arXiv subjects

David Sweeney

Publications and source records attributed to David Sweeney.

11 recordsLinked to original sources

arXiv2026

Predictions for astrometric microlensing in Gaia

ESA's astrometric space mission Gaia is uniquely positioned for microlensing studies thanks to its all-sky coverage and simultaneous astrometric and photometric observations. In Gaia Data Release 4 (DR4), astrometric time series will be published for the first time, providing a rich dataset for isolated stellar remnant searches. In anticipation of DR4, we prepared tools for fitting photometric and 1D astrometric measurements. We tested the recovery of true event parameters and population distributions with Gaia-like observations. We created a mock survey of microlensing events mirroring Gaia DR4's design. The events were generated using dedicated Galactic simulations to provide realistic expectations on stellar and dark lens yields. For selected events, we simulated observations following Gaia's scanning law and precision, using the astromet package. Such simulations are needed to interpret forthcoming data; they also enable testing inference tools with known ground truth. We used nested sampling to infer full posterior distributions and compare them with the true lens parameters. Our simulation predicts $322 \pm 70$ microlensing events with astrometric signals above Gaia precision thresholds; $209 \pm 57$ of them have detectable photometric signals. Among those, $82 \pm 9$ and $49 \pm 7$, respectively, have remnant lenses. To assess Gaia's capabilities in constraining remnant mass distributions, we modelled $49$ events from this sample. We recovered the true Einstein times and radii for most events. Microlensing parallax measurements are consistent with true values but uncertain, limiting mass determination. We recommend focusing on events with bright sources or anomalous fits to optimize dark lens searches. We make available the mock Gaia time-series dataset, as well as a toolkit repository for working with the data format, fitting models, and visualizing results.

astro-ph.GA↗

arXiv2026

Mitigating effects of telescope jitter through differentiable forward-modeling

Instabilities in telescope pointing, commonly referred to as jitter, introduce image degradation that can compromise the accuracy of critical scientific observables. This work presents a differentiable forward-modeling approach to both understand and mitigate the impact of jitter. We apply dLux -- a differentiable optical simulation framework built in the JAX numerical simulation framework -- to model the blurring effects of jitter on the final image. We categorize jitter into low-, medium-, and high-frequency regimes with respect to the camera frame rate and build simple jitter models based on its manifestation on the detector. The forward-model approach proves effective for low- and high-frequency regimes, but the inherent unpredictability of medium-frequency jitter may lead to model misspecification. As a test case we apply these models to the TOLIMAN mission, a forthcoming CubeSat telescope dedicated to detecting nearby Earth-analogue exoplanets through high-precision astrometry. Using Fisher information analysis, we quantify the effect of jitter on TOLIMAN's primary science observable -- the angular binary separation of the Alpha Centauri AB binary components. We find model misspecification does not introduce a systematic bias on the recovered binary separation except when fitting a one-dimensional jitter model to a two-dimensional motion, hence we recommend the use of a two-dimensional model. The forward-model approach offers a generalized method applicable to other telescope systems, including ongoing work with JWST's NIRISS instrument. This approach represents a significant step toward delivering higher accuracy measurements at modern observatories as demands on precision continue to rise.

astro-ph.IM↗

arXiv2026

The TOLIMAN mission: A low-cost space telescope for high precision narrow-angle astrometry

The TOLIMAN project is engaged with the construction, launch and operation of a low-cost space telescope of unorthodox optical design. Its primary science goal targets an exhaustive search for temperate-orbit rocky planets around either star in the alpha Centauri AB binary within our nearest-neighbor star system. Despite their favorable proximity and brightness, the detection of terrestrial exoplanets around such nearby Sun-like stars remains problematic for contemporary instrumental approaches. By performing narrow-angle astrometric monitoring of binary stars at extreme precision, any exoplanets will betray their presence by way of gravitationally-induced perturbations on the binary orbit. Recovery of this signal is challenging for it amounts to only a few microarcseconds of angular deflection (at best), and so is normally thought to require a large (meter-class) instrument. By implementing an innovative optical and signal encoding architecture, the TOLIMAN space telescope aims to recover such signals with a telescope aperture of only 12.5cm. This paper gives an overview of key features of the mission; in particular the concepts underlying the optics to enable image registration at the extreme levels of precision required. An outline is also provided, sketching further mission components and systems incorporated into the 16U CubeSat spacecraft bus in which the science payload is housed - all of which are now under construction.

