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Physics Astrophysics Instrumentation and Methods for Astrophysics

astro-ph.IM Watch Instrumentation and Methods for Astrophysics

Saturday 26 September

Instrumentation and Methods for Astrophysics

GPUPHOT: A Python Framework for High-Performance GPU-Accelerated Photometry and Distributed Astronomical Data Reduction

Samuel Lemes-Perera, Miguel R. Alarcon, Miquel Serra-Ricart et al. (+1 more)

We present GPUPHOT, an open-source Python framework for GPU-accelerated real-time photometry and astrometry of astronomical CCD and scientific CMOS images. Four of its seven stages run entirely on the GPU through CuPy (background estimation, source detection, PSF modeling and aperture photometry); the catalog crossmatch selects a CPU or GPU backend by problem size, and the zero-point and astrometric calibrations run on the CPU, within a containerized distributed system. Checkpoint-based GPU memory monitoring and an opt-in spatial-binning fallback let a single container image run on GPUs from a 4 GB laptop card to 80 GB datacenter accelerators. We benchmark the framework on nineteen observations from two robotic facilities, the Two-meter Twin Telescope and the Transient Survey Telescope, spanning 4.2 to 151.2 megapixels and 228 to 134,206 cataloged sources, on eight NVIDIA GPU platforms with one process per image. The H100 completes the densest 151.2-megapixel field end-to-end in 31.9 s, and GPU source detection on the A100 is 6-15x faster than the CPU library sep on the same frames. Once three sources of non-determinism are pinned, catalogs and zero points agree to the fourth decimal across GPU models and host CPUs. In this one-process-per-image regime the CuPy 14 / cuML stack showed a 7% lower peak memory and a median 38% higher per-image latency than CuPy 12, both due to the RAPIDS allocator displacing the CuPy memory pool at import; restoring the pool removes the memory difference and cuts the median overhead on datacenter GPUs to 11%, with identical output. Long-lived workers, the production mode, run the two stacks near parity. We recommend the CuPy 14 stack for its reproducibility and maintained libraries, not for memory or speed. GPUPHOT and its benchmark scripts are released for autonomous facilities that require end-to-end photometric reduction at survey cadence.
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All authors Samuel Lemes-Perera, Miguel R. Alarcon, Miquel Serra-Ricart, Pino Caballero-Gil

Instrumentation and Methods for Astrophysics · Cross-listed from physics.ins-det

Enhancing Conversion Gain in HEB Mixers using Negative Differential Resistance

Boris S. Karasik and Changyun Yoo

This work investigates how negative differential resistance (NDR) can be utilized to enhance conversion gain in superconducting niobium nitride (NbN) hot-electron bolometer (HEB) mixers. Conventional HEB operation avoids NDR regions due to parasitic oscillations caused by interactions between thermal inertia and bias-line reactance. Recent experimental results show that reducing the bias-T inductance suppresses these oscillations and enables stable biasing within the NDR regime, thereby increasing the mixer conversion gain beyond levels achievable under positive differential resistance (PDR) bias. Using a lumped thermal-electrical model, we interpret these experimental findings, derive stability conditions for NDR-biased operation, and predict the future performance limits achievable through optimized bias circuit designs. Our results indicate that further reductions in bias inductance, combined with appropriate load-line conditions, could yield several decibels of additional gain while maintaining practical IF bandwidths.
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Friday 25 September

Instrumentation and Methods for Astrophysics · Cross-listed from astro-ph.CO

CMB Data Analysis in the example of the POLARBEAR experiment and the LiteBIRD experiment

Kolen Cheung

In this dissertation, I briefly go through my subject areas — from Astrophysics, Cosmology, to Cosmic Microwave Background (CMB) radiation; and Data Science & High-Performance Computing. I go through the beginning of the Universe briefly in part I and introduce the Physics of the CMB in part II. Then I move on to how it can be observed experimentally, mathematically, and computationally in part III. In parts IV to VI, I write about 2 specific CMB experiments — POLARBEAR & LiteBIRD, together with my research involved in them. In part V, original research on a measurement of the CMB $B$-mode at sub-degree scales is presented using the 3rd-5th seasons of POLARBEAR observations. This demonstrates the capability of a single medium aperture telescope with a Continuously Rotating Half-Wave Plate (CRHWP) to target both the low-$\ell$ and high-$\ell$ $B$-mode science at $50 \leq \ell \leq 3000$. In part VI, the effect of detector crosstalk systematics on the CMB power-spectra is studied in detail in the example of the LiteBIRD experiment. An analytical, map-domain solution is developed, a computational simulation method is implemented, and the two predictions are compared using the LiteBIRD experiment design specification. The general agreement of the two shows that the analytical model well describes the LiteBIRD experiment, and can be used to calculate the systematic effects without performing time-consuming time-domain simulations with a high degree of accuracy. This can be used to forecast the amount of crosstalk systematics and to develop mitigation strategies. A mitigation strategy is presented, which is a hardware-based mitigation method that minimizes the crosstalk systematic effects in the 2pt power-spectra.
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2609.32037 · 25 Sep · PhD thesis, University of California, Berkeley, 2022. 241 pages, 66 figures, 6 tables. Filed version: https://escholarship.org/uc/item/0hh4w9v6. v2 corrects errors: fig. 4.1 overstated the FIRAS 1{\sigma} uncertainty tenfold; fig. 13.2 showed a simulated CMB map, not the Planck one; the fig. 36.8 discussion named the wrong ordering as the worst. All changes are listed in the ancillary changelog

Abstract PDF $CSMC ×1$TSCP ×1

Instrumentation and Methods for Astrophysics

An Analytic Error-Budget Model for the Habitable Worlds Observatory Coronagraph: From Optical Disturbances to Flux-Ratio Noise

