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Coherent control of single photon sources is a key requirement for the advancement of photonic quantum technologies. Among them, nanowire-based quantum dot sources are popular due to their potential for on-chip hybrid integration. Here we demonstrate on-demand single-photon generation ($g^{(2)}(0)(X^{*}) =0.078$ and $g^{(2)}(0)(X)= 0.03$) from resonantly excited InAsP/InP nanowire quantum dots and observe Rabi oscillations in the dot emission, indicating successful coherent manipulation of the excitonic states in the nanowire. We also measure a low emission time jitter for resonant excitation as compared to above-band excitation. This work addresses the long-standing challenge of resonantly exciting nanowire-quantum dots. It paves the way for hybrid quantum photonic integration, enabling spin-photon entanglement and matter memories on-chip.

Detecting non-classical light is a central requirement for photonics-based quantum technologies. Unrivaled high efficiencies and low dark counts have positioned superconducting nanowire single photon detectors (SNSPDs) as the leading detector technology for fiber and integrated photonic applications. However, a central challenge lies in their integration within photonic integrated circuits regardless of material platform or surface topography. Here, we introduce a method based on transfer printing that overcomes these constraints and allows for the integration of SNSPDs onto arbitrary photonic substrates. We prove this by integrating SNSPDs and showing through-waveguide single-photon detection in commercially manufactured silicon and lithium niobate on insulator integrated photonic circuits. Our method eliminates bottlenecks to the integration of high-quality single-photon detectors, turning them into a versatile and accessible building block for scalable quantum information processing., Comment: 11 pages, 12 figures

We provide a simple distribution regression estimator for treatment effects in the difference-in-differences (DiD) design. Our procedure is particularly useful when the treatment effect differs across the distribution of the outcome variable. Our proposed estimator easily incorporates covariates and, importantly, can be extended to settings where the treatment potentially affects the joint distribution of multiple outcomes. Our key identifying restriction is that the counterfactual distribution of the treated in the untreated state has no interaction effect between treatment and time. This assumption results in a parallel trend assumption on a transformation of the distribution. We highlight the relationship between our procedure and assumptions with the changes-in-changes approach of Athey and Imbens (2006). We also reexamine two existing empirical examples which highlight the utility of our approach., Comment: 49 pages, 10 figures, 8 tables

Observing exoplanets through transmission spectroscopy supplies detailed information on their atmospheric composition, physics, and chemistry. Prior to JWST, these observations were limited to a narrow wavelength range across the near-ultraviolet to near-infrared, alongside broadband photometry at longer wavelengths. To understand more complex properties of exoplanet atmospheres, improved wavelength coverage and resolution are necessary to robustly quantify the influence of a broader range of absorbing molecular species. Here we present a combined analysis of JWST transmission spectroscopy across four different instrumental modes spanning 0.5-5.2 micron using Early Release Science observations of the Saturn-mass exoplanet WASP-39b. Our uniform analysis constrains the orbital and stellar parameters within sub-percent precision, including matching the precision obtained by the most precise asteroseismology measurements of stellar density to-date, and further confirms the presence of Na, K, H$_2$O, CO, CO$_2$, and SO$_2$ atmospheric absorbers. Through this process, we also improve the agreement between the transmission spectra of all modes, except for the NIRSpec PRISM, which is affected by partial saturation of the detector. This work provides strong evidence that uniform light curve analysis is an important aspect to ensuring reliability when comparing the high-precision transmission spectra provided by JWST., Comment: 34 pages, 11 figures, 3 tables. Nat Astron (2024)

Surface acoustic waves (SAWs) are a powerful tool for controlling a wide range of quantum systems, particularly quantum dots (QDs) via their oscillating strain fields. The resulting energy modulation of these single photon sources can be harnessed to achieve spectral overlap between two QDs otherwise emitting at different wavelengths. In this study, we integrate InAsP/InP nanowire quantum dots onto a thin-film lithium niobate platform, a strong piezoelectric material, and embed them within Si$_{3}$N$_{4}$-loaded waveguides. We demonstrate emission wavelength modulation of 0.70 nm at 13 dBm with a single focused interdigital transducer (FIDT) operating at 400 MHz, and achieve twice this modulation by using two FIDTs as an acoustic cavity. Additionally, we bring two QDs with an initial wavelength difference of 0.5 nm into resonance using SAWs. This scalable strain-tuning approach represents a significant step towards producing indistinguishable single photons from remote emitters heterogeneously integrated on a single photonic chip, and paves the way for large scale on-chip quantum information processing using photonic platforms.

Due to stringent thermal budgets in cryogenic technologies such as superconducting quantum computers and sensors, minimizing the energy dissipation and power consumption of cryogenic electronic components is pivotal for large-scale devices. However, electronic building blocks that simultaneously offer low energy consumption, fast switching, low error rates, a small footprint and simple fabrication remain elusive. In this work, we demonstrate a superconducting switch with attojoule switching energy, high speed (pico-second rise/fall times), and high integration density (on the order of $10^{-2}$ $\mathrm{\mu m^2}$ per switch). The switch consists of a superconducting channel and a metal heater separated by an insulating silica layer, prepared using lift-off techniques. We experimentally demonstrate digital gate operations utilizing this technology, such as NOT, NAND, NOR, AND, and OR gates, with a few femtojoule energy consumption and ultralow bit error rates < $10^{-8}$. In addition, we build volatile memory elements with few femtojoule energy consumption per operation, a nanosecond operation speed, and a retention time over $10^5$ s. These superconducting switches open new possibilities for increasing the size and complexity of modern cryogenic technologies.

