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The performance of superconducting qubits is often limited by dissipation and two-level systems (TLS) losses. The dominant sources of these losses are believed to originate from amorphous materials and defects at interfaces and surfaces, likely as a result of fabrication processes or ambient exposure. Here, we explore a novel wet chemical surface treatment at the Josephson junction-substrate and the substrate-air interfaces by replacing a buffered oxide etch (BOE) cleaning process with one that uses hydrofluoric acid followed by aqueous ammonium fluoride. We show that the ammonium fluoride etch process results in a statistically significant improvement in median $\text{T}_1$ by $\sim22\%$ ($p=0.002$), and a reduction in the number of strongly-coupled TLS in the tunable frequency range. Microwave resonator measurements on samples treated with the ammonium fluoride etch prior to niobium deposition also show $\sim33\%$ lower TLS-induced loss tangent compared to the BOE treated samples. As the chemical treatment primarily modifies the Josephson junction-substrate interface and substrate-air interface, we perform targeted chemical and structural characterizations to examine materials' differences at these interfaces and identify multiple microscopic changes that could contribute to decreased TLS.

Studies of galaxy protoclusters yield insights into galaxy cluster formation complementary to those obtained via `archaeological' studies of present-day galaxy clusters. Submillimetre-selected galaxies (SMGs) are one class of sources used to find high-redshift protoclusters. However, due to the rarity of protoclusters (and thus the large simulation volume required) and the complexity of modeling dust emission from galaxies, the relationship between SMGs and protoclusters has not been adequately addressed in the theoretical literature. In this work, we apply the L-GALAXIES semi-analytic model (SAM) to the Millennium N-body simulation. We assign submillimetre (submm) flux densities to the model galaxies using a scaling relation from previous work, in which dust radiative transfer was performed on high-resolution galaxy zoom simulations. We find that the fraction of model galaxies that are submm-bright is higher in protocluster cores than in both protocluster `outskirts' and the field; the fractions for the latter two are similar. This excess is not driven by an enhanced starburst frequency. Instead, the primary reason is that overdense environments have a relative overdensity of high-mass halos and thus `oversample' the high-mass end of the star formation main sequence relative to less-dense environments. The fraction of SMGs that are optically bright is dependent on stellar mass and redshift but independent of environment. The fraction of galaxies for which the majority of star formation is dust-obscured is higher in protocluster cores, primarily due to the dust-obscured fraction being correlated with stellar mass. Our results can be used to guide and interpret multi-wavelength studies of galaxy populations in protoclusters., Comment: 24 pages, 16 figures (including Appendix), submitted to ApJ. Comments are very welcome!

Mindfulness, a practice of bringing attention to the present non-judgmentally, has many mental and physical well-being benefits, especially when practiced consistently. Many technologies have been invented to support solo or group mindfulness practice such as mobile apps, live streams, virtual reality environments, and wearables. In this paper, we present findings from an interview study with 20 experienced mindfulness practitioners about their everyday mindfulness practices and technology use. Participants identify the benefits and challenges of developing long-term commitment to mindfulness practice. They employ various strategies, such as brief mindfulness exercises, social accountability, and guidance from teachers, to sustain their practice. While conflicted about technology, they adopt and appropriate a range of technologies in their practice for reminders, emotion tracking, connecting with others, and attending online sessions. They also carefully consider when to use technology, when and how to limit its use, and ways to incorporate technology as an object for mindfulness. Based on our findings, we discuss expanding the definition of mindfulness and the tension between supporting short- and long-term mindfulness practice. We also propose a set of design recommendations to support everyday mindfulness including such as through the lens of metaphor, reappropriating non-mindfulness technology, and bringing community support into personal practice., Comment: Manuscripts accepted to Proc. ACM Hum.-Comput. Interact (CSCW24)