Slava G. Turyshev

A coronagraph stability allocation must protect a planet measurement, not merely satisfy a contrast target. Residual starlight both generates photon noise and interferes with small field perturbations, coupling optical stability to detection reliability. We develop a modular analytic model for the Habitable Worlds Observatory (HWO), using a reduced two-roll angular-differential-imaging realization of its OS-1 scenario. Complex-field sensitivities, wavefront sensing/control, finite observing windows, polarization, detector calibration are propagated to flux-ratio noise (FRN) and detection probabilities. Joint-visit Gaussian quadratic moments retain differential bias, cross covariance; spatial overlap/field phase determine which disturbances resemble a planet. A 6-m, 500-nm benchmark shows why the science test must precede category allocation. For a 115.46-parts-per-trillion (ppt) quadrature planet, 30,000 independent Gaussian search statistics, and a $10^{-3}$ family-wise false-alarm objective, 20-ppt FRN gives 64.55% conditional detection power; 99% requires 14.94 ppt. Photon and calibration noise exhaust the optical remainder at 8.11 pc in 100 h under the fixed response, so tighter stability alone cannot restore feasibility. An unrecognized 1% high-variance component carrying twenty percent of the variance tightens the modal allowance by a factor of 2.88; an ideal, exactly known state label reduces that penalty to 1.29 under equal conditional false-alarm limits and the same average-power objective. Thus, requirements depend on both the optical response and the information retained by the observing protocol. The framework identifies when suppression, stability, calibration, or state monitoring addresses the limiting mechanism. Numerical tolerances are controlled model results; flight allocation requires architecture-specific responses and calibrated disturbance state-estimation laws.
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Instrumentation and Methods for Astrophysics

A Delayed Rejection Reversible Jump Markov Chain Monte Carlo Method for Multi-Resolution Maps of the Stochastic Gravitational Wave Background with Pulsar Timing Array Data

Taha T. Moursy and Nihan S. Pol

Pulsar timing array anisotropy analyses often use a naive counting argument to set resolutions of inferred maps of the stochastic gravitational wave background (GWB). We present a data-driven method in the form of a delayed rejection reversible jump sampler tailored to multi-resolution pixel decompositions of the angular power density of the GWB. We also consider a rapid, frequentist alternative based on information criteria statistics. We verify our methods with a series of injection-and-recovery simulations, finding that the standard counting argument would lead to drastic overfitting of the data and that our data-driven methods reduce the number of parameters in the models by one to three orders of magnitude yet can achieve higher resolution than the standard counting argument when justified by the data. We make our sampler and frequentist method implementation available on GitHub.
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Instrumentation and Methods for Astrophysics · Cross-listed from gr-qc

Mind the second gap: The impact of gaps on noise and signal parameter inference

Ollie Burke, Federico Pozzoli, Martina Muratore et al. (+1 more)

Gravitational-wave data is never analysed without some conditioning: filtering and tapering act multiplicatively on the noise, destroying the stationarity on which the Whittle likelihood — the backbone of nearly all gravitational-wave inference — rests. The problem is particularly evident for LISA, where gaps are expected to overlap almost all signals and the noise must be estimated jointly with those astrophysical signals. We provide an analytical and numerical framework to assess the impact of noise mis-modelling when signal and noise parameters are inferred jointly in the presence of gaps. From a Fisher-matrix formalism verified against Bayesian inference, we obtain closed forms for the model uncertainties, their maximum-likelihood estimates and the true scatter in the latter, for various approximations to the likelihood. The Fisher-based linear formalism is extended through the Godambe–White curvature to the non-linear regime that severe mis-modelling produces. We survey gap families from long, well-tapered interruptions to short, high-rate ones, injecting massive black-hole binaries. Except in the case of frequent gaps, we show that the windowed covariance is well approximated by its leading diagonal — the window convolved with the power spectral density — for the estimation of both signal and noise parameters. By omitting the convolution, the signal sector remains unbiased but the noise parameters, in particular the optical-metrology noise which is dominant at high frequency, is displaced by over an order of magnitude in power. At the highest glitch rates the diagonal approximation stays accurate yet loses an order of magnitude in precision. To remedy this, we propose an exact time-domain likelihood of the surviving samples which can be efficiently (and accurately solved) via preconditioned conjugate gradient methods.
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All authors Ollie Burke, Federico Pozzoli, Martina Muratore, Jonathan R. Gair

Instrumentation and Methods for Astrophysics

MATISSE-py: a high-level Python interface for efficient, automated VLTI/MATISSE data reduction

A. Soulain, A. Matter, P. Berio et al. (+4 more)

The Multi AperTure mid-Infrared SpectroScopic Experiment (MATISSE) at the Very Large Telescope Interferometer (VLTI) delivers rich mid-infrared interferometric datasets that are reduced through a robust, multi-stage ESO pipeline. In its native form, however, the reduction relies on command-line calls to esorex, hand-edited set-of-files (SOF) and configuration files, and manual iterations that are difficult to automate, reproduce, or integrate into modern Python workflows. We present MATISSE-py, a modular Python interface that wraps the official ESO esorex recipes behind a single, user-friendly matisse command. It automates discovery, reduction, calibration, and inspection of the data, and ships as a tested, open-source package built on industry-standard practices. Beyond convenience, MATISSE-py introduces science-grade improvements developed over seven years of MATISSE operations: visibility- and photometry-factor (V-factor and P-factor) corrections derived from the GRAVITY fringe tracker to mitigate residual visibility losses, per-baseline data filtering, beam-commuting-device (BCD) "magic-number" corrections, and an absolute spectrophotometric flux calibration using state-of-the-art reference spectra. On faint targets observed under degraded conditions, the V-factor correction recovers up to a few percent of lost visibility and reduces the statistical uncertainties by nearly 20%, while yielding calibrator diameters that are consistent across BCD modes. MATISSE-py thus consolidates the consortium's expertise into a maintainable package and shortens the reduction-to-science loop for the community.
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All authors A. Soulain, A. Matter, P. Berio, F. Millour, B. Lopez, R. Petrov, S. Lagarde

Instrumentation and Methods for Astrophysics · Cross-listed from gr-qc

Architecture Acceleration of Machine Learning Gravitational Waveform Surrogate Models

