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The conventional wisdom among educators and literacy gurus is that reading comprehension depends on the acquisition of isolatable, teachable, and generalizable skills. Consequently, many elementary and middle school English classrooms follow the "reading workshop" model, an approach to literacy instruction, with several variations that typically involve teachers spending a few minutes modeling a supposedly important skill before sending students off to practice by reading self-selected but appropriately "leveled" books. This policy brief challenges that orthodoxy. It asserts that, once students have learned to decode, reading books and other texts of any purported "level" with understanding depends more on knowledge than skills and that successful knowledge building requires explicit, carefully sequenced and paced, teacher-directed instruction across multiple subjects, including but not limited to social studies, science, and literature. Key questions asked in this report include: (1) Does reading comprehension depend on acquiring a set of teachable skills?; (2) Do students need practice with "just right" books?; (3) Does letting students choose the books they read foster the motivation necessary to improve reading comprehension?; and (4) Does extended literacy instruction enhance reading comprehension?

Osteoarthritis (OA) is a prevalent degenerative joint disease, with the knee being the most commonly affected joint. Modern studies of knee joint injury and OA often measure biomechanical variables, particularly forces exerted during walking. However, the relationship among gait patterns, clinical profiles, and OA disease remains poorly understood. These biomechanical forces are typically represented as curves over time, but until recently, studies have relied on discrete values (or landmarks) to summarize these curves. This work aims to demonstrate the added value of analyzing full movement curves over conventional discrete summaries. Using data from the Intensive Diet and Exercise for Arthritis (IDEA) study (Messier et al., 2009, 2013), we developed a shape-based representation of variation in the full biomechanical curves. Compared to conventional discrete summaries, our approach yields more powerful predictors of disease progression and relevant clinical traits, as demonstrated by a nested model comparison. Notably, our work is among the first to use movement curves to predict disease progression and to quantitatively evaluate the added value of analyzing full movement curves over conventional discrete summaries

We analyse high-resolution ESPaDOnS/CFHT spectra of 20 very metal-poor stars ([Fe/H]~$<-2.0$) in the solar neighbourhood (within $\sim2$ kpc) selected to be on planar orbits (maximum height of $<4$ kpc). Targets include 11 prograde and 9 retrograde stars, spanning a wide range of eccentricities ($0.20-0.95$). Their chemical abundances are consistent with those observed in the Galactic halo but show a smaller spread, with no notable difference between progrades and retrogrades. This suggests a common chemical evolution and likely a shared formation site (except for one star). In this case, chemical evolution models indicate that the formation site would have had a baryonic mass of $\sim1.4\times10^9\msun$, similar to classical dwarf galaxies. High-energy supernovae and hypernovae are needed to reproduce the [X/Fe] up to the Fe-peak, while fast-rotating massive stars and neutron star merger events explain the [X/Fe] of the neutron-capture elements. The absence of Type Ia supernova signatures suggests a star formation duration of $<1$Gyr. Cosmological zoom-in simulations support the scenario that an in-plane infall of a single system could disperse stars over a wide range of angular momenta during the early Galactic assembly. We propose that these stars originated in a proto-Galactic building block, which we name \textit{Loki}. Less likely, if progrades and retrogrades formed in two different systems, their chemical evolution must have been very similar, with a combined baryonic mass twice that of a single system. The low number of targets and their limited metallicity range prevent us to exclude if these stars share a common progenitor with other detected structures, like GSE. A comparison (primarily [$\alpha$/Fe]) with other VMPs moving in planar orbits suggests multiple systems contributed to the Galactic planar population, presenting some differences in their kinematical parameters., Comment: Submitted to A&A, 21 pages, 14 Figures

