arXiv subjects
Publications and source records attributed to John K. Webb.
Randomly oriented flattened spheroids have been used to describe a broad range of astrophysical phenomena. Here we use this geometric approach to derive equations representing lines of sight through quasar absorption clouds to constrain cloud sizes.
Searches for variations of fundamental constants require accurate measurement errors. There are several potential sources of errors and quantifying each one accurately is essential. This paper addresses one source of uncertainty relating to measuring the fine structure constant on white dwarf surfaces. Detailed modelling of photospheric absorption lines requires knowing the underlying spectral continuum level. Here we describe the development of a fully automated, objective, and reproducible continuum estimation method, based on fitting cubic splines to carefully selected data regions. Example fits to the Hubble Space Telescope spectrum of the white dwarf G191-B2B are given. We carry out measurements of the fine structure constant using two continuum models. The results show that continuum placement variations result in small systematic shifts in the centroids of narrow photospheric absorption lines which impact significantly on fine structure constant measurements. This effect must therefore be included in the overall error budget of future measurements. Our results also suggest that continuum placement variations should be investigated in other contexts, including fine structure constant measurements in stars other than white dwarfs, quasar absorption line measurements of the fine structure constant, and quasar measurements of cosmological redshift drift.
The high resolution spectrograph ESPRESSO on the VLT allows measurements of fundamental constants at unprecedented precision and hence enables tests for spacetime variations predicted by some theories. In a series of recent papers, we developed optimal analysis procedures that both exposes and eliminates the subjectivity and bias in previous quasar absorption system measurements. In this paper we analyse the ESPRESSO spectrum of the absorption system at z_{abs}=1.15 towards the quasar HE0515-4414. Our goal here is not to provide a new unbiased measurement of fine structure constant, alpha, in this system (that will be done separately). Rather, it is to carefully examine the impact of blinding procedures applied in the recent analysis of the same data by Murphy (2022) and prior to that, in several other analyses. To do this we use supercomputer Monte Carlo AI calculations to generate a large number of independently constructed models of the absorption complex. Each model is obtained using AI-VPFIT, with alpha fixed until a "final" model is obtained, at which point alpha is then released as a free parameter for one final optimisation. The results show that the "measured" value of alpha is systematically biased towards the initially-fixed value i.e. this process produces meaningless measurements. The implication is straightforward: to avoid bias, all future measurements must include alpha as a free parameter from the beginning of the modelling process.
Recent advances in spectroscopic instrumentation and calibration methods dramatically improve the quality of quasar spectra. Supercomputer calculations show that, at high spectral resolution, procedures used in some previous analyses of spacetime variations of fundamental constants are likely to generate spurious measurements, biased systematically towards a null result. Developments in analysis methods are also summarised and a prescription given for the analysis of new and forthcoming data.
The parent paper to this Addendum describes the optimisation theory on which VPFIT, a non-linear least-squares program for modelling absorption spectra, is based. In that paper, we show that Voigt function derivatives can be calculated analytically using Taylor series expansions and look-up tables, for the specific case of one column density parameter for each absorption component. However, in many situations, modelling requires more complex parameterisation, such as summed column densities over a whole absorption complex, or common pattern relative ion abundances. This Addendum provides those analytic derivatives.
This paper describes the optimisation theory on which VPFIT, a non-linear least-squares program for modelling absorption spectra, is based. Particular attention is paid to precision. Voigt function derivatives have previously been calculated using numerical finite difference approximations. We show how these can instead be computed analytically using Taylor series expansions and look-up tables. We introduce a new optimisation method for an efficient descent path to the best-fit, combining the principles used in both the Gauss-Newton and Levenberg-Marquardt algorithms. A simple practical fix for ill-conditioning is described, a common problem when modelling quasar absorption systems. We also summarise how unbiased modelling depends on using an appropriate information criterion to guard against over- or under-fitting. The methods and the new implementations introduced in this paper are aimed at optimal usage of future data from facilities such as ESPRESSO/VLT and HIRES/ELT, particularly for the most demanding applications such as searches for spacetime variations in fundamental constants and attempts to detect cosmological redshift drift.