Rank-rank regressions are widely used in economic research to evaluate phenomena such as intergenerational income persistence or mobility. However, when covariates are incorporated to capture between-group persistence, the resulting coefficients can be difficult to interpret as such. We propose the conditional rank-rank regression, which uses conditional ranks instead of unconditional ranks, to measure average within-group income persistence. This property is analogous to that of the unconditional rank-rank regression that measures the overall income persistence. The difference between conditional and unconditional rank-rank regression coefficients therefore can measure between-group persistence. We develop a flexible estimation approach using distribution regression and establish a theoretical framework for large sample inference. An empirical study on intergenerational income mobility in Switzerland demonstrates the advantages of this approach. The study reveals stronger intergenerational persistence between fathers and sons compared to fathers and daughters, with the within-group persistence explaining 62% of the overall income persistence for sons and 52% for daughters. Families of small size or with highly educated fathers exhibit greater persistence in passing on their economic status., Comment: 40 pages, 3 figures, 8 tables

Social media platforms, particularly Telegram, play a pivotal role in shaping public perceptions and opinions on global and national issues. Unlike traditional news media, Telegram allows for the proliferation of user-generated content with minimal oversight, making it a significant venue for the spread of controversial and misinformative content. During the COVID-19 pandemic, Telegram's popularity surged in Singapore, a country with one of the highest rates of social media use globally. We leverage Singapore-based Telegram data to analyze information flows within groups focused on COVID-19 and climate change. Using k-means clustering, we identified distinct user archetypes, including Strategic Disruptor, Empirical Enthusiast, Inquisitive Moderate, and Critical Examiner, each contributing uniquely to the discourse. We developed a model to classify users into these clusters (Precision: Climate change: 0.99; COVID-19: 0.95).

This paper presents an extended version of the SPADE platform, which aims to empower intelligent agent systems with normative reasoning and value alignment capabilities. Normative reasoning involves evaluating social norms and their impact on decision-making, while value alignment ensures agents' actions are in line with desired principles and ethical guidelines. The extended platform equips agents with normative awareness and reasoning capabilities based on deontic logic, allowing them to assess the appropriateness of their actions and make informed decisions. By integrating normative reasoning and value alignment, the platform enhances agents' social intelligence and promotes responsible and ethical behaviors in complex environments.

This paper discusses the stability assessment of low-inertia power systems through a real-world large-scale low-inertia system, namely, the All-Island power system (AIPS) of Ireland and Northern Ireland. This system currently accommodates world-record levels of system non-synchronous penetration namely 75% (planning to increase to 80% next year). The paper discusses one-month results obtained with the state-of-the-art stability tool called look-ahead security assessment (LSAT). This tool carries out rotor-angle, frequency and voltage stability analyses and is implemented in the control centres of the transmission system operators (TSOs). The paper shows that, at the time of writing, the main binding stability constraint of the AIPS is related to the limits on the rate of change of frequency (RoCoF).

This paper discusses emerging operational challenges associated with the integration of solar photovoltaic (PV) in the All-Island power system (AIPS) of Ireland and Northern Ireland. These include the impact of solar PV on: (i) dispatch down levels; (ii) long-term frequency deviations; (iii) voltage magnitude variations; and (iv) operational demand variations. A case study based on actual data from the AIPS is used to analyze the above challenges. It is shown that despite its (still) relatively low penetration compared to wind power penetration, solar PV is challenging the real-time operation of the AIPS, e.g., maintaining frequency within operational limits. EirGrid and SONI, the transmission system operators (TSOs) of the AIPS, are working toward addressing all the above challenges.

Datalog is a powerful yet elegant language that allows expressing recursive computation. Although Datalog evaluation has been extensively studied in the literature, so far, only loose upper bounds are known on how fast a Datalog program can be evaluated. In this work, we ask the following question: given a Datalog program over a naturally-ordered semiring $\sigma$, what is the tightest possible runtime? To this end, our main contribution is a general two-phase framework for analyzing the data complexity of Datalog over $\sigma$: first ground the program into an equivalent system of polynomial equations (i.e. grounding) and then find the least fixpoint of the grounding over $\sigma$. We present algorithms that use structure-aware query evaluation techniques to obtain the smallest possible groundings. Next, efficient algorithms for fixpoint evaluation are introduced over two classes of semirings: (1) finite-rank semirings and (2) absorptive semirings of total order. Combining both phases, we obtain state-of-the-art and new algorithmic results. Finally, we complement our results with a matching fine-grained lower bound., Comment: To appear at PODS 2024

We propose an instrumental variable framework for identifying and estimating average and quantile effects of discrete and continuous treatments with binary instruments. The basis of our approach is a local copula representation of the joint distribution of the potential outcomes and unobservables determining treatment assignment. This representation allows us to introduce an identifying assumption, so-called copula invariance, that restricts the local dependence of the copula with respect to the treatment propensity. We show that copula invariance identifies treatment effects for the entire population and other subpopulations such as the treated. The identification results are constructive and lead to straightforward semiparametric estimation procedures based on distribution regression. An application to the effect of sleep on well-being uncovers interesting patterns of heterogeneity.

The Arellano-Bond estimator is a fundamental method for dynamic panel data models, widely used in practice. However, the estimator is severely biased when the data's time series dimension $T$ is long due to the large degree of overidentification. We show that weak dependence along the panel's time series dimension naturally implies approximate sparsity of the most informative moment conditions, motivating the following approach to remove the bias: First, apply LASSO to the cross-section data at each time period to construct most informative (and cross-fitted) instruments, using lagged values of suitable covariates. This step relies on approximate sparsity to select the most informative instruments. Second, apply a linear instrumental variable estimator after first differencing the dynamic structural equation using the constructed instruments. Under weak time series dependence, we show the new estimator is consistent and asymptotically normal under much weaker conditions on $T$'s growth than the Arellano-Bond estimator. Our theory covers models with high dimensional covariates, including multiple lags of the dependent variable, common in modern applications. We illustrate our approach by applying it to weekly county-level panel data from the United States to study opening K-12 schools and other mitigation policies' short and long-term effects on COVID-19's spread.

