Search

The EdResearch for Action "Overview Series" summarizes the research on key topics to provide K-12 education decision makers and advocates with an evidence base to ground discussions about how to best serve students. This brief discusses the central question: How can schools and districts promote the educational and social-emotional well-being of the diverse population of immigrant-origin students? Key insights are arranged in the following sections: (1) breaking down the issue; (2) evidence-based practices; and (3) practices to avoid. [This brief was co-prepared by Re-Imagining Migration and UC Santa Barbara, The Gevirtz School Graduate School of Education.]

Fusion is a potentially transformational energy technology, which promises limitless clean energy. Yet, it requires continued scientific and technological development to realize its potential. The conditions necessary for fusion energy gain in terms of the product of plasma pressure $P$ and confinement time $\tau$ have been known for many decades. An underappreciated fact is that pulsed magnetic fusion has demonstrated $P \tau$ performance on par with laser-driven ICF and tokamaks despite receiving only a small fraction of investment relative to those concepts. In light of this demonstrated performance, well-established scaling relations, and opportunities for further innovations, here we advocate for pulsed magnetic fusion as the most attractive path towards commercialization of fusion energy.

We present the discovery of 118 new ultracool dwarf candidates, discovered using a new machine learning tool, named \texttt{SMDET}, applied to time series images from the Wide-field Infrared Survey Explorer. We gathered photometric and astrometric data to estimate each candidate's spectral type, distance, and tangential velocity. This sample has a photometrically estimated spectral class distribution of 28 M dwarfs, 64 L dwarfs, and 18 T dwarfs. We also identify a T subdwarf candidate, two extreme T subdwarf candidates, and two candidate young ultracool dwarfs. Five objects did not have enough photometric data for any estimations to be made. To validate our estimated spectral types, spectra were collected for 2 objects, yielding confirmed spectral types of T5 (estimated T5) and T3 (estimated T4). Demonstrating the effectiveness of machine learning tools as a new large-scale discovery technique., Comment: 14 pages, 8 figures, 2 tables, extended table 1, accepted to American Astronomical Journal

We study carbon-aware spatiotemporal workload management, which seeks to address the growing environmental impact of data centers. We formalize this as an online problem called spatiotemporal online allocation with deadline constraints ($\mathsf{SOAD}$), in which an online player completes a workload (e.g., a batch compute job) by moving and scheduling the workload across a network subject to a deadline $T$. At each time step, a service cost function is revealed, representing, e.g., the carbon intensity of servicing a workload at each location, and the player must irrevocably decide the current allocation. Furthermore, whenever the player moves the allocation, it incurs a movement cost defined by a metric space $(X,d)$ that captures, e.g., the overhead of migrating a compute job. $\mathsf{SOAD}$ formalizes the open problem of combining general metrics and deadline constraints in the online algorithms literature, unifying problems such as metrical task systems and online search. We propose a competitive algorithm for $\mathsf{SOAD}$ along with a matching lower bound that proves it is optimal. Our main algorithm, ${\rm C{\scriptsize ARBON}C{\scriptsize LIPPER}}$, is a learning-augmented algorithm that takes advantage of predictions (e.g., carbon intensity forecasts) and achieves an optimal consistency-robustness trade-off. We evaluate our proposed algorithms for carbon-aware spatiotemporal workload management on a simulated global data center network, showing that ${\rm C{\scriptsize ARBON}C{\scriptsize LIPPER}}$ significantly improves performance compared to baseline methods and delivers meaningful carbon reductions., Comment: 50 pages, 21 figures