Adriano Frattale Mascioli, Lorenzo Piccari, Saulo Albuquerque et al. (+9 more)

Accurate and computationally efficient waveform models of compact binary coalescences are a fundamental requirement for gravitational wave data analysis. This work presents differentiable and hardware-accelerated implementations of the machine-learning surrogate models mlgw and mlgw-bns within the JAX ecosystem. The proposed framework enables JIT compilation, vector paralellization, native GPU acceleration, and automatic differentiation, while preserving the original surrogate training infrastructure and its applicability to arbitrary non-precessing waveform approximants. Benchmarks are performed in the binary black hole case with a newly trained surrogate of the SEOBNRv5HM approximant; on CPU, they show speed-ups in waveform evaluation time with respect to the original mlgw implementation that exceed one order of magnitude; further, when exploiting GPU acceleration and large-batch vectorization these reach approximately two orders of magnitude. The benchmarks performed in the case of binary neutron stars with a TEOBResumSPA surrogate model achieve similar gains on GPU. Our JAX-based surrogate modeling framework can be integrated into Bayesian parameter estimation pipelines through GWgpu-jax, an open-source package that connects JAX-compatible gravitational waveform generators to JAX-native sampling algorithms. We demonstrate this capability with a nested-sampling pipeline built upon BlackJax-NS, performing parameter estimation analyses of the GW150914 and GW170817 events with mlgw and mlgw-bns. The analyses require approximately twelve and seventeen minutes, respectively, on a single GPU and yield posterior distributions consistent with those reported by the LIGO-Virgo-KAGRA Collaboration. Beyond nested sampling, JAX automatic differentiation provides efficient gradient and Hessian evaluations of the waveform models, enabling integration with gradient-based Bayesian inference methods.
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All authors Adriano Frattale Mascioli, Lorenzo Piccari, Saulo Albuquerque, Gabriele Demasi, Giulia Capurri, Massimo Lenti, Angelo Ricciardone, Barbara Patricelli, Gianluca M. Guidi, Giulia Stratta, Walter Del Pozzo, Francesco Pannarale

Instrumentation and Methods for Astrophysics · Cross-listed from astro-ph.SR

The NEMESIS general YSO catalogue - I. Supervised classification with deep learning methods

G. Marton, M. Madarász, J. Roquette et al. (+4 more)

In modern large-scale surveys, young stellar objects (YSOs) are mostly identified by the infrared excess in their spectral energy distributions (SEDs). To this end, YSO identification and classification were mostly based on certain colours, resulting in wavelength-specific methods. Using all available data allows us to construct a uniformly classified YSO catalogue by applying the same identification method to heterogeneous samples, reducing systematic differences and enabling more consistent studies of YSO populations and star formation. Our goal is to develop a method that takes advantage of the heterogeneous data available in the VizieR database and to provide a tool that can be used to identify YSOs with high accuracy. We also aim to create the largest homogeneous catalogue of YSOs. We use the CDS VizieR and NASA/IPAC IRSA to collect data for a large number of objects of various types. The data collected included SEDs, light curves, and direct imaging and were used to build different image representations. These were used to teach deep learning algorithms to differentiate between YSOs and all other types of sources. Architectures from the PyTorch library and custom-built convolutional neural networks were applied to create an ensemble of binary classifiers specialised at identifying YSOs. The resulting method is able to automatically identify YSO candidates with an accuracy higher than 90% while contamination is identified with an accuracy higher than 99%. We applied our classifier to numerous YSO catalogues to confirm the youth of the stars and to create the largest catalogue of homogeneously identified potential YSOs ever – the NEMESIS General YSO catalogue contains 274\,408 unique, high reliability YSOs. Their positions on the colour-magnitude diagrams, and their distribution relative to the local Galactic structures, were also used to test their young nature.
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All authors G. Marton, M. Madarász, J. Roquette, M. Audard, I. Gezer, D. Hernandez, O. Dionatos

Instrumentation and Methods for Astrophysics · Cross-listed from astro-ph.SR

Beating and coupling in pulsating stars: A unified Fourier description and observational diagnostics

József M. Benkő and Emese Plachy

Long-term amplitude and phase variations in pulsating stars produce side peaks or multiplets in the Fourier spectrum of the light curves around the pulsation frequency and its harmonics. Such structures are often attributed to modulation, although linear beating and the non-linear coupling of close oscillations can also produce similar patterns. We develop a unified analytical Fourier description of these alternatives and identify observational relations that retain discriminatory power when their frequency patterns overlap. We represent the signal as a dominant, non-sinusoidal oscillation plus one or more secondary oscillations close to it, and analytically derive the frequencies, complex amplitudes, and phases resulting from linear superposition, quadratic and general non-linear coupling. We also illustrate the calculated phenomena using artificial light curves. We implement the resulting tests in a diagnostic tool "freqdiag", which compares modulation with primary–secondary quadratic coupling models anchored to either the higher- or lower-frequency side peak, using the same normalized complex amplitudes, and supplements the fit with hierarchical tests of side-peak amplitude progression. A sinusoidal secondary signal produces only one additional peak in the linear-beating case, whereas a non-sinusoidal secondary signal produces a harmonic sequence, whose separation from the primary harmonics increases with order. Quadratic coupling produces terms $nf_0+lf_B$, but their amplitudes and phases follow shifted-harmonic and combination relations. At general non-linear order, coupling and modulation occupy the same frequency grid. The formalism provides a practical framework for interpreting Blazhko-like RRc stars, HADS variables, and other pulsating stars in which modulation and coupling are difficult to separate observationally.
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Instrumentation and Methods for Astrophysics · Cross-listed from gr-qc