Formally verifying the properties of formal systems using a proof assistant requires justifying numerous minor lemmas about capture-avoiding substitution. Despite work on category-theoretic accounts of syntax and variable binding, raw, first-order representations of syntax, the kind considered by many practitioners and compiler frontends, have received relatively little attention. Therefore applications miss out on the benefits of category theory, most notably the promise of reusing formalized infrastructural lemmas between implementations of different systems. Our Coq framework Tealeaves provides libraries of reusable infrastructure for a raw, locally nameless representation and can be extended to other representations in a modular fashion. In this paper we give a string-diagrammatic account of decorated traversable monads (DTMs), the key abstraction implemented by Tealeaves. We define DTMs as monoids of structured endofunctors before proving a representation theorem a la Kleisli, yielding a recursion combinator for finitary tree-like datatypes., Comment: In Proceedings ACT 2023, arXiv:2312.08138

Partial least squares (PLS) is a dimensionality reduction technique introduced in the field of chemometrics and successfully employed in many other areas. The PLS components are obtained by maximizing the covariance between linear combinations of the regressors and of the target variables. In this work, we focus on its application to scalar regression problems. PLS regression consists in finding the least squares predictor that is a linear combination of a subset of the PLS components. Alternatively, PLS regression can be formulated as a least squares problem restricted to a Krylov subspace. This equivalent formulation is employed to analyze the distance between ${\hat{\boldsymbol\beta}\;}_{\mathrm{PLS}}^{\scriptscriptstyle {(L)}}$, the PLS estimator of the vector of coefficients of the linear regression model based on $L$ PLS components, and $\hat{\boldsymbol \beta}_{\mathrm{OLS}}$, the one obtained by ordinary least squares (OLS), as a function of $L$. Specifically, ${\hat{\boldsymbol\beta}\;}_{\mathrm{PLS}}^{\scriptscriptstyle {(L)}}$ is the vector of coefficients in the aforementioned Krylov subspace that is closest to $\hat{\boldsymbol \beta}_{\mathrm{OLS}}$ in terms of the Mahalanobis distance with respect to the covariance matrix of the OLS estimate. We provide a bound on this distance that depends only on the distribution of the eigenvalues of the regressor covariance matrix. Numerical examples on synthetic and real-world data are used to illustrate how the distance between ${\hat{\boldsymbol\beta}\;}_{\mathrm{PLS}}^{\scriptscriptstyle {(L)}}$ and $\hat{\boldsymbol \beta}_{\mathrm{OLS}}$ depends on the number of clusters in which the eigenvalues of the regressor covariance matrix are grouped.

Using CPS data for 1976 to 2022 we explore how wage inequality has evolved for married couples with both spouses working full time full year, and its impact on household income inequality. We also investigate how marriage sorting patterns have changed over this period. To determine the factors driving income inequality we estimate a model explaining the joint distribution of wages which accounts for the spouses' employment decisions. We find that income inequality has increased for these households and increased assortative matching of wages has exacerbated the inequality resulting from individual wage growth. We find that positive sorting partially reflects the correlation across unobservables influencing both members' of the marriage wages. We decompose the changes in sorting patterns over the 47 years comprising our sample into structural, composition and selection effects and find that the increase in positive sorting primarily reflects the increased skill premia for both observed and unobserved characteristics., Comment: 63 pages; 13 figures; 36 tables

The adverse effects of microgravity exposure on mammalian physiology during spaceflight necessitate a deep understanding of the underlying mechanisms to develop effective countermeasures. One such concern is muscle atrophy, which is partly attributed to the dysregulation of calcium levels due to abnormalities in SERCA pump functioning. To identify potential biomarkers for this condition, multi-omics data and physiological data available on the NASA Open Science Data Repository (osdr.nasa.gov) were used, and machine learning methods were employed. Specifically, we used multi-omics (transcriptomic, proteomic, and DNA methylation) data and calcium reuptake data collected from C57BL/6J mouse soleus and tibialis anterior tissues during several 30+ day-long missions on the international space station. The QLattice symbolic regression algorithm was introduced to generate highly explainable models that predict either experimental conditions or calcium reuptake levels based on multi-omics features. The list of candidate models established by QLattice was used to identify key features contributing to the predictive capability of these models, with Acyp1 and Rps7 proteins found to be the most predictive biomarkers related to the resilience of the tibialis anterior muscle in space. These findings could serve as targets for future interventions aiming to reduce the extent of muscle atrophy during space travel.

This report leverages state educational agency data to explore the association between Alabama Science in Motion (ASIM) implementation and student outcomes. We conducted this study in Alabama to evaluate the potential of teacher implementation of ASIM lab activities to improve high school level student achievement in science. This study follows a correlational design aimed at establishing the statistical association between a single metric of teacher preparation and student outcomes. Unlike experimental and quasi-experimental studies, it does not compare treatment and control groups. It focuses entirely on students exposed to the program (in this case, the implementation of ASIM labs)--and the differences in outcomes among them that can be attributed to the metrics of program implementation--making appropriate adjustments for differences in student and school characteristics and pretest scores. This study addresses the following questions: (1) Is there an association between ASIM implementation and science achievement for students in grade 11?; (2) Does the association of ASIM implementation with student achievement vary across student groups?; and (3) Where can improvement efforts be applied in the ASIM process to produce greater program effectiveness? [This report was funded by the University of Montevallo.]

