arXiv subjects

James Stevenson

Publications and source records attributed to James Stevenson.

6 recordsLinked to original sources

arXiv2026

HARMONI at ELT: Developing a Modular Review Process using TRIZ

HARMONI is the first light, adaptive optics assisted, near-IR integral field spectrograph for the ELT. It covers a spectral range from 800nm to 2450nm with resolving powers from 3000 to 7000 and spatial sampling of 25mas and 6mas. It can operate in two adaptive optics modes - SCAO (including a high contrast capability) and MCAO. The project is resuming its final design phase after a rescope design phase in 2025. The HARMONI team at UKATC have been pioneering the use of TRIZ by managing monthly TRIZ workshops to tackle significant project problems that arise. This TRIZ case study investigates how design changes of HARMONI can be reviewed effectively and efficiently. It draws on how the review process of Ground Based Astronomy projects can be improved to add quality to the successful creation of an instrument while reducing strain on designers and reviewer's time. To address resource-intensive and document-driven review processes, the case study utilised TRIZ techniques including: thinking in time and scale technique: the 40 inventive principles to tackle design contradiction: function analysis and size, time, cost analysis. The solution developed considered a modular, continuous review process focusing on specific subsystems or technical topics as they mature while encouraging a live review culture, where stakeholders and expert reviewers are engaged continuously through informal check-ins rather than infrequent formal meetings.

astro-ph.IM↗

arXiv2026

ANDES, the high-resolution spectrograph for the ELT: design and performance analysis of the YJH spectrograph

The ArmazoNes high Dispersion Echelle Spectrograph (ANDES) is a powerful second-generation high-resolution spectroscopic instrument for the Extremely Large Telescope (ELT). The UBV, RIZ, and YJH modules comprise fibre-fed spectrographs of the ANDES baseline design and will offer continuous wavelength coverage of 0.35-1.8 $\mu$m, with the addition of a K-band channel providing coverage up to 2.4 $\mu$m. Coupled with a spectral resolution of $\sim$100,000, ANDES must deliver the required wavelength calibration stability of 1 m/s over 24 hours, with a goal of 0.02 m/s across 10 years. These requirements establish the framework for the infrared module of ANDES, the YJH Spectrograph, leading to what will likely be the largest cryogenic, ultra-stable, high-resolution spectrograph ever built, and will offer the unique ability to observe in both seeing- and diffraction-limited modes interchangeably. We present the current design and performance analysis of the ANDES YJH Spectrograph, outlining the engineering challenges encountered alongside the corresponding strategies adopted to navigate them. In particular, we detail the technology development of the primary dispersing element, an echelle grating mosaic that will span over a metre in length.

astro-ph.IM↗

arXiv2025

Bridge2AI Recommendations for AI-Ready Genomic Data

Rapid advancements in technology have led to an increased use of artificial intelligence (AI) technologies in medicine and bioinformatics research. In anticipation of this, the National Institutes of Health (NIH) assembled the Bridge to Artificial Intelligence (Bridge2AI) consortium to coordinate development of AI-ready datasets that can be leveraged by AI models to address grand challenges in human health and disease. The widespread availability of genome sequencing technologies for biomedical research presents a key data type for informing AI models, necessitating that genomics data sets are AI-ready. To this end, the Genomic Information Standards Team (GIST) of the Bridge2AI Standards Working Group has documented a set of recommendations for maintaining AI-ready genomics datasets. In this report, we describe recommendations for the collection, storage, identification, and proper use of genomics datasets to enable them to be considered AI-ready and thus drive new insights in medicine through AI and machine learning applications.

q-bio.OT↗

arXiv2025

Efficient Long-Range Machine Learning Force Fields for Liquid and Materials Properties

Machine learning force fields (MLFFs) have emerged as a sophisticated tool for cost-efficient atomistic simulations approaching DFT accuracy, with recent message passing MLFFs able to cover the entire periodic table. We present an invariant message passing MLFF architecture (MPNICE) which iteratively predicts atomic partial charges, including long-range interactions, enabling the prediction of charge-dependent properties while achieving 5-20x faster inference versus models with comparable accuracy. We train direct and delta-learned MPNICE models for organic systems, and benchmark against experimental properties of liquid and solid systems. We also benchmark the energetics of finite systems, contributing a new set of torsion scans with charged species and a new set of DLPNO-CCSD(T) references for the TorsionNet500 benchmark. We additionally train and benchmark MPNICE models for bulk inorganic crystals, focusing on structural ranking and mechanical properties. Finally, we explore multi-task models for both inorganic and organic systems, which exhibit slightly decreased performance on domain-specific tasks but surprising generalization, stably predicting the gas phase structure of $\simeq500$ Pt/Ir organometallic complexes despite never training to organometallic complexes of any kind.

physics.chem-ph↗

arXiv2016

Constraining symmetron fields with atom interferometry

We apply the new constraints from atom-interferometry searches for screening mechanisms to the symmetron model, finding that these experiments exclude a previously unexplored region of parameter space. We discuss the possibility of networks of domain walls forming in the vacuum chamber, and how this could be used to discriminate between models of screening.

astro-ph.CO↗

arXiv2014

Ellipticity Weakens Chameleon Screening

The chameleon mechanism enables a long range fifth force to be screened in dense environments when non-trivial self interactions of the field cause its mass to increase with the local density. To date, chameleon fifth forces have mainly been studied for spherically symmetric sources, however the non-linear self interactions mean that the chameleon responds to changes in the shape of the source differently to gravity. In this work we focus on ellipsoidal departures from spherical symmetry and compute the full form of the chameleon force, comparing it's shape dependence to that of gravity. Enhancement of the chameleon force by up to 40% is possible when deforming a sphere to an ellipsoid of the same mass, with an ellipticity $\simeq 0.99$.

hep-th↗