Propagation delays and regional intensity changes in lensed hotspot images

Yong Li and Xiao-Gang Lan

Propagation delays cause an image recorded at a single observer time to combine radiation emitted at different stages of the source evolution. Comparable changes in total intensity can accompany distinct and even opposite changes in apparent image size. Using regional intensities, centroids, and covariances, we apply the law of total covariance to separate changes in regional intensity weights from changes in internal widths and centroid separation. Ray tracing simulations of a finite Gaussian hotspot moving along a prescribed strong field trajectory show two events with comparable attenuation in screen integrated intensity but opposite changes in second moment size. In the contracting event, the regional weights move away from balance; in the expanding event, they move toward balance even as the centroids approach each other. Differential propagation delays therefore drive these opposite size responses by redistributing intensity between spatially separated image regions.
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Thursday 24 September

Instrumentation and Methods for Astrophysics

Wavefront-Conditioned Photon Measurements for Exoplanet Spectroscopy: Contrast Limits and Conditional Gains

Slava G. Turyshev

A wavefront-sensor (WFS) prediction can select the photon measurement before detection or condition its likelihood afterward. This matters for reflected-light spectra requiring hundreds of hours, because subtracting residual starlight cannot remove its photon noise. In a two-mode, low-occupation model, isotropically distributed leakage makes planet-mode projection—ideal single-mode injection matched to the planet—the optimal fixed single-photon measurement, including unequal aligned backgrounds and equal Poisson detector-event rates per output. For nonzero leakage, an attainable two-output conditioned measurement is optimal and strictly more informative before differential loss. For an isotropic background, a contrast bound holds for any distribution of recorded leakage directions: relative transmission $0.80$ and relative admitted-time duty $0.90$ limit the Fisher information per scheduled time to $0.81$ of the fixed optimum at equal predictable-leakage and planet contrasts. Haar averaging sharpens this ceiling to $0.78$. The necessary leakage-to-planet ratios for gain are approximately $2.25$ for any direction law and $3.26$ for Haar directions. A concentration-model certificate identifies directional diversity sufficient to beat recalibrated fixed measurements. Independently gated fixed-basis fallback guarantees no loss of continuum-profiled spectral information when rates and costs are known. For the Habitable Worlds Observatory, the candidate regime is predictable, directionally diverse, leakage-dominated residuals, not a general sensitivity improvement.
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Instrumentation and Methods for Astrophysics

FOTO: Figure-Level Semantic Search for Astronomy

Hurum Maksora Tohfa and Francisco Villaescusa-Navarro

Astronomy papers carry much of their content in figures, but literature search indexes text, so there is no way to find a plot by describing what it shows. We present FOTO, a figure-level search tool over 482,750 captions from 53,839 peer-reviewed astro-ph papers. Each figure is indexed once by its title and caption, embedded with a 110M-parameter open model that runs locally, and a large language model is applied only to the retrieved shortlist, where it verifies real figures rather than generating references to ones that do not exist. Held to the harder figure-level criterion, FOTO recovers the target for 29 to 79% of queries at recall 20 depending on register, against 6 to 20% for Pathfinder and 8 to 16% for Semantic Scholar on the easier paper-level criterion, and it beats the paid embedding API it replaced. Reranking the shortlist then raises recall at 1 from 0.667 to 0.875 on detailed queries and from 0.071 to 0.571 on vague ones. Openly available models match or beat paid LLM models for verification
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Instrumentation and Methods for Astrophysics

Selective state space model for photon energy estimation in microwave kinetic inductance detectors

Benjamin A. Mazin

Microwave Kinetic Inductance Detectors (MKIDs) are superconducting photon counting detectors that simultaneously measure the energy and arrival time of individual photons and are suitable for large-format arrays. The energy resolving power R = E/$\Delta$E is the primary figure of merit for spectrophotometric applications. It is limited in practice by the assumptions underlying the Wiener optimal filter used to estimate photon energy: stationary noise, linear response, and energy independent pulse shapes, all of which MKIDs structurally violate. We present Venom (Very Efficient Neural Optimal-filter for MKIDs), a selective state space model based on the Mamba architecture that replaces the coordinate transform and optimal filter, operating directly on raw in-phase/quadrature timestream data, carrying 3,314 trainable parameters, and targeting deployment on the MKIDGen3 and future system-on-chip readout platforms. To deal with the small calibration datasets typical of MKID experiments, we train on synthetic pulses drawn from a streaming principal component analysis that samples photon energy continuously between calibration wavelengths. All numbers are reported on a stratified 15% held-out validation set, with R measured from a kernel density estimate. On an InHf bilayer resonator (ten wavelengths, 254-1310nm), Venom reaches a mean R of 26.4 versus 24.2 for the published per-wavelength optimal filter baseline, a 9% improvement from one model in place of ten per-laser filter templates. The R of 38.6 at 254 nm is the highest ever recorded for an ultraviolet-to-near-infrared MKID suitable for use in a dense array. On a PtSi resonator (five wavelengths, 808-1310nm), where the published analysis used one shared 920nm template, Venom matches the optimal filter, with a mean R of 9.1 versus 8.8 at the three interior wavelengths.
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Instrumentation and Methods for Astrophysics · Cross-listed from astro-ph.EP

Tails and Trails: Comets and NEOs Survive Co-addition in Rubin Early Data Preview 2

Colin Orion Chandler, Joseph Murtagh, Ian Chow et al. (+11 more)

We identify effectively single-visit imaging hidden within the deep co-added images of the NSF-DOE Vera C. Rubin Observatory Early Data Preview 2 (EDP2). These shallow regions contain only one or two contributing visits, providing access to single-visit-depth imaging ahead of the full Data Preview 2 (DP2) release in late 2026. We develop a workflow to locate known small Solar System bodies in these data, using our Ponder orchestrator with the Sorcha survey simulator to predict their positions and the Rubin Science Platform (RSP) to identify shallow coadds and extract image cutouts. Because cometary activity and near-Earth-object (NEO) trails produce extended morphologies, both remain identifiable in these shallow coadds. From approximately 700 comet and active-object cutouts, we identify 59 activity detections spanning 32 objects. We discover activity in 2025 NC6, previously unknown to be active; identify the first reported pre-perihelion activity of 2008 QZ44; and independently rediscover known comets 243P/NEAT and 510P/Boattini through their activity. We also recover 336 NEO cutouts, including 29 with predicted trails longer than 25 pixels. We provide accompanying galleries and tabular data, and highlight 99P/Kowal 1, 510P, and 303P/NEAT as targets for immediate follow-up. Shallow coadds are a relatively unexplored facet of Rubin data with applications beyond the Solar System examples presented here: regions with varying numbers of contributing visits will persist throughout the Legacy Survey of Space and Time (LSST).
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All authors Colin Orion Chandler, Joseph Murtagh, Ian Chow, Maxine West, A. Fraser Gillan, Peter S. Ferguson, Michael S. P. Kelley, Jacob A. Kurlander, Henry H. Hsieh, Pedro H. Bernardinelli, Wilson Beebe, Jeremy Kubica, Andrew Connolly, James R. A. Davenport