Understanding the morphology of galaxies is a critical aspect of astrophysics research, providing insight into the formation, evolution, and physical properties of these vast cosmic structures. Various observational and computational methods have been developed to quantify galaxy morphology, and with the advent of large galaxy simulations, the need for automated and effective classification methods has become increasingly important. This paper investigates the use of Principal Component Analysis (PCA) as an interpretable dimensionality reduction algorithm for galaxy morphology using the IllustrisTNG cosmological simulation dataset with the aim of developing a generative model for galaxies. We first generate a dataset of 2D images and 3D cubes of galaxies from the IllustrisTNG simulation, focusing on the mass, metallicity, and stellar age distribution of each galaxy. PCA is then applied to this data, transforming it into a lower-dimensional image space, where closeness of data points corresponds to morphological similarity. We find that PCA can effectively capture the key morphological features of galaxies, with a significant proportion of the variance in the data being explained by a small number of components. With our method we achieve a dimensionality reduction by a factor of $\sim200$ for 2D images and $\sim3650$ for 3D cubes at a reconstruction accuracy below five percent. Our results illustrate the potential of PCA in compressing large cosmological simulations into an interpretable generative model for galaxies that can easily be used in various downstream tasks such as galaxy classification and analysis., Comment: 13 pages, 9 without appendix, source code on GitHub: https://github.com/ufuk-cakir/MEGS , data on Zenodo: https://zenodo.org/record/8375344 , see also GAMMA: https://github.com/ufuk-cakir/GAMMA

To evaluate the safety and usefulness of deployment protocols for untrusted AIs, AI Control uses a red-teaming exercise played between a protocol designer and an adversary. This paper introduces AI-Control Games, a formal decision-making model of the red-teaming exercise as a multi-objective, partially observable, stochastic game. We also introduce methods for finding optimal protocols in AI-Control Games, by reducing them to a set of zero-sum partially observable stochastic games. We apply our formalism to model, evaluate and synthesise protocols for deploying untrusted language models as programming assistants, focusing on Trusted Monitoring protocols, which use weaker language models and limited human assistance. Finally, we demonstrate the utility of our formalism by showcasing improvements over empirical studies in existing settings, evaluating protocols in new settings, and analysing how modelling assumptions affect the safety and usefulness of protocols., Comment: 7 pages, with appendices

According to the well established hierarchical framework for galaxy evolution, galaxies grow through mergers with other galaxies and the LambdaCDM cosmological model predicts that the stellar halos of galaxies are rich in remnants from minor mergers. The Stellar Streams Legacy Survey has provided a first release of a catalogue with a statistically significant sample of stellar streams in the Local Universe that can be used to study minor mergers and test the cosmological models. The main objective is to compare the results of the observations of stellar tidal streams with the predictions of state-of-the-art cosmological simulations regarding the formation of stellar streams up to a redshift z < 0.02, according to the LambdaCDM model. We use the predictions of the cosmological simulations Copernicus Complexio, TNG50 of the IllustrisTNG project and Auriga to generate 225 mock-images of nearby halos at a distance of 70 Mpc, and search for stellar streams. We compare the obtained stream frequency and characteristics with those obtained from the Stellar Streams Legacy Survey. We find good agreement between the results of analysing real images from the Dark Energy Survey and mock-images from cosmological simulations. We obtained predictions for the detection rate of stellar streams to a surface brightness limit of 35 mag arcsec^-2. The cosmological simulations predict that for a surface brightness limit of 32 mag arcsec^-2 a frequency of almost 70% in the detection of streams around galaxies can be achieved., Comment: 18 pages, 17 figures

The transition energies of the two $1s$-core-excited soft X-ray lines (dubbed q and r) from $1s^2 2s ^1S_{1/2}$ to the respective upper levels $1s(^{2}S)2s2p(^{3}P) ^{2}P_{3/2}$ and $^{2}P_{1/2}$ of Li-like oxygen, fluorine and neon were measured and calibrated using several nearby transitions of He-like ions. The major remaining source of energy uncertainties in monochromators, the periodic fluctuations produced by imperfect angular encoder calibration, is addressed by a simultaneously running photoelectron spectroscopy measurement. This leads to an improved energy determination of 5 parts per million, showing fair agreement with previous theories as well as with our own, involving a complete treatment of the autoionizing states studied here. Our experimental results translate to an uncertainty of only 1.6\,km/s for the oxygen line qr-blend used to determine the outflow velocities of active galactic nuclei, ten times smaller than previously possible., Comment: 7 pages, 4 figures

