Search

A digital information explosion has transformed cities' residential and educational markets in ways that are still being uncovered. Although urban stratification scholars have increasingly scrutinized whether emerging digital platforms disrupt or reproduce longstanding segregation patterns, direct links between one theoretically important form of digital information--school quality data--and neighborhood and school segregation are rarely drawn. To clarify these dynamics, we leverage an exogenous digital information shock, in which the Los Angeles Times' website revealed measures of a particularly important school quality proxy--schools' value-added effectiveness--for nearly all elementary schools in the Los Angeles Unified School District. Results suggest that although the information shock had no detectable effects on residential sorting or neighborhood racial segregation, it did exert modest effects on school sorting--particularly for Latino and Asian students--albeit not in ways that materially diminished school racial segregation because the racial compositions of high and low value-added schools were broadly similar both before and after the information shock. We conclude that the urban stratification implications of digital information may be more nuanced than often appreciated, with effects shaped by racial heterogeneity in both constraints and preferences vis-à-vis specific types of information and operating through mechanisms beyond residential segregation.

The use of $\alpha$-tantalum in superconducting circuits has enabled a considerable improvement of the coherence time of transmon qubits. The standard approach to grow $\alpha$-tantalum thin films on silicon involves heating the substrate, which takes several hours per deposition and prevents the integration of this material with wafers containing temperature-sensitive components. We report a detailed experimental study of an alternative growth method of $\alpha$-tantalum on silicon, which is achieved at room temperature through the use of a niobium seed layer. Despite a substantially higher density of oxygen-rich grain boundaries in the films sputtered at room temperature, resonators made from these films are found to have state-of-the-art quality factors, comparable to resonators fabricated from tantalum grown at high temperature. This finding challenges previous assumptions about correlations between material properties and microwave loss of superconducting thin films, and opens a new avenue for the integration of tantalum into fabrication flows with limited thermal budget.

The Breakthrough Listen program is, to date, the most extensive search for technological life beyond Earth. As part of this goal, over the past nine years it has surveyed thousands of nearby stars, close to 100 nearby galaxies, and a variety of exotic and solar system objects with telescopes around the world, including the Robert C. Byrd Green Bank Telescope (GBT) in West Virginia. The goal is to find evidence of technosignatures of other civilizations, such as narrowband Doppler drifting radio signals. Despite the GBT's location in a radio-quiet zone, the primary challenge of this search continues to be the high quantities of human-generated radio-frequency interference (RFI), and the ability to pick out genuinely promising candidates from it. Here we present a novel search method aimed at finding these `needle-in-a-haystack' type signals, applied to 9,684 observation cadences of 3,077 stars (each observed with one or more of the L, S, C, and X band receivers) from the GBT archive. We implement a low-complexity statistical process to vet out RFI and highlight signals that, upon visual inspection, appear more promising than those from previous analyses. Our work returns candidate signals found previously using both traditional and machine learning algorithms, as well as many promising ones not previously identified. This analysis represents the largest dataset searched for technosignatures to date, and highlights the efficacy that traditional (non-machine-learning) algorithms continue to have in these types of technosignature searches. We find that less than 1% of stars host transmitters brighter than 0.3 Arecibo radar equivalents broadcasting in our direction over the frequency band covered., Comment: 24 pages, 17 figures. Submitted to Astronomy & Astrophysics

Despite large language models (LLMs) being known to exhibit bias against non-mainstream varieties, there are no known labeled datasets for sentiment analysis of English. To address this gap, we introduce BESSTIE, a benchmark for sentiment and sarcasm classification for three varieties of English: Australian (en-AU), Indian (en-IN), and British (en-UK). Using web-based content from two domains, namely, Google Place reviews and Reddit comments, we collect datasets for these language varieties using two methods: location-based and topic-based filtering. Native speakers of the language varieties manually annotate the datasets with sentiment and sarcasm labels. Subsequently, we fine-tune nine large language models (LLMs) (representing a range of encoder/decoder and mono/multilingual models) on these datasets, and evaluate their performance on the two tasks. Our results reveal that the models consistently perform better on inner-circle varieties (i.e., en-AU and en-UK), with significant performance drops for en-IN, particularly in sarcasm detection. We also report challenges in cross-variety generalisation, highlighting the need for language variety-specific datasets such as ours. BESSTIE promises to be a useful evaluative benchmark for future research in equitable LLMs, specifically in terms of language varieties. The BESSTIE datasets, code, and models are currently available on request, while the paper is under review. Please email aditya.joshi@unsw.edu.au., Comment: 10 pages, 7 figures, under review