We present the design and observations of low resolution JWST/NIRSpec PRISM spectroscopy from the Ultradeep NIRSpec and NIRCam ObserVations before the Epoch of Reionization (UNCOVER) Cycle 1 JWST Treasury program. Targets are selected using JWST/NIRCam photometry from UNCOVER and other programs, and cover a wide range of categories and redshifts to ensure the legacy value of the survey. These categories include the first galaxies at $z\gtrsim10$, faint galaxies during the Epoch of Reionization ($z\sim6-8$), high redshift AGN ($z\gtrsim6$), Population III star candidates, distant quiescent and dusty galaxies ($1\lesssim z \lesssim 6$), and filler galaxies sampling redshift--color--magnitude space from $z\sim 0.1-13$. Seven NIRSpec MSA masks across the extended Abell 2744 cluster were observed, along with NIRCam parallel imaging in 8 filters (F090W, F115W, F150W, F200W, F277W, F356W, F410M, F444W, F480M) over a total area of ~26 arcmin$^2$, overlapping existing HST coverage from programs including the Hubble Frontier Fields and BUFFALO. We successfully observed 553 objects down to $m_{\mathrm{F444W}}\sim30\mathrm{AB}$, and by leveraging mask overlaps, we reach total on-target exposure times ranging from 2.4-16.7h. We demonstrate the success rate and distribution of confirmed redshifts, and also highlight the rich information revealed by these ultradeep spectra for a subset of our targets. An updated lens model of Abell 2744 is also presented, including 14 additional spectroscopic redshifts and finding a total cluster mass of $M_{\mathrm{SL}}=(2.1\pm0.3)\times10^{15}\,\mathrm{M}_{\odot}$. We publicly release reduced 1D and 2D spectra for all objects observed in Summer 2023 along with a spectroscopic redshift catalog and the updated lens model of the cluster (https://jwst-uncover.github.io/DR4.html)., Comment: 19 pages, 9 figures, 4 tables, submitted to ApJ, comments welcome! Data available at: https://jwst-uncover.github.io/DR4.html (v2: figure format correction)

Modern artificial intelligence (AI) systems are powered by foundation models. This paper presents a new set of foundation models, called Llama 3. It is a herd of language models that natively support multilinguality, coding, reasoning, and tool usage. Our largest model is a dense Transformer with 405B parameters and a context window of up to 128K tokens. This paper presents an extensive empirical evaluation of Llama 3. We find that Llama 3 delivers comparable quality to leading language models such as GPT-4 on a plethora of tasks. We publicly release Llama 3, including pre-trained and post-trained versions of the 405B parameter language model and our Llama Guard 3 model for input and output safety. The paper also presents the results of experiments in which we integrate image, video, and speech capabilities into Llama 3 via a compositional approach. We observe this approach performs competitively with the state-of-the-art on image, video, and speech recognition tasks. The resulting models are not yet being broadly released as they are still under development.

This letter illustrates the opinion of the molecular dynamics (MD) community on the need to adopt a new FAIR paradigm for the use of molecular simulations. It highlights the necessity of a collaborative effort to create, establish, and sustain a database that allows findability, accessibility, interoperability, and reusability of molecular dynamics simulation data. Such a development would democratize the field and significantly improve the impact of MD simulations on life science research. This will transform our working paradigm, pushing the field to a new frontier. We invite you to support our initiative at the MDDB community (https://mddbr.eu/community/)

We present the preliminary design of GMagAO-X, the first-light high-contrast imager planned for the Giant Magellan Telescope. GMagAO-X will realize the revolutionary increase in spatial resolution and sensitivity provided by the 25 m GMT. It will enable, for the first time, the spectroscopic characterization of nearby potentially habitable terrestrial exoplanets orbiting late-type stars. Additional science cases include: reflected light characterization of mature giant planets; measurement of young extrasolar giant planet variability; characterization of circumstellar disks at unprecedented spatial resolution; characterization of benchmark stellar atmospheres at high spectral resolution; and mapping of resolved objects such as giant stars and asteroids. These, and many more, science cases will be enabled by a 21,000 actuator extreme adaptive optics system, a coronagraphic wavefront control system, and a suite of imagers and spectrographs. We will review the science-driven performance requirements for GMagAO-X, which include achieving a Strehl ratio of 70% at 800 nm on 8th mag and brighter stars, and post-processed characterization at astrophysical flux-ratios of 1e-7 at 4 lambda/D (26 mas at 800 nm) separation. We will provide an overview of the resulting mechanical, optical, and software designs optimized to deliver this performance. We will also discuss the interfaces to the GMT itself, and the concept of operations. We will present an overview of our end-to-end performance modeling and simulations, including the control of segment phasing, as well as an overview of prototype lab demonstrations. Finally, we will review the results of Preliminary Design Review held in February, 2024., Comment: Presented at SPIE Astronomical Telescopes