The region of $N\approx Z\approx 40$ has long been associated with strongly deformed nuclear configurations. The presence of this strong deformation was recently confirmed through lifetime measurements in $N\approx Z$ Sr and Zr nuclei. Theoretically, however, these nuclei present a challenge due to the vast valence space required to incorporate all deformation driving interactions. Recent state-of-the-art predictions indicate a near axial prolate deformation for $N=Z$ and $N=Z+2$ nuclei between $N=Z=36$ and $N=Z=40$. In this work we investigate the shores of this island of deformation through a sub-barrier Coulomb excitation study of the $N=Z+4$ nucleus, \textsuperscript{80}Sr. Extracting a spectroscopic quadrupole moment of $Q_s(2^+_1) = 0.45^{+0.83}_{-0.88}$~eb, we find that \textsuperscript{80}Sr is inconsistent with significant axial prolate deformation. This indicates that the predicted region of strong prolate deformation around $N=Z=40$ is tightly constrained to the quartet of nuclei: \textsuperscript{76,78}Sr and \textsuperscript{78,80}Zr., Comment: Submitted to Physics Letters B

The CONUS+ experiment aims to detect coherent elastic neutrino-nucleus scattering (CEvNS) of reactor antineutrinos on germanium nuclei in the fully coherent regime, continuing on this way the CONUS physics program started at the Brokdorf nuclear power plant, Germany. The CONUS+ setup is installed in the nuclear power plant in Leibstadt, Switzerland, at a distance of 20.7 m from the 3.6 GW thermal power reactor core. The CEvNS signature will be measured with the same four point-contact high-purity germanium (HPGe) detectors produced for the former experiment, however refurbished and with optimized low energy thresholds. To suppress the background in the CONUS+ detectors, the passive and active layers of the original CONUS shield were modified such to fit better to the significantly changed background conditions at the new experimental location. New data acquisition and monitoring systems were developed. A direct network connection between the experiment and the Max-Planck-Institut fur Kernphysik (MPIK) makes it possible to control and monitor data acquisition in real time. The impact of all these modifications is discussed with particular emphasis on the resulting CEvNS signal prediction for the first data collection phase of CONUS+. Prospects of the planned upgrade in a second phase integrating new larger HPGe detectors are also discussed., Comment: 14 pages. 12 figures

In reinforcement learning, specification gaming occurs when AI systems learn undesired behaviors that are highly rewarded due to misspecified training goals. Specification gaming can range from simple behaviors like sycophancy to sophisticated and pernicious behaviors like reward-tampering, where a model directly modifies its own reward mechanism. However, these more pernicious behaviors may be too complex to be discovered via exploration. In this paper, we study whether Large Language Model (LLM) assistants which find easily discovered forms of specification gaming will generalize to perform rarer and more blatant forms, up to and including reward-tampering. We construct a curriculum of increasingly sophisticated gameable environments and find that training on early-curriculum environments leads to more specification gaming on remaining environments. Strikingly, a small but non-negligible proportion of the time, LLM assistants trained on the full curriculum generalize zero-shot to directly rewriting their own reward function. Retraining an LLM not to game early-curriculum environments mitigates, but does not eliminate, reward-tampering in later environments. Moreover, adding harmlessness training to our gameable environments does not prevent reward-tampering. These results demonstrate that LLMs can generalize from common forms of specification gaming to more pernicious reward tampering and that such behavior may be nontrivial to remove., Comment: Make it easier to find samples from the model, and highlight that our operational definition of reward tampering has false positives where the model attempts to complete the task honestly but edits the reward. Add paragraph to conclusion to this effect, and add sentence to figure 1 to this effect

In a previous work (arXiv:2306.05948), we constructed by convex integration examples of energy dissipating solutions to the 2D Euler equations on $\mathbb{R}^2$ with vorticity in the real Hardy space $H^p(\mathbb{R}^2)$. In the present paper, we develop tools that significantly improve that result in two ways: Firstly, we achieve vorticities in $H^p(\mathbb{R}^2)$ in the optimal range $p\in (0,1)$ compared to $(2/3,1)$ in our previous work. Secondly, the solutions constructed here possess compact support and in particular preserve linear and angular momenta., Comment: 37 pages. arXiv admin note: text overlap with arXiv:2306.05948