The search for radio technosignatures is an anomaly detection problem: candidate signals represent needles of interest in the proverbial haystack of radio-frequency interference (RFI). Current search frameworks find an enormity of false-positive signals, especially in large surveys, requiring manual follow-up to a sometimes prohibitive degree. Unsupervised learning provides an algorithmic way to winnow the most anomalous signals from the chaff, as well as group together RFI signals that bear morphological similarities. We present GLOBULAR (Grouping Low-frequency Observations By Unsupervised Learning After Reduction) clustering, a signal processing method that uses HDBSCAN to reduce the false-positive rate and isolate outlier signals for further analysis. When combined with a standard narrowband signal detection and spatial filtering pipeline, such as turboSETI, GLOBULAR clustering offers significant improvements in the false-positive rate over the standard pipeline alone, suggesting dramatic potential for the amelioration of manual follow-up requirements for future large surveys. By removing RFI signals in regions of high spectral occupancy, GLOBULAR clustering may also enable the detection of signals missed by the standard pipeline. We benchmark our method against the Choza et al. (2024) turboSETI-only search of 97 nearby galaxies at L-band, demonstrating a false-positive hit reduction rate of 93.1% and a false-positive event reduction rate of 99.3%., Comment: 20 pages, 14 figures, submitted to AJ

Human excrement composting (HEC) is a sustainable strategy for human excrement (HE) management that recycles nutrients and mitigates health risks while reducing reliance on freshwater, fossil fuels, and fertilizers. We present a comprehensive microbial time series analysis of HEC and show that the initial gut-like microbiome of HEC systems transitions to a microbiome similar to soil and traditional compost in fifteen biological replicates tracked weekly for one year., Comment: Main text: 9 pages, 2 figures; Extended data: 10 figures; Supplemental Text: 32 pages, 8 figures, 2 tables

Rapid and accurate initialization of qubits, reset, is a crucial building block for various tasks in quantum information processing, such as quantum error-correction and estimation of statistics of noisy quantum devices with many qubits. We demonstrate unconditional reset of a frequency-tunable transmon qubit that simultaneously resets multiple excited states by utilizing a metamaterial waveguide engineered to provide a cold bath over a wide spectral range, while providing strong protection against Purcell decay of the qubit. We report reset error below 0.13% (0.16%) when prepared in the first (second) excited state of the transmon within 88ns. Additionally, through the sharp roll-off in the density of states of the metamaterial waveguide, we implement a leakage reduction unit that selectively resets the transmon's second excited state to 0.285(3)% residual population within 44ns while acting trivially in the computational subspace as an identity operation that preserves encoded information with an infidelity of 0.72(1)%., Comment: 17 pages, 11 figures

Dissipative cat qubits are a promising physical platform for quantum computing, since their large noise bias can enable more hardware-efficient quantum error correction. In this work we theoretically study the long-term prospects of a hybrid cat-transmon quantum computing architecture where dissipative cat qubits play the role of data qubits, and error syndromes are measured using ancillary transmon qubits. The cat qubits' noise bias enables more hardware-efficient quantum error correction, and the use of transmons allows for practical, high-fidelity syndrome measurement. While correction of the dominant cat Z errors with a repetition code has recently been demonstrated in experiment, here we show how the architecture can be scaled beyond a repetition code. In particular, we propose a cat-transmon entangling gate that enables the correction of residual cat X errors in a thin rectangular surface code, so that logical error can be arbitrarily suppressed by increasing code distance. We numerically estimate logical memory performance, finding significant overhead reductions in comparison to architectures without biased noise. For example, with current state-of-the-art coherence, physical error rates of $10^{-3}$ and noise biases in the range $10^{3} - 10^{4}$ are achievable. With this level of performance, the qubit overhead required to reach algorithmically-relevant logical error rates with the cat-transmon architecture matches that of an unbiased-noise architecture with physical error rates in the range $10^{-5} - 10^{-4}$., Comment: 13+14 pages, 8+9 figures

Populations are heterogeneous, deviating in numerous ways. Phenotypic diversity refers to the range of traits or characteristics across a population, where for cells this could be the levels of signalling, movement and growth activity, etc. Clearly, the phenotypic distribution -- and how this changes over time and space -- could be a major determinant of population-level dynamics. For instance, across a cancerous population, variations in movement, growth, and ability to evade death may determine its growth trajectory and response to therapy. In this review, we discuss how classical partial differential equation (PDE) approaches for modelling cellular systems and collective cell migration can be extended to include phenotypic structuring. The resulting non-local models -- which we refer to as phenotype-structured partial integro-differential equations (PS-PIDEs) -- form a sophisticated class of models with rich dynamics. We set the scene through a brief history of structured population modelling, and then review the extension of several classic movement models -- including the Fisher-KPP and Keller-Segel equations -- into a PS-PIDE form. We proceed with a tutorial-style section on derivation, analysis, and simulation techniques. First, we show a method to formally derive these models from underlying agent-based models. Second, we recount travelling waves in PDE models of spatial spread dynamics and concentration phenomena in non-local PDE models of evolutionary dynamics, and combine the two to deduce phenotypic structuring across travelling waves in PS-PIDE models. Third, we discuss numerical methods to simulate PS-PIDEs, illustrating with a simple scheme based on the method of lines and noting the finer points of consideration. We conclude with a discussion of future modelling and mathematical challenges.