We report the discovery of a high velocity, very low-mass star or brown dwarf whose kinematics suggest it is unbound to the Milky Way. CWISE J124909.08+362116.0 was identified by citizen scientists in the Backyard Worlds: Planet 9 program as a high proper motion ($\mu$ $=$ 0''9/yr) faint red source. Moderate resolution spectroscopy with Keck/NIRES reveals it to be a metal-poor early L subdwarf with a large radial velocity ($-$103$\pm$10 km/s), and its estimated distance of 125$\pm$8 pc yields a speed of 456$\pm$27 km/s in the Galactic rest frame, near the local escape velocity for the Milky Way. We explore several potential scenarios for the origin of this source, including ejection from the Galactic center $\gtrsim$3 Gyr in the past, survival as the mass donor companion to an exploded white dwarf. acceleration through a three-body interaction with a black hole binary in a globular cluster, and accretion from a Milky Way satellite system. CWISE J1249+3621 is the first hypervelocity very low mass star or brown dwarf to be found, and the nearest of all such systems. It may represent a broader population of very high velocity, low-mass objects that have undergone extreme accelerations., Comment: 17 pages, 3 figures, accepted for publication in Astrophysical Journal Letters

The scorching, arid northeastern state of Ceará, Brazil has long been known for growing cashews and coconuts. Now, it's defied expectations by cultivating one of the world's best public elementary school systems, despite high rates of poverty. How Sobral transformed its public school system and attained near-universal literacy offers lessons for communities everywhere. With 85 elementary schools and almost 34,000 students, Sobral now dominates national assessments in reading and math--outscoring even affluent students in Saõ Paulo, Brazil's financial center. In 2000, only 48% of Sobral's second-graders were reading at grade level. By 2004, that figure had almost doubled to 92%, with an average of 95% in the years since (until 2020 pandemic school closures). Since 2014, the average Sobral fifth grader has scored not just "proficient" but "advanced" on Brazil's national proficiency test (National Basic Education Assessment System, or SAEB). Sobral's story is one of system-wide transformation. It's a tale of a community that, over many years, changed every aspect of its primary education system. It features a grand vision and bold political leadership. It speaks to the power of aligned instructional systems, deep investments in educators, and a culture of love, support, and high expectations. It's a multi-faceted story that demonstrates the possibility of achieving near-universal literacy, even in resource-constrained environments.

SEERNet digital learning platforms (DLPs) are developing new infrastructure to support research in authentic contexts where student learning is happening. In order to contextualize this work within the larger field, we trace historical precedents along four main categories: data repositories, data collection services, research design interfaces, and research communities. By situating this innovative movement alongside its predecessors, we can identify the opportunities for SEERNet and others to progress and sustain the mission of making research more scalable, equitable, and rigorous.

In differential privacy (DP) mechanisms, it can be beneficial to release "redundant" outputs, in the sense that a quantity can be estimated by combining different combinations of privatized values. Indeed, this structure is present in the DP 2020 Decennial Census products published by the U.S. Census Bureau. With this structure, the DP output can be improved by enforcing self-consistency (i.e., estimators obtained by combining different values result in the same estimate) and we show that the minimum variance processing is a linear projection. However, standard projection algorithms are too computationally expensive in terms of both memory and execution time for applications such as the Decennial Census. We propose the Scalable Efficient Algorithm for Best Linear Unbiased Estimate (SEA BLUE), based on a two step process of aggregation and differencing that 1) enforces self-consistency through a linear and unbiased procedure, 2) is computationally and memory efficient, 3) achieves the minimum variance solution under certain structural assumptions, and 4) is empirically shown to be robust to violations of these structural assumptions. We propose three methods of calculating confidence intervals from our estimates, under various assumptions. We apply SEA BLUE to two 2010 Census demonstration products, illustrating its scalability and validity., Comment: 21 pages before references and appendices, 35 pages total, 2 figures and 6 tables