Elucidating the processes that shape the circumgalactic medium (CGM) is crucial for understanding galaxy evolution. Absorption and emission diagnostics can be interpreted using photoionization calculations to obtain information about the phase and ionization structure of the CGM. For simplicity, typically only the metagalactic background is considered in photoionization calculations, and local sources are ignored. To test this simplification, we perform Monte Carlo radiation transfer on 12 cosmological zoom-in simulations from the Feedback in Realistic Environments (FIRE) project with halo masses $10^{10.5}-10^{13} \mathrm{M}_{\odot}$ in the redshift range $z = 0-3.5$ to determine the spatial extent over which local sources appreciably contribute to the ionizing radiation field in the CGM. We find that on average, the contribution of stars within the galaxy is small beyond one-tenth of the virial radius, $R_{\mathrm{vir}}$, for $z < 1$. For $1 10^{12} \mathrm{M}_{\odot}$ at $z \sim 1.5-2.5$ and for all $M_{\mathrm{vir}}$ considered at $z>3$ , this transition radius can sometimes exceed 0.5 $R_{\mathrm{vir}}$. We also compute the escape fraction at $R_{\mathrm{vir}}$, finding typical values of less than $0.1$, except in higher-mass halos ($M_{\mathrm{halo}} \gtrsim 10^{12} \mathrm{M}_{\odot}$), which have consistently high values of $\sim 0.5-0.6$. Our results indicate that at low redshift, it is reasonable to ignore the ionizing radiation from host-galaxy stars outside of 0.2 $R_{\mathrm{vir}}$, while at Cosmic Noon, local stellar ionizing radiation likely extends further into the CGM and thus should be included in photoionization calculations., Comment: Submitted to OJA

The quantitative analysis of political ideological positions is a difficult task. In the past, various literature focused on parliamentary voting data of politicians, party manifestos and parliamentary speech to estimate political disagreement and polarization in various political systems. However previous methods of quantitative political analysis suffered from a common challenge which was the amount of data available for analysis. Also previous methods frequently focused on a more general analysis of politics such as overall polarization of the parliament or party-wide political ideological positions. In this paper, we present a method to analyze ideological positions of individual parliamentary representatives by leveraging the latent knowledge of LLMs. The method allows us to evaluate the stance of politicians on an axis of our choice allowing us to flexibly measure the stance of politicians in regards to a topic/controversy of our choice. We achieve this by using a fine-tuned BERT classifier to extract the opinion-based sentences from the speeches of representatives and projecting the average BERT embeddings for each representative on a pair of reference seeds. These reference seeds are either manually chosen representatives known to have opposing views on a particular topic or they are generated sentences which where created using the GPT-4 model of OpenAI. We created the sentences by prompting the GPT-4 model to generate a speech that would come from a politician defending a particular position.

Spectral energy distribution (SED) fitting has been extensively used to determine the nature of the faint radio source population. Recent efforts have combined fits from multiple SED-fitting codes to account for the host galaxy and any active nucleus that may be present. We show that it is possible to produce similar-quality classifications using a single energy-balance SED fitting code, Prospector, to model up to 26 bands of UV$-$far-infrared aperture-matched photometry for $\sim$31,000 sources in the ELAIS-N1 field from the LOFAR Two-Metre Sky Survey (LoTSS) Deep fields first data release. One of a new generation of SED-fitting codes, Prospector accounts for potential contributions from radiative active galactic nuclei (AGN) when estimating galaxy properties, including star formation rates (SFRs) derived using non-parametric star formation histories. Combining this information with radio luminosities, we classify 92 per cent of the radio sources as a star-forming galaxy, high/low-excitation radio galaxy, or radio-quiet AGN and study the population demographics as a function of 150 MHz flux density, luminosity, SFR, stellar mass, redshift and apparent $r$-band magnitude. Finally, we use Prospector SED fits to investigate the SFR$-$150 MHz luminosity relation for a sample of $\sim$$133,000~3.6~\mu$m-selected $z<1$ sources, finding that the stellar mass dependence is significantly weaker than previously reported, and may disappear altogether at $\log_{10} (\mathrm{SFR}/M_\odot~\mathrm{yr}^{-1}) > 0.5$. This approach makes it significantly easier to classify radio sources from LoTSS and elsewhere, and may have important implications for future studies of star-forming galaxies at radio wavelengths., Comment: 20 pages, 13 figures, accepted for publication in MNRAS