Energy is a primary constraint in processor design, and much of that energy is consumed in on-chip communication. Communication can be intra-core (e.g., from a register file to an ALU) or inter-core (e.g., over the on-chip network). In this paper, we use the on-chip network (OCN) as a case study for saving on-chip communication energy. We have identified a new way to reduce the OCN's link energy consumption by using line coding, a longstanding technique in information theory. Our line codes, called Low-Energy Line Codes (LELCs), reduce energy by reducing the frequency of voltage transitions of the links, and they achieve a range of energy/performance trade-offs.

We used the monochromatic soft-x-ray beamline P04 at the synchrotron-radiation facility PETRA III to resonantly excite the strongest $2p-3d$ transitions in neon-like Ni XIX ions, $[2p^6]_{J=0} \rightarrow [(2p^5)_{1/2}\,3d_{3/2}]_{J=1}$ and $[2p^6]_{J=0} \rightarrow [(2p^5)_{3/2}\,3d_{5/2}]_{J=1}$, respectively dubbed 3C and 3D, achieving a resolving power of 15\,000 and signal-to-background ratio of 30. We obtain their natural linewidths, with an accuracy of better than 10\%, as well as the oscillator-strength ratio $f(3C)/f(3D)$ = 2.51(11) from analysis of the resonant fluorescence spectra. These results agree with those of previous experiments, earlier predictions, and our own advanced calculations., Comment: 10 pages, 3 figures, 3 tables, published

Exploring the marks left by galactic accretion in the Milky Way helps us understand how our Galaxy was formed. However, finding and studying accreted stars and the galaxies they came from has been challenging. This study uses a simulation from the NIHAO project, which now includes a wider range of chemical compositions, to find better ways to spot these accreted stars. By comparing our findings with data from the GALAH spectroscopic survey, we confirm that the observationally established diagnostics of [Al/Fe] vs. [Mg/Mn] also show a separation of in-situ and accreted stars in the simulation, but stars from different accretion events tend to overlap in this plane even without observational uncertainties. Looking at the relationship between stellar age and linear or logarithmic abundances, such as [Fe/H], we can clearly separate different groups of these stars if the uncertainties in their chemical makeup are less than 0.15 dex and less than 20% for their ages. This method shows promise for studying the history of the Milky Way and other galaxies. Our work highlights how important it is to have accurate measurements of stellar ages and chemical content. It also shows how simulations can help us understand the complex process of galaxies merging and suggest how these events might relate to the differences we see between our Galaxy's thin and thick disk stars. This study provides a way to compare theoretical models with real observations, opening new paths for research in both our own Galaxy and beyond., Comment: 15 pages, 14 figures, submitted to MNRAS. Comments welcome. All code and data to reproduce the analysis and figures can be accessed via https://github.com/svenbuder/Accretion_ Clues_ObsSim

Chiral crystals and molecules were recently predicted to form an intriguing platform for unconventional orbital physics. Here, we report the observation of chirality-driven orbital textures in the bulk electronic structure of CoSi, a prototype member of the cubic B20 family of chiral crystals. Using circular dichroism in soft X-ray angle-resolved photoemission, we demonstrate the formation of a bulk orbital-angular-momentum texture and monopole-like orbital-momentum locking that depends on crystal handedness. We introduce the intrinsic chiral circular dichroism, icCD, as a differential photoemission observable and a natural probe of chiral electron states. Our findings render chiral crystals promising for spin-orbitronics applications., Comment: To be published in Physical Review Letters

Cosmological galaxy formation simulations are powerful tools to understand the complex processes that govern the formation and evolution of galaxies. However, evaluating the realism of these simulations remains a challenge. The two common approaches for evaluating galaxy simulations is either through scaling relations based on a few key physical galaxy properties, or through a set of pre-defined morphological parameters based on galaxy images. This paper proposes a novel image-based method for evaluating the quality of galaxy simulations using unsupervised deep learning anomaly detection techniques. By comparing full galaxy images, our approach can identify and quantify discrepancies between simulated and observed galaxies. As a demonstration, we apply this method to SDSS imaging and NIHAO simulations with different physics models, parameters, and resolution. We further compare the metric of our method to scaling relations as well as morphological parameters. We show that anomaly detection is able to capture similarities and differences between real and simulated objects that scaling relations and morphological parameters are unable to cover, thus indeed providing a new point of view to validate and calibrate cosmological simulations against observed data., Comment: 13 pages, 16 figures, published in MNRAS