We present the first homogeneous release of several thousand Type Ia supernovae (SNe Ia), all having spectroscopic classification, and spectroscopic redshifts for half the sample. This release, named the "DR2", contains 3628 nearby (z < 0.3) SNe Ia discovered, followed and classified by the Zwicky Transient Facility survey between March 2018 and December 2020. Of these, 3000 have good-to-excellent sampling and 2667 pass standard cosmology light-curve quality cuts. This release is thus the largest SN Ia release to date, increasing by an order of magnitude the number of well characterized low-redshift objects. With the "DR2", we also provide a volume-limited (z < 0.06) sample of nearly a thousand SNe Ia. With such a large, homogeneous and well controlled dataset, we are studying key current questions on SN cosmology, such as the linearity SNe Ia standardization, the SN and host dependencies, the diversity of the SN Ia population, and the accuracy of the current light-curve modeling. These, and more, are studied in detail in a series of articles associated with this release. Alongside the SN Ia parameters, we publish our force-photometry gri-band light curves, 5138 spectra, local and global host properties, observing logs, and a python tool to ease use and access of these data. The photometric accuracy of the "DR2" is not yet suited for cosmological parameter inference, which will follow as "DR2.5" release. We nonetheless demonstrate that the multi-thousand SN Ia Hubble Diagram has a typical 0.15 mag scatter., Comment: ZTF SN Ia DR2 release paper. Submitted to A&A (ZTF DR2 Special Issue). Already 1 response to referee

In the early stages of drug discovery, decisions regarding which experiments to pursue can be influenced by computational models. These decisions are critical due to the time-consuming and expensive nature of the experiments. Therefore, it is becoming essential to accurately quantify the uncertainty in machine learning predictions, such that resources can be used optimally and trust in the models improves. While computational methods for drug discovery often suffer from limited data and sparse experimental observations, additional information can exist in the form of censored labels that provide thresholds rather than precise values of observations. However, the standard approaches that quantify uncertainty in machine learning cannot fully utilize censored labels. In this work, we adapt ensemble-based, Bayesian, and Gaussian models with tools to learn from censored labels by using the Tobit model from survival analysis. Our results demonstrate that despite the partial information available in censored labels, they are essential to accurately and reliably model the real pharmaceutical setting.

This document summarizes the context and main outcomes of the discussions that took place during the NSF-UKRI bilateral workshop on Quantum Information Science in Chemistry, held on 12-13 February 2024, in Alexandria, Virginia (US). The workshop was jointly funded by the National Science Foundation (NSF) and UK Research and Innovation (UKRI) through the Engineering and Physical Sciences Research Council (EPSRC). It brought together scientific delegations from the United States of America (US) and the United Kingdom (UK)., Comment: 43 pages, 6 figures

Chemotactic biological or synthetic active matter shapes its environment by secretions of chemical signals from its self-propelled constituents, like cells, organisms or active colloids. From this indirect interaction collective effects emerge that can be used by the agents to migrate collectively, to form patterns or to search for targets more efficiently. Here, we use paradigmatic models to study the efficiency of collective search strategies of a large group of motile agents that release during their movement repulsive auto-chemotactic signals forcing them to move away from high concentrations of the chemical clue. We show that the repulsive chemotactic interactions improve the search efficiency, measured by the mean first passage time to find a randomly located target, by orders of magnitude depending on the strength of the chemotactic coupling. The mechanism for this improvement relies on two factors: the increase of the persistence length due to the agent's self-interaction with its own chemotactic field and by a more homogeneous distribution of the agents due to their mutual indirect repulsion mediated by the chemotactic field. At stronger particle-field coupling the chemotactic searchers self-organize into ballistically moving bands reminiscent of search-chains formed in search and rescue operations, whose efficiency depends on the number of searchers involved. Our comprehensive study of collective search strategies of large groups of interacting agents is not only relevant for chemotactic active matter but also for a wide range of fields like ethology, information engineering, robotics, and social engineering., Comment: 15 pages, 11 figures

This paper proposes two levels of preheating for the inflaton that is non-minimally coupled with gravity. The first level, later named by the quadratic regime, corresponds to the matter-dominated era and is responsible for draining the inflaton's energy density. The second level, which we will call the quartic regime, corresponds to the radiation-dominated era and is responsible for the reheating of the universe. We investigate the behavior of non-renormalizable higher dimension operators in both the quadratic and quartic regimes. In the quadratic regime, the certain order $n$ in the non-renormalizable higher-dimension operator could lead to an efficient preheating. On the other hand, the non-renormalizable higher dimension operators in the quartic regime are extremely inefficient for any order of $n$. In our work, we also introduce a mechanism controlled by the characteristic momentum $\alpha$ to suppress the particle production during preheating. Additionally, we emphasized the significance of the small momentum of the particles produced during preheating for the abundance of primordial black holes. This result favors the efficient preheating in the quadratic regime. Finally, we evaluate two modes of the reheating temperature, which differ based on the preheating efficiency during the quadratic regime.

