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Physics Astrophysics Instrumentation and Methods for Astrophysics

astro-ph.IM Watch Instrumentation and Methods for Astrophysics

Wednesday 16 September

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

Deep Learning Detection of Beyond-General-Relativity Deviations in Gravitational-Wave Signals: A Detection-Threshold Study with Real LIGO Noise

Muhammad Adnan Shahzad

We study machine-learning detection of controlled beyond-General-Relativity (beyond-GR) deviations in gravitational-wave signals, using both synthetic aLIGO-PSD noise and real LIGO H1 detector strain. Three deviation families are applied to General-Relativistic inspiral-merger-ringdown waveforms: amplitude modulation, phase modulation, and frequency modulation, each parameterized by a dimensionless strength coefficient $\beta$. A hybrid classifier combining a one-dimensional convolutional neural network with ten hand-crafted waveform statistics is trained on GR and modified waveforms and tested on a deviation type excluded from training. The central result is a quantitative detectability curve as a function of $\beta$. Using the real GW150914 strain as a template and real H1 detector noise, we find a detection threshold at $\beta \approx 0.25$, with accuracy rising smoothly from chance at $\beta \leq 0.2$ to perfect classification at $\beta \geq 0.5$. The threshold value is specific to the quadratic-in-time modulation form adopted here and should not be interpreted as a generic constraint on beyond-GR parameters. We nevertheless argue that the negative result at small $\beta$ is informative: it establishes a quantitative limit on machine-learning-only beyond-GR searches in real detector noise, in the absence of matched-filter signal extraction.
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Instrumentation and Methods for Astrophysics

Gravitas: A Browser-Based Astrophysics Laboratory for Prediction, Measurement, and Discovery

Carl Ziegler

Astronomy students are often asked to reason about systems that cannot be handled in a laboratory, evolve over inaccessible timescales, or reveal themselves only through indirect measurements. Gravitas is a free, browser-based astrophysics environment designed to turn those limitations into opportunities for experimentation. Its version 1.0.0 release combines a configurable gravitational sandbox with 59 ready-to-run scenarios and 22 guided investigations comprising 636 steps and roughly 15-19 hours of structured work. Students can build and alter systems, change reference frames, measure distances, angles, periods, energies, forces, and orbital elements, and observe simulated systems through transit, radial-velocity, astrometric, rotation-curve, stellar-evolution, and gravitational-wave displays. Guided activities use a predict-test-measure-revise-explain cycle, retain the student's evidence, and export a report for submission. Instructor guides, answer keys, short classroom routes, lecture and embed modes, reproducible share links, Spanish localization, keyboard-accessible navigation, and offline operation lower the practical barrier to adopting the simulation in introductory astronomy and physics courses. A public dashboard reports 243 scientific checks across 25 areas and names the sources and tolerances behind them. This article describes the learning experiences available in Gravitas, illustrates several ways it can be used from a brief demonstration to a full laboratory exercise, and states the scientific scope and limitations of the models. The aim is not to replace quantitative calculation or observation, but to give students a place where they can make a prediction, change one thing, measure what follows, and build an explanation from their own evidence.
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Instrumentation and Methods for Astrophysics

Characterization of the CSST Survey Camera CCDs: I. basic electro-optical performance

Zun Luo, Hu Zhan, Youhua Xu et al. (+8 more)

The Chinese Space-station Survey Telescope (CSST) is a flagship mission designed to carry out a large-area high-resolution multiband imaging and slitless spectroscopic survey over a decade. The survey's science drivers, ranging from precision cosmology to stellar astrophysics, impose stringent requirements on the performance of its focal plane detectors. This paper is the first in a series that present ground-based characterization of the 31 flight-model charge-coupled devices (CCDs) of the CSST Survey Camera. Measurements of basic electro-optical performance are reported here. Key results include: full-well capacity >80 ke (limited by the test electronics), non-linearity <1.4% in the range of 7-70 ke, median readout noise 3.6 e, dark current <0.02 e/pix/s at the operating temperature of -85 degree celsius, high quantum efficiency across the survey's spectral range (255-1000 nm), typical pixel response non-uniformity <1%, and charge transfer efficiency >99.9994% at the flat-field level of 10 ke. All 31 CCDs meet or exceed the Survey Camera's specifications. These measurements establish a performance baseline and provide inputs for CSST image simulation and data processing pipelines
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All authors Zun Luo, Hu Zhan, Youhua Xu, Qiuyan Luo, Yuhe Song, Fajun Li, Li Shao, Zhe Huang, Haonan Chi, Huaipu Mu, Xiaolei Meng

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

The Spitzer Data Fusion - A Far-Ultraviolet to Far-Infrared Multi-Wavelength Database in Spitzer Extragalactic Survey Fields

Mattia Vaccari

I present the Spitzer Data Fusion, a multi-wavelength photometric database providing far-ultraviolet to far-infrared flux measurements, together with photometric and spectroscopic redshifts, for 4.4 million IRAC-selected sources over 65\,deg$^2$ in eight of the most widely studied extragalactic survey fields. A companion product, the SERVS Data Fusion, provides 2.8 million sources over 18\,deg$^2$ selected from deeper Spitzer warm-mission imaging. Catalogs are band-merged with wavelength-dependent matching radii, astrometrically registered against 2MASS, and distributed as FITS binary tables, one per field, as \href{https://doi.org/10.5281/zenodo.6120913}{DOI: 10.5281/zenodo.6120913} and as CDS/VizieR \href{https://cdsarc.cds.unistra.fr/viz-bin/cat/II/377}{catalog II/377}. The database is intended as a community resource for photometric redshift calibration, spectral energy distribution fitting, sample selection and multi-wavelength cross-identification, and is a natural bridge between the Spitzer legacy fields and ongoing Euclid, Rubin and SKA precursor surveys.
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Instrumentation and Methods for Astrophysics

The Nancy Grace Roman Space Telescope Coronagraph Community Participation Program

Dmitry Savransky, Vanessa P. Bailey, Schuyler G. Wolff et al. (+53 more)

