately model the shape of spectral line profiles. For equivalent widths, a subsample consisting of only two snapshots is sufficient, introducing an abundance error of less than 0.015 dex. Conclusions: We have computed 32 new model atmospheres and recomputed 116 old model atmospheres present in the original grid. The public release of the STAGGER-grid contains 243 models, excluding models with [Fe/H] = -4.00, and the processed snapshots can be used to improve the accuracy of spectroscopic analyses.

Selective, accurate, fast, and with minimal usage of instrumentation has become paramount nowadays in areas of environmental monitoring. Here, we chemically modified fluorescent graphene quantum dots (GQDs) and trained a Machine Learning (ML) algorithm for the selective quantification of Hg2+ and Fe3+ ions present within real water samples. The probe is obtained by an electrosynthesis of CVD graphene in the presence of urea, followed by the functionalization with 1-nitroso-2-naphthol (NN). The functionalization with NN moieties dramatically improve selectivity and sensitivity toward Hg2+ and Fe3+, as demonstrated by LODs as low as 0.001 mg L-1 and 0.003 mg L-1; respectively. Time-dependent density-functional theory (TD-DFT) reveals that the NN molecules within the GQDs are responsible of the florescence emission of the probe. The emission spectra profiles exhibited distinct characteristics between Hg2+ and Fe3+ enabling the ML model to precisely quantify and differentiate between both analytes present in natural and drinking waters. The ML results were further validated by measurements via cold vapor-atomic fluorescence spectroscopy and UV-vis spectroscopy. The efficiency of the ML model eliminates the necessity of extensive training values and validations, making it a reliable tool for precisely quantifying the presence of Fe and Hg ions in real water samples.