We derive analytical expressions to describe how light is frequency-shifted when interacting with ultrasound within scattering media, due to the modulation of the refractive index induced by the ultrasound pressure waves. The model is validated through Monte Carlo simulations, works for high ultrasound pressures, and allows for many simultaneous ultrasound waves or frequency components, which is important due to the non-linear propagation effects in tissue. We also provide critical insights into how the ultrasound properties can be optimized for an enhanced efficiency of the light to be frequency-shifted, facilitating applications in ultrasound optical tomography and other photonic diagnostic techniques.

We present the results of the Large Binocular Telescope Satellites Of Nearby Galaxies Survey (LBT-SONG) ``Far Sample,'' including survey completeness estimates. We find 10 satellite candidates in the inner virial regions of 13 star-forming galaxies outside the Local Group. The hosts are at distances between $\sim 5-11$ Mpc and have stellar masses in the little explored range of $\sim 5 \times 10^8 - 5\times 10^{10}~\text{M}_{\odot}$. Among the 10 satellite candidates, 3 are new discoveries in this survey. In this paper, we characterize the properties of 8 low-mass satellite candidates, including the 3 new discoveries but excluding 2 well-studied massive satellites. Of the 8 low-mass dwarfs, optical colors from the LBT imaging and measurements in the ultraviolet with GALEX suggest that 2 show signs of active star formation, and 6 are likely quenched (although some may still have H\textsc{i} gas reservoirs). Notably, we report the discovery of an ultrafaint dwarf candidate, NGC 672 dwD, with $\text{M}_{\text{V}} = -6.6$ and an estimated stellar mass of $5.6 \times 10^4 ~\text{M}_{\odot}$ if its association with the host is confirmed. It is spatially coincident with a weak detection of H\textsc{i}, with $\text{M}_{\text{HI}}/\text{M}_{\text{*}} \sim 1$. If confirmed, it would be the least luminous known ultrafaint satellite to be so gas-rich. The prevalence of quenched satellites in our sample suggests there are environmental effects at work in lower mass hosts that are similar to those at play in Milky Way-size hosts, although the preponderance of H\textsc{i} detections is at odds with the paucity of H\textsc{i} detections in Milky Way satellites. By robustly measuring our survey completeness function, we are able to compare our observational results to predictions from theory, finding good agreement with the Cold Dark Matter galaxy evolution paradigm., Comment: 18 pages, 9 figures

The JWST and ALMA have detected emission lines from the ionized interstellar medium (ISM), including [OII], [OIII], and hydrogen Balmer series lines, in some of the first galaxies at z>6. These measurements present an opportunity to better understand galaxy assembly histories and may allow important tests of state-of-the-art galaxy formation simulations. It is challenging, however, to model these lines in their proper cosmological context given the huge dynamic range in spatial scales involved. In order to meet this challenge, we introduce a novel sub-grid line emission modeling framework. The framework uses the high-z zoom-in simulation suite from the Feedback in Realistic Environments (FIRE) collaboration. The line emission signals from HII regions within each simulated FIRE galaxy are modeled using the semi-analytic HIILines code. A machine learning, Mixture Density Network, approach is then used to determine the conditional probability distribution for the line luminosity to stellar-mass ratio from the HII regions around each simulated stellar particle given its age, metallicity, and its galaxy's total stellar mass. This conditional probability distribution can then be applied to predict the line luminosities around stellar particles in lower resolution, yet larger volume cosmological simulations. As an example, we apply this approach to the Illustris-TNG simulations at z=6. The resulting predictions for the [OII], [OIII], and Balmer line luminosities as a function of star-formation rate agree well with current observations. Our predictions differ, however, from related work in the literature which lack detailed sub-grid ISM models. This highlights the importance of our multi-scale simulation modeling framework. Finally, we provide forecasts for future line luminosity function measurements from the JWST and quantify the cosmic variance in such surveys., Comment: 19 pages, 12 figures