In preparation for the operational phase of the Nancy Grace Roman Space Telescope, NASA has created the Coronagraph Community Participation Program (CPP) to prepare for and execute Coronagraph Instrument technology demonstration observations. The CPP is composed of 7 small, US-based teams, selected competitively via the Nancy Grace Roman Space Telescope Research and Support Participation Opportunity, members of the Roman Project Team, and international partner teams from ESA, JAXA, CNES, and the Max Planck Institute for Astronomy. The primary goals of the CPP are to prepare simulation tools, target databases, and data reduction software for the execution of the Coronagraph Instrument observation phase. Here, we present the current status of the CPP and its working groups, along with plans for future CPP activities up through Roman's launch. We also discuss plans to potentially enable future commissioning of currently-unsupported modes.
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All authors Dmitry Savransky, Vanessa P. Bailey, Schuyler G. Wolff, Maxwell A. Millar-Blanchaer, Jason Wang, Lisa Altinier, Ramya Anche. Pierre Baudoz, Beth Biller, Sarah Blunt, Wolfgang Brandner, Marah Brinjikji, Oscar Carrión-González, Amanda Chavez, Elodie Choquet, David Doelman, Julien H. Girard, Alexandra Z. Greenbaum, Samantha N. Hasler. Justin Hom, James G. Ingalls, Stephen R. Kane, N. Jeremy Kasdin, Oliver Krause, Masayuki Kuzuhara, Alexis Lau, Zhexing Li, John Livingston, Patrick J. Lowrance, Kevin Ludwick, Bruce Macintosh, Eric Mamajek, Mark Marley, Johan Mazoyer, Bertrand Mennesson, Toshiyuki Mizuki, Sarah E. Moran, Naoshi Murakami, Jun Nishikawa, Malachi Noel, Laurent Pueyo, Sergi Hildebrandt Rafels, Jason Rhodes, Tyler Robinson, Robert J. De Rosa, Matthias Samland, Nicholas Schragal, Jürgen Schreiber, Jennifer Sobeck, Karl Stapelfeldt, Motohide Tamura, Taichi Uyajma, Arthur Vigan, Michele Woodland, Marie Ygouf, Kenta Yoneta, Robert T. Zellem, Neil T. Zimmerman

Instrumentation and Methods for Astrophysics

Supporting users in their observation preparation - the ESO ObsPrep tool

Monika G. Petr-Gotzens, Vincenzo Forchi, Andrea Mehner et al. (+6 more)

Ground based observatories are experiencing significant technological advances and telescopes are getting equipped with highly complex instruments to enable cutting-edge astronomical research. The increasing complexity of such instruments displays a challenge to their users when they want to plan and prepare specific observation programmes, that often request to define large amount of detailed instrument-specific information. Therefore, at ESO we developed an Observation Preparation tool (in short ObsPrep tool), which provides a layer of abstraction over the instrument-specific technical details and tries to harmonize the users experience when being faced with the preparation of observation blocks for different complex instruments. The ObsPrep tool allows interactive planning of the observations by visualization of various actions and observing strategies. In a joint approach by software engineers and astronomers, ObsPrep was started as a stand-alone java desktop application and over the years has evolved into an angular based web-application. It is now fully integrated in ESOs general use phase2 user interface (p2) that allows ESO users to create, modify, or delete observation blocks. Here we present the core functionalities of ObsPrep, as well as its special features and how the user interface integrates into ESOs generic phase2 observation preparation tool. We also outline the upcoming plans to incorporate the observation preparation for the instruments of the next generation of ESOs large telescopes, the ELT, into ObsPrep.
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All authors Monika G. Petr-Gotzens, Vincenzo Forchi, Andrea Mehner, Thomas Bierwirth, John Pritchard, Ahmed M. Khan, Olivier R. Hainaut, Kevin Knecht, Andre Graca

Instrumentation and Methods for Astrophysics

The GOTO Telescope Control System

Martin J. Dyer, Vik S. Dhillon, Stuart Littlefair et al. (+21 more)

The Gravitational-wave Optical Transient Observer (GOTO) operates a network of robotic, wide-field survey telescopes searching for optical transients to gravitational-wave signals and other astronomical events. Since 2023, the network has comprised two antipodal sites in the Canary Islands and Australia, each hosting two independent robotic mounts. The GOTO Telescope Control System (G-TeCS) is a custom Python software package that manages all operational aspects of the network; from alert processing and target scheduling to onsite hardware operations and monitoring. The central system consists of an alert monitor, observation database and scheduler, which issues targets to the four nodes. Each telescope operates using a system of independent control daemons, with a pilot master control program to coordinate nightly operations. This architecture, in development since 2015, provides a flexible and robust system that now successfully operates the fully autonomous network.
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All authors Martin J. Dyer, Vik S. Dhillon, Stuart Littlefair, Kendall Ackley, Sergey Belkin, Lisa Kelsey, Tom Killestein, Amit Kumar, Joseph Lyman, David O'Neill, Krzysztof Ulaczyk, Ben Godson, Dan Jarvis, Danny Steeghs, Duncan K. Galloway, Paul O'Brien, Gavin Ramsay, Kanthanakorn Noysena, Rubina Kotak, Rene Breton, Laura Nuttall, Ben Gompertz, Jorge Casares Velázquez, Don Pollacco

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

Searching for gravitational wave echo with group equivariant neural posterior estimation

Jian-Wei Luo and Yun-Song Piao

Current methods for the gravitational-wave (GW) echo searches generally require substantial computational time and resources. Recent advances in group equivariant neural posterior estimation (GNPE) have demonstrated the potential to substantially accelerate posterior inference. In this work, we adopt this framework and train a GNPE model to perform echo searches, significantly improving computational efficiency while maintaining comparable inference accuracy. We apply it to the O4a events and find no significant evidence for the GW echo.
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Instrumentation and Methods for Astrophysics · Cross-listed from astro-ph.EP