Existing benchmarks often fail to account for linguistic diversity, like language variants of English. In this paper, we share our experiences from our ongoing project of building a sentiment classification benchmark for three variants of English: Australian (en-AU), Indian (en-IN), and British (en-UK) English. Using Google Places reviews, we explore the effects of various sampling techniques based on label semantics, review length, and sentiment proportion and report performances on three fine-tuned BERT-based models. Our initial evaluation reveals significant performance variations influenced by sample characteristics, label semantics, and language variety, highlighting the need for nuanced benchmark design. We offer actionable insights for researchers to create robust benchmarks, emphasising the importance of diverse sampling, careful label definition, and comprehensive evaluation across linguistic varieties., Comment: Under review

In this paper, we develop novel techniques that can be used to alter the architecture of a neural network, while maintaining the function it represents. Such operations are known as function preserving transforms and have proven useful in transferring knowledge between networks to evaluate architectures quickly, thus having applications in efficient architectures searches. Our methods allow the integration of residual connections into function preserving transforms, so we call them R2R. We provide a derivation for R2R and show that it yields competitive performance with other function preserving transforms, thereby decreasing the restrictions on deep learning architectures that can be extended through function preserving transforms. We perform a comparative analysis with other function preserving transforms such as Net2Net and Network Morphisms, where we shed light on their differences and individual use cases. Finally, we show the effectiveness of R2R to train models quickly, as well as its ability to learn a more diverse set of filters on image classification tasks compared to Net2Net and Network Morphisms.

In both animal and cell populations, the presence of leaders often underlies the success of collective migration processes, which we characterise by a group maintaining a cohesive configuration that consistently moves toward a target. We extend a recent non-local hyperbolic model for follower-leader systems to investigate different degrees of leadership. Specifically, we consider three levels of leadership: indifferent leaders, who do not alter their movement according to followers; observant leaders, who attempt to remain connected with the followers, but do not allow followers to affect their desired alignment; and persuadable leaders, who integrate their attempt to reach some target with the alignment of all neighbours, both followers and leaders. A combination of analysis and numerical simulations is used to investigate under which conditions each degree of leadership allows successful collective movement to a destination. We find that the indifferent leaders' strategy can result in a cohesive and target-directed migration only for short times. Observant and persuadable leaders instead provide robust guidance, showing that the optimal leader behavior depends on the connection between the migrating individuals: if alignment is low, greater follower influence on leaders is beneficial for successful guidance; otherwise, it can be detrimental and may generate various unsuccessful swarming dynamics.

Millimeter emitting dust grains have sizes that make them susceptible to drift in protoplanetary disks due to a difference between their orbital speed and that of the gas. The characteristic drift timescale depends on the surface density of the gas. By comparing disk radii measurements from ALMA CO and continuum observations at millimeter wavelengths, the gas surface density profile and dust drift time can be self-consistently determined. We find that profiles which match the measured dust mass have very short drift timescales, an order of magnitude or more shorter than the stellar age, whereas profiles for disks that are on the cusp of gravitational instability, defined via the minimum value of the Toomre parameter, Qmin ~ 1-2, have drift timescales comparable to the stellar lifetime. This holds for disks with masses of dust > 5 MEarth across a range of absolute ages from less than 1 Myr to over 10 Myr. The inferred disk masses scale with stellar mass as Mdisk ~ Mstar / 5Qmin. This interpretation of the gas and dust disk sizes simultaneously solves two long standing issues regarding the dust lifetime and exoplanet mass budget and suggests that we consider millimeter wavelength observations as a window into an underlying population of particles with a wide size distribution in secular evolution with a massive planetesimal disk., Comment: 18 pages, 9 figures, accepted for publication in ApJ

Cat qubits, a type of bosonic qubit encoded in a harmonic oscillator, can exhibit an exponential noise bias against bit-flip errors with increasing mean photon number. Here, we focus on cat qubits stabilized by two-photon dissipation, where pairs of photons are added and removed from a harmonic oscillator by an auxiliary, lossy buffer mode. This process requires a large loss rate and strong nonlinearities of the buffer mode that must not degrade the coherence and linearity of the oscillator. In this work, we show how to overcome this challenge by coloring the loss environment of the buffer mode with a multi-pole filter and optimizing the circuit to take into account additional inductances in the buffer mode. Using these techniques, we achieve near-ideal enhancement of cat-qubit bit-flip times with increasing photon number, reaching over $0.1$ seconds with a mean photon number of only $4$. Concurrently, our cat qubit remains highly phase coherent, with phase-flip times corresponding to an effective lifetime of $T_{1,\text{eff}} \simeq 70$ $\mu$s, comparable with the bare oscillator lifetime. We achieve this performance even in the presence of an ancilla transmon, used for reading out the cat qubit states, by engineering a tunable oscillator-ancilla dispersive coupling. Furthermore, the low nonlinearity of the harmonic oscillator mode allows us to perform pulsed cat-qubit stabilization, an important control primitive, where the stabilization can remain off for a significant fraction (e.g., two thirds) of a $3~\mathrm{\mu s}$ cycle without degrading bit-flip times. These advances are important for the realization of scalable error-correction with cat qubits, where large noise bias and low phase-flip error rate enable the use of hardware-efficient outer error-correcting codes., Comment: Comments welcome!