Instrumentation and Methods for Astrophysics · Cross-listed from astro-ph.EP

Simulating the thermodynamics of gas, radiation, and multispecies dust: Method and applications to protoplanetary disks

Dhruv Muley, David Melon Fuksman, Prakruti Sudarshan et al. (+2 more)

The thermodynamics of protoplanetary disks, governed by a complex interplay between gas, dust, and radiation, exerts a strong influence on their morphology and dynamics at both large and small scales. Historically, hydrodynamical simulations have treated thermodynamics with approximate prescriptions, such as local isothermality, parametrized $\beta$-cooling, and radiation hydrodynamics with gas-dust thermal equilibrium. However, a more comprehensive and self-consistent approach would more accurately reproduce the wealth of features found in observations, which in modern times have reached unprecedented spectral, angular, and vertical resolution. With this motivation, we have devised a radiation-hydrodynamics scheme for the PLUTO code with energy exchange (via absorption, emission, and collisions) for gas, radiation, and multiple species of dust. Dust-gas dynamics are handled by treating each dust species as a pressureless, diffusive fluid, ensuring that our scheme can represent changes in disk illumination caused by grain settling and trapping. We demonstrate the effectiveness of our scheme in several test problems, and conclude by discussing its relevance to open questions in protoplanetary disk studies.
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All authors Dhruv Muley, David Melon Fuksman, Prakruti Sudarshan, Alexandros Ziampras, Mario Flock

Instrumentation and Methods for Astrophysics

Differential Double Blind Fourier Holography (diff-DBFH)

Oren Pedatzur and David T. Chuss

High-performance optical systems, including space telescopes, require wavefront-sensing and correction capabilities to achieve resolution near the diffraction limit. Existing wavefront-sensing approaches span a broad range of architectures, but many require dedicated interferometric hardware, rely on computationally intensive nonlinear or iterative reconstruction algorithms or provide only limited wavefront information. Focal-plane wavefront-sensing methods are particularly attractive because they can operate without dedicated metrology hardware, and among these, Double Blind Fourier Holography (DBFH) stands out as a robust and computationally light alternative to nonlinear and iterative solvers. Here we introduce differential Double Blind Fourier Holography (diff-DBFH), a two-image variant of DBFH based on a small pupil-plane amplitude perturbation. Inspired by differential Optical Transfer Function (dOTF), diff-DBFH leverages the linear framework of DBFH to produce a more precise wavefront estimate. We derive the diff-DBFH formalism, compare its performance against dOTF using numerical simulations on a segmented aperture geometry inspired by the Habitable Worlds Observatory, analyze its sensitivity under noisy conditions, and demonstrate the method experimentally using an optical bench model of the same aperture.
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Instrumentation and Methods for Astrophysics · Cross-listed from astro-ph.GA

CERIDWEN: Fast and Flexible GPU-Accelerated Stellar Population Inference

Amanda Stoffers, Sandro Tacchella and Benjamin D. Johnson

JWST has increased both the number of high-redshift galaxies with high-quality spectral energy distributions (SEDs) and their information content. In parallel, wide-area surveys from Euclid, Rubin's LSST, and Roman will increase galaxy samples by orders of magnitude. Analysing these datasets requires stellar-population models that are both flexible and computationally efficient. We present CERIDWEN, a GPU-native SED fitting framework written in JAX, with an end-to-end differentiable forward model spanning stellar populations, nebular emission, dust attenuation and emission, and projection into the observer frame. Its vectorised, compiled architecture lets nested sampling replace a batch of live points in parallel on the GPU, which makes flexible stellar-population models tractable under full Bayesian inference. Automatic differentiation also provides exact gradients for the gradient-based samplers in the package. We jointly infer time-dependent chemical-enrichment histories instead of a single stellar metallicity, and demonstrate non-parametric star-formation histories (SFHs) with $\sim$120 age bins. Using $\alpha$-enhanced stellar libraries from FSPS, CERIDWEN can sample stellar [$\alpha$/Fe] jointly with [Fe/H], mass, and SFH, so that the joint posterior represents the [Fe/H]-[$\alpha$/Fe] degeneracy explicitly. In controlled mocks, CERIDWEN recovers parameters with well-calibrated posterior uncertainties, while fits to real JWST observations reproduce posteriors from the established Prospector framework: on a single GPU, CERIDWEN completes a fit in a median sampling time of $\sim$4 min, $\sim$134$\times$ faster per fit than equivalent CPU-based Prospector runs. CERIDWEN therefore makes full Bayesian inference practical for larger galaxy samples and more flexible stellar-population models, reducing computational constraints on the physical complexity explored in SED fitting.
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Instrumentation and Methods for Astrophysics

Simultaneous PSF Matching via Dual Kernel Optimization

Carter Lee Rhea, Pieter Van Dokkum, Roberto Abraham et al. (+6 more)