astro-ph.IM↗

arXiv2025

Semi-Supervised Learning for Lensed Quasar Detection

Lensed quasars are key to many areas of study in astronomy, offering a unique probe into the intermediate and far universe. However, finding lensed quasars has proved difficult despite significant efforts from large collaborations. These challenges have limited catalogues of confirmed lensed quasars to the hundreds, despite theoretical predictions that they should be many times more numerous. We train machine learning classifiers to discover lensed quasar candidates. By using semi-supervised learning techniques we leverage the large number of potential candidates as unlabelled training data alongside the small number of known objects, greatly improving model performance. We present our two most successful models: (1) a variational autoencoder trained on millions of quasars to reduce the dimensionality of images for input to a dense neural network classifier that can make accurate predictions and (2) a convolutional neural network trained on a mix of labelled and unlabelled data via virtual adversarial training. These models are both capable of producing high-quality candidates, as evidenced by our discovery of GRALJ140833.73+042229.98. The success of our classifier, which uses only multi-band images, is particularly exciting as it can be combined with existing classifiers, which use other data than images, to improve the classifications of both models and discover more lensed quasars.

astro-ph.IM↗

arXiv2025

Bias-preserving and error-detectable entangling operations in a superconducting dual-rail system

For useful quantum computation, error-corrected machines are required that can dramatically reduce the inevitable errors experienced by physical qubits. While significant progress has been made in approaching and exceeding the surface-code threshold in superconducting platforms, large gains in the logical error rate with increasing system size remain out of reach. This is due both to the large number of required physical qubits and the need to operate far below threshold. Importantly, by exploiting the biases and structure of the physical errors, this threshold can be raised. Erasure qubits achieve this by detecting certain errors at the hardware level. Dual-rail qubits encoded in superconducting cavities are a promising erasure qubit wherein the dominant error, photon loss, can be detected and converted to an erasure. In these approaches, the complete set of operations, including two qubit gates, must be high performance and preserve as much of the desirable hierarchy or bias in the errors as possible. Here, we design and realize a novel two-qubit gate for dual-rail erasure qubits based on superconducting microwave cavities. The gate is high-speed ($\sim$500 ns duration), and yields a residual gate infidelity after error detection below 0.1%. Moreover, we experimentally demonstrate that this gate largely preserves the favorable error structure of idling dual-rail qubits, making it ideal for error correction. We measure low erasure rates of $\sim$0.5% per gate, as well as low and asymmetric dephasing errors that occur at least three times more frequently on control qubits compared to target qubits. Bit-flip errors are practically nonexistent, bounded at the few parts per million level. This error asymmetry has not been well explored but is extremely useful in quantum error correction and flag-qubit contexts, where it can create a faster path to effective error-corrected systems.

quant-ph↗

arXiv2024

Observing the Galactic Underworld: Predicting photometry and astrometry from compact remnant microlensing events

Isolated black holes (BHs) and neutron stars (NSs) are largely undetectable across the electromagnetic spectrum. For this reason, our only real prospect of observing these isolated compact remnants is via microlensing; a feat recently performed for the first time. However, characterisation of the microlensing events caused by BHs and NSs is still in its infancy. In this work, we perform N-body simulations to explore the frequency and physical characteristics of microlensing events across the entire sky. Our simulations find that every year we can expect $88_{-6}^{+6}$ BH, $6.8_{-1.6}^{+1.7}$ NS and $20^{+30}_{-20}$ stellar microlensing events which cause an astrometric shift larger than 2~mas. Similarly, we can expect $21_{-3}^{+3}$ BH, $18_{-3}^{+3}$ NS and $7500_{-500}^{+500}$ stellar microlensing events which cause a bump magnitude larger than 1~mag. Leveraging a more comprehensive dynamical model than prior work, we predict the fraction of microlensing events caused by BHs as a function of Einstein time to be smaller than previously thought. Comparison of our microlensing simulations to events in Gaia finds good agreement. Finally, we predict that in the combination of Gaia and GaiaNIR data there will be $14700_{-900}^{+600}$ BH and $1600_{-200}^{+300}$ NS events creating a centroid shift larger than 1~mas and $330_{-120}^{+100}$ BH and $310_{-100}^{+110}$ NS events causing bump magnitudes $> 1$. Of these, $<10$ BH and $5_{-5}^{+10}$ NS events should be detectable using current analysis techniques. These results inform future astrometric mission design, such as GaiaNIR, as they indicate that, compared to stellar events, there are fewer observable BH events than previously thought.