In order to solve problems of practical importance, quantum computers will likely need to incorporate quantum error correction, where a logical qubit is redundantly encoded in many noisy physical qubits. The large physical-qubit overhead typically associated with error correction motivates the search for more hardware-efficient approaches. Here, using a microfabricated superconducting quantum circuit, we realize a logical qubit memory formed from the concatenation of encoded bosonic cat qubits with an outer repetition code of distance $d=5$. The bosonic cat qubits are passively protected against bit flips using a stabilizing circuit. Cat-qubit phase-flip errors are corrected by the repetition code which uses ancilla transmons for syndrome measurement. We realize a noise-biased CX gate which ensures bit-flip error suppression is maintained during error correction. We study the performance and scaling of the logical qubit memory, finding that the phase-flip correcting repetition code operates below threshold, with logical phase-flip error decreasing with code distance from $d=3$ to $d=5$. Concurrently, the logical bit-flip error is suppressed with increasing cat-qubit mean photon number. The minimum measured logical error per cycle is on average $1.75(2)\%$ for the distance-3 code sections, and $1.65(3)\%$ for the longer distance-5 code, demonstrating the effectiveness of bit-flip error suppression throughout the error correction cycle. These results, where the intrinsic error suppression of the bosonic encodings allows us to use a hardware-efficient outer error correcting code, indicate that concatenated bosonic codes are a compelling paradigm for reaching fault-tolerant quantum computation., Comment: Comments on the manuscript welcome!

We give a sufficient condition on a positive integer $m$ for every stratum of a given real toric hyperplane arrangement to contain a rational point of denominator $m$. As a consequence, we give a sufficient condition on $m$ for the degree $m$ Frobenius pushforward of the structure sheaf on a smooth toric variety to contain all possible summands in the Picard group., Comment: 8 pages, 2 figures

Social behavior across animal species ranges from simple pairwise interactions to thousands of individuals coordinating goal-directed movements. Regardless of the scale, these interactions are governed by the interplay between multimodal sensory information and the internal state of each animal. Here, we investigate how animals use multiple sensory modalities to guide social behavior in the highly social zebrafish (Danio rerio) and uncover the complex features of pairwise interactions early in development. To identify distinct behaviors and understand how they vary over time, we developed a new hidden Markov model with constrained linear-model emissions to automatically classify states of coordinated interaction, using the movements of one animal to predict those of another. We discovered that social behaviors alternate between two interaction states within a single experimental session, distinguished by unique movements and timescales. Long-range interactions, akin to shoaling, rely on vision, while mechanosensation underlies rapid synchronized movements and parallel swimming, precursors of schooling. Altogether, we observe spontaneous interactions in pairs of fish, develop novel hidden Markov modeling to reveal two fundamental interaction modes, and identify the sensory systems involved in each. Our modeling approach to pairwise social interactions has broad applicability to a wide variety of naturalistic behaviors and species and solves the challenge of detecting transient couplings between quasi-periodic time series., Comment: 29 pages, 6 figures, 3 supplementary figures. *Joint first author, +Joint last author

Entangling microwave and optical photons is one of the promising ways to realize quantum transduction through quantum teleportation. This paper investigates the entanglement of microwave-optical photon pairs generated from an electro-optomechanical system driven by a blue-detuned pulsed Gaussian pump. The photon pairs are obtained through weak parametric-down-conversion, and their temporal correlation is revealed by the second-order correlation function. We then study the discrete variable entanglement encoded in the time bin degree of freedom, where entanglement is identified by Bell inequality violation. Furthermore, we estimate the laser-induced heating and show that the pulse-pumped system features lower heating effects while maintaining a reasonable coincidence photon counting rate.

Large language models (LLMs) are useful tools with the capacity for performing specific types of knowledge work at an effective scale. However, LLM deployments in high-risk and safety-critical domains pose unique challenges, notably the issue of ``hallucination,'' where LLMs can generate fabricated information. This is particularly concerning in settings such as drug safety, where inaccuracies could lead to patient harm. To mitigate these risks, we have developed and demonstrated a proof of concept suite of guardrails specifically designed to mitigate certain types of hallucinations and errors for drug safety, and potentially applicable to other medical safety-critical contexts. These guardrails include mechanisms to detect anomalous documents to prevent the ingestion of inappropriate data, identify incorrect drug names or adverse event terms, and convey uncertainty in generated content. We integrated these guardrails with an LLM fine-tuned for a text-to-text task, which involves converting both structured and unstructured data within adverse event reports into natural language. This method was applied to translate individual case safety reports, demonstrating effective application in a pharmacovigilance processing task. Our guardrail framework offers a set of tools with broad applicability across various domains, ensuring LLMs can be safely used in high-risk situations by eliminating the occurrence of key errors, including the generation of incorrect pharmacovigilance-related terms, thus adhering to stringent regulatory and quality standards in medical safety-critical environments., Comment: 27 pages, 6 figures, 4 tables and supplementary material provided