Standard point spread function (PSF) matching algorithms consider one image as the reference and aim to find a convolution kernel such that, when applied to the reference image, the PSFs of the reference and non-reference images are matched. This method works well if one image is a degraded version of the other. However, this is not always the case: if the PSFs of the two images have different orientations or shapes, a simple convolution of one of the images does not lead to a satisfactory match. While this can be trivially solved by convolving the first PSF with the second and vice-versa, this results in unnecessarily large PSFs. In this paper, we present a new algorithm, Dual Kernel Optimization (DKO), that simultaneously solves for two convolution kernels, one for each image, such that the PSFs match and the sizes of the kernels are minimized. This results in a minimally-degraded final set of PSFs. Since this problem is highly degenerate, we use Stochastic Gradient Langevin Dynamics (SGLD) which rigorously explores the parameter space and converges on the globally-optimal solution.We discuss the algorithmic challenges for this problem and the modifications to standard SGLD used to constrain it. Finally, we include a discussion on the application of this methodology to real-world images, including cases where the PSF varies over the field of view.
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All authors Carter Lee Rhea, Pieter Van Dokkum, Roberto Abraham, Imad Pasha, Steven R. Janssens, William P. Bowman, Deborah Lokhorst, Seery Chen, Qing Lui

Instrumentation and Methods for Astrophysics · Cross-listed from astro-ph.EP

Extracting Asteroid Physical Properties from Vera C. Rubin Observatory Science Validation Survey Data: Rotational Periods, Colors, and Taxonomies

V. Carruba, S. Greenstreet, M. Mastropietro et al. (+7 more)

The Vera C. Rubin Observatory will enable large-scale characterization of minor bodies through high-cadence, multi-band photometry. Early Science Validation (SV) observations from 2025-2026 provide one of the first extensive datasets for Solar System studies, but typically with sparser and more heterogeneous coverage than the Rubin First Look data, where hundreds of observations were available for well-characterized objects. In this work, we build on the methodology developed for the Rubin First Look data to extract asteroid rotation periods, amplitudes, colors, and taxonomic classifications from early Rubin SV data using multi-band (griz) photometry. Rotation periods are determined through a combination of high-order Fourier light-curve fitting and multi-band Lomb-Scargle analysis. A unified light-curve model is then used to derive rotation-corrected colors, which are converted into taxonomic classes using calibrated color indices and spectral slopes. We validate the method on objects with sufficient observational coverage and show that preliminary physical properties can be estimated from sparse and irregular datasets, while robust determinations require improved temporal coverage. By simulating sparsely observed data, we identify the observational conditions required for period determinations. The inclusion of z-band photometry extends traditional color-based taxonomy and improves compositional discrimination relative to gri-only analyses.
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All authors V. Carruba, S. Greenstreet, M. Mastropietro, S. Aljbaae, G. Caritá, R. C. Domingos, M. Huaman, M. M. Bala, R. D. Z. Pedroso, E. M. D. S. Delfino

Instrumentation and Methods for Astrophysics · Cross-listed from astro-ph.EP

VLTI/MATISSE observations of the hot dust around $\beta$ Pictoris: Observing faint objects with MATISSE

P. Priolet, J.-C. Augereau, J. Milli et al. (+32 more)

Context: Hot exozodiacal dust has been detected around approximately 20% of nearby main-sequence stars, indicating that it is a common feature of extrasolar planetary systems. However, its spatial distribution and grain properties remain poorly understood. Aims: We aim to show that the spatial distribution of hot dust around beta Pictoris, an iconic planetary system with two known planets and a population of exocomets, can be constrained through a detailed analysis of optical long-baseline interferometry data. Methods: We obtained L-band observations at approximately 3.5 microns of beta Pictoris with MATISSE at the VLTI. We developed a method to assess correlations in the visibility measurements by estimating the full data covariance matrix, and modeled the circumstellar emission with geometric brightness distributions. Results: We detect circumstellar emission around beta Pictoris consistent with hot exozodiacal dust. Modeling the emission with and without accounting for data correlations demonstrates their significant impact on the inferred dust properties. The best-fit model reveals a compact (approximately 0.05 au), highly inclined dust structure near the sublimation radius, misaligned by approximately 60 degrees on the sky with respect to the extended edge-on outer disk. It contributes approximately 4%-7.5% of the total flux at 3.4 microns and is composed of submicron-sized grains. The data are also compatible with an additional dust component near 1 au. Conclusions: For beta Pictoris, the two-decade-old paradigm placing hot exozodiacal dust near the sublimation radius and consisting of submicron-sized grains finds observational support in the detailed analysis of MATISSE data. The misalignment with the known debris disk further supports a link to exocometary activity.
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All authors P. Priolet, J.-C. Augereau, J. Milli, A. Matter, B. Lopez, H. Beust, J. Varga, P. Boley, W.-C. Danchi, L. Foteini, T. Henning, M. Houllé, M. Letessier, F. Millour, J. Scigliuto, G. Weigelt, S. Wolf, O. Absil, J.-P. Berger, Y.-I. Bouarour, G. Bourdarot, D. Defrère, C. Desgrange, J.-B. Le Bouquin, D. Iglesias, T. A. Stuber, P. Berio, F. Bettonvil, P. Cruzalèbes, M. Heininger, J. W. Isbell, S. Lagarde, A. Meilland, R. Petrov, S. Robbe-Dubois

Instrumentation and Methods for Astrophysics · Cross-listed from astro-ph.EP

Exoplanet Detection Techniques: Radial Velocity

Rafael Luque and Matthew R. Standing

The radial velocity (RV) technique enabled the discovery of the first exoplanets orbiting Sun-like stars. Since then, improvements in precision and sensitivity have enabled the detection of smaller planets, bringing us closer to the goal of discovering Earth analogs in the coming years. In this chapter, we provide an overview of the radial velocity method. We begin with a detailed description of the technique, including how precise radial velocities are measured and what limitations must be addressed to achieve reliable detection of small signals. We examine the unique challenges associated with the detection of circumbinary planets and outline the developments that have, for the first time, made their detection feasible using the radial velocity method. With over 2,000 planets detected to date, the radial velocity method remains one of the most reliable techniques, offering valuable insights into the demographics of exoplanets, especially at long orbital distances. As an example of its applications, we provide an analysis and interpretation of three publicly available radial velocity datasets: one from a single star, one for a circumbinary planet system, and another from a single star with transiting planets. Furthermore, we compile information on the spectrographs currently and soon-to-be available worldwide for radial velocity observations and a list of open-source tools designed for their analysis. In the Supplementary Material, we include a sample telescope proposal for obtaining radial velocity data, along with practical tips on writing a competitive proposal to aid early-career researchers entering the field. This chapter serves as a comprehensive guide for understanding the capabilities and applications of the radial velocity method, equipping readers with the knowledge and resources to address their own scientific questions using this technique.
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Instrumentation and Methods for Astrophysics

