arXiv subjects

William Martin

Publications and source records attributed to William Martin.

9 recordsLinked to original sources

arXiv2026

Dynamic Range Beyond Bit Depth of a CMOS Image Sensor Using Interleaved Row Readout

The dynamic range available from a sensor is vital to its utility. The limits on the dynamic range that can be obtained from an image sensor are set by the brightest and faintest objects that can be detected. In recent years, CMOS (complementary metal-oxide-semiconductor) image sensors (CIS) have gained high popularity due to their low cost and high availability. However, as with all detectors, the dynamic range is constrained by the sensor's bit depth. Here, we have modified the readout scheme of a commercial CIS120 sensor from Teledyne e2v, to enhance its dynamic range. We have advanced the interleaved row readout method proposed by Wocial et al. by using a more sophisticated approach, which enables us to readout chosen rows much more frequently to avoid saturation and then readout other rows on the sensor once to form the image. Our laboratory tests provide a dynamic range of 134 dB elevated from the sensor's native 12-bit of about 71 dB. We also built a camera housing that enabled first-time operation of interleaved row readout on-sky to observe the bright stars, Vega and Polaris. In complex mode we obtained unsaturated single exposure images of these bright stars, which have magnitudes near zero and detect background stars with Gaia G magnitudes around 15 in a single exposure, with a detection threshold of 5$\sigma$. The achievable dynamic range with this interleaved row readout is limited only by the readout noise and scattering in the camera optics.

astro-ph.IM↗

arXiv2025

Use of solid fused silica etalon with broadband metallic coatings for calibration of high-resolution optical spectrograph

Wavelength calibration is a key factor for high-resolution spectroscopic measurements for precision radial velocities. Hollow-cathode lamps (e.g., ThAr), absorption cells (e.g., iodine cell), dielectric coated Fabry-P\'erot etalons and laser frequency combs have been implemented over the years for precise wavelength calibration and wavelength drift measurements. However, due to their various impediments as wavelength calibrators, investigations of alternative methods remain of prime interest. In this paper, we examined the feasibility of low-cost (~ $1000) commercially available solid fused silica etalon with a broadband metallic coating as a calibrator. We studied the behaviour for two cavity spacings (free spectral range of 1/cm and 0.5/cm) with temperature from theoretical derivation and experimental data. Our setup had a temperature stability of 0.8 mK for a calibrator system using an off-the-shelf dewar flask with active stabilisation. Our result from radial velocity drift measurements demonstrated that such a calibration system is capable of providing higher signal-to-noise calibration and better nightly drift measurement relative to ThAr in the wavelength range between 470 nm and 780 nm. A similar result has been previously found for Fabry-P\'erot etalons, and although the metalon solution lacks the efficiency of an etalon, it does offers a cost-effective broadband solution, which should be less prone to aging relative to complex dielectric mirror coatings. Nonetheless, long-term monitoring is required to understand the metalon behaviour in detail.

astro-ph.IM↗

arXiv2025

A Quantum Framework for Protein Binding-Site Structure Prediction on Utility-Level Quantum Processors

Accurate prediction of protein active-site structures remains a central challenge in structural biology, particularly for short and flexible peptide fragments where conventional and simulation-based methods often fail. Here, we present a quantum computing framework specifically developed for utility-level quantum processors to address this problem. Starting from an amino acid sequence, we formulate structure prediction as a ground-state energy minimization problem using the Variational Quantum Eigensolver (VQE). Amino acid connectivity is encoded on a tetrahedral lattice model, and structural constraints-including steric, geometric, and chirality terms-are mapped into a problem-specific Hamiltonian represented as sparse Pauli operators. Optimization is performed with a two-stage architecture that separates energy estimation from measurement decoding, enabling noise mitigation under realistic device conditions. We evaluate the framework on 23 randomly selected protein fragments from the PDBbind dataset and 7 fragments from therapeutically relevant proteins, and execute experiments on the IBM-Cleveland Clinic quantum processor. Predictions are benchmarked against AlphaFold 3 (AF3) and classical simulation-based approaches using identical postprocessing and docking procedures. Our method outperforms both AF3 and classical baselines in RMSD (root-mean-square deviation) and docking efficacy. These results demonstrate an end-to-end, hardware-executable pipeline for biologically relevant structure prediction on real quantum processors, highlighting its engineering feasibility and practical advantages over existing classical and deep learning approaches.

cs.ET↗

arXiv2024

An approach to robust Bayesian regression in astronomy

Model mis-specification (e.g. the presence of outliers) is commonly encountered in astronomical analyses, often requiring the use of ad hoc algorithms which are sensitive to arbitrary thresholds (e.g. sigma-clipping). For any given dataset, the optimal approach will be to develop a bespoke statistical model of the data generation and measurement processes, but these come with a development cost; there is hence utility in having generic modelling approaches that are both principled and robust to model mis-specification. Here we develop and implement a generic Bayesian approach to linear regression, based on Student's t-distributions, that is robust to outliers and mis-specification of the noise model. Our method is validated using simulated datasets with various degrees of model mis-specification; the derived constraints are shown to be systematically less biased than those from a similar model using normal distributions. We demonstrate that, for a dataset without outliers, a worst-case inference using t-distributions would give unbiased results with $\lesssim\!10$ per cent increase in the reported parameter uncertainties. We also compare with existing analyses of real-world datasets, finding qualitatively different results where normal distributions have been used and agreement where more robust methods have been applied. A Python implementation of this model, t-cup, is made available for others to use.