Enhanced weathering (EW) is a promising modification to current agricultural practices that uses crushed silicate rocks to drive carbon dioxide removal (CDR). If widely adopted on farmlands, it could help achieve net-zero or negative emissions by 2050. We report detailed state-level analysis indicating EW deployed on agricultural land could sequester 0.23-0.38 Gt CO$_2$ yr$^{-1}$ and meet 36-60 % of U.S. technological CDR goals. Average CDR costs vary between state, being highest in the first decades before declining to a range of $\sim\$$100-150 tCO$_2{}^{-1}$ by 2050, including for three states (Iowa, Illinois, and Indiana) that contribute most to total national CDR. We identify multiple electoral swing states as being essential for scaling EW that are also key beneficiaries of the practice, indicating the need for strong bipartisan support of this technology. Assessment the geochemical capacity of rivers and oceans to carry dissolved EW products from soil drainage suggests EW provides secure long-term CO$_2$ removal on intergenerational time scales. We additionally forecast mitigation of ground-level ozone increases expected with future climate change, as an indirect benefit of EW, and consequent avoidance of yield reductions. Our assessment supports EW as a practical innovation for leveraging agriculture to enable positive action on climate change with adherence to federal environmental justice priorities. However, implementing a stage-gating framework as upscaling proceeds to safeguard against environmental and biodiversity concerns will be essential.

At the core of quantum photonic information processing and sensing, two major building pillarsare single-photon emitters and single-photon detectors. In this review, we systematically summarize the working theory, material platform, fabrication process, and game-changing applications enabled by state-of-the-art quantum dots in nanowire emitters and superconducting nanowire single-photon detectors. Such nanowire-based quantum hardware offers promising properties for modern quantum optics experiments.We highlight several burgeoning quantum photonics applications using nanowires and discuss development trends of integrated quantum photonics. Also, we propose quantum information processing and sensing experiments for the quantum optics community, and future interdisciplinary applications.

An on-demand source of bright entangled photon pairs is desirable for quantum key distribution (QKD) and quantum repeaters. The leading candidate to generate entangled photon pairs is based on spontaneous parametric down-conversion (SPDC) in a non-linear crystal. However, there exists a fundamental trade-off between entanglement fidelity and efficiency in SPDC sources due to multiphoton emission at high brightness, which limits the pair extraction efficiency to 0.1% when operating at near-unity fidelity. Quantum dots in photonic nanostructures can in principle overcome this trade-off; however, the quantum dots that have achieved entanglement fidelities on par with SPDC sources (99%) have poor pair extraction efficiencies of 0.01%. Here, we demonstrate a 65-fold increase in the pair extraction efficiency compared to quantum dots with equivalent peak fidelity from an InAsP quantum dot in a photonic nanowire waveguide. We measure a raw peak concurrence and fidelity of 95.3% $\pm$ 0.5% and 97.5% $\pm$ 0.8%, respectively. Finally, we show that an oscillating two-photon Bell state generated by a semiconductor quantum dot can be utilized to establish a secure key for QKD, alleviating the need to remove the quantum dot energy splitting of the intermediate exciton states in the biexciton-exciton cascade., Comment: 24 pages (7 main body, excluding references plus 14 supplemental information) and 4 main body figures

Quantum physics phenomena, entanglement and coherence, are crucial for quantum information protocols, but understanding these in systems with more than two parts is challenging due to increasing complexity. The W state, a multipartite entangled state, is notable for its robustness and benefits in quantum communication. Here, we generate an 8-mode on-demand single photon W states, using nanowire quantum dots and a silicon nitride photonic chip. We demonstrate a reliable, scalable technique for reconstructing W-state in photonic circuits using Fourier and real-space imaging, supported by the Gerchberg-Saxton phase retrieval algorithm. Additionally, we utilize an entanglement witness to distinguish between mixed and entangled states, thereby affirming the entangled nature of our generated state. The study provides a new imaging approach of assessing multipartite entanglement in W-states, paving the way for further progress in image processing and Fourier-space analysis techniques for complex quantum systems.

The interrelationship between localization, quantum transport, and disorder has remained a fascinating focus in scientific research. Traditionally, it has been widely accepted in the physics community that in one-dimensional systems, as disorder increases, localization intensifies, triggering a metal-insulator transition. However, a recent theoretical investigation [Phys. Rev. Lett. 126, 106803] has revealed that the interplay between dimerization and disorder leads to a reentrant localization transition, constituting a remarkable theoretical advancement in the field. Here, we present the experimental observation of reentrant localization using an experimentally friendly model, a photonic SSH lattice with random-dimer disorder, achieved by incrementally adjusting synthetic potentials. In the presence of correlated on-site potentials, certain eigenstates exhibit extended behavior following the localization transition as the disorder continues to increase. We directly probe the wave function in disordered lattices by exciting specific lattice sites and recording the light distribution. This reentrant phenomenon is further verified by observing an anomalous peak in the normalized participation ratio. Our study enriches the understanding of transport in disordered mediums and accentuates the substantial potential of integrated photonics for the simulation of intricate condensed matter physics phenomena.

Enhanced weathering (EW) with crushed basalt on farmlands is a promising scalable atmospheric carbon dioxide removal strategy that urgently requires performance assessment with commercial farming practices. Our large-scale replicated EW field trial in the heart of the U.S. Corn Belt shows cumulative time-integrated carbon sequestration of 15.4 +/- 4.1 t CO2 ha-1 over four years, with additional emissions mitigation of ~0.1 - 0.4 t CO2,e ha-1 yr-1 for soil nitrous oxide, a potent long-lived greenhouse gas. Maize and soybean yields increased 12-16% with EW following improved soil fertility, decreased soil acidification, and upregulation of root nutrient transport genes. Our findings suggest that widespread adoption of EW across farming sectors has the potential to contribute significantly to net-zero greenhouse gas emissions goals and global food and soil security.

We demonstrate a simplified out-door FSO link with modal split for down-/uplink and confirm its long-term stability without active beam tracking. We further prove the duality of modal and directional split through penalty-free full-duplex transmission.