We prove that a unital shift equivalence induces a graded isomorphism of Leavitt path algebras when the shift equivalence satisfies an alignment condition. This yields another step towards confirming the Graded Classification Conjecture. Our proof uses the bridging bimodule developed by Abrams, the fourth-named author and Tomforde, as well as a general lifting result for graded rings that we establish here. This general result also allows us to provide simplified proofs of two important recent results: one independently proven by Arnone and Va{\v s} through other means that the graded $K$-theory functor is full, and the other proven by Arnone and Corti\~nas that there is no unital graded homomorphism between a Leavitt algebra and the path algebra of a Cuntz splice., Comment: 13 pages

We compute the equivariant K-theory of torus fixed points of Cherkis bow varieties of affine type A. We deduce formulas for the generating series of the Euler numbers of these varieties and observe their modularity in certain cases. We also obtain refined formulas on the motivic level for a class of bow varieties strictly containing Nakajima quiver varieties. These series hence generalise results of Nakajima-Yoshioka. As a special case, we obtain formulas for certain Zastava spaces. We define a parabolic analogue of Nekrasov's partition function and find an equation relating it to the classical partition function., Comment: 32 pages. Comments are welcome

We revisit the theory of timelike and null geodesics in the (extended) Kerr spacetime. This work is a sequel to a recent paper by Cie\'{s}lik, Hackmann, and Mach, who applied the so-called Biermann-Weierstrass formula to integrate Kerr geodesic equations expressed in Boyer-Lindquist coordinates. We show that a formulation based on the Biermann-Weierstrass theorem can also be applied in horizon-penetrating Kerr coordinates, resulting in solutions that are smooth across Kerr horizons. Horizon-penetrating Kerr coordinates allow for an explicit continuation of timelike and null geodesics between appropriate regions of the maximal analytic extension of the Kerr spacetime. A part of this work is devoted to a graphic visualisation of such geodesics., Comment: 22 pages, 10 figures

Reinforcement learning agents can achieve superhuman performance in static tasks but are costly to train and fragile to task changes. This limits their deployment in real-world scenarios where training experience is expensive or the context changes through factors like sensor degradation, environmental processes or changing mission priorities. Lifelong reinforcement learning aims to improve sample efficiency and adaptability by studying how agents perform in evolving problems. The difficulty that these changes pose to an agent is rarely measured directly, however. Agent performances can be compared across a change, but this is often prohibitively expensive. We propose Change-Induced Regret Proxy (CHIRP) metrics, a class of metrics for approximating a change's difficulty while avoiding the high costs of using trained agents. A relationship between a CHIRP metric and agent performance is identified in two environments, a simple grid world and MetaWorld's suite of robotic arm tasks. We demonstrate two uses for these metrics: for learning, an agent that clusters MDPs based on a CHIRP metric achieves $17\%$ higher average returns than three existing agents in a sequence of MetaWorld tasks. We also show how a CHIRP can be calibrated to compare the difficulty of changes across distinctly different environments., Comment: 8 pages, 9 figures

Although best-fit is known to be slow, it excels at optimizing memory space utilization. Interestingly, by keeping the free memory region at the top of the memory, the process of memory allocation and deallocation becomes approximately 34.86% faster while also maintaining external fragmentation at minimum.