High resolution spectra of quasar absorption systems provide the best constraints on temporal or spatial changes of fundamental constants in the early universe. An important systematic that has never before been quantified concerns model non-uniqueness. The absorption structure is generally complicated, comprising many blended lines. This characteristic means any given system can be fitted equally well by many slightly different models, each having a different value of α, the fine structure constant. We use AI Monte Carlo modelling to quantify non-uniqueness. Extensive supercomputer calculations are reported, revealing new systematic effects that guide future analyses: (i) Whilst higher signal to noise and improved spectral resolution produces a smaller statistical uncertainty for α, model non-uniqueness adds a significant additional uncertainty. (ii) Non-uniqueness depends on the line broadening mechanism used. We show that modelling the spectral data using turbulent line broadening results in far greater non-uniqueness, hence this should no longer be done. Instead, for varying αstudies, it is important to use the more physically appropriate compound broadening. (iii) We have studied two absorption systems in detail. Generalising thus requires caution. Nevertheless, if non-uniqueness is present in all or most quasar absorption systems, it seems unavoidable that attempts to determine the existence (or non-existence) of spacetime variations of fundamental constants is best approached using a statistical sample.
Modifications were made to the Sloan Digital Sky Survey's Baryonic Oscillations Spectroscopic Survey (SDSS/BOSS) optical fibres assigned to quasar targets in order to improve the signal-to-noise ratio in the Lyman-alpha forest. However, the penalty for these modifications is that quasars observed in this way require additional flux correction procedures in order to recover the correct spectral shapes. In this paper we describe such a procedure, based on the geometry of the problem and other observational parameters. Applying several correction methods to four SDSS quasars with multiple observations permits a detailed check on the relative performances of the different flux correction procedures. We contrast our method (which takes into account a wavelength dependent seeing profile) with the BOSS pipeline approach (which does not). Our results provide independent confirmation that the geometric approach employed in the SDSS pipeline works well, although with room for improvement. By separating the contributions from four effects we are able to quantify their relative importance. Most importantly, we demonstrate that wavelength dependence has a significant impact on the derived spectral shapes and thus should not be ignored.
Exploring the possibility that fundamental constants of Nature might vary temporally or spatially constitutes one of the key science drivers for the European Southern Observatory's ESPRESSO spectrograph on the VLT and for the HIRES spectrograph on the ELT. High-resolution spectra of quasar absorption systems permit accurate measurements of fundamental constants out to high redshifts. The quality of new data demands completely objective and reproducible methods. We have developed a new fully automated Artificial Intelligence-based method capable of deriving optimal models of even the most complex absorption systems known. The AI structure is built around VPFIT, a well-developed and extensively-tested non-linear least-squares code. The new method forms a sophisticated parallelised system, eliminating human decision-making and hence bias. Here we describe the workings of such a system and apply it to synthetic spectra, in doing so establishing methods of importance for future analyses of VLT and ELT data. The results show that modelling line broadening for high-redshift absorption components should include both thermal and turbulent components. Failing to do so means it is easy to derive the wrong model and hence incorrect parameter estimates. We also argue that model non-uniqueness can be significant, such that it is not feasible to expect to derive an unambiguous estimate of the fine structure constant alpha from one or a small number of measurements. No matter how optimal the modelling method, it is a fundamental requirement to use a large sample of measurements to meaningfully constrain temporal or spatial alpha variation.
New observations of the quasar HE0515$-$4414 have been made using the HARPS spectrograph on the ESO 3.6m telescope, aided by the Laser Frequency Comb (LFC). We present three important advances for $α$ measurements in quasar absorption spectra from these observations. Firstly, the data have been wavelength calibrated using LFC and ThAr methods. The LFC wavelength calibration residuals are six times smaller than when using the standard ThAr calibration. We give a direct comparison between $α$ measurements made using the two methods. Secondly, spectral modelling was performed using Artificial Intelligence (fully automated, all human bias eliminated), including a temperature parameter for each absorption component. Thirdly, in contrast to previous work, additional model parameters were assigned to measure $α$ for each individual absorption component. The increase in statistical uncertainty from the larger number of model parameters is small and the method allows a substantial advantage; outliers that would otherwise contribute a significant systematic, possibly corrupting the entire measurement, are identified and removed, permitting a more robust overall result. The $z_{abs} = 1.15$ absorption system along the HE0515$-$4414 sightline yields 40 new $α$ measurements. We constrain spatial fluctuations in $α$ to be $Δα/α\leq 9 \times 10^{-5}$ on scales $\approx 20\;{\rm km\,s}^{-1}$, corresponding to $\approx25\;$kpc if the $z_{abs} = 1.15$ system arises in a $1\;$Mpc cluster. Collectively, the 40 measurements yield $Δα/α=-0.27\pm2.41\times10^{-6}$, consistent with no variation.