Quantum transport and localization are fundamental concepts in condensed matter physics. It is commonly believed that in one-dimensional systems, the existence of mobility edges is highly dependent on disorder. Recently, there has been a debate over the existence of an exact mobility edge in a modulated mosaic model without quenched disorder, the so-called mosaic Wannier-Stark lattice. Here, we experimentally implement such disorder-free mosaic photonic lattices using a silicon photonics platform. By creating a synthetic electric field, we could observe energy-dependent coexistence of both extended and localized states in a finite number of waveguides. The Wannier-Stark ladder emerges when the resulting potential is strong enough, and can be directly probed by exciting different spatial modes of the lattice. Our studies provide the experimental proof of coexisting sets of strongly localized and conducting (though weakly localized) states in finite-sized mosaic Wannier-Stark lattices, which hold the potential to encode high-dimensional quantum resources with compact and robust structures.

The mobility edge (ME) is a crucial concept in understanding localization physics, marking the critical transition between extended and localized states in the energy spectrum. Anderson localization scaling theory predicts the absence of ME in lower dimensional systems. Hence, the search for exact MEs, particularly for single particles in lower dimensions, has recently garnered significant interest in both theoretical and experimental studies, resulting in notable progress. However, several open questions remain, including the possibility of a single system exhibiting multiple MEs and the continual existence of extended states, even within the strong disorder domain. Here, we provide experimental evidence to address these questions by utilizing a quasiperiodic mosaic lattice with meticulously designed nanophotonic circuits. Our observations demonstrate the coexistence of both extended and localized states in lattices with broken duality symmetry and varying modulation periods. By single site injection and scanning the disorder level, we could approximately probe the ME of the modulated lattice. These results corroborate recent theoretical predictions, introduce a new avenue for investigating ME physics, and offer inspiration for further exploration of ME physics in the quantum regime using hybrid integrated photonic devices.

The integration of on-demand single photon sources in photonic circuits is a major prerequisite for on-chip quantum applications. Among the various high-quality sources, nanowire quantum dots can be efficiently coupled to optical waveguides because of their preferred emission direction along their growth direction. However, local tuning of the emission properties remains challenging. In this work, we transfer a nanowire quantum dot on a bulk lithium niobate substrate and show that its emission can be dynamically tuned by acousto-optical coupling with surface acoustic waves. The purity of the single photon source is preserved during the strain modulation. We further demonstrate that the transduction is maintained even with a SiO2 encapsulation layer deposited on top of the nanowire acting as the cladding of a photonic circuit. Based on these experimental findings and numerical simulations, we introduce a device architecture consisting of a nanowire quantum dot efficiently coupled to a thin film lithium niobate rib waveguide and strain-tunable by surface acoustic waves.

A study was conducted to evaluate the impact of CAPIT Reading on student early literacy achievement. The study utilized a quasi-experimental comparison group design using data from 12 elementary schools in a suburban school district in Oklahoma during the 2019-20 school year. CAPIT Reading is a comprehensive PK-2 literacy solution that includes a digital phonics curriculum and teacher professional development. Four schools used CAPIT to supplement their literacy instruction for kindergarten students while eight schools did not. The study linked CAPIT usage data and district demographic and achievement data to estimate the impact of CAPIT on the Letter Word Sounds Fluency (LWSF) and Early Literacy Composite scores of the aimsweb reading assessment administered by the district in August and January. We found a positive impact of CAPIT Reading on student early reading achievement on the aimsweb assessment for kindergarten students estimated at 4.4 test score points for the aimsweb Early Literacy Composite score (effect size 0.17, p = 0.01) and 7.8 points for the LWSF score (effect size 0.29, p < 0.001). This impact on the LWSF score is equivalent to a 29% increase in growth for the average CAPIT student from the fall to winter tests. We found limited evidence of differential impact favoring student subgroups, meaning that this positive impact for CAPIT users did not vary according to student characteristics such as eligibility for free and reduced-price lunch, race, or gender. We found that the impact on aimsweb overall was marginally greater for special education students by 4.9 points (p = 0.09) and that the impact on LWSF scores was greater for English Language Learners by 7.4 points (p = 0.09). Impact of CAPIT reading does not vary significantly across other student groups. [This paper was produced by Evidentally, Inc.]

We present a novel natural language processing (NLP) approach to deriving plain English descriptors for science cases otherwise restricted by obfuscating technical terminology. We address the limitations of common radio galaxy morphology classifications by applying this approach. We experimentally derive a set of semantic tags for the Radio Galaxy Zoo EMU (Evolutionary Map of the Universe) project and the wider astronomical community. We collect 8,486 plain English annotations of radio galaxy morphology, from which we derive a taxonomy of tags. The tags are plain English. The result is an extensible framework which is more flexible, more easily communicated, and more sensitive to rare feature combinations which are indescribable using the current framework of radio astronomy classifications., Comment: 17 pages, 11 Figures, Accepted at MNRAS

The Compact Muon Solenoid (CMS) experiment prepares its Phase-2 upgrade for the high-luminosity era of the LHC operation (HL-LHC). Due to the increase of occupancy, trigger latency and rates, the full electronics of the CMS Drift Tube (DT) chambers will need to be replaced. In the new design, the time bin for the digitisation of the chamber signals will be of around 1~ns, and the totality of the signals will be forwarded asynchronously to the service cavern at full resolution. The new backend system will be in charge of building the trigger primitives of each chamber. These trigger primitives contain the information at chamber level about the muon candidates position, direction, and collision time, and are used as input in the L1 CMS trigger. The added functionalities will improve the robustness of the system against ageing. An algorithm based on analytical solutions for reconstructing the DT trigger primitives, called Analytical Method, has been implemented both as a software C++ emulator and in firmware. Its performance has been estimated using the software emulator with simulated and real data samples, and through hardware implementation tests. Measured efficiencies are 96 to 98\% for all qualities and time and spatial resolutions are close to the ultimate performance of the DT chambers. A prototype chain of the HL-LHC electronics using the Analytical Method for trigger primitive generation has been installed during Long Shutdown 2 of the LHC and operated in CMS cosmic data taking campaigns in 2020 and 2021. Results from this validation step, the so-called Slice Test, are presented., Comment: 16 pages, 11 figures