Bridging magnetothermal winds and photoevaporation to model discs dispersal

Giovanni Picogna and Barbara Ercolano

Protoplanetary disc dispersal is driven by two processes usually modelled separately: photoevaporative and magnetohydrodynamic (MHD) disc winds. Global simulations indicate that in the inner disc these are not distinct outflows but a single magnetothermal wind. We assemble a closed-form, two-phase model that respects it. A single-field-line wind, whose base is fixed by the irradiated temperature and penetration column, supplies the launch and feeds a secular evolution, with photoevaporation convolved on as a sink. The flux closure $B_z\propto\Sigma^q$ is self-limiting: for $q\le1/2$ depletion alone cannot demagnetise the disc, so dispersal requires independent flux loss, parameterised by the magnetic Reynolds number $\mathcal{R}_m$. Integrating the coupled system yields two regimes. Efficient flux loss ($\mathcal{R}_m\lesssim1$) lets the magnetisation front recede by over an order of magnitude and opens a photoevaporative gap. Flux retention ($\mathcal{R}_m\gg1$) drives the front outward, sustains accretion, and defers dispersal by $\approx2.7$~Myr. Deriving the base from stellar irradiation instead of prescribing it, we find that the cold-launch approximation is valid during the early stages of disc evolution: anchoring the base at plasma equipartition ($\beta_{\rm base} \sim 1$) confines irradiation's influence on the magnetic lever arm to the magnetothermal annulus, decoupling the peak accretion rate from the incident flux. Both regimes clear the disc inside-out, through either a photoevaporatively amplified cavity wall or an expanding magnetothermal front.
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Instrumentation and Methods for Astrophysics

cosmokdtree: a flexible OpenMP-parallelized k-d tree for computational astrophysics applications

Óscar Monllor-Berbegal, David Vallés-Pérez, Susana Planelles et al. (+1 more)

Modern numerical astrophysics applications present a common demand for efficient spatial querying techniques, such as neighbor searches or density estimations over billions of resolution elements. To address the growing need for fast and versatile tools tailored to these tasks, we present cosmokdtree, a fast and flexible multi-purpose k-d tree implementation in Fortran, parallelized with OpenMP directives. Our library supports arbitrary dimensionality and spatial distributions, and is designed for efficient tree construction and fast query performance for moderate-scale applications (performance tested up to 10^9 points). Python bindings coupled to the module are also provided. All these ingredients yield a k-d tree package suitable for analysis purposes. We benchmark cosmokdtree across a variety of scenarios, including different point distributions, dimensionality, and parallel scaling. We also compare its performance against the widely used scipy implementation and other efficient alternatives such as coretran's and a GPU-based version, showing that cosmokdtree consistently achieves lower construction and query times than CPU alternatives while keeping a reasonable memory usage. Our tree-building phase implementation, executed on a mid-range workstation-class CPU, approaches the performance of GPU-based implementations when run on high-end consumer graphic cards, although data-center GPUs, out of the scope for our comparison, could still deliver substantially higher performance and a broader conclusion cannot be extracted. We further present some applications tackling common problems in astrophysics, namely, the friends-of-friends clustering algorithm and the particle-to-mesh assignment process. The code is publicly released and intended to serve as a flexible multi-purpose tool for computational applications in a wide range of scenarios, particularly in astrophysics.
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All authors Óscar Monllor-Berbegal, David Vallés-Pérez, Susana Planelles, Vicent Quilis

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

Toward Autonomous Radio Follow-up of Multi-messenger Transients with RADAR: From Alert Parsing to Inference and Observation Scheduling

Mihael Hategan-Marandiuc, Tanner O'Dwyer, Alessandra Corsi et al. (+6 more)

Multi-messenger astronomy (MMA), the joint study of cosmic sources through gravitational waves (GWs), electromagnetic (EM) radiation, neutrinos, and cosmic rays, is rapidly reshaping time-domain astrophysics. Realizing the promise of MMA will require coordinating heterogeneous observing resources and automating the chain from alert to analysis to follow-up. RADAR (Radio Afterglow Detection and AI-driven Response) is a federated, privacy-enhancing framework for the radio follow-up of GW events, previously validated on GW170817. Here, we extend it along three axes. First, we benchmark three large language models (LLMs; GPT-5.5, Claude-Opus-4.7, and Gemini-3.5-Flash) against the GW170817 radio light curve dataset. GPT-5.5 attains the highest event-level $F_1$ score, the harmonic mean of precision and recall, at $0.893 \pm 0.010$, and the highest GCN-level recall, $0.794 \pm 0.013$, improving on previous GPT-4.1 results by 16% and 10%, respectively, while Claude-Opus-4.7 achieves the highest precision, $0.978 \pm 0.014$. Second, we introduce concurrent likelihood evaluation, which speeds up the MCMC computation by a factor of $40\times$ over our previous results. Third, we present an LLM-driven scheme that converts natural-language observing requests into submission-ready scheduling blocks for the Karl G. Jansky Very Large Array. Together, these developments advance RADAR toward a scalable, largely autonomous system for GW radio follow up.
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All authors Mihael Hategan-Marandiuc, Tanner O'Dwyer, Alessandra Corsi, Eliu Huerta, Zilinghan Li, Ian T. Foster, Kyle Chard, Ryan Chard, Amal Gueroudji

Instrumentation and Methods for Astrophysics

Transitioning from ADS to SciX to Serve 21st Century Astronomy

Jennifer Lynn Bartlett, Suze Kundu, Alberto Accomazzi et al. (+1 more)

For decades, the NASA Astrophysics Data System (ADS) has been the foundational digital library for astronomy. As ADS becomes the Science Explorer (SciX), the team prioritizes preserving this trusted experience while increasing their support for space and Earth sciences broadly, without diluting its commitment to astrophysics.
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All authors Jennifer Lynn Bartlett, Suze Kundu, Alberto Accomazzi, Michael J. Kurtz