astro-ph.GA↗

arXiv2023

Nonlinear wavefront reconstruction from a pyramid sensor using neural networks

The pyramid wavefront sensor (PyWFS) has become increasingly popular to use in adaptive optics (AO) systems due to its high sensitivity. The main drawback of the PyWFS is that it is inherently nonlinear, which means that classic linear wavefront reconstruction techniques face a significant reduction in performance at high wavefront errors, particularly when the pyramid is unmodulated. In this paper, we consider the potential use of neural networks (NNs) to replace the widely used matrix vector multiplication (MVM) control. We aim to test the hypothesis that the neural network (NN)'s ability to model nonlinearities will give it a distinct advantage over MVM control. We compare the performance of a MVM linear reconstructor against a dense NN, using daytime data acquired on the Subaru Coronagraphic Extreme Adaptive Optics system (SCExAO) instrument. In a first set of experiments, we produce wavefronts generated from 14 Zernike modes and the PyWFS responses at different modulation radii (25, 50, 75, and 100 mas). We find that the NN allows for a far more precise wavefront reconstruction at all modulations, with differences in performance increasing in the regime where the PyWFS nonlinearity becomes significant. In a second set of experiments, we generate a dataset of atmosphere-like wavefronts, and confirm that the NN outperforms the linear reconstructor. The SCExAO real-time computer software is used as baseline for the latter. These results suggest that NNs are well positioned to improve upon linear reconstructors and stand to bring about a leap forward in AO performance in the near future.

astro-ph.IM↗

arXiv2023

Probing Dust and Water in Martian Atmosphere with Far-Infrared Frequency Spacecraft Occultation

Airborne dust plays an active role in determining the thermal structure and chemical composition of the present-day atmosphere of Mars and possibly the planet's climate evolution over time through radiative--convective and cloud microphysics processes. Thus, accurate measurements of the distribution and variability of dust are required. Observations from the Mars Global Surveyor/Thermal Emission Spectrometer Mars Mars Reconnaissance Orbiter/Mars Climate Sounder and Mars Express/Fourier Transform Spectrometer and the Curiosity Rover have limited capability to measure dust. We show that spacecraft occultation of the Martian atmosphere at far-infrared frequencies between 1 and 10 THz can provide the needed global and temporal data on atmospheric dust by providing co-located measurements of temperature and dust opacity from the top of the atmosphere all the way down to the surface. In addition, spacecraft occultation by a small-satellite constellation could provide global measurements of the development of dust storms.

astro-ph.EP↗

arXiv2022

The Galactic Underworld: The spatial distribution of compact remnants

We chart the expected Galactic distribution of neutron stars and black holes. These compact remnants of dead stars -- the Galactic underworld -- are found to exhibit a fundamentally different distribution and structure to the visible Galaxy. Compared to the visible Galaxy, concentration into a thin flattened disk structure is much less evident with the scale height more than tripling to 1260 +- 30 pc. This difference arises from two primary causes. Firstly, the distribution is in part inherited from the integration over the evolving structure of the Galaxy itself (and hence the changing distribution of the parent stars). Secondly, an even larger effect arises from the natal kick received by the remnant at the event of its supernova birth. Due to this kick we find 30% of remnants have sufficient kinetic energy to entirely escape the Galactic potential (40% of neutron stars and 2% of black holes) leading to a Galactic mass loss integrated to the present day of ~ 0.4% of the stellar mass of the Galaxy. The black hole -- neutron star fraction increases near the Galactic centre: a consequence of smaller kick velocities in the former (the assumption made is that kick velocity is inversely proportional to mass). Our simulated remnant distribution yields probable distances of 19 pc and 21 pc to the nearest neutron star and black hole respectively, while our nearest probable magnetar lies at 4.2 kpc. Although the underworld only contains of order ~ 1% of the Galaxy's mass, observational signatures and physical traces of its population, such as microlensing, will become increasingly present in data ranging from gravitational wave detectors to high precision surveys from space missions such as Gaia.

astro-ph.GA↗

arXiv2021

Learning the Lantern: Neural network applications to broadband photonic lantern modelling

Photonic lanterns allow the decomposition of highly multimodal light into a simplified modal basis such as single-moded and/or few-moded. They are increasingly finding uses in astronomy, optics and telecommunications. Calculating propagation through a photonic lantern using traditional algorithms takes $\sim 1$ hour per simulation on a modern CPU. This paper demonstrates that neural networks can bridge the disparate opto-electronic systems, and when trained can achieve a speed-up of over 5 orders of magnitude. We show that this approach can be used to model photonic lanterns with manufacturing defects as well as successfully generalising to polychromatic data. We demonstrate two uses of these neural network models, propagating seeing through the photonic lantern as well as performing global optimisation for purposes such as photonic lantern funnels and photonic lantern nullers.

physics.optics↗

arXiv2021

Achromatic photonic tricouplers for application in nulling interferometry

Integrated-optic components are being increasingly used in astrophysics, mainly where accuracy and precision are paramount. One such emerging technology is nulling interferometry that targets high contrast and high angular resolution. Two of the most critical limitations encountered by nullers are rapid phase fluctuations in the incoming light causing instability in the interference and chromaticity of the directional couplers that prevent a deep broadband interferometric null. We explore the use of a tricoupler designed by ultrafast laser inscription that solves both issues. Simulations of a tricoupler, incorporated into a nuller, result in order of a magnitude improvement in null depth.

astro-ph.IM↗