Long-range quantum communication requires the development of in-out light-matter interfaces to achieve a quantum advantage in entanglement distribution. Ideally, these quantum interconnections should be as fast as possible to achieve high-rate entangled qubits distribution. Here, we demonstrate the coherent quanta exchange between single photons generated on-demand from a GaAs quantum dot and atomic ensemble in a $^{87}$Rb vapor quantum memory. Through an open quantum system analysis, we demonstrate the mapping between the quantized electric field of photons and the coherence of the atomic ensemble. Our results play a pivotal role in understanding quantum light-matter interactions at the short time scales required to build fast hybrid quantum networks., Comment: arXiv admin note: text overlap with arXiv:1808.05921; v2: figure typo corrected

The ability to localise a smart device is very useful to visually or cognitively impaired people. Localisation-capable technologies are becoming more readily available as off-the-shelf components. In this paper, we highlight the need for such a service in the field of health and autonomy, especially for disabled people. We introduce a model for Semantic Position Description (SPD) (e.g. "The pill organiser in on the kitchen table") as well as various algorithms that transform raw distance estimations to SPD related to proximity, alignment and room identification. Two of these algorithms are evaluated using the LocURa4IoT testbed. The results are compared to the output of a pre-experiment involving ten human participants in the Maison Intelligente de Blagnac. The two studies indicate that both approaches converge up to 90% of the time. .

Photochemistry is a fundamental process of planetary atmospheres that regulates the atmospheric composition and stability. However, no unambiguous photochemical products have been detected in exoplanet atmospheres to date. Recent observations from the JWST Transiting Exoplanet Early Release Science Program found a spectral absorption feature at 4.05 $\mu$m arising from SO$_2$ in the atmosphere of WASP-39b. WASP-39b is a 1.27-Jupiter-radii, Saturn-mass (0.28 M$_J$) gas giant exoplanet orbiting a Sun-like star with an equilibrium temperature of $\sim$1100 K. The most plausible way of generating SO$_2$ in such an atmosphere is through photochemical processes. Here we show that the SO$_2$ distribution computed by a suite of photochemical models robustly explains the 4.05 $\mu$m spectral feature identified by JWST transmission observations with NIRSpec PRISM (2.7$\sigma$) and G395H (4.5$\sigma$). SO$_2$ is produced by successive oxidation of sulphur radicals freed when hydrogen sulphide (H$_2$S) is destroyed. The sensitivity of the SO$_2$ feature to the enrichment of the atmosphere by heavy elements (metallicity) suggests that it can be used as a tracer of atmospheric properties, with WASP-39b exhibiting an inferred metallicity of $\sim$10$\times$ solar. We further point out that SO$_2$ also shows observable features at ultraviolet and thermal infrared wavelengths not available from the existing observations., Comment: 39 pages, 14 figures, accepted to be published in Nature

Measuring the metallicity and carbon-to-oxygen (C/O) ratio in exoplanet atmospheres is a fundamental step towards constraining the dominant chemical processes at work and, if in equilibrium, revealing planet formation histories. Transmission spectroscopy provides the necessary means by constraining the abundances of oxygen- and carbon-bearing species; however, this requires broad wavelength coverage, moderate spectral resolution, and high precision that, together, are not achievable with previous observatories. Now that JWST has commenced science operations, we are able to observe exoplanets at previously uncharted wavelengths and spectral resolutions. Here we report time-series observations of the transiting exoplanet WASP-39b using JWST's Near InfraRed Camera (NIRCam). The long-wavelength spectroscopic and short-wavelength photometric light curves span 2.0 - 4.0 $\mu$m, exhibit minimal systematics, and reveal well-defined molecular absorption features in the planet's spectrum. Specifically, we detect gaseous H$_2$O in the atmosphere and place an upper limit on the abundance of CH$_4$. The otherwise prominent CO$_2$ feature at 2.8 $\mu$m is largely masked by H$_2$O. The best-fit chemical equilibrium models favour an atmospheric metallicity of 1-100$\times$ solar (i.e., an enrichment of elements heavier than helium relative to the Sun) and a sub-stellar carbon-to-oxygen (C/O) ratio. The inferred high metallicity and low C/O ratio may indicate significant accretion of solid materials during planet formation or disequilibrium processes in the upper atmosphere., Comment: 35 pages, 13 figures, 3 tables, Nature, accepted

Measuring the abundances of carbon and oxygen in exoplanet atmospheres is considered a crucial avenue for unlocking the formation and evolution of exoplanetary systems. Access to an exoplanet's chemical inventory requires high-precision observations, often inferred from individual molecular detections with low-resolution space-based and high-resolution ground-based facilities. Here we report the medium-resolution (R$\sim$600) transmission spectrum of an exoplanet atmosphere between 3-5 $\mu$m covering multiple absorption features for the Saturn-mass exoplanet WASP-39b, obtained with JWST NIRSpec G395H. Our observations achieve 1.46x photon precision, providing an average transit depth uncertainty of 221 ppm per spectroscopic bin, and present minimal impacts from systematic effects. We detect significant absorption from CO$_2$ (28.5$\sigma$) and H$_2$O (21.5$\sigma$), and identify SO$_2$ as the source of absorption at 4.1 $\mu$m (4.8$\sigma$). Best-fit atmospheric models range between 3 and 10x solar metallicity, with sub-solar to solar C/O ratios. These results, including the detection of SO$_2$, underscore the importance of characterising the chemistry in exoplanet atmospheres, and showcase NIRSpec G395H as an excellent mode for time series observations over this critical wavelength range., Comment: 44 pages, 11 figures, 3 tables. Resubmitted after revision to Nature