We report on spectroscopic and photometric observations of the AM CVn system ASASSN-21br, which was discovered in outburst by the All-Sky Automated Survey for Supernovae in February 2021. The outburst lasted for around three weeks, and exhibited a pronounced brightness dip for $\approx$ 4 days, during which the spectra showed a sudden transition from emission- to absorption-line dominated. Only $\approx$ 60 AM CVn systems with derived orbital periods are found in the Galaxy, therefore increasing the sample of AM CVn systems with known orbital periods is of tremendous importance to (1) constrain the physical mechanisms of their outbursts and (2) establish a better understanding of the low-frequency background noise of future gravitational wave surveys. Time-resolved photometry taken during the outburst of ASASSN-21br showed modulation with a period of around 36.65 minutes, which is likely the superhump or orbital period of the system. Time-resolved spectroscopy taken with the Southern African Large Telescope did not show any sign of periodicity in the He I absorption lines. This is possibly due to the origin of these lines in the outbursting accretion disc, which makes it challenging to retrieve periodicity from the spectral lines. Future follow up spectral observations during quiescence might allow us better constrain the orbital period of ASASSN-21br., Comment: 14 pages, 13 figures, accepted at MNRAS

Optomechanical crystals (OMCs) enable coherent interactions between optical photons and microwave acoustic phonons, and represent a platform for implementing quantum transduction between microwave and optical signals. Optical absorption-induced thermal noise at cryogenic (millikelvin) temperatures is one of the primary limitations of performance for OMC-based quantum transducers. Here, we address this challenge with a two-dimensional silicon OMC resonator that is side-coupled to a mechanically detached optical waveguide, realizing a six-fold reduction in the heating rate of the acoustic resonator compared to prior state-of-the-art, while operating in a regime of high optomechanical-backaction and millikelvin base temperature. This reduced heating translates into a demonstrated phonon-to-photon conversion efficiency of 93.1 $\pm$ 0.8% at an added noise of 0.25 $\pm$ 0.01 quanta, representing a significant advance toward quantum-limited microwave-optical frequency conversion and optically-controlled quantum acoustic memories.

Objective: To enhance the efficiency and accuracy of information retrieval from pharmacovigilance (PV) databases by employing Large Language Models (LLMs) to convert natural language queries (NLQs) into Structured Query Language (SQL) queries, leveraging a business context document. Materials and Methods: We utilized OpenAI's GPT-4 model within a retrieval-augmented generation (RAG) framework, enriched with a business context document, to transform NLQs into syntactically precise SQL queries. Each NLQ was presented to the LLM randomly and independently to prevent memorization. The study was conducted in three phases, varying query complexity, and assessing the LLM's performance both with and without the business context document. Results: Our approach significantly improved NLQ-to-SQL accuracy, increasing from 8.3\% with the database schema alone to 78.3\% with the business context document. This enhancement was consistent across low, medium, and high complexity queries, indicating the critical role of contextual knowledge in query generation. Discussion: The integration of a business context document markedly improved the LLM's ability to generate accurate and contextually relevant SQL queries. Performance achieved a maximum of 85\% when high complexity queries are excluded, suggesting promise for routine deployment. Conclusion: This study presents a novel approach to employing LLMs for safety data retrieval and analysis, demonstrating significant advancements in query generation accuracy. The methodology offers a framework applicable to various data-intensive domains, enhancing the accessibility and efficiency of information retrieval for non-technical users., Comment: 15 pages, 3 tables, 5 figures

To address the learning crisis and other challenges facing children and youth (those 15-24 years of age) it is critical for governments, multilateral and bilateral funders, other donors, and implementers to have a clear understanding of program costs and cost breakdowns to inform financing decisions. For nearly a decade, the Center for Universal Education (CUE) at the Brookings Institution has led the Childhood Cost Data initiative, a research project focused on the collection, analysis, and use of cost data to increase the volume and quality of funding for programs targeting children and youth. The initiative's end goal is to improve learning and life outcomes for the youngest generation through these advancements. As part of this initiative, Brookings developed the Childhood Cost Calculator (C3), intended to facilitate cost analysis. This study introduces C3, the tool's various dimensions and functionalities, and presents learnings from three case studies from piloting the calculator in the education or early childhood development (ECD) sectors in Cambodia, Ghana, and Honduras. It concludes with suggestions for a way forward that supports funders, implementers, and researchers to better use cost data to make strides in tackling the multiple crises facing children and youth today.