astro-ph.IM↗

arXiv2023

Mitigating Modal Noise in Multimode Circular Fibres by Optical Agitation using a Galvanometer

Modal noise appears due to the non-uniform and unstable distribution of light intensity among the finite number of modes in multimode fibres. It is an important limiting factor in measuring radial velocity precisely by fibre-fed high-resolution spectrographs. The problem can become particularly severe as the fibre's core become smaller and the number of modes that can propagate reduces. Thus, mitigating modal noise in relatively small core fibres still remains a challenge. We present here a novel technique to suppress modal noise. Two movable mirrors in the form of a galvanometer reimage the mode-pattern of an input fibre to an output fibre. The mixing of modes coupled to the output fibre can be controlled by the movement of mirrors applying two sinusoidal signals through a voltage generator. We test the technique for four multimode circular fibres: 10 and 50 micron step-index, 50 micron graded-index, and a combination of 50 micron graded-index and 5:1 tapered fibres (GI50t). We present the results of mode suppression both in terms of the direct image of the output fibre and spectrum of white light obtained with the high-resolution spectrograph. We found that the galvanometer mitigated modal noise in all the tested fibres, but was most useful for smaller core fibres. However, there is a trade-off between the modal noise reduction and light-loss. The GI50t provides the best result with about 60% mitigation of modal noise at a cost of about 5% output light-loss. Our solution is easy to use and can be implemented in fibre-fed spectrographs.

astro-ph.IM↗

arXiv2020

HiFLEx -- a highly flexible package to reduce cross-dispersed echelle spectra

We describe a flexible data reduction package for high resolution cross-dispersed echelle data. This open-source package is developed in Python and includes optional GUIs for most of the steps. It does not require any pre-knowledge about the form or position of the echelle-orders. It has been tested on cross-dispersed echelle spectrographs between 13k and 115k resolution (bifurcated fiber-fed spectrogaph ESO-HARPS and single fiber-fed spectrograph TNT-MRES). HiFLEx can be used to determine radial velocities and is designed to use the TERRA package but can also control the radial velocity packages such as CERES and SERVAL to perform the radial velocity analysis. Tests on HARPS data indicates radial velocities results within 3m/s of the literature pipelines without any fine tuning of extraction parameters.

astro-ph.IM↗

arXiv2019

Maestro: A Python library for multi-carrier energy district optimal control design

This paper introduces the Maestro library. This library for Python focuses on the design of predictive controllers for small to medium-scale energy networks. It allows non-expert users to describe multi-carrier (electricity, heat, gas) energy networks with a range of energy production, conversion, and storage component classes; together with consumption patterns. Based on this description a predictive controller can be synthesized and tested in simulation. This controller manages the dispatch of energy in the network, making sure that the demands are met, while minimizing the total energy cost. Alternative objectives can be specified. The library uses a mixed-integer linear modelling framework to describe the network and can be used in stand-alone based on standardized input files or as part of the larger energy network control platform PENTAGON.

eess.SY↗

arXiv2017

Bayesian Optimization Using Domain Knowledge on the ATRIAS Biped

Controllers in robotics often consist of expert-designed heuristics, which can be hard to tune in higher dimensions. It is typical to use simulation to learn these parameters, but controllers learned in simulation often don't transfer to hardware. This necessitates optimization directly on hardware. However, collecting data on hardware can be expensive. This has led to a recent interest in adapting data-efficient learning techniques to robotics. One popular method is Bayesian Optimization (BO), a sample-efficient black-box optimization scheme, but its performance typically degrades in higher dimensions. We aim to overcome this problem by incorporating domain knowledge to reduce dimensionality in a meaningful way, with a focus on bipedal locomotion. In previous work, we proposed a transformation based on knowledge of human walking that projected a 16-dimensional controller to a 1-dimensional space. In simulation, this showed enhanced sample efficiency when optimizing human-inspired neuromuscular walking controllers on a humanoid model. In this paper, we present a generalized feature transform applicable to non-humanoid robot morphologies and evaluate it on the ATRIAS bipedal robot -- in simulation and on hardware. We present three different walking controllers; two are evaluated on the real robot. Our results show that this feature transform captures important aspects of walking and accelerates learning on hardware and simulation, as compared to traditional BO.

cs.RO↗

arXiv2009

Detection of circular polarization in light scattered from photosynthetic microbes

The identification of a universal biosignature that could be sensed remotely is critical to the prospects for success in the search for life elsewhere in the universe. A candidate universal biosignature is homochirality, which is likely to be a generic property of all biochemical life. Due to the optical activity of chiral molecules, it has been hypothesized that this unique characteristic may provide a suitable remote sensing probe using circular polarization spectroscopy. Here, we report the detection of circular polarization in light scattered by photosynthetic microbes. We show that the circular polarization appears to arise from circular dichroism of the strong electronic transitions of photosynthetic absorption bands. We conclude that circular polarization spectroscopy could provide a powerful remote sensing technique for generic life searches.

astro-ph.EP↗