Instrumentation and Methods for Astrophysics

Progress in quantum telescopes

David R. Gozzard, Fiona H. Panther and Andrew G. White

Classically, the angular resolution of a telescope is limited by its diffraction limit: the ratio of its observing wavelength to its diameter. Developments in quantum information theory over the past decade have uncovered quantum-optimal measurement methods that enable super-resolution imaging beyond the diffraction limit, and many laboratory-scale demonstrations of these methods have been performed over the past decade, culminating in the recent first on-sky demonstration of quantum-enhanced astronomical imaging. In this Review, we detail the current progress and achievements of these theoretical and experimental results, discuss the astronomical science cases motivating the development of higher resolution telescopes, summarise the technological challenges facing the practical application of quantum imaging technologies to astronomy, and present a vision for the realization of quantum telescopes with imaging resolutions orders of magnitude better than current observatories.
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Instrumentation and Methods for Astrophysics · Cross-listed from astro-ph.SR

Physics-Informed Neural Networks for Fast Multilayer Spectral Inversion of H{\alpha} 6562.8 A and Ca II 8542.1 A Spectra

Ziyang Zhang, Qin Li, Vasyl B. Yurchyshyn et al. (+4 more)

Strong chromospheric absorption lines such as H$\alpha$ 6562.8 A and Ca II 8542.1 A provide vital diagnostics of plasma dynamics and thermal structure in the solar chromosphere. Multilayer spectral inversion (MLSI) offers a physically interpretable framework for modeling these lines using a finite number of radiative-transfer layers, but conventional MLSI relies on pixel-by-pixel nonlinear least-squares fitting, making it computationally expensive for large imaging spectroscopic data sets. Here, we introduce a physics-informed neural-network (PINN) framework to accelerate MLSI while preserving its analytic radiative-transfer formulation. The network predicts MLSI parameters directly from observed line profiles and passes them through a differentiable MLSI forward model to synthesize spectra. Training follows a two-stage approach: an initial stage optimized solely via spectral reconstruction loss, followed by fine-tuning that combines spectral consistency with parameter-space supervision from conventional MLSI results on a single reference image. This strategy eliminates the need for large precomputed training sets while maintaining physical interpretability. Applied to Fast Imaging Solar Spectrograph (FISS) observations from the Goode Solar Telescope (GST) targeting both quiet-Sun and active-region regions, MLSI-PINN parameter maps reproduce the primary spatial structures of direct inversions, achieving an arithmetic mean pixel-wise Pearson correlation coefficient of 0.933 across all evaluated parameters. The reconstructed spectra closely match both observed profiles and conventional MLSI fits. Post-training, MLSI-PINN processes a raster in approximately 5-15 seconds compared to 3-5 minutes for conventional MLSI, delivering an inference speedup of about 12-60 times without substantial loss in reconstruction quality, enabling efficient MLSI analysis on large chromospheric data sets.
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All authors Ziyang Zhang, Qin Li, Vasyl B. Yurchyshyn, Kangwoo Yi, Haimin Wang, Wenda Cao, Bo Shen

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

Environmental qualification and performance of a CubeSat-scale dual optical frequency comb payload for space applications

Stephanie D. Leifer, Matthew J. Kelley, Natalie Walsh et al. (+23 more)

We report the environmental qualification and performance of CombSat, a dual optical frequency comb payload designed for deployment on a 12U CubeSat in low Earth orbit. The payload integrates two self-referenced, 200 MHz hybrid fiber-waveguide frequency combs, a narrow-linewidth optical reference, a heterodyne beat detection unit, and FPGA-based control electronics in a total mass of 8.3 kg and volume of 5.7 L, and nominal power consumption of 21W. We describe the mechanical, thermal, and radiation-tolerant design features of the system and present the results of random vibration, storage temperature cycling, and thermal-vacuum testing conducted in accordance with NASA's General Environmental Verification Standard. We show that key comb performance metrics including oscillator and amplifier output power, frep, fCEO, and fopt signal-to-noise ratios, and integrated phase noise, remain within specification after environmental exposure, and we discuss observed failure modes and design modifications that improved robustness. These results demonstrate that compact, low power, fully stabilized, autonomous dual-comb systems can be engineered and qualified for spaceflight on CubeSat platforms, providing a path forward for future low-cost comb-based space applications.
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All authors Stephanie D. Leifer, Matthew J. Kelley, Natalie Walsh, Ziba Shahriary, Paul Steinvurzel, Chrissy Fortuna, Geoffrey Maul, Adam Darley, Ian Coddington, Laura C. Sinclair, Ariel Berman, Victor Chin, Henry Timmers, Kevin Knabe, Jason Pinon, Andrew Attar, Cole Smith, Cyrus Bry, Davis S. Kun, Stan Stanev, Nicole Thai, Bennett Sodergren, Daniel Deveraux, Grant Capan, Will McIntyre, Manas Choure

Tuesday 15 September

Instrumentation and Methods for Astrophysics

Graph neural networks for exoplanet atmospheres

Antonia Vojtekova, Kai Hou Yip, Ingo P. Waldmann et al. (+4 more)

Calculating disequilibrium chemistry in exoplanet atmospheres remains a significant computational bottleneck in atmospheric retrievals. The increasing observational precision from facilities such as JWST and the Ariel mission requires including disequilibrium chemistry in these analyses. Previous studies have demonstrated that neural networks can emulate kinetic chemistry, although their spatial inductive bias does not align with the topology of chemical reaction networks. This study introduces a graph neural network surrogate that represents chemical species as nodes and temperature-dependent reaction rates as edges, thereby enabling information propagation along physically meaningful chemical pathways. The model is trained on atmospheres generated using the Venot+2020 chemical scheme and Guillot temperature-pressure profiles. The GNN accurately reconstructs disequilibrium abundances across the sampled parameter space and reduces the mean abundance error by a factor of approximately 3 compared to the previous U-Net model. When applied to transmission spectra, most predictions fall within the observational precision expected for JWST and Ariel, with only about 7% of test atmospheres exceeding a 20 ppm mean spectral error. Performance variations are primarily observed in chemically transitional regimes near a carbon-to-oxygen ratio of one and at low temperatures. An evaluation of the boundary-case planet WASP-39b demonstrates effective performance under a moderate domain shift. Perturbation analysis indicates that disturbances propagate along chemical connectivity rather than spatial adjacency, confirming that the architecture captures the structure of reaction networks. These results suggest that GNN surrogates provide accurate, computationally efficient predictions of disequilibrium chemistry, facilitating integration into the atmospheric retrieval pipeline.
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All authors Antonia Vojtekova, Kai Hou Yip, Ingo P. Waldmann, Nikolaos Nikolaou, Olivia Venot, Ahmed Faris Al-Refaie, Bruno Merín