The observationally-inferred size versus stellar-mass relationship (SMR) for low-mass galaxies provides an important test for galaxy formation models. However, the relationship relies on assumptions that relate observed luminosity profiles to underlying stellar mass profiles. Here we use the Feedback in Realistic Environments simulations of low-mass galaxies to explore how the predicted SMR changes depending on whether one uses star-particle counts directly or mock observations. We reproduce the SMR found in The Exploration of Local Volume Satellites survey remarkably well only when we infer stellar masses and sizes using mock observations. However, when we use star particles to directly infer stellar masses and half-mass radii, we find that our galaxies are too large and obey a SMR with too little scatter compared to observations. This discrepancy between the "true" galaxy size and mass and those derived in the mock observation approach is twofold. First, our simulated galaxies have higher and more varied MLRs at a fixed colour than those commonly-adopted, which tends to underestimate their stellar masses compared to their true, simulated values. Second, our galaxies have radially increasing MLR gradients therefore using a single MLR tends to under-predict the mass in the outer regions. Similarly, the true half-mass radius is larger than the half-light radius because the light is more concentrated than the mass. If our simulations are accurate representations of the real universe, then the relationship between galaxy size and stellar mass is even tighter for low-mass galaxies than is commonly inferred from observed relations., Comment: 11 pages, 7 figures, 1 table

Decision trees are commonly used predictive models due to their flexibility and interpretability. This paper is directed at quantifying the uncertainty of decision tree predictions by employing a Bayesian inference approach. This is challenging because these approaches need to explore both the tree structure space and the space of decision parameters associated with each tree structure. This has been handled by using Markov Chain Monte Carlo (MCMC) methods, where a Markov Chain is constructed to provide samples from the desired Bayesian estimate. Importantly, the structure and the decision parameters are tightly coupled; small changes in the tree structure can demand vastly different decision parameters to provide accurate predictions. A challenge for existing MCMC approaches is proposing joint changes in both the tree structure and the decision parameters that result in efficient sampling. This paper takes a different approach, where each distinct tree structure is associated with a unique set of decision parameters. The proposed approach, entitled DCC-Tree, is inspired by the work in Zhou et al. [23] for probabilistic programs and Cochrane et al. [4] for Hamiltonian Monte Carlo (HMC) based sampling for decision trees. Results show that DCC-Tree performs comparably to other HMC-based methods and better than existing Bayesian tree methods while improving on consistency and reducing the per-proposal complexity., Comment: 38 pages, 5 figures

Measurements of the size of dust continuum emission are an important tool for constraining the spatial extent of star formation and hence the build-up of stellar mass. Compact dust emission has generally been observed at Cosmic Noon (z~2-3). However, at earlier epochs, toward the end of the Reionization (z~4-6), only the sizes of a handful of IR-bright galaxies have been measured. In this work, we derive the dust emission sizes of main-sequence galaxies at z~5 from the ALPINE survey. We measure the dust effective radius r_e,FIR in the uv-plane in Band 7 of ALMA for seven ALPINE galaxies with resolved emission and we compare it with rest-frame UV and [CII]158$\mu$m measurements. We study the r_e,FIR-L_IR scaling relation by considering our dust size measurements and all the data in literature at z~4-6. Finally, we compare our size measurements with predictions from simulations. The dust emission in the selected ALPINE galaxies is rather extended (r_e,FIR~1.5-3 kpc), similar to [CII]158 um but a factor of ~2 larger than the rest-frame UV emission. Putting together all the measurements at z~5, spanning 2 decades in luminosity from L_IR ~ 10^11 L_sun to L_IR ~ 10^13 L_sun, the data highlight a steeply increasing trend of the r_e,FIR-L_IR relation at L_IR< 10^12 L_sun, followed by a downturn and a decreasing trend at brighter luminosities. Finally, simulations that extend up to the stellar masses of the ALPINE galaxies considered in the present work predict a sub-set of galaxies (~25% at 10^10 M_sun < M_star < 10^11 M_sun) with sizes as large as those measured., Comment: 8 pages, Accepted by A&A