Cuprous oxide (Cu${}_2$O) has recently been proposed as a promising solid-state host for excitonic Rydberg states with large principal quantum numbers ($n$), whose exaggerated wavefunction sizes ($\propto n^2)$ facilitate gigantic dipole-dipole ($\propto n^4$) and van der Waals ($\propto n^{11}$) interactions, making them an ideal basis for solid-state quantum technology. Synthetic, thin-film Cu${}_2$O samples are of particular interest because they can be made defect-free via carefully controlled fabrication and are, in principle, suitable for the observation of extreme single-photon nonlinearities caused by the Rydberg blockade. Here, we present spectroscopic absorption and photoluminescence studies of Rydberg excitons in synthetic Cu${}_2$O grown on a transparent substrate, reporting yellow exciton series up to $n = 7$. We perform these studies at powers up to 2 mW and temperatures up to 150 K, the highest temperature where Rydberg series can be observed. These results open a new portal to scalable and integrable on-chip Rydberg-based quantum devices., Comment: 10 pages, 5 figures

Superconducting nanowire single-photon detectors (SNSPDs) show near unity efficiency, low dark count rate, and short recovery time. Combining these characteristics with temporal control of SNSPDs broadens their applications as in active de-latching for higher dynamic range counting or temporal filtering for pump-probe spectroscopy or LiDAR. To that end, we demonstrate active gating of an SNSPD with a minimum off-to-on rise time of 2.4 ns and a total gate length of 5.0 ns. We show how the rise time depends on the inductance of the detector in combination with the control electronics. The gate window is demonstrated to be fully and freely, electrically tunable up to 500 ns at a repetition rate of 1.0 MHz, as well as ungated, free-running operation. Control electronics to generate the gating are mounted on the 2.3 K stage of a closed-cycle sorption cryostat, while the detector is operated on the cold stage at 0.8 K. We show that the efficiency and timing jitter of the detector is not altered during the on-time of the gating window. We exploit gated operation to demonstrate a method to increase in the photon counting dynamic range by a factor 11.2, as well as temporal filtering of a strong pump in an emulated pump-probe experiment.

We define deriving semantic class targets as a novel multi-modal task. By doing so, we aim to improve classification schemes in the physical sciences which can be severely abstracted and obfuscating. We address this task for upcoming radio astronomy surveys and present the derived semantic radio galaxy morphology class targets., Comment: 6 pages, 1 figure, Accepted at Fifth Workshop on Machine Learning and the Physical Sciences (NeurIPS 2022), Neural Information Processing Systems 2022

Building upon the theory of Kalman Filtering on Lie Groups, this paper describes an Extended Kalman Filter and Smoother for Loosely Coupled Integration of GNSS/INS tailored for post-processing applications. The approach employs a dynamic model on a matrix Lie Group that aggregates position, velocity, attitude, and the IMU biases as a single element of a Lie group. The development was motivated by a drone-borne Differential Interferometric SAR (DinSAR) application, which requires high-precision navigation information for short-flight missions using low-cost MEMS sensors. The filter and the Rauch-Tung-Striebel (RTS) smoother are both implemented and validated. The paper also presents a novel algorithm to initialize the heading value as an alternative to gyro-compassing or magnetometer-based alignments. The Mahalanobis Distance and the $\chi^2$-test are employed during the filter update step to address the practical issue of outlier rejection for the GNSS measurements. The paper uses synthetic data to compare classic navigation schemes based on multiplicative quaternions and Euler angles. Finally, real data experiments demonstrate that the Kalman Filter based on Lie Groups performs better DinSAR processing than state-of-the-art commercial software.

Human relationships are complex processes that often involve following certain rules that regulate interactions and/or expected outcomes. These rules may be imposed by an authority or established by society. In multi-agent systems, normative systems have extensively addressed aspects such as norm synthesis, norm conflict detection, as well as norm emergence. However, if human behaviour is to be adequately simulated, not only normative aspects but also emotional aspects have to be taken into account. In this paper, we propose a Jason agent architecture that incorporates norms and emotions in its reasoning process to determine which plan (actions) to execute. The proposal is evaluated through a scenario based on a social network, which allows us to analyse the benefits of using emotional normative agents to achieve simulations closer to real human world., Comment: 39 pages, 10 figures, 4 tables

Carbon dioxide (CO2) is a key chemical species that is found in a wide range of planetary atmospheres. In the context of exoplanets, CO2 is an indicator of the metal enrichment (i.e., elements heavier than helium, also called "metallicity"), and thus formation processes of the primary atmospheres of hot gas giants. It is also one of the most promising species to detect in the secondary atmospheres of terrestrial exoplanets. Previous photometric measurements of transiting planets with the Spitzer Space Telescope have given hints of the presence of CO2 but have not yielded definitive detections due to the lack of unambiguous spectroscopic identification. Here we present the detection of CO2 in the atmosphere of the gas giant exoplanet WASP-39b from transmission spectroscopy observations obtained with JWST as part of the Early Release Science Program (ERS). The data used in this study span 3.0 to 5.5 {\mu}m in wavelength and show a prominent CO2 absorption feature at 4.3 {\mu}m (26{\sigma} significance). The overall spectrum is well matched by one-dimensional, 10x solar metallicity models that assume radiative-convective-thermochemical equilibrium and have moderate cloud opacity. These models predict that the atmosphere should have water, carbon monoxide, and hydrogen sulfide in addition to CO2, but little methane. Furthermore, we also tentatively detect a small absorption feature near 4.0 {\mu}m that is not reproduced by these models., Comment: 27 pages, 6 figures, Accepted for publication in Nature, data and models available at https://doi.10.5281/zenodo.6959427