Instrumentation and Methods for Astrophysics

Quantifying the temperature-dependent yields of N$_2$ and N$_2$H$_4$ formation in vacuum-ultraviolet-irradiated NH$_3$ ice

P. Samarth, G. Fedoseev, S. Ioppolo et al. (+3 more)

Gas–grain astrochemical models predict that a substantial fraction of elemental nitrogen in dense cores and protoplanetary disks is locked in molecular nitrogen (N$_2$), in the gas or ice phase, although interstellar N$_2$ ice has not been directly identified. Rosetta measurements at comet 67P/Churyumov–Gerasimenko showed strong N$_2$ depletion relative to CO, while NH$_3$ was the dominant detected nitrogen-bearing ice. We experimentally quantify the conversion of NH$_3$ ice into N$_2$ and N$_2$H$_4$ under astronomically relevant conditions by studying its temperature- and fluence-dependent VUV photochemistry. Experiments were performed under ultra-high vacuum using 40-monolayer NH$_3$ ice at 15, 25, and 70 K irradiated at 115–170 nm to a total fluence of $3.8\times10^{18}$ photons cm$^{-2}$. Laser desorption with post-ionization reflection time-of-flight mass spectrometry (ReTOF-MS) was used to monitor N$_2$ and N$_2$H$_4$ simultaneously. VUV photolysis efficiently forms both products, with formation kinetics and product ratios depending on temperature and photon fluence. Initial-growth fits gave the highest apparent ice-retained N$_2$ formation yield at 15 K, approximately an order of magnitude above those at 25 and 70 K. The N$_2$/NH$_3$ column-density ratio was determined as a function of fluence and compared with astronomical constraints. These results suggest that NH$_3$ ice photochemistry may provide an additional pathway to N$_2$ ice in cold outer planetary environments.
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All authors P. Samarth, G. Fedoseev, S. Ioppolo, L. Hornekær, E. F. van Dishoeck, K.-J. Chuang

Instrumentation and Methods for Astrophysics

Pulsed ion deflection to overcome detector saturation in cryogenic ice sampling

P. Samarth, M. Bulak, D. Paardekooper et al. (+2 more)

In 2014, we introduced a new experimental approach to study the UV photo-processing of cryogenic ices of astrophysical interest using laser ablation in combination with ionization and time-of-flight mass spectrometry (ToF-MS). The setup, MATRI$^2$CES (Mass Analytical Tool to Research Interstellar ICES), allowed us to detect newly formed species at low abundances. However, we found that with increasing molecular complexity, the detection of larger photoproducts was hindered by the dynamic range of the detector. Here, we introduce a method to overcome this issue that we expect to be useful for similar applications in other research fields. The concept is based on a precisely controlled high-energy pulser that regulates the voltage across the deflection plates of the ToF-MS to deflect the most abundant species and prevent them from reaching the detector. In this way, the detector sensitivity can be increased from an operating voltage of 2500~V up to 3000~V. The applicability is first illustrated using an argon matrix, in which $^{40}$Ar$^+$ ions are deflected to increase the detection sensitivity for $^{40}$Ar$^{2+}$ at $m/z=20$ and $^{40}$Ar$_2^+$ at $m/z=80$ by a factor of 30. Similarly, we show that substantially larger complex organic molecules can be measured in UV-irradiated methanol ice.
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All authors P. Samarth, M. Bulak, D. Paardekooper, K.-J. Chuang, H.Linnartz

Instrumentation and Methods for Astrophysics

Optimising instrument concepts with Machine Learning: Application to CMB spectral distortion experiments

Xavier Coulon, Nabila Aghanim and Bruno Maffei

Understanding how instrumental and mission parameters affect the ability to measure faint astrophysical signals is a key challenge in the design of future experiments. This is particularly relevant for CMB spectral distortions, whose weak signals are affected by both instrumental effects and astrophysical foregrounds. We develop a method to explore and optimise the multidimensional parameter space of an astronomical instrument, and apply it to CMB spectral distortion measurements using the FOSSIL mission concept. We combine a dedicated sky model with a realistic instrument model and use Fisher forecasts to assess measurement capabilities of the simulated instrument. Decision-tree-based regression models are then used to learn the non-linear mapping between instrumental parameters and the predicted signal-to-noise ratios of the sky observables. Random Forest and gradient boosting models accurately reproduce the forecasted measurement performance. SHAP values are used to interpret the impact of instrumental parameters on the measurement. The temperature of the warmest instrumental component is found to be the dominant parameter for all three observables, highlighting the importance of limiting internal emission and operating the instrument at cryogenic temperatures. Frequency coverage is also highly influential, revealing a trade-off between spectral coverage and instrumental sensitivity. The proposed optimisation method provides a fast and interpretable approach to explore high-dimensional instrumental parameter spaces and identify parameters that most strongly influence the scientific performance of an experiment. To the best of our knowledge, this work represents the first application of machine-learning methods to the global optimisation of an astronomical instrument and can readily be extended to other astronomical instruments and mission concepts.
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Instrumentation and Methods for Astrophysics · Cross-listed from gr-qc

Massively parallel transdimensional sampling with data assimilation: an application to LISA galactic binaries