GIMLI: a toolkit connecting linear and non-linear magnetohydrodynamic regimes

Jordi De Jonghe, Nicolas Brughmans and Rony Keppens

In this work, we present the General Interface for MPI-AMRVAC / Legolas Interconnection (or GIMLI, for short) as a toolkit for in-depth (magneto)hydrodynamic studies combining linear and non-linear methods. Acting as a bridge between the linear (M)HD spectroscopy code Legolas and the non-linear simulation code MPI-AMRVAC, GIMLI facilitates the initialization of non-linear MPI-AMRVAC simulations with linear solutions. We showcase this functionality on both Cartesian and cylindrical setups, covering representative plasma physical and astrophysical scenarios: Parker unstable magnetized atmospheres, interchange modes in a straight tokamak setup, resistive Harris sheet evolutions and thermally modified discrete Alfvén waves in coronal loops. We offer suggestions on how to combine linear and non-linear methods, and demonstrate how to leverage GIMLI in the process.
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Instrumentation and Methods for Astrophysics

Uber-calibration-based Two-level Radial-velocity Zero-point Correction for APOGEE

Jinming Zhang, Haibo Yuan and Zhijia Tian

APOGEE delivers high-resolution, near-infrared spectroscopy and highly precise radial velocities (RVs), with extensive repeat observations spanning more than a decade. Long-term RV repeatability is nevertheless limited by instrumental zero-point systematics: exposure-to-exposure drift and fiber-dependent offsets that are only partially tracked by lamp-based wavelength calibration, and that can evolve as fibers are serviced or replaced. We infer and remove these zero points directly from the published per-visit RVs using an uber-calibration framework based on shared repeat observations. We solve sequentially for two sets of minimal calibration units: (plate, night) exposure-level offsets and time-dependent (fiber, observing year) offsets. We apply the method independently to APO and LCO DR17 and to APO DR19. After correction, the same-fiber repeatability within two days reaches a limiting precision of ~14 m/s, and the long-baseline single-visit precision improves by a factor of two from 98.2 to 44.7 m/s. We release per-visit, value-added RV catalogs for DR17 (APO+LCO) and DR19 (APO) containing 3,501,727 visits (3,336,141 fully corrected) of 930,519 unique stars, enabling more reliable RV variability, binary, and Galactic-dynamics studies.
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Instrumentation and Methods for Astrophysics · Cross-listed from astro-ph.HE

DETECT: Real-Time Identification of Transients with DESI Spectroscopic Redshift

Yu-Hsing Lee, Ting-Wan Chen, Ze-Ning Wang et al. (+10 more)

Wide-field surveys now report thousands of transients per month, while spectra are obtained for only a few per cent of them. We present DETECT (DESI–Transient Event Cross-matching Tool), a pipeline that turns each Transient Name Server (TNS) alert into a distance-informed candidate within an hour by placing it in the context of the Dark Energy Spectroscopic Instrument (DESI) archive. DETECT cross-matches every new report against the 22 million spectra of DESI EDR and DR1 through a HEALPix index, associates the transient with a host galaxy by a directional-light-radius rule whose morphology-dependent thresholds are calibrated on 4,474 supernovae with known redshifts (92.5% completeness, 0.4% wrong hosts), and passes ambiguous cases to a reviewer through a web interface. With a validated host redshift it derives the peak absolute magnitude, the projected offset and basic host properties of each event, and ranks it for spectroscopic follow-up. Applied retrospectively to ~1.2x10^5 TNS reports from 2020–2024, DETECT recovers a spectroscopic host for 15% of them, from these we build a Gold Sample of ~5,400 well-sampled light curves whose luminosity distributions by class reproduce those of untargeted surveys. Because the absolute magnitude is known at discovery, intrinsically overluminous events stand out immediately: in the prospective 2025 run this is how the lensed superluminous supernova SN~2025wny was flagged within hours of its report, and how faint, fast-declining kilonova candidates were screened against model grids and archival photometry. DETECT shows how an archival spectroscopic survey can make host redshifts a routine part of transient triage ahead of the Rubin Observatory's LSST.
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All authors Yu-Hsing Lee, Ting-Wan Chen, Ze-Ning Wang, Sheng Yang, Limeng Deng, Chuan-Jui Li, K. C. Chambers, Thomas de Boer, Chien-Cheng Lin, Thomas B. Lowe, Paloma Mínguez, Gregory S. H. Paek, Richard Wainscoat

Instrumentation and Methods for Astrophysics · Cross-listed from cs.LG

Image Fidelity is Not Field Fidelity: Joint Thermodynamic Reconstruction and Error Localization in Neural Tomography

Alan Hsu, Jenna Samra, Alin Razvan Paraschiv et al. (+1 more)

Neural fields for scientific tomography are optimized from 2D images, but the actual quantity of interest is often a latent 3D physical field. Because the forward map is many-to-one, low 2D image error need not certify a correct 3D field. Moreover, the latent field is not directly supervised during training, and its error cannot be evaluated against truth at deployment. We develop CoroNeRF to jointly optimize 3D electron density and temperature fields directly from multiview, multiline intensities through a differentiable atomic-emission renderer. Using solar coronal tomography as a controlled testbed, we evaluate physical-field recovery and test whether cross-seed instability provides a ground-truth-free-at-inference indicator of local physical-field error. We underscore the following two observations. (i) Image fidelity is not field fidelity: spectral ablations show that limited-channel reconstructions can fit their available observations well while recovering substantially worse fields, whereas evaluation on a common richer probe exposes the discrepancy. (ii) Cross-seed instability ranks local physical-field error across tested matched-model conditions, supported by sparsification and physical signal-strength controls. Seed-deviation projections provide complementary directional validation, but shared forward-model mismatch can still produce incorrect cross-seed consensus. These results characterize joint thermodynamic recovery and the usefulness and limits of seed-based error localization in a controlled, single-scene solar tomography testbed.
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All authors Alan Hsu, Jenna Samra, Alin Razvan Paraschiv, Liam Connor