Unknown class distributions in unlabelled astrophysical training data have previously been shown to detrimentally affect model performance due to dataset shift between training and validation sets. For radio galaxy classification, we demonstrate in this work that removing low angular extent sources from the unlabelled data before training produces qualitatively different training dynamics for a contrastive model. By applying the model on an unlabelled data-set with unknown class balance and sub-population distribution to generate a representation space of radio galaxies, we show that with an appropriate cut threshold we can find a representation with FRI/FRII class separation approaching that of a supervised baseline explicitly trained to separate radio galaxies into these two classes. Furthermore we show that an excessively conservative cut threshold blocks any increase in validation accuracy. We then use the learned representation for the downstream task of performing a similarity search on rare hybrid sources, finding that the contrastive model can reliably return semantically similar samples, with the added bonus of finding duplicates which remain after pre-processing., Comment: Accepted in: Machine Learning for Astrophysics Workshop at the Thirty Ninth International Conference on Machine Learning (ICML 2022); final version

The Astropy Project supports and fosters the development of open-source and openly-developed Python packages that provide commonly needed functionality to the astronomical community. A key element of the Astropy Project is the core package $\texttt{astropy}$, which serves as the foundation for more specialized projects and packages. In this article, we summarize key features in the core package as of the recent major release, version 5.0, and provide major updates for the Project. We then discuss supporting a broader ecosystem of interoperable packages, including connections with several astronomical observatories and missions. We also revisit the future outlook of the Astropy Project and the current status of Learn Astropy. We conclude by raising and discussing the current and future challenges facing the Project., Comment: 43 pages, 5 figures. To appear in ApJ. The author list has two parts: the authors that made significant contributions to the writing and/or coordination of the paper, followed by maintainers of and contributors to the Astropy Project. The position in the author list does not correspond to contributions to the Astropy Project as a whole

New astronomical tasks are often related to earlier tasks for which labels have already been collected. We adapt the contrastive framework BYOL to leverage those labels as a pretraining task while also enforcing augmentation invariance. For large-scale pretraining, we introduce GZ-Evo v0.1, a set of 96.5M volunteer responses for 552k galaxy images plus a further 1.34M comparable unlabelled galaxies. Most of the 206 GZ-Evo answers are unknown for any given galaxy, and so our pretraining task uses a Dirichlet loss that naturally handles unknown answers. GZ-Evo pretraining, with or without hybrid learning, improves on direct training even with plentiful downstream labels (+4% accuracy with 44k labels). Our hybrid pretraining/contrastive method further improves downstream accuracy vs. pretraining or contrastive learning, especially in the low-label transfer regime (+6% accuracy with 750 labels)., Comment: Accepted at the ICML 2022 Workshop on Machine Learning for Astrophysics. Data: www.github.com/mwalmsley/pytorch-galaxy-datasets. Please reach out to share your labelled data - all contributions will be credited in future work

In May of 2020, the Advanced Distributed Learning Initiative (ADL) and the Defense Acquisition University (DAU) partnered with USALearning/PowerTrain to create a practical application of ADL's 2019 TLA Reference Implementation. The purpose of this project was to recreate key components of the Reference Implementation with commercially-available, open source, and customized solutions to demonstrate the value of organizations choosing to adopt the architecture to improve their ability to track competency-based learning. [This report was created with USALearning and PowerTrain.]

29P/Schwassmann-Wachmann 1 is a distant Centaur/comet, showing persistent CO-driven activity and frequent outbursts. We used the Herschel space observatory in 2010, 2011, and 2013 to observe H$_2$O and NH$_3$ and to image the dust coma. Observations with the IRAM 30 m were undertaken in 2007, 2010, 2011, and 2021 to monitor the CO production rate and to search for HCN. Modeling was performed to constrain the size of the sublimating icy grains and to derive the dust production rate. HCN is detected for the first time in comet 29P (at 5$\sigma$ in the line area). H$_2$O is detected as well, but not NH$_3$. H$_2$O and HCN line shapes differ strongly from the CO line shape, indicating that these two species are released from icy grains. CO production rates are in the range (2.9-5.6) $\times$ 10$^{28}$ s$^{-1}$ (1400--2600 kg s$^{-1}$). A correlation between the CO production rate and coma brightness is observed, as is a correlation between CO and H$_2$O production. The correlation obtained between the excess of CO production and excess of dust brightness with respect to the quiescent state is similar to that established for the continuous activity of comet Hale-Bopp. The measured $Q$(H$_2$O)/$Q$(CO) and $Q$(HCN)/$Q$(CO) production rate ratios are 10.0 $\pm$ 1.5 % and 0.12 $\pm$ 0.03 %, respectively, averaging the April-May 2010 measurements ($Q$(H$_2$O) = (4.1 $\pm$ 0.6) $\times$ 10$^{27}$ s$^{-1}$, $Q$(HCN) = (4.8 $\pm$ 1.1) $\times$ 10$^{25}$ s$^{-1}$). We derive three independent and similar values of the effective radius of the nucleus, $\sim$ 31 $\pm$ 3 km. The inferred dust mass-loss rates during quiescent phases are in the range 30-120 kg s$^{-1}$, indicating a dust-to-gas mass ratio $<$ 0.1 during quiescent activity. We conclude that strong local heterogeneities exist on the surface of 29P, with quenched dust activity from most of the surface, but not in outbursting regions., Comment: 28 pages, 15 figures, A&A in press

pyspeckit is a toolkit and library for spectroscopic analysis in Python. We describe the pyspeckit package and highlight some of its capabilities, such as interactively fitting a model to data, akin to the historically widely-used splot function in IRAF. pyspeckit employs the Levenberg-Marquardt optimization method via the mpfit and lmfit implementations, and important assumptions regarding error estimation are described here. Wrappers to use pymc and emcee as optimizers are provided. A parallelized wrapper to fit lines in spectral cubes is included. As part of the astropy affiliated package ecosystem, pyspeckit is open source and open development and welcomes input and collaboration from the community., Comment: Version 1.0 of pyspeckit is released alongside this paper; https://pyspeckit.readthedocs.io/en/latest/