Decision trees have found widespread application within the machine learning community due to their flexibility and interpretability. This paper is directed towards learning decision trees from data using a Bayesian approach, which is challenging due to the potentially enormous parameter space required to span all tree models. Several approaches have been proposed to combat this challenge, with one of the more successful being Markov chain Monte Carlo (MCMC) methods. The efficacy and efficiency of MCMC methods fundamentally rely on the quality of the so-called proposals, which is the focus of this paper. In particular, this paper investigates using a Hamiltonian Monte Carlo (HMC) approach to explore the posterior of Bayesian decision trees more efficiently by exploiting the geometry of the likelihood within a global update scheme. Two implementations of the novel algorithm are developed and compared to existing methods by testing against standard datasets in the machine learning and Bayesian decision tree literature. HMC-based methods are shown to perform favourably with respect to predictive test accuracy, acceptance rate, and tree complexity., Comment: 43 pages, 7 figures

We investigate the formation of dense stellar clumps in a suite of high-resolution cosmological zoom-in simulations of a massive, star forming galaxy at $z \sim 2$ under the presence of strong quasar winds. Our simulations include multi-phase ISM physics from the Feedback In Realistic Environments (FIRE) project and a novel implementation of hyper-refined accretion disk winds. We show that powerful quasar winds can have a global negative impact on galaxy growth while in the strongest cases triggering the formation of an off-center clump with stellar mass ${\rm M}_{\star}\sim 10^{7}\,{\rm M}_{\odot}$, effective radius ${\rm R}_{\rm 1/2\,\rm Clump}\sim 20\,{\rm pc}$, and surface density $\Sigma_{\star} \sim 10^{4}\,{\rm M}_{\odot}\,{\rm pc}^{-2}$. The clump progenitor gas cloud is originally not star-forming, but strong ram pressure gradients driven by the quasar winds (orders of magnitude stronger than experienced in the absence of winds) lead to rapid compression and subsequent conversion of gas into stars at densities much higher than the average density of star-forming gas. The AGN-triggered star-forming clump reaches ${\rm SFR} \sim 50\,{\rm M}_{\odot}\,{\rm yr}^{-1}$ and $\Sigma_{\rm SFR} \sim 10^{4}\,{\rm M}_{\odot}\,{\rm yr}^{-1}\,{\rm kpc}^{-2}$, converting most of the progenitor gas cloud into stars in $\sim$2\,Myr, significantly faster than its initial free-fall time and with stellar feedback unable to stop star formation. In contrast, the same gas cloud in the absence of quasar winds forms stars over a much longer period of time ($\sim$35\,Myr), at lower densities, and losing spatial coherency. The presence of young, ultra-dense, gravitationally bound stellar clumps in recently quenched galaxies could thus indicate local positive feedback acting alongside the strong negative impact of powerful quasar winds, providing a plausible formation scenario for globular clusters., Comment: 14 pages, 12 figures. Accepted for publication in MNRAS; doi:10.1093/mnras/stae1021