Wednesday 23 September

Instrumentation and Methods for Astrophysics · Cross-listed from gr-qc

MAGGIE: A Magnetic Gravitational Wave Induction Experiment

Jasper Jödicke, Marios Maroudas, Toma-Stefan Cezar et al. (+1 more)

Gravitational waves (GWs) can induce effective electromagnetic currents when interacting with external electric and magnetic fields, as described by linearized gravity modifications to Maxwell's equations. This coupling enables a novel detection approach for high-frequency gravitational waves (HFGWs) using axion haloscope experiments. Here we present the MAGnetic Gravitational wave Induction Experiment (MAGGIE), the first lumped-element HFGW detector proposed in Europe, designed to probe HFGWs in the kHz-MHz regime by leveraging a 14 T solenoidal magnet at the University of Hamburg. The GW-induced magnetic flux is captured by a custom-designed pickup loop optimized for the expected symmetry of the effective current. A figure-8-shaped geometry, oriented to break the azimuthal symmetry, is implemented, together with a blind-loop configuration, for real-time noise rejection and calibration. The readout scheme is tailored for continuous signals and time-domain transient searches, using waveform templates for primordial black hole (PBH) mergers. The expected experimental reach in terms of strain spectral noise density at the 40 MHz high-frequency end is projected to reach $\sim 4 \times 10^{-16}/\sqrt{\mathrm{Hz}}$ for transient searches, and in terms of strain, projected to reach $\sim 10^{-19}$ for 1 year of continuous search. This allows MAGGIE to constrain currently unexplored regions of the HFGW parameter space.
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All authors Jasper Jödicke, Marios Maroudas, Toma-Stefan Cezar, Dieter Horns

Instrumentation and Methods for Astrophysics

FPCA-Enhanced Simulation-Based Inference for Robust Type Ia Supernova Cosmology

Moonzarin Reza and Lifan Wang

Precision cosmology is a cornerstone of modern astronomy, and upcoming wide-field photometric surveys make it crucial to develop robust, data-driven inference methods that can handle complex survey systematics without relying on closed-form likelihoods. Simulation-Based Inference (SBI) meets this need by enabling forward simulations that encode complex survey characteristics. Previous SBI analyses in supernova cosmology have used SALT2 light-curve parameters as summary statistics; however, SALT2's two-basis spectral template imposes rigid modeling assumptions, motivating a more flexible representation. In this work, we present the first application of Functional Principal Component Analysis (FPCA) light-curve parameters as summary statistics for SBI-based cosmological inference under a non-flat {\Lambda}CDM model. On identically generated simulations, FPCA+SBI yields constraints comparable to both SALT2-based SBI and explicit-likelihood analyses, while providing more robust constraints on out-of-domain simulations than SALT2. Applying the model trained on LSST-like light curves to a spectroscopically confirmed DES Year 5 supernova sample, we recover constraints consistent with those of the DES collaboration to within 0.12 {\sigma} and 0.23 {\sigma} in {\Omega}m and {\Omega}{\Lambda} respectively, establishing the method's generalizability to real survey data. By introducing host-dependent systematics through a mass-dependent dust extinction law, we find FPCA-based summary statistics implicitly encode host-dependent systematics, suggesting dedicated host modeling may be unnecessary within this framework. Combined with its previously demonstrated effectiveness for photometric classification, FPCA offers a compelling foundation for unified, data-driven pipelines capable of jointly performing supernova classification and cosmological inference for upcoming wide-field photometric surveys.
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Instrumentation and Methods for Astrophysics

PSFSim: PhySics First Simulations for the Point Spread Function of the Roman Space Telescope

Nihar Dalal, Chris Hirata, Charuhas Shiveshwarkar et al. (+6 more)

We present a new tool for generating simulated point spread functions (PSFs) in the Wide Field Instrument (WFI) of the Nancy Grace Roman Space Telescope. The simulation tool is physics forward, and performs a raytrace of the optical system of the instrument to compute the PSF, while also accounting for various detector effects. The tool also has the capability to add perturbations to the optical system and detectors. We explore several applications of the tool that may arise during the commissioning of the telescope, including optical ghosts, measuring the optical aberrations from diffraction spikes, and studying the effect of mirror polarization.
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All authors Nihar Dalal, Chris Hirata, Charuhas Shiveshwarkar, Anthony Harbo Torres, Chun-Hao To, Elise Moore, Katherine Laliotis, David Kuhtenia, Emily Macbeth

Instrumentation and Methods for Astrophysics

A Practical Primer on Software Citation in Research

Floor S. Broekgaarden, Phil R. Van-Lane, Sasha Levina et al. (+9 more)

Software underlies virtually all modern research, yet citation practices for software remain inconsistent and often inadequate. This short primer offers practical guidance in two directions: how to properly cite the software you use in your research, and how to make your own software easy for others to cite. We describe a seven-step workflow for citing software and a five-step workflow for making your software citeable, along with the community tools and resources that support each step. We also address common questions about what software, and how much, to cite. The guidance is field-independent; we use astronomy as a running example throughout, and readers in other disciplines can substitute the equivalent tools and conventions of their own community. Our goal is to lower the practical barrier to good software citation practice and to support a research culture in which software receives the scholarly credit it deserves.
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All authors Floor S. Broekgaarden, Phil R. Van-Lane, Sasha Levina, Ahmed Bello, Sandra Gesing, Daniel S. Katz, Bhavesh Patel, Pengyin Shan, Samantha Teplitzky, Simon Thill, Peter K. G. Williams, Andrea Zonca