Gabriele Demasi and Walter Del Pozzo

Transdimensional Bayesian inference is becoming a key ingredient in gravitational-wave astronomy. In many relevant applications, the number of components needed to describe the data is not known a priori and must be inferred jointly with their parameters. We present a transdimensional Sequential Monte Carlo (SMC) framework designed to exploit massive parallelism. The method evolves a population of particles through a sequence of tempered distributions and uses the No-U-Turn Sampler for the exploration of fixed-dimensional parameter space while reversible-jump birth and death moves allow the number of components to vary. The same SMC construction also enables posterior samples obtained from a shorter data segment to be updated as additional data become available, enhancing the overall efficiency of the analysis. We validate the approach on two proof-of-concept problems: the recovery of a sequence of Gaussian pulses and a simplified LISA Galactic-binary inference problem. In both cases, the method recovers the injected number of components and produces consistent posterior estimates. These results indicate that the proposed method is a promising avenue toward scalable and parallel Bayesian transdimensional inference for current and future gravitational-wave astronomy.
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Instrumentation and Methods for Astrophysics

The OpenGadget3 Code for Cosmological Simulations

Klaus Dolag, Geray S. Karademir, Luca Tornatore et al. (+28 more)

We present the public release of OpenGadget3 (OG3), a substantially extended and re-organised version of the widely used Gadget-2/3 family of cosmological simulation codes. Since G2 was made publicly available, the absence of continued official development led to the creation of numerous, mutually incompatible developer versions of G3 across the community. This made it effectively impossible to track bug fixes, reproduce published results, or consistently credit the many individual contributors. OG3 addresses this by consolidating these disparate developments into a single, documented, and continuously maintained code base, released under the GNU GPLv3 through a GitLab repository (with an accompanying wiki), regularly synchronised with the active developer branch, and supported by a dedicated continuous-integration (CI) pipeline. OG3 retains the core algorithmic backbone of its predecessors, a Barnes&Hut oct-tree combined with a Particle-Mesh method for gravity, and a choice of Smoothed Particle Hydrodynamics or Meshless-Finite-Mass solvers for gas dynamics, within a hybrid MPI/OpenMP parallelisation framework, extended with GPU offloading via OpenACC and OpenMP. The code integrates an extensive suite of sub-resolution and physical modules, including primordial chemistry, radiative cooling, star formation, stellar feedback and chemical enrichment, dust formation and evolution, black hole growth and AGN feedback, MHD, thermal conduction, physical viscosity, SIDM, and massive neutrinos. OG3 introduces new features improving robustness, reproducibility, and usability: a flexible mixed-precision framework spanning 16- to 128-bit representations; expert-level tagged parameters with restart-time change log; extensive consistency checks against invalid configurations; and FAIR-compliant reporting of all settings, parameters, and specific publications. (shortened and abridged)
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All authors Klaus Dolag, Geray S. Karademir, Luca Tornatore, Antonio Ragagnin, Milena Valentini, Ludwig M. Böss, Frederick Groth, Giuseppe Murante, Stefano Borgani, Volker Springel, Cenanda Arido, Javier Badía, Tiago Castro, Alice Damiano, Laura Di Federico, Moritz S. Fischer, Gian Luigi Granato, Nitya Hariharan, David Klemmer, Umberto Maio, Tirso Marin-Gilabert, Ilaria Marini, Yashraj Patil, Margarita Egelhofer, Cinthia Ragone-Figueroa, Luca Sala, Cecilia Scannapieco, Ludwig D. Schmidt, Ulrich P. Steinwandel, Giovanni Tedeschi-Prades, Marc Wiertel

Instrumentation and Methods for Astrophysics

Rethinking Domain Specialization for Open-Ended Scientific Reasoning in Astronomy Language Models

Vanessa Lama, Sanjay Das, Emily Herron et al. (+5 more)

Domain-specialized language models are widely used for scientific question answering, but stronger general-purpose systems raise a sharper question: when does domain-specific fine-tuning remain valuable for open-ended scientific reasoning? We study this in astronomy with a curated QA benchmark from publicly available 2017–2026 Olympiad-style materials. The free-response subset contains 300 questions, including 204 text-only and 96 image-linked examples. We compare open-weight and API-served general-purpose, multimodal, and astronomy-specialized models using judge-based correctness and complementary reference metrics. Strong general-purpose models establish the highest correctness baseline in this testbed, while analyses of metric agreement, judge sensitivity, benchmark composition, and modality reveal variation not captured by a single leaderboard. These results motivate treating domain specialization as a task- and deployment-dependent property and highlight the role of domain-specific evaluation in determining which models, capabilities, and evaluation criteria are appropriate for scientific workflows.
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All authors Vanessa Lama, Sanjay Das, Emily Herron, Yuan-Sen Ting, Tijmen de Haan, Junqi Yin, Tirthankar Ghosal, Feiyi Wang

Instrumentation and Methods for Astrophysics

IViS: Interferometric Visibility-domain inversion Software - A GPU-accelerated Python framework for joint deconvolution with ASKAP

A. Marchal, N. M. McClure-Griffiths, J. Dempsey et al. (+9 more)

Wide-field spectral-line imaging with modern radio interferometers remains challenging when the emission is extended, multiscale, and distributed over many overlapping pointings. Accurate reconstruction requires joint treatment of the calibrated visibilities, control of image-domain regularity, and recovery of missing short spacings from single-dish data. We present IViS (Interferometric Visibility-domain Inversion Software), a GPU-accelerated Python framework for visibility-domain joint deconvolution, and assess its performance for wide-field HI imaging with the Australian Square Kilometre Array Pathfinder (ASKAP). The current model, Classic3D, reconstructs a non-parametric sky cube directly from calibrated visibilities by minimizing a regularized least-squares criterion. The forward model relies on a non-uniform fast Fourier transform (NUFFT), supports joint deconvolution across mosaic pointings and positivity constraints, and can incorporate single-dish data through a fusion term. We validate the method using point-source, noise-only, and multiscale diffuse-emission simulations, and apply it to ASKAP observations toward the Large Magellanic Cloud (LMC). The simulations show that IViS recovers point-source flux accurately without regularization and that regularization sets the trade-off between noise suppression and effective resolution. Joint deconvolution can recover more large-scale power than linear mosaicking of independently deconvolved pointings. With single-dish information, the reconstructed power spectra closely reproduce the input sky statistics. Applied to ASKAP data, IViS yields 10h mosaics with an effective resolution of 22” and reduced residual side-lobe structure. Compared with ASKAPSoft multi-scale CLEAN for a single observing block, Classic3D exhibits fewer residual side-lobes and recovers substantially more power at low spatial frequencies.
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All authors A. Marchal, N. M. McClure-Griffiths, J. Dempsey, H. Nguyen, H. Dénes, J. Dickey, C. Lynn, Y. K. Ma, D. McConnell, M.-A. Miville-Deschênes, N. Pingel, J. Th. van Loon