We investigate how the recovery of galaxy star formation rates (SFRs) using energy-balance spectral energy distribution (SED) fitting codes depends on their recent star formation histories (SFHs). We use the Magphys and Prospector codes to fit 6,706 synthetic spectral energy distributions of simulated massive galaxies at $1 < z < 8$ from the Feedback in Realistic Environments (FIRE) project. We identify a previously-unknown systematic error in the Magphys results due to bursty star formation: the derived SFRs can differ from the truth by as much as 1 dex, at large statistical significance ($>5\sigma$), depending on the details of their recent SFH. SFRs inferred using Prospector with non-parametric SFHs do not exhibit this trend. We show that using parametric SFHs (pSFHs) causes SFR uncertainties to be underestimated by a factor of up to $5\times$. Although this undoubtedly contributes to the significance of the systematic, it cannot explain the largest biases in the SFRs of the starbursting galaxies, which could be caused by details of the stochastic prior sampling or the burst implementation in the Magphys libraries. We advise against using pSFHs and urge careful consideration of starbursts when SED modelling galaxies where the SFR may have changed significantly over the last ~100 Myr, such as recently quenched galaxies, or those experiencing a burst. This concern is especially relevant, e.g. when fitting JWST observations of very high-redshift galaxies., Comment: 5 pages, 3 figures, accepted for publication in MNRAS Letters

Galaxies that are invisible in deep optical-NIR imaging but detected at longer wavelengths have been the focus of several recent observational studies, with speculation that they could constitute a substantial missing population and even dominate the cosmic star formation rate density at $z\gtrsim4$. The depths now achievable with JWST at the longest wavelengths probed by HST, coupled with the transformative resolution at longer wavelengths, are already enabling detailed, spatially-resolved characterisation of sources that were invisible to HST, often known as `HST-dark' galaxies. However, until now, there has been little theoretical work to compare against. We present the first simulation-based study of this population, using highly-resolved galaxies from the Feedback in Realistic Environments (FIRE) project, with multi-wavelength images along several lines of sight forward-modelled using radiative transfer. We naturally recover a population of modelled sources that meet commonly-used selection criteria ($H_{\rm{AB}}>27\,\rm{mag}$ and $H_{\rm{AB}}-\rm{F444W}>2.3$). These simulated HST-dark galaxies lie at high redshifts ($z=4-7$), have high levels of dust attenuation ($A_{V}=2-4$), and display compact recent star formation ($R_{1/2,\,\rm{4.4\,\mu\rm{m}}}\lesssim1\,\rm{kpc}$). Orientation is very important: for all but one of the 17 simulated galaxy snapshots with HST-dark sightlines, there exist other sightlines that do not meet the criteria. This result has important implications for comparisons between observations and models that do not resolve the detailed star-dust geometry, such as semi-analytic models or coarsely-resolved hydrodynamical simulations. Critically, we demonstrate that HST-dark sources are not an unexpected or exotic population, but a subset of high-redshift, highly-dust-attenuated sources viewed along certain lines of sight., Comment: 12 pages, 8 figures. Accepted for publication in ApJ

Recent works have suggested that energy balance spectral energy distribution (SED) fitting codes may be of limited use for studying high-redshift galaxies for which the observed ultraviolet and far-infrared emission are offset (spatially `decoupled'). It has been proposed that such offsets could lead energy balance codes to miscalculate the overall energetics, preventing them from recovering such galaxies' true properties. In this work, we test how well the SED fitting code Magphys can recover the stellar mass, star formation rate (SFR), specific SFR, dust mass and luminosity by fitting 6,706 synthetic SEDs generated from four zoom-in simulations of dusty, high-redshift galaxies from the FIRE project via dust continuum radiative transfer. Comparing our panchromatic results (using wavelengths 0.4-500$\mu$m, and spanning $1