In the last decade, the first law of binary black hole mechanics played an important unifying role in the gravitational two-body problem. More recently, binary black hole scattering and the application of high-energy physics methods have provided a new avenue into this classical problem. In this Letter, we connect these two themes by extending the first law to the case of scattering orbits. We present derivations based on classical S-matrix, Hamiltonian, and pseudo-Hamiltonian methods, the last of which allows us to include dissipative effects for the first time. Finally, a "boundary to bound" map links this first law to the traditional bound-orbit version. Through this map a little-known observable for scatter orbits, the elapsed proper time, is mapped to the Detweiler redshift for bound orbits., Comment: 5 pages + supplemental material

The polynomials of degree $\frac{p-1}{2}$ of range sum $p$ was determined in {\tt arXiv:2311.06136 [math.NT]} for large enough primes. We extend this result by reducing the lower bound for the primes to $23$ by introducing a new and elementary way of estimating sums of Legendre symbols., Comment: 12 pages

Anisotropies of the Sunyaev Zel'dovich (SZ) effect serve as a powerful probe of the thermal history of the universe. At high redshift, hot galactic outflows driven by supernovae (SNe) can inject a significant amount of thermal energy into the intergalactic medium, causing a strong $y$-type distortion of the CMB spectrum through inverse Compton scattering. The resulting anisotropies of the $y$-type distortion are sensitive to key physical properties of high-$z$ galaxies pertaining to the launch of energetic SNe-driven outflows, such as the efficiency and the spatio-temporal clustering of star formation. We develop a simple analytic framework to calculate anisotropies of $y$-type distortion associated with SNe-powered outflows of galaxies at $z>6$. We show that galactic outflows are likely the dominant source of thermal energy injection, compared to contributions from reionized bubbles and gravitational heating. We further show that next-generation CMB experiments such as LiteBIRD can detect the contribution to $y$ anisotropies from high-$z$ galactic outflows through the cross-correlation with surveys of Lyman-break galaxies by e.g. the Roman Space Telescope. Our analysis and forecasts demonstrate that thermal SZ anisotropies are a promising probe of SNe feedback in early star-forming galaxies., Comment: 6 pages, 3 figures, comments welcome!

Achieving high-precision measurements on near-term quantum devices is critical for advancing quantum computing applications. In this paper, we explore several practical techniques to enhance measurement accuracy using randomized measurements, focusing on minimizing shot overhead, circuit overhead, measurement noise, and time-dependent measurement noise. Our approach leverages locally biased random measurements to reduce shot overhead, in addition to repeated settings and parallel quantum detector tomography to reduce circuit overhead and mitigate measurement noise. Additionally, we employ a blended scheduling technique to mitigate time-dependent measurement noise. We demonstrate the effectiveness of these techniques through a case study on the molecular energy estimation of the BODIPY molecule using the Hartree-Fock state on an IBM Eagle r3 computer, showcasing significant improvements in measurement precision. These strategies pave the way for more reliable and accurate quantum computations, particularly in applications requiring precise molecular energy calculations., Comment: 15 pages, 8 figures

The cores of stars are the cosmic furnaces where light elements are fused into heavier nuclei. The fusion of hydrogen to helium initially powers all stars. The ashes of the fusion reactions are then predicted to serve as fuel in a series of stages, eventually transforming massive stars into a structure of concentric shells. These are composed of natal hydrogen on the outside, and consecutively heavier compositions inside, predicted to be dominated by helium, carbon/oxygen, oxygen/neon/magnesium, and oxygen/silicon/sulphur. Silicon and sulphur are fused into inert iron, leading to the collapse of the core and either a supernova explosion or the direct formation of a black hole. Stripped stars, where the outer hydrogen layer has been removed and the internal He-rich layer (in Wolf-Rayet WN stars) or even the C/O layer below it (in Wolf-Rayet WC/WO stars) are exposed, provide evidence for this shell structure, and the cosmic element production mechanism it reflects. The types of supernova explosions that arise from stripped stars embedded in shells of circumstellar material (most notably Type Ibn supernovae from stars with outer He layers, and Type Icn supernovae from stars with outer C/O layers) confirm this scenario. However, direct evidence for the most interior shells, which are responsible for the production of elements heavier than oxygen, is lacking. Here, we report the discovery of the first-of-its-kind supernova arising from a star peculiarly stripped all the way to the silicon and sulphur-rich internal layer. Whereas the concentric shell structure of massive stars is not under debate, it is the first time that such a thick, massive silicon and sulphur-rich shell, expelled by the progenitor shortly before the SN explosion, has been directly revealed., Comment: 48 pages, 12 figures and 10 tables. Submitted to a high-impact journal. The reduced spectra and photometry will be made available via the journal webpage and the WISeREP archive after the acceptance of the paper