Monte-Carlo Tree Search (MCTS) methods, such as Upper Confidence Bound applied to Trees (UCT), are instrumental to automated planning techniques. However, UCT can be slow to explore an optimal action when it initially appears inferior to other actions. Maximum ENtropy Tree-Search (MENTS) incorporates the maximum entropy principle into an MCTS approach, utilising Boltzmann policies to sample actions, naturally encouraging more exploration. In this paper, we highlight a major limitation of MENTS: optimal actions for the maximum entropy objective do not necessarily correspond to optimal actions for the original objective. We introduce two algorithms, Boltzmann Tree Search (BTS) and Decaying ENtropy Tree-Search (DENTS), that address these limitations and preserve the benefits of Boltzmann policies, such as allowing actions to be sampled faster by using the Alias method. Our empirical analysis shows that our algorithms show consistent high performance across several benchmark domains, including the game of Go., Comment: Camera ready version of NeurIPS2023 paper

Fuzzy Dark Matter (FDM) comprised of ultralight ($m \sim 10^{-22}~\rm{eV}$) boson particles has received significant attention as a viable alternative to Cold Dark Matter (CDM), as it approximates CDM on large scales ($\gtrsim 1$ Mpc) while potentially resolving some of its small-scale problems via kiloparsec-scale quantum interference. However, the most basic FDM model, with one free parameter (the boson mass), is subject to a tension: small boson masses yield the desired cores of dwarf galaxies but underpredict structure in the Lyman-$\alpha$ forest, while large boson masses render FDM effectively identical to CDM. This Catch-22 problem may be alleviated by considering an axion-like particle with attractive particle self-interactions. We simulate an idealized FDM halo with self-interactions parameterized by an energy decay constant $f \sim 10^{15}~\rm{GeV}$ related to the axion symmetry-breaking conjectured to solve the strong-CP problem in particle physics. We observe solitons, a hallmark of FDM, condensing within a broader halo envelope, and find that the density profile and soliton mass depend on self-interaction strength. We propose generalized formulae to extend those from previous works to include self-interactions. We also investigate a critical mass threshold predicted for strong interactions at which the soliton collapses into a compact, unresolved state. We find that the collapse happens quickly and its effects are initially contained to the central region of the halo., Comment: 20 pages, 16 figures; to be submitted to MNRAS

A fundamental feature of collective cell migration is phenotypic heterogeneity which, for example, influences tumour progression and relapse. While current mathematical models often consider discrete phenotypic structuring of the cell population, in-line with the `go-or-grow' hypothesis \cite{hatzikirou2012go, stepien2018traveling}, they regularly overlook the role that the environment may play in determining the cells' phenotype during migration. Comparing a previously studied volume-filling model for a homogeneous population of generalist cells that can proliferate, move and degrade extracellular matrix (ECM) \cite{crossley2023travelling} to a novel model for a heterogeneous population comprising two distinct sub-populations of specialist cells that can either move and degrade ECM or proliferate, this study explores how different hypothetical phenotypic switching mechanisms affect the speed and structure of the invading cell populations. Through a continuum model derived from its individual-based counterpart, insights into the influence of the ECM and the impact of phenotypic switching on migrating cell populations emerge. Notably, specialist cell populations that cannot switch phenotype show reduced invasiveness compared to generalist cell populations, while implementing different forms of switching significantly alters the structure of migrating cell fronts. This key result suggests that the structure of an invading cell population could be used to infer the underlying mechanisms governing phenotypic switching., Comment: 35 pages, 12 figures

The Extreme Universe Space Observatory on a Super Pressure Balloon 1 (EUSO-SPB1) was launched in 2017 April from Wanaka, New Zealand. The plan of this mission of opportunity on a NASA super pressure balloon test flight was to circle the southern hemisphere. The primary scientific goal was to make the first observations of ultra-high-energy cosmic-ray extensive air showers (EASs) by looking down on the atmosphere with an ultraviolet (UV) fluorescence telescope from suborbital altitude (33~km). After 12~days and 4~hours aloft, the flight was terminated prematurely in the Pacific Ocean. Before the flight, the instrument was tested extensively in the West Desert of Utah, USA, with UV point sources and lasers. The test results indicated that the instrument had sensitivity to EASs of approximately 3 EeV. Simulations of the telescope system, telescope on time, and realized flight trajectory predicted an observation of about 1 event assuming clear sky conditions. The effects of high clouds were estimated to reduce this value by approximately a factor of 2. A manual search and a machine-learning-based search did not find any EAS signals in these data. Here we review the EUSO-SPB1 instrument and flight and the EAS search., Comment: 18 pages, 19 figures