To improve privacy and ensure quality-of-service (QoS), deep learning (DL) models are increasingly deployed on Internet of Things (IoT) devices for data processing, significantly increasing the carbon footprint associated with DL on IoT, covering both operational and embodied aspects. Existing operational energy predictors often overlook quantized DL models and emerging neural processing units (NPUs), while embodied carbon footprint modeling tools neglect non-computing hardware components common in IoT devices, creating a gap in accurate carbon footprint modeling tools for IoT-enabled DL. This paper introduces \textit{\carb}, an end-to-end tool for precise carbon footprint estimation in IoT-enabled DL, with deviations as low as 5\% for operational and 3.23\% for embodied carbon footprints compared to actual measurements across various DL models. Additionally, practical applications of \carb~are showcased through multiple user case studies., Comment: 5 figures, 8 tables

The detection of inelastically scattered soft X-rays with high energy resolution usually requires large grating spectrometers. Recently, photoelectron spectrometry for analysis of X-rays (PAX) has been rediscovered for modern spectroscopy experiments at synchrotron light sources. By converting scattered photons to electrons and using an electron energy analyser, the energy resolution for resonant inelastic X-ray scattering (RIXS) becomes decoupled from the X-ray spot size and instrument length. In this work, we develop PAX towards high energy resolution using a modern photoemission spectroscopy setup studying Ba2Cu3O4Cl2 at the Cu L3-edge. We measure a momentum transfer range of 24% of the first Brillouin zone simultaneously. Our results hint at the observation of a magnon excitation below 100 meV energy transfer and show intensity variations related to the dispersion of dd-excitations. With dedicated setups, PAX can become an alternative to the best and largest RIXS instruments, while at the same time opening new opportunities to acquire RIXS at a range of momentum transfers simultaneously and combine it with angle-resolved photoemission spectroscopy in a single instrument.

We present the High-$z$ Evolution of Large and Luminous Objects (HELLO) project, a set of more than 30 high-resolution hydrodynamical cosmological simulations aimed to study Milky Way analogues ($M_\star\sim10^{10-11}$ $\mathrm{M}_\odot$) at high redshift, namely at $z=3.6$ (age $\sim$ 1.7 Gyr) and $z=2$ (age $\sim$ 3.3 Gyr). The HELLO project features an updated scheme for chemical enrichment and the addition of local photoionization feedback processes. Independently of redshift and stellar mass, all galaxies follow a similar evolutionary path: (i) first a smooth progression along the star formation main sequence, where galaxies grow in both stellar mass and size, (ii) a (short) period of intense star formation, which causes a contraction phase in the stellar size, until the galaxies reach their peak star formation rate (SFR), during this period we also witness a significant black hole growth, and (iii) the onset of declining SFRs, which is due to a mix of gas consumption, stellar feedback, and AGN feedback, but with AGN feedback still being subdominant with respect to stellar feedback for energy deposition. The exact phase in which a galaxy in our mass range can be found at a given redshift is set by its gas reservoir and assembly history. Finally, our galaxies are in excellent agreement with several various scaling relations observed with the Hubble Space Telescope and the James Webb Space Telescope, and hence can be used to provide the theoretical framework to interpret current and future observations from these facilities and shed light on the transition from star-forming to quiescent galaxies., Comment: 22 pages, 16 figures, 3 tables, submitted to MNRAS