Robust model-fitting to spectroscopic transitions is a requirement across many fields of science. The corrected Akaike and Bayesian information criteria (AICc and BIC) are most frequently used to select the optimal number of fitting parameters. In general, AICc modelling is thought to overfit (too many model parameters) and BIC underfits. For spectroscopic modelling, both AICc and BIC lack in two important respects: (a) no penalty distinction is made according to line strength such that parameters of weak lines close to the detection threshold are treated with equal importance as strong lines and (b) no account is taken of the way in which spectral lines impact on narrow data regions. In this paper we introduce a new information criterion that addresses these shortcomings, the "Spectral Information Criterion" (SpIC). Spectral simulations are used to compare performances. The main findings are (i) SpIC clearly outperforms AICc for high signal to noise data, (ii) SpIC and AICc work equally well for lower signal to noise data, although SpIC achieves this with fewer parameters, and (iii) BIC does not perform well (for this application) and should be avoided. The new method should be of broader applicability (beyond spectroscopy), wherever different model parameters influence separated small ranges within a larger dataset and/or have widely varying sensitivities.
Observations of the redshift z=7.085 quasar J1120+0641 have been used to search for variations of the fine structure constant, alpha, over the redshift range 5.5 to 7.1. Observations at z=7.1 probe the physics of the universe when it was only 0.8 billion years old. These are the most distant direct measurements of alpha to date and the first measurements made with a near-IR spectrograph. A new AI analysis method has been employed. Four measurements from the X-SHOOTER spectrograph on the European Southern Observatory's Very Large Telescope (VLT) directly constrain any changes in alpha relative to the value measured on Earth (alpha_0). The weighted mean strength of the electromagnetic force over this redshift range in this location in the universe is da/a = (alpha_z - alpha_0)/alpha_0 = (-2.18 +/- 7.27) X 10^{-5}, i.e. we find no evidence for a temporal change from the 4 new very high redshift measurements. When the 4 new measurements are combined with a large existing sample of lower redshift measurements, a new limit on possible spatial variation of da/a is marginally preferred over a no-variation model at the 3.7 sigma level.
We present the first paper of the series Origin of Metals around Galaxies (OMG) aimed to study the origin of the metals observed in the circumgalactic and intergalactic media. In this work we extract and build the catalogs of metal absorbers that will be used in future analyses, and make our results publicly available to the community. We design a fully automatic algorithm to search for absorption metal-line doublets of the species CIV, NV, SiIV and MgII in high-resolution ($R\gtrsim30\,000$) quasar spectra without human intervention, and apply it to the high-resolution and signal-to-noise ratio spectra of 690 quasars, observed with the UVES and HIRES instruments. We obtain $5\,656$ CIV doublets, $7\,919$ doublets of MgII, $2\,258$ of SiIV, and 239 of NV, constituting the largest high-resolution metal-doublet samples to date, and estimate the dependence of their completeness and purity on various doublet parameters such as equivalent width and redshift, using real and artificial quasar spectra. The catalogs include doublets with rest-frame line equivalent widths down to a few ${\rm mÅ}$, all detected at a significance above 3$σ$, and covering the redshifts between $1<z \lesssim 5$, properties that make them useful for a wide range of chemical evolution studies.
We recently presented a new "artificial intelligence" method for the analysis of high-resolution absorption spectra (Bainbridge and Webb, Mon. Not. R. Astron. Soc. 2017, 468,1639-1670). This new method unifies three established numerical methods: a genetic algorithm (GVPFIT); non-linear least-squares optimisation with parameter constraints (VPFIT); and Bayesian Model Averaging (BMA). In this work, we investigate the performance of GVPFIT and BMA over a broad range of velocity structures using synthetic spectra. We found that this new method recovers the velocity structures of the absorption systems and accurately estimates variation in the fine structure constant. Studies such as this one are required to evaluate this new method before it can be applied to the analysis of large sets of absorption spectra. This is the first time that a sample of synthetic spectra has been utilised to investigate the analysis of absorption spectra. Probing the variation of nature's fundamental constants (such as the fine structure constant), through the analysis of absorption spectra, is one of the most direct ways of testing the universality of physical laws. This "artificial intelligence" method provides a way to avoid the main limiting factor, i.e., human interaction, in the analysis of absorption spectra.