Hot Jupiters were many of the first exoplanets discovered in the 1990s, but in the decades since their discovery, the mysteries surrounding their origins remain. Here, we present nine new hot Jupiters (TOI-1855 b, TOI-2107 b, TOI-2368 b, TOI-3321 b, TOI-3894 b, TOI-3919 b, TOI-4153 b, TOI-5232 b, and TOI-5301 b) discovered by NASA's TESS mission and confirmed using ground-based imaging and spectroscopy. These discoveries are the first in a series of papers named the Migration and Evolution of giant ExoPlanets (MEEP) survey and are part of an ongoing effort to build a complete sample of hot Jupiters orbiting FGK stars, with a limiting Gaia $G$-band magnitude of 12.5. This effort aims to use homogeneous detection and analysis techniques to generate a set of precisely measured stellar and planetary properties that is ripe for statistical analysis. The nine planets presented in this work occupy a range of masses (0.55 Jupiter masses (M$_{\rm{J}}$) $<$ M$_{\rm{P}}$ $<$ 3.88 M$_{\rm{J}}$) and sizes (0.967 Jupiter radii (R$_{\rm{J}}$) $<$ R$_{\rm{P}}$ $<$ 1.438 R$_{\rm{J}}$) and orbit stars that range in temperature from 5360 K $<$ Teff $<$ 6860 K with Gaia $G$-band magnitudes ranging from 11.1 to 12.7. Two of the planets in our sample have detectable orbital eccentricity: TOI-3919 b ($e = 0.259^{+0.033}_{-0.036}$) and TOI-5301 b ($e = 0.33^{+0.11}_{-0.10}$). These eccentric planets join a growing sample of eccentric hot Jupiters that are consistent with high-eccentricity tidal migration, one of the three most prominent theories explaining hot Jupiter formation and evolution., Comment: 35 pages, 7 tables, and 14 figures. Submitted to AAS Journals on 2023 Dec 28

Entanglement is an extraordinary feature of quantum mechanics. Sources of entangled optical photons were essential to test the foundations of quantum physics through violations of Bell's inequalities. More recently, entangled many-body states have been realized via strong non-linear interactions in microwave circuits with superconducting qubits. Here we demonstrate a chip-scale source of entangled optical and microwave photonic qubits. Our device platform integrates a piezo-optomechanical transducer with a superconducting resonator which is robust under optical illumination. We drive a photon-pair generation process and employ a dual-rail encoding intrinsic to our system to prepare entangled states of microwave and optical photons. We place a lower bound on the fidelity of the entangled state by measuring microwave and optical photons in two orthogonal bases. This entanglement source can directly interface telecom wavelength time-bin qubits and GHz frequency superconducting qubits, two well-established platforms for quantum communication and computation, respectively., Comment: 14 pages, 12 figures

Optomechanical crystals are a promising device platform for quantum transduction and sensing. Precise targeting of the optical and acoustic resonance frequencies of these devices is crucial for future advances on these fronts. However, fabrication disorder in these wavelength-scale nanoscale devices typically leads to inhomogeneous resonance frequencies. Here we achieve in-situ, selective frequency tuning of optical and acoustic resonances in silicon optomechanical crystals via electric field-induced nano-oxidation using an atomic-force microscope. Our method can achieve a tuning range >2 nm (0.13%) for the optical resonance wavelength in the telecom C-band, and >60 MHz (1.2%) for the acoustic resonance frequency at 5 GHz. The tuning resolution of 1.1 nm for the optical wavelength, and $150$ kHz for the acoustic frequency allows us to spectrally align multiple optomechanical crystal resonators using optimal oxidation patterns determined via an inverse design protocol. Our results establish a method for precise post-fabrication tuning of optomechancical crystals. This technique can enable coupled optomechanical resonator arrays, scalable resonant optomechanical circuits, and frequency matching of microwave-optical quantum transducers.

This paper investigates the potential of AI models, particularly large language models (LLMs), to support knowledge exploration and augment human creativity during ideation. We present "Latent Lab" an interactive tool for discovering connections among MIT Media Lab research projects, emphasizing "exploration" over search. The work offers insights into collaborative AI systems by addressing the challenges of organizing, searching, and synthesizing content. In a user study, the tool's success was evaluated based on its ability to introduce users to an unfamiliar knowledge base, ultimately setting the groundwork for the ongoing advancement of human-AI knowledge exploration systems.

We formulate haptotaxis models of cancer invasion wherein the infiltrating cancer cells can occupy a spectrum of states in phenotype space, ranging from `fully mesenchymal' to `fully epithelial'. The more mesenchymal cells are those that display stronger haptotaxis responses and have greater capacity to modify the extracellular matrix (ECM) through enhanced secretion of matrix-degrading enzymes (MDEs). However, as a trade-off, they have lower proliferative capacity than the more epithelial cells. The framework is multiscale in that we start with an individual-based model that tracks the dynamics of single cells, which is based on a branching random walk over a lattice representing both physical and phenotype space. We formally derive the corresponding continuum model, which takes the form of a coupled system comprising a partial integro-differential equation for the local cell population density function, a partial differential equation for the MDE concentration and an infinite-dimensional ordinary differential equation for the ECM density. Despite the intricacy of the model, we show, through formal asymptotic techniques, that for certain parameter regimes it is possible to carry out a detailed travelling wave analysis and obtain invading fronts with spatial structuring of phenotypes. Precisely, the most mesenchymal cells dominate the leading edge of the invasion wave and the most epithelial (and most proliferative) dominate the rear, representing a bulk tumour population. As such, the model recapitulates similar observations into a front to back structuring of invasion waves into leader-type and follower-type cells, witnessed in an increasing number of experimental studies over recent years.