Forward-modeling observables from galaxy simulations enables direct comparisons between theory and observations. To generate synthetic spectral energy distributions (SEDs) that include dust absorption, re-emission, and scattering, Monte Carlo radiative transfer is often used in post-processing on a galaxy-by-galaxy basis. However, this is computationally expensive, especially if one wants to make predictions for suites of many cosmological simulations. To alleviate this computational burden, we have developed a radiative transfer emulator using an artificial neural network (ANN), ANNgelina, that can reliably predict SEDs of simulated galaxies using a small number of integrated properties of the simulated galaxies: star formation rate, stellar and dust masses, and mass-weighted metallicities of all star particles and of only star particles with age <10 Myr. Here, we present the methodology and quantify the accuracy of the predictions. We train the ANN on SEDs computed for galaxies from the IllustrisTNG project's TNG50 cosmological magnetohydrodynamical simulation. ANNgelina is able to predict the SEDs of TNG50 galaxies in the ultraviolet (UV) to millimetre regime with a typical median absolute error of ~7 per cent. The prediction error is the greatest in the UV, possibly due to the viewing-angle dependence being greatest in this wavelength regime. Our results demonstrate that our ANN-based emulator is a promising computationally inexpensive alternative for forward-modeling galaxy SEDs from cosmological simulations.

Supramolecular chemistry protocols applied on surfaces offer compelling avenues for atomic scale control over organic-inorganic interface structures. In this approach, adsorbate-surface interactions and two-dimensional confinement can lead to morphologies and properties that differ dramatically from those achieved via conventional synthetic approaches. Here, we describe the bottom-up, on-surface synthesis of one-dimensional coordination nanostructures based on an iron (Fe)-terpyridine (tpy) interaction borrowed from functional metal-organic complexes used in photovoltaic and catalytic applications. Thermally activated diffusion of sequentially deposited ligands and metal atoms, and intra-ligand conformational changes, lead to Fe-tpy coordination and formation of these nanochains. Low-temperature Scanning Tunneling Microscopy and Density Functional Theory were used to elucidate the atomic-scale morphology of the system, providing evidence of a linear tri-Fe linkage between facing, coplanar tpy groups. Scanning Tunneling Spectroscopy reveals highest occupied orbitals with dominant contributions from states located at the Fe node, and ligand states that mostly contribute to the lowest unoccupied orbitals. This electronic structure yields potential for hosting photo-induced metal-to-ligand charge transfer in the visible/near-infrared. The formation of this unusual tpy/tri-Fe/tpy coordination motif has not been observed for wet chemistry synthesis methods, and is mediated by the bottom-up on-surface approach used here.

Semiconductor quantum dots operated dynamically are the basis of many quantum technologies such as quantum sensors and computers. Hence, modelling their electrical properties at microwave frequencies becomes essential to simulate their performance in larger electronic circuits. Here, we develop a self-consistent quantum master equation formalism to obtain the admittance of a quantum dot tunnel-coupled to a charge reservoir under the effect of a coherent photon bath. We find a general expression for the admittance that captures the well-known semiclassical (thermal) limit, along with the transition to lifetime and power broadening regimes due to the increased coupling to the reservoir and amplitude of the photonic drive, respectively. Furthermore, we describe two new photon-mediated regimes: Floquet broadening, determined by the dressing of the QD states, and broadening determined by photon loss in the system. Our results provide a method to simulate the high-frequency behaviour of QDs in a wide range of limits, describe past experiments, and propose novel explorations of QD-photon interactions.