Spectra observed with the Ultraviolet and Visual Echelle Spectrograph (UVES) on the European Southern Observatory's VLT exhibit long-range wavelength distortions. These distortions impose a systematic error on high-precision measurements of the fine-structure constant, $α$, derived from intervening quasar absorption systems. If the distortion is modelled using a model that is too simplistic, the resulting bias in $Δα/α$ away from the true value can be larger than the statistical uncertainty on the $α$ measurement. If the effect is ignored altogether, the same is true. If the effect is modelled properly, accounting for the way in which final spectra are generally formed from the co-addition of exposures made at several different instrumental settings, the effect can be accurately removed and the correct $Δα/α$ recovered.
Hot white dwarf stars are the ideal probe for a relationship between the fine-structure constant and strong gravitational fields, providing us with an opportunity for a direct observational test. We study a sample of hot white dwarf stars, combining far-UV spectroscopic observations, atomic physics, atmospheric modelling and fundamental physics, in the search for variation in the fine structure constant. This variation manifests as shifts in the observed wavelengths of absorption lines, such as quadruply ionized iron (FeV) and quadruply ionized nickel (NiV), when compared to laboratory wavelengths. Berengut et al. (Phys. Rev. Lett. 2013, 111, 010801) demonstrated the validity of such an analysis using high-resolution Hubble Space Telescope (HST)/Space Telescope Imaging Spectrograph (STIS) spectra of G191-B2B. We have made three important improvements by: (a) using three new independent sets of laboratory wavelengths, (b) analysing a sample of objects, and (c) improving the methodology by incorporating robust techniques from previous studies towards quasars (the Many Multiplet method). A successful detection would be the first direct measurement of a gravitational field effect on a bare constant of nature. Here we describe our approach and present preliminary results from nine objects using both FeV and NiV.
A new and automated method is presented for the analysis of high-resolution absorption spectra. Three established numerical methods are unified into one "artificial intelligence" process: a genetic algorithm (GVPFIT); non-linear least-squares with parameter constraints (VPFIT); and Bayesian Model Averaging (BMA). The method has broad application but here we apply it specifically to the problem of measuring the fine structure constant at high redshift. For this we need objectivity and reproducibility. GVPFIT is also motivated by the importance of obtaining a large statistical sample of measurements of $Δα/α$. Interactive analyses are both time consuming and complex and automation makes obtaining a large sample feasible. In contrast to previous methodologies, we use BMA to derive results using a large set of models and show that this procedure is more robust than a human picking a single preferred model since BMA avoids the systematic uncertainties associated with model choice. Numerical simulations provide stringent tests of the whole process and we show using both real and simulated spectra that the unified automated fitting procedure out-performs a human interactive analysis. The method should be invaluable in the context of future instrumentation like ESPRESSO on the VLT and indeed future ELTs. We apply the method to the $z_{abs} = 1.8389$ absorber towards the $z_{em} = 2.145$ quasar J110325-264515. The derived constraint of $Δα/α= 3.3 \pm 2.9 \times 10^{-6}$ is consistent with no variation and also consistent with the tentative spatial variation reported in Webb et al (2011) and King et al (2012).
We present an analysis of 23 absorption systems along the lines of sight towards 18 quasars in the redshift range of $0.4 \leq z_{abs} \leq 2.3$ observed on the Very Large Telescope (VLT) using the Ultraviolet and Visual Echelle Spectrograph (UVES). Considering both statistical and systematic error contributions we find a robust estimate of the weighted mean deviation of the fine-structure constant from its current, laboratory value of $Δα/α=\left(0.22\pm0.23\right)\times10^{-5}$, consistent with the dipole variation reported in Webb et al. and King et al. This paper also examines modelling methodologies and systematic effects. In particular we focus on the consequences of fitting quasar absorption systems with too few absorbing components and of selectively fitting only the stronger components in an absorption complex. We show that using insufficient continuum regions around an absorption complex causes a significant increase in the scatter of a sample of $Δα/α$ measurements, thus unnecessarily reducing the overall precision. We further show that fitting absorption systems with too few velocity components also results in a significant increase in the scatter of $Δα/α$ measurements, and in addition causes $Δα/α$ error estimates to be systematically underestimated. These results thus identify some of the potential pitfalls in analysis techniques and provide a guide for future analyses.