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

$B$-sure. Part II. Scattering transforms as robustness test for tensor-to-scalar ratio detection from CMB observations

Claudio Ranucci, Sébastien Pierre, Léo Vacher et al. (+7 more)

Galactic foregrounds represent a major contamination to the measurement of primordial $B$-modes from observations of the Cosmic Microwave Background polarisation. Even after the application of component separation algorithms, foreground residuals may potentially still bias the estimate of the tensor-to-scalar ratio $r$, causing a false detection. In this work, we present the methodology of a robustness test for the validation of an eventual detection of primordial $B$-modes, as obtained by a future, LiteBIRD-like satellite experiment. The goal of the test is to identify the foreground residuals contamination by looking for non-Gaussian properties in the CMB $B$-modes map, recovered through blind component separation algorithms. We adopt scattering transforms (ST) as our summary statistics sensitive to the non-Gaussian features of foreground residuals and to their correlation with foregrounds tracer maps. We characterise and validate the methodology on realistic sky simulations with different levels of foregrounds complexity. The proposed test is able to identify a bias on the tensor-to-scalar ratio of $\gtrsim 10^{-3}$ in $\sim 90\%$ of our simulations, with this bias value being of the same order of the accuracy targeted by LiteBIRD. Additionally, for our particular experimental configuration, the test is passed when the bias is lower than the sensitivity on the $r$ parameter, and no warning is raised. These results provide an important step forward in the development of statistical tools for validating future measurement of cosmological parameters, against foregrounds contamination.
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All authors Claudio Ranucci, Sébastien Pierre, Léo Vacher, Alessandro Carones, Nicoletta Krachmalnicoff, Erwan Allys, Jean-Marc Delouis, Paolo Campeti, Giuseppe Puglisi, Carlo Baccigalupi

Instrumentation and Methods for Astrophysics

Assessing ionospheric effects on image quality in the LOFAR Decametre Sky Survey

Cristina-Maria Cordun, Harish K. Vedantham and Maaijke Mevius

The terrestrial ionosphere is a major limitation for high angular resolution imaging at decametre wavelengths. Its rapidly varying and direction-dependent phase errors can defocus sources, reduce recovered flux densities, and produce strong field-to-field variations in image quality. We investigate these effects using three overlapping pointings from the LOFAR Decametre Sky Survey (LoDeSS), observed under different ionospheric conditions. Using phase-calibration solutions on a bright source, we derive the spatial diffractive scale, the temporal decorrelation time, and the angular scale over which direction-dependent calibration solutions can be transferred before residual phase errors become significant. These metrics are reflected in the final image quality. The field with the weakest ionospheric phase structure has the sharpest compact sources and the most reliable flux-density scale, while the field with the strongest phase structure shows substantial source broadening and flux-density loss. The comparison indicates that spatial ionospheric structure is the dominant limitation in these observations. Calibration-derived ionospheric metrics, therefore, provide a practical way to diagnose and predict image-quality variations in decametre survey data.
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Instrumentation and Methods for Astrophysics · Cross-listed from astro-ph.EP

DewTwin-Coin: an onboard autonomous framework for lunar water-ice prospecting using Chandrayaan-3 LIBS and ChaSTE data

Soundarya R. and Debasish Mondal

It is important to locate water-ice in the lunar regolith to build futuristic, sustainable bases there. But communication delays from Earth, limited bandwidth, and power constraints demand an onboard, autonomous, time-efficient decision-making framework for locating volatiles such as water-ice in the lunar regolith. In this work, we present a framework, DewTwin-Coin, that can locate potential water-ice sites in real time without drilling. Its decision-making principle is based on a find-S learning algorithm that uses surface temperature and the Hydrogen-to-Oxygen intensity ratio at a location. The core idea is a physics-based rule $-$ water-ice is stable only if the temperature is below 110 K and the Hydrogen-to-Oxygen intensity ratio is between 1.7 and 2.3. We validate DewTwin-Coin on Chandrayaan-3's 3165 laser-induced breakdown spectroscopy (LIBS) elemental data with 387 Chandra's surface thermophysical experiment (ChaSTE) data. On a 16 GB RAM system, it classified all 3165 locations within 615 seconds, yielding no strong signatures of water-ice, which matches the Chandrayaan-3 in-situ analysis. This framework is very important for future lunar and other planetary missions in which an onboard rover can autonomously determine feasible drilling locations for water-ice without issuing false drilling commands in warm terrains. Thus, the mission's onboard setup can stretch its technical limits in both power and memory capacity.
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Instrumentation and Methods for Astrophysics

Characterization of IBEX LmAPD detectors at CEA for future low-noise NIR astronomy instruments

Jean Le Graët, Vincent Affatato, Marion Baumann et al. (+9 more)