Recent discoveries of a significant population of bright galaxies at cosmic dawn $\left(z \gtrsim 10\right)$ have enabled critical tests of cosmological galaxy formation models. In particular, the bright end of the galaxy UV luminosity function (UVLF) appears higher than predicted by many models. Using approximately 25,000 galaxy snapshots at $8 \leq z \leq 12$ in a suite of FIRE-2 cosmological "zoom-in'' simulations from the Feedback in Realistic Environments (FIRE) project, we show that the observed abundance of UV-bright galaxies at cosmic dawn is reproduced in these simulations with a multi-channel implementation of standard stellar feedback processes, without any fine-tuning. Notably, we find no need to invoke previously suggested modifications such as a non-standard cosmology, a top-heavy stellar initial mass function, or a strongly enhanced star formation efficiency. We contrast the UVLFs predicted by bursty star formation in these original simulations to those derived from star formation histories (SFHs) smoothed over prescribed timescales (e.g., 100 Myr). The comparison demonstrates that the strongly time-variable SFHs predicted by the FIRE simulations play a key role in correctly reproducing the observed, bright-end UVLFs at cosmic dawn: the bursty SFHs induce order-or-magnitude changes in the abundance of UV-bright ($M_\mathrm{UV} \lesssim -20$) galaxies at $z \gtrsim 10$. The predicted bright-end UVLFs are consistent with both the spectroscopically confirmed population and the photometrically selected candidates. We also find good agreement between the predicted and observationally inferred integrated UV luminosity densities, which evolve more weakly with redshift in FIRE than suggested by some other models., Comment: 12 pages, 4 figures + 1 table, ApJL accepted

Radio-mode feedback is a key ingredient in galaxy formation and evolution models, required to reproduce the observed properties of massive galaxies in the local Universe. We study the cosmic evolution of radio-AGN feedback out to $z\sim2.5$ using a sample of 9485 radio-excess AGN. We combine the evolving radio luminosity functions with a radio luminosity scaling relationship to estimate AGN jet kinetic powers and derive the cosmic evolution of the kinetic luminosity density, $\Omega_{\rm{kin}}$ (i.e. the volume-averaged heating output). Compared to all radio-AGN, low-excitation radio galaxies (LERGs) dominate the feedback activity out to $z\sim2.5$, with both these populations showing a constant heating output of $\Omega_{\rm{kin}} \approx 4-5 \times 10^{32}\,\rm{W\,Mpc^{-3}}$ across $0.5 < z < 2.5$. We compare our observations to predictions from semi-analytical and hydrodynamical simulations, which broadly match the observed evolution in $\Omega_{\rm{kin}}$, although their absolute normalisation varies. Comparison to the Semi-Analytic Galaxy Evolution (SAGE) model suggests that radio-AGN may provide sufficient heating to offset radiative cooling losses, providing evidence for a self-regulated AGN feedback cycle. We integrate the kinetic luminosity density across cosmic time to obtain the kinetic energy density output from AGN jets throughout cosmic history to be $\sim 10^{50}\,\rm{J\,Mpc^{-3}}$. Compared to AGN winds, the kinetic energy density from AGN jets dominates the energy budget at $z \lesssim 2$; this suggests that AGN jets play an important role in AGN feedback across most of cosmic history., Comment: 15 pages, 6 figures, accepted for publication in MNRAS

We present a detailed study of the cosmic star formation history over $90$ per cent of cosmic time ($0\lesssim z\lesssim4$), using deep, radio continuum observations that probe star formation activity independent of dust. The Low Frequency Array Two Metre Sky Survey has imaged three well-studied extragalactic fields, Elais-N1, Bo\"otes and the Lockman Hole, reaching $\sim20\,\mu\rm{Jy/beam}$ rms sensitivity at $150\,\rm{MHz}$. The availability of high-quality ancillary data from ultraviolet to far-infrared wavelengths has enabled accurate photometric redshifts and the robust separation of radio-bright AGN from their star-forming counterparts. We capitalise on this unique combination of deep, wide fields and robustly-selected star-forming galaxies to construct radio luminosity functions and derive the cosmic star formation rate density. We carefully constrain and correct for scatter in the $L_{150\,\rm{MHz}}-\rm{SFR}$ relation, which we find to be $\sim0.3\,\rm{dex}$. Our derived star formation rate density lies between previous measurements at all redshifts studied. We derive higher star formation rate densities between $z\sim0$ and $z\sim3$ than are typically inferred from short wavelength emission; at earlier times, this discrepancy is reduced. Our measurements are generally in good agreement with far-infrared and radio-based studies, with small offsets resulting from differing star formation rate calibrations., Comment: 22 pages, 14 figures; accepted for publication in MNRAS