The impact of the DART spacecraft into Dimorphos, moon of the asteroid Didymos, changed Dimorphos' orbit substantially, largely from the ejection of material. We present results from twelve Earth-based facilities involved in a world-wide campaign to monitor the brightness and morphology of the ejecta in the first 35 days after impact. After an initial brightening of ~1.4 magnitudes, we find consistent dimming rates of 0.11-0.12 magnitudes/day in the first week, and 0.08-0.09 magnitudes/day over the entire study period. The system returned to its pre-impact brightness 24.3-25.3 days after impact through the primary ejecta tail remained. The dimming paused briefly eight days after impact, near in time to the appearance of the second tail. This was likely due to a secondary release of material after re-impact of a boulder released in the initial impact, through movement of the primary ejecta through the aperture likely played a role., Comment: 16 pages, 5 Figures, accepted in the Astrophysical Journal Letters (ApJL) on October 16, 2023

GRS 1747-312 is a bright Low-Mass X-ray Binary in the globular cluster Terzan 6, located at a distance of 9.5 kpc from the Earth. It exhibits regular outbursts approximately every 4.5 months, during which periodic eclipses are known to occur. These eclipses have only been observed in the outburst phase, and are not clearly seen when the source is quiescent. Recent Chandra observations of the source were performed in June 2019 and April, June, and August of 2021. Two of these observations captured the source during its outburst, and showed clear flux decreases at the expected time of eclipse. The other two observations occurred when the source was quiescent. We present the discovery of a dip that occurred during the quiescent state. The dip is of longer duration and its time of occurrence does not fit the ephemeris of the shorter eclipses. We study the physical characteristics of the dip and determine that it has all the properties of an eclipse by an object with a well defined surface. We find that there are several possibilities for the nature of the object causing the 5.3 ks eclipse. First, GRS 1747-312 may be an X-ray triple, with an LMXB orbited by an outer third object, which could be an M-dwarf, brown dwarf, or planet. Second, there could be two LMXBs in close proximity to each other, likely bound together. Whatever the true nature of the eclipser, its presence suggests that the GRS 1747-312 system is unique., Comment: 38 pages, 30 figures, submitted to MNRAS

Although most pregnancies result in a good outcome, complications are not uncommon and can be associated with serious implications for mothers and babies. Predictive modeling has the potential to improve outcomes through better understanding of risk factors, heightened surveillance for high risk patients, and more timely and appropriate interventions, thereby helping obstetricians deliver better care. We identify and study the most important risk factors for four types of pregnancy complications: (i) severe maternal morbidity, (ii) shoulder dystocia, (iii) preterm preeclampsia, and (iv) antepartum stillbirth. We use an Explainable Boosting Machine (EBM), a high-accuracy glass-box learning method, for prediction and identification of important risk factors. We undertake external validation and perform an extensive robustness analysis of the EBM models. EBMs match the accuracy of other black-box ML methods such as deep neural networks and random forests, and outperform logistic regression, while being more interpretable. EBMs prove to be robust. The interpretability of the EBM models reveals surprising insights into the features contributing to risk (e.g. maternal height is the second most important feature for shoulder dystocia) and may have potential for clinical application in the prediction and prevention of serious complications in pregnancy., Comment: 25 pages (including appendix and references), 12 figures, 2 tables. J Healthc Inform Res (2023)

Noise within solid-state systems at low temperatures, where many of the degrees of freedom of the host material are frozen out, can typically be traced back to material defects that support low-energy excitations. These defects can take a wide variety of microscopic forms, and for amorphous materials are broadly described using generic models such as the tunneling two-level systems (TLS) model. Although the details of TLS, and their impact on the low-temperature behavior of materials have been studied since the 1970s, these states have recently taken on further relevance in the field of quantum computing, where the limits to the coherence of superconducting microwave quantum circuits are dominated by TLS. Efforts to mitigate the impact of TLS have thus far focused on circuit design, material selection, and material surface treatment. In this work, we take a new approach that seeks to directly modify the properties of TLS through nanoscale-engineering. This is achieved by periodically structuring the host material, forming an acoustic bandgap that suppresses all microwave-frequency phonons in a GHz-wide frequency band around the operating frequency of a transmon qubit superconducting quantum circuit. For embedded TLS that are strongly coupled to the electric qubit, we measure a pronounced increase in relaxation time by two orders of magnitude when the TLS transition frequency lies within the acoustic bandgap, with the longest $T_1$ time exceeding $5$ milliseconds. Our work paves the way for in-depth investigation and coherent control of TLS, which is essential for deepening our understanding of noise in amorphous materials and advancing solid-state quantum devices., Comment: 11 + 25 pages, 4 + 22 figures, 6 tables; comments welcome!