Future near-infrared (NIR) astronomy missions dedicated to photon-starved science cases, in particular an all-sky astrometric survey extending the legacy of Gaia into the NIR, as identified within the ESA Voyage~2050 programme, require large-format detectors combining sub-electron effective read noise with very low dark current. Linear-mode avalanche photodiodes (LmAPDs) based on HgCdTe meet this need by multiplying the photo-generated charge by an avalanche gain before the readout stage, thereby reducing the relative contribution of the read noise. We report the first electro-optical characterization of an IBEX detector, a $2048\times2048$, \SI{15}{\micro\meter}-pitch HgCdTe LmAPD array developed by Leonardo with the European Space Agency and operated at \SI{80}{\kelvin} on a dedicated bench at CEA-IRFU. We first discuss the central difficulty of characterizing an APD array, the degeneracy between avalanche gain, quantum efficiency (QE), and conversion gain in the measured response, and we then separate the measurements into two categories. Among the quantities that are directly measurable without assumptions, we report a signal-to-noise ratio for a CDS measurement that exceeds that of a Euclid-type H2RG above \SI{8}{\volt} pixel bias under identical low-flux conditions, a photo-response non-uniformity stable at the $\sim$10% level, and a quantum efficiency-to-excess-noise ratio (QEFR) of \num{0.40} at \SI{10.5}{\volt}. Among the quantities derived under an explicit set of assumptions, we obtain a conversion gain corresponding to a sense-node capacitance of \SI{27}{\femto\farad}, a quantum efficiency of $46\pm12\%$ at \SI{2.5}{\volt}, and an excess noise factor $F=1.15\pm0.14$ at \SI{10.5}{\volt}. These results establish IBEX as a promising European large-format detector for future ultra-low-flux NIR instruments.
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All authors Jean Le Graët, Vincent Affatato, Marion Baumann, Olivier Boulade, Cyrille Delisle, Eloy Hernandez, Christian Ketchazo, Frederic Lemmel, Vincent Moreau, Salima Mouzali, Thibault Pichon, François Visticot

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

A fast radio burst from a non-targeted low-frequency survey

Cristian Di Pietrantonio, Marcin Sokolowski, Clancy W. James et al. (+13 more)

Fast radio bursts (FRBs) are bright, millisecond-duration transient radio signals of extragalactic origin with unknown source and emission mechanisms. While several thousand FRBs have been discovered at frequencies above 400 MHz, detections at lower frequencies have been exceptionally rare. Contributing to their rarity are the magnified dispersive delay, in the tens of seconds, and signal scattering that make low-frequency searches with established techniques computationally prohibitive. In particular, the only confirmed detection below 300 MHz came from a Low-Frequency Array observing campaign targeted at FRB 20180916B, a source already known to emit at higher frequencies. Here we present the first non-targeted detection of an FRB below 300 MHz, achieved in a wide-field, imaging-based survey with the Murchison Widefield Array. The implied FRB rate is consistent with that observed at higher frequencies, demonstrating that non-targeted wide-field surveys can uncover an unbiased, large low-frequency FRB population. This result challenges models invoking severe scattering or absorption to explain previous non-detections, and strengthens the case of low-frequency observations as promising avenue to study the local environment of FRBs.
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All authors Cristian Di Pietrantonio, Marcin Sokolowski, Clancy W. James, N. D. Ramesh Bhat, Randall Wayth, Danny C. Price, Christopher Harris, Chia Min Tan, Christopher P. Lee, Bradley W. Meyers, Mahitha Ega, Samuel J. McSweeney, Christopher Schlipalius, Gregory Sleap, Steven E. Tremblay, Mengyao Xue

Instrumentation and Methods for Astrophysics

PyExoCross 2.0: A Python Framework for LTE and non-LTE Spectra, Cross Sections, and Spectroscopic Post-processing of Atomic and Molecular Line Lists

Jingxin Zhang, Sergei N. Yurchenko and Jonathan Tennyson

PyExoCross is a Python-based spectroscopic post-processing framework for converting large atomic and molecular line lists into scientifically useful quantities, including partition function, specific heats, cooling functions, lifetimes, oscillator strengths, line intensities, stick spectra, and absorption and emission cross sections. It is intended for applications in astrophysics, planetary atmospheres, laboratory spectroscopy, and other high-temperature environments where large modern databases require efficient and reproducible computational treatment. The new release provides both a configuration-file-driven command-line interface (CLI) and a Python application programming interface (API) within a unified computational framework. The original input file workflow is retained, while the Python API enables direct use in scripts, notebooks, and automated pipelines. The version PyExoCross 2.0 also adds explicit support for non-local thermodynamic equilibrium (non-LTE) calculations, including two-temperature models and user-defined density and population treatments for both absorption and emission spectra. In addition, database compatibility has been expanded beyond ExoMol, HITRAN, and HITEMP line lists to include high-resolution molecular database ExoMolHR and atomic database ExoAtom. GPU acceleration is also introduced for computationally intensive intensity and cross-section calculations and is available for all currently supported database formats. These developments improve workflow flexibility, reproducibility, and integration with modern data-analysis environments, while extending the physical modelling capabilities of the code. PyExoCross therefore provides a more general and extensible platform for large-scale spectroscopic simulations based on modern atomic and molecular databases.
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Instrumentation and Methods for Astrophysics · Cross-listed from astro-ph.SR

Count-based spectral component imaging (CCI) of solar flares in X-rays

Alessia Guidetti, Muriel Zoë Stiefel, Paolo Massa et al. (+3 more)

X-ray emission in solar flares is produced by both multi-thermal plasma and accelerated electrons. Classical imaging approaches reconstruct X-ray intensity maps which contain contributions from multiple spectral components (e.g., hot, superhot, and non-thermal), and do not allow retrieving the morphology of the different components separately. We introduce a novel imaging technique, called "Count-based spectral Component Imaging (CCI)", to jointly reconstruct spatially resolved emission measure maps of the thermal components, and the electron flux distribution of the non-thermal component from data provided by the Spectrometer/Telescope for Imaging X-rays (STIX) aboard Solar Orbiter. We formulate a linear model linking the Differential Emission Measure (DEM), approximated by two thermal components, and the non-thermal electron flux to the observed counts. The resulting inverse problem is solved with the Richardson-Lucy algorithm. We apply CCI to STIX observations of SOL2024-10-01T22 and compare it with the previously developed Spectral Component Imaging (SCI) method, as well as classical imaging approaches. The reconstructed thermal and non-thermal components show good agreement with those obtained using SCI. This proof-of-concept study shows that CCI obtains results consistent with SCI but with fewer inputs. In contrast with SCI, CCI can also be applied to hard X-ray focusing optics imaging.
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All authors Alessia Guidetti, Muriel Zoë Stiefel, Paolo Massa, Anna Maria Massone, Michele Piana, Säm Krucker