Connected automated vehicles (CAV), which incorporate vehicle-to-vehicle (V2V) communication into their motion planning, are expected to provide a wide range of benefits for individual and overall traffic flow. A frequent constraint or required precondition is that compatible CAVs must already be available in traffic at high penetration rates. Achieving such penetration rates incrementally before providing ample benefits for users presents a chicken-and-egg problem that is common in connected driving development. Based on the example of a cooperative driving function for bottleneck traffic flows (e.g. at a roadblock), we illustrate how such an evolutionary, incremental introduction can be achieved under transparent assumptions and objectives. To this end, we analyze the challenge from the perspectives of automation technology, traffic flow, human factors and market, and present a principle that 1) accounts for individual requirements from each domain; 2) provides benefits for any penetration rate of compatible CAVs between 0 % and 100 % as well as upward-compatibility for expected future developments in traffic; 3) can strictly limit the negative effects of cooperation for any participant and 4) can be implemented with close-to-market technology. We discuss the technical implementation as well as the effect on traffic flow over a wide parameter spectrum for human and technical aspects., Comment: 8 pages, 7 figures

A graph short-time Fourier transform is defined using the eigenvectors of the graph Laplacian and a graph heat kernel as a window parametrized by a non-negative time parameter $t$. We show that the corresponding Gabor-like system forms a frame for $\mathbb{C}^d$ and give a description of the spectrum of the corresponding frame operator in terms of the graph heat kernel and the spectrum of the underlying graph Laplacian. For two classes of algebraic graphs, we prove the frame is tight and independent of the window parameter $t$., Comment: 12 pages, 4 figures

We report the experimental discovery of orbital vortex lines in the three-dimensional (3D) band structure of a topological semimetal. Combining linear and circular dichroism in soft x-ray angle-resolved photoemission (SX-ARPES) with first-principles theory, we image the winding of atomic orbital angular momentum, thereby revealing - and determining the location of - lines of vorticity in full 3D momentum space. Our observation of momentum-space vortex lines with quantized winding number establishes an analogue to real-space quantum vortices, for instance, in type-II superconductors and certain non-collinear magnets. These results establish multimodal dichroism in SX-ARPES as an approach to trace 3D orbital textures. Our present findings particularly constitute the first imaging of non-trivial quantum-phase winding at line nodes and may pave the way to new orbitronic phenomena in quantum materials

In data science, hypergraphs are natural models for data exhibiting multi-way relations, whereas graphs only capture pairwise. Nonetheless, many proposed hypergraph neural networks effectively reduce hypergraphs to undirected graphs via symmetrized matrix representations, potentially losing important information. We propose an alternative approach to hypergraph neural networks in which the hypergraph is represented as a non-reversible Markov chain. We use this Markov chain to construct a complex Hermitian Laplacian matrix - the magnetic Laplacian - which serves as the input to our proposed hypergraph neural network. We study HyperMagNet for the task of node classification, and demonstrate its effectiveness over graph-reduction based hypergraph neural networks., Comment: 9 pages, 1 figure

The emergence of correlated phenomena arising from the combination of 1$\mathrm{T}$ and 1$\mathrm{H}$ van der Waals layers is the focus of intense research. Here, we synthesize a novel self-stacked 6$\mathrm{R}$ phase in NbSeTe, showing a perfect alternating 1T and 1H layers that grow coherently along the c-direction, as revealed by scanning transmission electron microscopy. Angle resolved photoemission spectroscopy shows a mixed contribution of the trigonal and octahedral Nb bands to the Fermi level. Diffuse scattering reveals temperature-independent short-range charge fluctuations with propagation vector $\mathrm{q_{CO}}$=(0.25,0), derived from the condensation of a longitudinal mode in the 1T layer. We observe that ligand disorder quenches the formation of a charge density wave. Magnetization measurements suggest the presence of an inhomogeneous, short-range magnetic order, further supported by the absence of a clear phase transition in the specific heat. These experimental analyses in combination with \textit{ab initio} calculations indicate that the ground state of 6$\mathrm{R}$-NbSeTe is described by a statistical distribution of short-range charge-modulated and spin-correlated regions driven by ligand disorder. Our results devise a route to synthesize 1$\mathrm{T}$-1$\mathrm{H}$ self-stacked bulk heterostructures to study emergent phases of matter., Comment: 12 pages, including Supplementary Information. 4 figures + 6 supplementary figures