Source classifications, stellar masses and star formation rates are presented for 80,000 radio sources from the first data release of the Low Frequency Array Two-metre Sky Survey (LoTSS) Deep Fields, which represents the widest deep radio survey ever undertaken. Using deep multi-wavelength data spanning from the ultraviolet to the far-infrared, spectral energy distribution (SED) fitting is carried out for all of the LoTSS-Deep host galaxies using four different SED codes, two of which include modelling of the contributions from an active galactic nucleus (AGN). Comparing the results of the four codes, galaxies that host a radiative AGN are identified, and an optimised consensus estimate of the stellar mass and star-formation rate for each galaxy is derived. Those galaxies with an excess of radio emission over that expected from star formation are then identified, and the LoTSS-Deep sources are divided into four classes: star-forming galaxies, radio-quiet AGN, and radio-loud high-excitation and low-excitation AGN. Ninety-five per cent of the sources can be reliably classified, of which more than two-thirds are star-forming galaxies, ranging from normal galaxies in the nearby Universe to highly-starbursting systems at z>4. Star-forming galaxies become the dominant population below 150-MHz flux densities of about 1 mJy, accounting for 90 per cent of sources at a 150-MHz flux density of 100 microJy. Radio-quiet AGN comprise around 10 per cent of the overall population. Results are compared against the predictions of the SKADS and T-RECS radio sky simulations, and improvements to the simulations are suggested., Comment: Accepted for publication in MNRAS. Catalogues available at www.lofar-surveys.org/deepfields.html. 27 pages

We present a feasibility study for passive sounding of Uranian icy moons using Uranian Kilometric Radio (UKR) emissions in the 100 - 900 kHz band. We provide a summary description of the observation geometry, the UKR characteristics, and estimate the sensitivity for an instrument analogous to the Cassini Radio Plasma Wave Science (RPWS) but with a modified receiver digitizer and signal processing chain. We show that the concept has the potential to directly and unambiguously detect cold oceans within Uranian satellites and provide strong constraints on the interior structure in the presence of warm or no oceans. As part of a geophysical payload, the concept could therefore have a key role in the detection of oceans within the Uranian satellites. The main limitation of the concept is coherence losses attributed to the extended source size of the UKR and dependence on the illumination geometry. These factors represent constraints on the tour design of a future Uranus mission in terms of flyby altitudes and encounter timing.

Fast measurements of quantum devices is important in areas such as quantum sensing, quantum computing and nanodevice quality analysis. Here, we develop a superconductor-semiconductor multi-module microwave assembly to demonstrate charge state readout at the state-of-the-art. The assembly consist of a superconducting readout resonator interfaced to a silicon-on-insulator (SOI) chiplet containing quantum dots (QDs) in a high-$\kappa$ nanowire transistor. The superconducting chiplet contains resonant and coupling elements as well as $LC$ filters that, when interfaced with the silicon chip, result in a resonant frequency $f=2.12$ GHz, a loaded quality factor $Q=850$, and a resonator impedance $Z=470$ $\Omega$. Combined with the large gate lever arms of SOI technology, we achieve a minimum integration time for single and double QD transitions of 2.77 ns and 13.5 ns, respectively. We utilize the assembly to measure charge noise over 9 decades of frequency up to 500 kHz and find a 1/$f$ dependence across the whole frequency spectrum as well as a charge noise level of 4 $\mu$eV/$\sqrt{\text{Hz}}$ at 1 Hz. The modular microwave circuitry presented here can be directly utilized in conjunction with other quantum device to improve the readout performance as well as enable large bandwidth noise spectroscopy, all without the complexity of superconductor-semiconductor monolithic fabrication., Comment: Main: 8 pages, 4 figures. Supplementary: 4 pages, 7 figures