In recent years, the diagnosis of gliomas has become increasingly complex. Analysis of glioma histopathology images using artificial intelligence (AI) offers new opportunities to support diagnosis and outcome prediction. To give an overview of the current state of research, this review examines 83 publicly available research studies that have proposed AI-based methods for whole-slide histopathology images of human gliomas, covering the diagnostic tasks of subtyping (23/83), grading (27/83), molecular marker prediction (20/83), and survival prediction (29/83). All studies were reviewed with regard to methodological aspects as well as clinical applicability. It was found that the focus of current research is the assessment of hematoxylin and eosin-stained tissue sections of adult-type diffuse gliomas. The majority of studies (52/83) are based on the publicly available glioblastoma and low-grade glioma datasets from The Cancer Genome Atlas (TCGA) and only a few studies employed other datasets in isolation (16/83) or in addition to the TCGA datasets (15/83). Current approaches mostly rely on convolutional neural networks (63/83) for analyzing tissue at 20x magnification (35/83). A new field of research is the integration of clinical data, omics data, or magnetic resonance imaging (29/83). So far, AI-based methods have achieved promising results, but are not yet used in real clinical settings. Future work should focus on the independent validation of methods on larger, multi-site datasets with high-quality and up-to-date clinical and molecular pathology annotations to demonstrate routine applicability.

We improve by a factor of 4-20 the energy accuracy of the strongest soft X-ray transitions of Fe XVII ions by resonantly exciting them in an electron beam ion trap with a monochromatic beam at the P04 beamline of the PETRA III synchrotron facility. By simultaneously tracking instantaneous photon-energy fluctuations with a high-resolution photoelectron spectrometer, we minimize systematic uncertainties down to 10-15 meV, or velocity equivalent $\pm\sim$5 km s$^{-1}$ in their rest energies, substantially improving our knowledge of this key astrophysical ion. Our large-scale configuration-interaction computations include more than four million relativistic configurations and agree with the experiment at a level without precedent for a 10-electron system. Thereby, theoretical uncertainties for interelectronic correlations become far smaller than those of quantum electrodynamics (QED) corrections. The present QED benchmark strengthens our trust in future calculations of many other complex atomic ions of interest to astrophysics, plasma physics, and for the development of optical clocks with highly charged ions., Comment: 14 pages, 2 figures, 4 tables, published version

The CONUS experiment studies coherent elastic neutrino nucleus scattering in four 1 kg germanium spectrometers. Low ionization energy thresholds of 210 eV were achieved. The detectors were operated inside an optimized shield at the Brokdorf nuclear power plant which provided a reactor antineutrino flux of up to $2.3\cdot10^{13}$ cm$^{-2}$s$^{-1}$. In the final phase of data collection at this site, the constraints on the neutrino interaction rate were improved by an order of magnitude as compared to the previous CONUS analysis. The new limit of less than 0.34 signal events kg$^{-1}$d$^{-1}$ is within a factor 2 of the rate predicted by the Standard Model., Comment: 8 figures, 4 tables

Humans are capable of strategically deceptive behavior: behaving helpfully in most situations, but then behaving very differently in order to pursue alternative objectives when given the opportunity. If an AI system learned such a deceptive strategy, could we detect it and remove it using current state-of-the-art safety training techniques? To study this question, we construct proof-of-concept examples of deceptive behavior in large language models (LLMs). For example, we train models that write secure code when the prompt states that the year is 2023, but insert exploitable code when the stated year is 2024. We find that such backdoor behavior can be made persistent, so that it is not removed by standard safety training techniques, including supervised fine-tuning, reinforcement learning, and adversarial training (eliciting unsafe behavior and then training to remove it). The backdoor behavior is most persistent in the largest models and in models trained to produce chain-of-thought reasoning about deceiving the training process, with the persistence remaining even when the chain-of-thought is distilled away. Furthermore, rather than removing backdoors, we find that adversarial training can teach models to better recognize their backdoor triggers, effectively hiding the unsafe behavior. Our results suggest that, once a model exhibits deceptive behavior, standard techniques could fail to remove such deception and create a false impression of safety., Comment: updated to add missing acknowledgements